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A search for the weak production of charginos and neutralinos into final states with three electrons or muons and missing transverse momentum is presented. The analysis uses 2.06 fb^-1 of sqrt(s) = 7 TeV proton-proton collision data delivered by the Large Hadron Collider and recorded with the ATLAS detector. Observations are consistent with standard model expectations in two signal regions that are either depleted or enriched in Z-boson decays. Upper limits at 95% confidence level are set in R-parity conserving phenomenological minimal supersymmetric and simplified models. For the simplified models, degenerate lightest chargino and next-to-lightest neutralino masses up to 300 GeV are excluded for mass differences from the lightest neutralino up to 300 GeV.
Transverse momentum distribution for the first leading lepton for events in the SR1 signal region for DATA and SM predictions.
Transverse momentum distribution for the first leading lepton for events in the SR2 signal region for DATA and SM predictions.
Transverse momentum distribution for the second leading lepton for events in the SR1 signal region for DATA and SM predictions.
Transverse momentum distribution for the second leading lepton for events in the SR2 signal region for DATA and SM predictions.
Transverse momentum distribution for the third leading lepton for events in the SR1 signal region for DATA and SM predictions.
Transverse momentum distribution for the third leading lepton for events in the SR2 signal region for DATA and SM predictions.
Missing transverse energy for events in the SR1 signal region for DATA and SM predictions.
Missing transverse energy for events in the SR2 signal region for DATA and SM predictions.
Invariant mass of the same-flavour-opposite-sign (SFOS) lepton pair for events in the SR1 signal region for DATA and SM predictions.
The Cross Section in signal region SR1 for the SUSY pMSSM model with M1=100 GeV grid.
The Cross Section in signal region SR1 for the SUSY simplified model grid.
The Number of generated Events in signal region SR1 for the SUSY pMSSM model with M1=100 GeV grid.
The Number of generated Events in signal region SR1 for the SUSY simplified model grid.
The Efficiency in signal region SR1 for the SUSY pMSSM model with M1=100 GeV grid.
The Efficiency in signal region SR1 for the SUSY simplified model grid.
The Acceptance in signal region SR1 for the SUSY pMSSM model with M1=100 GeV grid.
The Acceptance in signal region SR1 for the SUSY simplified model grid.
The Acceptance*Efficiency in signal region SR1 for the SUSY pMSSM model with M1=100 GeV grid.
The Acceptance*Efficiency in signal region SR1 for the SUSY simplified model grid.
The Systematic Uncertainty of the data (excluding the Monte Carlo) in signal region SR1 for the SUSY pMSSM model with M1=100 GeV grid.
The Systematic Uncertainty of the data (excluding the Monte Carlo) in signal region SR1 for the SUSY simplified model grid.
CL values for the pMSSM with M1=100 GeV model grid for the SR1 signal region.
CL values for the simplified model model grid for the SR1 signal region.
A search is presented for direct top squark pair production in final states with one isolated electron or muon, jets, and missing transverse momentum in proton-proton collisions at sqrt(s) = 7 TeV. The measurement is based on 4.7 fb-1 of data collected with the ATLAS detector at the LHC. Each top squark is assumed to decay to a top quark and the lightest supersymmetric particle (LSP). The data are found to be consistent with Standard Model expectations. Top squark masses between 230 GeV and 440 GeV are excluded with 95% confidence for massless LSPs, and top squark masses around 400 GeV are excluded for LSP masses up to 125 GeV.
The observed and standard model prediction for the distribution of missing ET in signal region A.
The observed 95% exclusion limits for the five signal regions.
The expected 95% exclusion limits for the five signal regions.
The stop pair production cross section and its uncertainty due to PDF, factorization and the renormalization scales.
The results of a search for direct pair production of heavy top-quark partners in 4.7 fb-1 of integrated luminosity from pp collisions at sqrt(s) = 7 TeV collected by the ATLAS detector at the LHC are reported. Heavy top-quark partners decaying into a top quark and a neutral non-interacting particle are searched for in events with two leptons in the final state. No excess above the Standard Model expectation is observed. Limits are placed on the mass of a supersymmetric scalar top and of a spin-1/2 top-quark partner. A spin-1/2 top-quark partner with a mass between 300 GeV and 480 GeV, decaying to a top quark and a neutral non-interacting particle lighter than 100 GeV, is excluded at 95% confidence level.
(1) Number of generated MC events for the scalar top signal grid (2) Relative Cross section uncertainties for the scalar top signal grid.
(1) Acceptance of the same flavour selection for the scalar top signal grid (2) Selection efficiency of the same flavour selection for the scalar top signal grid (3) Product of the acceptance and efficiency of the same flavour selection for the scalar top signal grid (4) Relative experimental uncertainties on the acceptance times efficiency of the same flavour selection for the scalar top signal grid.
(1) Acceptance of the different flavour selection for the scalar top signal grid (2) Selection efficiency of the different flavour selection for the scalar top signal grid (3) Product of the acceptance and efficiency of the different flavour selection for the scalar top signal grid (4) Relative experimental uncertainties on the acceptance times efficiency of the different flavour selection for the scalar top signal grid.
(1) Number of generated MC events for the spin 1/2 top partner signal grid (2) Relative Cross section uncertainties for the spin 1/2 top partner signal grid.
(1) Acceptance of the same flavour selection for the spin 1/2 top partner signal grid (2) Selection efficiency of the same flavour selection for the spin 1/2 top partner signal grid (3) Product of the acceptance and efficiency of the same flavour selection for the spin 1/2 top partner signal grid (4) Relative experimental uncertainties on the acceptance times efficiency of the same flavour selection for the spin 1/2 top partner signal grid.
(1) Acceptance of the different flavour selection for the spin 1/2 top partner signal grid (2) Selection efficiency of the different flavour selection for the spin 1/2 top partner signal grid (3) Product of the acceptance and efficiency of the different flavour selection for the spin 1/2 top partner signal grid (4) Relative experimental uncertainties on the acceptance times efficiency of the different flavour selection for the spin 1/2 top partner signal grid.
(1) Observed CLs values for the scalar top signal grid (2) Expected CLs values for the scalar top signal grid.
(1) Observed CLs values for the spin 1/2 top partner signal grid (2) Expected CLs values for the spin 1/2 top partner signal grid.
Cross section limits [pb] for the scalar top signal grid.
Cross section limits [pb] for the spin 1/2 top partner signal grid.
Observed 95% CL limit for stop grid as a function of the scalar top and neutralino masses.
Observed 95% CL limit for stop grid as a function of the scalar top and neutralino masses, varying signal cross section of +1sigma.
Observed 95% CL limit for stop grid as a function of the scalar top and neutralino masses, varying signal cross section of -1sigma.
Expected 95% CL limit for stop grid as a function of the scalar top and neutralino masses.
Expected 95% CL limit for stop grid as a function of the scalar top and neutralino masses, varying the uncertainty of +1sigma.
Expected 95% CL limit for stop grid as a function of the scalar top and neutralino masses, varying the uncertainty of -1sigma.
Observed 95% CL limit for top partner grid as a function of the top partner and neutralino masses.
Observed 95% CL limit for top partner grid as a function of the top partner and neutralino masses, varying signal cross section of +1sigma.
Observed 95% CL limit for top partner grid as a function of the top partner and neutralino masses, varying signal cross section of -1sigma.
Expected 95% CL limit for top partner grid as a function of the top partner and neutralino masses.
Expected 95% CL limit for top partner grid as a function of the top partner and neutralino masses, varying the uncertainty of +1sigma.
Expected 95% CL limit for top partner grid as a function of the top partner and neutralino masses, varying the uncertainty of -1sigma.
A search has been performed for the experimental signature of an isolated photon with high transverse momentum, at least one jet identified as originating from a bottom quark, and high missing transverse momentum. Such a final state may originate from supersymmetric models with gauge-mediated supersymmetry breaking in events in which one of a pair of higgsino-like neutralinos decays into a photon and a gravitino while the other decays into a Higgs boson and a gravitino. The search is performed using the full dataset of 7 TeV proton-proton collisions recorded with the ATLAS detector at the LHC in 2011, corresponding to an integrated luminosity of 4.7 fb-1. A total of 7 candidate events are observed while 7.5 pm 2.2 events are expected from the Standard Model background. The results of the search are interpreted in the context of general gauge mediation to exclude certain regions of a benchmark plane for higgsino-like neutralino production.
Missing ET distribution.
Signal Point Information: (1) Number of Monte Carlo events generated (2) Total signal cross section (pb) (3) Signal acceptance (4) Relative uncertainty on acceptance (5) CLs expected (6) CLs observed.
The observed limit contour in the GLUINO-NEUTRALINO plane.
The expected limit contour in the GLUINO-NEUTRALINO plane.
The observed limit contour in the SQUARK-NEUTRALINO plane.
The expected limit contour in the SQUARK-NEUTRALINO plane.
A search for strongly produced supersymmetric particles is conducted using signatures involving multiple energetic jets and either two isolated leptons ($e$ or $\mu$) with the same electric charge, or at least three isolated leptons. The search also utilises jets originating from b-quarks, missing transverse momentum and other observables to extend its sensitivity. The analysis uses a data sample corresponding to a total integrated luminosity of 20.3 fb$^{-1}$ of $\sqrt{s} =$ 8 TeV proton-proton collisions recorded with the ATLAS detector at the Large Hadron Collider in 2012. No deviation from the Standard Model expectation is observed. New or significantly improved exclusion limits are set on a wide variety of supersymmetric models in which the lightest squark can be of the first, second or third generations, and in which R-parity can be conserved or violated.
Numbers of observed and background events for SR0b for each bin of the distribution in Meff. The table corresponds to Fig. 4(b). The statistical and systematic uncertainties are combined for the expected backgrounds.
Numbers of observed and background events for SR1b for each bin of the distribution in Meff. The table corresponds to Fig. 4(c). The statistical and systematic uncertainties are combined for the predicted numbers.
Numbers of observed and background events for SR3b for each bin of the distribution in Meff. The table corresponds to Fig. 4(a). The statistical and systematic uncertainties are combined for the predicted numbers.
Numbers of observed and background events for SR3L low for each bin of the distribution in Meff. The table corresponds to Fig. 4(d). The statistical and systematic uncertainties are combined for the predicted numbers.
Numbers of observed and background events for SR3L high for each bin of the distribution in Meff. The table corresponds to Fig. 4(e). The statistical and systematic uncertainties are combined for the predicted numbers.
The efficiencies are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of squarks that decay into two steps into q q W Z W Z chi1^0 chi1^0 (see Fig. 6c in the paper).
The efficiencies are calculated for all simplified extra dimension model (see Fig. 8d in the paper). For each model, the values are given for the five signal regions and their combination.
The efficiencies are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay via sleptons into q q q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6d in the paper).
The efficiencies are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay into q q q q W W chi1^0 chi1^0 (see Fig. 6a in the paper).
The efficiencies are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay into t tbar t tbar chi1^0 chi1^0 (see Fig. 5a in the paper). This particular model assumes that top quark is much heavier than gluino.
The efficiencies are calculated for all mSUGRA models (see Fig. 8a in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes tan(beta)=30, A0=2m0, and mu>0.
The efficiencies are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos. A gluino decays into t c chi1^0 (see Fig. 5c in the paper). This particular model assumes that m(chi1^0) = m(stop) - 20 GeV.
The efficiencies are calculated for all GMSB models (see Fig. 8c in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes mmess=250 TeV, m5=3, mu>0, and Cgrav=1.
The efficiencies are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7a in the paper). This particular model assumes that m(chi1^0)=60 GeV.
The efficiencies are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos and top squarks. Top squarks undergo R-parity violating decays into b s and gluinos decay into t stop (see Fig. 5d in the paper).
The efficiencies are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7b in the paper). This particular model assumes that m(chi1^0)=2(chi1^0).
The efficiencies are calculated for all mSUGRA/CMSSM models with bRPV (see Fig. 8b in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes tan(beta)=30, A0=2m0, mu>0, and bRPV.
The efficiencies are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of squarks. Squarks decay into q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6e in the paper).
The efficiencies are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct pair-production of gluinos that decay via a two-step process into q q q q W Z W Z chi1^0 chi1^0 (see Fig. 6b in the paper).
The efficiencies are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct pair production of gluinos. A gluino decays into t stop. Consequently, a top squark squark decays into b chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 5b in the paper). This particular model assumes that m(stop) < m(gluino), m(chi1^0)=6 GeV, and m(chi1^(+-))=118 GeV.
The acceptances (in percent, %) are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of squarks that decay into two steps into q q W Z W Z chi1^0 chi1^0 (see Fig. 6c in the paper).
The acceptances (in percent, %) are calculated for all simplified extra dimension model (see Fig. 8d in the paper). For each model, the values are given for the five signal regions and their combination.
The acceptances (in percent, %) are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay via sleptons into q q q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6d in the paper).
The acceptances (in percent, %) are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay into q q q q W W chi1^0 chi1^0 (see Fig. 6a in the paper).
The acceptances (in percent, %) are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay into t tbar t tbar chi1^0 chi1^0 (see Fig. 5a in the paper). This particular model assumes that top quark is much heavier than gluino.
The acceptances (in percent, %) are calculated for all mSUGRA models (see Fig. 8a in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes tan(beta)=30, A0=2m0, and mu>0.
The acceptances (in percent, %) are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos. A gluino decays into t c chi1^0 (see Fig. 5c in the paper). This particular model assumes that m(chi1^0) = m(stop) - 20 GeV.
The acceptances (in percent, %) are calculated for all GMSB models (see Fig. 8c in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes mmess=250 TeV, m5=3, mu>0, and Cgrav=1.
The acceptances (in percent, %) are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7a in the paper). This particular model assumes that m(chi1^0)=60 GeV.
The acceptances (in percent, %) are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos and top squarks. Top squarks undergo R-parity violating decays into bs and gluinos decay into t stop (see Fig. 5d in the paper).
The acceptances (in percent, %) are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W chi1^0 (see Fig. 7b in the paper). This particular model assumes that m(chi1^0)=2(chi1^0).
The acceptances (in percent, %) are calculated for all mSUGRA/CMSSM models with bRPV (see Fig. 8b in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes tan(beta)=30, A0=2m0, mu>0, and bRPV.
The acceptances (in percent, %) are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of squarks. Squarks decay into q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6e in the paper).
The acceptances (in percent, %) are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct pair-production of gluinos that decay via a two-step process into q q q q W Z W Z chi1^0 chi1^0 (see Fig. 6b in the paper).
The acceptances (in percent, %) are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct pair production of gluinos. A gluino decays into t stop. Consequently, a top squark squark decays into b chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 5b in the paper). This particular model assumes that m(stop) < m(gluino), m(chi1^0)=6 GeV, and m(chi1^(+-))=118 GeV.
The limits on observed cross section are calculated for all simplified models. The simplified models are for direct pair production of squarks that decay into two steps into q q W Z W Z chi1^0 chi1^0 (see Fig. 6c in the paper).
The limits on observed cross sections are calculated for all simplified models. The simplified models are for direct pair-production of gluinos that decay via sleptons into q q q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6d in the paper).
The limits on observed cross sections are calculated for all simplified models. The simplified models are for direct production of gluinos that decay into q q q q W W chi1^0 chi1^0 (see Fig. 6a in the paper).
The limits on observed cross sections are calculated for all simplified models. The simplified models are for direct production of gluinos that decay into t tbar t tbar chi1^0 chi1^0 (see Fig. 5a in the paper). This particular model assumes that top quark is much heavier than gluino.
The limits on observed cross sections are calculated for all simplified models. The simplified models are for direct pair production of gluinos. A gluino decays into t c chi1^0 (see Fig. 5c in the paper). This particular model assumes that m(chi1^0) = m(stop) - 20 GeV.
The limits on observed cross sections are calculated for all simplified models. The simplified models are for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7a in the paper). This particular model assumes that m(chi1^0)=60 GeV.
The limits on observed cross sections are calculated for all simplified models. The simplified models are for direct production of gluinos and top squarks. Top squarks undergo R-parity violating decays into bs and gluinos decay into t stop (see Fig. 5d in the paper).
The limits on observed cross sections are calculated for all simplified models. The simplified models are for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7b in the paper). This particular model assumes that m(chi1^0)=2(chi1^0).
The limits on observed cross sections are calculated for all simplified models. The simplified models are for direct production of squarks. Squarks decay into q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6e in the paper).
The limits on observed cross sections are calculated for all simplified models. The simplified models are for direct pair-production of gluinos that decay via a two-step process into q q q q W Z W Z chi1^0 chi1^0 (see Fig. 6b in the paper).
The limits on observed cross sections are calculated for all simplified models. The simplified models are for direct pair production of gluinos. A gluino decays into t stop. Consequently, a top squark squark decays into b chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 5b in the paper). This particular model assumes that m(stop) < m(gluino), m(chi1^0)=6 GeV, and m(chi1^(+-))=118 GeV.
The signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of squarks that decay into two steps into q q W Z W Z chi1^0 chi1^0 (see Fig. 6c in the paper).
The signal event yields are calculated for all simplified extra dimension model (see Fig. 8d in the paper). For each model, the values are given for the five signal regions and their combination.
The signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay via sleptons into q q q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6d in the paper).
The signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay into q q q q W W chi1^0 chi1^0 (see Fig. 6a in the paper).
The signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay into t tbar t tbar chi1^0 chi1^0 (see Fig. 5a in the paper). This particular model assumes that top quark is much heavier than gluino.
The signal event yields are calculated for all mSUGRA models (see Fig. 8a in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes tan(beta)=30, A0=2m0, and mu>0.
The signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos. A gluino decays into t c chi1^0 (see Fig. 5c in the paper). This particular model assumes that m(chi1^0) = m(stop)-20 GeV.
The signal event yields are calculated for all GMSB models (see Fig. 8c in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes mmess=250 TeV, m5=3, mu>0, and Cgrav=1.
The signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7a in the paper). This particular model assumes that m(chi1^0)=60 GeV.
The signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos and top squarks. Top squarks undergo R-parity violating decays into bs and gluinos decay into t stop (see Fig. 5d in the paper).
The signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7b in the paper). This particular model assumes that m(chi1^0)=2(chi1^0).
The signal event yields are calculated for all mSUGRA/CMSSM models with bRPV (see Fig. 8b in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes tan(beta)=30, A0=2m0, mu>0, and bRPV.
The signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of squarks. Squarks decay into q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6e in the paper).
The signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct pair-production of gluinos that decay via a two-step process into q q q q W Z W Z chi1^0 chi1^0 (see Fig. 6b in the paper).
The signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct pair-production of gluinos. A gluino decays into t stop. Consequently, a top squark squark decays into b chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 5b in the paper). This particular model assumes that m(stop) < m(gluino), m(chi1^0)=6 GeV, and m(chi1^(+-))=118 GeV.
Experimental uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of squarks that decay into two steps into q q W Z W Z chi1^0 chi1^0 (see Fig. 6c in the paper).
Experimental uncertainties on the signal event yields are calculated for all simplified extra dimension model (see Fig. 8d in the paper). For each model, the values are given for the five signal regions and their combination.
Experimental uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay via sleptons into q q q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6d in the paper).
Experimental uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay into q q q q W W chi1^0 chi1^0 (see Fig. 6a in the paper).
Experimental uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay into t tbar t tbar chi1^0 chi1^0 (see Fig. 5a in the paper). This particular model assumes that top quark is much heavier than gluino.
Experimental uncertainties on the signal event yields are calculated for all mSUGRA models (see Fig. 8a in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes tan(beta)=30, A0=2m0, and mu>0.
Experimental uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos. A gluino decays into t c chi1^0 (see Fig. 5c in the paper). This particular model assumes that m(chi1^0) = m(stop) - 20 GeV.
Experimental uncertainties on the signal event yields are calculated for all GMSB models (see Fig. 8c in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes mmess=250 TeV, m5=3, mu>0, and Cgrav=1.
Experimental uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7a in the paper). This particular model assumes that m(chi1^0)=60 GeV.
Experimental uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos and top squarks. Top squarks undergo R-parity violating decays into bs and gluinos decay into t stop (see Fig. 5d in the paper).
Experimental uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7b in the paper). This particular model assumes that m(chi1^0)=2(chi1^0).
Experimental uncertainties on the signal event yields are calculated for all mSUGRA/CMSSM models with bRPV (see Fig. 8b in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes tan(beta)=30, A0=2m0, mu>0, and bRPV.
Experimental uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of squarks. Squarks decay into q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6e in the paper).
Experimental uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct pair-production of gluinos that decay via a two-step process into q q q q W Z W Z chi1^0 chi1^0 (see Fig. 6b in the paper).
Experimental uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct pair-production of gluinos. A gluino decays into t stop. Consequently, a top squark squark decays into b chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 5b in the paper). This particular model assumes that m(stop) < m(gluino), m(chi1^0)=6 GeV, and m(chi1^(+-))=118 GeV.
Statistical uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of squarks that decay into two steps into q q W Z W Z chi1^0 chi1^0 (see Fig. 6c in the paper).
Statistical uncertainties on the signal event yields are calculated for all simplified extra dimension model (see Fig. 8d in the paper). For each model, the values are given for the five signal regions and their combination.
Statistical uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay via sleptons into q q q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6d in the paper).
Statistical uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay into q q q q W W chi1^0 chi1^0 (see Fig. 6a in the paper).
Statistical uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos that decay into t tbar t tbar chi1^0 chi1^0 (see Fig. 5a in the paper). This particular model assumes that top quark is much heavier than gluino.
Statistical uncertainties on the signal event yields are calculated for all mSUGRA models (see Fig. 8a in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes tan(beta)=30, A0=2m0, and mu>0.
Statistical uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos. A gluino decays into t c chi1^0 (see Fig. 5c in the paper). This particular model assumes that m(chi1^0) = m(stop) - 20 GeV.
Statistical uncertainties on the signal event yields are calculated for all GMSB models (see Fig. 8c in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes mmess=250 TeV, m5=3, mu>0, and Cgrav=1.
Statistical uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7a in the paper). This particular model assumes that m(chi1^0)=60 GeV.
Statistical uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of gluinos and top squarks. Top squarks undergo R-parity violating decays into bs and gluinos decay into t stop (see Fig. 5d in the paper).
Statistical uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7b in the paper). This particular model assumes that m(chi1^0)=2(chi1^0).
Statistical uncertainties on the signal event yields are calculated for all mSUGRA/CMSSM models with bRPV (see Fig. 8b in the paper). For each model, the values are given for the five signal regions and their combination. The model assumes tan(beta)=30, A0=2m0, mu>0, and bRPV.
Statistical uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct production of squarks. Squarks decay into q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6e in the paper).
Statistical uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct pair-production of gluinos that decay via a two-step process into q q q q W Z W Z chi1^0 chi1^0 (see Fig. 6b in the paper).
Statistical uncertainties on the signal event yields are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct pair-production of gluinos. A gluino decays into t stop. Consequently, a top squark squark decays into b chi1^(+-) and chi1^(+-) --> W ^(+-) chi1^0 (see Fig. 5b in the paper). This particular model assumes that m(stop) < m(gluino), m(chi1^0)=6 GeV, and m(chi1^(+-))=118 GeV.
The confidence levels are calculated for all simplified models. For each model, the observed and expected values are given. The simplified model is for direct production of gluinos that decay into t tbar t tbar chi1^0 chi1^0 (see Fig. 5a in the paper). This particular model assumes that top quark is much heavier than gluino.
The confidence levels are calculated for all simplified models. For each model, the observed and expected values are given. The simplified model is for direct production of squarks that decay into two steps into q q W Z W Z chi1^0 chi1^0 (see Fig. 6c in the paper).
The confidence levels are calculated for all simplified models. For each model, the values are given for the five signal regions and their combination. The simplified model is for direct pair-production of gluinos that decay via a two-step process into q q q q W Z W Z chi1^0 chi1^0 (see Fig. 6b in the paper).
The confidence levels are calculated for all simplified models. For each model, the expected and observed values are given. The simplified model is for direct production of gluinos that decay via sleptons into q q q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6d in the paper).
The confidence levels are calculated for all simplified models. For each model, the expected and observed values are given. The simplified model is for direct pair-production of gluinos. A gluino decays into t stop. Consequently, a top squark squark decays into b chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 5b in the paper). This particular model assumes that m(stop) < m(gluion), m(chi1^0)=6 GeV, and m(chi1^(+-))=118 GeV.
The confidence levels are calculated for all simplified models. For each model, the expected and observed values are given. The simplified model is for direct production of gluinos. A gluino decays into t c chi1^0 (see Fig. 5c in the paper). This particular model assumes that m(chi1^0) = m(stop) - 20 GeV.
The confidence levels are calculated for all simplified models. For each model, the expected and observed values are given. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7b in the paper). This particular model assumes that m(chi1^0)=2(chi1^0).
The confidence levels are calculated for all simplified models. For each model, the expected and observed values are given. The simplified model is for direct production of bottom squarks. A bottom squark decays into t chi1^(+-) and chi1^(+-) --> W^(+-) chi1^0 (see Fig. 7a in the paper). This particular model assumes that m(chi1^0)=60 GeV.
The confidence levels are calculated for all simplified models. For each model, the expected and observed values are given. The simplified model is for direct production of squarks. Squarks decay into q q l l (l l) chi1^0 chi1^0 + neutrinos (see Fig. 6e in the paper).
The confidence levels are calculated for all GMSB models (see Fig. 8c in the paper). For each model, the expected and observed values are given. The model assumes mmess=250 TeV, m5=3, mu>0, and Cgrav=1.
The confidence levels are calculated for all simplified models. For each model, the expected and observed values are given. The simplified model is for direct production of gluinos and top squarks. Top squarks undergo R-parity violating decays into bs and gluinos decay into t stop (see Fig. 5d in the paper).
The confidence levels are calculated for all mSUGRA/CMSSM models with bRPV (see Fig. 8b in the paper). For each model, the expected and observed values are given. The model assumes tan(beta)=30, A0=2m0, mu>0, and bRPV.
The confidence levels are calculated for all simplified extra dimension model (see Fig. 8d in the paper). For each model, the expected and observed values are given.
The confidence levels are calculated for all simplified models. For each model, the expected and observed values are given. The simplified model is for direct production of gluinos that decay into q q q q W W chi1^0 chi1^0 (see Fig. 6a in the paper).
The confidence levels are calculated for all mSUGRA models (see Fig. 8a in the paper). For each model, the expected and observed values are given. The model assumes tan(beta)=30, A0=2m0, and mu>0.
A search for physics beyond the standard model in events with at least three leptons is presented. The data sample, corresponding to an integrated luminosity of 19.5 inverse femtobarns of proton-proton collisions with center-of-mass energy sqrt(s) = 8 TeV, was collected by the CMS experiment at the LHC during 2012. The data are divided into exclusive categories based on the number of leptons and their flavor, the presence or absence of an opposite-sign, same-flavor lepton pair (OSSF), the invariant mass of the OSSF pair, the presence or absence of a tagged bottom-quark jet, the number of identified hadronically decaying tau leptons, and the magnitude of the missing transverse energy and of the scalar sum of jet transverse momenta. The numbers of observed events are found to be consistent with the expected numbers from standard model processes, and limits are placed on new-physics scenarios that yield multilepton final states. In particular, scenarios that predict Higgs boson production in the context of supersymmetric decay chains are examined. We also place a 95% confidence level upper limit of 1.3% on the branching fraction for the decay of a top quark to a charm quark and a Higgs boson (t to c H), which translates to a bound on the left- and right-handed top-charm flavor-violating Higgs Yukawa couplings, lambda[H, tc] and lambda[H, ct], respectively, of sqrt(abs(lambda[H, tc])^2 + abs(lambda[H, ct])^2) < 0.21.
Observed and expected numbers of events with four or more leptons with the scalar sum of jet transverse momentum values HT > 200 GeV. "On-Z" refers to events with at least one E+ E- or MU+ MU- (OSSF) pair with dilepton mass between 75 and 105 GeV, while "Off-Z" refers to events with one or two OSSF pairs, none of which fall in this mass range. The OSSFN designation refers to the number of E+ E- and MU+ MU- pairs in the event. Search channels binned in ET have been combined into coarse ET bins for the purposes of presentation.
Observed and expected numbers of events with four or more leptons with the scalar sum of jet transverse momentum values HT < 200 GeV. "On-Z" refers to events with at least one E+ E- or MU+ MU- (OSSF) pair with dilepton mass between 75 and 105 GeV, while "Off-Z" refers to events with one or two OSSF pairs, none of which fall in this mass range. The OSSFN designation refers to the number of E+ E- and MU+ MU- pairs in the event. Search channels binned in ET have been combined into coarse ET bins for the purposes of presentation.
Observed and expected numbers of events with exactly three leptons with the scalar sum of jet transverse momentum values HT > 200 GeV. "On-Z" refers to events with at least one E+ E- or MU+ MU- (OSSF) pair with dilepton mass between 75 and 105 GeV, while "Off-Z" refers to events with one or two OSSF pairs, none of which fall in this mass range. The OSSFN designation refers to the number of E+ E- and MU+ MU- pairs in the event. Search channels binned in ET have been combined into coarse ET bins for the purposes of presentation.
Observed and expected numbers of events with exactly three leptons with the scalar sum of jet transverse momentum values HT < 200 GeV. "On-Z" refers to events with at least one E+ E- or MU+ MU- (OSSF) pair with dilepton mass between 75 and 105 GeV, while "Off-Z" refers to events with one or two OSSF pairs, none of which fall in this mass range. The OSSFN designation refers to the number of E+ E- and MU+ MU- pairs in the event. Search channels binned in ET have been combined into coarse ET bins for the purposes of presentation.
The product of acceptance and efficiency for the calculation of the 95% C.L. limits for the natural Higgsino NLSP scenario with BR(NEUTRALINO1 --> HIGGS GRAVITINO) = BR(NEUTRALINO1 --> Z GRAVITINO) = 0.5 for strong plus electroweak production.
The product of acceptance and efficiency for the calculation of the 95% C.L. limits for the natural Higgsino NLSP scenario with BR(NEUTRALINO1 --> HIGGS GRAVITINO) = 1.0 for strong plus electroweak production.
The product of acceptance and efficiency for the calculation of the 95% C.L. limits for the natural Higgsino NLSP scenario with BR(NEUTRALINO1 --> Z0 GRAVITINO) = 1.0 for strong plus electroweak production.
The product of acceptance and efficiency for the calculation of the 95% C.L. limit for the natural Higgsino NLSP scenario with strong plus electroweak production for BR(NEUTRALINO1 --> HIGGS GRAVITINO) = BR(NEUTRALINO1 --> Z0 GRAVITINO) = 0.5. The chargino-Higgsino mass is fixed at 150 GeV.
The product of acceptance and efficiency for the calculation of the 95% C.L. limit for the natural Higgsino NLSP scenario with strong plus electroweak production for BR(NEUTRALINO1 --> HIGGS GRAVITINO) = BR(NEUTRALINO1 --> Z0 GRAVITINO) = 0.5. The chargino-Higgsino mass is fixed at 350 GeV.
The product of acceptance and efficiency for the calculation of the 95% C.L. limits for the natural Higgsino NLSP scenario with strong plus electroweak production for BR(NEUTRALINO1 --> HIGGS GRAVITINO) = 1.0. The chargino-Higgsino mass is fixed at 150 GeV.
The product of acceptance and efficiency for the calculation of the 95% C.L. limits for the natural Higgsino NLSP scenario with strong plus electroweak production for BR(NEUTRALINO1 --> HIGGS GRAVITINO) = 1.0. The chargino-Higgsino mass is fixed at 350 GeV.
The product of acceptance and efficiency for the calculation of the 95% C.L. limits for the natural Higgsino NLSP scenario with strong plus electroweak production for BR(NEUTRALINO1 --> Z0 GRAVITINO) = 1.0. The chargino-Higgsino mass is fixed at 150 GeV.
The product of acceptance and efficiency for the calculation of the 95% C.L. limits for the natural Higgsino NLSP scenario with strong plus electroweak production for BR(NEUTRALINO1 --> Z0 GRAVITINO) = 1.0. The chargino-Higgsino mass is fixed at 350 GeV.
The product of acceptance and efficiency for the calculation of the 95% C.L. limit on BR(NEUTRALINO1 --> HIGGS GRAVITINO) for the natural Higgsino NLSP scenario with fixed chargino-Higgsino mass of 150 GeV assuming BR(NEUTRALINO1 --> HIGGS GRAVITINO) + BR(NEUTRALINO1 --> Z GRAVITINO) = 1.0 and strong plus weak production.
The product of acceptance and efficiency for the calculation of the 95% C.L. limit on BR(NEUTRALINO1 --> HIGGS GRAVITINO) for the natural Higgsino NLSP scenario with fixed chargino-Higgsino mass of 250 GeV assuming BR(NEUTRALINO1 --> HIGGS GRAVITINO) + BR(NEUTRALINO1 --> Z0 GRAVITINO) = 1.0 and strong plus weak production.
The product of acceptance and efficiency for the calculation of the 95% C.L. limit on BR(NEUTRALINO1 --> HIGGS GRAVITINO) for the natural Higgsino NLSP scenario with fixed chargino-Higgsino mass of 350 GeV assuming BR(NEUTRALINO1 --> HIGGS GRAVITINO) + BR(NEUTRALINO1 --> Z0 GRAVITINO) = 1.0 and strong plus weak production.
The product of acceptance and efficiency for the calculation of the 95% C.L. limits for the slepton co-NLSP model in the gluino-chargino (wino-like chargino) mass plane.
The product of acceptance and efficiency for the calculation of the 95% C.L. limits for the stau-NLSP and stau-NNLSP scenario in the degenerate smuon- and selectron- stau mass plane.
The product of acceptance and efficiency for the calculation of the 95% C.L. limits for the T1tttt model in the gluino-neutralino mass plane.
The product of acceptance and efficiency for the calculation of the 95% C.L. limits for the T6ttWW model in the sbottom-chargino mass plane.
Observed 95% C.L. exclusion contour for the T1tttt scenario.
Observed - 1sig(theoretical) 95% C.L. exclusion contour for the T1tttt scenario.
Observed + 1sig(theoretical) 95% C.L. exclusion contour for the T1tttt scenario.
Expected 95% C.L. exclusion contour for the T1tttt scenario.
Expected - 1sig 95% C.L. exclusion contour for the T1tttt scenario.
Expected + 1sig 95% C.L. exclusion contour for the T1tttt scenario.
Observed 95% C.L. exclusion contour for the T6ttWW scenario.
Observed - 1sig(theoretical) 95% C.L. exclusion contour for the T6ttWW scenario.
Observed + 1sig(theoretical) 95% C.L. exclusion contour for the T6ttWW scenario.
Expected 95% C.L. exclusion contour for the T6ttWW scenario.
Expected - 1sig 95% C.L. exclusion contour for the T6ttWW scenario.
Expected + 1sig 95% C.L. exclusion contour for the T6ttWW scenario.
Observed and expected 95% C.L. limits for the natural Higgsino NLSP scenario with BR(NEUTRALINO1 --> HIGGS GRAVITINO) = BR(NEUTRALINO1 --> Z GRAVITINO) = 0.5 for strong plus electroweak production.
Observed and expected 95% C.L. limits for the natural Higgsino NLSP scenario with BR(NEUTRALINO1 --> HIGGS GRAVITINO) = 1.0 for strong plus electroweak production. Successive instances of SIG(OBS) = SIG(EXP) =0 have been rebinned over M(STOP) to reduce the size of the table.
Observed and expected 95% C.L. limits for the natural Higgsino NLSP scenario with BR(NEUTRALINO1 --> Z0 GLUINO) = 1.0 for strong plus electroweak production.
Observed 95% C.L. limits on BR(NEUTRALINO1 --> HIGGS GRAVITINO) for the natural Higgsino NLSP scenario with fixed chargino-Higgsino mass of 150 GeV assuming BR(NEUTRALINO1 --> HIGGS GRAVITINO) + BR(NEUTRALINO1 --> Z GRAVITINO) = 1.0 and strong plus weak production.
Observed 95% C.L. limits on BR(NEUTRALINO1 --> HIGGS GRAVITINO) for the natural Higgsino NLSP scenario with fixed chargino-Higgsino mass of 250 GeV assuming BR(NEUTRALINO1 --> HIGGS GRAVITINO) + BR(NEUTRALINO1 --> Z GRAVITINO) = 1.0 and strong plus weak production.
Observed 95% C.L. limits on BR(NEUTRALINO1 --> HIGGS GRAVITINO) for the natural Higgsino NLSP scenario with fixed chargino-Higgsino mass of 350 GeV assuming BR(NEUTRALINO1 --> HIGGS GRAVITINO) + BR(NEUTRALINO1 --> Z GRAVITINO) = 1.0 and strong plus weak production.
Observed and expected 95% C.L. limits for the slepton co-NLSP model in the gluino-chargino (wino-like chargino) mass plane are shown.
Observed and expected 95% C.L. limits for the stau-NLSP and stau-NNLSP scenario in the degenerate smuon- and selectron- stau mass plane are shown. Successive instances of SIG(OBS) = SIG(EXP) =0 have been rebinned over M(SELECTRON) to reduce the size of the table.
Observed and expected 95% C.L. limits for the T1tttt model in the gluino-neutralino mass plane are shown.
Observed and expected 95% C.L. limits for the T6ttWW model in the sbottom-chargino mass plane are given.
Results from a search for supersymmetry in events with four or more leptons including electrons, muons and taus are presented. The analysis uses a data sample corresponding to 20.3 $fb^{-1}$ of proton--proton collisions delivered by the Large Hadron Collider at $\sqrt{s}$ = 8 TeV and recorded by the ATLAS detector. Signal regions are designed to target supersymmetric scenarios that can be either enriched in or depleted of events involving the production of a $Z$ boson. No significant deviations are observed in data from Standard Model predictions and results are used to set upper limits on the event yields from processes beyond the Standard Model. Exclusion limits at the 95% confidence level on the masses of relevant supersymmetric particles are obtained. In R-parity-violating simplified models with decays of the lightest supersymmetric particle to electrons and muons, limits of 1350 GeV and 750 GeV are placed on gluino and chargino masses, respectively. In R-parity-conserving simplified models with heavy neutralinos decaying to a massless lightest supersymmetric particle, heavy neutralino masses up to 620 GeV are excluded. Limits are also placed on other supersymmetric scenarios.
The ETmiss distribution in VR0Z.
The effective mass distribution in VR0Z.
The ETmiss distribution in VR2Z.
The effective mass distribution in VR2Z.
The ETmiss distribution in SR0noZa.
The effective mass distribution in SR0noZa.
The ETmiss distribution in SR1noZa.
The effective mass distribution in SR1noZa.
The ETmiss distribution in SR2noZa.
The effective mass distribution in SR2noZa.
The ETmiss distribution in SR0noZb.
The effective mass distribution in SR0noZb.
The ETmiss distribution in SR1noZb.
The effective mass distribution in SR1noZb.
The ETmiss distribution in SR2noZb.
The effective mass distribution in SR2noZb.
The ETmiss distribution in SR0Z.
The effective mass distribution in SR0Z.
The ETmiss distribution in SR1Z.
The effective mass distribution in SR1Z.
The ETmiss distribution in SR2Z.
The effective mass distribution in SR2Z.
Observed 95% CL exclusion contour for the RPV chargino NLSP model with lambda_121 != 0.
Expected 95% CL exclusion contour for the RPV chargino NLSP model with lambda_121 != 0.
Observed 95% CL exclusion contour for the RPV chargino NLSP model with lambda_122 != 0.
Expected 95% CL exclusion contour for the RPV chargino NLSP model with lambda_122 != 0.
Observed 95% CL exclusion contour for the RPV chargino NLSP model with lambda_133 != 0.
Expected 95% CL exclusion contour for the RPV chargino NLSP model with lambda_133 != 0.
Observed 95% CL exclusion contour for the RPV chargino NLSP model with lambda_233 != 0.
Expected 95% CL exclusion contour for the RPV chargino NLSP model with lambda_233 != 0.
Observed 95% CL exclusion contour for the RPV gluino NLSP model with lambda_121 != 0.
Expected 95% CL exclusion contour for the RPV gluino NLSP model with lambda_121 != 0.
Observed 95% CL exclusion contour for the RPV gluino NLSP model with lambda_122 != 0.
Expected 95% CL exclusion contour for the RPV gluino NLSP model with lambda_122 != 0.
Observed 95% CL exclusion contour for the RPV gluino NLSP model with lambda_133 != 0.
Expected 95% CL exclusion contour for the RPV gluino NLSP model with lambda_133 != 0.
Observed 95% CL exclusion contour for the RPV gluino NLSP model with lambda_233 != 0.
Expected 95% CL exclusion contour for the RPV gluino NLSP model with lambda_233 != 0.
Observed 95% CL exclusion contour for the RPV Lslepton NLSP model with lambda_121 != 0.
Expected 95% CL exclusion contour for the RPV Lslepton NLSP model with lambda_121 != 0.
Observed 95% CL exclusion contour for the RPV Lslepton NLSP model with lambda_122 != 0.
Expected 95% CL exclusion contour for the RPV Lslepton NLSP model with lambda_122 != 0.
Observed 95% CL exclusion contour for the RPV Lslepton NLSP model with lambda_133 != 0.
Expected 95% CL exclusion contour for the RPV Lslepton NLSP model with lambda_133 != 0.
Observed 95% CL exclusion contour for the RPV Lslepton NLSP model with lambda_233 != 0.
Expected 95% CL exclusion contour for the RPV Lslepton NLSP model with lambda_233 != 0.
Observed 95% CL exclusion contour for the RPV Rslepton NLSP model with lambda_121 != 0.
Expected 95% CL exclusion contour for the RPV Rslepton NLSP model with lambda_121 != 0.
Observed 95% CL exclusion contour for the RPV Rslepton NLSP model with lambda_122 != 0.
Expected 95% CL exclusion contour for the RPV Rslepton NLSP model with lambda_122 != 0.
Observed 95% CL exclusion contour for the RPV Rslepton NLSP model with lambda_133 != 0.
Expected 95% CL exclusion contour for the RPV Rslepton NLSP model with lambda_133 != 0.
Observed 95% CL exclusion contour for the RPV Rslepton NLSP model with lambda_233 != 0.
Expected 95% CL exclusion contour for the RPV Rslepton NLSP model with lambda_233 != 0.
Observed 95% CL exclusion contour for the RPV sneutrino NLSP model with lambda_121 != 0.
Expected 95% CL exclusion contour for the RPV sneutrino NLSP model with lambda_121 != 0.
Observed 95% CL exclusion contour for the RPV sneutrino NLSP model with lambda_122 != 0.
Expected 95% CL exclusion contour for the RPV sneutrino NLSP model with lambda_122 != 0.
Observed 95% CL exclusion contour for the RPV sneutrino NLSP model with lambda_133 != 0.
Expected 95% CL exclusion contour for the RPV sneutrino NLSP model with lambda_133 != 0.
Observed 95% CL exclusion contour for the RPV sneutrino NLSP model with lambda_233 != 0.
Expected 95% CL exclusion contour for the RPV sneutrino NLSP model with lambda_233 != 0.
Observed 95% CL exclusion contour for the R-slepton RPC model.
Expected 95% CL exclusion contour for the R-slepton RPC model.
Observed and expected 95% CL cross-section upper limits for the Stau RPC model, together with the theoretically predicted cross-section.
Observed and expected 95% CL cross-section upper limits for the Z RPC model, together with the theoretically predicted cross-section.
Observed 95% CL exclusion contour for the GGM tan beta = 1.5 model.
Expected 95% CL exclusion contour for the GGM tan beta = 1.5 model.
Observed 95% CL exclusion contour for the GGM tan beta = 30 model.
Expected 95% CL exclusion contour for the GGM tan beta = 30 model.
Observed 95% CL cross-section upper limit for the RPV chargino NLSP models with lambda_121 != 0 and lambda_122 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).
Observed 95% CL cross-section upper limit for the RPV chargino NLSP models with lambda_133 != 0 and lambda_233 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).
Observed 95% CL cross-section upper limit for the RPV gluino NLSP models with lambda_121 != 0 and lambda_122 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).
Observed 95% CL cross-section upper limit for the RPV gluino NLSP models with lambda_133 != 0 and lambda_233 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).
Observed 95% CL cross-section upper limit for the RPV Lslepton NLSP models with lambda_121 != 0 and lambda_122 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).
Observed 95% CL cross-section upper limit for the RPV Lslepton NLSP models with lambda_133 != 0 and lambda_233 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).
Observed 95% CL cross-section upper limit for the RPV Rslepton NLSP models with lambda_121 != 0 and lambda_122 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).
Observed 95% CL cross-section upper limit for the RPV Rslepton NLSP models with lambda_133 != 0 and lambda_233 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).
Observed 95% CL cross-section upper limit for the RPV sneutrino NLSP models with lambda_121 != 0 and lambda_122 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).
Observed 95% CL cross-section upper limit for the RPV sneutrino NLSP models with lambda_133 != 0 and lambda_233 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).
Observed 95% CL cross-section upper limit for the R-slepton RPC model, and the selection of Z-veto signal regions used to set limits in this model. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bbb' means that the regions SR0noZb, SR1noZb and SR2noZb were used, in addition to the three Z-rich regions (SR0-2Z). For the RPC stau and Z models, the ``aaa' combination of regions was used throughout.
Performance of the SR0noZa selection in the R-slepton RPC model: number of generated signal events; total signal cross-section; acceptance; efficiency; total experimental systematic uncertainty, not including Monte Carlo statistics; observed CL using this region alone; expected CL using this region alone.
Performance of the SR0noZb selection in the RPV chargino NLSP model with lambda_121 != 0: number of generated signal events; total signal cross-section; acceptance; efficiency; total experimental systematic uncertainty, not including Monte Carlo statistics; observed CL using this region alone; expected CL using this region alone.
Performance of the SR1noZa selection in the RPV sneutrino NLSP model with lambda_233 != 0: number of generated signal events; total signal cross-section; acceptance; efficiency; total experimental systematic uncertainty, not including Monte Carlo statistics; observed CL using this region alone; expected CL using this region alone.
Performance of the SR1noZb selection in the RPV gluino NLSP model with lambda_133 != 0: number of generated signal events; total signal cross-section; acceptance; efficiency; total experimental systematic uncertainty, not including Monte Carlo statistics; observed CL using this region alone; expected CL using this region alone.
Performance of the SR2noZa selection in the RPV sneutrino NLSP model with lambda_233 != 0: number of generated signal events; total signal cross-section; acceptance; efficiency; total experimental systematic uncertainty, not including Monte Carlo statistics; observed CL using this region alone; expected CL using this region alone.
Performance of the SR2noZb selection in the RPV gluino NLSP model with lambda_133 != 0: number of generated signal events; total signal cross-section; acceptance; efficiency; total experimental systematic uncertainty, not including Monte Carlo statistics; observed CL using this region alone; expected CL using this region alone.
Performance of the SR0Z selection in the GGM tan beta = 30 model: number of generated signal events; total signal cross-section; acceptance; efficiency; total experimental systematic uncertainty, not including Monte Carlo statistics; observed CL using this region alone; expected CL using this region alone.
Cut flows for a representative selection of SUSY signal points in the Z-veto signal regions. In each case, m2 and m1 refer to the axes of the plots in Sec. XI, where m2 is the larger of the two masses. The number of events expected for a luminosity of 20.3 fb-1 is quoted at each step of the selection. The preselection requires four baseline leptons, at least two of which are light leptons; the signal lepton selection is made at the ``Lepton Multiplicity' stage. ``Event Cleaning' refers to the selection criteria applied to remove non-collision backgrounds and detector noise.
Cut flows for a representative selection of SUSY signal points in the Z-rich signal regions. In each case, m2 and m1 refer to the axes of the plots in Sec. XI, where m2 is the larger of the two masses (or the value of mu in the case of GGM models). The number of events expected for a luminosity of 20.3 fb-1 is quoted at each step of the selection. The preselection requires four baseline leptons, at least two of which are light leptons; the signal lepton selection is made at the ``Lepton Multiplicity' stage. ``Event Cleaning' refers to the selection criteria applied to remove non-collision backgrounds and detector noise.
Cut flows by lepton channel for a representative selection of SUSY signal points in the SR0noZa signal region. In each case, m2 and m1 refer to the axes of the plots in Sec. XI, where m2 is the larger of the two masses. The number of events expected for a luminosity of 20.3 fb-1 is quoted at each step of the selection. The preselection requires four baseline leptons, at least two of which are light leptons; the signal lepton selection is made at the ``Lepton Multiplicity' stage. ``Event Cleaning' refers to the selection criteria applied to remove non-collision backgrounds and detector noise. The RPC R-slepton model is used, with (m2,m1) = (450,300) GeV.
Cut flows by lepton channel for a representative selection of SUSY signal points in the SR1noZb signal region. In each case, m2 and m1 refer to the axes of the plots in Sec. XI, where m2 is the larger of the two masses. The number of events expected for a luminosity of 20.3 fb-1 is quoted at each step of the selection. The preselection requires four baseline leptons, at least two of which are light leptons; the signal lepton selection is made at the ``Lepton Multiplicity' stage. ``Event Cleaning' refers to the selection criteria applied to remove non-collision backgrounds and detector noise. The RPV gluino NLSP model is used, with lambda_133 != 0 and (m2,m1) = (800,400) GeV.
Cut flows by lepton channel for a representative selection of SUSY signal points in the SR0Z signal region. In each case, m2 and m1 refer to the axes of the plots in Sec. XI, where m2 is the value of mu. The number of events expected for a luminosity of 20.3 fb-1 is quoted at each step of the selection. The preselection requires four baseline leptons, at least two of which are light leptons; the signal lepton selection is made at the ``Lepton Multiplicity' stage. ``Event Cleaning' refers to the selection criteria applied to remove non-collision backgrounds and detector noise. The GGM tan beta = 30 model is used, with (m2,m1) = (200,1000) GeV.
Differential cross sections as a function of transverse momentum pt are presented for the production of Y(nS) (n = 1, 2, 3) states decaying into a pair of muons. Data corresponding to an integrated luminosity of 4.9 inverse femtobarns in pp collisions at sqrt(s) = 7 TeV were collected with the CMS detector at the LHC. The analysis selects events with dimuon rapidity abs(y) < 1.2 and dimuon transverse momentum in the range 10 < pt < 100 GeV. The measurements show a transition from an exponential to a power-law behavior at pt ~ 20 GeV for the three Y states. Above that transition, the Y spectrum is significantly harder than that of the Y(1S) and Y(2S). The ratios of the Y(3S) and Y(2S) differential cross sections to the Y(1S) cross section show a rise as pt increases at low pt, then become flatter at higher pt.
The $p_{\rm T}$ bin width, the weighted mean $p_{\rm T}$ within a bin, and the differential cross section times the dimuon branching fraction for the $\Upsilon$(1S), $\Upsilon$(2S), and $\Upsilon$(3S) with $0 < |y| < 0.6$. The statistical and systematic uncertainties in the differential cross section are given as the percentage of the cross section.
The $p_{\rm T}$ bin width, the weighted mean $p_{\rm T}$ within a bin, and the differential cross section times the dimuon branching fraction for the $\Upsilon$(1S), $\Upsilon$(2S), and $\Upsilon$(3S) with $0.6 < |y| < 1.2$. The statistical and systematic uncertainties in the differential cross section are given as the percentage of the cross section.
The $p_{\rm T}$ bin width, the weighted mean $p_{\rm T}$ within a bin, and the differential cross section times the dimuon branching fraction for the $\Upsilon$(1S), $\Upsilon$(2S), and $\Upsilon$(3S) with $|y| < 1.2$. The statistical and systematic uncertainties in the differential cross section are given as the percentage of the cross section.
The $p_{\rm T}$ bin width and corrected yield ratios R21 and R31 for $|y| < 0.6$. The statistical and systematic uncertainties in the corrected yield ratios are given as the percentage of the ratio.
The $p_{\rm T}$ bin width and corrected yield ratios R21 and R31 for $0.6 < |y| < 1.2$. The statistical and systematic uncertainties in the corrected yield ratios are given as the percentage of the ratio.
The $p_{\rm T}$ bin width and corrected yield ratios R21 and R31 for $|y| < 1.2$. The statistical and systematic uncertainties in the corrected yield ratios are given as the percentage of the ratio.
The dimuon acceptance $\mathcal{A}$ calculated using the CMS measured polarization and its positive and negative uncertainties $\mathcal{A}(\sigma^{\pm})$, and the values of the acceptance assuming no polarization $\mathcal{A}$(unpol), transverse polarization $\mathcal{A}(T)$, and longitudinal polarization $\mathcal{A}(L)$ for the $\Upsilon$(1S) state and $|y| <0.6$.
The dimuon acceptance $\mathcal{A}$ calculated using the CMS measured polarization and its positive and negative uncertainties $\mathcal{A}(\sigma^{\pm})$, and the values of the acceptance assuming no polarization $\mathcal{A}$(unpol), transverse polarization $\mathcal{A}(T)$, and longitudinal polarization $\mathcal{A}(L)$ for the $\Upsilon $(1S) state and $0.6 < |y| < 1.2$.
The dimuon acceptance $\mathcal{A}$ calculated using the CMS measured polarization and its positive and negative uncertainties $\mathcal{A}(\sigma^{\pm})$, and the values of the acceptance assuming no polarization $\mathcal{A}$(unpol), transverse polarization $\mathcal{A}(T)$, and longitudinal polarization $\mathcal{A}(L)$ for the $\Upsilon $(1S) state and $|y| < 1.2$.
The dimuon acceptance $\mathcal{A}$ calculated using the CMS measured polarization and its positive and negative uncertainties $\mathcal{A}(\sigma^{\pm})$, and the values of the acceptance assuming no polarization $\mathcal{A}$(unpol), transverse polarization $\mathcal{A}(T)$, and longitudinal polarization $\mathcal{A}(L)$ for the $\Upsilon $(2S) state and $|y| < 0.6$.
The dimuon acceptance $\mathcal{A}$ calculated using the CMS measured polarization and its positive and negative uncertainties $\mathcal{A}(\sigma^{\pm})$, and the values of the acceptance assuming no polarization $\mathcal{A}$(unpol), transverse polarization $\mathcal{A}(T)$, and longitudinal polarization $\mathcal{A}(L)$ for the $\Upsilon $(2S) state and $0.6 < |y| < 1.2$.
The dimuon acceptance $\mathcal{A}$ calculated using the CMS measured polarization and its positive and negative uncertainties $\mathcal{A}(\sigma^{\pm})$, and the values of the acceptance assuming no polarization $\mathcal{A}$(unpol), transverse polarization $\mathcal{A}(T)$, and longitudinal polarization $\mathcal{A}(L)$ for the $\Upsilon $(2S) state and $|y| < 1.2$.
The dimuon acceptance $\mathcal{A}$ calculated using the CMS measured polarization and its positive and negative uncertainties $\mathcal{A}(\sigma^{\pm})$, and the values of the acceptance assuming no polarization $\mathcal{A}$(unpol), transverse polarization $\mathcal{A}(T)$, and longitudinal polarization $\mathcal{A}(L)$ for the $\Upsilon $(3S) state and $|y| < 0.6$.
The dimuon acceptance $\mathcal{A}$ calculated using the CMS measured polarization and its positive and negative uncertainties $\mathcal{A}(\sigma^{\pm})$, and the values of the acceptance assuming no polarization $\mathcal{A}$(unpol), transverse polarization $\mathcal{A}(T)$, and longitudinal polarization $\mathcal{A}(L)$ for the $\Upsilon $(3S) state and $0.6 < |y| < 1.2$.
The dimuon acceptance $\mathcal{A}$ calculated using the CMS measured polarization and its positive and negative uncertainties $\mathcal{A}(\sigma^{\pm})$, and the values of the acceptance assuming no polarization $\mathcal{A}$(unpol), transverse polarization $\mathcal{A}(T)$, and longitudinal polarization $\mathcal{A}(L)$ for the $\Upsilon $(3S) state and $|y| < 1.2$.
A search is performed for heavy Majorana neutrinos (N) decaying into a W boson and a lepton using the CMS detector at the Large Hadron Collider. A signature of two jets and either two same sign electrons or a same sign electron-muon pair is searched for using 19.7 inverse femtobarns of data collected during 2012 in proton-proton collisions at a centre-of-mass energy of 8 TeV. The data are found to be consistent with the expected standard model (SM) background and, in the context of a Type-1 seesaw mechanism, upper limits are set on the cross section times branching fraction for production of heavy Majorana neutrinos in the mass range between 40 and 500 GeV. The results are additionally interpreted as limits on the mixing between the heavy Majorana neutrinos and the SM neutrinos. In the mass range considered, the upper limits range between 0.00015 - 0.72 for |V[eN]|^2 and 6.6E-5 - 0.47 for |V[eN] V*[muN]|^2 / ( |V[eN]|^2 + |V[muN]|^2 ), where V[lN] is the mixing element describing the mixing of the heavy neutrino with the SM neutrino of flavour l. These limits are the most restrictive direct limits for heavy Majorana neutrino masses above 200 GeV.
Selection requirements for the low- and high-mass signal regions.
ee channel. Selection requirements on discriminating variables determined by the optimization for each Majorana neutrino mass point. The last column shows the overall signal acceptance. Different selection criteria are used for low- and high-mass search regions. The "-" indicates that no selection requirement is made.
e$\mu$ channel. Selection requirements on discriminating variables determined by the optimization for each Majorana neutrino mass point. The last column shows the overall signal acceptance. Different selection criteria are used for low- and high-mass search regions. The ''-'' indicates that no selection requirement is made.
Observed event yields and estimated backgrounds in the low- and high-mass control regions. The uncertainty in the background yield is the sum in quadrature of the statistical and systematic uncertainties.
Summary of the relative systematic uncertainties in heavy Majorana neutrino signal yields and the background from prompt same-sign leptons, both estimated from simulation. The relative systematic uncertainties assigned to the data-driven backgrounds for the misidentified lepton background and mismeasured charge background are also shown. The uncertainties are given for the low-mass selections.
Summary of the relative systematic uncertainties in heavy Majorana neutrino signal yields and the background from prompt same-sign leptons, both estimated from simulation. The relative systematic uncertainties assigned to the data-driven backgrounds for the misidentified lepton background and mismeasured charge background are also shown. The uncertainties are given for the high-mass selections.
Summary of contributions to the systematic uncertainty related to the prompt same-sign leptons background, misidentified lepton background, and mismeasured charge background on the total background uncertainty for the case of $m_{\rm N}$ = 100 and 500 GeV.
Observed event yields and estimated backgrounds after the application of all selection, except for the final optimization. The background predictions from prompt same-sign leptons (Prompt bkgd.), misidentified leptons (Misid. bkgd.), mismeasured charge (Charge mismeas. bkgd.) and the total background (Total bkgd.) are shown together withthe number of events observed in data. The uncertainties shown are the statistical and systematic components, respectively.
Dielectron channel results after final optimization. The background predictions from prompt same-sign leptons, misidentified leptons, and mismeasured charge are shown along with the total background estimate and the number of events observed in data. The uncertainties shown are the statistical and systematic components, respectively.
Electron-muon channel results after final optimization. The background predictions from prompt same-sign leptons and misidentified leptons are shown along with the total background estimate and the number of events observed in data. The uncertainties shown are the statistical and systematic components, respectively.
The results of a search for new heavy $W^\prime$ bosons decaying to an electron or muon and a neutrino using proton-proton collision data at a centre-of-mass energy of $\sqrt{s} = 13$ TeV are presented. The dataset was collected in 2015 and 2016 by the ATLAS experiment at the Large Hadron Collider and corresponds to an integrated luminosity of 36.1 fb$^{-1}$. As no excess of events above the Standard Model prediction is observed, the results are used to set upper limits on the $W^\prime$ boson cross-section times branching ratio to an electron or muon and a neutrino as a function of the $W^\prime$ mass. Assuming a $W^\prime$ boson with the same couplings as the Standard Model $W$ boson, $W^\prime$ masses below 5.1 TeV are excluded at the 95% confidence level.
Transverse mass distribution for events satisfying all selection criteria in the electron channel.
Transverse mass distribution for events satisfying all selection criteria in the electron channel.
Transverse mass distribution for events satisfying all selection criteria in the muon channel.
Transverse mass distribution for events satisfying all selection criteria in the muon channel.
Upper limits at the 95% CL on the cross section for SSM W' production and decay to the electron+neutrino channel as a function of the W' pole mass.
Upper limits at the 95% CL on the cross section for SSM W' production and decay to the electron+neutrino channel as a function of the W' pole mass.
Upper limits at the 95% CL on the cross section for SSM W' production and decay to the muon+neutrino channel as a function of the W' pole mass.
Upper limits at the 95% CL on the cross section for SSM W' production and decay to the muon+neutrino channel as a function of the W' pole mass.
Combined (electron and muon channels) upper limits at the 95% CL on the cross section for SSM W' production and decay to a single lepton generation as a function of the W' pole mass.
Combined (electron and muon channels) upper limits at the 95% CL on the cross section for SSM W' production and decay to a single lepton generation as a function of the W' pole mass.
Product of acceptance and efficiency for the electron and muon selections as a function of the W' pole mass.
Product of acceptance and efficiency for the electron and muon selections as a function of the W' pole mass.
A search for pair production of a scalar partner of the top quark in events with four or more jets plus missing transverse momentum is presented. An analysis of 36.1 fb$^{-1}$ of $\sqrt{s}$=13 TeV proton-proton collisions collected using the ATLAS detector at the LHC yields no significant excess over the expected Standard Model background. To interpret the results a simplified supersymmetric model is used where the top squark is assumed to decay via $\tilde{t}_1 \rightarrow t^{(*)} \tilde\chi^0_1$ and $\tilde{t}_1\rightarrow b\tilde\chi^\pm_1 \rightarrow b W^{(*)} \tilde\chi^0_1$, where $\tilde\chi^0_1$ ($\chi^\pm_1$) denotes the lightest neutralino (chargino). Exclusion limits are placed in terms of the top-squark and neutralino masses. Assuming a branching ratio of 100% to $t \tilde\chi^0_1$, top-squark masses in the range 450-950 GeV are excluded for $\tilde\chi^0_1$ masses below 160 GeV. In the case where $m_{\tilde{t}_1}\sim m_t+m_{\tilde\chi^0_1}$, top-squark masses in the range 235-590 GeV are excluded.
Distribution of $E_\text{T}^\text{miss}$ for SRA-TT after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $E_\text{T}^\text{miss}$ for SRA-TT after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $E_\text{T}^\text{miss}$ for SRA-TT after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $E_\text{T}^\text{miss}$ for SRA-TT after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $E_\text{T}^\text{miss}$ for SRA-TT after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $E_\text{T}^\text{miss}$ for SRA-TT after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $E_\text{T}^\text{miss}$ for SRA-TT after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $m_\text{T2}^{\chi^2}$ for SRA-T0 after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $m_\text{T2}^{\chi^2}$ for SRA-T0 after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $m_\text{T2}^{\chi^2}$ for SRA-T0 after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $m_\text{T2}^{\chi^2}$ for SRA-T0 after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $m_\text{T2}^{\chi^2}$ for SRA-T0 after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $m_\text{T2}^{\chi^2}$ for SRA-T0 after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $m_\text{T2}^{\chi^2}$ for SRA-T0 after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $m_\text{T}^{b,\text{max}}$ for SRB-TW after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $m_\text{T}^{b,\text{max}}$ for SRB-TW after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $m_\text{T}^{b,\text{max}}$ for SRB-TW after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $m_\text{T}^{b,\text{max}}$ for SRB-TW after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $m_\text{T}^{b,\text{max}}$ for SRB-TW after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $m_\text{T}^{b,\text{max}}$ for SRB-TW after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $m_\text{T}^{b,\text{max}}$ for SRB-TW after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $R_\text{ISR}$ for SRC1-5 after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $R_\text{ISR}$ for SRC1-5 after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $R_\text{ISR}$ for SRC1-5 after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $R_\text{ISR}$ for SRC1-5 after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $R_\text{ISR}$ for SRC1-5 after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $R_\text{ISR}$ for SRC1-5 after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $R_\text{ISR}$ for SRC1-5 after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $m_\text{T}^{b,\text{max}}$ for SRD-high after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $m_\text{T}^{b,\text{max}}$ for SRD-high after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $m_\text{T}^{b,\text{max}}$ for SRD-high after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $m_\text{T}^{b,\text{max}}$ for SRD-high after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $m_\text{T}^{b,\text{max}}$ for SRD-high after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $m_\text{T}^{b,\text{max}}$ for SRD-high after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $m_\text{T}^{b,\text{max}}$ for SRD-high after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $H_\text{T}$ for SRE after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $H_\text{T}$ for SRE after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $H_\text{T}$ for SRE after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $H_\text{T}$ for SRE after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $H_\text{T}$ for SRE after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $H_\text{T}$ for SRE after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Distribution of $H_\text{T}$ for SRE after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.
Expected (blue solid line) exclusion limits at 95% CL as a function of stop and LSP masses in the scenario where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Expected (blue solid line) exclusion limits at 95% CL as a function of stop and LSP masses in the scenario where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Expected (blue solid line) exclusion limits at 95% CL as a function of stop and LSP masses in the scenario where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Expected (blue solid line) exclusion limits at 95% CL as a function of stop and LSP masses in the scenario where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Expected (blue solid line) exclusion limits at 95% CL as a function of stop and LSP masses in the scenario where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Expected (blue solid line) exclusion limits at 95% CL as a function of stop and LSP masses in the scenario where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Expected (blue solid line) exclusion limits at 95% CL as a function of stop and LSP masses in the scenario where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Observed (red solid line) exclusion limits at 95% CL as a function of stop and LSP masses in the scenario where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Observed (red solid line) exclusion limits at 95% CL as a function of stop and LSP masses in the scenario where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Observed (red solid line) exclusion limits at 95% CL as a function of stop and LSP masses in the scenario where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Observed (red solid line) exclusion limits at 95% CL as a function of stop and LSP masses in the scenario where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Observed (red solid line) exclusion limits at 95% CL as a function of stop and LSP masses in the scenario where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Observed (red solid line) exclusion limits at 95% CL as a function of stop and LSP masses in the scenario where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Observed (red solid line) exclusion limits at 95% CL as a function of stop and LSP masses in the scenario where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.
Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small tan$\beta$ assumption.
Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small tan$\beta$ assumption.
Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small tan$\beta$ assumption.
Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small tan$\beta$ assumption.
Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small tan$\beta$ assumption.
Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small tan$\beta$ assumption.
Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small tan$\beta$ assumption.
Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small tan$\beta$ assumption.
Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small tan$\beta$ assumption.
Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small tan$\beta$ assumption.
Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small tan$\beta$ assumption.
Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small tan$\beta$ assumption.
Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small tan$\beta$ assumption.
Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small tan$\beta$ assumption.
Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a large tan$\beta$ assumption.
Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a large tan$\beta$ assumption.
Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a large tan$\beta$ assumption.
Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a large tan$\beta$ assumption.
Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a large tan$\beta$ assumption.
Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a large tan$\beta$ assumption.
Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a large tan$\beta$ assumption.
Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a large tan$\beta$ assumption.
Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a large tan$\beta$ assumption.
Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a large tan$\beta$ assumption.
Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a large tan$\beta$ assumption.
Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a large tan$\beta$ assumption.
Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a large tan$\beta$ assumption.
Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a large tan$\beta$ assumption.
Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small right-handed top-squark mass parameter assumption.
Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small right-handed top-squark mass parameter assumption.
Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small right-handed top-squark mass parameter assumption.
Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small right-handed top-squark mass parameter assumption.
Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small right-handed top-squark mass parameter assumption.
Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small right-handed top-squark mass parameter assumption.
Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small right-handed top-squark mass parameter assumption.
Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small right-handed top-squark mass parameter assumption.
Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small right-handed top-squark mass parameter assumption.
Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small right-handed top-squark mass parameter assumption.
Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small right-handed top-squark mass parameter assumption.
Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small right-handed top-squark mass parameter assumption.
Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small right-handed top-squark mass parameter assumption.
Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small right-handed top-squark mass parameter assumption.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a negative value of $\mu$.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a negative value of $\mu$.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a negative value of $\mu$.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a negative value of $\mu$.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a negative value of $\mu$.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a negative value of $\mu$.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a negative value of $\mu$.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a negative value of $\mu$.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a negative value of $\mu$.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a negative value of $\mu$.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a negative value of $\mu$.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a negative value of $\mu$.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a negative value of $\mu$.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a negative value of $\mu$.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a positive value of $\mu$.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a positive value of $\mu$.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a positive value of $\mu$.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a positive value of $\mu$.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a positive value of $\mu$.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a positive value of $\mu$.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a positive value of $\mu$.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a positive value of $\mu$.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a positive value of $\mu$.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a positive value of $\mu$.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a positive value of $\mu$.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a positive value of $\mu$.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a positive value of $\mu$.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a positive value of $\mu$.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the left-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the left-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the left-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the left-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the left-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the left-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the left-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the left-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the left-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the left-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the left-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the left-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the left-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the left-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the right-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the right-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the right-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the right-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the right-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the right-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the right-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the right-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the right-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the right-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the right-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the right-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the right-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the right-handed top-squark mass parameter scan in the well-tempered pMSSM model.
Expected exclusion limits at 95% CL exclusion as a function of $\tilde{g}$ and $\tilde{t}$ masses in the scenario where both gluinos decay via $\tilde{g}\to t \tilde{t}\to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Expected exclusion limits at 95% CL exclusion as a function of $\tilde{g}$ and $\tilde{t}$ masses in the scenario where both gluinos decay via $\tilde{g}\to t \tilde{t}\to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Expected exclusion limits at 95% CL exclusion as a function of $\tilde{g}$ and $\tilde{t}$ masses in the scenario where both gluinos decay via $\tilde{g}\to t \tilde{t}\to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Expected exclusion limits at 95% CL exclusion as a function of $\tilde{g}$ and $\tilde{t}$ masses in the scenario where both gluinos decay via $\tilde{g}\to t \tilde{t}\to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Expected exclusion limits at 95% CL exclusion as a function of $\tilde{g}$ and $\tilde{t}$ masses in the scenario where both gluinos decay via $\tilde{g}\to t \tilde{t}\to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Expected exclusion limits at 95% CL exclusion as a function of $\tilde{g}$ and $\tilde{t}$ masses in the scenario where both gluinos decay via $\tilde{g}\to t \tilde{t}\to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Expected exclusion limits at 95% CL exclusion as a function of $\tilde{g}$ and $\tilde{t}$ masses in the scenario where both gluinos decay via $\tilde{g}\to t \tilde{t}\to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Observed exclusion limits at 95% CL exclusion as a function of $\tilde{g}$ and $\tilde{t}$ masses in the scenario where both gluinos decay via $\tilde{g}\to t \tilde{t}\to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Observed exclusion limits at 95% CL exclusion as a function of $\tilde{g}$ and $\tilde{t}$ masses in the scenario where both gluinos decay via $\tilde{g}\to t \tilde{t}\to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Observed exclusion limits at 95% CL exclusion as a function of $\tilde{g}$ and $\tilde{t}$ masses in the scenario where both gluinos decay via $\tilde{g}\to t \tilde{t}\to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Observed exclusion limits at 95% CL exclusion as a function of $\tilde{g}$ and $\tilde{t}$ masses in the scenario where both gluinos decay via $\tilde{g}\to t \tilde{t}\to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Observed exclusion limits at 95% CL exclusion as a function of $\tilde{g}$ and $\tilde{t}$ masses in the scenario where both gluinos decay via $\tilde{g}\to t \tilde{t}\to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Observed exclusion limits at 95% CL exclusion as a function of $\tilde{g}$ and $\tilde{t}$ masses in the scenario where both gluinos decay via $\tilde{g}\to t \tilde{t}\to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Observed exclusion limits at 95% CL exclusion as a function of $\tilde{g}$ and $\tilde{t}$ masses in the scenario where both gluinos decay via $\tilde{g}\to t \tilde{t}\to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Results of the exclusion fits for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ from the combination of SRA, SRB, SRC, SRD and SRE, based on the best expected $CL_s$. The numbers centered on the grid points indicate which of the signal regions gave the best expected $CL_s$ (with 1, 2, 3, 4, 5, 6 corresponding to SRA, SRB, SRC, SRD-low,SR D-high, SRE respectively).
Results of the exclusion fits for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ from the combination of SRA, SRB, SRC, SRD and SRE, based on the best expected $CL_s$. The numbers centered on the grid points indicate which of the signal regions gave the best expected $CL_s$ (with 1, 2, 3, 4, 5, 6 corresponding to SRA, SRB, SRC, SRD-low,SR D-high, SRE respectively).
Results of the exclusion fits for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ from the combination of SRA, SRB, SRC, SRD and SRE, based on the best expected $CL_s$. The numbers centered on the grid points indicate which of the signal regions gave the best expected $CL_s$ (with 1, 2, 3, 4, 5, 6 corresponding to SRA, SRB, SRC, SRD-low,SR D-high, SRE respectively).
Results of the exclusion fits for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ from the combination of SRA, SRB, SRC, SRD and SRE, based on the best expected $CL_s$. The numbers centered on the grid points indicate which of the signal regions gave the best expected $CL_s$ (with 1, 2, 3, 4, 5, 6 corresponding to SRA, SRB, SRC, SRD-low,SR D-high, SRE respectively).
Results of the exclusion fits for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ from the combination of SRA, SRB, SRC, SRD and SRE, based on the best expected $CL_s$. The numbers centered on the grid points indicate which of the signal regions gave the best expected $CL_s$ (with 1, 2, 3, 4, 5, 6 corresponding to SRA, SRB, SRC, SRD-low,SR D-high, SRE respectively).
Results of the exclusion fits for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ from the combination of SRA, SRB, SRC, SRD and SRE, based on the best expected $CL_s$. The numbers centered on the grid points indicate which of the signal regions gave the best expected $CL_s$ (with 1, 2, 3, 4, 5, 6 corresponding to SRA, SRB, SRC, SRD-low,SR D-high, SRE respectively).
Results of the exclusion fits for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ from the combination of SRA, SRB, SRC, SRD and SRE, based on the best expected $CL_s$. The numbers centered on the grid points indicate which of the signal regions gave the best expected $CL_s$ (with 1, 2, 3, 4, 5, 6 corresponding to SRA, SRB, SRC, SRD-low,SR D-high, SRE respectively).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 0%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 0%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 0%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 0%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 0%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 0%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 0%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 25%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 25%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 25%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 25%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 25%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 25%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 25%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 50%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 50%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 50%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 50%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 50%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 50%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 50%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 0 (top left), 25% (top right), 50% (middle left), 75% middle right) and 100% (bottom). The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 0 (top left), 25% (top right), 50% (middle left), 75% middle right) and 100% (bottom). The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 0 (top left), 25% (top right), 50% (middle left), 75% middle right) and 100% (bottom). The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 0 (top left), 25% (top right), 50% (middle left), 75% middle right) and 100% (bottom). The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 0 (top left), 25% (top right), 50% (middle left), 75% middle right) and 100% (bottom). The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 0 (top left), 25% (top right), 50% (middle left), 75% middle right) and 100% (bottom). The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 0 (top left), 25% (top right), 50% (middle left), 75% middle right) and 100% (bottom). The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).
Results of the exclusion fits in the wino NLSP grid for negative values of $\mu$. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the wino NLSP grid for negative values of $\mu$. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the wino NLSP grid for negative values of $\mu$. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the wino NLSP grid for negative values of $\mu$. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the wino NLSP grid for negative values of $\mu$. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the wino NLSP grid for negative values of $\mu$. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the wino NLSP grid for negative values of $\mu$. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the wino NLSP grid for positive values of $\mu$. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the wino NLSP grid for positive values of $\mu$. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the wino NLSP grid for positive values of $\mu$. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the wino NLSP grid for positive values of $\mu$. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the wino NLSP grid for positive values of $\mu$. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the wino NLSP grid for positive values of $\mu$. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the wino NLSP grid for positive values of $\mu$. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the well-tempered neutralino grid for the $m_{q3L}$ scenario. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the well-tempered neutralino grid for the $m_{q3L}$ scenario. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the well-tempered neutralino grid for the $m_{q3L}$ scenario. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the well-tempered neutralino grid for the $m_{q3L}$ scenario. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the well-tempered neutralino grid for the $m_{q3L}$ scenario. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the well-tempered neutralino grid for the $m_{q3L}$ scenario. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the well-tempered neutralino grid for the $m_{q3L}$ scenario. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the well-tempered neutralino grid for the $m_{tR}$ scenario. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the well-tempered neutralino grid for the $m_{tR}$ scenario. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the well-tempered neutralino grid for the $m_{tR}$ scenario. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the well-tempered neutralino grid for the $m_{tR}$ scenario. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the well-tempered neutralino grid for the $m_{tR}$ scenario. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the well-tempered neutralino grid for the $m_{tR}$ scenario. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the well-tempered neutralino grid for the $m_{tR}$ scenario. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).
Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenarios with large tan$\beta$ (top left) is shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).
Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenarios with large tan$\beta$ (top left) is shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).
Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenarios with large tan$\beta$ (top left) is shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).
Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenarios with large tan$\beta$ (top left) is shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).
Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenarios with large tan$\beta$ (top left) is shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).
Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenarios with large tan$\beta$ (top left) is shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).
Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenarios with large tan$\beta$ (top left) is shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).
Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenarios with small tan$\beta$ are shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).
Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenarios with small tan$\beta$ are shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).
Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenarios with small tan$\beta$ are shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).
Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenarios with small tan$\beta$ are shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).
Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenarios with small tan$\beta$ are shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).
Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenarios with small tan$\beta$ are shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).
Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenarios with small tan$\beta$ are shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).
Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenario with a mostly right-handed top squark partner is shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).
Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenario with a mostly right-handed top squark partner is shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).
Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenario with a mostly right-handed top squark partner is shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).
Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenario with a mostly right-handed top squark partner is shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).
Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenario with a mostly right-handed top squark partner is shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).
Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenario with a mostly right-handed top squark partner is shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).
Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenario with a mostly right-handed top squark partner is shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).
Acceptance for SRA-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRA-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRA-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRA-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRA-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRA-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRA-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRB-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRB-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRB-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRB-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRB-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRB-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRB-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRE for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRE for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRE for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRE for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRE for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRE for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRE for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRA-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRA-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRA-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRA-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRA-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRA-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRA-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRB-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRB-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRB-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRB-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRB-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRB-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRB-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRA-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRA-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRA-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRA-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRA-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRA-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRA-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRB-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRB-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRB-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRB-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRB-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRB-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRB-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC1 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC1 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC1 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC1 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC1 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC1 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC1 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC2 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC2 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC2 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC2 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC2 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC2 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC2 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC3 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC3 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC3 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC3 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC3 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC3 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC3 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC4 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC4 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC4 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC4 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC4 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC4 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC4 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC5 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC5 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC5 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC5 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC5 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC5 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRC5 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Acceptance for SRD-low for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Acceptance for SRD-low for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Acceptance for SRD-low for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Acceptance for SRD-low for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Acceptance for SRD-low for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Acceptance for SRD-low for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Acceptance for SRD-low for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Acceptance for SRD-high for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Acceptance for SRD-high for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Acceptance for SRD-high for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Acceptance for SRD-high for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Acceptance for SRD-high for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Acceptance for SRD-high for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Acceptance for SRD-high for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Acceptance for SRE for gluino pair production in the case where both gluinos decay via $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Acceptance for SRE for gluino pair production in the case where both gluinos decay via $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Acceptance for SRE for gluino pair production in the case where both gluinos decay via $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Acceptance for SRE for gluino pair production in the case where both gluinos decay via $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Acceptance for SRE for gluino pair production in the case where both gluinos decay via $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Acceptance for SRE for gluino pair production in the case where both gluinos decay via $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Acceptance for SRE for gluino pair production in the case where both gluinos decay via $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Efficiencies for SRA-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRA-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRA-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRA-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRA-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRA-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRA-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRB-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRB-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRB-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRB-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRB-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRB-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRB-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRE for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRE for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRE for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRE for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRE for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRE for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRE for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRA-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRA-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRA-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRA-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRA-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRA-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRA-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRB-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRB-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRB-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRB-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRB-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRB-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRB-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRA-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRA-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRA-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRA-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRA-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRA-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRA-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRB-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRB-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRB-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRB-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRB-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRB-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRB-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC1 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC1 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC1 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC1 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC1 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC1 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC1 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC2 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC2 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC2 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC2 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC2 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC2 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC2 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC3 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC3 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC3 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC3 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC3 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC3 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC3 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC4 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC4 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC4 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC4 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC4 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC4 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC4 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC5 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC5 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC5 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC5 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC5 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC5 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRC5 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.
Efficiencies for SRD-low for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Efficiencies for SRD-low for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Efficiencies for SRD-low for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Efficiencies for SRD-low for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Efficiencies for SRD-low for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Efficiencies for SRD-low for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Efficiencies for SRD-low for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Efficiencies for SRD-high for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Efficiencies for SRD-high for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Efficiencies for SRD-high for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Efficiencies for SRD-high for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Efficiencies for SRD-high for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Efficiencies for SRD-high for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Efficiencies for SRD-high for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.
Efficiencies for SRE for gluino pair production in the case where both gluinos decay via $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Efficiencies for SRE for gluino pair production in the case where both gluinos decay via $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Efficiencies for SRE for gluino pair production in the case where both gluinos decay via $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Efficiencies for SRE for gluino pair production in the case where both gluinos decay via $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Efficiencies for SRE for gluino pair production in the case where both gluinos decay via $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Efficiencies for SRE for gluino pair production in the case where both gluinos decay via $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Efficiencies for SRE for gluino pair production in the case where both gluinos decay via $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.
Upper limit cross-section, in femtobarn, for the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ grid.
Upper limit cross-section, in femtobarn, for the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ grid.
Upper limit cross-section, in femtobarn, for the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ grid.
Upper limit cross-section, in femtobarn, for the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ grid.
Upper limit cross-section, in femtobarn, for the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ grid.
Upper limit cross-section, in femtobarn, for the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ grid.
Upper limit cross-section, in femtobarn, for the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ grid.
Upper limit cross-section, in femtobarn, for the $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft grid.
Upper limit cross-section, in femtobarn, for the $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft grid.
Upper limit cross-section, in femtobarn, for the $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft grid.
Upper limit cross-section, in femtobarn, for the $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft grid.
Upper limit cross-section, in femtobarn, for the $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft grid.
Upper limit cross-section, in femtobarn, for the $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft grid.
Upper limit cross-section, in femtobarn, for the $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft grid.
Cutflow for SRA for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (800,1) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRA for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (800,1) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRA for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (800,1) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRA for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (800,1) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRA for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (800,1) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRA for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (800,1) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRA for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (800,1) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow SRB for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (600,300) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow SRB for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (600,300) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow SRB for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (600,300) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow SRB for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (600,300) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow SRB for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (600,300) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow SRB for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (600,300) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow SRB for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (600,300) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRC1 and SRC2 for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (250,77) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRC1 and SRC2 for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (250,77) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRC1 and SRC2 for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (250,77) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRC1 and SRC2 for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (250,77) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRC1 and SRC2 for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (250,77) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRC1 and SRC2 for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (250,77) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRC1 and SRC2 for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (250,77) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRC3, SRC4, and SRC5 for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (500,327) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRC3, SRC4, and SRC5 for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (500,327) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRC3, SRC4, and SRC5 for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (500,327) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRC3, SRC4, and SRC5 for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (500,327) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRC3, SRC4, and SRC5 for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (500,327) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRC3, SRC4, and SRC5 for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (500,327) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRC3, SRC4, and SRC5 for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (500,327) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRD-high for a signal model with bottom squark pair production in the case where both bottom squarks decay via $b\tilde\chi^{\pm}_1\to bW^{(*)} \tilde\chi^0_1$, with $m(\tilde\chi^{\pm}_1)-m(\tilde\chi^0_1) = 1$ GeV with $m(\tilde{t}_1,\tilde\chi^{\pm}_1)=$ (800,100) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRD-high for a signal model with bottom squark pair production in the case where both bottom squarks decay via $b\tilde\chi^{\pm}_1\to bW^{(*)} \tilde\chi^0_1$, with $m(\tilde\chi^{\pm}_1)-m(\tilde\chi^0_1) = 1$ GeV with $m(\tilde{b}_1,\tilde\chi^{\pm}_1)=$ (750,200) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRD-high for a signal model with bottom squark pair production in the case where both bottom squarks decay via $b\tilde\chi^{\pm}_1\to bW^{(*)} \tilde\chi^0_1$, with $m(\tilde\chi^{\pm}_1)-m(\tilde\chi^0_1) = 1$ GeV with $m(\tilde{b}_1,\tilde\chi^{\pm}_1)=$ (750,200) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRD-high for a signal model with bottom squark pair production in the case where both bottom squarks decay via $b\tilde\chi^{\pm}_1\to bW^{(*)} \tilde\chi^0_1$, with $m(\tilde\chi^{\pm}_1)-m(\tilde\chi^0_1) = 1$ GeV with $m(\tilde{b}_1,\tilde\chi^{\pm}_1)=$ (750,200) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRD-high for a signal model with bottom squark pair production in the case where both bottom squarks decay via $b\tilde\chi^{\pm}_1\to bW^{(*)} \tilde\chi^0_1$, with $m(\tilde\chi^{\pm}_1)-m(\tilde\chi^0_1) = 1$ GeV with $m(\tilde{b}_1,\tilde\chi^{\pm}_1)=$ (800,100) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRD-high for a signal model with bottom squark pair production in the case where both bottom squarks decay via $b\tilde\chi^{\pm}_1\to bW^{(*)} \tilde\chi^0_1$, with $m(\tilde\chi^{\pm}_1)-m(\tilde\chi^0_1) = 1$ GeV with $m(\tilde{b}_1,\tilde\chi^{\pm}_1)=$ (750,200) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRD-high for a signal model with bottom squark pair production in the case where both bottom squarks decay via $b\tilde\chi^{\pm}_1\to bW^{(*)} \tilde\chi^0_1$, with $m(\tilde\chi^{\pm}_1)-m(\tilde\chi^0_1) = 1$ GeV with $m(\tilde{b}_1,\tilde\chi^{\pm}_1)=$ (750,200) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRD-low for a signal model with bottom squark pair production in the case where both bottom squarks decay via $b\tilde\chi^{\pm}_1\to bW^{(*)} \tilde\chi^0_1$, with $m(\tilde\chi^{\pm}_1)-m(\tilde\chi^0_1) = 1$ GeV witht $m(\tilde{t}_1,\tilde\chi^{\pm}_1)=$ (600,200) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRD-low for a signal model with bottom squark pair production in the case where both bottom squarks decay via $b\tilde\chi^{\pm}_1\to bW^{(*)} \tilde\chi^0_1$, with $m(\tilde\chi^{\pm}_1)-m(\tilde\chi^0_1) = 1$ GeV witht $m(\tilde{b}_1,\tilde\chi^{\pm}_1)=$ (400,200) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRD-low for a signal model with bottom squark pair production in the case where both bottom squarks decay via $b\tilde\chi^{\pm}_1\to bW^{(*)} \tilde\chi^0_1$, with $m(\tilde\chi^{\pm}_1)-m(\tilde\chi^0_1) = 1$ GeV witht $m(\tilde{b}_1,\tilde\chi^{\pm}_1)=$ (400,200) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRD-low for a signal model with bottom squark pair production in the case where both bottom squarks decay via $b\tilde\chi^{\pm}_1\to bW^{(*)} \tilde\chi^0_1$, with $m(\tilde\chi^{\pm}_1)-m(\tilde\chi^0_1) = 1$ GeV witht $m(\tilde{b}_1,\tilde\chi^{\pm}_1)=$ (400,200) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRD-low for a signal model with bottom squark pair production in the case where both bottom squarks decay via $b\tilde\chi^{\pm}_1\to bW^{(*)} \tilde\chi^0_1$, with $m(\tilde\chi^{\pm}_1)-m(\tilde\chi^0_1) = 1$ GeV witht $m(\tilde{b}_1,\tilde\chi^{\pm}_1)=$ (600,200) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRD-low for a signal model with bottom squark pair production in the case where both bottom squarks decay via $b\tilde\chi^{\pm}_1\to bW^{(*)} \tilde\chi^0_1$, with $m(\tilde\chi^{\pm}_1)-m(\tilde\chi^0_1) = 1$ GeV witht $m(\tilde{b}_1,\tilde\chi^{\pm}_1)=$ (400,200) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRD-low for a signal model with bottom squark pair production in the case where both bottom squarks decay via $b\tilde\chi^{\pm}_1\to bW^{(*)} \tilde\chi^0_1$, with $m(\tilde\chi^{\pm}_1)-m(\tilde\chi^0_1) = 1$ GeV witht $m(\tilde{b}_1,\tilde\chi^{\pm}_1)=$ (400,200) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRE for a signal model with gluino pair production in the case where both gluinos decay via $\tilde{g}\to t\tilde{t}_1\to t\tilde\chi^0_1+$soft and $\Delta m(\tilde{t}_1, \tilde\chi^0_1)=5$ GeV with $m(\tilde{g},\tilde{t}_1)=$ (1700,400) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRE for a signal model with gluino pair production in the case where both gluinos decay via $\tilde{g}\to t\tilde{t}_1\to t\tilde\chi^0_1+$soft and $\Delta m(\tilde{t}_1, \tilde\chi^0_1)=5$ GeV with $m(\tilde{g},\tilde{t}_1)=$ (1700,400) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRE for a signal model with gluino pair production in the case where both gluinos decay via $\tilde{g}\to t\tilde{t}_1\to t\tilde\chi^0_1+$soft and $\Delta m(\tilde{t}_1, \tilde\chi^0_1)=5$ GeV with $m(\tilde{g},\tilde{t}_1)=$ (1700,400) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRE for a signal model with gluino pair production in the case where both gluinos decay via $\tilde{g}\to t\tilde{t}_1\to t\tilde\chi^0_1+$soft and $\Delta m(\tilde{t}_1, \tilde\chi^0_1)=5$ GeV with $m(\tilde{g},\tilde{t}_1)=$ (1700,400) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRE for a signal model with gluino pair production in the case where both gluinos decay via $\tilde{g}\to t\tilde{t}_1\to t\tilde\chi^0_1+$soft and $\Delta m(\tilde{t}_1, \tilde\chi^0_1)=5$ GeV with $m(\tilde{g},\tilde{t}_1)=$ (1700,400) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRE for a signal model with gluino pair production in the case where both gluinos decay via $\tilde{g}\to t\tilde{t}_1\to t\tilde\chi^0_1+$soft and $\Delta m(\tilde{t}_1, \tilde\chi^0_1)=5$ GeV with $m(\tilde{g},\tilde{t}_1)=$ (1700,400) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
Cutflow for SRE for a signal model with gluino pair production in the case where both gluinos decay via $\tilde{g}\to t\tilde{t}_1\to t\tilde\chi^0_1+$soft and $\Delta m(\tilde{t}_1, \tilde\chi^0_1)=5$ GeV with $m(\tilde{g},\tilde{t}_1)=$ (1700,400) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.
A search for heavy neutral Higgs bosons and $Z^{\prime}$ bosons is performed using a data sample corresponding to an integrated luminosity of 36.1 fb$^{-1}$ from proton-proton collisions at $\sqrt{s}$ = 13 TeV recorded by the ATLAS detector at the LHC during 2015 and 2016. The heavy resonance is assumed to decay to $\tau^+\tau^-$ with at least one tau lepton decaying to final states with hadrons and a neutrino. The search is performed in the mass range of 0.2-2.25 TeV for Higgs bosons and 0.2-4.0 TeV for $Z^{\prime}$ bosons. The data are in good agreement with the background predicted by the Standard Model. The results are interpreted in benchmark scenarios. In the context of the hMSSM scenario, the data exclude $\tan\beta > 1.0$ for $m_A$ = 0.25 TeV and $\tan\beta > 42$ for $m_A$ = 1.5 TeV at the 95% confidence level. For the Sequential Standard Model, $Z^{\prime}_\mathrm{SSM}$ with $m_{Z^{\prime}} < 2.42$ TeV is excluded at 95% confidence level, while $Z^{\prime}_\mathrm{NU}$ with $m_{Z^{\prime}} < 2.25$ TeV is excluded for the non-universal $G(221)$ model that exhibits enhanced couplings to third-generation fermions.
Observed and predicted mTtot distribution in the b-veto category of the 1l1tau_h channel. Despite listing this as an exclusive final state (as there must be no b-jets), there is no explicit selection on the presence of additional light-flavour jets. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. In the paper, the first bin is cut off at 60 GeV for aesthetics but contains underflows down to 50 GeV as in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 300, 500 and 800 GeV and $\tan\beta$ = 10 in the hMSSM scenario are also provided.
Observed and predicted mTtot distribution in the b-tag category of the 1l1tau_h channel. Despite listing this as an exclusive final state (as there must be at least one b-jets), there is no explicit selection on the presence of additional light-flavour jets. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. In the paper, the first bin is cut off at 60 GeV for aesthetics but contains underflows down to 50 GeV as in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 300, 500 and 800 GeV and $\tan\beta$ = 10 in the hMSSM scenario are also provided.
Observed and predicted mTtot distribution in the b-veto category of the 2tau_h channel. Despite listing this as an exclusive final state (as there must be no b-jets), there is no explicit selection on the presence of additional light-flavour jets. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 300, 500 and 800 GeV and $\tan\beta$ = 10 in the hMSSM scenario are also provided.
Observed and predicted mTtot distribution in the b-tag category of the 2tau_h channel. Despite listing this as an exclusive final state (as there must be at least one b-jets), there is no explicit selection on the presence of additional light-flavour jets. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 300, 500 and 800 GeV and $\tan\beta$ = 10 in the hMSSM scenario are also provided.
Observed and predicted mTtot distribution for the b-inclusive selection in the 1l1tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. In the paper, the first bin is cut off at 60 GeV for aesthetics but contains underflows down to 50 GeV as in the HepData table. The last bin includes overflows. The prediction for a SSM Zprime with masses of 1500, 2000 and 2500 GeV are also provided.
Observed and predicted mTtot distribution for the b-inclusive selection in the 2tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The prediction for a SSM Zprime with masses of 1500, 2000 and 2500 GeV are also provided.
Observed and expected 95% CL upper limits on the b-associated Higgs boson production cross section times ditau branching fraction as a function of the boson mass.
Observed and expected 95% CL upper limits on the Drell Yan production cross section times ditau branching fraction as a function of the Zprime boson mass.
Observed and expected 95% CL upper limits on the Higgs boson production cross section times ditau branching fraction as a function of the boson mass and the relative strength of the b-associated production.
Ratio of the 95% CL upper limits on the production cross section times branching fraction for alternate Zprime models with respect to the SSM, both observed and expected are shown.
Acceptance, acceptance times efficiency and b-tag category fraction for a scalar boson produced by gluon-gluon fusion as a function of the scalar boson mass.
Acceptance, acceptance times efficiency and b-tag category fraction for a scalar boson produced by b-associated production as a function of the scalar boson mass.
Acceptance and acceptance times efficiency for a heavy gauge boson produced by Drell Yan as a function of the gauge boson mass.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times braching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the Higgs boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. Vaules are provided for the fit to the observed data and to the expected data, which is the sum of Standard Model contributions not including the SM Higgs boson. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively.
Observed and expected 95% CL upper limits on the gluon-gluon fusion Higgs boson production cross section times ditau branching fraction as a function of the boson mass.
This paper presents a search for direct electroweak gaugino or gluino pair production with a chargino nearly mass-degenerate with a stable neutralino. It is based on an integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ of $pp$ collisions at $\sqrt{s} = 13$ TeV collected by the ATLAS experiment at the LHC. The final state of interest is a disappearing track accompanied by at least one jet with high transverse momentum from initial-state radiation or by four jets from the gluino decay chain. The use of short track segments reconstructed from the innermost tracking layers significantly improves the sensitivity to short chargino lifetimes. The results are found to be consistent with Standard Model predictions. Exclusion limits are set at 95% confidence level on the mass of charginos and gluinos for different chargino lifetimes. For a pure wino with a lifetime of about 0.2 ns, chargino masses up to 460 GeV are excluded. For the strong production channel, gluino masses up to 1.65 TeV are excluded assuming a chargino mass of 460 GeV and lifetime of 0.2 ns.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the high-Emiss region.
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Model dependent upper limits on cross-section (fb) for the electroweak production are shown by grey numbers in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Model dependent upper limits on cross-section (pb) for the electroweak production are shown by grey numbers in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Model dependent upper limits on cross-section (pb) for the electroweak production are shown by grey numbers in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Model dependent upper limits on cross-section (pb) for the electroweak production are shown by grey numbers in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Model dependent upper limits on cross-section (pb) for the electroweak production are shown by grey numbers in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Total acceptance $\times$ efficiency of the electroweak channel. The total signal acceptance $\times$ efficiency is defined as the probability of an event passing the signal region selection when an electroweak gaugino pair is produced in a pp collision.
Total acceptance $\times$ efficiency of the electroweak channel. The total signal acceptance $\times$ efficiency is defined as the probability of an event passing the signal region selection when an electroweak gaugino pair is produced in a pp collision.
Total acceptance $\times$ efficiency of the electroweak channel. The total signal acceptance $\times$ efficiency is defined as the probability of an event passing the signal region selection when an electroweak gaugino pair is produced in a pp collision.
Total acceptance $\times$ efficiency of the electroweak channel. The total signal acceptance $\times$ efficiency is defined as the probability of an event passing the signal region selection when an electroweak gaugino pair is produced in a pp collision.
Total acceptance $\times$ efficiency of the electroweak channel. The total signal acceptance $\times$ efficiency is defined as the probability of an event passing the signal region selection when an electroweak gaugino pair is produced in a pp collision.
Total acceptance $\times$ efficiency of the strong channel. In white regions, no simulation sample is available. The left-upper triangle region is not allowed kinematically in wino-LSP scenarios. The total signal acceptance $\times$ efficiency is calculated relative to events in which the gluinos decay into electroweak gaugino pairs.
Total acceptance $\times$ efficiency of the strong channel. In white regions, no simulation sample is available. The left-upper triangle region is not allowed kinematically in wino-LSP scenarios. The total signal acceptance $\times$ efficiency is calculated relative to events in which the gluinos decay into electroweak gaugino pairs.
Total acceptance $\times$ efficiency of the strong channel. In white regions, no simulation sample is available. The left-upper triangle region is not allowed kinematically in wino-LSP scenarios. The total signal acceptance $\times$ efficiency is calculated relative to events in which the gluinos decay into electroweak gaugino pairs.
Total acceptance $\times$ efficiency of the strong channel. In white regions, no simulation sample is available. The left-upper triangle region is not allowed kinematically in wino-LSP scenarios. The total signal acceptance $\times$ efficiency is calculated relative to events in which the gluinos decay into electroweak gaugino pairs.
Total acceptance $\times$ efficiency of the strong channel. In white regions, no simulation sample is available. The left-upper triangle region is not allowed kinematically in wino-LSP scenarios. The total signal acceptance $\times$ efficiency is calculated relative to events in which the gluinos decay into electroweak gaugino pairs.
The generator-level acceptance after reconstruction, for selecting and reconstructing charginos as a function of the chargino $eta$ and chargino decay radius (at generator level).
The generator-level acceptance for charginos produced in the electroweak channel as a function of the chargino $eta$ and chargino decay radius (at generator level).
The generator-level acceptance for charginos produced in the electroweak channel as a function of the chargino $eta$ and chargino decay radius (at generator level).
The generator-level acceptance for charginos produced in the electroweak channel as a function of the chargino $eta$ and chargino decay radius (at generator level).
The generator-level acceptance for charginos produced in the electroweak channel as a function of the chargino $eta$ and chargino decay radius (at generator level).
The generator-level acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
The acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos produced in the electroweak channel as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
The acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos produced in the electroweak channel as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
The acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos produced in the electroweak channel as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
The acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos produced in the electroweak channel as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
The generator-level acceptance after reconstruction, for selecting and reconstructing charginos as a function of the chargino $\eta$ and chargino decay radius (at generator level).
The generator-level acceptance for charginos produced in the strong channel as a function of the chargino $\eta$ and chargino decay radius (at generator level).
The generator-level acceptance for charginos produced in the strong channel as a function of the chargino $\eta$ and chargino decay radius (at generator level).
The generator-level acceptance for charginos produced in the strong channel as a function of the chargino $\eta$ and chargino decay radius (at generator level).
The generator-level acceptance for charginos produced in the strong channel as a function of the chargino $\eta$ and chargino decay radius (at generator level).
The generator-level acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
The acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos produced in the strong channel as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
The acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos produced in the strong channel as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
The acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos produced in the strong channel as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
The acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos produced in the strong channel as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in direct electroweak production with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in direct electroweak production with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in direct electroweak production with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in direct electroweak production with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in direct electroweak production with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in the strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in the strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in the strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in the strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in the strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
The event and tracklet generator-level acceptance and selection efficiency for a few electroweak signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
The event and tracklet generator-level acceptance and selection efficiency for a few electroweak signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
The event and tracklet generator-level acceptance and selection efficiency for a few electroweak signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
The event and tracklet generator-level acceptance and selection efficiency for a few electroweak signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
The event and tracklet generator-level acceptance and selection efficiency for a few electroweak signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
The event and tracklet generator-level acceptance and selection efficiency for a few strong signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
The event and tracklet generator-level acceptance and selection efficiency for a few strong signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
The event and tracklet generator-level acceptance and selection efficiency for a few strong signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
The event and tracklet generator-level acceptance and selection efficiency for a few strong signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
The event and tracklet generator-level acceptance and selection efficiency for a few strong signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
Systematic uncertainties in the signal event yields at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. The uncertainty in the cross-section of the strong production is large due to the large effect from the PDF uncertainty.
Systematic uncertainties in the signal event yields at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. The uncertainty in the cross-section of the strong production is large due to the large effect from the PDF uncertainty.
Systematic uncertainties in the signal event yields at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. The uncertainty in the cross-section of the strong production is large due to the large effect from the PDF uncertainty.
Systematic uncertainties in the signal event yields at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. The uncertainty in the cross-section of the strong production is large due to the large effect from the PDF uncertainty.
Systematic uncertainties in the signal event yields at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. The uncertainty in the cross-section of the strong production is large due to the large effect from the PDF uncertainty.
Observed events, expected background for null signal, and expected signal yields for two benchmark models: electroweak channel with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) and strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. Also shown are the probability of a background-only experiment being more signal-like than observed ($p_0$) and the upper limit on the model-independent visible cross-section at 95\% CL. The uncertainty in the total background yield is different from the sum of uncertainties in quadrature due to anticorrelation between different backgrounds.
Observed events, expected background for null signal, and expected signal yields for two benchmark models: electroweak channel with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) and strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. Also shown are the probability of a background-only experiment being more signal-like than observed ($p_0$) and the upper limit on the model-independent visible cross-section at 95\% CL. The uncertainty in the total background yield is different from the sum of uncertainties in quadrature due to anti-correlation between different backgrounds.
Observed events, expected background for null signal, and expected signal yields for two benchmark models: electroweak channel with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) and strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. Also shown are the probability of a background-only experiment being more signal-like than observed ($p_0$) and the upper limit on the model-independent visible cross-section at 95\% CL. The uncertainty in the total background yield is different from the sum of uncertainties in quadrature due to anti-correlation between different backgrounds.
Observed events, expected background for null signal, and expected signal yields for two benchmark models: electroweak channel with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) and strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. Also shown are the probability of a background-only experiment being more signal-like than observed ($p_0$) and the upper limit on the model-independent visible cross-section at 95\% CL. The uncertainty in the total background yield is different from the sum of uncertainties in quadrature due to anti-correlation between different backgrounds.
Observed events, expected background for null signal, and expected signal yields for two benchmark models: electroweak channel with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) and strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. Also shown are the probability of a background-only experiment being more signal-like than observed ($p_0$) and the upper limit on the model-independent visible cross-section at 95\% CL. The uncertainty in the total background yield is different from the sum of uncertainties in quadrature due to anti-correlation between different backgrounds.
Effects of systematic uncertainties on the signal exclusion significance at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. Effects of uncertainties on the fake-tracklet background is smaller in the strong channel analysis because the estimated number of the fake-tracket background events is small.
Effects of systematic uncertainties on the signal exclusion significance at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. Effects of uncertainties on the fake-tracklet background is smaller in the strong channel analysis because the estimated number of the fake-tracklet background events is small.
Effects of systematic uncertainties on the signal exclusion significance at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. Effects of uncertainties on the fake-tracklet background is smaller in the strong channel analysis because the estimated number of the fake-tracklet background events is small.
Effects of systematic uncertainties on the signal exclusion significance at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. Effects of uncertainties on the fake-tracklet background is smaller in the strong channel analysis because the estimated number of the fake-tracklet background events is small.
Effects of systematic uncertainties on the signal exclusion significance at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. Effects of uncertainties on the fake-tracklet background is smaller in the strong channel analysis because the estimated number of the fake-tracklet background events is small.
Cross-section upper limits for the strong production, presented in unit of fb. Left-upper triangle region is unphysical because the wino mass is larger than the gluino mass.
Cross-section upper limits for the strong production, presented in unit of fb. Left-upper triangle region is unphysical because the wino mass is larger than the gluino mass.
Cross-section upper limits for the strong production, presented in unit of fb. Left-upper triangle region is unphysical because the wino mass is larger than the gluino mass.
Cross-section upper limits for the strong production, presented in unit of fb. Left-upper triangle region is unphysical because the wino mass is larger than the gluino mass.
Cross-section upper limits for the strong production, presented in unit of fb. Left-upper triangle region is unphysical because the wino mass is larger than the gluino mass.
A search for a new heavy particle decaying to a pair of vector bosons (WW or WZ) is presented using data from the CMS detector corresponding to an integrated luminosity of 35.9 fb$^{-1}$ collected in proton-proton collisions at a centre-of-mass energy of 13 TeV in 2016. One of the bosons is required to be a W boson decaying to e$\nu$ or $\mu\nu$, while the other boson is required to be reconstructed as a single massive jet with substructure compatible with that of a highly-energetic quark pair from a W or Z boson decay. The search is performed in the resonance mass range between 1.0 and 4.5 TeV. The largest deviation from the background-only hypothesis is observed for a mass near 1.4 TeV and corresponds to a local significance of 2.5 standard deviations. The result is interpreted as an upper bound on the resonance production cross section. Comparing the excluded cross section values and the expectations from theoretical calculations in the bulk graviton and heavy vector triplet models, spin-2 WW resonances with mass smaller than 1.07 TeV and spin-1 WZ resonances lighter than 3.05 TeV, respectively, are excluded at 95% confidence level.
Exclusion limits on the product of the production cross section and the branching fraction for a new spin-2 resonance decaying to WW, as a function of the resonance mass hypothesis.
Exclusion limits on the product of the production cross section and the branching fraction for a new spin-1 resonance decaying to WZ, as a function of the resonance mass hypothesis.
Signal selection efficiency times acceptance as a function of resonance mass for a spin-2 bulk graviton decaying to WW and a spin-1 W' decaying to WZ.
A search for supersymmetry in events with large missing transverse momentum, jets, and at least one hadronically decaying $\tau$-lepton is presented. Two exclusive final states with either exactly one or at least two $\tau$-leptons are considered. The analysis is based on proton-proton collisions at $\sqrt{s}$ = 13 TeV corresponding to an integrated luminosity of 36.1 fb$^{-1}$ delivered by the Large Hadron Collider and recorded by the ATLAS detector in 2015 and 2016. No significant excess is observed over the Standard Model expectation. At 95% confidence level, model-independent upper limits on the cross section are set and exclusion limits are provided for two signal scenarios: a simplified model of gluino pair production with $\tau$-rich cascade decays, and a model with gauge-mediated supersymmetry breaking (GMSB). In the simplified model, gluino masses up to 2000 GeV are excluded for low values of the mass of the lightest supersymmetric particle (LSP), while LSP masses up to 1000 GeV are excluded for gluino masses around 1400 GeV. In the GMSB model, values of the supersymmetry-breaking scale are excluded below 110 TeV for all values of $\tan\beta$ in the range $2 \leq \tan\beta \leq 60$, and below 120 TeV for $\tan\beta>30$.
1$\tau$ Compressed SR eff.
1$\tau$ Compressed SR eff.
1$\tau$ MediumMass SR eff.
1$\tau$ MediumMass SR eff.
2$\tau$ Compressed SR eff.
2$\tau$ Compressed SR eff.
2$\tau$ HighMass SR eff.
2$\tau$ HighMass SR eff.
2$\tau$ multibin SR eff.
2$\tau$ multibin SR eff.
2$\tau$ GMSB SR eff.
2$\tau$ GMSB SR eff.
1$\tau$ Compressed SR eff.
1$\tau$ Compressed SR eff.
1$\tau$ MediumMass SR eff.
1$\tau$ MediumMass SR eff.
2$\tau$ Compressed SR eff.
2$\tau$ Compressed SR eff.
2$\tau$ HighMass SR eff.
2$\tau$ HighMass SR eff.
2$\tau$ multibin SR eff.
2$\tau$ multibin SR eff.
2$\tau$ GMSB SR eff.
2$\tau$ GMSB SR eff.
1$\tau$ Compressed SR acceptance.
1$\tau$ Compressed SR acceptance.
1$\tau$ MediumMass SR acceptance.
1$\tau$ MediumMass SR acceptance.
2$\tau$ Compressed SR acceptance.
2$\tau$ Compressed SR acceptance.
2$\tau$ HighMass SR acceptance.
2$\tau$ HighMass SR acceptance.
2$\tau$ multibin SR acceptance.
2$\tau$ multibin SR acceptance.
2$\tau$ GMSB SR acceptance.
2$\tau$ GMSB SR acceptance.
1$\tau$ Compressed SR acceptance.
1$\tau$ Compressed SR acceptance.
1$\tau$ MediumMass SR acceptance.
1$\tau$ MediumMass SR acceptance.
2$\tau$ Compressed SR acceptance.
2$\tau$ Compressed SR acceptance.
2$\tau$ HighMass SR acceptance.
2$\tau$ HighMass SR acceptance.
2$\tau$ multibin SR acceptance.
2$\tau$ multibin SR acceptance.
2$\tau$ GMSB SR acceptance.
2$\tau$ GMSB SR acceptance.
Cutflow table of the $1\tau$ compressed SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.
Cutflow table of the $1\tau$ compressed SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.
Cutflow table of the $1\tau$ medium-mass SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.
Cutflow table of the $1\tau$ medium-mass SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.
Cutflow table of the $2\tau$ compressed SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.
Cutflow table of the $2\tau$ compressed SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.
Cutflow table of the $2\tau$ high-mass SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.
Cutflow table of the $2\tau$ high-mass SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.
Cutflow table of the $2\tau$ multibin SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.
Cutflow table of the $2\tau$ multibin SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.
Cutflow table of the $2\tau$ GMSB SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.
Cutflow table of the $2\tau$ GMSB SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.
Best performing fit setups entering the final combination as a function of the LSP mass and the gluino mass. 'S' marks the simultaneous fit of the four simplified model single-bin SRs, 'M' denotes the simultaneous fit of the two $1\tau$ SRs and the $2\tau$ multibin SR.
Best performing fit setups entering the final combination as a function of the LSP mass and the gluino mass. 'S' marks the simultaneous fit of the four simplified model single-bin SRs, 'M' denotes the simultaneous fit of the two $1\tau$ SRs and the $2\tau$ multibin SR.
Observed exclusion contour at 95% CL as a function of tanBeta and the SUSY-breaking mass scale Lambda.
Observed exclusion contour at 95% CL as a function of tanBeta and the SUSY-breaking mass scale Lambda.
Expected exclusion contour at 95% CL as a function of tanBeta and the SUSY-breaking mass scale Lambda.
Expected exclusion contour at 95% CL as a function of tanBeta and the SUSY-breaking mass scale Lambda.
Observed exclusion contour at 95% CL as a function of the LSP mass and the gluino mass.
Observed exclusion contour at 95% CL as a function of the LSP mass and the gluino mass.
Expected exclusion contour at 95% CL as a function of the LSP mass and the gluino mass.
Expected exclusion contour at 95% CL as a function of the LSP mass and the gluino mass.
Observed upper limits on the production cross section at 95% CL in pb as a function of tanBeta and SUSY breaking mass scale Lambda.
Observed upper limits on the production cross section at 95% CL in pb as a function of tanBeta and SUSY breaking mass scale Lambda.
Observed upper limits on the production cross section at 95% CL in pb as a function of the LSP mass and the gluino mass.
Observed upper limits on the production cross section at 95% CL in pb as a function of the LSP mass and the gluino mass.
Yields of the expected background from the SM in the bins of the multibin SR of the $2\tau$ channel with all bins being simultaneously used to constrain the background prediction. Expectation is given with the scalings computed in the combined fit applied. Uncertainties are statistial plus systematrics. Only the subsamples contributing the respective region are considered.
Yields of the expected background from the SM in the bins of the multibin SR of the $2\tau$ channel with all bins being simultaneously used to constrain the background prediction. Expectation is given with the scalings computed in the combined fit applied. Uncertainties are statistial plus systematrics. Only the subsamples contributing the respective region are considered.
$m_{\mathrm{T}}^{\tau}$ in the compressed $m_{\mathrm{T}}^{\tau}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$m_{\mathrm{T}}^{\tau}$ in the compressed $m_{\mathrm{T}}^{\tau}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$E_{\mathrm{T}}^{\mathrm{miss}}$ in the compressed $E_{\mathrm{T}}^{\mathrm{miss}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$E_{\mathrm{T}}^{\mathrm{miss}}$ in the compressed $E_{\mathrm{T}}^{\mathrm{miss}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$m_{\mathrm{T}}^{\tau}$ in the medium-mass $m_{\mathrm{T}}^{\tau}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$m_{\mathrm{T}}^{\tau}$ in the medium-mass $m_{\mathrm{T}}^{\tau}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$E_{\mathrm{T}}^{\mathrm{miss}}$ in the medium-mass $E_{\mathrm{T}}^{\mathrm{miss}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$E_{\mathrm{T}}^{\mathrm{miss}}$ in the medium-mass $E_{\mathrm{T}}^{\mathrm{miss}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$H_{\mathrm{T}}$ in the medium-mass $H_{\mathrm{T}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$H_{\mathrm{T}}$ in the medium-mass $H_{\mathrm{T}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$m_{\mathrm{T}}^{\tau_1}$ + $m_{\mathrm{T}}^{\tau_2}$ in the top VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$m_{\mathrm{T}}^{\tau_1}$ + $m_{\mathrm{T}}^{\tau_2}$ in the top VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$H_{\mathrm{T}}$ in the $W$ VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$H_{\mathrm{T}}$ in the $W$ VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$m_{\mathrm{T}}^{\tau_1}$ + $m_{\mathrm{T}}^{\tau_2}$ in the $Z$ VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$m_{\mathrm{T}}^{\tau_1}$ + $m_{\mathrm{T}}^{\tau_2}$ in the $Z$ VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$m_{\mathrm{T}}^{\tau}$ in the compressed SR of the $1\tau$ channel before application of the $m_{\mathrm{T}}^{\tau}$ > 80 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.
$m_{\mathrm{T}}^{\tau}$ in the compressed SR of the $1\tau$ channel before application of the $m_{\mathrm{T}}^{\tau}$ > 80 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.
$H_{\mathrm{T}}$ in the medium-mass SR of the $1\tau$ channel before application of the $H_{\mathrm{T}}$ > 1000 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.
$H_{\mathrm{T}}$ in the medium-mass SR of the $1\tau$ channel before application of the $H_{\mathrm{T}}$ > 1000 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.
$m_{\mathrm{T}}^{\mathrm{sum}}$ in the compressed SR of the $2\tau$ channel before application of the $m_{\mathrm{T}}^{\mathrm{sum}}$ > 1600 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.
$m_{\mathrm{T}}^{\mathrm{sum}}$ in the compressed SR of the $2\tau$ channel before application of the $m_{\mathrm{T}}^{\mathrm{sum}}$ > 1600 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.
$H_{\mathrm{T}}$ in the high-mass SR of the $2\tau$ channel before application of the $H_{\mathrm{T}}$ > 1100 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.
$H_{\mathrm{T}}$ in the high-mass SR of the $2\tau$ channel before application of the $H_{\mathrm{T}}$ > 1100 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.
mT(tau_1) + mT(tau_2) in the multibin SR of the 2T channel. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.
mT(tau_1) + mT(tau_2) in the multibin SR of the 2T channel. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.
$H_{\mathrm{T}}$ in the GMSB SR of the $2\tau$ channel before application of the $H_{\mathrm{T}}$ > 1900 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.
$H_{\mathrm{T}}$ in the GMSB SR of the $2\tau$ channel before application of the $H_{\mathrm{T}}$ > 1900 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.
A search is performed for events consistent with the pair production of a new heavy particle that acts as a mediator between a dark sector and normal matter, and that decays to a light quark and a new fermion called a dark quark. The search is based on data corresponding to an integrated luminosity of 16.1 fb$^{-1}$ from proton-proton collisions at $\sqrt{s} =$ 13 TeV collected by the CMS experiment at the LHC in 2016. The dark quark is charged only under a new quantum-chromodynamics-like force, and forms an "emerging jet" via a parton shower, containing long-lived dark hadrons that give rise to displaced vertices when decaying to standard model hadrons. The data are consistent with the expectation from standard model processes. Limits are set at 95% confidence level excluding dark pion decay lengths between 5 and 225 mm for dark mediators with masses between 400 and 1250 GeV. Decay lengths smaller than 5 mm and greater than 225 mm are also excluded in the lower part of this mass range. The dependence of the limit on the dark pion mass is weak for masses between 1 and 10 GeV. This analysis is the first dedicated search for the pair production of a new particle that decays to a jet and an emerging jet.
Distributions of $\langle IP_{\mathrm{2D}}\rangle$ for background (black) and for signals with a mediator mass of 1 TeV and a dark pion proper decay length of 25 mm, for various dark pion masses.
Distributions of $\alpha_\mathrm{3D}$ for background (black) and for signals with a mediator mass of 1 TeV and a dark pion mass of 5 GeV for dark pion proper decay lengths ranging from 1 to 300 mm.
The signal acceptance A, defined as the fraction of simulated signal events passing the selection criteria, for models with a dark pion mass $m_{\pi_\mathrm{DK}}$ of 5 GeV as a function of the mediator mass $m_{\mathrm{X_{DK}}}$ and the dark pion proper decay length $c\tau_{\pi_\mathrm{DK}}$. The corresponding selection set number for each model is indicated as text on the plot.
Measured misidentification probability distribution as a function of track multiplicity for the EMJ-1 criteria group defined in Table 2. The red up-pointing triangles are for b jets while the blue down-pointing triangles are for light-flavor jets. The horizontal lines on the data points indicate the variable bin width.
The $H_\mathrm{T}$ distribution for the observed data events (black points) and the predicted background estimation (blue) for selection set 8 (SM QCD-enhanced), requiring at least two jets tagged by loose emerging jet criteria.
The number of associated tracks distribution for the observed data events (black points) and the predicted background estimation (blue) for selection set 8 (SM QCD-enhanced), requiring at least two jets tagged by loose emerging jet criteria.
The $H_\mathrm{T}$ distribution for the observed data events (black points) and the predicted background estimation (blue) for selection set 9 (SM QCD-enhanced), requiring at least one jet tagged by loose emerging jet criteria and large $p_\mathrm{T}^\mathrm{miss}$.
The number of associated tracks distribution for the observed data events (black points) and the predicted background estimation (blue) for selection set 9 (SM QCD-enhanced), requiring at least one jet tagged by loose emerging jet criteria and large $p_\mathrm{T}^\mathrm{miss}$.
Upper limits at 95% CL on the signal cross section for models with dark pion mass $(m_{\pi_\mathrm{DK}})$ of 5 GeV in the proper decay length $(c\tau_{\pi_\mathrm{DK}})$ versus dark mediator mass $(m_{\mathrm{X_{DK}}})$ plane.
Dark mediator mass exclusion limits at 95% CL derived from theoretical cross sections for models with dark pion mass $(m_{\pi_\mathrm{DK}})$ of 5 GeV in the proper decay length $(c\tau_{\pi_\mathrm{DK}})$ versus dark mediator mass $(m_{\mathrm{X_{DK}}})$ plane.
A search for heavy charged long-lived particles is performed using a data sample of 36.1 fb$^{-1}$ of proton-proton collisions at $\sqrt{s} = 13$ TeV collected by the ATLAS experiment at the Large Hadron Collider. The search is based on observables related to ionization energy loss and time of flight, which are sensitive to the velocity of heavy charged particles traveling significantly slower than the speed of light. Multiple search strategies for a wide range of lifetimes, corresponding to path lengths of a few meters, are defined as model-independently as possible, by referencing several representative physics cases that yield long-lived particles within supersymmetric models, such as gluinos/squarks ($R$-hadrons), charginos and staus. No significant deviations from the expected Standard Model background are observed. Upper limits at 95% confidence level are provided on the production cross sections of long-lived $R$-hadrons as well as directly pair-produced staus and charginos. These results translate into lower limits on the masses of long-lived gluino, sbottom and stop $R$-hadrons, as well as staus and charginos of 2000 GeV, 1250 GeV, 1340 GeV, 430 GeV and 1090 GeV, respectively.
- - - - - - - - Overview of HEPData Record - - - - - - - - <br/><br/> <b>Lower mass requirement for signal regions.</b> <ul> <li><a href="86565?version=1&table=Table1">Gluinos and squarks</a></li> <li><a href="86565?version=1&table=Table2">Staus and charginos</a></li> </ul> <b>Discovery regions:</b> <ul> <li><a href="86565?version=1&table=Table3">Yields</a></li> <li><a href="86565?version=1&table=Table6">p0-values and limits</a></li> </ul> <b>Signal yield tables:</b> <ul> <li><a href="86565?version=1&table=Table4">MS-agnostic R-hadron search</a></li> <li><a href="86565?version=1&table=Table5">Full-detector R-hadron search</a></li> <li><a href="86565?version=1&table=Table7">MS-agnostic search for metastable gluino R-hadrons</a></li> <li><a href="86565?version=1&table=Table8">Full-detector direct-stau search</a></li> <li><a href="86565?version=1&table=Table9">Full-detector chargino search</a></li> </ul> <b>Limits:</b> <ul> <li><a href="86565?version=1&table=Table10">Gluino R-hadron search</a></li> <li><a href="86565?version=1&table=Table11">Sbottom R-hadron search</a></li> <li><a href="86565?version=1&table=Table12">Stop R-hadron search</a></li> <li><a href="86565?version=1&table=Table13">Stau search</a></li> <li><a href="86565?version=1&table=Table14">Chargino search</a></li> <li><a href="86565?version=1&table=Table15">Meta-stable gluino R-hadron search</a></li> <li><a href="86565?version=1&table=Table17">Meta-stable gluino R-hadron search</a></li> </ul> <b>Acceptance and efficiency:</b> <ul> <li><a href="86565?version=1&table=Table16">MS-agnostic R-hadron search</a></li> </ul> <b>Truth quantities:</b> <ul> <li><a href="86565?version=1&table=Table18">Flavor composition of 800 GeV stop R-hadrons simulated using the generic model</a></li> <li><a href="86565?version=1&table=Table19">Flavor composition of 800 GeV anti-stop R-hadrons simulated using the generic model</a></li> <li><a href="86565?version=1&table=Table20">Flavor composition of 800 GeV stop R-hadrons simulated using the Regge model</a></li> <li><a href="86565?version=1&table=Table21">Flavor composition of 800 GeV anti-stop R-hadrons simulated using the Regge model</a></li> </ul> <b>Reinterpretation material:</b> <ul> <li><a href="86565?version=1&table=Table22">ETmiss trigger efficiency as function of true ETmiss</a></li> <li><a href="86565?version=1&table=Table23">Single-muon trigger efficiency as function of |eta| and beta</a></li> <li><a href="86565?version=1&table=Table24">Candidate reconstruction efficiency for ID+Calo selection</a></li> <li><a href="86565?version=1&table=Table25">Candidate reconstruction efficiency for loose selection</a></li> <li><a href="86565?version=1&table=Table26">Efficiency for a loose candidate to be promoted to a tight candidate</a></li> <li><a href="86565?version=1&table=Table27">Resolution and average of reconstructed dE/dx mass for a given simulated mass for ID+calo candidates</a></li> <li><a href="86565?version=1&table=Table28">Resolution and average of reconstructed ToF mass for a given simulated mass for ID+calo candidates</a></li> <li><a href="86565?version=1&table=Table29">Resolution and average of reconstructed ToF mass for a given simulated mass for FullDet candidates</a></li> </ul> <p><b>Pseudo-code snippets</b> and <b>example SLHA setups</b> are available in the "Resources" linked on the left, and more detailed reinterpretation material is available at <a href="http://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/SUSY-2016-32/hepdata_info.pdf">http://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/SUSY-2016-32/hepdata_info.pdf</a>.</p>
- - - - - - - - Overview of HEPData Record - - - - - - - - <br/><br/> <b>Lower mass requirement for signal regions.</b> <ul> <li><a href="86565?version=1&table=Table1">Gluinos and squarks</a></li> <li><a href="86565?version=1&table=Table2">Staus and charginos</a></li> </ul> <b>Discovery regions:</b> <ul> <li><a href="86565?version=1&table=Table3">Yields</a></li> <li><a href="86565?version=1&table=Table6">p0-values and limits</a></li> </ul> <b>Signal yield tables:</b> <ul> <li><a href="86565?version=1&table=Table4">MS-agnostic R-hadron search</a></li> <li><a href="86565?version=1&table=Table5">Full-detector R-hadron search</a></li> <li><a href="86565?version=1&table=Table7">MS-agnostic search for metastable gluino R-hadrons</a></li> <li><a href="86565?version=1&table=Table8">Full-detector direct-stau search</a></li> <li><a href="86565?version=1&table=Table9">Full-detector chargino search</a></li> </ul> <b>Limits:</b> <ul> <li><a href="86565?version=1&table=Table10">Gluino R-hadron search</a></li> <li><a href="86565?version=1&table=Table11">Sbottom R-hadron search</a></li> <li><a href="86565?version=1&table=Table12">Stop R-hadron search</a></li> <li><a href="86565?version=1&table=Table13">Stau search</a></li> <li><a href="86565?version=1&table=Table14">Chargino search</a></li> <li><a href="86565?version=1&table=Table15">Meta-stable gluino R-hadron search</a></li> <li><a href="86565?version=1&table=Table17">Meta-stable gluino R-hadron search</a></li> </ul> <b>Acceptance and efficiency:</b> <ul> <li><a href="86565?version=1&table=Table16">MS-agnostic R-hadron search</a></li> </ul> <b>Truth quantities:</b> <ul> <li><a href="86565?version=1&table=Table18">Flavor composition of 800 GeV stop R-hadrons simulated using the generic model</a></li> <li><a href="86565?version=1&table=Table19">Flavor composition of 800 GeV anti-stop R-hadrons simulated using the generic model</a></li> <li><a href="86565?version=1&table=Table20">Flavor composition of 800 GeV stop R-hadrons simulated using the Regge model</a></li> <li><a href="86565?version=1&table=Table21">Flavor composition of 800 GeV anti-stop R-hadrons simulated using the Regge model</a></li> </ul> <b>Reinterpretation material:</b> <ul> <li><a href="86565?version=1&table=Table22">ETmiss trigger efficiency as function of true ETmiss</a></li> <li><a href="86565?version=1&table=Table23">Single-muon trigger efficiency as function of |eta| and beta</a></li> <li><a href="86565?version=1&table=Table24">Candidate reconstruction efficiency for ID+Calo selection</a></li> <li><a href="86565?version=1&table=Table25">Candidate reconstruction efficiency for loose selection</a></li> <li><a href="86565?version=1&table=Table26">Efficiency for a loose candidate to be promoted to a tight candidate</a></li> <li><a href="86565?version=1&table=Table27">Resolution and average of reconstructed dE/dx mass for a given simulated mass for ID+calo candidates</a></li> <li><a href="86565?version=1&table=Table28">Resolution and average of reconstructed ToF mass for a given simulated mass for ID+calo candidates</a></li> <li><a href="86565?version=1&table=Table29">Resolution and average of reconstructed ToF mass for a given simulated mass for FullDet candidates</a></li> </ul> <p><b>Pseudo-code snippets</b> and <b>example SLHA setups</b> are available in the "Resources" linked on the left, and more detailed reinterpretation material is available at <a href="http://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/SUSY-2016-32/hepdata_info.pdf">http://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/SUSY-2016-32/hepdata_info.pdf</a>.</p>
Lower mass requirement for signal regions.
Lower mass requirement for signal regions.
Lower mass requirement for signal regions.
Lower mass requirement for signal regions.
Expected and observed events in the 16 discovery regions along with the according control regions.
Expected and observed events in the 16 discovery regions along with the according control regions.
Expected signal yield and acceptance x efficiency, estimated background and observed number of events in data for the full range of simulated masses in the MS-agnostic R-hadron search.
Expected signal yield and acceptance x efficiency, estimated background and observed number of events in data for the full range of simulated masses in the MS-agnostic R-hadron search.
Expected signal yield and acceptance x efficiency, estimated background and observed number of events in data for the full range of simulated masses in the full-detector R-hadron search.
Expected signal yield and acceptance x efficiency, estimated background and observed number of events in data for the full range of simulated masses in the full-detector R-hadron search.
p0-values and model-independent upper limits on cross-section x acceptance x efficiency for the 16 discovery regions.
p0-values and model-independent upper limits on cross-section x acceptance x efficiency for the 16 discovery regions.
Expected signal yield and acceptance x efficiency, estimated background and observed number of events in data for the full range of simulated masses in the MS-agnostic search for metastable gluino R-hadrons.
Expected signal yield and acceptance x efficiency, estimated background and observed number of events in data for the full range of simulated masses in the MS-agnostic search for metastable gluino R-hadrons.
Expected signal yield and acceptance x efficiency, estimated background and observed number of events in data for the full range of simulated masses in the full-detector direct-stau search.
Expected signal yield and acceptance x efficiency, estimated background and observed number of events in data for the full range of simulated masses in the full-detector direct-stau search.
Expected signal yield and acceptance x efficiency, estimated background and observed number of events in data for the full range of simulated masses in the full-detector chargino search.
Expected signal yield and acceptance x efficiency, estimated background and observed number of events in data for the full range of simulated masses in the full-detector chargino search.
Upper cross-section limit in gluino R-hadron search.
Upper cross-section limit in gluino R-hadron search.
Upper cross-section limit in sbottom R-hadron search.
Upper cross-section limit in sbottom R-hadron search.
Upper cross-section limit in stop R-hadron search.
Upper cross-section limit in stop R-hadron search.
Upper cross-section limit in stau search.
Upper cross-section limit in stau search.
Upper cross-section limit in chargino search.
Upper cross-section limit in chargino search.
Lower mass limit as function of gluino lifetime.
Lower mass limit as function of gluino lifetime.
Acceptance x efficiency, acceptance and efficiency for the full range of simulated masses in the MS-agnostic R-hadron search.
Acceptance x efficiency, acceptance and efficiency for the full range of simulated masses in the MS-agnostic R-hadron search.
Upper cross-section limit in meta-stable gluino R-hadron search.
Upper cross-section limit in meta-stable gluino R-hadron search.
Flavor composition of 800 GeV stop R-hadrons simulated using the generic model as a function of radial distance from the interaction point.
Flavor composition of 800 GeV stop R-hadrons simulated using the generic model as a function of radial distance from the interaction point.
Flavor composition of 800 GeV anti-stop R-hadrons simulated using the generic model as a function of radial distance from the interaction point.
Flavor composition of 800 GeV anti-stop R-hadrons simulated using the generic model as a function of radial distance from the interaction point.
Flavor composition of 800 GeV stop R-hadrons simulated using the Regge model as a function of radial distance from the interaction point.
Flavor composition of 800 GeV stop R-hadrons simulated using the Regge model as a function of radial distance from the interaction point.
Flavor composition of 800 GeV anti-stop R-hadrons simulated using the Regge model as a function of radial distance from the interaction point.
Flavor composition of 800 GeV anti-stop R-hadrons simulated using the Regge model as a function of radial distance from the interaction point.
ETmiss trigger efficiency as function of true ETmiss (EtmissTurnOn).
ETmiss trigger efficiency as function of true ETmiss (EtmissTurnOn).
Single-muon trigger efficiency as function of $|\eta|$ and $\beta$ (SingleMuTurnOn).
Single-muon trigger efficiency as function of $|\eta|$ and $\beta$ (SingleMuTurnOn).
Candidate reconstruction efficiency for ID+Calo selection (IDCaloEff).
Candidate reconstruction efficiency for ID+Calo selection (IDCaloEff).
Candidate reconstruction efficiency for loose selection (LooseEff).
Candidate reconstruction efficiency for loose selection (LooseEff).
Efficiency for a loose candidate to be promoted to a tight candidate (TightPromotionEff).
Efficiency for a loose candidate to be promoted to a tight candidate (TightPromotionEff).
Resolution and average of reconstructed dE/dx mass for a given simulated mass for ID+calo candidates.
Resolution and average of reconstructed dE/dx mass for a given simulated mass for ID+calo candidates.
Resolution and average of reconstructed ToF mass for a given simulated mass for ID+calo candidates.
Resolution and average of reconstructed ToF mass for a given simulated mass for ID+calo candidates.
Resolution and average of reconstructed ToF mass for a given simulated mass for FullDet candidates.
Resolution and average of reconstructed ToF mass for a given simulated mass for FullDet candidates.
A general search is presented for a low-mass $\tau^-\tau^+$ resonance produced in association with a bottom quark. The search is based on proton-proton collision data at a center-of-mass energy of 13 TeV collected by the CMS experiment at the LHC, corresponding to an integrated luminosity of 35.9 fb$^{-1}$. The data are consistent with the standard model expectation. Upper limits at 95% confidence level on the cross section times branching fraction are determined for two signal models: a light pseudoscalar Higgs boson decaying to a pair of $\tau$ leptons produced in association with bottom quarks, and a low-mass boson X decaying to a $\tau$-lepton pair that is produced in the decay of a bottom-like quark B such that B $\to$ bX. Masses between 25 and 70 GeV are probed for the light pseudoscalar boson with upper limits ranging from 250 to 44 pb. Upper limits from 20 to 0.3 pb are set on B masses between 170 and 450 GeV for X boson masses between 20 and 70 GeV.
The product of acceptance, efficiency, and branching fraction of $\mathrm{b}\overline{\mathrm{b}}\mathrm{A}$ production with $\mathrm{A} \rightarrow \tau\tau$ in the $\mathrm{e}\tau_\mathrm{h}$ and $\mu\tau_\mathrm{h}$ channels of the 1 b tag event category, as a function of the pseudoscalar mass. The selections are as described in the paper. The uncertainty refers to the statistical uncertainty only.
Observed $m_{\tau\tau}$ distribution in the $\mathrm{e}\tau_\mathrm{h}$ channel of the 1 b tag category, compared to the expected SM background contributions. The signal distributions for $\mathrm{b}\overline{\mathrm{b}}\mathrm{A}$ production with pseudoscalar mass 40 and 60 GeV are overlaid to illustrate the sensitivity. They are normalized to the cross section times branching fraction of 800 pb. The uncertainty band represents the sum in quadrature of statistical and systematic uncertainties obtained from the fit. The lower panel shows the ratio between the observed and expected events in each bin.
Observed $m_{\tau\tau}$ distribution in the $\mu\tau_\mathrm{h}$ channel of the 1 b tag category, compared to the expected SM background contributions. The signal distributions for $\mathrm{b}\overline{\mathrm{b}}\mathrm{A}$ production with pseudoscalar mass 40 and 60 GeV are overlaid to illustrate the sensitivity. They are normalized to the cross section times branching fraction of 800 pb. The uncertainty band represents the sum in quadrature of statistical and systematic uncertainties obtained from the fit. The lower panel shows the ratio between the observed and expected events in each bin.
Observed (black solid) and expected (black dotted) limits at 95% confidence level on the product of the the cross section for bbA prodcution and the branching fraction $\mathrm{A} \rightarrow \tau\tau$, obtained from the combination of the $\mathrm{e}\tau_\mathrm{h}$ and $\mu\tau_\mathrm{h}$ channels in the 1 b tag category, as a function of the A boson mass. The green and yellow bands represent the one and two standard deviation uncertainties in the expected limits.
Observed (black solid) and expected (black dotted) limits at 95% confidence level on the product of the the cross section for bbA prodcution and the branching fraction $\mathrm{A} \rightarrow \tau\tau$, obtained in the $\mathrm{e}\tau_\mathrm{h}$ channel of the 1 b tag category, as a function of the A boson mass. The green and yellow bands represent the one and two standard deviation uncertainties in the expected limits.
Observed (black solid) and expected (black dotted) limits at 95% confidence level on the product of the the cross section for bbA prodcution and the branching fraction $\mathrm{A} \rightarrow \tau\tau$, obtained in the $\mu\tau_\mathrm{h}$ channel of the 1 b tag category, as a function of the A boson mass. The green and yellow bands represent the one and two standard deviation uncertainties in the expected limits.
The product of acceptance, efficiency, and branching fraction of the qbX signal with $\mathrm{X} \rightarrow \tau\tau$ and $m_{\mathrm{B}}=170~\mathrm{GeV}$ in $\mathrm{e}\tau_\mathrm{h}$ and $\mu\tau_\mathrm{h}$ channels of the 1b1f and 1b1c event categories, as a function of the X boson mass. The selections are as described in the paper. The uncertainty refers to the statistical uncertainty only.
Observed $m_{\tau\tau}$ distribution in the $\mathrm{e}\tau_\mathrm{h}$ channel of the 1b1f category, compared to the expected SM background contributions. The distributions of the qbX signal with $m_{\mathrm{B}}=170~\mathrm{GeV}$, and X boson mass 40 and 60 GeV are overlaid to illustrate the sensitivity. They are normalized to the cross section times branching fraction of 20 pb. The uncertainty band represents the sum in quadrature of statistical and systematic uncertainties obtained from the fit. The lower panel shows the ratio between the observed and expected events in each bin.
Observed $m_{\tau\tau}$ distribution in the $\mathrm{e}\tau_\mathrm{h}$ channel of the 1b1c category, compared to the expected SM background contributions. The distributions of the qbX signal with $m_{\mathrm{B}}=170~\mathrm{GeV}$, and X boson mass 40 and 60 GeV are overlaid to illustrate the sensitivity. They are normalized to the cross section times branching fraction of 20 pb. The uncertainty band represents the sum in quadrature of statistical and systematic uncertainties obtained from the fit. The lower panel shows the ratio between the observed and expected events in each bin.
Observed $m_{\tau\tau}$ distribution in the $\mu\tau_\mathrm{h}$ channel of the 1b1f category, compared to the expected SM background contributions. The distributions of the qbX signal with $m_{\mathrm{B}}=170~\mathrm{GeV}$, and X boson mass 40 and 60 GeV are overlaid to illustrate the sensitivity. They are normalized to the cross section times branching fraction of 20 pb. The uncertainty band represents the sum in quadrature of statistical and systematic uncertainties obtained from the fit. The lower panel shows the ratio between the observed and expected events in each bin.
Observed $m_{\tau\tau}$ distribution in the $\mu\tau_\mathrm{h}$ channel of the 1b1c category, compared to the expected SM background contributions. The distributions of the qbX signal with $m_{\mathrm{B}}=170~\mathrm{GeV}$, and X boson mass 40 and 60 GeV are overlaid to illustrate the sensitivity. They are normalized to the cross section times branching fraction of 20 pb. The uncertainty band represents the sum in quadrature of statistical and systematic uncertainties obtained from the fit. The lower panel shows the ratio between the observed and expected events in each bin.
Observed (black solid) and expected (black dotted) limits at 95% confidence level on the product of the the cross section for the prodcution of the qbX signal with mB = 170 GeV and the branching fraction $\mathrm{X} \rightarrow \tau\tau$, obtained from the combination of the $\mathrm{e}\tau_\mathrm{h}$ and $\mu\tau_\mathrm{h}$ channels, and the 1b1f and 1b1c categories, as a function of the X boson mass. The green and yellow bands represent the one and two standard deviation uncertainties in the expected limits.
Observed (black solid) and expected (black dotted) limits at 95% confidence level on the product of the the cross section for the prodcution of the qbX signal with mB = 300 GeV and the branching fraction $\mathrm{X} \rightarrow \tau\tau$, obtained from the combination of the $\mathrm{e}\tau_\mathrm{h}$ and $\mu\tau_\mathrm{h}$ channels, and the 1b1f and 1b1c categories, as a function of the X boson mass. The green and yellow bands represent the one and two standard deviation uncertainties in the expected limits.
Observed (black solid) and expected (black dotted) limits at 95% confidence level on the product of the the cross section for the prodcution of the qbX signal with mB = 450 GeV and the branching fraction $\mathrm{X} \rightarrow \tau\tau$, obtained from the combination of the $\mathrm{e}\tau_\mathrm{h}$ and $\mu\tau_\mathrm{h}$ channels, and the 1b1f and 1b1c categories, as a function of the X boson mass. The green and yellow bands represent the one and two standard deviation uncertainties in the expected limits.
Observed (black solid) and expected (black dotted) limits at 95% confidence level on the product of the the cross section for the prodcution of the qbX signal with mB = 170 GeV and the branching fraction $\mathrm{X} \rightarrow \tau\tau$, obtained in the $\mathrm{e}\tau_\mathrm{h}$ channel of the 1b1f category, as a function of the X boson mass. The green and yellow bands represent the one and two standard deviation uncertainties in the expected limits.
Observed (black solid) and expected (black dotted) limits at 95% confidence level on the product of the the cross section for the prodcution of the qbX signal with mB = 170 GeV and the branching fraction $\mathrm{X} \rightarrow \tau\tau$, obtained in the $\mathrm{e}\tau_\mathrm{h}$ channel of the 1b1c category, as a function of the X boson mass. The green and yellow bands represent the one and two standard deviation uncertainties in the expected limits.
Observed (black solid) and expected (black dotted) limits at 95% confidence level on the product of the the cross section for the prodcution of the qbX signal with mB = 170 GeV and the branching fraction $\mathrm{X} \rightarrow \tau\tau$, obtained in the $\mu\tau_\mathrm{h}$ channel of the 1b1f category, as a function of the X boson mass. The green and yellow bands represent the one and two standard deviation uncertainties in the expected limits.
Observed (black solid) and expected (black dotted) limits at 95% confidence level on the product of the the cross section for the prodcution of the qbX signal with mB = 170 GeV and the branching fraction $\mathrm{X} \rightarrow \tau\tau$, obtained in the $\mu\tau_\mathrm{h}$ channel of the 1b1c category, as a function of the X boson mass. The green and yellow bands represent the one and two standard deviation uncertainties in the expected limits.
A search for a heavy charged-boson resonance decaying into a charged lepton (electron or muon) and a neutrino is reported. A data sample of 139 fb$^{-1}$ of proton-proton collisions at $\sqrt{s} = 13$ TeV collected with the ATLAS detector at the LHC during 2015-2018 is used in the search. The observed transverse mass distribution computed from the lepton and missing transverse momenta is consistent with the distribution expected from the Standard Model, and upper limits on the cross section for $pp \to W^\prime \to \ell\nu$ are extracted ($\ell = e$ or $\mu$). These vary between 1.3 pb and 0.05 fb depending on the resonance mass in the range between 0.15 and 7.0 TeV at 95% confidence level for the electron and muon channels combined. Gauge bosons with a mass below 6.0 TeV and 5.1 TeV are excluded in the electron and muon channels, respectively, in a model with a resonance that has couplings to fermions identical to those of the Standard Model $W$ boson. Cross-section limits are also provided for resonances with several fixed $\Gamma / m$ values in the range between 1% and 15%. Model-independent limits are derived in single-bin signal regions defined by a varying minimum transverse mass threshold. The resulting visible cross-section upper limits range between 4.6 (15) pb and 22 (22) ab as the threshold increases from 130 (110) GeV to 5.1 (5.1) TeV in the electron (muon) channel.
Transverse mass distribution for events satisfying all selection criteria in the electron channel.
Transverse mass distribution for events satisfying all selection criteria in the muon channel.
Upper limits at the 95% CL on the cross section for SSM $W^\prime$ production and decay to the electron+neutrino channel as a function of the $W^\prime$ pole mass.
Upper limits at the 95% CL on the cross section for SSM $W^\prime$ production and decay to the muon+neutrino channel as a function of the $W^\prime$ pole mass.
Combined (electron and muon channels) upper limits at the 95% CL on the cross section for SSM $W^\prime$ production and decay to a single lepton generation as a function of the $W^\prime$ pole mass.
Observed upper limits at the 95% CL on the cross section for generic $W^\prime$ production and decay to the electron+neutrino channel as a function of the $W^\prime$ pole mass.
Observed upper limits at the 95% CL on the cross section for generic $W^\prime$ production and decay to the muon+neutrino channel as a function of the $W^\prime$ pole mass.
Combined (electron and muon channels) observed upper limits at the 95% CL on the cross section for generic $W^\prime$ production and decay to a single lepton generation as a function of the $W^\prime$ pole mass.
Observed upper limits at the 95% CL on the visible cross section in the electron+neutrino channel as a function of the transverse mass threshold.
Observed upper limits at the 95% CL on the visible cross section in the muon+neutrino channel as a function of the transverse mass threshold.
Product of acceptance and efficiency for the electron and muon selections as a function of the $W^\prime$ pole mass.
Expected upper limits at the 95% CL on the cross section for generic $W^\prime$ production and decay to the electron+neutrino channel as a function of the $W^\prime$ pole mass.
Expected upper limits at the 95% CL on the cross section for generic $W^\prime$ production and decay to the muon+neutrino channel as a function of the $W^\prime$ pole mass.
Combined (electron and muon channels) expected upper limits at the 95% CL on the cross section for generic $W^\prime$ production and decay to a single lepton generation as a function of the $W^\prime$ pole mass.
A search for long-lived particles decaying to displaced, nonprompt jets and missing transverse momentum is presented. The data sample corresponds to an integrated luminosity of 137 fb$^{-1}$ of proton-proton collisions at a center-of-mass energy of 13 TeV collected by the CMS experiment at the CERN LHC in 2016-2018. Candidate signal events containing nonprompt jets are identified using the timing capabilities of the CMS electromagnetic calorimeter. The results of the search are consistent with the background prediction and are interpreted using a gauge-mediated supersymmetry breaking reference model with a gluino next-to-lightest supersymmetric particle. In this model, gluino masses up to 2100, 2500, and 1900 GeV are excluded at 95% confidence level for proper decay lengths of 0.3, 1, and 100 m, respectively. These are the best limits to date for such massive gluinos with proper decay lengths greater than $\sim$0.5 m.
Summary of the estimated number of background events.
Summary of the estimated number of background events.
The timing distribution of the backgrounds predicted to contribute to the signal region, compared to those for a representative signal model. The time is defined by the jet in the event with the largest $t_{\mathrm{jet}}$ passing the relevant selection. The distributions for the major backgrounds are taken from control regions and normalized to the predictions. The observed data is shown by the black points.
The timing distribution of the background sources predicted to contribute to the signal region, compared to those for a representative signal model. The time is defined by the jet in the event with the largest $t_{\mathrm{jet}}$ passing the relevant selection. The distributions for the major backgrounds are taken from control regions and normalized to the predictions. The observed data is shown by the black points. No events are observed in data for $t_{\mathrm{jet}} > 3\,$ns (indicated with a vertical black line).
The product of the acceptance and efficiency in the $c\tau_{0}$ vs. $m_{\tilde{g}}$ plane for the GMSB model, after all requirements.
The product of the acceptance and efficiency in the $c\tau_{0}$ vs. $m_{\tilde{g}}$ plane for the GMSB model, after all requirements.
The observed upper limits at $95\%$ CL for the gluino pair production cross section in the GMSB model, shown in the plane of $m_{\tilde{g}}$ and $c\tau_{0}$. A branching fraction of $100\%$ for the gluino decay to a gluon and a gravitino is assumed.
The observed upper limits at $95\%$ CL for the gluino pair production cross section in the GMSB model, shown in the plane of $m_{\tilde{g}}$ and $c\tau_{0}$. A branching fraction of $100\%$ for the gluino decay to a gluon and a gravitino is assumed. The area below the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm 1$ standard deviation ranges. The thin black lines show the effect of the theoretical uncertainties on the signal cross section.
The observed upper limits at $95\%$ CL for the gluino pair production cross section in the GMSB model, shown in the plane of $m_{\tilde{g}}$ and $c\tau_{0}$. A branching fraction of $100\%$ for the gluino decay to a gluon and a gravitino is assumed.
The observed upper limits at $95\%$ CL for the gluino pair production cross section in the GMSB model, shown in the plane of $m_{\tilde{g}}$ and $c\tau_{0}$. A branching fraction of $100\%$ for the gluino decay to a gluon and a gravitino is assumed. The area below the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm 1$ standard deviation ranges. The thin black lines show the effect of the theoretical uncertainties on the signal cross section.
The observed and expected upper limits at $95\%$ CL on the gluino pair production cross section for a gluino GMSB model with $m_{\tilde{g}}=2400$ GeV. The one (two) standard deviation variation in the expected limit is shown in the inner green (outer yellow) band. The blue solid line shows the observed limit obtained by the CMS displaced jet search
The observed and expected upper limits at $95\%$ CL on the gluino pair production cross section for a gluino GMSB model with $m_{\tilde{g}}=2400$ GeV. The one (two) standard deviation variation in the expected limit is shown in the inner green (outer yellow) band. The blue solid line shows the observed limit obtained by the CMS displaced jet search
The distribution (normalized to unity) of number of ECAL cells hit in the jet for jets in a background enriched data sample (satisfying $|\eta| < 1.48$, $PV_{\rm track}^{\rm fraction} > 1/12$, $\mathrm{HEF} > 0.2$, $t_{\mathrm{jet}} < -3\,\mathrm{ns}$ and $E^{\mathrm{CSC}}_\mathrm{ECAL}/E_{\mathrm{ECAL}} < 0.8$) and for signal jets satisfying signal region requirements (except those on $E_{\mathrm{ECAL}}$ and $N^{\mathrm{cell}}_{\mathrm{ECAL}}$).
The distribution (normalized to unity) of number of ECAL cells hit in the jet for jets in a background enriched data sample (satisfying $|\eta| < 1.48$, $p_\mathrm{T}tf > 0.08$, $\mathrm{HEF} > 0.2$, $t_{\mathrm{jet}} < -3\,\mathrm{ns}$ and $E^{\mathrm{CSC}}_\mathrm{ECAL}/E_{\mathrm{ECAL}} < 0.8$) and for signal jets satisfying signal region requirements (except those on $E_{\mathrm{ECAL}}$ and $N^{\mathrm{cell}}_{\mathrm{ECAL}}$).
The distribution (normalized to unity) of $\mathrm{HEF}$ for a data sample enriched in beam halo and noise jets (satisfying $|\eta| < 1.48$, $p_\mathrm{T} > 30 \,\mathrm{GeV}$, $PV_{\rm track}^{\rm fraction} < 1/12$, $t_{\mathrm{jet}} < -3\,\mathrm{ns}$, $E_{\mathrm{ECAL}} > 20\,\mathrm{GeV}$ and $t^{\mathrm{RMS}}_\mathrm{jet}/t_{\mathrm{jet}} < 0.4$) and for signal jets passing signal region selections (except on $\mathrm{HEF}$).
The distribution (normalized to unity) of $\mathrm{HEF}$ for a data sample enriched in beam halo and noise jets (satisfying $|\eta| < 1.48$, $p_\mathrm{T} > 30 \,\mathrm{GeV}$, $p_\mathrm{T}tf < 0.08$, $t_{\mathrm{jet}} < -3\,\mathrm{ns}$, $E_{\mathrm{ECAL}} > 20\,\mathrm{GeV}$ and $t^{\mathrm{RMS}}_\mathrm{jet}/t_{\mathrm{jet}} < 0.4$) and for signal jets passing signal region selections (except on $\mathrm{HEF}$).
The distribution (normalized to unity) of $E_{\mathrm{HCAL}}$ for a data sample enriched in beam halo and noise jets (satisfying $|\eta| < 1.48$, $p_\mathrm{T} > 30 \,\mathrm{GeV}$, $PV_{\rm track}^{\rm fraction} < 1/12$, $t_{\mathrm{jet}} < -3\,\mathrm{ns}$, $E_{\mathrm{ECAL}} > 20\,\mathrm{GeV}$ and $t^{\mathrm{RMS}}_\mathrm{jet}/t_{\mathrm{jet}} < 0.4$) and for signal jets passing signal region selections (except on $E_{\mathrm{HCAL}}$).
The distribution (normalized to unity) of $E_{\mathrm{HCAL}}$ for a data sample enriched in beam halo and noise jets (satisfying $|\eta| < 1.48$, $p_\mathrm{T} > 30 \,\mathrm{GeV}$, $p_\mathrm{T}tf < 0.08$, $t_{\mathrm{jet}} < -3\,\mathrm{ns}$, $E_{\mathrm{ECAL}} > 20\,\mathrm{GeV}$ and $t^{\mathrm{RMS}}_\mathrm{jet}/t_{\mathrm{jet}} < 0.4$) and for signal jets passing signal region selections (except on $E_{\mathrm{HCAL}}$).
The distribution (normalized to unity) of $t^{\mathrm{RMS}}_\mathrm{jet}/t_{\mathrm{jet}}$ for data sample enriched in jets from noise (satisfying $|\eta| < 1.48$, $p_\mathrm{T} > 30\,\mathrm{GeV}$, $PV_{\rm track}^{\rm fraction} > 1/12$, $\mathrm{HEF} > 0.2$, $t_{\mathrm{jet}} < -3\,\mathrm{ns}$, $E_{\mathrm{ECAL}} > 20 \,\mathrm{GeV}$ and $E^{\mathrm{CSC}}_\mathrm{ECAL}/E_{\mathrm{ECAL}} < 0.8$) and for signal jets passing signal region selections (except on $t^{\mathrm{RMS}}_\mathrm{jet}/t_{\mathrm{jet}}$ and $t^{\mathrm{RMS}}_\mathrm{jet}$)
The distribution (normalized to unity) of $t^{\mathrm{RMS}}_\mathrm{jet}/t_{\mathrm{jet}}$ for data sample enriched in jets from noise (satisfying $|\eta| < 1.48$, $p_\mathrm{T} > 30\,\mathrm{GeV}$, $p_\mathrm{T}tf > 0.08$, $\mathrm{HEF} > 0.2$, $t_{\mathrm{jet}} < -3\,\mathrm{ns}$, $E_{\mathrm{ECAL}} > 20 \,\mathrm{GeV}$ and $E^{\mathrm{CSC}}_\mathrm{ECAL}/E_{\mathrm{ECAL}} < 0.8$) and for signal jets passing signal region selections (except on $t^{\mathrm{RMS}}_\mathrm{jet}/t_{\mathrm{jet}}$ and $t^{\mathrm{RMS}}_\mathrm{jet}$)
The distribution (normalized to unity) of $t^{\mathrm{RMS}}_\mathrm{jet}$ for data sample enriched in jets from noise (satisfying $|\eta| < 1.48$, $p_\mathrm{T} > 30\,\mathrm{GeV}$, $PV_{\rm track}^{\rm fraction} > 1/12$, $\mathrm{HEF} > 0.2$, $t_{\mathrm{jet}} < -3\,\mathrm{ns}$, $E_{\mathrm{ECAL}} > 20 \,\mathrm{GeV}$ and $E^{\mathrm{CSC}}_\mathrm{ECAL}/E_{\mathrm{ECAL}} < 0.8$) and for signal jets passing signal region selections (except on $t^{\mathrm{RMS}}_\mathrm{jet}/t_{\mathrm{jet}}$ and $t^{\mathrm{RMS}}_\mathrm{jet}$)
The distribution (normalized to unity) of $t^{\mathrm{RMS}}_\mathrm{jet}$ for data sample enriched in jets from noise (satisfying $|\eta| < 1.48$, $p_\mathrm{T} > 30\,\mathrm{GeV}$, $p_\mathrm{T}tf > 0.08$, $\mathrm{HEF} > 0.2$, $t_{\mathrm{jet}} < -3\,\mathrm{ns}$, $E_{\mathrm{ECAL}} > 20 \,\mathrm{GeV}$ and $E^{\mathrm{CSC}}_\mathrm{ECAL}/E_{\mathrm{ECAL}} < 0.8$) and for signal jets passing signal region selections (except on $t^{\mathrm{RMS}}_\mathrm{jet}/t_{\mathrm{jet}}$ and $t^{\mathrm{RMS}}_\mathrm{jet}$)
The distribution (normalized to unity) of $PV_{\rm track}^{\rm fraction}$ for a data sample enriched in main bunch backgrounds (satisfying $p_\mathrm{T} > 30\,\mathrm{GeV}$, $|\eta| < 1.48$, $E^{\mathrm{CSC}}_\mathrm{ECAL}/E_{\mathrm{ECAL}} < 0.8$, $|t_{\mathrm{jet}}| < 3\,\mathrm{ns}$ and $E_{\mathrm{ECAL}} >20\,\mathrm{GeV}$) and for signal jets passing signal selections (except on $PV_{\rm track}^{\rm fraction}$).
The distribution (normalized to unity) of $p_\mathrm{T}tf$ for a data sample enriched in main bunch backgrounds (satisfying $p_\mathrm{T} > 30\,\mathrm{GeV}$, $|\eta| < 1.48$, $E^{\mathrm{CSC}}_\mathrm{ECAL}/E_{\mathrm{ECAL}} < 0.8$, $|t_{\mathrm{jet}}| < 3\,\mathrm{ns}$ and $E_{\mathrm{ECAL}} >20\,\mathrm{GeV}$) and for signal jets passing signal selections (except on $p_\mathrm{T}tf$).
The distribution (normalized to unity) of $E^{\mathrm{CSC}}_\mathrm{ECAL}/E_{\mathrm{ECAL}}$ for a data sample enriched in beam halo (satisfying $p_\mathrm{T} > 30\,\mathrm{GeV}$, $|\eta| < 1.48$, $PV_{\rm track}^{\rm fraction} < 1/12$, $\mathrm{HEF} < 0.2$, $t^{\mathrm{RMS}}_\mathrm{jet}/t_{\mathrm{jet}} < 0.4$, $t_{\mathrm{jet}} < -3\,\mathrm{ns}$ and $E_{\mathrm{ECAL}} > 20\,\mathrm{GeV}$) and for signal jets passing signal selections (except on $E^{\mathrm{CSC}}_\mathrm{ECAL}/E_{\mathrm{ECAL}}$)
The distribution (normalized to unity) of $E^{\mathrm{CSC}}_\mathrm{ECAL}/E_{\mathrm{ECAL}}$ for a data sample enriched in beam halo (satisfying $p_\mathrm{T} > 30\,\mathrm{GeV}$, $|\eta| < 1.48$, $p_\mathrm{T}tf < 0.08$, $\mathrm{HEF} < 0.2$, $t^{\mathrm{RMS}}_\mathrm{jet}/t_{\mathrm{jet}} < 0.4$, $t_{\mathrm{jet}} < -3\,\mathrm{ns}$ and $E_{\mathrm{ECAL}} > 20\,\mathrm{GeV}$) and for signal jets passing signal selections (except on $E^{\mathrm{CSC}}_\mathrm{ECAL}/E_{\mathrm{ECAL}}$)
The distribution (normalized to unity) of $\mathrm{max}(\Delta \phi_{\mathrm{DT}})$ for a data sample enriched in cosmic muons (satisfying $E^{\mathrm{CSC}}_\mathrm{ECAL}/E_{\mathrm{ECAL}} < 0.8$, $p_\mathrm{T} > 30\,\mathrm{GeV}$, $|\eta| < 1.48$, $PV_{\rm track}^{\rm fraction} < 1/12$, $\mathrm{HEF} > 0.2$, $t^{\mathrm{RMS}}_\mathrm{jet}/t_{\mathrm{jet}} < 0.4$, $t_{\mathrm{jet}} > 3\,\mathrm{ns}$, $E_{\mathrm{ECAL}} > 20\,\mathrm{GeV}$ and failing the HCAL noise rejection quality filters) and for signal jets passing signal selections (except on $\mathrm{max}(\Delta \phi_{\mathrm{DT}})$).
The distribution (normalized to unity) of $\mathrm{max}(\Delta \phi_{\mathrm{DT}})$ for a data sample enriched in cosmic muons (satisfying $E^{\mathrm{CSC}}_\mathrm{ECAL}/E_{\mathrm{ECAL}} < 0.8$, $p_\mathrm{T} > 30\,\mathrm{GeV}$, $|\eta| < 1.48$, $p_\mathrm{T}tf < 0.08$, $\mathrm{HEF} > 0.2$, $t^{\mathrm{RMS}}_\mathrm{jet}/t_{\mathrm{jet}} < 0.4$, $t_{\mathrm{jet}} > 3\,\mathrm{ns}$, $E_{\mathrm{ECAL}} > 20\,\mathrm{GeV}$ and failing the HCAL noise rejection quality filters) and for signal jets passing signal selections (except on $\mathrm{max}(\Delta \phi_{\mathrm{DT}})$).
The distribution (normalized to unity) of $\mathrm{max}(\Delta \phi_{\mathrm{RPC}})$ for a data sample enriched in cosmic muons (satisfying $E^{\mathrm{CSC}}_\mathrm{ECAL}/E_{\mathrm{ECAL}} < 0.8$, $p_\mathrm{T} > 30\,\mathrm{GeV}$, $|\eta| < 1.48$, $PV_{\rm track}^{\rm fraction} < 1/12$, $\mathrm{HEF} > 0.2$, $t^{\mathrm{RMS}}_\mathrm{jet}/t_{\mathrm{jet}} < 0.4$, $t_{\mathrm{jet}} > 3\,\mathrm{ns}$, $E_{\mathrm{ECAL}} > 20\,\mathrm{GeV}$ and failing the HCAL noise rejection quality filters) and for signal jets passing signal selections (except on $\mathrm{max}(\Delta \phi_{\mathrm{RPC}})$).
The distribution (normalized to unity) of $\mathrm{max}(\Delta \phi_{\mathrm{RPC}})$ for a data sample enriched in cosmic muons (satisfying $E^{\mathrm{CSC}}_\mathrm{ECAL}/E_{\mathrm{ECAL}} < 0.8$, $p_\mathrm{T} > 30\,\mathrm{GeV}$, $|\eta| < 1.48$, $p_\mathrm{T}tf < 0.08$, $\mathrm{HEF} > 0.2$, $t^{\mathrm{RMS}}_\mathrm{jet}/t_{\mathrm{jet}} < 0.4$, $t_{\mathrm{jet}} > 3\,\mathrm{ns}$, $E_{\mathrm{ECAL}} > 20\,\mathrm{GeV}$ and failing the HCAL noise rejection quality filters) and for signal jets passing signal selections (except on $\mathrm{max}(\Delta \phi_{\mathrm{RPC}})$).
Distribution of $t_{\mathrm{jet}}$ for jets with the full Run 2 dataset with no cleaning selection applied (a) and after all jet cleaning selections are applied (b) in events satisfying the trigger requirements and satisfying $p_T^\mathrm{miss} > 300$. The jets are required to pass an inverted selection of $PV_{\rm track}^{\rm fraction} > 1/12$ to enrich the sample in those originating from main and satellite bunch backgrounds. The cleaning selections are shown to reduce the backgrounds by many orders of magnitude.
Distribution of $t_{\mathrm{jet}}$ for jets with the full Run 2 dataset with no cleaning selection applied (a) and after all jet cleaning selections are applied (b) in events satisfying the trigger requirements and satisfying $p_T^\mathrm{miss} > 300$. The jets are required to pass an inverted selection of $PV_{\rm track}^{\rm fraction} > 0.08$ to enrich the sample in those originating from main and satellite bunch backgrounds. The cleaning selections are shown to reduce the backgrounds by many orders of magnitude.
Distribution of $t_{\mathrm{jet}}$ for jets with the full Run 2 dataset in events satisfying the trigger requirements and satisfying $p_T^\mathrm{miss} < 300$. The jets are required to pass an inverted selection of $PV_{\rm track}^{\rm fraction} > 1/12$ to enrich the sample in those originating from main and satellite bunch backgrounds (all other jet cleaning selections are applied). Clear contributions from jets from satellite bunch collisions can be seen peaked around -5, 5 and 10 ns.
Distribution of $t_{\mathrm{jet}}$ for jets with the full Run 2 dataset in events satisfying the trigger requirements and satisfying $p_T^\mathrm{miss} < 300$. The jets are required to pass an inverted selection of $PV_{\rm track}^{\rm fraction} > 0.08$ to enrich the sample in those originating from main and satellite bunch backgrounds (all other jet cleaning selections are applied). Clear contributions from jets from satellite bunch collisions can be seen peaked around -5, 5 and 10 ns.
Contribution to the delayed time of jets from the $\beta$ of the gluino is plotted against the delay contribution from the difference (assuming straight line paths) between the path taken by the gluino and the particle forming the jet from the path length for a particle travelling directly to the same position on the ECAL barrel for gluino $c\tau_{0} = 10$ m and mass of 1000 Gev (top) and 3000 GeV (bottom). The dominant contribution is shown to be the gluino $\beta$.
Contribution to the delayed time of jets from the $\beta$ of the gluino is plotted against the delay contribution from the difference (assuming straight line paths) between the path taken by the gluino and the particle forming the jet from the path length for a particle travelling directly to the same position on the ECAL barrel for gluino $c\tau_{0} = 10$ m and mass of 1000 Gev (top) and 3000 GeV (bottom). The dominant contribution is shown to be the gluino $\beta$.
Selection efficiencies for the GMSB model with $m_{\tilde{g}}=1000$ and various proper decay lengths
Selection efficiencies for the GMSB model with $m_{\tilde{g}}=1000$ and various proper decay lengths
Selection efficiencies for the GMSB model with $m_{\tilde{g}}=2400$ and various proper decay lengths
Selection efficiencies for the GMSB model with $m_{\tilde{g}}=2400$ and various proper decay lengths
Selection efficiencies for the GMSB model with $m_{\tilde{g}}=3000$ and various proper decay lengths
Selection efficiencies for the GMSB model with $m_{\tilde{g}}=3000$ and various proper decay lengths
The observed upper limits at $95\%$ CL for the gluino pair production cross section relative to the theoretical cross section in the GMSB model, shown in the plane of $m_{\tilde{g}}$ and $c\tau_{0}$. A branching fraction of $100\%$ for the gluino decay to a gluon and a gravitino is assumed. The area below the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm 1$ standard deviation ranges from experimental uncertainties. The thin black lines show the effect of the theoretical uncertainties on the signal cross section.
The observed upper limits at $95\%$ CL for the gluino pair production cross section relative to the theoretical cross section in the GMSB model, shown in the plane of $m_{\tilde{g}}$ and $c\tau_{0}$. A branching fraction of $100\%$ for the gluino decay to a gluon and a gravitino is assumed. The area below the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm 1$ standard deviation ranges from experimental uncertainties. The thin black lines show the effect of the theoretical uncertainties on the signal cross section.
The expected upper limits at $95\%$ CL for the gluino pair production cross section relative to the theoretical cross section in the GMSB model, shown in the plane of $m_{\tilde{g}}$ and $c\tau_{0}$. A branching fraction of $100\%$ for the gluino decay to a gluon and a gravitino is assumed. The area below the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm 1$ standard deviation ranges from experimental uncertainties. The thin black lines show the effect of the theoretical uncertainties on the signal cross section.
The expected upper limits at $95\%$ CL for the gluino pair production cross section relative to the theoretical cross section in the GMSB model, shown in the plane of $m_{\tilde{g}}$ and $c\tau_{0}$. A branching fraction of $100\%$ for the gluino decay to a gluon and a gravitino is assumed. The area below the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm 1$ standard deviation ranges from experimental uncertainties. The thin black lines show the effect of the theoretical uncertainties on the signal cross section.
The expected plus 1 $\sigma_{\mathrm{experiment}}$ upper limits at $95\%$ CL for the gluino pair production cross section relative to the theoretical cross section in the GMSB model, shown in the plane of $m_{\tilde{g}}$ and $c\tau_{0}$. A branching fraction of $100\%$ for the gluino decay to a gluon and a gravitino is assumed. The area below the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm 1$ standard deviation ranges from experimental uncertainties. The thin black lines show the effect of the theoretical uncertainties on the signal cross section.
The expected plus 1 $\sigma_{\mathrm{experiment}}$ upper limits at $95\%$ CL for the gluino pair production cross section relative to the theoretical cross section in the GMSB model, shown in the plane of $m_{\tilde{g}}$ and $c\tau_{0}$. A branching fraction of $100\%$ for the gluino decay to a gluon and a gravitino is assumed. The area below the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm 1$ standard deviation ranges from experimental uncertainties. The thin black lines show the effect of the theoretical uncertainties on the signal cross section.
The expected minus 1 $\sigma_{\mathrm{experiment}}$ upper limits at $95\%$ CL for the gluino pair production cross section relative to the theoretical cross section in the GMSB model, shown in the plane of $m_{\tilde{g}}$ and $c\tau_{0}$. A branching fraction of $100\%$ for the gluino decay to a gluon and a gravitino is assumed. The area below the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm 1$ standard deviation ranges from experimental uncertainties. The thin black lines show the effect of the theoretical uncertainties on the signal cross section.
The expected minus 1 $\sigma_{\mathrm{experiment}}$ upper limits at $95\%$ CL for the gluino pair production cross section relative to the theoretical cross section in the GMSB model, shown in the plane of $m_{\tilde{g}}$ and $c\tau_{0}$. A branching fraction of $100\%$ for the gluino decay to a gluon and a gravitino is assumed. The area below the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm 1$ standard deviation ranges from experimental uncertainties. The thin black lines show the effect of the theoretical uncertainties on the signal cross section.
The expected upper limits at $95\%$ CL for the gluino pair production cross section in the GMSB model, shown in the plane of $m_{\tilde{g}}$ and $c\tau_{0}$. A branching fraction of $100\%$ for the gluino decay to a gluon and a gravitino is assumed. The area below the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm 1$ standard deviation ranges from experimental uncertainties. The thin black lines show the effect of the theoretical uncertainties on the signal cross section.
The expected upper limits at $95\%$ CL for the gluino pair production cross section in the GMSB model, shown in the plane of $m_{\tilde{g}}$ and $c\tau_{0}$. A branching fraction of $100\%$ for the gluino decay to a gluon and a gravitino is assumed. The area below the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm 1$ standard deviation ranges from experimental uncertainties. The thin black lines show the effect of the theoretical uncertainties on the signal cross section.
The expected plus 1 $\sigma_{\mathrm{experiment}}$ upper limits at $95\%$ CL for the gluino pair production cross section in the GMSB model, shown in the plane of $m_{\tilde{g}}$ and $c\tau_{0}$. A branching fraction of $100\%$ for the gluino decay to a gluon and a gravitino is assumed. The area below the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm 1$ standard deviation ranges from experimental uncertainties. The thin black lines show the effect of the theoretical uncertainties on the signal cross section.
The expected plus 1 $\sigma_{\mathrm{experiment}}$ upper limits at $95\%$ CL for the gluino pair production cross section in the GMSB model, shown in the plane of $m_{\tilde{g}}$ and $c\tau_{0}$. A branching fraction of $100\%$ for the gluino decay to a gluon and a gravitino is assumed. The area below the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm 1$ standard deviation ranges from experimental uncertainties. The thin black lines show the effect of the theoretical uncertainties on the signal cross section.
The expected minus 1 $\sigma_{\mathrm{experiment}}$ upper limits at $95\%$ CL for the gluino pair production cross section in the GMSB model, shown in the plane of $m_{\tilde{g}}$ and $c\tau_{0}$. A branching fraction of $100\%$ for the gluino decay to a gluon and a gravitino is assumed. The area below the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm 1$ standard deviation ranges from experimental uncertainties. The thin black lines show the effect of the theoretical uncertainties on the signal cross section.
The expected minus 1 $\sigma_{\mathrm{experiment}}$ upper limits at $95\%$ CL for the gluino pair production cross section in the GMSB model, shown in the plane of $m_{\tilde{g}}$ and $c\tau_{0}$. A branching fraction of $100\%$ for the gluino decay to a gluon and a gravitino is assumed. The area below the thick black curve represents the observed exclusion region, while the dashed red lines indicate the expected limits and their $\pm 1$ standard deviation ranges from experimental uncertainties. The thin black lines show the effect of the theoretical uncertainties on the signal cross section.
A search for long-lived particles decaying into an oppositely charged lepton pair, $\mu\mu$, $ee$, or $e\mu$, is presented using 32.8 fb$^{-1}$ of $pp$ collision data collected at $\sqrt{s}=13$ TeV by the ATLAS detector at the LHC. Candidate leptons are required to form a vertex, within the inner tracking volume of ATLAS, displaced from the primary $pp$ interaction region. No lepton pairs with an invariant mass greater than 12 GeV are observed, consistent with the background expectations derived from data. The detection efficiencies for generic resonances with lifetimes ($c\tau$) of 100-1000 mm decaying into a dilepton pair with masses between 0.1-1.0 TeV are presented as a function of $p_T$ and decay radius of the resonances to allow the extraction of upper limits on the cross sections for theoretical models. The result is also interpreted in a supersymmetric model in which the lightest neutralino, produced via squark-antisquark production, decays into $\ell^{+}\ell^{'-}\nu$ ($\ell, \ell^{'} = e$, $\mu$) with a finite lifetime due to the presence of R-parity violating couplings. Cross-section limits are presented for specific squark and neutralino masses. For a 700 GeV squark, neutralinos with masses of 50-500 GeV and mean proper lifetimes corresponding to $c\tau$ values between 1 mm to 6 m are excluded. For a 1.6 TeV squark, $c\tau$ values between 3 mm to 1 m are excluded for 1.3 TeV neutralinos.
<h1>Overview of reinterpretation material</h1><p><b>Important note:</b> A detailed explanation of the reinterpretation material can be found <a href="https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/SUSY-2017-04/hepdata_info.pdf">here</a>.<br/>Please read this stand-alone document before reinterpreting the search.</p><h2>Parameterized detection efficiencies</h2><p>RPV SUSY model: Tables <a href="90606?version=1&table=Table27">27</a> to <a href="90606?version=1&table=Table44">44</a><br/>Z' toy model: Tables <a href="90606?version=1&table=Table45">45</a> to <a href="90606?version=1&table=Table59">59</a></p><h2>Further material for the RPV SUSY model</h2><p>Acceptances: Tables <a href="90606?version=1&table=Table18">18</a> (ee), <a href="90606?version=1&table=Table19">19</a> (emu) and <a href="90606?version=1&table=Table20">20</a> (mumu)<br/>Detection efficiencies: Tables <a href="90606?version=1&table=Table21">21</a> (ee), <a href="90606?version=1&table=Table22">22</a> (emu) and <a href="90606?version=1&table=Table23">23</a> (mumu)<br/>Overall signal efficiencies: Tables <a href="90606?version=1&table=Table24">24</a> (ee), <a href="90606?version=1&table=Table25">25</a> (emu) and <a href="90606?version=1&table=Table26">26</a> (mumu)</p><h2>Further material for the Z' toy model</h2><p>Acceptances, detection efficiencies and overall signal efficiencies: Tables <a href="90606?version=1&table=Table60">60</a> (mZ' = 100 GeV) to <a href="90606?version=1&table=Table64">64</a> (mZ' = 1000 GeV)</p>
dRcos distribution of dimuon pairs (scaled) and dimuon vertices in the cosmic rays control region. The distribution of all dimuon pairs is scaled to the DV distribution.
Dependence of the overall signal efficiency on the transverse decay radius Rxy of the long-lived Z' for Z' -> ee. The error bars indicate the total uncertainties.
Dependence of the overall signal efficiency on the pT of the long-lived Z' for Z' -> ee. The error bars indicate the total uncertainties.
Dependence of the overall signal efficiency on the transverse decay radius Rxy of the long-lived Z' for Z' -> emu. The error bars indicate the total uncertainties.
Dependence of the overall signal efficiency on the pT of the long-lived Z' for Z' -> emu. The error bars indicate the total uncertainties.
Dependence of the overall signal efficiency on the transverse decay radius Rxy of the long-lived Z' for Z' -> mumu. The error bars indicate the total uncertainties.
Dependence of the overall signal efficiency on the pT of the long-lived Z' for Z' -> mumu. The error bars indicate the total uncertainties.
Overall signal efficiency as a function of the mean proper lifetime (ctau) of the neutralino for the lambda121 scenario of the RPV SUSY model. The error bars indicate the total uncertainties.
Overall signal efficiency as a function of the mean proper lifetime (ctau) of the neutralino for the lambda122 scenario of the RPV SUSY model. The error bars indicate the total uncertainties.
95% CL upper limits on the squark-antisquark production cross-section as a function of the mean proper lifetime (ctau) of the neutralino for the lambda121 scenario of the RPV SUSY model and a 700 GeV squark. The uncertainties of the expected limit indicate the +-1sigma variations.
95% CL upper limits on the squark-antisquark production cross-section as a function of the mean proper lifetime (ctau) of the neutralino for the lambda122 scenario of the RPV SUSY model and a 700 GeV squark. The uncertainties of the expected limit indicate the +-1sigma variations.
95% CL upper limits on the squark-antisquark production cross-section as a function of the mean proper lifetime (ctau) of the neutralino for the lambda121 scenario of the RPV SUSY model and a 1600 GeV squark. The uncertainties of the expected limit indicate the +-1sigma variations.
95% CL upper limits on the squark-antisquark production cross-section as a function of the mean proper lifetime (ctau) of the neutralino for the lambda122 scenario of the RPV SUSY model and a 1600 GeV squark. The uncertainties of the expected limit indicate the +-1sigma variations.
Fraction of detector volume covered by the material veto as a function of z and Rxy of the displaced dilepton vertex.
Fraction of detector volume covered by the disabled pixel modules veto veto as a function of z and Rxy of the displaced dilepton vertex.
Observed Rxy distribution of vertices composed of two non-leptonic tracks in a control sample in the data and the predicted distribution obtained from the event mixing. The error bars indicate the statistical uncertainties.
Rxy distributions of Kshort vertices from the large radius tracking in the data and background MC samples. Data has been normalised such that the total number of Kshort from the standard tracking in the data agrees with the total number of Kshort from the standard tracking in the MC. The error bars indicate the statistical uncertainties.
Acceptance per decay as a function of the mean proper lifetime (ctau) of the neutralino for neutralino -> eenu. The error bars indicate the statistical uncertainties.
Acceptance per decay as a function of the mean proper lifetime (ctau) of the neutralino for neutralino -> emunu. The error bars indicate the statistical uncertainties.
Acceptance per decay as a function of the mean proper lifetime (ctau) of the neutralino for neutralino -> mumunu. The error bars indicate the statistical uncertainties.
Detection efficiency per decay as a function of the mean proper lifetime (ctau) of the neutralino for neutralino -> eenu. The error bars indicate the total uncertainties.
Detection efficiency per decay as a function of the mean proper lifetime (ctau) of the neutralino for neutralino -> emunu. The error bars indicate the total uncertainties.
Detection efficiency per decay as a function of the mean proper lifetime (ctau) of the neutralino for neutralino -> mumunu. The error bars indicate the total uncertainties.
Overall signal efficiency (acceptance times efficiency) per decay as a function of the mean proper lifetime (ctau) of the neutralino for neutralino -> eenu. The error bars indicate the total uncertainties.
Overall signal efficiency (acceptance times efficiency) per decay as a function of the mean proper lifetime (ctau) of the neutralino for neutralino -> emunu. The error bars indicate the total uncertainties.
Overall signal efficiency (acceptance times efficiency) per decay as a function of the mean proper lifetime (ctau) of the neutralino for neutralino -> mumunu. The error bars indicate the total uncertainties.
Detection efficiency per decay for Rxy < 22 mm as a function of the invariant mass and pT of the electron pair in LLP -> eeX.
Detection efficiency per decay for 22 <= Rxy < 38 mm as a function of the invariant mass and pT of the electron pair in LLP -> eeX.
Detection efficiency per decay for 38 <= Rxy < 73 mm as a function of the invariant mass and pT of the electron pair in LLP -> eeX.
Detection efficiency per decay for 73 <= Rxy < 111 mm as a function of the invariant mass and pT of the electron pair in LLP -> eeX.
Detection efficiency per decay for 111 <= Rxy < 145 mm as a function of the invariant mass and pT of the electron pair in LLP -> eeX.
Detection efficiency per decay for 145 <= Rxy < 300 mm as a function of the invariant mass and pT of the electron pair in LLP -> eeX.
Detection efficiency per decay for Rxy < 22 mm as a function of the invariant mass and pT of the electron and muon pair in LLP -> emuX.
Detection efficiency per decay for 22 <= Rxy < 38 mm as a function of the invariant mass and pT of the electron and muon pair in LLP -> emuX.
Detection efficiency per decay for 38 <= Rxy < 73 mm as a function of the invariant mass and pT of the electron and muon pair in LLP -> emuX.
Detection efficiency per decay for 73 <= Rxy < 111 mm as a function of the invariant mass and pT of the electron and muon pair in LLP -> emuX.
Detection efficiency per decay for 111 <= Rxy < 145 mm as a function of the invariant mass and pT of the electron and muon pair in LLP -> emuX.
Detection efficiency per decay for 145 <= Rxy < 300 mm as a function of the invariant mass and pT of the electron and muon pair in LLP -> emuX.
Detection efficiency per decay for Rxy < 22 mm as a function of the invariant mass and pT of the muon pair in LLP -> mumuX.
Detection efficiency per decay for 22 <= Rxy < 38 mm as a function of the invariant mass and pT of the muon pair in LLP -> mumuX.
Detection efficiency per decay for 38 <= Rxy < 73 mm as a function of the invariant mass and pT of the muon pair in LLP -> mumuX.
Detection efficiency per decay for 73 <= Rxy < 111 mm as a function of the invariant mass and pT of the muon pair in LLP -> mumuX.
Detection efficiency per decay for 111 <= Rxy < 145 mm as a function of the invariant mass and pT of the muon pair in LLP -> mumuX.
Detection efficiency per decay for 145 <= Rxy < 300 mm as a function of the invariant mass and pT of the muon pair in LLP -> mumuX.
Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 100 GeV and LLP -> ee.
Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 100 GeV and LLP -> emu.
Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 100 GeV and LLP -> mumu.
Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 250 GeV and LLP -> ee.
Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 250 GeV and LLP -> emu.
Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 250 GeV and LLP -> mumu.
Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 500 GeV and LLP -> ee.
Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 500 GeV and LLP -> emu.
Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 500 GeV and LLP -> mumu.
Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 750 GeV and LLP -> ee.
Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 750 GeV and LLP -> emu.
Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 750 GeV and LLP -> mumu.
Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 1000 GeV and LLP -> ee.
Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 1000 GeV and LLP -> emu.
Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 1000 GeV and LLP -> mumu.
Acceptance, detection efficiency, and overall signal efficiency in the Z' toy model for mZ' = 100 GeV, three mean proper lifetimes (ctau) and the three decay modes of the Z'.
Acceptance, detection efficiency, and overall signal efficiency in the Z' toy model for mZ' = 250 GeV, three mean proper lifetimes (ctau) and the three decay modes of the Z'.
Acceptance, detection efficiency, and overall signal efficiency in the Z' toy model for mZ' = 500 GeV, three mean proper lifetimes (ctau) and the three decay modes of the Z'.
Acceptance, detection efficiency, and overall signal efficiency in the Z' toy model for mZ' = 750 GeV, three mean proper lifetimes (ctau) and the three decay modes of the Z'.
Acceptance, detection efficiency, and overall signal efficiency in the Z' toy model for mZ' = 1000 GeV, three mean proper lifetimes (ctau) and the three decay modes of the Z'.
A search for the electroweak production of charginos and sleptons decaying into final states with two electrons or muons is presented. The analysis is based on 139 fb$^{-1}$ of proton-proton collisions recorded by the ATLAS detector at the Large Hadron Collider at $\sqrt{s}=13$ TeV. Three $R$-parity-conserving scenarios where the lightest neutralino is the lightest supersymmetric particle are considered: the production of chargino pairs with decays via either $W$ bosons or sleptons, and the direct production of slepton pairs. The analysis is optimised for the first of these scenarios, but the results are also interpreted in the others. No significant deviations from the Standard Model expectations are observed and limits at 95 % confidence level are set on the masses of relevant supersymmetric particles in each of the scenarios. For a massless lightest neutralino, masses up to 420 GeV are excluded for the production of the lightest-chargino pairs assuming $W$-boson-mediated decays and up to 1 TeV for slepton-mediated decays, whereas for slepton-pair production masses up to 700 GeV are excluded assuming three generations of mass-degenerate sleptons.
- - - - - - - - Overview of HEPData Record - - - - - - - - <br/><br/> <b>Background Fit results:</b> <ul> <li><a href="89413?version=1&table=Backgroundfit1">CRs</a> <li><a href="89413?version=1&table=Backgroundfit2">VRs</a> <li><a href="89413?version=1&table=Backgroundfit5">inclusive DF-0J SRs</a> <li><a href="89413?version=1&table=Backgroundfit6">inclusive DF-1J SRs</a> <li><a href="89413?version=1&table=Backgroundfit3">inclusive SF-0J SRs</a> <li><a href="89413?version=1&table=Backgroundfit4">inclusive SF-1J SRs</a> </ul> <b>Kinematic distributions in VRs:</b> <ul> <li><a href="89413?version=1&table=VRkinematics1">$m_{T2}$ in VR-top-low</a> <li><a href="89413?version=1&table=VRkinematics2">$m_{T2}$ in VR-top-high</a> <li><a href="89413?version=1&table=VRkinematics3">$E_T^{miss}$ in VR-WW-0J</a> <li><a href="89413?version=1&table=VRkinematics4">$E_T^{miss}$ in VR-WW-1J</a> <li><a href="89413?version=1&table=VRkinematics5">$E_T^{miss}$ sig in VR-VZ</a> <li><a href="89413?version=1&table=VRkinematics6">$E_T^{miss}$ sig in VR-top-WW</a> </ul> <b>Kinematic distributions in SRs:</b> <ul> <li><a href="89413?version=1&table=SRkinematics1">$m_{T2}$ in SR-SF-0J</a> <li><a href="89413?version=1&table=SRkinematics2">$m_{T2}$ in SR-SF-1J</a> <li><a href="89413?version=1&table=SRkinematics3">$m_{T2}$ in SR-DF-0J</a> <li><a href="89413?version=1&table=SRkinematics4">$m_{T2}$ in SR-DF-1J</a> </ul> <b>Systematic uncertaities:</b> <ul> <li><a href="89413?version=1&table=Systematic uncertainties">dominant systematic uncertainties in the inclusive SRs</a> </ul> <b>Exclusion contours:</b> <ul> <li><a href="89413?version=1&table=Exclusioncontour(obs)1">expected exclusion contour direct chargino-pair production via W decay grid</a> <li><a href="89413?version=1&table=Exclusioncontour(exp)1">observed exclusion contour direct chargino-pair production via W decay grid</a> <li><a href="89413?version=1&table=Exclusioncontour(obs)2">expected exclusion contour direct chargino-pair production via slepton decay grid</a> <li><a href="89413?version=1&table=Exclusioncontour(exp)2">observed exclusion contour direct chargino-pair production via slepton decay grid</a> <li><a href="89413?version=1&table=Exclusioncontour(obs)3">expected exclusion contour direct slepton-pair production grid</a> <li><a href="89413?version=1&table=Exclusioncontour(exp)3">observed exclusion contour direct slepton-pair production grid</a> </ul> <br/><br/><b>AUXILIARY MATERIAL</b><br/> <b>Background Fit in binned SRs:</b> <ul> <li><a href="89413?version=1&table=Backgroundfit7">binned DF-0J SRs</a> <li><a href="89413?version=1&table=Backgroundfit8">binned DF-1J SRs</a> <li><a href="89413?version=1&table=Backgroundfit9">binned SF-0J SRs</a> <li><a href="89413?version=1&table=Backgroundfit10">binned SF-1J SRs</a> </ul> <b>Exclusion contours:</b> <ul> <li><a href="89413?version=1&table=Exclusioncontour(obs)4">expected exclusion contour left-handed slepton-pair production</a> <li><a href="89413?version=1&table=Exclusioncontour(exp)4">observed exclusion contour left-handed slepton-pair production</a> <li><a href="89413?version=1&table=Exclusioncontour(obs)5">expected exclusion contour right-handed slepton-pair production</a> <li><a href="89413?version=1&table=Exclusioncontour(exp)5">observed exclusion contour right-handed slepton-pair production</a> <li><a href="89413?version=1&table=Exclusioncontour(obs)6">expected exclusion contour selectron-pair production</a> <li><a href="89413?version=1&table=Exclusioncontour(exp)6">observed exclusion contour selectron-pair production</a> <li><a href="89413?version=1&table=Exclusioncontour(obs)7">expected exclusion contour left-handed selectron-pair production</a> <li><a href="89413?version=1&table=Exclusioncontour(exp)7">observed exclusion contour left-handed selectron-pair production</a> <li><a href="89413?version=1&table=Exclusioncontour(obs)8">expected exclusion contour right-handed selectron-pair production</a> <li><a href="89413?version=1&table=Exclusioncontour(exp)8">observed exclusion contour right-handed selectron-pair production</a> <li><a href="89413?version=1&table=Exclusioncontour(obs)9">expected exclusion contour smuon-pair production</a> <li><a href="89413?version=1&table=Exclusioncontour(exp)9">observed exclusion contour smuon-pair production</a> <li><a href="89413?version=1&table=Exclusioncontour(obs)10">expected exclusion contour left-handed smuon-pair production</a> <li><a href="89413?version=1&table=Exclusioncontour(exp)10">observed exclusion contour left-handed smuon-pair production</a> <li><a href="89413?version=1&table=Exclusioncontour(obs)11">expected exclusion contour right-handed smuon-pair production</a> <li><a href="89413?version=1&table=Exclusioncontour(exp)11">observed exclusion contour right-handed smuon-pair production</a> </ul> <b>Cross section upper limits:</b> <ul> <li><a href="89413?version=1&table=xsecupperlimits1">upper limits on signal cross section for direct chargino-pair production via W decay</a> <li><a href="89413?version=1&table=xsecupperlimits2">upper limits on signal cross section for direct chargino-pair production via slepton decay</a> <li><a href="89413?version=1&table=xsecupperlimits3">upper limits on signal cross section for direct slepton-pair production</a> </ul> <b>Acceptances and Efficiencies for direct chargino-pair production via W decay grid </b> <ul> <li> <b>Acceptance</b> <br/> <a href="89413?version=1&table=AcceptanceSR-DF-0J-[100,inf)forC1C1WWgrid">SR-DF-0J-[100,inf) </a> <a href="89413?version=1&table=AcceptanceSR-DF-0J-[160,inf)forC1C1WWgrid">SR-DF-0J-[160,inf) </a> <a href="89413?version=1&table=AcceptanceSR-DF-0J-[100,120)forC1C1WWgrid">SR-DF-0J-[100,120) </a> <a href="89413?version=1&table=AcceptanceSR-DF-0J-[120,160)forC1C1WWgrid">SR-DF-0J-[120,160) </a> <a href="89413?version=1&table=AcceptanceSR-DF-0J-[100,105)forC1C1WWgrid">SR-DF-0J-[100,105) </a> <a href="89413?version=1&table=AcceptanceSR-DF-0J-[105,110)forC1C1WWgrid">SR-DF-0J-[105,110) </a> <a href="89413?version=1&table=AcceptanceSR-DF-0J-[110,120)forC1C1WWgrid">SR-DF-0J-[110,120) </a> <a href="89413?version=1&table=AcceptanceSR-DF-0J-[120,140)forC1C1WWgrid">SR-DF-0J-[120,140) </a> <a href="89413?version=1&table=AcceptanceSR-DF-0J-[140,160)forC1C1WWgrid">SR-DF-0J-[140,160) </a> <a href="89413?version=1&table=AcceptanceSR-DF-0J-[160,180)forC1C1WWgrid">SR-DF-0J-[160,180) </a> <a href="89413?version=1&table=AcceptanceSR-DF-0J-[180,220)forC1C1WWgrid">SR-DF-0J-[180,220) </a> <a href="89413?version=1&table=AcceptanceSR-DF-0J-[220,260)forC1C1WWgrid">SR-DF-0J-[220,260) </a> <a href="89413?version=1&table=AcceptanceSR-DF-0J-[260,inf)forC1C1WWgrid">SR-DF-0J-[260,inf) </a><br/> <a href="89413?version=1&table=AcceptanceSR-DF-1J-[100,inf)forC1C1WWgrid">SR-DF-1J-[100,inf) </a> <a href="89413?version=1&table=AcceptanceSR-DF-1J-[160,inf)forC1C1WWgrid">SR-DF-1J-[160,inf) </a> <a href="89413?version=1&table=AcceptanceSR-DF-1J-[100,120)forC1C1WWgrid">SR-DF-1J-[100,120) </a> <a href="89413?version=1&table=AcceptanceSR-DF-1J-[120,160)forC1C1WWgrid">SR-DF-1J-[120,160) </a> <a href="89413?version=1&table=AcceptanceSR-DF-1J-[100,105)forC1C1WWgrid">SR-DF-1J-[100,105) </a> <a href="89413?version=1&table=AcceptanceSR-DF-1J-[105,110)forC1C1WWgrid">SR-DF-1J-[105,110) </a> <a href="89413?version=1&table=AcceptanceSR-DF-1J-[110,120)forC1C1WWgrid">SR-DF-1J-[110,120) </a> <a href="89413?version=1&table=AcceptanceSR-DF-1J-[120,140)forC1C1WWgrid">SR-DF-1J-[120,140) </a> <a href="89413?version=1&table=AcceptanceSR-DF-1J-[140,160)forC1C1WWgrid">SR-DF-1J-[140,160) </a> <a href="89413?version=1&table=AcceptanceSR-DF-1J-[160,180)forC1C1WWgrid">SR-DF-1J-[160,180) </a> <a href="89413?version=1&table=AcceptanceSR-DF-1J-[180,220)forC1C1WWgrid">SR-DF-1J-[180,220) </a> <a href="89413?version=1&table=AcceptanceSR-DF-1J-[220,260)forC1C1WWgrid">SR-DF-1J-[220,260) </a> <a href="89413?version=1&table=AcceptanceSR-DF-1J-[260,inf)forC1C1WWgrid">SR-DF-1J-[260,inf) </a><br/> <a href="89413?version=1&table=AcceptanceSR-SF-0J-[100,inf)forC1C1WWgrid">SR-SF-0J-[100,inf) </a> <a href="89413?version=1&table=AcceptanceSR-SF-0J-[160,inf)forC1C1WWgrid">SR-SF-0J-[160,inf) </a> <a href="89413?version=1&table=AcceptanceSR-SF-0J-[100,120)forC1C1WWgrid">SR-SF-0J-[100,120) </a> <a href="89413?version=1&table=AcceptanceSR-SF-0J-[120,160)forC1C1WWgrid">SR-SF-0J-[120,160) </a> <a href="89413?version=1&table=AcceptanceSR-SF-0J-[100,105)forC1C1WWgrid">SR-SF-0J-[100,105) </a> <a href="89413?version=1&table=AcceptanceSR-SF-0J-[105,110)forC1C1WWgrid">SR-SF-0J-[105,110) </a> <a href="89413?version=1&table=AcceptanceSR-SF-0J-[110,120)forC1C1WWgrid">SR-SF-0J-[110,120) </a> <a href="89413?version=1&table=AcceptanceSR-SF-0J-[120,140)forC1C1WWgrid">SR-SF-0J-[120,140) </a> <a href="89413?version=1&table=AcceptanceSR-SF-0J-[140,160)forC1C1WWgrid">SR-SF-0J-[140,160) </a> <a href="89413?version=1&table=AcceptanceSR-SF-0J-[160,180)forC1C1WWgrid">SR-SF-0J-[160,180) </a> <a href="89413?version=1&table=AcceptanceSR-SF-0J-[180,220)forC1C1WWgrid">SR-SF-0J-[180,220) </a> <a href="89413?version=1&table=AcceptanceSR-SF-0J-[220,260)forC1C1WWgrid">SR-SF-0J-[220,260) </a> <a href="89413?version=1&table=AcceptanceSR-SF-0J-[260,inf)forC1C1WWgrid">SR-SF-0J-[260,inf) </a><br/> <a href="89413?version=1&table=AcceptanceSR-SF-1J-[100,inf)forC1C1WWgrid">SR-SF-1J-[100,inf) </a> <a href="89413?version=1&table=AcceptanceSR-SF-1J-[160,inf)forC1C1WWgrid">SR-SF-1J-[160,inf) </a> <a href="89413?version=1&table=AcceptanceSR-SF-1J-[100,120)forC1C1WWgrid">SR-SF-1J-[100,120) </a> <a href="89413?version=1&table=AcceptanceSR-SF-1J-[120,160)forC1C1WWgrid">SR-SF-1J-[120,160) </a> <a href="89413?version=1&table=AcceptanceSR-SF-1J-[100,105)forC1C1WWgrid">SR-SF-1J-[100,105) </a> <a href="89413?version=1&table=AcceptanceSR-SF-1J-[105,110)forC1C1WWgrid">SR-SF-1J-[105,110) </a> <a href="89413?version=1&table=AcceptanceSR-SF-1J-[110,120)forC1C1WWgrid">SR-SF-1J-[110,120) </a> <a href="89413?version=1&table=AcceptanceSR-SF-1J-[120,140)forC1C1WWgrid">SR-SF-1J-[120,140) </a> <a href="89413?version=1&table=AcceptanceSR-SF-1J-[140,160)forC1C1WWgrid">SR-SF-1J-[140,160) </a> <a href="89413?version=1&table=AcceptanceSR-SF-1J-[160,180)forC1C1WWgrid">SR-SF-1J-[160,180) </a> <a href="89413?version=1&table=AcceptanceSR-SF-1J-[180,220)forC1C1WWgrid">SR-SF-1J-[180,220) </a> <a href="89413?version=1&table=AcceptanceSR-SF-1J-[220,260)forC1C1WWgrid">SR-SF-1J-[220,260) </a> <a href="89413?version=1&table=AcceptanceSR-SF-1J-[260,inf)forC1C1WWgrid">SR-SF-1J-[260,inf) </a><br/> <li> <b>Efficiency</b> <br/> <a href="89413?version=1&table=EfficiencySR-DF-0J-[100,inf)forC1C1WWgrid">SR-DF-0J-[100,inf) </a> <a href="89413?version=1&table=EfficiencySR-DF-0J-[160,inf)forC1C1WWgrid">SR-DF-0J-[160,inf) </a> <a href="89413?version=1&table=EfficiencySR-DF-0J-[100,120)forC1C1WWgrid">SR-DF-0J-[100,120) </a> <a href="89413?version=1&table=EfficiencySR-DF-0J-[120,160)forC1C1WWgrid">SR-DF-0J-[120,160) </a> <a href="89413?version=1&table=EfficiencySR-DF-0J-[100,105)forC1C1WWgrid">SR-DF-0J-[100,105) </a> <a href="89413?version=1&table=EfficiencySR-DF-0J-[105,110)forC1C1WWgrid">SR-DF-0J-[105,110) </a> <a href="89413?version=1&table=EfficiencySR-DF-0J-[110,120)forC1C1WWgrid">SR-DF-0J-[110,120) </a> <a href="89413?version=1&table=EfficiencySR-DF-0J-[120,140)forC1C1WWgrid">SR-DF-0J-[120,140) </a> <a href="89413?version=1&table=EfficiencySR-DF-0J-[140,160)forC1C1WWgrid">SR-DF-0J-[140,160) </a> <a href="89413?version=1&table=EfficiencySR-DF-0J-[160,180)forC1C1WWgrid">SR-DF-0J-[160,180) </a> <a href="89413?version=1&table=EfficiencySR-DF-0J-[180,220)forC1C1WWgrid">SR-DF-0J-[180,220) </a> <a href="89413?version=1&table=EfficiencySR-DF-0J-[220,260)forC1C1WWgrid">SR-DF-0J-[220,260) </a> <a href="89413?version=1&table=EfficiencySR-DF-0J-[260,inf)forC1C1WWgrid">SR-DF-0J-[260,inf) </a><br/> <a href="89413?version=1&table=EfficiencySR-DF-1J-[100,inf)forC1C1WWgrid">SR-DF-1J-[100,inf) </a> <a href="89413?version=1&table=EfficiencySR-DF-1J-[160,inf)forC1C1WWgrid">SR-DF-1J-[160,inf) </a> <a href="89413?version=1&table=EfficiencySR-DF-1J-[100,120)forC1C1WWgrid">SR-DF-1J-[100,120) </a> <a href="89413?version=1&table=EfficiencySR-DF-1J-[120,160)forC1C1WWgrid">SR-DF-1J-[120,160) </a> <a href="89413?version=1&table=EfficiencySR-DF-1J-[100,105)forC1C1WWgrid">SR-DF-1J-[100,105) </a> <a href="89413?version=1&table=EfficiencySR-DF-1J-[105,110)forC1C1WWgrid">SR-DF-1J-[105,110) </a> <a href="89413?version=1&table=EfficiencySR-DF-1J-[110,120)forC1C1WWgrid">SR-DF-1J-[110,120) </a> <a href="89413?version=1&table=EfficiencySR-DF-1J-[120,140)forC1C1WWgrid">SR-DF-1J-[120,140) </a> <a href="89413?version=1&table=EfficiencySR-DF-1J-[140,160)forC1C1WWgrid">SR-DF-1J-[140,160) </a> <a href="89413?version=1&table=EfficiencySR-DF-1J-[160,180)forC1C1WWgrid">SR-DF-1J-[160,180) </a> <a href="89413?version=1&table=EfficiencySR-DF-1J-[180,220)forC1C1WWgrid">SR-DF-1J-[180,220) </a> <a href="89413?version=1&table=EfficiencySR-DF-1J-[220,260)forC1C1WWgrid">SR-DF-1J-[220,260) </a> <a href="89413?version=1&table=EfficiencySR-DF-1J-[260,inf)forC1C1WWgrid">SR-DF-1J-[260,inf) </a><br/> <a href="89413?version=1&table=EfficiencySR-SF-0J-[100,inf)forC1C1WWgrid">SR-SF-0J-[100,inf) </a> <a href="89413?version=1&table=EfficiencySR-SF-0J-[160,inf)forC1C1WWgrid">SR-SF-0J-[160,inf) </a> <a href="89413?version=1&table=EfficiencySR-SF-0J-[100,120)forC1C1WWgrid">SR-SF-0J-[100,120) </a> <a href="89413?version=1&table=EfficiencySR-SF-0J-[120,160)forC1C1WWgrid">SR-SF-0J-[120,160) </a> <a href="89413?version=1&table=EfficiencySR-SF-0J-[100,105)forC1C1WWgrid">SR-SF-0J-[100,105) </a> <a href="89413?version=1&table=EfficiencySR-SF-0J-[105,110)forC1C1WWgrid">SR-SF-0J-[105,110) </a> <a href="89413?version=1&table=EfficiencySR-SF-0J-[110,120)forC1C1WWgrid">SR-SF-0J-[110,120) </a> <a href="89413?version=1&table=EfficiencySR-SF-0J-[120,140)forC1C1WWgrid">SR-SF-0J-[120,140) </a> <a href="89413?version=1&table=EfficiencySR-SF-0J-[140,160)forC1C1WWgrid">SR-SF-0J-[140,160) </a> <a href="89413?version=1&table=EfficiencySR-SF-0J-[160,180)forC1C1WWgrid">SR-SF-0J-[160,180) </a> <a href="89413?version=1&table=EfficiencySR-SF-0J-[180,220)forC1C1WWgrid">SR-SF-0J-[180,220) </a> <a href="89413?version=1&table=EfficiencySR-SF-0J-[220,260)forC1C1WWgrid">SR-SF-0J-[220,260) </a> <a href="89413?version=1&table=EfficiencySR-SF-0J-[260,inf)forC1C1WWgrid">SR-SF-0J-[260,inf) </a><br/> <a href="89413?version=1&table=EfficiencySR-SF-1J-[100,inf)forC1C1WWgrid">SR-SF-1J-[100,inf) </a> <a href="89413?version=1&table=EfficiencySR-SF-1J-[160,inf)forC1C1WWgrid">SR-SF-1J-[160,inf) </a> <a href="89413?version=1&table=EfficiencySR-SF-1J-[100,120)forC1C1WWgrid">SR-SF-1J-[100,120) </a> <a href="89413?version=1&table=EfficiencySR-SF-1J-[120,160)forC1C1WWgrid">SR-SF-1J-[120,160) </a> <a href="89413?version=1&table=EfficiencySR-SF-1J-[100,105)forC1C1WWgrid">SR-SF-1J-[100,105) </a> <a href="89413?version=1&table=EfficiencySR-SF-1J-[105,110)forC1C1WWgrid">SR-SF-1J-[105,110) </a> <a href="89413?version=1&table=EfficiencySR-SF-1J-[110,120)forC1C1WWgrid">SR-SF-1J-[110,120) </a> <a href="89413?version=1&table=EfficiencySR-SF-1J-[120,140)forC1C1WWgrid">SR-SF-1J-[120,140) </a> <a href="89413?version=1&table=EfficiencySR-SF-1J-[140,160)forC1C1WWgrid">SR-SF-1J-[140,160) </a> <a href="89413?version=1&table=EfficiencySR-SF-1J-[160,180)forC1C1WWgrid">SR-SF-1J-[160,180) </a> <a href="89413?version=1&table=EfficiencySR-SF-1J-[180,220)forC1C1WWgrid">SR-SF-1J-[180,220) </a> <a href="89413?version=1&table=EfficiencySR-SF-1J-[220,260)forC1C1WWgrid">SR-SF-1J-[220,260) </a> <a href="89413?version=1&table=EfficiencySR-SF-1J-[260,inf)forC1C1WWgrid">SR-SF-1J-[260,inf) </a><br/> </ul> <b>Cutflow:</b> <ul> <li><a href="89413?version=1&table=Cutflow1">Cutflow for direct chargino-pair production via W decay $m(\tilde{\chi}^{\pm}_1,\tilde{\chi}^{0}_1)=(300,50) GeV$</a> <li><a href="89413?version=1&table=Cutflow1">Cutflow for direct chargino-pair production via slepton decay $m(\tilde{\chi}^{\pm}_1,\tilde{l},\tilde{\chi}^{0}_1)=(600,300,1) GeV$</a> <li><a href="89413?version=1&table=Cutflow1">Cutflow for direct slepton-pair production $m(\tilde{l},\tilde{\chi}^{0}_1)=(400,200) GeV$</a> </ul> <b>Truth Code snippets</b> are available under "Resources" (purple button on the left)
- - - - - - - - Overview of HEPData Record - - - - - - - - <br/><br/> <b>Background Fit results:</b> <ul> <li><a href="89413?version=1&table=Backgroundfit1">CRs</a> <li><a href="89413?version=1&table=Backgroundfit2">VRs</a> <li><a href="89413?version=1&table=Backgroundfit5">inclusive DF-0J SRs</a> <li><a href="89413?version=1&table=Backgroundfit6">inclusive DF-1J SRs</a> <li><a href="89413?version=1&table=Backgroundfit3">inclusive SF-0J SRs</a> <li><a href="89413?version=1&table=Backgroundfit4">inclusive SF-1J SRs</a> </ul> <b>Kinematic distributions in VRs:</b> <ul> <li><a href="89413?version=1&table=VRkinematics1">$m_{T2}$ in VR-top-low</a> <li><a href="89413?version=1&table=VRkinematics2">$m_{T2}$ in VR-top-high</a> <li><a href="89413?version=1&table=VRkinematics3">$E_T^{miss}$ in VR-WW-0J</a> <li><a href="89413?version=1&table=VRkinematics4">$E_T^{miss}$ in VR-WW-1J</a> <li><a href="89413?version=1&table=VRkinematics5">$E_T^{miss}$ sig in VR-VZ</a> <li><a href="89413?version=1&table=VRkinematics6">$E_T^{miss}$ sig in VR-top-WW</a> </ul> <b>Kinematic distributions in SRs:</b> <ul> <li><a href="89413?version=1&table=SRkinematics1">$m_{T2}$ in SR-SF-0J</a> <li><a href="89413?version=1&table=SRkinematics2">$m_{T2}$ in SR-SF-1J</a> <li><a href="89413?version=1&table=SRkinematics3">$m_{T2}$ in SR-DF-0J</a> <li><a href="89413?version=1&table=SRkinematics4">$m_{T2}$ in SR-DF-1J</a> </ul> <b>Systematic uncertaities:</b> <ul> <li><a href="89413?version=1&table=Systematic uncertainties">dominant systematic uncertainties in the inclusive SRs</a> </ul> <b>Exclusion contours:</b> <ul> <li><a href="89413?version=1&table=Exclusioncontour(obs)1">expected exclusion contour direct chargino-pair production via W decay grid</a> <li><a href="89413?version=1&table=Exclusioncontour(exp)1">observed exclusion contour direct chargino-pair production via W decay grid</a> <li><a href="89413?version=1&table=Exclusioncontour(obs)2">expected exclusion contour direct chargino-pair production via slepton decay grid</a> <li><a href="89413?version=1&table=Exclusioncontour(exp)2">observed exclusion contour direct chargino-pair production via slepton decay grid</a> <li><a href="89413?version=1&table=Exclusioncontour(obs)3">expected exclusion contour direct slepton-pair production grid</a> <li><a href="89413?version=1&table=Exclusioncontour(exp)3">observed exclusion contour direct slepton-pair production grid</a> </ul> <br/><br/><b>AUXILIARY MATERIAL</b><br/> <b>Background Fit in binned SRs:</b> <ul> <li><a href="89413?version=1&table=Backgroundfit7">binned DF-0J SRs</a> <li><a href="89413?version=1&table=Backgroundfit8">binned DF-1J SRs</a> <li><a href="89413?version=1&table=Backgroundfit9">binned SF-0J SRs</a> <li><a href="89413?version=1&table=Backgroundfit10">binned SF-1J SRs</a> </ul> <b>Exclusion contours:</b> <ul> <li><a href="89413?version=1&table=Exclusioncontour(obs)4">expected exclusion contour left-handed slepton-pair production</a> <li><a href="89413?version=1&table=Exclusioncontour(exp)4">observed exclusion contour left-handed slepton-pair production</a> <li><a href="89413?version=1&table=Exclusioncontour(obs)5">expected exclusion contour right-handed slepton-pair production</a> <li><a href="89413?version=1&table=Exclusioncontour(exp)5">observed exclusion contour right-handed slepton-pair production</a> <li><a href="89413?version=1&table=Exclusioncontour(obs)6">expected exclusion contour selectron-pair production</a> <li><a href="89413?version=1&table=Exclusioncontour(exp)6">observed exclusion contour selectron-pair production</a> <li><a href="89413?version=1&table=Exclusioncontour(obs)7">expected exclusion contour left-handed selectron-pair production</a> <li><a href="89413?version=1&table=Exclusioncontour(exp)7">observed exclusion contour left-handed selectron-pair production</a> <li><a href="89413?version=1&table=Exclusioncontour(obs)8">expected exclusion contour right-handed selectron-pair production</a> <li><a href="89413?version=1&table=Exclusioncontour(exp)8">observed exclusion contour right-handed selectron-pair production</a> <li><a href="89413?version=1&table=Exclusioncontour(obs)9">expected exclusion contour smuon-pair production</a> <li><a href="89413?version=1&table=Exclusioncontour(exp)9">observed exclusion contour smuon-pair production</a> <li><a href="89413?version=1&table=Exclusioncontour(obs)10">expected exclusion contour left-handed smuon-pair production</a> <li><a href="89413?version=1&table=Exclusioncontour(exp)10">observed exclusion contour left-handed smuon-pair production</a> <li><a href="89413?version=1&table=Exclusioncontour(obs)11">expected exclusion contour right-handed smuon-pair production</a> <li><a href="89413?version=1&table=Exclusioncontour(exp)11">observed exclusion contour right-handed smuon-pair production</a> </ul> <b>Cross section upper limits:</b> <ul> <li><a href="89413?version=1&table=xsecupperlimits1">upper limits on signal cross section for direct chargino-pair production via W decay</a> <li><a href="89413?version=1&table=xsecupperlimits2">upper limits on signal cross section for direct chargino-pair production via slepton decay</a> <li><a href="89413?version=1&table=xsecupperlimits3">upper limits on signal cross section for direct slepton-pair production</a> </ul> <b>Acceptances and Efficiencies for direct chargino-pair production via W decay grid </b> <ul> <li> <b>Acceptance</b> <br/> <a href="89413?version=1&table=AcceptanceSR-DF-0J-[100,inf)forC1C1WWgrid">SR-DF-0J-[100,inf) </a> <a href="89413?version=1&table=AcceptanceSR-DF-0J-[160,inf)forC1C1WWgrid">SR-DF-0J-[160,inf) </a> <a href="89413?version=1&table=AcceptanceSR-DF-0J-[100,120)forC1C1WWgrid">SR-DF-0J-[100,120) </a> <a href="89413?version=1&table=AcceptanceSR-DF-0J-[120,160)forC1C1WWgrid">SR-DF-0J-[120,160) </a> <a href="89413?version=1&table=AcceptanceSR-DF-0J-[100,105)forC1C1WWgrid">SR-DF-0J-[100,105) </a> <a href="89413?version=1&table=AcceptanceSR-DF-0J-[105,110)forC1C1WWgrid">SR-DF-0J-[105,110) </a> <a href="89413?version=1&table=AcceptanceSR-DF-0J-[110,120)forC1C1WWgrid">SR-DF-0J-[110,120) </a> <a href="89413?version=1&table=AcceptanceSR-DF-0J-[120,140)forC1C1WWgrid">SR-DF-0J-[120,140) </a> <a href="89413?version=1&table=AcceptanceSR-DF-0J-[140,160)forC1C1WWgrid">SR-DF-0J-[140,160) </a> <a href="89413?version=1&table=AcceptanceSR-DF-0J-[160,180)forC1C1WWgrid">SR-DF-0J-[160,180) </a> <a href="89413?version=1&table=AcceptanceSR-DF-0J-[180,220)forC1C1WWgrid">SR-DF-0J-[180,220) </a> <a href="89413?version=1&table=AcceptanceSR-DF-0J-[220,260)forC1C1WWgrid">SR-DF-0J-[220,260) </a> <a href="89413?version=1&table=AcceptanceSR-DF-0J-[260,inf)forC1C1WWgrid">SR-DF-0J-[260,inf) </a><br/> <a href="89413?version=1&table=AcceptanceSR-DF-1J-[100,inf)forC1C1WWgrid">SR-DF-1J-[100,inf) </a> <a href="89413?version=1&table=AcceptanceSR-DF-1J-[160,inf)forC1C1WWgrid">SR-DF-1J-[160,inf) </a> <a href="89413?version=1&table=AcceptanceSR-DF-1J-[100,120)forC1C1WWgrid">SR-DF-1J-[100,120) </a> <a href="89413?version=1&table=AcceptanceSR-DF-1J-[120,160)forC1C1WWgrid">SR-DF-1J-[120,160) </a> <a href="89413?version=1&table=AcceptanceSR-DF-1J-[100,105)forC1C1WWgrid">SR-DF-1J-[100,105) </a> <a href="89413?version=1&table=AcceptanceSR-DF-1J-[105,110)forC1C1WWgrid">SR-DF-1J-[105,110) </a> <a href="89413?version=1&table=AcceptanceSR-DF-1J-[110,120)forC1C1WWgrid">SR-DF-1J-[110,120) </a> <a href="89413?version=1&table=AcceptanceSR-DF-1J-[120,140)forC1C1WWgrid">SR-DF-1J-[120,140) </a> <a href="89413?version=1&table=AcceptanceSR-DF-1J-[140,160)forC1C1WWgrid">SR-DF-1J-[140,160) </a> <a href="89413?version=1&table=AcceptanceSR-DF-1J-[160,180)forC1C1WWgrid">SR-DF-1J-[160,180) </a> <a href="89413?version=1&table=AcceptanceSR-DF-1J-[180,220)forC1C1WWgrid">SR-DF-1J-[180,220) </a> <a href="89413?version=1&table=AcceptanceSR-DF-1J-[220,260)forC1C1WWgrid">SR-DF-1J-[220,260) </a> <a href="89413?version=1&table=AcceptanceSR-DF-1J-[260,inf)forC1C1WWgrid">SR-DF-1J-[260,inf) </a><br/> <a href="89413?version=1&table=AcceptanceSR-SF-0J-[100,inf)forC1C1WWgrid">SR-SF-0J-[100,inf) </a> <a href="89413?version=1&table=AcceptanceSR-SF-0J-[160,inf)forC1C1WWgrid">SR-SF-0J-[160,inf) </a> <a href="89413?version=1&table=AcceptanceSR-SF-0J-[100,120)forC1C1WWgrid">SR-SF-0J-[100,120) </a> <a href="89413?version=1&table=AcceptanceSR-SF-0J-[120,160)forC1C1WWgrid">SR-SF-0J-[120,160) </a> <a href="89413?version=1&table=AcceptanceSR-SF-0J-[100,105)forC1C1WWgrid">SR-SF-0J-[100,105) </a> <a href="89413?version=1&table=AcceptanceSR-SF-0J-[105,110)forC1C1WWgrid">SR-SF-0J-[105,110) </a> <a href="89413?version=1&table=AcceptanceSR-SF-0J-[110,120)forC1C1WWgrid">SR-SF-0J-[110,120) </a> <a href="89413?version=1&table=AcceptanceSR-SF-0J-[120,140)forC1C1WWgrid">SR-SF-0J-[120,140) </a> <a href="89413?version=1&table=AcceptanceSR-SF-0J-[140,160)forC1C1WWgrid">SR-SF-0J-[140,160) </a> <a href="89413?version=1&table=AcceptanceSR-SF-0J-[160,180)forC1C1WWgrid">SR-SF-0J-[160,180) </a> <a href="89413?version=1&table=AcceptanceSR-SF-0J-[180,220)forC1C1WWgrid">SR-SF-0J-[180,220) </a> <a href="89413?version=1&table=AcceptanceSR-SF-0J-[220,260)forC1C1WWgrid">SR-SF-0J-[220,260) </a> <a href="89413?version=1&table=AcceptanceSR-SF-0J-[260,inf)forC1C1WWgrid">SR-SF-0J-[260,inf) </a><br/> <a href="89413?version=1&table=AcceptanceSR-SF-1J-[100,inf)forC1C1WWgrid">SR-SF-1J-[100,inf) </a> <a href="89413?version=1&table=AcceptanceSR-SF-1J-[160,inf)forC1C1WWgrid">SR-SF-1J-[160,inf) </a> <a href="89413?version=1&table=AcceptanceSR-SF-1J-[100,120)forC1C1WWgrid">SR-SF-1J-[100,120) </a> <a href="89413?version=1&table=AcceptanceSR-SF-1J-[120,160)forC1C1WWgrid">SR-SF-1J-[120,160) </a> <a href="89413?version=1&table=AcceptanceSR-SF-1J-[100,105)forC1C1WWgrid">SR-SF-1J-[100,105) </a> <a href="89413?version=1&table=AcceptanceSR-SF-1J-[105,110)forC1C1WWgrid">SR-SF-1J-[105,110) </a> <a href="89413?version=1&table=AcceptanceSR-SF-1J-[110,120)forC1C1WWgrid">SR-SF-1J-[110,120) </a> <a href="89413?version=1&table=AcceptanceSR-SF-1J-[120,140)forC1C1WWgrid">SR-SF-1J-[120,140) </a> <a href="89413?version=1&table=AcceptanceSR-SF-1J-[140,160)forC1C1WWgrid">SR-SF-1J-[140,160) </a> <a href="89413?version=1&table=AcceptanceSR-SF-1J-[160,180)forC1C1WWgrid">SR-SF-1J-[160,180) </a> <a href="89413?version=1&table=AcceptanceSR-SF-1J-[180,220)forC1C1WWgrid">SR-SF-1J-[180,220) </a> <a href="89413?version=1&table=AcceptanceSR-SF-1J-[220,260)forC1C1WWgrid">SR-SF-1J-[220,260) </a> <a href="89413?version=1&table=AcceptanceSR-SF-1J-[260,inf)forC1C1WWgrid">SR-SF-1J-[260,inf) </a><br/> <li> <b>Efficiency</b> <br/> <a href="89413?version=1&table=EfficiencySR-DF-0J-[100,inf)forC1C1WWgrid">SR-DF-0J-[100,inf) </a> <a href="89413?version=1&table=EfficiencySR-DF-0J-[160,inf)forC1C1WWgrid">SR-DF-0J-[160,inf) </a> <a href="89413?version=1&table=EfficiencySR-DF-0J-[100,120)forC1C1WWgrid">SR-DF-0J-[100,120) </a> <a href="89413?version=1&table=EfficiencySR-DF-0J-[120,160)forC1C1WWgrid">SR-DF-0J-[120,160) </a> <a href="89413?version=1&table=EfficiencySR-DF-0J-[100,105)forC1C1WWgrid">SR-DF-0J-[100,105) </a> <a href="89413?version=1&table=EfficiencySR-DF-0J-[105,110)forC1C1WWgrid">SR-DF-0J-[105,110) </a> <a href="89413?version=1&table=EfficiencySR-DF-0J-[110,120)forC1C1WWgrid">SR-DF-0J-[110,120) </a> <a href="89413?version=1&table=EfficiencySR-DF-0J-[120,140)forC1C1WWgrid">SR-DF-0J-[120,140) </a> <a href="89413?version=1&table=EfficiencySR-DF-0J-[140,160)forC1C1WWgrid">SR-DF-0J-[140,160) </a> <a href="89413?version=1&table=EfficiencySR-DF-0J-[160,180)forC1C1WWgrid">SR-DF-0J-[160,180) </a> <a href="89413?version=1&table=EfficiencySR-DF-0J-[180,220)forC1C1WWgrid">SR-DF-0J-[180,220) </a> <a href="89413?version=1&table=EfficiencySR-DF-0J-[220,260)forC1C1WWgrid">SR-DF-0J-[220,260) </a> <a href="89413?version=1&table=EfficiencySR-DF-0J-[260,inf)forC1C1WWgrid">SR-DF-0J-[260,inf) </a><br/> <a href="89413?version=1&table=EfficiencySR-DF-1J-[100,inf)forC1C1WWgrid">SR-DF-1J-[100,inf) </a> <a href="89413?version=1&table=EfficiencySR-DF-1J-[160,inf)forC1C1WWgrid">SR-DF-1J-[160,inf) </a> <a href="89413?version=1&table=EfficiencySR-DF-1J-[100,120)forC1C1WWgrid">SR-DF-1J-[100,120) </a> <a href="89413?version=1&table=EfficiencySR-DF-1J-[120,160)forC1C1WWgrid">SR-DF-1J-[120,160) </a> <a href="89413?version=1&table=EfficiencySR-DF-1J-[100,105)forC1C1WWgrid">SR-DF-1J-[100,105) </a> <a href="89413?version=1&table=EfficiencySR-DF-1J-[105,110)forC1C1WWgrid">SR-DF-1J-[105,110) </a> <a href="89413?version=1&table=EfficiencySR-DF-1J-[110,120)forC1C1WWgrid">SR-DF-1J-[110,120) </a> <a href="89413?version=1&table=EfficiencySR-DF-1J-[120,140)forC1C1WWgrid">SR-DF-1J-[120,140) </a> <a href="89413?version=1&table=EfficiencySR-DF-1J-[140,160)forC1C1WWgrid">SR-DF-1J-[140,160) </a> <a href="89413?version=1&table=EfficiencySR-DF-1J-[160,180)forC1C1WWgrid">SR-DF-1J-[160,180) </a> <a href="89413?version=1&table=EfficiencySR-DF-1J-[180,220)forC1C1WWgrid">SR-DF-1J-[180,220) </a> <a href="89413?version=1&table=EfficiencySR-DF-1J-[220,260)forC1C1WWgrid">SR-DF-1J-[220,260) </a> <a href="89413?version=1&table=EfficiencySR-DF-1J-[260,inf)forC1C1WWgrid">SR-DF-1J-[260,inf) </a><br/> <a href="89413?version=1&table=EfficiencySR-SF-0J-[100,inf)forC1C1WWgrid">SR-SF-0J-[100,inf) </a> <a href="89413?version=1&table=EfficiencySR-SF-0J-[160,inf)forC1C1WWgrid">SR-SF-0J-[160,inf) </a> <a href="89413?version=1&table=EfficiencySR-SF-0J-[100,120)forC1C1WWgrid">SR-SF-0J-[100,120) </a> <a href="89413?version=1&table=EfficiencySR-SF-0J-[120,160)forC1C1WWgrid">SR-SF-0J-[120,160) </a> <a href="89413?version=1&table=EfficiencySR-SF-0J-[100,105)forC1C1WWgrid">SR-SF-0J-[100,105) </a> <a href="89413?version=1&table=EfficiencySR-SF-0J-[105,110)forC1C1WWgrid">SR-SF-0J-[105,110) </a> <a href="89413?version=1&table=EfficiencySR-SF-0J-[110,120)forC1C1WWgrid">SR-SF-0J-[110,120) </a> <a href="89413?version=1&table=EfficiencySR-SF-0J-[120,140)forC1C1WWgrid">SR-SF-0J-[120,140) </a> <a href="89413?version=1&table=EfficiencySR-SF-0J-[140,160)forC1C1WWgrid">SR-SF-0J-[140,160) </a> <a href="89413?version=1&table=EfficiencySR-SF-0J-[160,180)forC1C1WWgrid">SR-SF-0J-[160,180) </a> <a href="89413?version=1&table=EfficiencySR-SF-0J-[180,220)forC1C1WWgrid">SR-SF-0J-[180,220) </a> <a href="89413?version=1&table=EfficiencySR-SF-0J-[220,260)forC1C1WWgrid">SR-SF-0J-[220,260) </a> <a href="89413?version=1&table=EfficiencySR-SF-0J-[260,inf)forC1C1WWgrid">SR-SF-0J-[260,inf) </a><br/> <a href="89413?version=1&table=EfficiencySR-SF-1J-[100,inf)forC1C1WWgrid">SR-SF-1J-[100,inf) </a> <a href="89413?version=1&table=EfficiencySR-SF-1J-[160,inf)forC1C1WWgrid">SR-SF-1J-[160,inf) </a> <a href="89413?version=1&table=EfficiencySR-SF-1J-[100,120)forC1C1WWgrid">SR-SF-1J-[100,120) </a> <a href="89413?version=1&table=EfficiencySR-SF-1J-[120,160)forC1C1WWgrid">SR-SF-1J-[120,160) </a> <a href="89413?version=1&table=EfficiencySR-SF-1J-[100,105)forC1C1WWgrid">SR-SF-1J-[100,105) </a> <a href="89413?version=1&table=EfficiencySR-SF-1J-[105,110)forC1C1WWgrid">SR-SF-1J-[105,110) </a> <a href="89413?version=1&table=EfficiencySR-SF-1J-[110,120)forC1C1WWgrid">SR-SF-1J-[110,120) </a> <a href="89413?version=1&table=EfficiencySR-SF-1J-[120,140)forC1C1WWgrid">SR-SF-1J-[120,140) </a> <a href="89413?version=1&table=EfficiencySR-SF-1J-[140,160)forC1C1WWgrid">SR-SF-1J-[140,160) </a> <a href="89413?version=1&table=EfficiencySR-SF-1J-[160,180)forC1C1WWgrid">SR-SF-1J-[160,180) </a> <a href="89413?version=1&table=EfficiencySR-SF-1J-[180,220)forC1C1WWgrid">SR-SF-1J-[180,220) </a> <a href="89413?version=1&table=EfficiencySR-SF-1J-[220,260)forC1C1WWgrid">SR-SF-1J-[220,260) </a> <a href="89413?version=1&table=EfficiencySR-SF-1J-[260,inf)forC1C1WWgrid">SR-SF-1J-[260,inf) </a><br/> </ul> <b>Cutflow:</b> <ul> <li><a href="89413?version=1&table=Cutflow1">Cutflow for direct chargino-pair production via W decay $m(\tilde{\chi}^{\pm}_1,\tilde{\chi}^{0}_1)=(300,50) GeV$</a> <li><a href="89413?version=1&table=Cutflow1">Cutflow for direct chargino-pair production via slepton decay $m(\tilde{\chi}^{\pm}_1,\tilde{l},\tilde{\chi}^{0}_1)=(600,300,1) GeV$</a> <li><a href="89413?version=1&table=Cutflow1">Cutflow for direct slepton-pair production $m(\tilde{l},\tilde{\chi}^{0}_1)=(400,200) GeV$</a> </ul> <b>SimpleAnalysis framework implementation</b> of the search SRs is available under "Resources" (purple button on the left)
- - - - - - - - Overview of HEPData Record - - - - - - - - <br/><br/> <b>Background Fit results:</b> <ul> <li><a href="89413?version=3&table=Background fit 1">CRs</a> <li><a href="89413?version=3&table=Background fit 2">VRs</a> <li><a href="89413?version=3&table=Background fit 5">inclusive DF-0J SRs</a> <li><a href="89413?version=3&table=Background fit 6">inclusive DF-1J SRs</a> <li><a href="89413?version=3&table=Background fit 3">inclusive SF-0J SRs</a> <li><a href="89413?version=3&table=Background fit 4">inclusive SF-1J SRs</a> </ul> <b>Kinematic distributions in VRs:</b> <ul> <li><a href="89413?version=3&table=VR kinematics 1">$m_{T2}$ in VR-top-low</a> <li><a href="89413?version=3&table=VR kinematics 2">$m_{T2}$ in VR-top-high</a> <li><a href="89413?version=3&table=VR kinematics 3">$E_T^{miss}$ in VR-WW-0J</a> <li><a href="89413?version=3&table=VR kinematics 4">$E_T^{miss}$ in VR-WW-1J</a> <li><a href="89413?version=3&table=VR kinematics 5">$E_T^{miss}$ sig in VR-VZ</a> <li><a href="89413?version=3&table=VR kinematics 6">$E_T^{miss}$ sig in VR-top-WW</a> </ul> <b>Kinematic distributions in SRs:</b> <ul> <li><a href="89413?version=3&table=SR kinematics 1">$m_{T2}$ in SR-SF-0J</a> <li><a href="89413?version=3&table=SR kinematics 2">$m_{T2}$ in SR-SF-1J</a> <li><a href="89413?version=3&table=SR kinematics 3">$m_{T2}$ in SR-DF-0J</a> <li><a href="89413?version=3&table=SR kinematics 4">$m_{T2}$ in SR-DF-1J</a> </ul> <b>Systematic uncertaities:</b> <ul> <li><a href="89413?version=3&table=Systematic uncertainties">dominant systematic uncertainties in the inclusive SRs</a> </ul> <b>Exclusion contours:</b> <ul> <li><a href="89413?version=3&table=Exclusion contour (exp) 1">expected exclusion contour direct chargino-pair production via W decay grid</a> <li><a href="89413?version=3&table=Exclusion contour (obs) 1">observed exclusion contour direct chargino-pair production via W decay grid</a> <li><a href="89413?version=3&table=Exclusion contour (exp) 2">expected exclusion contour direct chargino-pair production via slepton decay grid</a> <li><a href="89413?version=3&table=Exclusion contour (obs) 2">observed exclusion contour direct chargino-pair production via slepton decay grid</a> <li><a href="89413?version=3&table=Exclusion contour (exp) 3">expected exclusion contour direct slepton-pair production grid</a> <li><a href="89413?version=3&table=Exclusion contour (obs) 3">observed exclusion contour direct slepton-pair production grid</a> </ul> <br/><br/><b>AUXILIARY MATERIAL</b><br/> <b>Background Fit in binned SRs:</b> <ul> <li><a href="89413?version=3&table=Background fit 7">binned DF-0J SRs</a> <li><a href="89413?version=3&table=Background fit 8">binned DF-1J SRs</a> <li><a href="89413?version=3&table=Background fit 9">binned SF-0J SRs</a> <li><a href="89413?version=3&table=Background fit 10">binned SF-1J SRs</a> </ul> <b>Exclusion contours:</b> <ul> <li><a href="89413?version=3&table=Exclusion contour (exp) 4">expected exclusion contour left-handed slepton-pair production</a> <li><a href="89413?version=3&table=Exclusion contour (obs) 4">observed exclusion contour left-handed slepton-pair production</a> <li><a href="89413?version=3&table=Exclusion contour (exp) 5">expected exclusion contour right-handed slepton-pair production</a> <li><a href="89413?version=3&table=Exclusion contour (obs) 5">observed exclusion contour right-handed slepton-pair production</a> <li><a href="89413?version=3&table=Exclusion contour (exp) 6">expected exclusion contour selectron-pair production</a> <li><a href="89413?version=3&table=Exclusion contour (obs) 6">observed exclusion contour selectron-pair production</a> <li><a href="89413?version=3&table=Exclusion contour (exp) 7">expected exclusion contour left-handed selectron-pair production</a> <li><a href="89413?version=3&table=Exclusion contour (obs) 7">observed exclusion contour left-handed selectron-pair production</a> <li><a href="89413?version=3&table=Exclusion contour (exp) 8">expected exclusion contour right-handed selectron-pair production</a> <li><a href="89413?version=3&table=Exclusion contour (obs) 8">observed exclusion contour right-handed selectron-pair production</a> <li><a href="89413?version=3&table=Exclusion contour (exp) 9">expected exclusion contour smuon-pair production</a> <li><a href="89413?version=3&table=Exclusion contour (obs) 9">observed exclusion contour smuon-pair production</a> <li><a href="89413?version=3&table=Exclusion contour (exp) 10">expected exclusion contour left-handed smuon-pair production</a> <li><a href="89413?version=3&table=Exclusion contour (obs) 10">observed exclusion contour left-handed smuon-pair production</a> <li><a href="89413?version=3&table=Exclusion contour (exp) 11">expected exclusion contour right-handed smuon-pair production</a> <li><a href="89413?version=3&table=Exclusion contour (obs) 11">observed exclusion contour right-handed smuon-pair production</a> </ul> <b>Cross section upper limits:</b> <ul> <li><a href="89413?version=3&table=xsec upper limits 1">upper limits on signal cross section for direct chargino-pair production via W decay</a> <li><a href="89413?version=3&table=xsec upper limits 2">upper limits on signal cross section for direct chargino-pair production via slepton decay</a> <li><a href="89413?version=3&table=xsec upper limits 3">upper limits on signal cross section for direct slepton-pair production</a> </ul> <b>Acceptances and Efficiencies for direct chargino-pair production via W decay grid </b> <ul> <li> <b>Acceptance</b> <br/> <a href="89413?version=3&table=Acceptance SR-DF-0J-[100,inf) for C1C1WW grid">SR-DF-0J-[100,inf) </a> <a href="89413?version=3&table=Acceptance SR-DF-0J-[160,inf) for C1C1WW grid">SR-DF-0J-[160,inf) </a> <a href="89413?version=3&table=Acceptance SR-DF-0J-[100,120) for C1C1WW grid">SR-DF-0J-[100,120) </a> <a href="89413?version=3&table=Acceptance SR-DF-0J-[120,160) for C1C1WW grid">SR-DF-0J-[120,160) </a> <a href="89413?version=3&table=Acceptance SR-DF-0J-[100,105) for C1C1WW grid">SR-DF-0J-[100,105) </a> <a href="89413?version=3&table=Acceptance SR-DF-0J-[105,110) for C1C1WW grid">SR-DF-0J-[105,110) </a> <a href="89413?version=3&table=Acceptance SR-DF-0J-[110,120) for C1C1WW grid">SR-DF-0J-[110,120) </a> <a href="89413?version=3&table=Acceptance SR-DF-0J-[120,140) for C1C1WW grid">SR-DF-0J-[120,140) </a> <a href="89413?version=3&table=Acceptance SR-DF-0J-[140,160) for C1C1WW grid">SR-DF-0J-[140,160) </a> <a href="89413?version=3&table=Acceptance SR-DF-0J-[160,180) for C1C1WW grid">SR-DF-0J-[160,180) </a> <a href="89413?version=3&table=Acceptance SR-DF-0J-[180,220) for C1C1WW grid">SR-DF-0J-[180,220) </a> <a href="89413?version=3&table=Acceptance SR-DF-0J-[220,260) for C1C1WW grid">SR-DF-0J-[220,260) </a> <a href="89413?version=3&table=Acceptance SR-DF-0J-[260,inf) for C1C1WW grid">SR-DF-0J-[260,inf) </a><br/> <a href="89413?version=3&table=Acceptance SR-DF-1J-[100,inf) for C1C1WW grid">SR-DF-1J-[100,inf) </a> <a href="89413?version=3&table=Acceptance SR-DF-1J-[160,inf) for C1C1WW grid">SR-DF-1J-[160,inf) </a> <a href="89413?version=3&table=Acceptance SR-DF-1J-[100,120) for C1C1WW grid">SR-DF-1J-[100,120) </a> <a href="89413?version=3&table=Acceptance SR-DF-1J-[120,160) for C1C1WW grid">SR-DF-1J-[120,160) </a> <a href="89413?version=3&table=Acceptance SR-DF-1J-[100,105) for C1C1WW grid">SR-DF-1J-[100,105) </a> <a href="89413?version=3&table=Acceptance SR-DF-1J-[105,110) for C1C1WW grid">SR-DF-1J-[105,110) </a> <a href="89413?version=3&table=Acceptance SR-DF-1J-[110,120) for C1C1WW grid">SR-DF-1J-[110,120) </a> <a href="89413?version=3&table=Acceptance SR-DF-1J-[120,140) for C1C1WW grid">SR-DF-1J-[120,140) </a> <a href="89413?version=3&table=Acceptance SR-DF-1J-[140,160) for C1C1WW grid">SR-DF-1J-[140,160) </a> <a href="89413?version=3&table=Acceptance SR-DF-1J-[160,180) for C1C1WW grid">SR-DF-1J-[160,180) </a> <a href="89413?version=3&table=Acceptance SR-DF-1J-[180,220) for C1C1WW grid">SR-DF-1J-[180,220) </a> <a href="89413?version=3&table=Acceptance SR-DF-1J-[220,260) for C1C1WW grid">SR-DF-1J-[220,260) </a> <a href="89413?version=3&table=Acceptance SR-DF-1J-[260,inf) for C1C1WW grid">SR-DF-1J-[260,inf) </a><br/> <a href="89413?version=3&table=Acceptance SR-SF-0J-[100,inf) for C1C1WW grid">SR-SF-0J-[100,inf) </a> <a href="89413?version=3&table=Acceptance SR-SF-0J-[160,inf) for C1C1WW grid">SR-SF-0J-[160,inf) </a> <a href="89413?version=3&table=Acceptance SR-SF-0J-[100,120) for C1C1WW grid">SR-SF-0J-[100,120) </a> <a href="89413?version=3&table=Acceptance SR-SF-0J-[120,160) for C1C1WW grid">SR-SF-0J-[120,160) </a> <a href="89413?version=3&table=Acceptance SR-SF-0J-[100,105) for C1C1WW grid">SR-SF-0J-[100,105) </a> <a href="89413?version=3&table=Acceptance SR-SF-0J-[105,110) for C1C1WW grid">SR-SF-0J-[105,110) </a> <a href="89413?version=3&table=Acceptance SR-SF-0J-[110,120) for C1C1WW grid">SR-SF-0J-[110,120) </a> <a href="89413?version=3&table=Acceptance SR-SF-0J-[120,140) for C1C1WW grid">SR-SF-0J-[120,140) </a> <a href="89413?version=3&table=Acceptance SR-SF-0J-[140,160) for C1C1WW grid">SR-SF-0J-[140,160) </a> <a href="89413?version=3&table=Acceptance SR-SF-0J-[160,180) for C1C1WW grid">SR-SF-0J-[160,180) </a> <a href="89413?version=3&table=Acceptance SR-SF-0J-[180,220) for C1C1WW grid">SR-SF-0J-[180,220) </a> <a href="89413?version=3&table=Acceptance SR-SF-0J-[220,260) for C1C1WW grid">SR-SF-0J-[220,260) </a> <a href="89413?version=3&table=Acceptance SR-SF-0J-[260,inf) for C1C1WW grid">SR-SF-0J-[260,inf) </a><br/> <a href="89413?version=3&table=Acceptance SR-SF-1J-[100,inf) for C1C1WW grid">SR-SF-1J-[100,inf) </a> <a href="89413?version=3&table=Acceptance SR-SF-1J-[160,inf) for C1C1WW grid">SR-SF-1J-[160,inf) </a> <a href="89413?version=3&table=Acceptance SR-SF-1J-[100,120) for C1C1WW grid">SR-SF-1J-[100,120) </a> <a href="89413?version=3&table=Acceptance SR-SF-1J-[120,160) for C1C1WW grid">SR-SF-1J-[120,160) </a> <a href="89413?version=3&table=Acceptance SR-SF-1J-[100,105) for C1C1WW grid">SR-SF-1J-[100,105) </a> <a href="89413?version=3&table=Acceptance SR-SF-1J-[105,110) for C1C1WW grid">SR-SF-1J-[105,110) </a> <a href="89413?version=3&table=Acceptance SR-SF-1J-[110,120) for C1C1WW grid">SR-SF-1J-[110,120) </a> <a href="89413?version=3&table=Acceptance SR-SF-1J-[120,140) for C1C1WW grid">SR-SF-1J-[120,140) </a> <a href="89413?version=3&table=Acceptance SR-SF-1J-[140,160) for C1C1WW grid">SR-SF-1J-[140,160) </a> <a href="89413?version=3&table=Acceptance SR-SF-1J-[160,180) for C1C1WW grid">SR-SF-1J-[160,180) </a> <a href="89413?version=3&table=Acceptance SR-SF-1J-[180,220) for C1C1WW grid">SR-SF-1J-[180,220) </a> <a href="89413?version=3&table=Acceptance SR-SF-1J-[220,260) for C1C1WW grid">SR-SF-1J-[220,260) </a> <a href="89413?version=3&table=Acceptance SR-SF-1J-[260,inf) for C1C1WW grid">SR-SF-1J-[260,inf) </a><br/> <li> <b>Efficiency</b> <br/> <a href="89413?version=3&table=Efficiency SR-DF-0J-[100,inf) for C1C1WW grid">SR-DF-0J-[100,inf) </a> <a href="89413?version=3&table=Efficiency SR-DF-0J-[160,inf) for C1C1WW grid">SR-DF-0J-[160,inf) </a> <a href="89413?version=3&table=Efficiency SR-DF-0J-[100,120) for C1C1WW grid">SR-DF-0J-[100,120) </a> <a href="89413?version=3&table=Efficiency SR-DF-0J-[120,160) for C1C1WW grid">SR-DF-0J-[120,160) </a> <a href="89413?version=3&table=Efficiency SR-DF-0J-[100,105) for C1C1WW grid">SR-DF-0J-[100,105) </a> <a href="89413?version=3&table=Efficiency SR-DF-0J-[105,110) for C1C1WW grid">SR-DF-0J-[105,110) </a> <a href="89413?version=3&table=Efficiency SR-DF-0J-[110,120) for C1C1WW grid">SR-DF-0J-[110,120) </a> <a href="89413?version=3&table=Efficiency SR-DF-0J-[120,140) for C1C1WW grid">SR-DF-0J-[120,140) </a> <a href="89413?version=3&table=Efficiency SR-DF-0J-[140,160) for C1C1WW grid">SR-DF-0J-[140,160) </a> <a href="89413?version=3&table=Efficiency SR-DF-0J-[160,180) for C1C1WW grid">SR-DF-0J-[160,180) </a> <a href="89413?version=3&table=Efficiency SR-DF-0J-[180,220) for C1C1WW grid">SR-DF-0J-[180,220) </a> <a href="89413?version=3&table=Efficiency SR-DF-0J-[220,260) for C1C1WW grid">SR-DF-0J-[220,260) </a> <a href="89413?version=3&table=Efficiency SR-DF-0J-[260,inf) for C1C1WW grid">SR-DF-0J-[260,inf) </a><br/> <a href="89413?version=3&table=Efficiency SR-DF-1J-[100,inf) for C1C1WW grid">SR-DF-1J-[100,inf) </a> <a href="89413?version=3&table=Efficiency SR-DF-1J-[160,inf) for C1C1WW grid">SR-DF-1J-[160,inf) </a> <a href="89413?version=3&table=Efficiency SR-DF-1J-[100,120) for C1C1WW grid">SR-DF-1J-[100,120) </a> <a href="89413?version=3&table=Efficiency SR-DF-1J-[120,160) for C1C1WW grid">SR-DF-1J-[120,160) </a> <a href="89413?version=3&table=Efficiency SR-DF-1J-[100,105) for C1C1WW grid">SR-DF-1J-[100,105) </a> <a href="89413?version=3&table=Efficiency SR-DF-1J-[105,110) for C1C1WW grid">SR-DF-1J-[105,110) </a> <a href="89413?version=3&table=Efficiency SR-DF-1J-[110,120) for C1C1WW grid">SR-DF-1J-[110,120) </a> <a href="89413?version=3&table=Efficiency SR-DF-1J-[120,140) for C1C1WW grid">SR-DF-1J-[120,140) </a> <a href="89413?version=3&table=Efficiency SR-DF-1J-[140,160) for C1C1WW grid">SR-DF-1J-[140,160) </a> <a href="89413?version=3&table=Efficiency SR-DF-1J-[160,180) for C1C1WW grid">SR-DF-1J-[160,180) </a> <a href="89413?version=3&table=Efficiency SR-DF-1J-[180,220) for C1C1WW grid">SR-DF-1J-[180,220) </a> <a href="89413?version=3&table=Efficiency SR-DF-1J-[220,260) for C1C1WW grid">SR-DF-1J-[220,260) </a> <a href="89413?version=3&table=Efficiency SR-DF-1J-[260,inf) for C1C1WW grid">SR-DF-1J-[260,inf) </a><br/> <a href="89413?version=3&table=Efficiency SR-SF-0J-[100,inf) for C1C1WW grid">SR-SF-0J-[100,inf) </a> <a href="89413?version=3&table=Efficiency SR-SF-0J-[160,inf) for C1C1WW grid">SR-SF-0J-[160,inf) </a> <a href="89413?version=3&table=Efficiency SR-SF-0J-[100,120) for C1C1WW grid">SR-SF-0J-[100,120) </a> <a href="89413?version=3&table=Efficiency SR-SF-0J-[120,160) for C1C1WW grid">SR-SF-0J-[120,160) </a> <a href="89413?version=3&table=Efficiency SR-SF-0J-[100,105) for C1C1WW grid">SR-SF-0J-[100,105) </a> <a href="89413?version=3&table=Efficiency SR-SF-0J-[105,110) for C1C1WW grid">SR-SF-0J-[105,110) </a> <a href="89413?version=3&table=Efficiency SR-SF-0J-[110,120) for C1C1WW grid">SR-SF-0J-[110,120) </a> <a href="89413?version=3&table=Efficiency SR-SF-0J-[120,140) for C1C1WW grid">SR-SF-0J-[120,140) </a> <a href="89413?version=3&table=Efficiency SR-SF-0J-[140,160) for C1C1WW grid">SR-SF-0J-[140,160) </a> <a href="89413?version=3&table=Efficiency SR-SF-0J-[160,180) for C1C1WW grid">SR-SF-0J-[160,180) </a> <a href="89413?version=3&table=Efficiency SR-SF-0J-[180,220) for C1C1WW grid">SR-SF-0J-[180,220) </a> <a href="89413?version=3&table=Efficiency SR-SF-0J-[220,260) for C1C1WW grid">SR-SF-0J-[220,260) </a> <a href="89413?version=3&table=Efficiency SR-SF-0J-[260,inf) for C1C1WW grid">SR-SF-0J-[260,inf) </a><br/> <a href="89413?version=3&table=Efficiency SR-SF-1J-[100,inf) for C1C1WW grid">SR-SF-1J-[100,inf) </a> <a href="89413?version=3&table=Efficiency SR-SF-1J-[160,inf) for C1C1WW grid">SR-SF-1J-[160,inf) </a> <a href="89413?version=3&table=Efficiency SR-SF-1J-[100,120) for C1C1WW grid">SR-SF-1J-[100,120) </a> <a href="89413?version=3&table=Efficiency SR-SF-1J-[120,160) for C1C1WW grid">SR-SF-1J-[120,160) </a> <a href="89413?version=3&table=Efficiency SR-SF-1J-[100,105) for C1C1WW grid">SR-SF-1J-[100,105) </a> <a href="89413?version=3&table=Efficiency SR-SF-1J-[105,110) for C1C1WW grid">SR-SF-1J-[105,110) </a> <a href="89413?version=3&table=Efficiency SR-SF-1J-[110,120) for C1C1WW grid">SR-SF-1J-[110,120) </a> <a href="89413?version=3&table=Efficiency SR-SF-1J-[120,140) for C1C1WW grid">SR-SF-1J-[120,140) </a> <a href="89413?version=3&table=Efficiency SR-SF-1J-[140,160) for C1C1WW grid">SR-SF-1J-[140,160) </a> <a href="89413?version=3&table=Efficiency SR-SF-1J-[160,180) for C1C1WW grid">SR-SF-1J-[160,180) </a> <a href="89413?version=3&table=Efficiency SR-SF-1J-[180,220) for C1C1WW grid">SR-SF-1J-[180,220) </a> <a href="89413?version=3&table=Efficiency SR-SF-1J-[220,260) for C1C1WW grid">SR-SF-1J-[220,260) </a> <a href="89413?version=3&table=Efficiency SR-SF-1J-[260,inf) for C1C1WW grid">SR-SF-1J-[260,inf) </a><br/> </ul> <b>Cutflow:</b> <ul> <li><a href="89413?version=3&table=Cutflow 1">Cutflow for direct chargino-pair production via W decay $m(\tilde{\chi}^{\pm}_1,\tilde{\chi}^{0}_1)=(300,50) GeV$</a> <li><a href="89413?version=3&table=Cutflow 2">Cutflow for direct chargino-pair production via slepton decay $m(\tilde{\chi}^{\pm}_1,\tilde{l},\tilde{\chi}^{0}_1)=(600,300,1) GeV$</a> <li><a href="89413?version=3&table=Cutflow 3">Cutflow for direct slepton-pair production $m(\tilde{l},\tilde{\chi}^{0}_1)=(400,200) GeV$</a> </ul> <b>SimpleAnalysis framework implementation</b> of the search SRs is available under "Resources" (purple button on the left)
- - - - - - - - Overview of HEPData Record - - - - - - - - <br/><br/> <b>Background Fit results:</b> <ul> <li><a href="89413?version=4&table=Background fit 1">CRs</a> <li><a href="89413?version=4&table=Background fit 2">VRs</a> <li><a href="89413?version=4&table=Background fit 5">inclusive DF-0J SRs</a> <li><a href="89413?version=4&table=Background fit 6">inclusive DF-1J SRs</a> <li><a href="89413?version=4&table=Background fit 3">inclusive SF-0J SRs</a> <li><a href="89413?version=4&table=Background fit 4">inclusive SF-1J SRs</a> </ul> <b>Kinematic distributions in VRs:</b> <ul> <li><a href="89413?version=4&table=VR kinematics 1">$m_{T2}$ in VR-top-low</a> <li><a href="89413?version=4&table=VR kinematics 2">$m_{T2}$ in VR-top-high</a> <li><a href="89413?version=4&table=VR kinematics 3">$E_T^{miss}$ in VR-WW-0J</a> <li><a href="89413?version=4&table=VR kinematics 4">$E_T^{miss}$ in VR-WW-1J</a> <li><a href="89413?version=4&table=VR kinematics 5">$E_T^{miss}$ sig in VR-VZ</a> <li><a href="89413?version=4&table=VR kinematics 6">$E_T^{miss}$ sig in VR-top-WW</a> </ul> <b>Kinematic distributions in SRs:</b> <ul> <li><a href="89413?version=4&table=SR kinematics 1">$m_{T2}$ in SR-SF-0J</a> <li><a href="89413?version=4&table=SR kinematics 2">$m_{T2}$ in SR-SF-1J</a> <li><a href="89413?version=4&table=SR kinematics 3">$m_{T2}$ in SR-DF-0J</a> <li><a href="89413?version=4&table=SR kinematics 4">$m_{T2}$ in SR-DF-1J</a> </ul> <b>Systematic uncertaities:</b> <ul> <li><a href="89413?version=4&table=Systematic uncertainties">dominant systematic uncertainties in the inclusive SRs</a> </ul> <b>Exclusion contours:</b> <ul> <li><a href="89413?version=4&table=Exclusion contour (exp) 1">expected exclusion contour direct chargino-pair production via W decay grid</a> <li><a href="89413?version=4&table=Exclusion contour (obs) 1">observed exclusion contour direct chargino-pair production via W decay grid</a> <li><a href="89413?version=4&table=Exclusion contour (exp) 2">expected exclusion contour direct chargino-pair production via slepton decay grid</a> <li><a href="89413?version=4&table=Exclusion contour (obs) 2">observed exclusion contour direct chargino-pair production via slepton decay grid</a> <li><a href="89413?version=4&table=Exclusion contour (exp) 3">expected exclusion contour direct slepton-pair production grid</a> <li><a href="89413?version=4&table=Exclusion contour (obs) 3">observed exclusion contour direct slepton-pair production grid</a> </ul> <br/><br/><b>AUXILIARY MATERIAL</b><br/> <b>Background Fit in binned SRs:</b> <ul> <li><a href="89413?version=4&table=Background fit 7">binned DF-0J SRs</a> <li><a href="89413?version=4&table=Background fit 8">binned DF-1J SRs</a> <li><a href="89413?version=4&table=Background fit 9">binned SF-0J SRs</a> <li><a href="89413?version=4&table=Background fit 10">binned SF-1J SRs</a> </ul> <b>Exclusion contours:</b> <ul> <li><a href="89413?version=4&table=Exclusion contour (exp) 4">expected exclusion contour left-handed slepton-pair production</a> <li><a href="89413?version=4&table=Exclusion contour (obs) 4">observed exclusion contour left-handed slepton-pair production</a> <li><a href="89413?version=4&table=Exclusion contour (exp) 5">expected exclusion contour right-handed slepton-pair production</a> <li><a href="89413?version=4&table=Exclusion contour (obs) 5">observed exclusion contour right-handed slepton-pair production</a> <li><a href="89413?version=4&table=Exclusion contour (exp) 6">expected exclusion contour selectron-pair production</a> <li><a href="89413?version=4&table=Exclusion contour (obs) 6">observed exclusion contour selectron-pair production</a> <li><a href="89413?version=4&table=Exclusion contour (exp) 7">expected exclusion contour left-handed selectron-pair production</a> <li><a href="89413?version=4&table=Exclusion contour (obs) 7">observed exclusion contour left-handed selectron-pair production</a> <li><a href="89413?version=4&table=Exclusion contour (exp) 8">expected exclusion contour right-handed selectron-pair production</a> <li><a href="89413?version=4&table=Exclusion contour (obs) 8">observed exclusion contour right-handed selectron-pair production</a> <li><a href="89413?version=4&table=Exclusion contour (exp) 9">expected exclusion contour smuon-pair production</a> <li><a href="89413?version=4&table=Exclusion contour (obs) 9">observed exclusion contour smuon-pair production</a> <li><a href="89413?version=4&table=Exclusion contour (exp) 10">expected exclusion contour left-handed smuon-pair production</a> <li><a href="89413?version=4&table=Exclusion contour (obs) 10">observed exclusion contour left-handed smuon-pair production</a> <li><a href="89413?version=4&table=Exclusion contour (exp) 11">expected exclusion contour right-handed smuon-pair production</a> <li><a href="89413?version=4&table=Exclusion contour (obs) 11">observed exclusion contour right-handed smuon-pair production</a> </ul> <b>Cross section upper limits:</b> <ul> <li><a href="89413?version=4&table=xsec upper limits 1">upper limits on signal cross section for direct chargino-pair production via W decay</a> <li><a href="89413?version=4&table=xsec upper limits 2">upper limits on signal cross section for direct chargino-pair production via slepton decay</a> <li><a href="89413?version=4&table=xsec upper limits 3">upper limits on signal cross section for direct slepton-pair production</a> </ul> <b>Acceptances and Efficiencies for direct chargino-pair production via W decay grid </b> <ul> <li> <b>Acceptance</b> <br/> <a href="89413?version=4&table=Acceptance SR-DF-0J-[100,inf) for C1C1WW grid">SR-DF-0J-[100,inf) </a> <a href="89413?version=4&table=Acceptance SR-DF-0J-[160,inf) for C1C1WW grid">SR-DF-0J-[160,inf) </a> <a href="89413?version=4&table=Acceptance SR-DF-0J-[100,120) for C1C1WW grid">SR-DF-0J-[100,120) </a> <a href="89413?version=4&table=Acceptance SR-DF-0J-[120,160) for C1C1WW grid">SR-DF-0J-[120,160) </a> <a href="89413?version=4&table=Acceptance SR-DF-0J-[100,105) for C1C1WW grid">SR-DF-0J-[100,105) </a> <a href="89413?version=4&table=Acceptance SR-DF-0J-[105,110) for C1C1WW grid">SR-DF-0J-[105,110) </a> <a href="89413?version=4&table=Acceptance SR-DF-0J-[110,120) for C1C1WW grid">SR-DF-0J-[110,120) </a> <a href="89413?version=4&table=Acceptance SR-DF-0J-[120,140) for C1C1WW grid">SR-DF-0J-[120,140) </a> <a href="89413?version=4&table=Acceptance SR-DF-0J-[140,160) for C1C1WW grid">SR-DF-0J-[140,160) </a> <a href="89413?version=4&table=Acceptance SR-DF-0J-[160,180) for C1C1WW grid">SR-DF-0J-[160,180) </a> <a href="89413?version=4&table=Acceptance SR-DF-0J-[180,220) for C1C1WW grid">SR-DF-0J-[180,220) </a> <a href="89413?version=4&table=Acceptance SR-DF-0J-[220,260) for C1C1WW grid">SR-DF-0J-[220,260) </a> <a href="89413?version=4&table=Acceptance SR-DF-0J-[260,inf) for C1C1WW grid">SR-DF-0J-[260,inf) </a><br/> <a href="89413?version=4&table=Acceptance SR-DF-1J-[100,inf) for C1C1WW grid">SR-DF-1J-[100,inf) </a> <a href="89413?version=4&table=Acceptance SR-DF-1J-[160,inf) for C1C1WW grid">SR-DF-1J-[160,inf) </a> <a href="89413?version=4&table=Acceptance SR-DF-1J-[100,120) for C1C1WW grid">SR-DF-1J-[100,120) </a> <a href="89413?version=4&table=Acceptance SR-DF-1J-[120,160) for C1C1WW grid">SR-DF-1J-[120,160) </a> <a href="89413?version=4&table=Acceptance SR-DF-1J-[100,105) for C1C1WW grid">SR-DF-1J-[100,105) </a> <a href="89413?version=4&table=Acceptance SR-DF-1J-[105,110) for C1C1WW grid">SR-DF-1J-[105,110) </a> <a href="89413?version=4&table=Acceptance SR-DF-1J-[110,120) for C1C1WW grid">SR-DF-1J-[110,120) </a> <a href="89413?version=4&table=Acceptance SR-DF-1J-[120,140) for C1C1WW grid">SR-DF-1J-[120,140) </a> <a href="89413?version=4&table=Acceptance SR-DF-1J-[140,160) for C1C1WW grid">SR-DF-1J-[140,160) </a> <a href="89413?version=4&table=Acceptance SR-DF-1J-[160,180) for C1C1WW grid">SR-DF-1J-[160,180) </a> <a href="89413?version=4&table=Acceptance SR-DF-1J-[180,220) for C1C1WW grid">SR-DF-1J-[180,220) </a> <a href="89413?version=4&table=Acceptance SR-DF-1J-[220,260) for C1C1WW grid">SR-DF-1J-[220,260) </a> <a href="89413?version=4&table=Acceptance SR-DF-1J-[260,inf) for C1C1WW grid">SR-DF-1J-[260,inf) </a><br/> <a href="89413?version=4&table=Acceptance SR-SF-0J-[100,inf) for C1C1WW grid">SR-SF-0J-[100,inf) </a> <a href="89413?version=4&table=Acceptance SR-SF-0J-[160,inf) for C1C1WW grid">SR-SF-0J-[160,inf) </a> <a href="89413?version=4&table=Acceptance SR-SF-0J-[100,120) for C1C1WW grid">SR-SF-0J-[100,120) </a> <a href="89413?version=4&table=Acceptance SR-SF-0J-[120,160) for C1C1WW grid">SR-SF-0J-[120,160) </a> <a href="89413?version=4&table=Acceptance SR-SF-0J-[100,105) for C1C1WW grid">SR-SF-0J-[100,105) </a> <a href="89413?version=4&table=Acceptance SR-SF-0J-[105,110) for C1C1WW grid">SR-SF-0J-[105,110) </a> <a href="89413?version=4&table=Acceptance SR-SF-0J-[110,120) for C1C1WW grid">SR-SF-0J-[110,120) </a> <a href="89413?version=4&table=Acceptance SR-SF-0J-[120,140) for C1C1WW grid">SR-SF-0J-[120,140) </a> <a href="89413?version=4&table=Acceptance SR-SF-0J-[140,160) for C1C1WW grid">SR-SF-0J-[140,160) </a> <a href="89413?version=4&table=Acceptance SR-SF-0J-[160,180) for C1C1WW grid">SR-SF-0J-[160,180) </a> <a href="89413?version=4&table=Acceptance SR-SF-0J-[180,220) for C1C1WW grid">SR-SF-0J-[180,220) </a> <a href="89413?version=4&table=Acceptance SR-SF-0J-[220,260) for C1C1WW grid">SR-SF-0J-[220,260) </a> <a href="89413?version=4&table=Acceptance SR-SF-0J-[260,inf) for C1C1WW grid">SR-SF-0J-[260,inf) </a><br/> <a href="89413?version=4&table=Acceptance SR-SF-1J-[100,inf) for C1C1WW grid">SR-SF-1J-[100,inf) </a> <a href="89413?version=4&table=Acceptance SR-SF-1J-[160,inf) for C1C1WW grid">SR-SF-1J-[160,inf) </a> <a href="89413?version=4&table=Acceptance SR-SF-1J-[100,120) for C1C1WW grid">SR-SF-1J-[100,120) </a> <a href="89413?version=4&table=Acceptance SR-SF-1J-[120,160) for C1C1WW grid">SR-SF-1J-[120,160) </a> <a href="89413?version=4&table=Acceptance SR-SF-1J-[100,105) for C1C1WW grid">SR-SF-1J-[100,105) </a> <a href="89413?version=4&table=Acceptance SR-SF-1J-[105,110) for C1C1WW grid">SR-SF-1J-[105,110) </a> <a href="89413?version=4&table=Acceptance SR-SF-1J-[110,120) for C1C1WW grid">SR-SF-1J-[110,120) </a> <a href="89413?version=4&table=Acceptance SR-SF-1J-[120,140) for C1C1WW grid">SR-SF-1J-[120,140) </a> <a href="89413?version=4&table=Acceptance SR-SF-1J-[140,160) for C1C1WW grid">SR-SF-1J-[140,160) </a> <a href="89413?version=4&table=Acceptance SR-SF-1J-[160,180) for C1C1WW grid">SR-SF-1J-[160,180) </a> <a href="89413?version=4&table=Acceptance SR-SF-1J-[180,220) for C1C1WW grid">SR-SF-1J-[180,220) </a> <a href="89413?version=4&table=Acceptance SR-SF-1J-[220,260) for C1C1WW grid">SR-SF-1J-[220,260) </a> <a href="89413?version=4&table=Acceptance SR-SF-1J-[260,inf) for C1C1WW grid">SR-SF-1J-[260,inf) </a><br/> <li> <b>Efficiency</b> <br/> <a href="89413?version=4&table=Efficiency SR-DF-0J-[100,inf) for C1C1WW grid">SR-DF-0J-[100,inf) </a> <a href="89413?version=4&table=Efficiency SR-DF-0J-[160,inf) for C1C1WW grid">SR-DF-0J-[160,inf) </a> <a href="89413?version=4&table=Efficiency SR-DF-0J-[100,120) for C1C1WW grid">SR-DF-0J-[100,120) </a> <a href="89413?version=4&table=Efficiency SR-DF-0J-[120,160) for C1C1WW grid">SR-DF-0J-[120,160) </a> <a href="89413?version=4&table=Efficiency SR-DF-0J-[100,105) for C1C1WW grid">SR-DF-0J-[100,105) </a> <a href="89413?version=4&table=Efficiency SR-DF-0J-[105,110) for C1C1WW grid">SR-DF-0J-[105,110) </a> <a href="89413?version=4&table=Efficiency SR-DF-0J-[110,120) for C1C1WW grid">SR-DF-0J-[110,120) </a> <a href="89413?version=4&table=Efficiency SR-DF-0J-[120,140) for C1C1WW grid">SR-DF-0J-[120,140) </a> <a href="89413?version=4&table=Efficiency SR-DF-0J-[140,160) for C1C1WW grid">SR-DF-0J-[140,160) </a> <a href="89413?version=4&table=Efficiency SR-DF-0J-[160,180) for C1C1WW grid">SR-DF-0J-[160,180) </a> <a href="89413?version=4&table=Efficiency SR-DF-0J-[180,220) for C1C1WW grid">SR-DF-0J-[180,220) </a> <a href="89413?version=4&table=Efficiency SR-DF-0J-[220,260) for C1C1WW grid">SR-DF-0J-[220,260) </a> <a href="89413?version=4&table=Efficiency SR-DF-0J-[260,inf) for C1C1WW grid">SR-DF-0J-[260,inf) </a><br/> <a href="89413?version=4&table=Efficiency SR-DF-1J-[100,inf) for C1C1WW grid">SR-DF-1J-[100,inf) </a> <a href="89413?version=4&table=Efficiency SR-DF-1J-[160,inf) for C1C1WW grid">SR-DF-1J-[160,inf) </a> <a href="89413?version=4&table=Efficiency SR-DF-1J-[100,120) for C1C1WW grid">SR-DF-1J-[100,120) </a> <a href="89413?version=4&table=Efficiency SR-DF-1J-[120,160) for C1C1WW grid">SR-DF-1J-[120,160) </a> <a href="89413?version=4&table=Efficiency SR-DF-1J-[100,105) for C1C1WW grid">SR-DF-1J-[100,105) </a> <a href="89413?version=4&table=Efficiency SR-DF-1J-[105,110) for C1C1WW grid">SR-DF-1J-[105,110) </a> <a href="89413?version=4&table=Efficiency SR-DF-1J-[110,120) for C1C1WW grid">SR-DF-1J-[110,120) </a> <a href="89413?version=4&table=Efficiency SR-DF-1J-[120,140) for C1C1WW grid">SR-DF-1J-[120,140) </a> <a href="89413?version=4&table=Efficiency SR-DF-1J-[140,160) for C1C1WW grid">SR-DF-1J-[140,160) </a> <a href="89413?version=4&table=Efficiency SR-DF-1J-[160,180) for C1C1WW grid">SR-DF-1J-[160,180) </a> <a href="89413?version=4&table=Efficiency SR-DF-1J-[180,220) for C1C1WW grid">SR-DF-1J-[180,220) </a> <a href="89413?version=4&table=Efficiency SR-DF-1J-[220,260) for C1C1WW grid">SR-DF-1J-[220,260) </a> <a href="89413?version=4&table=Efficiency SR-DF-1J-[260,inf) for C1C1WW grid">SR-DF-1J-[260,inf) </a><br/> <a href="89413?version=4&table=Efficiency SR-SF-0J-[100,inf) for C1C1WW grid">SR-SF-0J-[100,inf) </a> <a href="89413?version=4&table=Efficiency SR-SF-0J-[160,inf) for C1C1WW grid">SR-SF-0J-[160,inf) </a> <a href="89413?version=4&table=Efficiency SR-SF-0J-[100,120) for C1C1WW grid">SR-SF-0J-[100,120) </a> <a href="89413?version=4&table=Efficiency SR-SF-0J-[120,160) for C1C1WW grid">SR-SF-0J-[120,160) </a> <a href="89413?version=4&table=Efficiency SR-SF-0J-[100,105) for C1C1WW grid">SR-SF-0J-[100,105) </a> <a href="89413?version=4&table=Efficiency SR-SF-0J-[105,110) for C1C1WW grid">SR-SF-0J-[105,110) </a> <a href="89413?version=4&table=Efficiency SR-SF-0J-[110,120) for C1C1WW grid">SR-SF-0J-[110,120) </a> <a href="89413?version=4&table=Efficiency SR-SF-0J-[120,140) for C1C1WW grid">SR-SF-0J-[120,140) </a> <a href="89413?version=4&table=Efficiency SR-SF-0J-[140,160) for C1C1WW grid">SR-SF-0J-[140,160) </a> <a href="89413?version=4&table=Efficiency SR-SF-0J-[160,180) for C1C1WW grid">SR-SF-0J-[160,180) </a> <a href="89413?version=4&table=Efficiency SR-SF-0J-[180,220) for C1C1WW grid">SR-SF-0J-[180,220) </a> <a href="89413?version=4&table=Efficiency SR-SF-0J-[220,260) for C1C1WW grid">SR-SF-0J-[220,260) </a> <a href="89413?version=4&table=Efficiency SR-SF-0J-[260,inf) for C1C1WW grid">SR-SF-0J-[260,inf) </a><br/> <a href="89413?version=4&table=Efficiency SR-SF-1J-[100,inf) for C1C1WW grid">SR-SF-1J-[100,inf) </a> <a href="89413?version=4&table=Efficiency SR-SF-1J-[160,inf) for C1C1WW grid">SR-SF-1J-[160,inf) </a> <a href="89413?version=4&table=Efficiency SR-SF-1J-[100,120) for C1C1WW grid">SR-SF-1J-[100,120) </a> <a href="89413?version=4&table=Efficiency SR-SF-1J-[120,160) for C1C1WW grid">SR-SF-1J-[120,160) </a> <a href="89413?version=4&table=Efficiency SR-SF-1J-[100,105) for C1C1WW grid">SR-SF-1J-[100,105) </a> <a href="89413?version=4&table=Efficiency SR-SF-1J-[105,110) for C1C1WW grid">SR-SF-1J-[105,110) </a> <a href="89413?version=4&table=Efficiency SR-SF-1J-[110,120) for C1C1WW grid">SR-SF-1J-[110,120) </a> <a href="89413?version=4&table=Efficiency SR-SF-1J-[120,140) for C1C1WW grid">SR-SF-1J-[120,140) </a> <a href="89413?version=4&table=Efficiency SR-SF-1J-[140,160) for C1C1WW grid">SR-SF-1J-[140,160) </a> <a href="89413?version=4&table=Efficiency SR-SF-1J-[160,180) for C1C1WW grid">SR-SF-1J-[160,180) </a> <a href="89413?version=4&table=Efficiency SR-SF-1J-[180,220) for C1C1WW grid">SR-SF-1J-[180,220) </a> <a href="89413?version=4&table=Efficiency SR-SF-1J-[220,260) for C1C1WW grid">SR-SF-1J-[220,260) </a> <a href="89413?version=4&table=Efficiency SR-SF-1J-[260,inf) for C1C1WW grid">SR-SF-1J-[260,inf) </a><br/> </ul> <b>Cutflow:</b> <ul> <li><a href="89413?version=4&table=Cutflow 1">Cutflow for direct chargino-pair production via W decay $m(\tilde{\chi}^{\pm}_1,\tilde{\chi}^{0}_1)=(300,50) GeV$</a> <li><a href="89413?version=4&table=Cutflow 2">Cutflow for direct chargino-pair production via slepton decay $m(\tilde{\chi}^{\pm}_1,\tilde{l},\tilde{\chi}^{0}_1)=(600,300,1) GeV$</a> <li><a href="89413?version=4&table=Cutflow 3">Cutflow for direct slepton-pair production $m(\tilde{l},\tilde{\chi}^{0}_1)=(400,200) GeV$</a> </ul> <b>SimpleAnalysis framework implementation</b> of the search SRs is available under "Resources" (purple button on the left)
Observed events and predicted background yields from the fit for the CRs. For backgrounds whose normalisation is extracted from the fit, the yield expected from the simulation before the fit is also reported. The background denoted as "Other" in the Table includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$ +V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.
Observed events and predicted background yields from the fit for the CRs. For backgrounds whose normalisation is extracted from the fit, the yield expected from the simulation before the fit is also reported. The background denoted as "Other" in the Table includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$ +V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.
Observed events and predicted background yields from the fit for the CRs. For backgrounds whose normalisation is extracted from the fit, the yield expected from the simulation before the fit is also reported. The background denoted as "Other" in the Table includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$ +V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.
Observed events and predicted background yields from the fit for the CRs. For backgrounds whose normalisation is extracted from the fit, the yield expected from the simulation before the fit is also reported. The background denoted as "Other" in the Table includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$ +V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.
Observed events and predicted post-fit background yields in the VRs. For backgrounds whose normalisation is extracted from the fit in the CRs, the yield expected from the simulation before the fit is also reported. The background denoted as "Other" includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$ +V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.
Observed events and predicted post-fit background yields in the VRs. For backgrounds whose normalisation is extracted from the fit in the CRs, the yield expected from the simulation before the fit is also reported. The background denoted as "Other" includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$ +V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.
Observed events and predicted post-fit background yields in the VRs. For backgrounds whose normalisation is extracted from the fit in the CRs, the yield expected from the simulation before the fit is also reported. The background denoted as "Other" includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$ +V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.
Observed events and predicted post-fit background yields in the VRs. For backgrounds whose normalisation is extracted from the fit in the CRs, the yield expected from the simulation before the fit is also reported. The background denoted as "Other" includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$ +V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.
Distributions of $m_{T2}$ in VR-top-low for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow.
Distributions of $m_{T2}$ in VR-top-low for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow.
Distributions of $m_{T2}$ in VR-top-low for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow.
Distributions of $m_{T2}$ in VR-top-low for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow.
Distributions of $m_{T2}$ in VR-top-high for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow.
Distributions of $m_{T2}$ in VR-top-high for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow.
Distributions of $m_{T2}$ in VR-top-high for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow.
Distributions of $m_{T2}$ in VR-top-high for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow.
Distributions of $E_T^{miss}$ in VR-WW-0J for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow.
Distributions of $E_T^{miss}$ in VR-WW-0J for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow.
Distributions of $E_T^{miss}$ in VR-WW-0J for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow.
Distributions of $E_T^{miss}$ in VR-WW-0J for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow.
Distributions of $E_T^{miss}$ in VR-WW-1J for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow.
Distributions of $E_T^{miss}$ in VR-WW-1J for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow.
Distributions of $E_T^{miss}$ in VR-WW-1J for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow.
Distributions of $E_T^{miss}$ in VR-WW-1J for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow.
Distributions of $E_T^{miss}$ significance in VR-VZ for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow.
Distributions of $E_T^{miss}$ significance in VR-VZ for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow.
Distributions of $E_T^{miss}$ significance in VR-VZ for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow.
Distributions of $E_T^{miss}$ significance in VR-VZ for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow.
Distributions of $E_T^{miss}$ significance in VR-top-WW for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow.
Distributions of $E_T^{miss}$ significance in VR-top-WW for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow.
Distributions of $E_T^{miss}$ significance in VR-top-WW for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow.
Distributions of $E_T^{miss}$ significance in VR-top-WW for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow.
Breakdown of the dominant systematic uncertainties on background estimates in the inclusive SRs requiring $m_{T2}$>100 GeV after performing the profile likelihood fit. Note that the individual uncertainties can be correlated, and do not necessarily add up quadratically to the total background uncertainty. The percentages show the size of the uncertainty relative to the total expected background. "Top theoretical uncertainties" refers to $t\bar t$ theoretical uncertainties and the uncertainty associated to $Wt-t\bar t$ interference added quadratically.
Breakdown of the dominant systematic uncertainties on background estimates in the inclusive SRs requiring $m_{T2}$>100 GeV after performing the profile likelihood fit. Note that the individual uncertainties can be correlated, and do not necessarily add up quadratically to the total background uncertainty. The percentages show the size of the uncertainty relative to the total expected background. "Top theoretical uncertainties" refers to $t\bar t$ theoretical uncertainties and the uncertainty associated to $Wt-t\bar t$ interference added quadratically.
Breakdown of the dominant systematic uncertainties on background estimates in the inclusive SRs requiring $m_{T2}$>100 GeV after performing the profile likelihood fit. Note that the individual uncertainties can be correlated, and do not necessarily add up quadratically to the total background uncertainty. The percentages show the size of the uncertainty relative to the total expected background. "Top theoretical uncertainties" refers to $t\bar t$ theoretical uncertainties and the uncertainty associated to $Wt-t\bar t$ interference added quadratically.
Breakdown of the dominant systematic uncertainties on background estimates in the inclusive SRs requiring $m_{T2}$>100 GeV after performing the profile likelihood fit. Note that the individual uncertainties can be correlated, and do not necessarily add up quadratically to the total background uncertainty. The percentages show the size of the uncertainty relative to the total expected background. "Top theoretical uncertainties" refers to $t\bar t$ theoretical uncertainties and the uncertainty associated to $Wt-t\bar t$ interference added quadratically.
Observed events and predicted post-fit background yields for the DF inclusive SRs. The model independent upper limits at 95% confidence level (CL) on the observed and expected number of beyond the SM events $S^{0.95}_{obs/exp}$ and the effective beyond the SM cross-section $\sigma^{0.95}_{obs}$ are also reported. The last row reports the $p_0$-value of the SM-only hypothesis. For SRs where the data yield is smaller than expected, the $p$-value is truncated at 0.50. The background denoted as "Other" in the Table includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$+V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.
Observed events and predicted post-fit background yields for the DF inclusive SRs. The model independent upper limits at 95% confidence level (CL) on the observed and expected number of beyond the SM events $S^{0.95}_{obs/exp}$ and the effective beyond the SM cross-section $\sigma^{0.95}_{obs}$ are also reported. The last row reports the $p_0$-value of the SM-only hypothesis. For SRs where the data yield is smaller than expected, the $p$-value is truncated at 0.50. The background denoted as "Other" in the Table includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$+V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.
Observed events and predicted post-fit background yields for the DF inclusive SRs. The model independent upper limits at 95% confidence level (CL) on the observed and expected number of beyond the SM events $S^{0.95}_{obs/exp}$ and the effective beyond the SM cross-section $\sigma^{0.95}_{obs}$ are also reported. The last row reports the $p_0$-value of the SM-only hypothesis. For SRs where the data yield is smaller than expected, the $p$-value is truncated at 0.50. The background denoted as "Other" in the Table includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$+V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.
Observed events and predicted post-fit background yields for the DF inclusive SRs. The model independent upper limits at 95% confidence level (CL) on the observed and expected number of beyond the SM events $S^{0.95}_{obs/exp}$ and the effective beyond the SM cross-section $\sigma^{0.95}_{obs}$ are also reported. The last row reports the $p_0$-value of the SM-only hypothesis. For SRs where the data yield is smaller than expected, the $p$-value is truncated at 0.50. The background denoted as "Other" in the Table includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$+V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.
Observed events and predicted post-fit background yields for the DF inclusive SRs. The model independent upper limits at 95% confidence level (CL) on the observed and expected number of beyond the SM events $S^{0.95}_{obs/exp}$ and the effective beyond the SM cross-section $\sigma^{0.95}_{obs}$ are also reported. The last row reports the $p_0$-value of the SM-only hypothesis. For SRs where the data yield is smaller than expected, the $p$-value is truncated at 0.50. The background denoted as "Other" in the Table includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$+V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.
Observed events and predicted post-fit background yields for the DF inclusive SRs. The model independent upper limits at 95% confidence level (CL) on the observed and expected number of beyond the SM events $S^{0.95}_{obs/exp}$ and the effective beyond the SM cross-section $\sigma^{0.95}_{obs}$ are also reported. The last row reports the $p_0$-value of the SM-only hypothesis. For SRs where the data yield is smaller than expected, the $p$-value is truncated at 0.50. The background denoted as "Other" in the Table includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$+V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.
Observed events and predicted post-fit background yields for the DF inclusive SRs. The model independent upper limits at 95% confidence level (CL) on the observed and expected number of beyond the SM events $S^{0.95}_{obs/exp}$ and the effective beyond the SM cross-section $\sigma^{0.95}_{obs}$ are also reported. The last row reports the $p_0$-value of the SM-only hypothesis. For SRs where the data yield is smaller than expected, the $p$-value is truncated at 0.50. The background denoted as "Other" in the Table includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$+V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.
Observed events and predicted post-fit background yields for the DF inclusive SRs. The model independent upper limits at 95% confidence level (CL) on the observed and expected number of beyond the SM events $S^{0.95}_{obs/exp}$ and the effective beyond the SM cross-section $\sigma^{0.95}_{obs}$ are also reported. The last row reports the $p_0$-value of the SM-only hypothesis. For SRs where the data yield is smaller than expected, the $p$-value is truncated at 0.50. The background denoted as "Other" in the Table includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$+V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.
Observed events and predicted post-fit background yields for the SF inclusive SRs. The model independent upper limits at 95% confidence level (CL) on the observed and expected number of beyond the SM events $S^{0.95}_{obs/exp}$ and the effective beyond the SM cross-section $\sigma^{0.95}_{obs}$ are also reported. The last row reports the $p_0$-value of the SM-only hypothesis. For SRs where the data yield is smaller than expected, the $p$-value is truncated at 0.50. The background denoted as "Other" in the Table includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$+V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.
Observed events and predicted post-fit background yields for the SF inclusive SRs. The model independent upper limits at 95% confidence level (CL) on the observed and expected number of beyond the SM events $S^{0.95}_{obs/exp}$ and the effective beyond the SM cross-section $\sigma^{0.95}_{obs}$ are also reported. The last row reports the $p_0$-value of the SM-only hypothesis. For SRs where the data yield is smaller than expected, the $p$-value is truncated at 0.50. The background denoted as "Other" in the Table includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$+V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.
Observed events and predicted post-fit background yields for the SF inclusive SRs. The model independent upper limits at 95% confidence level (CL) on the observed and expected number of beyond the SM events $S^{0.95}_{obs/exp}$ and the effective beyond the SM cross-section $\sigma^{0.95}_{obs}$ are also reported. The last row reports the $p_0$-value of the SM-only hypothesis. For SRs where the data yield is smaller than expected, the $p$-value is truncated at 0.50. The background denoted as "Other" in the Table includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$+V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.
Observed events and predicted post-fit background yields for the SF inclusive SRs. The model independent upper limits at 95% confidence level (CL) on the observed and expected number of beyond the SM events $S^{0.95}_{obs/exp}$ and the effective beyond the SM cross-section $\sigma^{0.95}_{obs}$ are also reported. The last row reports the $p_0$-value of the SM-only hypothesis. For SRs where the data yield is smaller than expected, the $p$-value is truncated at 0.50. The background denoted as "Other" in the Table includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$+V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.
Observed events and predicted post-fit background yields for the SF inclusive SRs. The model independent upper limits at 95% confidence level (CL) on the observed and expected number of beyond the SM events $S^{0.95}_{obs/exp}$ and the effective beyond the SM cross-section $\sigma^{0.95}_{obs}$ are also reported. The last row reports the $p_0$-value of the SM-only hypothesis. For SRs where the data yield is smaller than expected, the $p$-value is truncated at 0.50. The background denoted as "Other" in the Table includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$+V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.
Observed events and predicted post-fit background yields for the SF inclusive SRs. The model independent upper limits at 95% confidence level (CL) on the observed and expected number of beyond the SM events $S^{0.95}_{obs/exp}$ and the effective beyond the SM cross-section $\sigma^{0.95}_{obs}$ are also reported. The last row reports the $p_0$-value of the SM-only hypothesis. For SRs where the data yield is smaller than expected, the $p$-value is truncated at 0.50. The background denoted as "Other" in the Table includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$+V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.
Observed events and predicted post-fit background yields for the SF inclusive SRs. The model independent upper limits at 95% confidence level (CL) on the observed and expected number of beyond the SM events $S^{0.95}_{obs/exp}$ and the effective beyond the SM cross-section $\sigma^{0.95}_{obs}$ are also reported. The last row reports the $p_0$-value of the SM-only hypothesis. For SRs where the data yield is smaller than expected, the $p$-value is truncated at 0.50. The background denoted as "Other" in the Table includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$+V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.
Observed events and predicted post-fit background yields for the SF inclusive SRs. The model independent upper limits at 95% confidence level (CL) on the observed and expected number of beyond the SM events $S^{0.95}_{obs/exp}$ and the effective beyond the SM cross-section $\sigma^{0.95}_{obs}$ are also reported. The last row reports the $p_0$-value of the SM-only hypothesis. For SRs where the data yield is smaller than expected, the $p$-value is truncated at 0.50. The background denoted as "Other" in the Table includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$+V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.
Distributions of $m_{T2}$ in SRSF-0J for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow. Distributions for three benchmark signal points are overlaid for comparison.
Distributions of $m_{T2}$ in SRSF-0J for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow. Distributions for three benchmark signal points are overlaid for comparison.
Distributions of $m_{T2}$ in SRSF-0J for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow. Distributions for three benchmark signal points are overlaid for comparison.
Distributions of $m_{T2}$ in SRSF-0J for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow. Distributions for three benchmark signal points are overlaid for comparison.
Distributions of $m_{T2}$ in SRSF-1J for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow. Distributions for three benchmark signal points are overlaid for comparison.
Distributions of $m_{T2}$ in SRSF-1J for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow. Distributions for three benchmark signal points are overlaid for comparison.
Distributions of $m_{T2}$ in SRSF-1J for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow. Distributions for three benchmark signal points are overlaid for comparison.
Distributions of $m_{T2}$ in SRSF-1J for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow. Distributions for three benchmark signal points are overlaid for comparison.
Distributions of $m_{T2}$ in SRDF-0J for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow. Distributions for three benchmark signal points are overlaid for comparison.
Distributions of $m_{T2}$ in SRDF-0J for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow. Distributions for three benchmark signal points are overlaid for comparison.
Distributions of $m_{T2}$ in SRDF-0J for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow. Distributions for three benchmark signal points are overlaid for comparison.
Distributions of $m_{T2}$ in SRDF-0J for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow. Distributions for three benchmark signal points are overlaid for comparison.
Distributions of $m_{T2}$ in SRDF-1J for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow. Distributions for three benchmark signal points are overlaid for comparison.
Distributions of $m_{T2}$ in SRDF-1J for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow. Distributions for three benchmark signal points are overlaid for comparison.
Distributions of $m_{T2}$ in SRDF-1J for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow. Distributions for three benchmark signal points are overlaid for comparison.
Distributions of $m_{T2}$ in SRDF-1J for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow. Distributions for three benchmark signal points are overlaid for comparison.
Observed exclusion limits on SUSY simplified models for chargino-pair production with $W$ boson mediated decays. All limits are computed at 95% CL.
Observed exclusion limits on SUSY simplified models for chargino-pair production with $W$ boson mediated decays. All limits are computed at 95% CL.
Observed exclusion limits on SUSY simplified models for chargino-pair production with $W$ boson mediated decays. All limits are computed at 95% CL.
Observed exclusion limits on SUSY simplified models for chargino-pair production with $W$ boson mediated decays. All limits are computed at 95% CL.
Expected exclusion limits on SUSY simplified models for chargino-pair production with $W$ boson mediated decays. All limits are computed at 95% CL.
Expected exclusion limits on SUSY simplified models for chargino-pair production with $W$ boson mediated decays. All limits are computed at 95% CL.
Expected exclusion limits on SUSY simplified models for chargino-pair production with $W$ boson mediated decays. All limits are computed at 95% CL.
Expected exclusion limits on SUSY simplified models for chargino-pair production with $W$ boson mediated decays. All limits are computed at 95% CL.
Observed exclusion limits on SUSY simplified models for chargino-pair production with slepton/sneutrino mediated mediated decays. The mass relation $m(\tilde{l}_L)=\frac{1}{2}[m(\tilde{\chi}^{\pm}_1 + m(\tilde{\chi}^{0}_1)]$ is assumed. All limits are computed at 95% CL.
Observed exclusion limits on SUSY simplified models for chargino-pair production with slepton/sneutrino mediated mediated decays. The mass relation $m(\tilde{l}_L)=\frac{1}{2}[m(\tilde{\chi}^{\pm}_1 + m(\tilde{\chi}^{0}_1)]$ is assumed. All limits are computed at 95% CL.
Observed exclusion limits on SUSY simplified models for chargino-pair production with slepton/sneutrino mediated mediated decays. The mass relation $m(\tilde{l}_L)=\frac{1}{2}[m(\tilde{\chi}^{\pm}_1 + m(\tilde{\chi}^{0}_1)]$ is assumed. All limits are computed at 95% CL.
Observed exclusion limits on SUSY simplified models for chargino-pair production with slepton/sneutrino mediated mediated decays. The mass relation $m(\tilde{l}_L)=\frac{1}{2}[m(\tilde{\chi}^{\pm}_1 + m(\tilde{\chi}^{0}_1)]$ is assumed. All limits are computed at 95% CL.
Expected exclusion limits on SUSY simplified models for chargino-pair production with slepton/sneutrino mediated mediated decays. The mass relation $m(\tilde{l}_L)=\frac{1}{2}[m(\tilde{\chi}^{\pm}_1 + m(\tilde{\chi}^{0}_1)]$ is assumed. All limits are computed at 95% CL.
Expected exclusion limits on SUSY simplified models for chargino-pair production with slepton/sneutrino mediated mediated decays. The mass relation $m(\tilde{l}_L)=\frac{1}{2}[m(\tilde{\chi}^{\pm}_1 + m(\tilde{\chi}^{0}_1)]$ is assumed. All limits are computed at 95% CL.
Expected exclusion limits on SUSY simplified models for chargino-pair production with slepton/sneutrino mediated mediated decays. The mass relation $m(\tilde{l}_L)=\frac{1}{2}[m(\tilde{\chi}^{\pm}_1 + m(\tilde{\chi}^{0}_1)]$ is assumed. All limits are computed at 95% CL.
Expected exclusion limits on SUSY simplified models for chargino-pair production with slepton/sneutrino mediated mediated decays. The mass relation $m(\tilde{l}_L)=\frac{1}{2}[m(\tilde{\chi}^{\pm}_1 + m(\tilde{\chi}^{0}_1)]$ is assumed. All limits are computed at 95% CL.
Observed exclusion limits on SUSY simplified models for slepton-pair production. All limits are computed at 95% CL.
Observed exclusion limits on SUSY simplified models for slepton-pair production. All limits are computed at 95% CL.
Observed exclusion limits on SUSY simplified models for slepton-pair production. All limits are computed at 95% CL.
Observed exclusion limits on SUSY simplified models for slepton-pair production. All limits are computed at 95% CL.
Expected exclusion limits on SUSY simplified models for slepton-pair production. All limits are computed at 95% CL.
Expected exclusion limits on SUSY simplified models for slepton-pair production. All limits are computed at 95% CL.
Expected exclusion limits on SUSY simplified models for slepton-pair production. All limits are computed at 95% CL.
Expected exclusion limits on SUSY simplified models for slepton-pair production. All limits are computed at 95% CL.
Observed exclusion limits on SUSY simplified models for selectron-pair production, with left and right handed selectron production combined. All limits are computed at 95% CL.
Observed exclusion limits on SUSY simplified models for selectron-pair production, with left and right handed selectron production combined. All limits are computed at 95% CL.
Observed exclusion limits on SUSY simplified models for selectron-pair production, with left and right handed selectron production combined. All limits are computed at 95% CL.
Observed exclusion limits on SUSY simplified models for selectron-pair production, with left and right handed selectron production combined. All limits are computed at 95% CL.
Expected exclusion limits on SUSY simplified models for selectron-pair production, with left and right handed selectron production combined. All limits are computed at 95% CL.
Expected exclusion limits on SUSY simplified models for selectron-pair production, with left and right handed selectron production combined. All limits are computed at 95% CL.
Expected exclusion limits on SUSY simplified models for selectron-pair production, with left and right handed selectron production combined. All limits are computed at 95% CL.
Expected exclusion limits on SUSY simplified models for selectron-pair production, with left and right handed selectron production combined. All limits are computed at 95% CL.
Observed exclusion limits on SUSY simplified models for left-handed selectron-pair production. All limits are computed at 95% CL.
Observed exclusion limits on SUSY simplified models for left-handed selectron-pair production. All limits are computed at 95% CL.
Observed exclusion limits on SUSY simplified models for left-handed selectron-pair production. All limits are computed at 95% CL.
Observed exclusion limits on SUSY simplified models for left-handed selectron-pair production. All limits are computed at 95% CL.
Expected exclusion limits on SUSY simplified models for left-handed selectron-pair production. All limits are computed at 95% CL.
Expected exclusion limits on SUSY simplified models for left-handed selectron-pair production. All limits are computed at 95% CL.
Expected exclusion limits on SUSY simplified models for left-handed selectron-pair production. All limits are computed at 95% CL.
Expected exclusion limits on SUSY simplified models for left-handed selectron-pair production. All limits are computed at 95% CL.
Observed exclusion limits on SUSY simplified models for right-handed selectron-pair production. All limits are computed at 95% CL.
Observed exclusion limits on SUSY simplified models for right-handed selectron-pair production. All limits are computed at 95% CL.
Observed exclusion limits on SUSY simplified models for right-handed selectron-pair production. All limits are computed at 95% CL.
Observed exclusion limits on SUSY simplified models for right-handed selectron-pair production. All limits are computed at 95% CL.
Expected exclusion limits on SUSY simplified models for right-handed selectron-pair production. All limits are computed at 95% CL.
Expected exclusion limits on SUSY simplified models for right-handed selectron-pair production. All limits are computed at 95% CL.
Expected exclusion limits on SUSY simplified models for right-handed selectron-pair production. All limits are computed at 95% CL.
Expected exclusion limits on SUSY simplified models for right-handed selectron-pair production. All limits are computed at 95% CL.
Observed exclusion limits on SUSY simplified models for smuon-pair production, with left and right handed smuon production combined. All limits are computed at 95% CL.
Observed exclusion limits on SUSY simplified models for smuon-pair production, with left and right handed smuon production combined. All limits are computed at 95% CL.
Observed exclusion limits on SUSY simplified models for smuon-pair production, with left and right handed smuon production combined. All limits are computed at 95% CL.
Observed exclusion limits on SUSY simplified models for smuon-pair production, with left and right handed smuon production combined. All limits are computed at 95% CL.
Expected exclusion limits on SUSY simplified models for smuon-pair production, with left and right handed smuon production combined. All limits are computed at 95% CL.
Expected exclusion limits on SUSY simplified models for smuon-pair production, with left and right handed smuon production combined. All limits are computed at 95% CL.
Expected exclusion limits on SUSY simplified models for smuon-pair production, with left and right handed smuon production combined. All limits are computed at 95% CL.
Expected exclusion limits on SUSY simplified models for smuon-pair production, with left and right handed smuon production combined. All limits are computed at 95% CL.
Observed exclusion limits on SUSY simplified models for left-handed smuon-pair production. All limits are computed at 95% CL.
Observed exclusion limits on SUSY simplified models for left-handed smuon-pair production. All limits are computed at 95% CL.
Observed exclusion limits on SUSY simplified models for left-handed smuon-pair production. All limits are computed at 95% CL.
Observed exclusion limits on SUSY simplified models for left-handed smuon-pair production. All limits are computed at 95% CL.
Expected exclusion limits on SUSY simplified models for left-handed smuon-pair production. All limits are computed at 95% CL.
Expected exclusion limits on SUSY simplified models for left-handed smuon-pair production. All limits are computed at 95% CL.
Expected exclusion limits on SUSY simplified models for left-handed smuon-pair production. All limits are computed at 95% CL.
Expected exclusion limits on SUSY simplified models for left-handed smuon-pair production. All limits are computed at 95% CL.
Observed exclusion limits on SUSY simplified models for right-handed smuon-pair production. All limits are computed at 95% CL.
Observed exclusion limits on SUSY simplified models for right-handed smuon-pair production. All limits are computed at 95% CL.
Observed exclusion limits on SUSY simplified models for right-handed smuon-pair production. All limits are computed at 95% CL.
Observed exclusion limits on SUSY simplified models for right-handed smuon-pair production. All limits are computed at 95% CL.
Expected exclusion limits on SUSY simplified models for right-handed smuon-pair production. All limits are computed at 95% CL.
Expected exclusion limits on SUSY simplified models for right-handed smuon-pair production. All limits are computed at 95% CL.
Expected exclusion limits on SUSY simplified models for right-handed smuon-pair production. All limits are computed at 95% CL.
Expected exclusion limits on SUSY simplified models for right-handed smuon-pair production. All limits are computed at 95% CL.
Observed events and predicted background yields from the fit in the binned DF SRs with $n_{non-b-tagged jets}=0$. For backgrounds whose normalisation is extracted from the fit in the CRs, the yield expected from the simulation before the fit is also reported. The background denoted as "Other" in the Table includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$ +V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.
Observed events and predicted background yields from the fit in the binned DF SRs with $n_{non-b-tagged jets}=0$. For backgrounds whose normalisation is extracted from the fit in the CRs, the yield expected from the simulation before the fit is also reported. The background denoted as "Other" in the Table includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$ +V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.
Observed events and predicted background yields from the fit in the binned DF SRs with $n_{non-b-tagged jets}=0$. For backgrounds whose normalisation is extracted from the fit in the CRs, the yield expected from the simulation before the fit is also reported. The background denoted as "Other" in the Table includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$ +V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.
Observed events and predicted background yields from the fit in the binned DF SRs with $n_{non-b-tagged jets}=0$. For backgrounds whose normalisation is extracted from the fit in the CRs, the yield expected from the simulation before the fit is also reported. The background denoted as "Other" in the Table includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$ +V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.
Observed events and predicted background yields from the fit in the binned DF SRs with $n_{non-b-tagged jets}=1$. For backgrounds whose normalisation is extracted from the fit in the CRs, the yield expected from the simulation before the fit is also reported. The background denoted as "Other" in the Table includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$ +V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.
Observed events and predicted background yields from the fit in the binned DF SRs with $n_{non-b-tagged jets}=1$. For backgrounds whose normalisation is extracted from the fit in the CRs, the yield expected from the simulation before the fit is also reported. The background denoted as "Other" in the Table includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$ +V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.
Observed events and predicted background yields from the fit in the binned DF SRs with $n_{non-b-tagged jets}=1$. For backgrounds whose normalisation is extracted from the fit in the CRs, the yield expected from the simulation before the fit is also reported. The background denoted as "Other" in the Table includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$ +V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.
Observed events and predicted background yields from the fit in the binned DF SRs with $n_{non-b-tagged jets}=1$. For backgrounds whose normalisation is extracted from the fit in the CRs, the yield expected from the simulation before the fit is also reported. The background denoted as "Other" in the Table includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$ +V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.
Observed events and predicted background yields from the fit in the binned SF SRs with $n_{non-b-tagged jets}=0$. For backgrounds whose normalisation is extracted from the fit in the CRs, the yield expected from the simulation before the fit is also reported. The background denoted as "Other" in the Table includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$ +V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.
Observed events and predicted background yields from the fit in the binned SF SRs with $n_{non-b-tagged jets}=0$. For backgrounds whose normalisation is extracted from the fit in the CRs, the yield expected from the simulation before the fit is also reported. The background denoted as "Other" in the Table includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$ +V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.
Observed events and predicted background yields from the fit in the binned SF SRs with $n_{non-b-tagged jets}=0$. For backgrounds whose normalisation is extracted from the fit in the CRs, the yield expected from the simulation before the fit is also reported. The background denoted as "Other" in the Table includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$ +V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.
Observed events and predicted background yields from the fit in the binned SF SRs with $n_{non-b-tagged jets}=0$. For backgrounds whose normalisation is extracted from the fit in the CRs, the yield expected from the simulation before the fit is also reported. The background denoted as "Other" in the Table includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$ +V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.
Observed events and predicted background yields from the fit in the binned SF SRs with $n_{non-b-tagged jets}=1$. For backgrounds whose normalisation is extracted from the fit in the CRs, the yield expected from the simulation before the fit is also reported. The background denoted as "Other" in the Table includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$ +V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.
Observed events and predicted background yields from the fit in the binned SF SRs with $n_{non-b-tagged jets}=1$. For backgrounds whose normalisation is extracted from the fit in the CRs, the yield expected from the simulation before the fit is also reported. The background denoted as "Other" in the Table includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$ +V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.
Observed events and predicted background yields from the fit in the binned SF SRs with $n_{non-b-tagged jets}=1$. For backgrounds whose normalisation is extracted from the fit in the CRs, the yield expected from the simulation before the fit is also reported. The background denoted as "Other" in the Table includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$ +V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.
Observed events and predicted background yields from the fit in the binned SF SRs with $n_{non-b-tagged jets}=1$. For backgrounds whose normalisation is extracted from the fit in the CRs, the yield expected from the simulation before the fit is also reported. The background denoted as "Other" in the Table includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$ +V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.
Observed exclusion limits on SUSY simplified models for left-handed slepton-pair production. All limits are computed at 95% CL.
Observed exclusion limits on SUSY simplified models for left-handed slepton-pair production. All limits are computed at 95% CL.
Observed exclusion limits on SUSY simplified models for left-handed slepton-pair production. All limits are computed at 95% CL.
Observed exclusion limits on SUSY simplified models for left-handed slepton-pair production. All limits are computed at 95% CL.
Expected exclusion limits on SUSY simplified models for left-handed slepton-pair production. All limits are computed at 95% CL.
Expected exclusion limits on SUSY simplified models for left-handed slepton-pair production. All limits are computed at 95% CL.
Expected exclusion limits on SUSY simplified models for left-handed slepton-pair production. All limits are computed at 95% CL.
Expected exclusion limits on SUSY simplified models for left-handed slepton-pair production. All limits are computed at 95% CL.
Observed exclusion limits on SUSY simplified models for right-handed slepton-pair production. All limits are computed at 95% CL.
Observed exclusion limits on SUSY simplified models for right-handed slepton-pair production. All limits are computed at 95% CL.
Observed exclusion limits on SUSY simplified models for right-handed slepton-pair production. All limits are computed at 95% CL.
Observed exclusion limits on SUSY simplified models for right-handed slepton-pair production. All limits are computed at 95% CL.
Expected exclusion limits on SUSY simplified models for right-handed slepton-pair production. All limits are computed at 95% CL.
Expected exclusion limits on SUSY simplified models for right-handed slepton-pair production. All limits are computed at 95% CL.
Expected exclusion limits on SUSY simplified models for right-handed slepton-pair production. All limits are computed at 95% CL.
Expected exclusion limits on SUSY simplified models for right-handed slepton-pair production. All limits are computed at 95% CL.
Upper limits on signal cross-section (fb) for chargino-pair production with W -boson-mediated decays.
Upper limits on signal cross-section (fb) for chargino-pair production with W -boson-mediated decays.
Upper limits on signal cross-section (fb) for chargino-pair production with W -boson-mediated decays.
Upper limits on signal cross-section (fb) for chargino-pair production with W -boson-mediated decays.
Upper limits on signal cross-section (fb) for chargino-pair production with slepton/sneutrino-mediated decays. The mass relation $m(\tilde{l}_L)=\frac{1}{2}[m(\tilde{\chi}^{\pm}_1 + m(\tilde{\chi}^{0}_1)]$ is assumed.
Upper limits on signal cross-section (fb) for chargino-pair production with slepton/sneutrino-mediated decays. The mass relation $m(\tilde{l}_L)=\frac{1}{2}[m(\tilde{\chi}^{\pm}_1 + m(\tilde{\chi}^{0}_1)]$ is assumed.
Upper limits on signal cross-section (fb) for chargino-pair production with slepton/sneutrino-mediated decays. The mass relation $m(\tilde{l}_L)=\frac{1}{2}[m(\tilde{\chi}^{\pm}_1 + m(\tilde{\chi}^{0}_1)]$ is assumed.
Upper limits on signal cross-section (fb) for chargino-pair production with slepton/sneutrino-mediated decays. The mass relation $m(\tilde{l}_L)=\frac{1}{2}[m(\tilde{\chi}^{\pm}_1 + m(\tilde{\chi}^{0}_1)]$ is assumed.
Upper limits on signal cross-section (fb) for slepton-pair production.
Upper limits on signal cross-section (fb) for slepton-pair production.
Upper limits on signal cross-section (fb) for slepton-pair production.
Upper limits on signal cross-section (fb) for slepton-pair production.
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[100,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[100,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[100,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[100,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[100,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[100,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[100,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[100,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[100,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[100,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[100,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[100,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[100,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[100,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[100,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[100,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[100,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[100,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[100,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[100,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[100,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[100,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[100,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[100,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[100,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[100,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[100,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[100,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[100,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[100,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[100,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[100,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[160,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[160,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[160,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[160,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[160,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[160,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[160,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[160,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[160,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[160,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[160,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[160,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[160,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[160,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[160,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[160,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[160,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[160,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[160,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[160,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[160,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[160,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[160,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[160,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[160,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[160,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[160,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[160,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[160,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[160,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[160,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[160,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[100,120).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[100,120).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[100,120).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[100,120).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[100,120).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[100,120).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[100,120).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[100,120).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[100,120).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[100,120).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[100,120).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[100,120).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[100,120).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[100,120).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[100,120).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[100,120).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[100,120).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[100,120).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[100,120).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[100,120).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[100,120).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[100,120).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[100,120).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[100,120).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[100,120).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[100,120).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[100,120).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[100,120).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[100,120).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[100,120).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[100,120).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[100,120).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[120,160).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[120,160).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[120,160).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[120,160).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[120,160).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[120,160).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[120,160).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[120,160).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[120,160).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[120,160).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[120,160).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[120,160).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[120,160).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[120,160).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[120,160).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[120,160).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[120,160).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[120,160).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[120,160).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[120,160).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[120,160).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[120,160).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[120,160).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[120,160).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[120,160).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[120,160).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[120,160).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[120,160).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[120,160).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[120,160).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[120,160).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[120,160).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[100,105).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[100,105).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[100,105).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[100,105).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[100,105).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[100,105).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[100,105).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[100,105).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[100,105).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[100,105).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[100,105).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[100,105).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[100,105).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[100,105).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[100,105).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[100,105).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[100,105).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[100,105).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[100,105).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[100,105).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[100,105).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[100,105).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[100,105).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[100,105).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[100,105).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[100,105).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[100,105).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[100,105).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[100,105).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[100,105).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[100,105).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[100,105).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[105,110).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[105,110).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[105,110).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[105,110).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[105,110).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[105,110).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[105,110).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[105,110).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[105,110).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[105,110).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[105,110).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[105,110).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[105,110).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[105,110).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[105,110).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[105,110).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[105,110).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[105,110).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[105,110).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[105,110).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[105,110).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[105,110).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[105,110).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[105,110).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[105,110).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[105,110).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[105,110).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[105,110).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[105,110).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[105,110).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[105,110).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[105,110).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[110,120).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[110,120).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[110,120).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[110,120).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[110,120).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[110,120).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[110,120).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[110,120).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[110,120).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[110,120).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[110,120).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[110,120).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[110,120).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[110,120).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[110,120).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[110,120).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[110,120).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[110,120).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[110,120).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[110,120).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[110,120).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[110,120).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[110,120).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[110,120).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[110,120).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[110,120).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[110,120).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[110,120).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[110,120).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[110,120).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[110,120).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[110,120).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[120,140).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[120,140).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[120,140).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[120,140).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[120,140).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[120,140).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[120,140).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[120,140).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[120,140).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[120,140).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[120,140).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[120,140).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[120,140).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[120,140).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[120,140).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[120,140).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[120,140).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[120,140).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[120,140).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[120,140).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[120,140).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[120,140).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[120,140).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[120,140).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[120,140).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[120,140).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[120,140).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[120,140).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[120,140).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[120,140).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[120,140).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[120,140).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[140,160).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[140,160).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[140,160).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[140,160).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[140,160).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[140,160).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[140,160).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[140,160).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[140,160).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[140,160).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[140,160).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[140,160).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[140,160).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[140,160).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[140,160).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[140,160).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[140,160).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[140,160).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[140,160).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[140,160).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[140,160).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[140,160).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[140,160).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[140,160).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[140,160).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[140,160).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[140,160).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[140,160).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[140,160).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[140,160).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[140,160).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[140,160).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[160,180).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[160,180).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[160,180).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[160,180).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[160,180).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[160,180).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[160,180).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[160,180).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[160,180).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[160,180).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[160,180).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[160,180).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[160,180).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[160,180).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[160,180).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[160,180).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[160,180).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[160,180).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[160,180).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[160,180).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[160,180).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[160,180).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[160,180).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[160,180).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[160,180).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[160,180).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[160,180).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[160,180).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[160,180).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[160,180).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[160,180).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[160,180).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[180,220).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[180,220).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[180,220).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[180,220).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[180,220).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[180,220).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[180,220).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[180,220).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[180,220).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[180,220).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[180,220).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[180,220).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[180,220).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[180,220).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[180,220).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[180,220).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[180,220).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[180,220).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[180,220).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[180,220).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[180,220).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[180,220).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[180,220).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[180,220).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[180,220).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[180,220).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[180,220).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[180,220).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[180,220).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[180,220).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[180,220).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[180,220).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[220,260).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[220,260).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[220,260).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[220,260).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[220,260).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[220,260).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[220,260).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[220,260).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[220,260).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[220,260).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[220,260).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[220,260).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[220,260).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[220,260).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[220,260).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[220,260).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[220,260).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[220,260).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[220,260).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[220,260).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[220,260).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[220,260).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[220,260).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[220,260).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[220,260).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[220,260).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[220,260).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[220,260).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[220,260).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[220,260).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[220,260).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[220,260).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[260,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[260,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[260,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[260,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[260,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[260,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[260,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[260,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[260,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[260,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[260,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[260,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[260,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[260,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[260,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[260,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[260,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[260,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[260,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[260,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[260,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[260,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[260,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[260,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[260,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[260,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[260,inf).
Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[260,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[260,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[260,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[260,inf).
Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[260,inf).
Cutflow for supersymmetric model where $\tilde{\chi}_1^{\pm}\tilde{\chi}_1^{\mp}$ decay via $W^{\pm}W^{\mp}$. The masses of the two charginos are 300 GeV, while the mass of $\tilde{\chi}_1^{0}$ is 50 GeV. The numbers are normalised to the luminosity of 139~fb$^{-1}$.
Cutflow for supersymmetric model where $\tilde{\chi}_1^{\pm}\tilde{\chi}_1^{\mp}$ decay via $W^{\pm}W^{\mp}$. The masses of the two charginos are 300 GeV, while the mass of $\tilde{\chi}_1^{0}$ is 50 GeV. The numbers are normalised to the luminosity of 139~fb$^{-1}$.
Cutflow for supersymmetric model where $\tilde{\chi}_1^{\pm}\tilde{\chi}_1^{\mp}$ decay via $W^{\pm}W^{\mp}$. The masses of the two charginos are 300 GeV, while the mass of $\tilde{\chi}_1^{0}$ is 50 GeV. The numbers are normalised to the luminosity of 139~fb$^{-1}$.
Cutflow for supersymmetric model where $\tilde{\chi}_1^{\pm}\tilde{\chi}_1^{\mp}$ decay via $W^{\pm}W^{\mp}$. The masses of the two charginos are 300 GeV, while the mass of $\tilde{\chi}_1^{0}$ is 50 GeV. The numbers are normalised to the luminosity of 139~fb$^{-1}$.
Cutflow for supersymmetric model where $\tilde{\chi}_1^{\pm}\tilde{\chi}_1^{\mp}$ decay via slepton-neutrino/sneutrino-lepton pair. The masses of the two charginos are 600 GeV, while the mass of $\tilde{\chi}_1^{0}$ is 1 GeV. The slepton/sneutrino masses are 300 GeV. The numbers are normalised to the luminosity of 139~fb$^{-1}$.
Cutflow for supersymmetric model where $\tilde{\chi}_1^{\pm}\tilde{\chi}_1^{\mp}$ decay via slepton-neutrino/sneutrino-lepton pair. The masses of the two charginos are 600 GeV, while the mass of $\tilde{\chi}_1^{0}$ is 1 GeV. The slepton/sneutrino masses are 300 GeV. The numbers are normalised to the luminosity of 139~fb$^{-1}$.
Cutflow for supersymmetric model where $\tilde{\chi}_1^{\pm}\tilde{\chi}_1^{\mp}$ decay via slepton-neutrino/sneutrino-lepton pair. The masses of the two charginos are 600 GeV, while the mass of $\tilde{\chi}_1^{0}$ is 1 GeV. The slepton/sneutrino masses are 300 GeV. The numbers are normalised to the luminosity of 139~fb$^{-1}$.
Cutflow for supersymmetric model where $\tilde{\chi}_1^{\pm}\tilde{\chi}_1^{\mp}$ decay via slepton-neutrino/sneutrino-lepton pair. The masses of the two charginos are 600 GeV, while the mass of $\tilde{\chi}_1^{0}$ is 1 GeV. The slepton/sneutrino masses are 300 GeV. The numbers are normalised to the luminosity of 139~fb$^{-1}$.
Cutflow for supersymmetric model where $\tilde\ell\tilde\ell$ are produced. Only $\tilde{e}$ and $\tilde{\mu}$ are considered in this model. The masses of the two sleptons are 400 GeV, while the mass of $\tilde{\chi}_1^{0}$ is 200 GeV. The numbers are normalised to the luminosity of 139~fb$^{-1}$.
Cutflow for supersymmetric model where $\tilde\ell\tilde\ell$ are produced. Only $\tilde{e}$ and $\tilde{\mu}$ are considered in this model. The masses of the two sleptons are 400 GeV, while the mass of $\tilde{\chi}_1^{0}$ is 200 GeV. The numbers are normalised to the luminosity of 139~fb$^{-1}$.
Cutflow for supersymmetric model where $\tilde\ell\tilde\ell$ are produced. Only $\tilde{e}$ and $\tilde{\mu}$ are considered in this model. The masses of the two sleptons are 400 GeV, while the mass of $\tilde{\chi}_1^{0}$ is 200 GeV. The numbers are normalised to the luminosity of 139~fb$^{-1}$.
Cutflow for supersymmetric model where $\tilde\ell\tilde\ell$ are produced. Only $\tilde{e}$ and $\tilde{\mu}$ are considered in this model. The masses of the two sleptons are 400 GeV, while the mass of $\tilde{\chi}_1^{0}$ is 200 GeV. The numbers are normalised to the luminosity of 139~fb$^{-1}$.
A search for supersymmetric partners of gluons and quarks is presented, involving signatures with jets and either two isolated leptons (electrons or muons) with the same electric charge, or at least three isolated leptons. A data sample of proton-proton collisions at $\sqrt{s}$ = 13 TeV recorded with the ATLAS detector at the Large Hadron Collider between 2015 and 2018, corresponding to a total integrated luminosity of 139 fb$^{-1}$, is used for the search. No significant excess over the Standard Model expectation is observed. The results are interpreted in simplified supersymmetric models featuring both R-parity conservation and R-parity violation, raising the exclusion limits beyond those of previous ATLAS searches to 1600 GeV for gluino masses and 750 GeV for bottom and top squark masses in these scenarios.
Observed 95% CL exclusion contours in signal region Rpc2L0b on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g \to q \bar{q}^{'} \tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm \to W^\pm \tilde{\chi}_2^0$ and $ \tilde{\chi}_2^0 \to Z \tilde{\chi}_1^0$.
Observed 95% CL exclusion contours in signal region Rpc2L0b on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g \to q \bar{q}^{'} \tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm \to W^\pm \tilde{\chi}_2^0$ and $ \tilde{\chi}_2^0 \to Z \tilde{\chi}_1^0$.
Observed 95% CL exclusion contours in signal region Rpc2L0b on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g \to q \bar{q}^{'} \tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm \to W^\pm \tilde{\chi}_2^0$ and $ \tilde{\chi}_2^0 \to Z \tilde{\chi}_1^0$.
Observed 95% CL exclusion contours in signal region Rpc2L0b on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g \to q \bar{q}^{'} \tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm \to W^\pm \tilde{\chi}_2^0$ and $ \tilde{\chi}_2^0 \to Z \tilde{\chi}_1^0$.
Expected 95% CL exclusion contours in signal region Rpc2L0b on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Expected 95% CL exclusion contours in signal region Rpc2L0b on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Expected 95% CL exclusion contours in signal region Rpc2L0b on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Expected 95% CL exclusion contours in signal region Rpc2L0b on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Observed 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Observed 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Observed 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Observed 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Expected 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Expected 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Expected 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Expected 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Observed 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Observed 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Observed 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Observed 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Expected 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Expected 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Expected 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Expected 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L0b, in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde \chi_1^\pm)$ = 1200 GeV, $m(\tilde \chi_2^0)$ = 1000 GeV and $m(\tilde \chi_1^0)$ = 800 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L0b, in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde \chi_1^\pm)$ = 1200 GeV, $m(\tilde \chi_2^0)$ = 1000 GeV and $m(\tilde \chi_1^0)$ = 800 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L0b, in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde \chi_1^\pm)$ = 1200 GeV, $m(\tilde \chi_2^0)$ = 1000 GeV and $m(\tilde \chi_1^0)$ = 800 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L0b, in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde \chi_1^\pm)$ = 1200 GeV, $m(\tilde \chi_2^0)$ = 1000 GeV and $m(\tilde \chi_1^0)$ = 800 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L1b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 850 GeV, $m(\tilde \chi_1^\pm)$ = 500 GeV and $m(\tilde \chi_1^0)$ = 400 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L1b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 850 GeV, $m(\tilde \chi_1^\pm)$ = 500 GeV and $m(\tilde \chi_1^0)$ = 400 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L1b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 850 GeV, $m(\tilde \chi_1^\pm)$ = 500 GeV and $m(\tilde \chi_1^0)$ = 400 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L1b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 850 GeV, $m(\tilde \chi_1^\pm)$ = 500 GeV and $m(\tilde \chi_1^0)$ = 400 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L2b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 850 GeV, $m(\tilde \chi_1^\pm)$ = 500 GeV and $m(\tilde \chi_1^0)$ = 400 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L2b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 900 GeV, $m(\tilde \chi_1^\pm)$ = 150 GeV and $m(\tilde \chi_1^0)$ = 50 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L2b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 900 GeV, $m(\tilde \chi_1^\pm)$ = 150 GeV and $m(\tilde \chi_1^0)$ = 50 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L2b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 900 GeV, $m(\tilde \chi_1^\pm)$ = 150 GeV and $m(\tilde \chi_1^0)$ = 50 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc3LSS1b, in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate. The masses of the superpartners involved in the process are set to $m(\tilde{t}^{}_1)$ = 800 GeV, $m(\tilde \chi_2^0)$ = 625 GeV, $m(\tilde \chi_1^\pm)\approx m(\tilde \chi_1^0)$ = 525 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc3LSS1b, in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate. The masses of the superpartners involved in the process are set to $m(\tilde{t}^{}_1)$ = 800 GeV, $m(\tilde \chi_2^0)$ = 625 GeV, $m(\tilde \chi_1^\pm)\approx m(\tilde \chi_1^0)$ = 525 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc3LSS1b, in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate. The masses of the superpartners involved in the process are set to $m(\tilde{t}^{}_1)$ = 800 GeV, $m(\tilde \chi_2^0)$ = 625 GeV, $m(\tilde \chi_1^\pm)\approx m(\tilde \chi_1^0)$ = 525 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc3LSS1b, in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate. The masses of the superpartners involved in the process are set to $m(\tilde{t}^{}_1)$ = 800 GeV, $m(\tilde \chi_2^0)$ = 625 GeV, $m(\tilde \chi_1^\pm)\approx m(\tilde \chi_1^0)$ = 525 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpv2L, in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde{t}^{}_{1})$ = 800 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpv2L, in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde{t}^{}_{1})$ = 800 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpv2L, in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde{t}^{}_{1})$ = 800 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpv2L, in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde{t}^{}_{1})$ = 800 GeV. Only statistical uncertainties are shown.
Signal acceptance for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Signal acceptance for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Signal acceptance for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Signal acceptance for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Signal acceptance for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal acceptance for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal acceptance for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal acceptance for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal acceptance for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal acceptance for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal acceptance for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal acceptance for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal acceptance for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Signal acceptance for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Signal acceptance for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Signal acceptance for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Signal acceptance for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.
Signal acceptance for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.
Signal acceptance for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.
Signal acceptance for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.
Signal efficiency for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Signal efficiency for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Signal efficiency for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Signal efficiency for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Signal efficiency for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal efficiency for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal efficiency for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal efficiency for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal efficiency for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal efficiency for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal efficiency for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal efficiency for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal efficiency for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Signal efficiency for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Signal efficiency for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Signal efficiency for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Signal efficiency for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.
Signal efficiency for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.
Signal efficiency for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.
Signal efficiency for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.
Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Observed 95% CL upper limit on $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Observed 95% CL upper limit on $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Observed 95% CL upper limit on $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Observed 95% CL upper limit on $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Observed 95% CL upper limit on $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.
Observed 95% CL upper limit on $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.
Observed 95% CL upper limit on $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.
Observed 95% CL upper limit on $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.
Best observed 95% CL exclusion contours selected from Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Best observed 95% CL exclusion contours selected from Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Best observed 95% CL exclusion contours selected from Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Best observed 95% CL exclusion contours selected from Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L0b from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L0b from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L0b from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L0b from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}} / m_{\mathrm{eff}}$ of observed data and expected background towards Rpc2L1b from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}} / m_{\mathrm{eff}}$ of observed data and expected background towards Rpc2L1b from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}} / m_{\mathrm{eff}}$ of observed data and expected background towards Rpc2L1b from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}} / m_{\mathrm{eff}}$ of observed data and expected background towards Rpc2L1b from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L2b from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L2b from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L2b from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L2b from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $m_{\mathrm{eff}}$ of observed data and expected background towards Rpv2L from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $m_{\mathrm{eff}}$ of observed data and expected background towards Rpv2L from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $m_{\mathrm{eff}}$ of observed data and expected background towards Rpv2L from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $m_{\mathrm{eff}}$ of observed data and expected background towards Rpv2L from publication's Figure 5 . The last bin is inclusive.
The results of a search for electroweakino pair production $pp \rightarrow \tilde\chi^\pm_1 \tilde\chi^0_2$ in which the chargino ($\tilde\chi^\pm_1$) decays into a $W$ boson and the lightest neutralino ($\tilde\chi^0_1$), while the heavier neutralino ($\tilde\chi^0_2$) decays into the Standard Model 125 GeV Higgs boson and a second $\tilde\chi^0_1$ are presented. The signal selection requires a pair of $b$-tagged jets consistent with those from a Higgs boson decay, and either an electron or a muon from the $W$ boson decay, together with missing transverse momentum from the corresponding neutrino and the stable neutralinos. The analysis is based on data corresponding to 139 $\mathrm{fb}^{-1}$ of $\sqrt{s}=13$ TeV $pp$ collisions provided by the Large Hadron Collider and recorded by the ATLAS detector. No statistically significant evidence of an excess of events above the Standard Model expectation is found. Limits are set on the direct production of the electroweakinos in simplified models, assuming pure wino cross-sections. Masses of $\tilde{\chi}^{\pm}_{1}/\tilde{\chi}^{0}_{2}$ up to 740 GeV are excluded at 95% confidence level for a massless $\tilde{\chi}^{0}_{1}$.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-onLM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-onLM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-onLM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-onLM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-onMM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-onMM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-onMM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-onMM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-onHM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-onHM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-onHM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-onHM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-offLM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-offLM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-offLM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-offLM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-offMM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-offMM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-offMM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-offMM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-offHM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-offHM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-offHM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution is shown in the validation region VR-offHM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.
The post-fit $m_{CT}$ distribution for SR-HM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.
The post-fit $m_{CT}$ distribution for SR-HM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.
The post-fit $m_{CT}$ distribution for SR-HM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.
The post-fit $m_{CT}$ distribution for SR-HM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.
The post-fit $m_{CT}$ distribution for SR-MM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.
The post-fit $m_{CT}$ distribution for SR-MM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.
The post-fit $m_{CT}$ distribution for SR-MM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.
The post-fit $m_{CT}$ distribution for SR-MM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.
The post-fit $m_{CT}$ distribution for SR-LM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.
The post-fit $m_{CT}$ distribution for SR-LM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.
The post-fit $m_{CT}$ distribution for SR-LM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.
The post-fit $m_{CT}$ distribution for SR-LM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.
The post-fit $m_{bb}$ distribution is shown in the signal region SR-HM after all the selection requirements are applied other than the $m_{bb}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection.The overflow events, where present, are included in the last bin.
The post-fit $m_{bb}$ distribution is shown in the signal region SR-HM after all the selection requirements are applied other than the $m_{bb}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection.The overflow events, where present, are included in the last bin.
The post-fit $m_{bb}$ distribution is shown in the signal region SR-HM after all the selection requirements are applied other than the $m_{bb}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection.The overflow events, where present, are included in the last bin.
The post-fit $m_{bb}$ distribution is shown in the signal region SR-HM after all the selection requirements are applied other than the $m_{bb}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection.The overflow events, where present, are included in the last bin.
The post-fit $m_{bb}$ distribution is shown in the signal region SR-MM after all the selection requirements are applied other than the $m_{bb}$ cut. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection. The overflow events, where present, are included in the last bin.
The post-fit $m_{bb}$ distribution is shown in the signal region SR-MM after all the selection requirements are applied other than the $m_{bb}$ cut. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection. The overflow events, where present, are included in the last bin.
The post-fit $m_{bb}$ distribution is shown in the signal region SR-MM after all the selection requirements are applied other than the $m_{bb}$ cut. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection. The overflow events, where present, are included in the last bin.
The post-fit $m_{bb}$ distribution is shown in the signal region SR-MM after all the selection requirements are applied other than the $m_{bb}$ cut. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection. The overflow events, where present, are included in the last bin.
The post-fit $m_{bb}$ distribution is shown in the signal region SR-LM after all the selection requirements are applied other than the $m_{bb}$ cut. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection. The overflow events, where present, are included in the last bin.
The post-fit $m_{bb}$ distribution is shown in the signal region SR-LM after all the selection requirements are applied other than the $m_{bb}$ cut. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection. The overflow events, where present, are included in the last bin.
The post-fit $m_{bb}$ distribution is shown in the signal region SR-LM after all the selection requirements are applied other than the $m_{bb}$ cut. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection. The overflow events, where present, are included in the last bin.
The post-fit $m_{bb}$ distribution is shown in the signal region SR-LM after all the selection requirements are applied other than the $m_{bb}$ cut. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection. The overflow events, where present, are included in the last bin.
The observed exclusion for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. Experimental and theoretical systematic uncertainties are applied to background and signal samples and illustrated by the yellow band and the red dotted contour lines, respectively. The red dotted lines indicate the $\pm$ 1 standard-deviation variation on the observed exclusion limit due to theoretical uncertainties in the signal cross-section.
The observed exclusion for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. Experimental and theoretical systematic uncertainties are applied to background and signal samples and illustrated by the yellow band and the red dotted contour lines, respectively. The red dotted lines indicate the $\pm$ 1 standard-deviation variation on the observed exclusion limit due to theoretical uncertainties in the signal cross-section.
The observed exclusion for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. Experimental and theoretical systematic uncertainties are applied to background and signal samples and illustrated by the yellow band and the red dotted contour lines, respectively. The red dotted lines indicate the $\pm$ 1 standard-deviation variation on the observed exclusion limit due to theoretical uncertainties in the signal cross-section.
The observed exclusion for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. Experimental and theoretical systematic uncertainties are applied to background and signal samples and illustrated by the yellow band and the red dotted contour lines, respectively. The red dotted lines indicate the $\pm$ 1 standard-deviation variation on the observed exclusion limit due to theoretical uncertainties in the signal cross-section.
The observed exclusion up limit for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. The red dotted lines indicate the $\pm 1 \sigma$ on the observed exclusion limit due to the theoretical uncertainties in the signal cross-section.
The observed exclusion up limit for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. The red dotted lines indicate the $\pm 1 \sigma$ on the observed exclusion limit due to the theoretical uncertainties in the signal cross-section.
The observed exclusion up limit for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. The red dotted lines indicate the $\pm 1 \sigma$ on the observed exclusion limit due to the theoretical uncertainties in the signal cross-section.
The observed exclusion up limit for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. The red dotted lines indicate the $\pm 1 \sigma$ on the observed exclusion limit due to the theoretical uncertainties in the signal cross-section.
The observed exclusion down limit for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. The red dotted lines indicate the $\pm 1 \sigma$ on the observed exclusion limit due to the theoretical uncertainties in the signal cross-section.
The observed exclusion down limit for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. The red dotted lines indicate the $\pm 1 \sigma$ on the observed exclusion limit due to the theoretical uncertainties in the signal cross-section.
The observed exclusion down limit for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. The red dotted lines indicate the $\pm 1 \sigma$ on the observed exclusion limit due to the theoretical uncertainties in the signal cross-section.
The observed exclusion down limit for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. The red dotted lines indicate the $\pm 1 \sigma$ on the observed exclusion limit due to the theoretical uncertainties in the signal cross-section.
The expected exclusion for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. Experimental and theoretical systematic uncertainties are applied to background and signal samples and illustrated by the yellow band and the red dotted contour lines, respectively. The red dotted lines indicate the $\pm$ 1 standard-deviation variation on the observed exclusion limit due to theoretical uncertainties in the signal cross-section.
The expected exclusion for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. Experimental and theoretical systematic uncertainties are applied to background and signal samples and illustrated by the yellow band and the red dotted contour lines, respectively. The red dotted lines indicate the $\pm$ 1 standard-deviation variation on the observed exclusion limit due to theoretical uncertainties in the signal cross-section.
The expected exclusion for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. Experimental and theoretical systematic uncertainties are applied to background and signal samples and illustrated by the yellow band and the red dotted contour lines, respectively. The red dotted lines indicate the $\pm$ 1 standard-deviation variation on the observed exclusion limit due to theoretical uncertainties in the signal cross-section.
The expected exclusion for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. Experimental and theoretical systematic uncertainties are applied to background and signal samples and illustrated by the yellow band and the red dotted contour lines, respectively. The red dotted lines indicate the $\pm$ 1 standard-deviation variation on the observed exclusion limit due to theoretical uncertainties in the signal cross-section.
Upper limits on the cross sections for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Upper limits on the cross sections for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Upper limits on the cross sections for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Upper limits on the cross sections for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-LM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-LM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-LM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-LM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-LM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-LM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-LM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-LM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-LM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-LM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-LM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-LM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-LM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-LM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-LM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-LM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-MM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-MM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-MM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-MM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-MM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-MM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-MM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-MM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-MM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-MM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-MM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-MM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-MM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-MM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-MM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-MM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-HM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. 1lb\bar{b}$ production
Signal acceptance in SR-HM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. 1lb\bar{b}$ production
Signal acceptance in SR-HM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. 1lb\bar{b}$ production
Signal acceptance in SR-HM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. 1lb\bar{b}$ production
Signal acceptance in SR-HM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-HM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-HM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-HM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-HM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-HM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-HM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-HM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-HM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-HM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-HM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal acceptance in SR-HM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-LM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-LM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-LM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-LM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-LM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-LM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-LM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-LM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-LM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-LM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-LM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-LM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-LM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-LM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-LM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-LM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-MM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-MM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-MM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-MM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-MM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-MM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-MM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-MM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-MM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-MM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-MM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-MM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-MM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-MM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-MM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-MM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-HM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-HM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-HM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-HM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-HM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-HM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-HM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-HM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-HM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-HM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-HM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-HM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-HM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-HM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-HM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Signal efficiency in SR-HM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.
Event selection cutflow for a representative signal sample for the SR-LM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-LM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-LM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-LM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-LM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-LM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-LM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-LM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-LM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-LM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-LM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-LM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-MM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-MM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-MM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-MM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-MM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-MM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-MM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-MM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-MM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-MM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-MM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-MM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-HM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-HM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-HM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-HM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-HM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-HM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-HM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-HM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-HM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-HM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-HM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the SR-HM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the discovery SR-LM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the discovery SR-LM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the discovery SR-LM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the discovery SR-LM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the discovery SR-MM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the discovery SR-MM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the discovery SR-MM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the discovery SR-MM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the discovery SR-HM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the discovery SR-HM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the discovery SR-HM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
Event selection cutflow for a representative signal sample for the discovery SR-HM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.
A search for physics beyond the standard model in events with at least three charged leptons (electrons or muons) is presented. The data sample corresponds to an integrated luminosity of 137 fb$^{-1}$ of proton-proton collisions at $\sqrt{s} =$ 13 TeV, collected with the CMS detector at the LHC in 2016-2018. The two targeted signal processes are pair production of type-III seesaw heavy fermions and production of a light scalar or pseudoscalar boson in association with a pair of top quarks. The heavy fermions may be manifested as an excess of events with large values of leptonic transverse momenta or missing transverse momentum. The light scalars or pseudoscalars may create a localized excess in the dilepton mass spectra. The results exclude heavy fermions of the type-III seesaw model for masses below 880 GeV at 95% confidence level in the scenario of equal branching fractions to each lepton flavor. This is the most restrictive limit on the flavor-democratic scenario of the type-III seesaw model to date. Assuming a Yukawa coupling of unit strength to top quarks, branching fractions of new scalar (pseudoscalar) bosons to dielectrons or dimuons above 0.004 (0.03) and 0.04 (0.03) are excluded at 95% confidence level for masses in the range 15-75 and 108-340 GeV, respectively. These are the first limits in these channels on an extension of the standard model with scalar or pseudoscalar particles.
The $M_{T}$ distribution in the WZ-enriched region. The last bin contains the overflow events.
The $L_{T}$ distribution in the ttZ-enriched region. The last bin contains the overflow events.
The $S_{T}$ distribution in the ZZ-enriched region. The last bin contains the overflow events.
The $L_{T}$ distribution in the MisID-enriched region. The last bin contains the overflow events.
The $L_{T}+p^{miss}_{T}$ distribution in the 3L below-Z signal region. The last bin contains the overflow events.
The $M_{T}$ distribution in the 3L on-Z signal region. The last bin contains the overflow events.
The $L_{T}+p^{miss}_{T}$ distribution in the 3L above-Z signal region. The last bin contains the overflow events.
The $L_{T}+p^{miss}_{T}$ distribution in the 3L OSSF0 signal region. The last bin contains the overflow events.
The $L_{T}+p^{miss}_{T}$ distribution in the 4L OSSF0 signal region. The last bin contains the overflow events.
The $L_{T}+p^{miss}_{T}$ distribution in the 4L OSSF1 signal region. The last bin contains the overflow events.
The $L_{T}+p^{miss}_{T}$ distribution in the 4L OSSF2 signal region. The last bin contains the overflow events.
The dielectron $M_{OSSF}^{20}$ distribution in the 3L(ee) 0B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.
The dielectron $M_{OSSF}^{300}$ distribution in the 3L(ee) 0B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.
The dielectron $M_{OSSF}^{20}$ distribution in the 3L(ee) 0B, 400<$S_{T}$<800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.
The dielectron $M_{OSSF}^{300}$ distribution in the 3L(ee) 0B, 400<$S_{T}$<800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.
The dielectron $M_{OSSF}^{20}$ distribution in the 3L(ee) 0B, $S_{T}$>800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.
The dielectron $M_{OSSF}^{300}$ distribution in the 3L(ee) 0B, $S_{T}$>800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.
The dielectron $M_{OSSF}^{20}$ distribution in the 3L(ee) 1B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.
The dielectron $M_{OSSF}^{300}$ distribution in the 3L(ee) 1B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.
The dielectron $M_{OSSF}^{20}$ distribution in the 3L(ee) 1B, 400<$S_{T}$<800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.
The dielectron $M_{OSSF}^{300}$ distribution in the 3L(ee) 1B, 400<$S_{T}$<800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.
The dielectron $M_{OSSF}^{20}$ distribution in the 3L(ee) 1B, $S_{T}$>800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.
The dielectron $M_{OSSF}^{300}$ distribution in the 3L(ee) 1B, $S_{T}$>800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.
The dielectron $M_{OSSF}^{20}$ distribution in the 4L(ee) 0B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.
The dielectron $M_{OSSF}^{300}$ distribution in the 4L(ee) 0B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.
The dielectron $M_{OSSF}^{20}$ distribution in the 4L(ee) 0B, $S_{T}$>400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.
The dielectron $M_{OSSF}^{300}$ distribution in the 4L(ee) 0B, $S_{T}$>400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.
The dielectron $M_{OSSF}^{20}$ distribution in the 4L(ee) 1B signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.
The dielectron $M_{OSSF}^{300}$ distribution in the 4L(ee) 1B signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {ee})$=0.05.
The dimuon $M_{OSSF}^{20}$ distribution in the 3L($\mu\mu$) 0B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.
The dimuon $M_{OSSF}^{300}$ distribution in the 3L($\mu\mu$) 0B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.
The dimuon $M_{OSSF}^{20}$ distribution in the 3L($\mu\mu$) 0B, 400<$S_{T}$<800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.
The dimuon $M_{OSSF}^{300}$ distribution in the 3L($\mu\mu$) 0B, 400<$S_{T}$<800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.
The dimuon $M_{OSSF}^{20}$ distribution in the 3L($\mu\mu$) 0B, $S_{T}$>800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.
The dimuon $M_{OSSF}^{300}$ distribution in the 3L($\mu\mu$) 0B, $S_{T}$>800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.
The dimuon $M_{OSSF}^{20}$ distribution in the 3L($\mu\mu$) 1B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.
The dimuon $M_{OSSF}^{300}$ distribution in the 3L($\mu\mu$) 1B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.
The dimuon $M_{OSSF}^{20}$ distribution in the 3L($\mu\mu$) 1B, 400<$S_{T}$<800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.
The dimuon $M_{OSSF}^{300}$ distribution in the 3L($\mu\mu$) 1B, 400<$S_{T}$<800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.
The dimuon $M_{OSSF}^{20}$ distribution in the 3L($\mu\mu$) 1B, $S_{T}$>800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.
The dimuon $M_{OSSF}^{300}$ distribution in the 3L($\mu\mu$) 1B, $S_{T}$>800 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.
The dimuon $M_{OSSF}^{20}$ distribution in the 4L($\mu\mu$) 0B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.
The dimuon $M_{OSSF}^{300}$ distribution in the 4L($\mu\mu$) 0B, $S_{T}$<400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.
The dimuon $M_{OSSF}^{20}$ distribution in the 4L($\mu\mu$) 0B, $S_{T}$>400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.
The dimuon $M_{OSSF}^{300}$ distribution in the 4L($\mu\mu$) 0B, $S_{T}$>400 GeV signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.
The dimuon $M_{OSSF}^{20}$ distribution in the 4L($\mu\mu$) 1B signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.
The dimuon $M_{OSSF}^{300}$ distribution in the 4L($\mu\mu$) 1B signal region. The last bin does not contain the overflow events. The signal is shown with $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$=0.05.
The 95% confidence level exclusion limits for the flavor-democratic scenario on the total production cross section of heavy fermion pairs.
The 95% confidence level exclusion limits on the product of the total production cross section of tt$\phi$(S) and $\mathcal{B}(\phi - {ee})$.
The 95% confidence level exclusion limits on the product of the total production cross section of tt$\phi$(PS) and $\mathcal{B}(\phi - {ee})$.
The 95% confidence level exclusion limits on the product of the total production cross section of tt$\phi$(S) and $\mathcal{B}(\phi - {\mu\mu})$.
The 95% confidence level exclusion limits on the product of the total production cross section of tt$\phi$(PS) and $\mathcal{B}(\phi - {\mu\mu})$.
The 95% confidence level exclusion limits on $g_{t}^2\mathcal{B}(\phi - {ee})$ for tt$\phi$(S).
The 95% confidence level exclusion limits on $g_{t}^2\mathcal{B}(\phi - {ee})$ for tt$\phi$(PS).
The 95% confidence level exclusion limits on $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$ for tt$\phi$(S).
The 95% confidence level exclusion limits on $g_{t}^2\mathcal{B}(\phi - {\mu\mu})$ for tt$\phi$(PS).
Product of the fiducial acceptance and the event selection efficiency for the type-III Seesaw signal model at various signal mass hypotheses calculated after all analysis selection requirements.
Product of the fiducial acceptance and the event selection efficiency for the tt$\phi$ signal models at various signal mass hypotheses calculated after all analysis selection requirements.
A search for the direct production of the supersymmetric partners of $\tau$-leptons (staus) in final states with two hadronically decaying $\tau$-leptons is presented. The analysis uses a dataset of $pp$ collisions corresponding to an integrated luminosity of $139$ fb$^{-1}$, recorded with the ATLAS detector at the Large Hadron Collider at a center-of-mass energy of 13 TeV. No significant deviation from the expected Standard Model background is observed. Limits are derived in scenarios of direct production of stau pairs with each stau decaying into the stable lightest neutralino and one $\tau$-lepton in simplified models where the two stau mass eigenstates are degenerate. Stau masses from 120 GeV to 390 GeV are excluded at 95% confidence level for a massless lightest neutralino.
The observed upper limits on the model cross-section in units of pb for simplified models with combined ${\tilde{\tau}}^{+}_{R,L} {\tilde{\tau}}^{-}_{R,L}$ production. Three points at ${M({\tilde{\chi}}^{0}_{1})}=200GeV$ were removed from the plot but kept in the table because they overlapped with the plot's legend and are far from the exclusion contour.
The observed upper limits on the model cross-section in units of pb for simplified models with combined ${\tilde{\tau}}^{+}_{R,L} {\tilde{\tau}}^{-}_{R,L}$ production. Three points at ${M({\tilde{\chi}}^{0}_{1})}=200GeV$ were removed from the plot but kept in the table because they overlapped with the plot's legend and are far from the exclusion contour.
The observed upper limits on the model cross-section in units of pb for simplified models with ${\tilde{\tau}}_L {\tilde{\tau}}_L$ only production. Three points at $M({\tilde{\chi}}^{0}_{1})=200GeV$ were removed from the plot but kept in the table because they overlapped with the plot's legend and are far from the exclusion contour.
The observed upper limits on the model cross-section in units of pb for simplified models with ${\tilde{\tau}}_L {\tilde{\tau}}_L$ only production. Three points at $M({\tilde{\chi}}^{0}_{1})=200GeV$ were removed from the plot but kept in the table because they overlapped with the plot's legend and are far from the exclusion contour.
The observed 95\% CL exclusion contours for the combined fit of SR-lowMass and SR-highMass for simplified models with combined ${\tilde{\tau}}^{+}_{R,L} {\tilde{\tau}}^{-}_{R,L}$ production.
The observed 95\% CL exclusion contours for the combined fit of SR-lowMass and SR-highMass for simplified models with combined ${\tilde{\tau}}^{+}_{R,L} {\tilde{\tau}}^{-}_{R,L}$ production.
The expected 95% CL exclusion contours for the combined fit of SR-lowMass and SR-highMass for simplified models with combined ${\tilde{\tau}}^{+}_{R,L} {\tilde{\tau}}^{-}_{R,L}$ production.
The expected 95% CL exclusion contours for the combined fit of SR-lowMass and SR-highMass for simplified models with combined ${\tilde{\tau}}^{+}_{R,L} {\tilde{\tau}}^{-}_{R,L}$ production.
The observed 95% CL exclusion contours for the combined fit of SR-lowMass and SR-highMass for simplified models with ${\tilde{\tau}}_L {\tilde{\tau}}_L$ only production.
The observed 95% CL exclusion contours for the combined fit of SR-lowMass and SR-highMass for simplified models with ${\tilde{\tau}}_L {\tilde{\tau}}_L$ only production.
The expected 95% CL exclusion contours for the combined fit of SR-lowMass and SR-highMass for simplified models with ${\tilde{\tau}}_L {\tilde{\tau}}_L$ only production.
The expected 95% CL exclusion contours for the combined fit of SR-lowMass and SR-highMass for simplified models with ${\tilde{\tau}}_L {\tilde{\tau}}_L$ only production.
Observed 95% CL exclusion limits for simplified models with direct stau pair production in SR-lowMass.
Observed 95% CL exclusion limits for simplified models with direct stau pair production in SR-lowMass.
Expected 95% CL exclusion limits for simplified models with direct stau pair production in SR-lowMass.
Expected 95% CL exclusion limits for simplified models with direct stau pair production in SR-lowMass.
Observed 95% CL exclusion limits for simplified models with direct stau pair production in SR-highMass.
Observed 95% CL exclusion limits for simplified models with direct stau pair production in SR-highMass.
Expected 95% CL exclusion limits for simplified models with direct stau pair production in SR-highMass.
Expected 95% CL exclusion limits for simplified models with direct stau pair production in SR-highMass.
Signal acceptance in SR highMass for combined stau final states
Signal acceptance in SR highMass for combined stau final states
Signal acceptance in SR lowMass for combined stau final states
Signal acceptance in SR lowMass for combined stau final states
Signal efficiency in SR highMass for combined stau final states
Signal efficiency in SR highMass for combined stau final states
Signal efficiency in SR lowMass for combined stau final states
Signal efficiency in SR lowMass for combined stau final states
Signal acceptance*efficiency in SR highMass for combined stau final states
Signal acceptance*efficiency in SR highMass for combined stau final states
Signal acceptance*efficiency in SR lowMass for combined stau final states
Signal acceptance*efficiency in SR lowMass for combined stau final states
Cutflow for two reference points (${\tilde{\tau}}^{+}_{R,L} {\tilde{\tau}}^{-}_{R,L}$ production) in SR. The column labelled $N_{weighted}$ shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$, while $N_{raw}$ in brackets shows the results for the generated number of events. The quoted uncertainties are statistical only. The "Generator filter" includes the requirements that two $\tau$ in the event have ${p}_{T} > 15$ GeV and $|\eta| <$ 2.6. The "Baseline Cut" includes the requirement of two baseline $\tau$ with a minimum value at 0.01 of the boosted decision tree discriminant (JetBDTSigTransMin $>$ 0.01) and ${p}_{T, \tau_{1}} > 50$ GeV and ${p}_{T, \tau_{2}} > 40$ GeV. At the step "Trigger & offline cuts", the following requirements are applied: the event is recorded using the asymmetric di-$\tau$ trigger (di-$\tau$ $E_{T}^{miss}$ trigger) in SR-lowMass (SR-highMass), and the lepton $p_{T}$ and $E_{T}^{miss}$ are required at plateau.
Cutflow for two reference points (${\tilde{\tau}}^{+}_{R,L} {\tilde{\tau}}^{-}_{R,L}$ production) in SR. The column labelled $N_{weighted}$ shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$, while $N_{raw}$ in brackets shows the results for the generated number of events. The quoted uncertainties are statistical only. The "Generator filter" includes the requirements that two $\tau$ in the event have ${p}_{T} > 15$ GeV and $|\eta| <$ 2.6. The "Baseline Cut" includes the requirement of two baseline $\tau$ with a minimum value at 0.01 of the boosted decision tree discriminant (JetBDTSigTransMin $>$ 0.01) and ${p}_{T, \tau_{1}} > 50$ GeV and ${p}_{T, \tau_{2}} > 40$ GeV. At the step "Trigger & offline cuts", the following requirements are applied: the event is recorded using the asymmetric di-$\tau$ trigger (di-$\tau$ $E_{T}^{miss}$ trigger) in SR-lowMass (SR-highMass), and the lepton $p_{T}$ and $E_{T}^{miss}$ are required at plateau.
Observed and expected numbers of events in the control and signal regions where all control and signal region bins are included as constraints in the likelihood. The expected event yields of SM processes are given after the background-only fit. The entries marked as "--" are negligible. The uncertainties correspond to the sum in quadrature of statistical and systematic uncertainties. The correlation of systematic uncertainties among control regions and among background processes is fully taken into account.
Observed and expected numbers of events in the control and signal regions where all control and signal region bins are included as constraints in the likelihood. The expected event yields of SM processes are given after the background-only fit. The entries marked as "--" are negligible. The uncertainties correspond to the sum in quadrature of statistical and systematic uncertainties. The correlation of systematic uncertainties among control regions and among background processes is fully taken into account.
The post-fit $m_{T2}$ distribution for SR-lowMass. The stacked histograms show the expected SM backgrounds. The multi-jet contribution is estimated from data using the ABCD method. The contributions of multi-jet and $W$+jets events are scaled with the corresponding normalization factors derived from the background-only fit. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distributions from the SUSY reference points are also shown as dashed lines. The last bin includes the overflow events.
The post-fit $m_{T2}$ distribution for SR-lowMass. The stacked histograms show the expected SM backgrounds. The multi-jet contribution is estimated from data using the ABCD method. The contributions of multi-jet and $W$+jets events are scaled with the corresponding normalization factors derived from the background-only fit. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distributions from the SUSY reference points are also shown as dashed lines. The last bin includes the overflow events.
The post-fit $m_{T2}$ distribution for SR-highMass. The stacked histograms show the expected SM backgrounds. The multi-jet contribution is estimated from data using the ABCD method. The contributions of multi-jet and $W$+jets events are scaled with the corresponding normalization factors derived from the background-only fit. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distributions from the SUSY reference points are also shown as dashed lines. The last bin includes the overflow events.
The post-fit $m_{T2}$ distribution for SR-highMass. The stacked histograms show the expected SM backgrounds. The multi-jet contribution is estimated from data using the ABCD method. The contributions of multi-jet and $W$+jets events are scaled with the corresponding normalization factors derived from the background-only fit. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distributions from the SUSY reference points are also shown as dashed lines. The last bin includes the overflow events.
The $m_{T2}$ post-fit distributions in the multi-jet background validation region VR-F (lowMass). The stacked histograms show the contribution of each relevant SM process. The multi-jet shape is taken from VR-E in the ABCD method and the normalization is determined by the transfer factor $T$ and rescaled by a correction factor determined by the fit. The hatched bands represent the combined statistical and systematic uncertainties in the sum of the SM backgrounds shown. For illustration, the distributions of the SUSY reference points are also shown as dashed lines.
The $m_{T2}$ post-fit distributions in the multi-jet background validation region VR-F (lowMass). The stacked histograms show the contribution of each relevant SM process. The multi-jet shape is taken from VR-E in the ABCD method and the normalization is determined by the transfer factor $T$ and rescaled by a correction factor determined by the fit. The hatched bands represent the combined statistical and systematic uncertainties in the sum of the SM backgrounds shown. For illustration, the distributions of the SUSY reference points are also shown as dashed lines.
The $m_{T2}$ post-fit distributions in the multi-jet background validation VR-F (highMass). The stacked histograms show the contribution of each relevant SM process. The multi-jet shape is taken from VR-E in the ABCD method and the normalization is determined by the transfer factor $T$ and rescaled by a correction factor determined by the fit. The hatched bands represent the combined statistical and systematic uncertainties in the sum of the SM backgrounds shown. For illustration, the distributions of the SUSY reference points are also shown as dashed lines.
The $m_{T2}$ post-fit distributions in the multi-jet background validation VR-F (highMass). The stacked histograms show the contribution of each relevant SM process. The multi-jet shape is taken from VR-E in the ABCD method and the normalization is determined by the transfer factor $T$ and rescaled by a correction factor determined by the fit. The hatched bands represent the combined statistical and systematic uncertainties in the sum of the SM backgrounds shown. For illustration, the distributions of the SUSY reference points are also shown as dashed lines.
The $E_{T}^{miss}$ post-fit distributions in the multi-jet background validation region VR-F (lowMass). The stacked histograms show the contribution of each relevant SM process. The multi-jet shape is taken from VR-E in the ABCD method and the normalization is determined by the transfer factor $T$ and rescaled by a correction factor determined by the fit. The hatched bands represent the combined statistical and systematic uncertainties in the sum of the SM backgrounds shown. For illustration, the distributions of the SUSY reference points are also shown as dashed lines.
The $E_{T}^{miss}$ post-fit distributions in the multi-jet background validation region VR-F (lowMass). The stacked histograms show the contribution of each relevant SM process. The multi-jet shape is taken from VR-E in the ABCD method and the normalization is determined by the transfer factor $T$ and rescaled by a correction factor determined by the fit. The hatched bands represent the combined statistical and systematic uncertainties in the sum of the SM backgrounds shown. For illustration, the distributions of the SUSY reference points are also shown as dashed lines.
The $E_{T}^{miss}$ post-fit distributions in the multi-jet background validation region VR-F (highMass). The stacked histograms show the contribution of each relevant SM process. The multi-jet shape is taken from VR-E in the ABCD method and the normalization is determined by the transfer factor $T$ and rescaled by a correction factor determined by the fit. The hatched bands represent the combined statistical and systematic uncertainties in the sum of the SM backgrounds shown. For illustration, the distributions of the SUSY reference points are also shown as dashed lines.
The $E_{T}^{miss}$ post-fit distributions in the multi-jet background validation region VR-F (highMass). The stacked histograms show the contribution of each relevant SM process. The multi-jet shape is taken from VR-E in the ABCD method and the normalization is determined by the transfer factor $T$ and rescaled by a correction factor determined by the fit. The hatched bands represent the combined statistical and systematic uncertainties in the sum of the SM backgrounds shown. For illustration, the distributions of the SUSY reference points are also shown as dashed lines.
The pre-fit $m_{T2}$ distribution in the $WCR$. The SM backgrounds other than multi-jet production are estimated from MC simulation. The multi-jet contribution is estimated from data using the OS--SS method. The hatched bands represent the combined statistical and systematic uncertainties of the total SM background. For illustration, the distributions of the SUSY reference points are also shown as dashed lines.
The pre-fit $m_{T2}$ distribution in the $WCR$. The SM backgrounds other than multi-jet production are estimated from MC simulation. The multi-jet contribution is estimated from data using the OS--SS method. The hatched bands represent the combined statistical and systematic uncertainties of the total SM background. For illustration, the distributions of the SUSY reference points are also shown as dashed lines.
The post-fit yields in the $WVR$, $TVRs$, $ZVRs$ and $VVVRs$. The SM backgrounds other than multi-jet production are estimated from MC simulation. The multi-jet contribution is negligible and is estimated from data using the ABCD method, using CRs obtained with the same technique used for the SRs. The hatched bands represent the combined statistical and systematic uncertainties of the total SM background. For illustration, the distributions of the SUSY reference points are also shown as dashed lines. The lower panels show the ratio of data to the SM background estimate.
The post-fit yields in the $WVR$, $TVRs$, $ZVRs$ and $VVVRs$. The SM backgrounds other than multi-jet production are estimated from MC simulation. The multi-jet contribution is negligible and is estimated from data using the ABCD method, using CRs obtained with the same technique used for the SRs. The hatched bands represent the combined statistical and systematic uncertainties of the total SM background. For illustration, the distributions of the SUSY reference points are also shown as dashed lines. The lower panels show the ratio of data to the SM background estimate.
A search for supersymmetry through the pair production of electroweakinos with mass splittings near the electroweak scale and decaying via on-shell $W$ and $Z$ bosons is presented for a three-lepton final state. The analyzed proton-proton collision data taken at a center-of-mass energy of $\sqrt{s}$ = 13 TeV were collected between 2015 and 2018 by the ATLAS experiment at the Large Hadron Collider, corresponding to an integrated luminosity of 139 fb$^{-1}$. A search, emulating the recursive jigsaw reconstruction technique with easily reproducible laboratory-frame variables, is performed. The two excesses observed in the 2015-2016 data recursive jigsaw analysis in the low-mass three-lepton phase space are reproduced. Results with the full dataset are in agreement with the Standard Model expectations. They are interpreted to set exclusion limits at 95% confidence level on simplified models of chargino-neutralino pair production for masses up to 345 GeV.
Distributions in SR-low of the data and post-fit background prediction for m<sub>T</sub>. The SR-low event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Distributions in SR-low of the data and post-fit background prediction for m<sub>T</sub>. The SR-low event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Distributions in SR-low of the data and post-fit background prediction for H<sup>boost</sup>. The SR-low event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Distributions in SR-low of the data and post-fit background prediction for H<sup>boost</sup>. The SR-low event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Distributions in SR-low of the data and post-fit background prediction for m<sub>eff</sub><sup>3ℓ</sup>/H<sup>boost</sup>. The SR-low event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Distributions in SR-low of the data and post-fit background prediction for m<sub>eff</sub><sup>3ℓ</sup>/H<sup>boost</sup>. The SR-low event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Distributions in SR-low of the data and post-fit background prediction for p<sub>T</sub><sup>soft</sup>/(p<sub>T</sub><sup>soft</sup> + m<sub>eff</sub><sup>3ℓ</sup>). The SR-low event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Distributions in SR-low of the data and post-fit background prediction for p<sub>T</sub><sup>soft</sup>/(p<sub>T</sub><sup>soft</sup> + m<sub>eff</sub><sup>3ℓ</sup>). The SR-low event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Distributions in SR-ISR of the data and post-fit background prediction for m<sub>T</sub>. The SR-ISR event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Distributions in SR-ISR of the data and post-fit background prediction for m<sub>T</sub>. The SR-ISR event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Distributions in SR-ISR of the data and post-fit background prediction for R(E<sub>T</sub><sup>miss</sup>,jets). The SR-ISR event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Distributions in SR-ISR of the data and post-fit background prediction for R(E<sub>T</sub><sup>miss</sup>,jets). The SR-ISR event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Distributions in SR-ISR of the data and post-fit background prediction for p<sub>T</sub><sup>soft</sup>. The SR-ISR event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Distributions in SR-ISR of the data and post-fit background prediction for p<sub>T</sub><sup>soft</sup>. The SR-ISR event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Distributions in SR-ISR of the data and post-fit background prediction for p<sub>T</sub><sup>jets</sup>. The SR-ISR event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Distributions in SR-ISR of the data and post-fit background prediction for p<sub>T</sub><sup>jets</sup>. The SR-ISR event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Observed exclusion contour on C1N2 production assuming on-shell $W/Z$ decays as a function of the C1/N2 and N1 masses, and derived from the combined fit of low-mass and ISR regions.
Observed exclusion contour on C1N2 production assuming on-shell $W/Z$ decays as a function of the C1/N2 and N1 masses, and derived from the combined fit of low-mass and ISR regions.
Expected exclusion contour on C1N2 production assuming on-shell $W/Z$ decays as a function of the C1/N2 and N1 masses, and derived from the combined fit of low-mass and ISR regions.
Expected exclusion contour on C1N2 production assuming on-shell $W/Z$ decays as a function of the C1/N2 and N1 masses, and derived from the combined fit of low-mass and ISR regions.
Plus 1$\sigma$ uncertainty, varying the signal cross section within its uncertainty, on the observed exclusion contour on C1N2 production assuming on-shell $W/Z$ decays as a function of the C1/N2 and N1 masses, and derived from the combined fit of low-mass and ISR regions.
Plus 1$\sigma$ uncertainty, varying the signal cross section within its uncertainty, on the observed exclusion contour on C1N2 production assuming on-shell $W/Z$ decays as a function of the C1/N2 and N1 masses, and derived from the combined fit of low-mass and ISR regions.
Minus 1$\sigma$ uncertainty, varying the signal cross section within its uncertainty, on the observed exclusion contour on C1N2 production assuming on-shell $W/Z$ decays as a function of the C1/N2 and N1 masses, and derived from the combined fit of low-mass and ISR regions.
Minus 1$\sigma$ uncertainty, varying the signal cross section within its uncertainty, on the observed exclusion contour on C1N2 production assuming on-shell $W/Z$ decays as a function of the C1/N2 and N1 masses, and derived from the combined fit of low-mass and ISR regions.
Plus 1$\sigma$ uncertainty, due to uncertainties in the background prediction and experimental uncertainties affecting the signal, on the expected exclusion contour on C1N2 production assuming on-shell $W/Z$ decays as a function of the C1/N2 and N1 masses, and derived from the combined fit of low-mass and ISR regions.
Plus 1$\sigma$ uncertainty, due to uncertainties in the background prediction and experimental uncertainties affecting the signal, on the expected exclusion contour on C1N2 production assuming on-shell $W/Z$ decays as a function of the C1/N2 and N1 masses, and derived from the combined fit of low-mass and ISR regions.
Minus 1$\sigma$ uncertainty, due to uncertainties in the background prediction and experimental uncertainties affecting the signal, on the expected exclusion contour on C1N2 production assuming on-shell $W/Z$ decays as a function of the C1/N2 and N1 masses, and derived from the combined fit of low-mass and ISR regions.
Minus 1$\sigma$ uncertainty, due to uncertainties in the background prediction and experimental uncertainties affecting the signal, on the expected exclusion contour on C1N2 production assuming on-shell $W/Z$ decays as a function of the C1/N2 and N1 masses, and derived from the combined fit of low-mass and ISR regions.
Upper limits on observed wino-bino simplified model signal cross section $\sigma_\text{obs}^\text{95}$.
Upper limits on observed wino-bino simplified model signal cross section $\sigma_\text{obs}^\text{95}$.
Upper limits on expected wino-bino simplified model signal cross section $\sigma_\text{exp}^\text{95}$.
Upper limits on expected wino-bino simplified model signal cross section $\sigma_\text{exp}^\text{95}$.
Signal acceptance in SR-low, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} \geq 100$ GeV.
Signal acceptance in SR-low, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} \geq 100$ GeV.
Signal efficiency in SR-low, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} \geq 100$ GeV.
Signal efficiency in SR-low, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} \geq 100$ GeV.
Signal acceptance in SR-ISR, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} \geq 100$ GeV.
Signal acceptance in SR-ISR, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} \geq 100$ GeV.
Signal efficiency in SR-ISR, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} \geq 100$ GeV.
Signal efficiency in SR-ISR, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} \geq 100$ GeV.
Signal acceptance in SR-low, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} < 100$ GeV.
Signal acceptance in SR-low, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} < 100$ GeV.
Signal efficiency in SR-low, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} < 100$ GeV.
Signal efficiency in SR-low, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} < 100$ GeV.
Signal acceptance in SR-ISR, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} < 100$ GeV.
Signal acceptance in SR-ISR, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} < 100$ GeV.
Signal efficiency in SR-ISR, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} < 100$ GeV.
Signal efficiency in SR-ISR, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} < 100$ GeV.
The observed and expected yields after the background-only fit in the SRs. The normalization factors of the $WZ$ sample for the low-mass and ISR regions are different and are treated separately in the combined fit. \The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. Combined statistical and systematic uncertainties are presented. The individual uncertainties can be correlated and do not necessarily add in quadrature to equal the total background uncertainty.
The observed and expected yields after the background-only fit in the SRs. The normalization factors of the $WZ$ sample for the low-mass and ISR regions are different and are treated separately in the combined fit. \The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. Combined statistical and systematic uncertainties are presented. The individual uncertainties can be correlated and do not necessarily add in quadrature to equal the total background uncertainty.
Summary of the expected background and data yields in $\text{SR-low}$ and $\text{SR-ISR}$. The second and third columns show the data and total expected background with systematic uncertainties. The fourth column gives the model-independent upper limits at 95\% CL on the visible cross section ($\sigma_\text{vis}$). The fifth and sixth columns give the visible number of observed ($S^{95}_\text{obs}$) and expected ($S^{95}_\text{exp}$) events of a generic beyond-the-SM process, where uncertainties on $S^{95}_\text{exp}$ reflect the $\pm 1 \sigma$ uncertainties on the background estimation. The last column shows the discovery $p$-value and Gaussian significance $Z$ assuming no signal.
Summary of the expected background and data yields in $\text{SR-low}$ and $\text{SR-ISR}$. The second and third columns show the data and total expected background with systematic uncertainties. The fourth column gives the model-independent upper limits at 95\% CL on the visible cross section ($\sigma_\text{vis}$). The fifth and sixth columns give the visible number of observed ($S^{95}_\text{obs}$) and expected ($S^{95}_\text{exp}$) events of a generic beyond-the-SM process, where uncertainties on $S^{95}_\text{exp}$ reflect the $\pm 1 \sigma$ uncertainties on the background estimation. The last column shows the discovery $p$-value and Gaussian significance $Z$ assuming no signal.
Upper limits on observed (expected) wino-bino simplified model signal cross section $\sigma_\text{obs(exp)}^\text{95}$.
Upper limits on observed (expected) wino-bino simplified model signal cross section $\sigma_\text{obs(exp)}^\text{95}$.
Full list of event selections and MC generator-weighted yields and in $\text{SR-ISR}$ for the main $WZ$ background and a representative $\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2}$ signal point of mass 200 GeV and mass splitting $\Delta m = 100$ GeV normalized to 139 fb$^{-1}$. 40000 events were generated.
Full list of event selections and MC generator-weighted yields and in $\text{SR-ISR}$ for the main $WZ$ background and a representative $\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2}$ signal point of mass 200 GeV and mass splitting $\Delta m = 100$ GeV normalized to 139 fb$^{-1}$. 40000 events were generated.
Full list of event selections and MC generator-weighted yields and in $\text{SR-low}$ for the main $WZ$ background and a representative $\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2}$ signal point of mass 200 GeV and mass splitting $\Delta m = 100$ GeV normalized to 139 fb$^{-1}$. 40000 events were generated.
Full list of event selections and MC generator-weighted yields and in $\text{SR-low}$ for the main $WZ$ background and a representative $\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2}$ signal point of mass 200 GeV and mass splitting $\Delta m = 100$ GeV normalized to 139 fb$^{-1}$. 40000 events were generated.
A search for heavy neutral Higgs bosons is performed using the LHC Run 2 data, corresponding to an integrated luminosity of 139 fb$^{-1}$ of proton-proton collisions at $\sqrt{s}=13$ TeV recorded with the ATLAS detector. The search for heavy resonances is performed over the mass range 0.2-2.5 TeV for the $\tau^+\tau^-$ decay with at least one $\tau$-lepton decaying into final states with hadrons. The data are in good agreement with the background prediction of the Standard Model. In the $M_{h}^{125}$ scenario of the Minimal Supersymmetric Standard Model, values of $\tan\beta>8$ and $\tan\beta>21$ are excluded at the 95% confidence level for neutral Higgs boson masses of 1.0 TeV and 1.5 TeV, respectively, where $\tan\beta$ is the ratio of the vacuum expectation values of the two Higgs doublets.
Observed and predicted mTtot distribution in the b-veto category of the 1l1tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table.The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-veto category of the 1l1tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table.The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-veto category of the 1l1tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table.The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-veto category of the 1l1tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table.The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-tag category of the 1l1tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-tag category of the 1l1tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-tag category of the 1l1tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-tag category of the 1l1tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-veto category of the 2tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-veto category of the 2tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-veto category of the 2tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-veto category of the 2tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-tag category of the 2tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-tag category of the 2tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-tag category of the 2tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and predicted mTtot distribution in the b-tag category of the 2tau_h channel. Please note that the bin content is divided by the bin width in the paper figure, but not in the HepData table. The last bin includes overflows. The combined prediction for A and H bosons with masses of 400, 1000 and 1500 GeV and $\tan\beta$ = 6, 12 and 25 respectively in the mh125 scenario are also provided. The combined prediction for A and H bosons with masses of 1000 and 1500 GeV is scaled by 100 in the paper figure, but not in the HepData table.
Observed and expected 95% CL upper limits on the gluon-gluon fusion Higgs boson production cross section times ditau branching fraction as a function of the Higgs boson mass.
Observed and expected 95% CL upper limits on the gluon-gluon fusion Higgs boson production cross section times ditau branching fraction as a function of the Higgs boson mass.
Observed and expected 95% CL upper limits on the gluon-gluon fusion Higgs boson production cross section times ditau branching fraction as a function of the Higgs boson mass.
Observed and expected 95% CL upper limits on the gluon-gluon fusion Higgs boson production cross section times ditau branching fraction as a function of the Higgs boson mass.
Observed and expected 95% CL upper limits on the b-associated Higgs boson production cross section times ditau branching fraction as a function of the boson mass.
Observed and expected 95% CL upper limits on the b-associated Higgs boson production cross section times ditau branching fraction as a function of the boson mass.
Observed and expected 95% CL upper limits on the b-associated Higgs boson production cross section times ditau branching fraction as a function of the boson mass.
Observed and expected 95% CL upper limits on the b-associated Higgs boson production cross section times ditau branching fraction as a function of the boson mass.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered for the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. No theoretical uncertainty is considered when computing these limits.
Acceptance times efficiency for a scalar boson produced by gluon-gluon fusion as a function of the scalar boson mass.
Acceptance times efficiency for a scalar boson produced by gluon-gluon fusion as a function of the scalar boson mass.
Acceptance times efficiency for a scalar boson produced by gluon-gluon fusion as a function of the scalar boson mass.
Acceptance times efficiency for a scalar boson produced by gluon-gluon fusion as a function of the scalar boson mass.
Acceptance times efficiency for a scalar boson produced by b-associated production as a function of the scalar boson mass.
Acceptance times efficiency for a scalar boson produced by b-associated production as a function of the scalar boson mass.
Acceptance times efficiency for a scalar boson produced by b-associated production as a function of the scalar boson mass.
Acceptance times efficiency for a scalar boson produced by b-associated production as a function of the scalar boson mass.
Observed 95% CL upper limits on the scalar boson production cross section times ditau branching fraction as a function of the scalar boson mass and the fraction of the b-associated production. The limits are calculated from a statistical combination of the 1l1tau_h and 2tau_h channels.
Observed 95% CL upper limits on the scalar boson production cross section times ditau branching fraction as a function of the scalar boson mass and the fraction of the b-associated production. The limits are calculated from a statistical combination of the 1l1tau_h and 2tau_h channels.
Observed 95% CL upper limits on the scalar boson production cross section times ditau branching fraction as a function of the scalar boson mass and the fraction of the b-associated production. The limits are calculated from a statistical combination of the 1l1tau_h and 2tau_h channels.
Observed 95% CL upper limits on the scalar boson production cross section times ditau branching fraction as a function of the scalar boson mass and the fraction of the b-associated production. The limits are calculated from a statistical combination of the 1l1tau_h and 2tau_h channels.
Expected 95% CL upper limits on the scalar boson production cross section times ditau branching fraction as a function of the scalar boson mass and the fraction of the b-associated production. The limits are calculated from a statistical combination of the 1l1tau_h and 2tau_h channels.
Expected 95% CL upper limits on the scalar boson production cross section times ditau branching fraction as a function of the scalar boson mass and the fraction of the b-associated production. The limits are calculated from a statistical combination of the 1l1tau_h and 2tau_h channels.
Expected 95% CL upper limits on the scalar boson production cross section times ditau branching fraction as a function of the scalar boson mass and the fraction of the b-associated production. The limits are calculated from a statistical combination of the 1l1tau_h and 2tau_h channels.
Expected 95% CL upper limits on the scalar boson production cross section times ditau branching fraction as a function of the scalar boson mass and the fraction of the b-associated production. The limits are calculated from a statistical combination of the 1l1tau_h and 2tau_h channels.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 200 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 200 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 200 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 200 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 250 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 250 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 250 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 250 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 300 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 300 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 300 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 300 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 350 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 350 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 350 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 350 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 400 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 400 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 400 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 400 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 500 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 500 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 500 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 500 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 600 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 600 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 600 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 600 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 700 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 700 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 700 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 700 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 800 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 800 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 800 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 800 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1000 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1000 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1000 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1000 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1200 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1200 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1200 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1200 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1500 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1500 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1500 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1500 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2000 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2000 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2000 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2000 GeV signal mass point is shown in the HEPData table.
Two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2500 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2500 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2500 GeV signal mass point is shown in the HEPData table.
Observed two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2500 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 200 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 200 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 200 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 250 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 250 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 250 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 300 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 300 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 300 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 350 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 350 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 350 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 400 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 400 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 400 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 500 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 500 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 500 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 600 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 600 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 600 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 700 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 700 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 700 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 800 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 800 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 800 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1000 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1000 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1000 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1200 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1200 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1200 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1500 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1500 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 1500 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2000 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2000 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2000 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2500 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2500 GeV signal mass point is shown in the HEPData table.
Expected two dimensional likelihood scan of the gluon-gluon fusion cross section times branching fraction, $\sigma(gg\phi)\times B(\phi\to\tau\tau)$, vs the b-associated production times branching fraction, $\sigma(bb\phi)\times B(\phi\to\tau\tau)$ for the scalar boson mass ($m_\phi$) indicated in the table. For each mass, 10000 points are scanned. At each point $\Delta(\mathrm{NLL})$ is calculated, defined as the negative-log-likelihood (NLL) of the conditional fit with $\sigma(gg\phi)$ and $\sigma(bb\phi)$ fixed to their values at the point and with the minimum NLL value at any point subtracted. The best-fit point and the preferred 68% and 95% boundaries are found at $2\Delta(\mathrm{NLL})$ values of 0.0, 2.30 and 5.90, respectively. The value of $2\Delta(\mathrm{NLL})$ for 2500 GeV signal mass point is shown in the HEPData table.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the hMSSM scenario. The lowest value of $\tan\beta$ considered by the hMSSM scenario is 0.8 and the highest value of mass is 2 TeV. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\chi})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\chi})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\chi})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\chi})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\chi})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\chi})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\chi})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\chi})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\chi})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\chi})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\chi})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\chi})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The observed 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\tau})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\tau})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\tau})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\tau})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\tau})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\tau})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\tau})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\tau})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\tau})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\tau})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(\widetilde{\tau})$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(\widetilde{\tau})$ scenario is 0.5. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The range of $\tan\beta$ shown in the paper figure and the HEPData is from 1 to 60. The theoretical uncertainty of signal cross section is considered.
The observed 95% CL upper limits with one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(alignment)$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 1.0. The highest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 20.0. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(alignment)$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 1.0. The highest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 20.0. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with plus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(alignment)$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 1.0. The highest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 20.0. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with minus one sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(alignment)$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 1.0. The highest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 20.0. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with plus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(alignment)$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 1.0. The highest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 20.0. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The theoretical uncertainty of signal cross section is considered.
The expected 95% CL upper limits with minus two sigma on $\tan\beta$ as a function of $m_{A}$ in the $M_{h}^{125}(alignment)$ scenario. The lowest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 1.0. The highest value of $\tan\beta$ considered by the $M_{h}^{125}(alignment)$ scenario is 20.0. The points in the region which is called "Not applicable" in the paper figure are kept in the HEPData table. Linear connection is applied in the range of signal mass points from 400 to 1000 GeV in the paper figure. The theoretical uncertainty of signal cross section is considered.
A search for direct pair production of scalar partners of the top quark (top squarks or scalar third-generation up-type leptoquarks) in the all-hadronic $t\bar{t}$ plus missing transverse momentum final state is presented. The analysis of 139 fb$^{-1}$ of ${\sqrt{s}=13}$ TeV proton-proton collision data collected using the ATLAS detector at the LHC yields no significant excess over the Standard Model background expectation. To interpret the results, a supersymmetric model is used where the top squark decays via $\tilde{t} \to t^{(*)} \tilde{\chi}^0_1$, with $t^{(*)}$ denoting an on-shell (off-shell) top quark and $\tilde{\chi}^0_1$ the lightest neutralino. Three specific event selections are optimised for the following scenarios. In the scenario where $m_{\tilde{t}}> m_t+m_{\tilde{\chi}^0_1}$, top squark masses are excluded in the range 400-1250 GeV for $\tilde{\chi}^0_1$ masses below $200$ GeV at 95 % confidence level. In the situation where $m_{\tilde{t}}\sim m_t+m_{\tilde{\chi}^0_1}$, top squark masses in the range 300-630 GeV are excluded, while in the case where $m_{\tilde{t}}< m_W+m_b+m_{\tilde{\chi}^0_1}$ (with $m_{\tilde{t}}-m_{\tilde{\chi}^0_1}\ge 5$ GeV), considered for the first time in an ATLAS all-hadronic search, top squark masses in the range 300-660 GeV are excluded. Limits are also set for scalar third-generation up-type leptoquarks, excluding leptoquarks with masses below $1240$ GeV when considering only leptoquark decays into a top quark and a neutrino.
<b>- - - - - - - - Overview of HEPData Record - - - - - - - -</b> <br><br> <b>Exclusion contours:</b> <ul> <li><a href="?table=stop_obs">Stop exclusion contour (Obs.)</a> <li><a href="?table=stop_obs_down">Stop exclusion contour (Obs. Down)</a> <li><a href="?table=stop_obs_up">Stop exclusion contour (Obs. Up)</a> <li><a href="?table=stop_exp">Stop exclusion contour (Exp.)</a> <li><a href="?table=stop_exp_down">Stop exclusion contour (Exp. Down)</a> <li><a href="?table=stop_exp_up">Stop exclusion contour (Exp. Up)</a> <li><a href="?table=LQ3u_obs">LQ3u exclusion contour (Obs.)</a> <li><a href="?table=LQ3u_obs_down">LQ3u exclusion contour (Obs. Down)</a> <li><a href="?table=LQ3u_obs_up">LQ3u exclusion contour (Obs. Up)</a> <li><a href="?table=LQ3u_exp">LQ3u exclusion contour (Exp.)</a> <li><a href="?table=LQ3u_exp_down">LQ3u exclusion contour (Exp. Down)</a> <li><a href="?table=LQ3u_exp_up">LQ3u exclusion contour (Exp. Up)</a> </ul> <b>Upper limits:</b> <ul> <li><a href="?table=stop_xSecUpperLimit_obs">stop_xSecUpperLimit_obs</a> <li><a href="?table=stop_xSecUpperLimit_exp">stop_xSecUpperLimit_exp</a> <li><a href="?table=LQ3u_xSecUpperLimit_obs">LQ3u_xSecUpperLimit_obs</a> <li><a href="?table=LQ3u_xSecUpperLimit_exp">LQ3u_xSecUpperLimit_exp</a> </ul> <b>Kinematic distributions:</b> <ul> <li><a href="?table=SRATW_metsigST">SRATW_metsigST</a> <li><a href="?table=SRBTT_m_1fatjet_kt12">SRBTT_m_1fatjet_kt12</a> <li><a href="?table=SRC_RISR">SRC_RISR</a> <li><a href="?table=SRD0_htSig">SRD0_htSig</a> <li><a href="?table=SRD1_htSig">SRD1_htSig</a> <li><a href="?table=SRD2_htSig">SRD2_htSig</a> </ul> <b>Cut flows:</b> <ul> <li><a href="?table=cutflow_SRATT">cutflow_SRATT</a> <li><a href="?table=cutflow_SRATW">cutflow_SRATW</a> <li><a href="?table=cutflow_SRAT0">cutflow_SRAT0</a> <li><a href="?table=cutflow_SRB">cutflow_SRB</a> <li><a href="?table=cutflow_SRC">cutflow_SRC</a> <li><a href="?table=cutflow_SRD0">cutflow_SRD0</a> <li><a href="?table=cutflow_SRD1">cutflow_SRD1</a> <li><a href="?table=cutflow_SRD2">cutflow_SRD2</a> </ul> <b>Acceptance and efficiencies:</b> As explained in <a href="https://twiki.cern.ch/twiki/bin/view/AtlasPublic/SupersymmetryPublicResults#summary_of_auxiliary_material">the twiki</a>. <ul> <li> <b>SRATT:</b> <a href="?table=Acc_SRATT">Acc_SRATT</a> <a href="?table=Eff_SRATT">Eff_SRATT</a> <li> <b>SRATW:</b> <a href="?table=Acc_SRATW">Acc_SRATW</a> <a href="?table=Eff_SRATW">Eff_SRATW</a> <li> <b>SRAT0:</b> <a href="?table=Acc_SRAT0">Acc_SRAT0</a> <a href="?table=Eff_SRAT0">Eff_SRAT0</a> <li> <b>SRBTT:</b> <a href="?table=Acc_SRBTT">Acc_SRBTT</a> <a href="?table=Eff_SRBTT">Eff_SRBTT</a> <li> <b>SRBTW:</b> <a href="?table=Acc_SRBTW">Acc_SRBTW</a> <a href="?table=Eff_SRBTW">Eff_SRBTW</a> <li> <b>SRBT0:</b> <a href="?table=Acc_SRBT0">Acc_SRBT0</a> <a href="?table=Eff_SRBT0">Eff_SRBT0</a> <li> <b>SRC1:</b> <a href="?table=Acc_SRC1">Acc_SRC1</a> <a href="?table=Eff_SRC1">Eff_SRC1</a> <li> <b>SRC2:</b> <a href="?table=Acc_SRC2">Acc_SRC2</a> <a href="?table=Eff_SRC2">Eff_SRC2</a> <li> <b>SRC3:</b> <a href="?table=Acc_SRC3">Acc_SRC3</a> <a href="?table=Eff_SRC3">Eff_SRC3</a> <li> <b>SRC4:</b> <a href="?table=Acc_SRC4">Acc_SRC4</a> <a href="?table=Eff_SRC4">Eff_SRC4</a> <li> <b>SRC5:</b> <a href="?table=Acc_SRC5">Acc_SRC5</a> <a href="?table=Eff_SRC5">Eff_SRC5</a> <li> <b>SRD0:</b> <a href="?table=Acc_SRD0">Acc_SRD0</a> <a href="?table=Eff_SRD0">Eff_SRD0</a> <li> <b>SRD1:</b> <a href="?table=Acc_SRD1">Acc_SRD1</a> <a href="?table=Eff_SRD1">Eff_SRD1</a> <li> <b>SRD2:</b> <a href="?table=Acc_SRD2">Acc_SRD2</a> <a href="?table=Eff_SRD2">Eff_SRD2</a> </ul> <b>Truth Code snippets</b> and <b>SLHA</a> files are available under "Resources" (purple button on the left)
<b>- - - - - - - - Overview of HEPData Record - - - - - - - -</b> <br><br> <b>Exclusion contours:</b> <ul> <li><a href="?table=stop_obs">Stop exclusion contour (Obs.)</a> <li><a href="?table=stop_obs_down">Stop exclusion contour (Obs. Down)</a> <li><a href="?table=stop_obs_up">Stop exclusion contour (Obs. Up)</a> <li><a href="?table=stop_exp">Stop exclusion contour (Exp.)</a> <li><a href="?table=stop_exp_down">Stop exclusion contour (Exp. Down)</a> <li><a href="?table=stop_exp_up">Stop exclusion contour (Exp. Up)</a> <li><a href="?table=LQ3u_obs">LQ3u exclusion contour (Obs.)</a> <li><a href="?table=LQ3u_obs_down">LQ3u exclusion contour (Obs. Down)</a> <li><a href="?table=LQ3u_obs_up">LQ3u exclusion contour (Obs. Up)</a> <li><a href="?table=LQ3u_exp">LQ3u exclusion contour (Exp.)</a> <li><a href="?table=LQ3u_exp_down">LQ3u exclusion contour (Exp. Down)</a> <li><a href="?table=LQ3u_exp_up">LQ3u exclusion contour (Exp. Up)</a> </ul> <b>Upper limits:</b> <ul> <li><a href="?table=stop_xSecUpperLimit_obs">stop_xSecUpperLimit_obs</a> <li><a href="?table=stop_xSecUpperLimit_exp">stop_xSecUpperLimit_exp</a> <li><a href="?table=LQ3u_xSecUpperLimit_obs">LQ3u_xSecUpperLimit_obs</a> <li><a href="?table=LQ3u_xSecUpperLimit_exp">LQ3u_xSecUpperLimit_exp</a> </ul> <b>Kinematic distributions:</b> <ul> <li><a href="?table=SRATW_metsigST">SRATW_metsigST</a> <li><a href="?table=SRBTT_m_1fatjet_kt12">SRBTT_m_1fatjet_kt12</a> <li><a href="?table=SRC_RISR">SRC_RISR</a> <li><a href="?table=SRD0_htSig">SRD0_htSig</a> <li><a href="?table=SRD1_htSig">SRD1_htSig</a> <li><a href="?table=SRD2_htSig">SRD2_htSig</a> </ul> <b>Cut flows:</b> <ul> <li><a href="?table=cutflow_SRATT">cutflow_SRATT</a> <li><a href="?table=cutflow_SRATW">cutflow_SRATW</a> <li><a href="?table=cutflow_SRAT0">cutflow_SRAT0</a> <li><a href="?table=cutflow_SRB">cutflow_SRB</a> <li><a href="?table=cutflow_SRC">cutflow_SRC</a> <li><a href="?table=cutflow_SRD0">cutflow_SRD0</a> <li><a href="?table=cutflow_SRD1">cutflow_SRD1</a> <li><a href="?table=cutflow_SRD2">cutflow_SRD2</a> </ul> <b>Acceptance and efficiencies:</b> As explained in <a href="https://twiki.cern.ch/twiki/bin/view/AtlasPublic/SupersymmetryPublicResults#summary_of_auxiliary_material">the twiki</a>. <ul> <li> <b>SRATT:</b> <a href="?table=Acc_SRATT">Acc_SRATT</a> <a href="?table=Eff_SRATT">Eff_SRATT</a> <li> <b>SRATW:</b> <a href="?table=Acc_SRATW">Acc_SRATW</a> <a href="?table=Eff_SRATW">Eff_SRATW</a> <li> <b>SRAT0:</b> <a href="?table=Acc_SRAT0">Acc_SRAT0</a> <a href="?table=Eff_SRAT0">Eff_SRAT0</a> <li> <b>SRBTT:</b> <a href="?table=Acc_SRBTT">Acc_SRBTT</a> <a href="?table=Eff_SRBTT">Eff_SRBTT</a> <li> <b>SRBTW:</b> <a href="?table=Acc_SRBTW">Acc_SRBTW</a> <a href="?table=Eff_SRBTW">Eff_SRBTW</a> <li> <b>SRBT0:</b> <a href="?table=Acc_SRBT0">Acc_SRBT0</a> <a href="?table=Eff_SRBT0">Eff_SRBT0</a> <li> <b>SRC1:</b> <a href="?table=Acc_SRC1">Acc_SRC1</a> <a href="?table=Eff_SRC1">Eff_SRC1</a> <li> <b>SRC2:</b> <a href="?table=Acc_SRC2">Acc_SRC2</a> <a href="?table=Eff_SRC2">Eff_SRC2</a> <li> <b>SRC3:</b> <a href="?table=Acc_SRC3">Acc_SRC3</a> <a href="?table=Eff_SRC3">Eff_SRC3</a> <li> <b>SRC4:</b> <a href="?table=Acc_SRC4">Acc_SRC4</a> <a href="?table=Eff_SRC4">Eff_SRC4</a> <li> <b>SRC5:</b> <a href="?table=Acc_SRC5">Acc_SRC5</a> <a href="?table=Eff_SRC5">Eff_SRC5</a> <li> <b>SRD0:</b> <a href="?table=Acc_SRD0">Acc_SRD0</a> <a href="?table=Eff_SRD0">Eff_SRD0</a> <li> <b>SRD1:</b> <a href="?table=Acc_SRD1">Acc_SRD1</a> <a href="?table=Eff_SRD1">Eff_SRD1</a> <li> <b>SRD2:</b> <a href="?table=Acc_SRD2">Acc_SRD2</a> <a href="?table=Eff_SRD2">Eff_SRD2</a> </ul> <b>Truth Code snippets</b> and <b>SLHA</a> files are available under "Resources" (purple button on the left)
The observed exclusion contour at 95% CL as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$. Masses that are within the contours are excluded.
The observed exclusion contour at 95% CL as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$. Masses that are within the contours are excluded.
The expected exclusion contour at 95% CL as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$. Masses that are within the contour are excluded.
The expected exclusion contour at 95% CL as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$. Masses that are within the contour are excluded.
The minus $1\sigma$ variation of observed exclusion contour obtained by varying the signal cross section within its uncertainty. The contour is given as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$.
The minus $1\sigma$ variation of observed exclusion contour obtained by varying the signal cross section within its uncertainty. The contour is given as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$.
The plus $1\sigma$ variation of observed exclusion contour obtained by varying the signal cross section within its uncertainty. The contour is given as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$.
The plus $1\sigma$ variation of observed exclusion contour obtained by varying the signal cross section within its uncertainty. The contour is given as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$.
The minus $1\sigma$ variation of expected exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties (excluding signal cross section uncertainties). The contour is given as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$.
The minus $1\sigma$ variation of expected exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties (excluding signal cross section uncertainties). The contour is given as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$.
The plus $1\sigma$ variation of expected exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties (excluding signal cross section uncertainties). The contour is given as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$.
The plus $1\sigma$ variation of expected exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties (excluding signal cross section uncertainties). The contour is given as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$.
The observed exclusion contour at 95% CL as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$. Points that are within the contours are excluded.
The observed exclusion contour at 95% CL as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$. Points that are within the contours are excluded.
The expected exclusion contour at 95% CL as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$. Points that are within the contours are excluded.
The expected exclusion contour at 95% CL as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$. Points that are within the contours are excluded.
The minus $1\sigma$ variation of observed exclusion contour obtained by varying the signal cross section within its uncertainty. The contour is given as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$
The minus $1\sigma$ variation of observed exclusion contour obtained by varying the signal cross section within its uncertainty. The contour is given as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$
The plus $1\sigma$ variation of observed exclusion contour obtained by varying the signal cross section within its uncertainty. The contour is given as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$
The plus $1\sigma$ variation of observed exclusion contour obtained by varying the signal cross section within its uncertainty. The contour is given as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$
The plus $1\sigma$ variation of expected exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties (excluding signal cross section uncertainties). The contour is given as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$
The plus $1\sigma$ variation of expected exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties (excluding signal cross section uncertainties). The contour is given as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$
The minus $1\sigma$ variation of expected exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties (excluding signal cross section uncertainties). The contour is given as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$
The minus $1\sigma$ variation of expected exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties (excluding signal cross section uncertainties). The contour is given as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$
Model dependent upper limit on the cross section for the $(\tilde{t},\tilde{\chi}^{0}_{1})$ signal grid. The column titled 'Leading Region' stores information on which of the fit regions (SRA-B, SRC or SRD) is the dominant based on the expected CLs values.
Model dependent upper limit on the cross section for the $(\tilde{t},\tilde{\chi}^{0}_{1})$ signal grid. The column titled 'Leading Region' stores information on which of the fit regions (SRA-B, SRC or SRD) is the dominant based on the expected CLs values.
Expected model dependent upper limit on the cross section for the $(\tilde{t},\tilde{\chi}^{0}_{1})$ signal grid. The column titled 'Leading Region' stores information on which of the fit regions (SRA-B, SRC or SRD) is the dominant based on the expected CLs values.
Expected model dependent upper limit on the cross section for the $(\tilde{t},\tilde{\chi}^{0}_{1})$ signal grid. The column titled 'Leading Region' stores information on which of the fit regions (SRA-B, SRC or SRD) is the dominant based on the expected CLs values.
Model dependent upper limit on the cross section for the $LQ_{3}^{u}$ signal grid with $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau))=0$ %. Only the SRA-B fit region is considered in this interpretation.
Model dependent upper limit on the cross section for the $LQ_{3}^{u}$ signal grid with $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau))=0$ %. Only the SRA-B fit region is considered in this interpretation.
Expected model dependent upper limit on the cross section for the $LQ_{3}^{u}$ signal grid with $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau))=0$ %. Only the SRA-B fit region is considered in this interpretation.
Expected model dependent upper limit on the cross section for the $LQ_{3}^{u}$ signal grid with $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau))=0$ %. Only the SRA-B fit region is considered in this interpretation.
The distributions of $S$ in SRA-TW. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.
The distributions of $S$ in SRA-TW. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.
The distributions of $\it{m}^{\mathrm{R=1.2}}_{1}$ in SRB-TT. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.
The distributions of $\it{m}^{\mathrm{R=1.2}}_{1}$ in SRB-TT. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.
The distributions of R$_{ISR}$ in SRC signal regions before R$_{ISR}$ cuts are applied. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.
The distributions of R$_{ISR}$ in SRC signal regions before R$_{ISR}$ cuts are applied. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.
The distributions of $E^{miss}_{T}/\sqrt{H_{T}}$ in SRD0. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.
The distributions of $E^{miss}_{T}/\sqrt{H_{T}}$ in SRD0. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.
The distributions of $E^{miss}_{T}/\sqrt{H_{T}}$ in SRD1. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.
The distributions of $E^{miss}_{T}/\sqrt{H_{T}}$ in SRD1. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.
The distributions of $E^{miss}_{T}/\sqrt{H_{T}}$ in SRD2. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.
The distributions of $E^{miss}_{T}/\sqrt{H_{T}}$ in SRD2. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.
Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (1300,1)\ \mathrm{GeV} $ in SRA-TT. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 30000 raw MC events were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.
Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (1300,1)\ \mathrm{GeV} $ in SRA-TT. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 30000 raw MC events were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.
Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (1300,1)\ \mathrm{GeV} $ in SRA-TW. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 30000 raw MC events were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.
Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (1300,1)\ \mathrm{GeV} $ in SRA-TW. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 30000 raw MC events were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.
Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (1300,1)\ \mathrm{GeV} $ in SRA-T0. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 30000 raw MC events were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.
Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (1300,1)\ \mathrm{GeV} $ in SRA-T0. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 30000 raw MC events were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.
Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (700,400)\ \mathrm{GeV} $ in signal regions SRB-TT, SRB-TW and SRB-T0. The regions differ by the last cut applied. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 60000 raw MC events were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.
Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (700,400)\ \mathrm{GeV} $ in signal regions SRB-TT, SRB-TW and SRB-T0. The regions differ by the last cut applied. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 60000 raw MC events were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.
Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (500,327)\ \mathrm{GeV} $ in regions SRC-1, SRC-2, SRC-3, SRC-4 and SRC-5. The regions differ by the last cut applied. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 150000 raw MC events with filter efficiency of 0.384 were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.
Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (500,327)\ \mathrm{GeV} $ in regions SRC-1, SRC-2, SRC-3, SRC-4 and SRC-5. The regions differ by the last cut applied. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 150000 raw MC events with filter efficiency of 0.384 were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.
Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (550,500)\ \mathrm{GeV} $ in SRD0. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 90000 raw MC events with filter efficiency of 0.428 were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.
Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (550,500)\ \mathrm{GeV} $ in SRD0. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 90000 raw MC events with filter efficiency of 0.428 were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.
Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (550,500)\ \mathrm{GeV} $ in SRD1. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 90000 raw MC events with filter efficiency of 0.428 were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.
Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (550,500)\ \mathrm{GeV} $ in SRD1. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 90000 raw MC events with filter efficiency of 0.428 were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.
Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (550,500)\ \mathrm{GeV} $ in SRD2. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 90000 raw MC events with filter efficiency of 0.428 were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.
Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (550,500)\ \mathrm{GeV} $ in SRD2. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 90000 raw MC events with filter efficiency of 0.428 were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.
Signal acceptance in SRA-TT for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal acceptance in SRA-TT for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal efficiency in SRA-TT for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.
Signal efficiency in SRA-TT for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.
Signal acceptance in SRA-TW for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal acceptance in SRA-TW for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal efficiency in SRA-TW for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.
Signal efficiency in SRA-TW for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.
Signal acceptance in SRA-T0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal acceptance in SRA-T0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal efficiency in SRA-T0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.
Signal efficiency in SRA-T0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.
Signal acceptance in SRB-TT for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal acceptance in SRB-TT for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal efficiency in SRB-TT for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.
Signal efficiency in SRB-TT for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.
Signal acceptance in SRB-TW for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal acceptance in SRB-TW for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal efficiency in SRB-TW for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.
Signal efficiency in SRB-TW for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.
Signal acceptance in SRB-T0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal acceptance in SRB-T0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal efficiency in SRB-T0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.
Signal efficiency in SRB-T0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.
Signal acceptance in SRC1 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal acceptance in SRC1 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal efficiency in SRC1 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal efficiency in SRC1 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal acceptance in SRC2 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal acceptance in SRC2 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal efficiency in SRC2 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal efficiency in SRC2 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal acceptance in SRC3 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal acceptance in SRC3 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal efficiency in SRC3 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal efficiency in SRC3 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal acceptance in SRC4 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal acceptance in SRC4 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal efficiency in SRC4 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ plane showed in the paper plot.
Signal efficiency in SRC4 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ plane showed in the paper plot.
Signal acceptance in SRC5 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ plane showed in the paper plot.
Signal acceptance in SRC5 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ plane showed in the paper plot.
Signal efficiency in SRC5 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal efficiency in SRC5 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal acceptance in SRD0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal acceptance in SRD0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal efficiency in SRD0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal efficiency in SRD0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal acceptance in SRD1 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal acceptance in SRD1 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal efficiency in SRD1 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal efficiency in SRD1 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal acceptance in SRD2 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal acceptance in SRD2 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal efficiency in SRD2 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
Signal efficiency in SRD2 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.
This paper describes a search for beyond the Standard Model decays of the Higgs boson into a pair of new spin-0 particles subsequently decaying into $b$-quark pairs, $H \rightarrow aa \rightarrow (b\bar{b})(b\bar{b})$, using proton-proton collision data collected by the ATLAS detector at the Large Hadron Collider at center-of-mass energy $\sqrt{s}=13$ TeV. This search focuses on the regime where the decay products are collimated and in the range $15 \leq m_a \leq 30$ GeV and is complementary to a previous search in the same final state targeting the regime where the decay products are well separated and in the range $20 \leq m_a \leq 60$ GeV. A novel strategy for the identification of the $a \rightarrow b\bar{b}$ decays is deployed to enhance the efficiency for topologies with small separation angles. The search is performed with 36 fb$^{-1}$ of integrated luminosity collected in 2015 and 2016 and sets upper limits on the production cross-section of $H \rightarrow aa \rightarrow (b\bar{b})(b\bar{b})$, where the Higgs boson is produced in association with a $Z$ boson.
Summary of the 95% CL upper limits on $\sigma_{ZH} BR(H\rightarrow aa \rightarrow (b\bar{b})(b\bar{b}))$. Both observed and expected limits are listed. In the case of the expected limits, one- and two-standard-deviation uncertainty bands are also listed.
Summary of the 95% CL upper limits on $\sigma_{ZH} BR(H\rightarrow aa \rightarrow (b\bar{b})(b\bar{b}))$. Both observed and expected limits are listed. In the case of the expected limits, one- and two-standard-deviation uncertainty bands are also listed.
Summary of the observed 95% CL upper limits on $\sigma_{ZH} BR(H\rightarrow aa \rightarrow (b\bar{b})(b\bar{b}))$ for the resolved analysis.
Summary of the 95% C.L. upper limits on $\sigma_{ZH} BR(H\rightarrow aa \rightarrow (b\bar{b})(b\bar{b}))$ for the dilepton channel in the resolved analysis. The observed limits are shown, together with the expected limits (dotted black lines). In the case of the expected limits, one- and two-standard-deviation uncertainty bands are also displayed. The data was published in JHEP 10 (2018) 031.
Efficiency and acceptance for simulated $ZH(\rightarrow aa\rightarrow (b\bar{b})(b\bar{b}))$ samples in two signal regions (SR) of the analysis, one with two $a\to b\bar{b}$ candidates in the High Purity Category (HPC), and the other with one $a\to b\bar{b}$ candidate in the High Purity Category (HPC) and one in the Low Purity Category (LPC).
Efficiency and acceptance for simulated $ZH(\rightarrow aa\rightarrow (b\bar{b})(b\bar{b}))$ samples in two signal regions (SR) of the analysis, one with two $a\to b\bar{b}$ candidates in the High Purity Category (HPC), and the other with one $a\to b\bar{b}$ candidate in the High Purity Category (HPC) and one in the Low Purity Category (LPC).
Event yields for a simulated $ZH(\rightarrow aa\rightarrow (b\bar{b})(b\bar{b}))$ sample with $m_a = 17.5\,\text{GeV}$. The signal sample is produced with cross section equals to the standard model $pp\to ZH$, i.e. $0.88\,\text{pb}$. Cut 0 corresponds to the initial number of events. Cut 1 requires the single lepton trigger. Cut 2 requires 2 identified leptons. Cut 3 requires the Z-boson mass window. Cut 4 requires 2 reconstructed $a\to b\bar{b}$ candidates. Cut 5a requires 2 identified $a\to b\bar{b}$ candidates in the 1HPC1LPC region. Cut 6a requires the 2 $a\to b\bar{b}$ candidates in the 1HPC1LPC region to be inside the Higgs mass window. Cut 5b requires 2 identified $a\to b\bar{b}$ candidates in the 2HPC region. Cut 6b requires the 2 $a\to b\bar{b}$ candidates in the 2HPC region to be inside the Higgs mass window.
Event yields for a simulated $ZH(\rightarrow aa\rightarrow (b\bar{b})(b\bar{b}))$ sample with $m_a = 17.5\,\text{GeV}$. The signal sample is produced with cross section equals to the standard model $pp\to ZH$, i.e. $0.88\,\text{pb}$. Cut 0 corresponds to the initial number of events. Cut 1 requires the single lepton trigger. Cut 2 requires 2 identified leptons. Cut 3 requires the Z-boson mass window. Cut 4 requires 2 reconstructed $a\to b\bar{b}$ candidates. Cut 5a requires 2 identified $a\to b\bar{b}$ candidates in the 1HPC1LPC region. Cut 6a requires the 2 $a\to b\bar{b}$ candidates in the 1HPC1LPC region to be inside the Higgs mass window. Cut 5b requires 2 identified $a\to b\bar{b}$ candidates in the 2HPC region. Cut 6b requires the 2 $a\to b\bar{b}$ candidates in the 2HPC region to be inside the Higgs mass window.
Background yield table for Z+jets, $t\bar{t}$, and rare sources. Observed data yield. Signal $ZH(\rightarrow aa\rightarrow (b\bar{b})(b\bar{b}))$ yield with $m_a = 20\,\text{GeV}$. The signal sample is produced with cross section equals to the standard model $pp\to ZH$, i.e. $0.88\,\text{pb}$, with a branching ratio set to 1 for the $H \rightarrow aa$ decay, whereas the ATLAS figure attached to this entry instead uses the upper-limit branching ratio (smaller than 1). The table includes the yields in two signal regions with leptons consistent with an on-shell Z-boson decay, one with 2 $a\to b\bar{b}$ candidates in the 2HPC region and one with 2 $a\to b\bar{b}$ candidates in the 1HPC1LPC region. The table also includes the yields in four control regions, one with leptons consistent with an on-shell Z-boson decay and 2 $a\to b\bar{b}$ candidates in the Low Purity Category (LPC), and three others where the leptons are not consistent an on-shell Z-boson decay.
Background yield table for Z+jets, $t\bar{t}$, and rare sources. Observed data yield. Signal $ZH(\rightarrow aa\rightarrow (b\bar{b})(b\bar{b}))$ yield with $m_a = 20\,\text{GeV}$. The signal sample is produced with cross section equals to the standard model $pp\to ZH$, i.e. $0.88\,\text{pb}$. The table includes the yields in two signal regions with leptons consistent with an on-shell Z-boson decay, one with 2 $a\to b\bar{b}$ candidates in the 2HPC region and one with 2 $a\to b\bar{b}$ candidates in the 1HPC1LPC region. The table also includes the yields in four control regions, one with leptons consistent with an on-shell Z-boson decay and 2 $a\to b\bar{b}$ candidates in the Low Purity Category (LPC), and three others where the leptons are not consistent an on-shell Z-boson decay.
A search for new-physics resonances decaying into a lepton and a jet performed by the ATLAS experiment is presented. Scalar leptoquarks pair-produced in $pp$ collisions at $\sqrt{s}=13$ TeV at the Large Hadron Collider are considered using an integrated luminosity of 139 fb$^{-1}$, corresponding to the full Run 2 dataset. They are searched for in events with two electrons or two muons and two or more jets, including jets identified as arising from the fragmentation of $c$- or $b$-quarks. The observed yield in each channel is consistent with the Standard Model background expectation. Leptoquarks with masses below 1.8 TeV and 1.7 TeV are excluded in the electron and muon channels, respectively, assuming a branching ratio into a charged lepton and a quark of 100%, with minimal dependence on the quark flavour. Upper limits on the aforementioned branching ratio are also given as a function of the leptoquark mass.
Distribution of the resonance mass in the pretag Signal Region of the $ qe$ channel for the post-fit background, the observed data, and the expected signal with $m_{LQ} = 1$ TeV.
Distribution of the resonance mass in the pretag Signal Region of the $ q\mu$ channel for the post-fit background, the observed data, and the expected signal with $m_{LQ} = 1$ TeV.
Distribution of the resonance mass in the untagged Signal Region of the $ ce$ channel for the post-fit background, the observed data, and the expected signal with $m_{LQ} = 1$ TeV.
Distribution of the resonance mass in the c-tag Signal Region of the $ ce$ channel for the post-fit background, the observed data, and the expected signal with $m_{LQ} = 1$ TeV.
Distribution of the resonance mass in the b-tag Signal Region of the $ ce$ channel for the post-fit background, the observed data, and the expected signal with $m_{LQ} = 1$ TeV.
Distribution of the resonance mass in the untagged Signal Region of the $ c\mu$ channel for the post-fit background, the observed data, and the expected signal with $m_{LQ} = 1$ TeV.
Distribution of the resonance mass in the c-tag Signal Region of the $ c\mu$ channel for the post-fit background, the observed data, and the expected signal with $m_{LQ} = 1$ TeV.
Distribution of the resonance mass in the b-tag Signal Region of the $ c\mu$ channel for the post-fit background, the observed data, and the expected signal with $m_{LQ} = 1$ TeV.
Distribution of the resonance mass in the 0-tag Signal Region of the $ be$ channel for the post-fit background, the observed data, and the expected signal with $m_{LQ} = 1$ TeV.
Distribution of the resonance mass in the 1-tag Signal Region of the $ be$ channel for the post-fit background, the observed data, and the expected signal with $m_{LQ} = 1$ TeV.
Distribution of the resonance mass in the 2-tag Signal Region of the $ be$ channel for the post-fit background, the observed data, and the expected signal with $m_{LQ} = 1$ TeV.
Distribution of the resonance mass in the 0-tag Signal Region of the $ b\mu$ channel for the post-fit background, the observed data, and the expected signal with $m_{LQ} = 1$ TeV.
Distribution of the resonance mass in the 1-tag Signal Region of the $ b\mu$ channel for the post-fit background, the observed data, and the expected signal with $m_{LQ} = 1$ TeV.
Distribution of the resonance mass in the 2-tag Signal Region of the $ b\mu$ channel for the post-fit background, the observed data, and the expected signal with $m_{LQ} = 1$ TeV.
The observed and expected limits on the leptoquark pair production cross-section at 95% CL for $\mathcal{B}=1$ into electrons, shown as a function of $m_{LQ}$ for the $qe$ channel.
The observed and expected limits on the leptoquark pair production cross-section at 95% CL for $\mathcal{B}=1$ into muons, shown as a function of $m_{LQ}$ for the $q\mu$ channel.
The observed and expected limits on the leptoquark pair production cross-section at 95% CL for $\mathcal{B}=1$ into electrons, shown as a function of $m_{LQ}$ for the $ce$ channel.
The observed and expected limits on the leptoquark pair production cross-section at 95% CL for $\mathcal{B}=1$ into muons, shown as a function of $m_{LQ}$ for the $c\mu$ channel.
The observed and expected limits on the leptoquark pair production cross-section at 95% CL for $\mathcal{B}=1$ into electrons, shown as a function of $m_{LQ}$ for the $be$ channel.
The observed and expected limits on the leptoquark pair production cross-section at 95% CL for $\mathcal{B}=1$ into muons, shown as a function of $m_{LQ}$ for the $b\mu$ channel.
The observed and expected limits on the leptoquark branching ratio at 95% CL, shown as a function of $m_{LQ}$ for the $qe$ channel.
The observed and expected limits on the leptoquark branching ratio at 95% CL, shown as a function of $m_{LQ}$ for the $q\mu$ channel.
The observed and expected limits on the leptoquark branching ratio at 95% CL, shown as a function of $m_{LQ}$ for the $ce$ channel.
The observed and expected limits on the leptoquark branching ratio at 95% CL, shown as a function of $m_{LQ}$ for the $c\mu$ channel.
The observed and expected limits on the leptoquark branching ratio at 95% CL, shown as a function of $m_{LQ}$ for the $be$ channel.
The observed and expected limits on the leptoquark branching ratio at 95% CL, shown as a function of $m_{LQ}$ for the $b\mu$ channel.
The signal selection efficiency x acceptance summed over all signal regions, for all masses and LQ decay channels considered.
The observed and expected limits for all masses and LQ decay channels considered.
Cutflow Table in the electron channel, considering signal samples with LQ mass of 1 TeV.
Cutflow Table in the muon channel, considering signal samples with LQ mass of 1 TeV.
In this paper, a new technique for reconstructing and identifying hadronically decaying $\tau^+\tau^-$ pairs with a large Lorentz boost, referred to as the di-$\tau$ tagger, is developed and used for the first time in the ATLAS experiment at the Large Hadron Collider. A benchmark di-$\tau$ tagging selection is employed in the search for resonant Higgs boson pair production, where one Higgs boson decays into a boosted $b\bar{b}$ pair and the other into a boosted $\tau^+\tau^-$ pair, with two hadronically decaying $\tau$-leptons in the final state. Using 139 fb$^{-1}$ of proton$-$proton collision data recorded at a centre-of-mass energy of 13 TeV, the efficiency of the di-$\tau$ tagger is determined and the background with quark- or gluon-initiated jets misidentified as di-$\tau$ objects is estimated. The search for a heavy, narrow, scalar resonance produced via gluon$-$gluon fusion and decaying into two Higgs bosons is carried out in the mass range 1$-$3 TeV using the same dataset. No deviations from the Standard Model predictions are observed, and 95% confidence-level exclusion limits are set on this model.
Signal acceptance times selection efficiency as a function of the resonance mass, at various stages of the event selection. From top to bottom: an event pre-selection (trigger, object definitions and $E_{T}^{miss}>10$ GeV) is performed first; the requirements on the di-$\tau$ object and large-$R$ jet detailed in the text are then applied; finally, the $HH$ SR definition must be satisfied.
Signal acceptance times selection efficiency as a function of the resonance mass, at various stages of the event selection. From top to bottom: an event pre-selection (trigger, object definitions and $E_{T}^{miss}>10$ GeV) is performed first; the requirements on the di-$\tau$ object and large-$R$ jet detailed in the text are then applied; finally, the $HH$ SR definition must be satisfied.
Distribution of $m^{vis}_{HH}$ after applying all the event selection that define the $HH$ SR, except the requirement on $m^{vis}_{HH}$. The background labelled as "Others" contains $W$+jets, diboson, $t\bar{t}$ and single-top-quark processes. The $X\rightarrow HH \rightarrow b\bar{b}\tau^{+}\tau^{-}$ signal is overlaid for two resonance mass hypotheses with a cross-section set to the expected limit, while all backgrounds are pre-fit. The first and the last bins contains the under-flow and over-flow bin entries, respectively. The hatched bands represent combined statistical and systematic uncertainties.
Distribution of $m^{vis}_{HH}$ after applying all the event selection that define the $HH$ SR, except the requirement on $m^{vis}_{HH}$. The background labelled as "Others" contains $W$+jets, diboson, $t\bar{t}$ and single-top-quark processes. The $X\rightarrow HH \rightarrow b\bar{b}\tau^{+}\tau^{-}$ signal is overlaid for two resonance mass hypotheses with a cross-section set to the expected limit, while all backgrounds are pre-fit. The first and the last bins contains the under-flow and over-flow bin entries, respectively. The hatched bands represent combined statistical and systematic uncertainties.
Event yields of the various estimated backgrounds and data, computed in the signal region of the search for $X\rightarrow HH \rightarrow b\bar{b}\tau^{+}\tau^{-}$. The background labelled as "Others" contains $W$+jets, diboson, $t\bar{t}$ and single-top-quark processes. Statistical and systematic uncertainties are quoted. The background yields and uncertainties are pre-fit and are found to be similar to those post-fit.
Event yields of the various estimated backgrounds and data, computed in the signal region of the search for $X\rightarrow HH \rightarrow b\bar{b}\tau^{+}\tau^{-}$. The background labelled as "Others" contains $W$+jets, diboson, $t\bar{t}$ and single-top-quark processes. Statistical and systematic uncertainties are quoted. The background yields and uncertainties are pre-fit and are found to be similar to those post-fit.
Expected and observed 95% CL upper limits on the production of a heavy, narrow-width, scalar resonance decaying to a pair of Higgs bosons ($X\rightarrow HH$). The final state used in the search consists of a boosted $b\bar{b}$ pair and a boosted hadronically decaying $\tau^{+}\tau^{-}$ pair, and the SM braching ratio of the Higgs boson are assumed. The $\pm 1\sigma$ and $\pm 2\sigma$ variations about the expected limit are indicated by the error bands. Two different requirements are applied on the visible mass of the two boosted Higgs boson candidates for the resonance mass hypotheses of 1.6 TeV and 2.5 TeV, leading to discontinuities in the limits (at 1.6 TeV, the difference between imposing no requirement and $m^{vis}_{HH}>900$ GeV is less than 1% though).
Expected and observed 95% CL upper limits on the production of a heavy, narrow-width, scalar resonance decaying to a pair of Higgs bosons ($X\rightarrow HH$). The final state used in the search consists of a boosted $b\bar{b}$ pair and a boosted hadronically decaying $\tau^{+}\tau^{-}$ pair, and the SM braching ratio of the Higgs boson are assumed. The $\pm 1\sigma$ and $\pm 2\sigma$ variations about the expected limit are indicated by the error bands. Two different requirements are applied on the visible mass of the two boosted Higgs boson candidates for the resonance mass hypotheses of 1.6 TeV and 2.5 TeV, leading to discontinuities in the limits (at 1.6 TeV, the difference between imposing no requirement and $m^{vis}_{HH}>900$ GeV is less than 1% though).
Results of a search for new particles decaying into eight or more jets and moderate missing transverse momentum are presented. The analysis uses 139 fb$^{-1}$ of proton$-$proton collision data at $\sqrt{s} = 13$ TeV collected by the ATLAS experiment at the Large Hadron Collider between 2015 and 2018. The selection rejects events containing isolated electrons or muons, and makes requirements according to the number of $b$-tagged jets and the scalar sum of masses of large-radius jets. The search extends previous analyses both in using a larger dataset and by employing improved jet and missing transverse momentum reconstruction methods which more cleanly separate signal from background processes. No evidence for physics beyond the Standard Model is found. The results are interpreted in the context of supersymmetry-inspired simplified models, significantly extending the limits on the gluino mass in those models. In particular, limits on the gluino mass are set at 2 TeV when the lightest neutralino is nearly massless in a model assuming a two-step cascade decay via the lightest chargino and second-lightest neutralino.
Post-fit yields for data and prediction in each of the multi-bin signal regions for the 8 jet regions.
Post-fit yields for data and prediction in each of the multi-bin signal regions for the 9 jet regions.
Post-fit yields for data and prediction in each of the multi-bin signal regions for the 10 jet regions.
Post-fit yields for data and prediction in each of the single-bin signal regions of the analysis.
Observed 95% confidence level limit for the two-step signal grid.
Observed 95% confidence level limit for the two-step signal grid with the signal cross section increased by one sigma.
Observed 95% confidence level limit for the two-step signal grid with the signal cross section decreased by one sigma.
Expected 95% confidence level limit for the two-step signal grid.
Expected 95% confidence level limit for the two-step signal grid plus one sigma from experimental systematics.
Expected 95% confidence level limit for the two-step signal grid minus one sigma from experimental systematics.
Observed 95% confidence level limit for the Gtt signal grid.
Observed 95% confidence level limit for the Gtt signal grid with the signal cross section increased by one sigma.
Observed 95% confidence level limit for the Gtt signal grid with the signal cross section decreased by one sigma.
Expected 95% confidence level limit for the Gtt signal grid.
Expected 95% confidence level limit for the Gtt signal grid plus one sigma from experimental systematics.
Expected 95% confidence level limit for the Gtt signal grid minus one sigma from experimental systematics.
Observed 95% confidence level limit for the RPV signal grid.
Observed 95% confidence level limit for the RPV signal grid with the signal cross section increased by one sigma.
Observed 95% confidence level limit for the RPV signal grid with the signal cross section decreased by one sigma.
Expected 95% confidence level limit for the RPV signal grid.
Expected 95% confidence level limit for the RPV signal grid plus one sigma from experimental systematics.
Expected 95% confidence level limit for the RPV signal grid minus one sigma from experimental systematics.
Observed 95% confidence level limit for the two-step signal grid.
Expected 95% confidence level limit for the two-step signal grid.
Observed 95% confidence level limit for the Gtt signal grid.
Expected 95% confidence level limit for the Gtt signal grid.
Observed 95% confidence level limit for the RPV signal grid.
Expected 95% confidence level limit for the RPV signal grid.
$\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ distribution in the signal region SR-10ij50-0ib-MJ340. Two benchmark signal models are shown along with the background yields. These models, each representing a single mass point, are labelled 'RPV' with $(m_{\tilde{g}}, m_{\tilde{t}}) = (1600, 600) \, \mathrm{GeV}$ and 'two-step' with $(m_{\tilde{g}}, m_{\tilde{\chi^{0}_{1}}}) = (1600, 100) \, \mathrm{GeV}$.
$\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ distribution in the signal region SR-12ij50-2ib. Two benchmark signal models are shown along with the background yields. These models, each representing a single mass point, are labelled 'RPV' with $(m_{\tilde{g}}, m_{\tilde{t}}) = (1600, 600) \, \mathrm{GeV}$ and 'two-step' with $(m_{\tilde{g}}, m_{\tilde{\chi^{0}_{1}}}) = (1600, 100) \, \mathrm{GeV}$.
$\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ distribution in the signal region SR-9ij80-0ib. Two benchmark signal models are shown along with the background yields. These models, each representing a single mass point, are labelled 'RPV' with $(m_{\tilde{g}}, m_{\tilde{t}}) = (1600, 600) \, \mathrm{GeV}$ and 'two-step' with $(m_{\tilde{g}}, m_{\tilde{\chi^{0}_{1}}}) = (1600, 100) \, \mathrm{GeV}$.
Number of signal events expected for $139 \, \mathrm{fb}^{-1} $ after different analysis selections in the signal region SR-8ij50-0ib-MJ500. This 'two-step' model requires that a strongly produced gluino decays into quarks, the W and Z bosons, and the lightest stable neutralino where $(m_{\tilde{g}}, m_{\tilde{\chi^{0}_{1}}}) = (1600, 100) \, \mathrm{GeV}$.
Number of signal events expected for $139 \, \mathrm{fb}^{-1} $ after different analysis selections in the signal region SR-9ij50-0ib-MJ340. This 'two-step' model requires that a strongly produced gluino decays into quarks, the W and Z bosons, and the lightest stable neutralino where $(m_{\tilde{g}}, m_{\tilde{\chi^{0}_{1}}}) = (1600, 100) \, \mathrm{GeV}$.
Number of signal events expected for $139 \, \mathrm{fb}^{-1} $ after different analysis selections in the signal region SR-10ij50-0ib-MJ340. This 'two-step' model requires that a strongly produced gluino decays into quarks, the W and Z bosons, and the lightest stable neutralino where $(m_{\tilde{g}}, m_{\tilde{\chi^{0}_{1}}}) = (1600, 100) \, \mathrm{GeV}$.
Number of signal events expected for $139 \, \mathrm{fb}^{-1} $ after different analysis selections in the signal region SR-10ij50-0ib-MJ500. This 'two-step' model requires that a strongly produced gluino decays into quarks, the W and Z bosons, and the lightest stable neutralino where $(m_{\tilde{g}}, m_{\tilde{\chi^{0}_{1}}}) = (1600, 100) \, \mathrm{GeV}$.
Number of signal events expected for $139 \, \mathrm{fb}^{-1} $ after different analysis selections in the signal region SR-10ij50-1ib-MJ500. This 'two-step' model requires that a strongly produced gluino decays into quarks, the W and Z bosons, and the lightest stable neutralino where $(m_{\tilde{g}}, m_{\tilde{\chi^{0}_{1}}}) = (1600, 100) \, \mathrm{GeV}$.
Number of signal events expected for $139 \, \mathrm{fb}^{-1} $ after different analysis selections in the signal region SR-11ij50-0ib. This 'two-step' model requires that a strongly produced gluino decays into quarks, the W and Z bosons, and the lightest stable neutralino where $(m_{\tilde{g}}, m_{\tilde{\chi^{0}_{1}}}) = (1600, 100) \, \mathrm{GeV}$.
Number of signal events expected for $139 \, \mathrm{fb}^{-1} $ after different analysis selections in the signal region SR-12ij50-2ib. This 'two-step' model requires that a strongly produced gluino decays into quarks, the W and Z bosons, and the lightest stable neutralino where $(m_{\tilde{g}}, m_{\tilde{\chi^{0}_{1}}}) = (1600, 100) \, \mathrm{GeV}$.
Number of signal events expected for $139 \, \mathrm{fb}^{-1} $ after different analysis selections in the signal region SR-9ij80-0ib. This 'two-step' model requires that a strongly produced gluino decays into quarks, the W and Z bosons, and the lightest stable neutralino where $(m_{\tilde{g}}, m_{\tilde{\chi^{0}_{1}}}) = (1600, 100) \, \mathrm{GeV}$.
Acceptance for the signal region SR-8ij50-0ib-MJ500 showing the acceptance for the complete two-step signal grid.
Efficiency for the signal region SR-8ij50-0ib-MJ500 showing the efficiency for the complete two-step signal grid.
Acceptance for the signal region SR-9ij50-0ib-MJ340 showing the acceptance for the complete two-step signal grid.
Efficiency for the signal region SR-9ij50-0ib-MJ340 showing the efficiency for the complete two-step signal grid.
Acceptance for the signal region SR-10ij50-0ib-MJ340 showing the acceptance for the complete two-step signal grid.
Efficiency for the signal region SR-10ij50-0ib-MJ340 showing the efficiency for the complete two-step signal grid.
Acceptance for the signal region SR-10ij50-0ib-MJ500 showing the acceptance for the complete two-step signal grid.
Efficiency for the signal region SR-10ij50-0ib-MJ500 showing the efficiency for the complete two-step signal grid.
Acceptance for the signal region SR-10ij50-1ib-MJ500 showing the acceptance for the complete two-step signal grid.
Efficiency for the signal region SR-10ij50-1ib-MJ500 showing the efficiency for the complete two-step signal grid.
Acceptance for the signal region SR-11ij50-0ib showing the acceptance for the complete two-step signal grid.
Efficiency for the signal region SR-11ij50-0ib showing the efficiency for the complete two-step signal grid.
Acceptance for the signal region SR-12ij50-2ib showing the acceptance for the complete two-step signal grid.
Efficiency for the signal region SR-12ij50-2ib showing the efficiency for the complete two-step signal grid.
Acceptance for the signal region SR-9ij80-0ib showing the acceptance for the complete two-step signal grid.
Efficiency for the signal region SR-9ij80-0ib showing the efficiency for the complete two-step signal grid.
The normalisation factors for the dominant backgrounds of the analysis in each of the multi-bin and single-bin regions.
Post-fit yields for data and prediction in each of the single-bin validation regions to test the $N_{\mathrm{jet}}$ extraction.
Post-fit yields for data and prediction in each of the single-bin validation regions to test the $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ extrapolation.
Post-fit yields for data and prediction in each of the multi-bin validation regions to test the $N_{\mathrm{jet}}$ extraction.
Post-fit yields for data and prediction in each of the multi-bin validation regions to test the $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ extrapolation.
The observed Cls from the best expected signal regions for the two-step decay.
The observed Cls from the best expected signal regions for the Gtt decay.
The observed Cls from the best expected signal regions for the RPV decay.
Number of events in each signal region broken down by background type and the number of observed data events.
From left to right; the $95\%$ CL upper limits on the visible cross section (${\langle \epsilon\sigma \rangle}^{95}_{obs}$) and on the number of signal events. Next is the $95\%$ CL upper limit on the number of signal events, given the expected number of background events. The last two columns show the confidence level for the background only hypothesis ($CL_{b}$) and the dicovery $p$-value along with the Gaussian significance (Z).
Visualisation of the highest jet multiplicity event selected in signal regions targeting long cascade decays of pair-produced gluinos. This event was recorded by ATLAS on 23 October 2016, and contains 16 jets, illustrated by cones. Yellow blocks represent the calorimeter energy measured in noise-suppressed clusters. Of the reconstructed jets, 13 (11) have transverse momenta above 50 GeV (80 GeV), with 3 (2) being b-tagged. The leading jet has a transverse momentum of 507 GeV, and the sum of jet transverse momenta $H_T=2.9$ TeV. A value of 343 GeV is observed for the $E_{T}^{miss}$, whose direction is shown by the dashed red line, producing a significance $S(E_{T}^{miss})=6.4$. The sum of the masses of large-radius jets is evaluated as $M_{J}^{\Sigma}=1070$ GeV.
Visualisation of the highest jet multiplicity event selected in a control region used to make predictions of the background from multijet production. This event was recorded by ATLAS on 18 July 2018, and contains 19 jets, illustrated by cones. Yellow blocks represent the calorimeter energy measured in in noise-suppressed clusters. Of the reconstructed jets, 16 (10) have transverse momenta above 50 GeV (80 GeV). No jets were b-tagged. The leading et has a transverse momentum of 371 GeV, and the sum of jet transverse momenta $H_T=2.2$ TeV. A value of 8 GeV is observed for the $E_{T}^{miss}$, whose direction is shown by the dashed red line, producing a significance $S(E_{T}^{miss})=0.2$. The sum of the masses of large-radius jets is evaluated as $M_{J}^{\Sigma}=767$ GeV.
A search is presented for new phenomena in events characterised by high jet multiplicity, no leptons (electrons or muons), and four or more jets originating from the fragmentation of $b$-quarks ($b$-jets). The search uses 139 fb$^{-1}$ of $\sqrt{s}$ = 13 TeV proton-proton collision data collected by the ATLAS experiment at the Large Hadron Collider during Run 2. The dominant Standard Model background originates from multijet production and is estimated using a data-driven technique based on an extrapolation from events with low $b$-jet multiplicity to the high $b$-jet multiplicities used in the search. No significant excess over the Standard Model expectation is observed and 95% confidence-level limits that constrain simplified models of R-parity-violating supersymmetry are determined. The exclusion limits reach 950 GeV in top-squark mass in the models considered.
<b>- - - - - - - - Overview of HEPData Record - - - - - - - -</b> <br><br> <b>Exclusion contours:</b> <ul> <li><a href="?table=stbchionly_obs">Stop to bottom quark and chargino exclusion contour (Obs.)</a> <li><a href="?table=stbchionly_exp">Stop to bottom quark and chargino exclusion contour (Exp.)</a> <li><a href="?table=stbchi_obs">Stop to higgsino LSP exclusion contour (Obs.)</a> <li><a href="?table=stbchi_exp">Stop to higgsino LSP exclusion contour (Exp.)</a> <li><a href="?table=sttN_obs">Stop to top quark and neutralino exclusion contour (Obs.)</a> <li><a href="?table=sttN_exp">Stop to top quark and neutralino exclusion contour (Exp.)</a> </ul> <b>Upper limits:</b> <ul> <li><a href="?table=stbchionly_xSecUL_obs">Obs Xsection upper limit in stop to bottom quark and chargino</a> <li><a href="?table=stop_xSecUL_obs">Obs Xsection upper limit in higgsino LSP</a> <li><a href="?table=stbchionly_xSecUL_exp">Exp Xsection upper limit in stop to bottom quark and chargino</a> <li><a href="?table=stop_xSecUL_exp">Exp Xsection upper limit in higgsino LSP</a> </ul> <b>Kinematic distributions:</b> <ul> <li><a href="?table=SR_yields">SR_yields</a> </ul> <b>Cut flows:</b> <ul> <li><a href="?table=cutflow">cutflow</a> </ul> <b>Acceptance and efficiencies:</b> As explained in <a href="https://twiki.cern.ch/twiki/bin/view/AtlasPublic/SupersymmetryPublicResults#summary_of_auxiliary_material">the twiki</a>. <ul> <li> <b>stbchi_6je4be:</b> <a href="?table=stbchi_Acc_6je4be">stbchi_Acc_6je4be</a> <a href="?table=stbchi_Eff_6je4be">stbchi_Eff_6je4be</a> <li> <b>stbchi_7je4be:</b> <a href="?table=stbchi_Acc_7je4be">stbchi_Acc_7je4be</a> <a href="?table=stbchi_Eff_7je4be">stbchi_Eff_7je4be</a> <li> <b>stbchi_8je4be:</b> <a href="?table=stbchi_Acc_8je4be">stbchi_Acc_8je4be</a> <a href="?table=stbchi_Eff_8je4be">stbchi_Eff_8je4be</a> <li> <b>stbchi_9ji4be:</b> <a href="?table=stbchi_Acc_9ji4be">stbchi_Acc_9ji4be</a> <a href="?table=stbchi_Eff_9ji4be">stbchi_Eff_9ji4be</a> <li> <b>stbchi_6je5bi:</b> <a href="?table=stbchi_Acc_6je5bi">stbchi_Acc_6je5bi</a> <a href="?table=stbchi_Eff_6je5bi">stbchi_Eff_6je5bi</a> <li> <b>stbchi_7je5bi:</b> <a href="?table=stbchi_Acc_7je5bi">stbchi_Acc_7je5bi</a> <a href="?table=stbchi_Eff_7je5bi">stbchi_Eff_7je5bi</a> <li> <b>stbchi_8je5bi:</b> <a href="?table=stbchi_Acc_8je5bi">stbchi_Acc_8je5bi</a> <a href="?table=stbchi_Eff_8je5bi">stbchi_Eff_8je5bi</a> <li> <b>stbchi_9ji5bi:</b> <a href="?table=stbchi_Acc_9ji5bi">stbchi_Acc_9ji5bi</a> <a href="?table=stbchi_Eff_9ji5bi">stbchi_Eff_9ji5bi</a> <li> <b>stbchi_8ji5bi:</b> <a href="?table=stbchi_Acc_8ji5bi">stbchi_Acc_8ji5bi</a> <a href="?table=stbchi_Eff_8ji5bi">stbchi_Eff_8ji5bi</a> <li> <b>sttN_6je4be:</b> <a href="?table=sttN_Acc_6je4be">sttN_Acc_6je4be</a> <a href="?table=sttN_Eff_6je4be">sttN_Eff_6je4be</a> <li> <b>sttN_7je4be:</b> <a href="?table=sttN_Acc_7je4be">sttN_Acc_7je4be</a> <a href="?table=sttN_Eff_7je4be">sttN_Eff_7je4be</a> <li> <b>sttN_8je4be:</b> <a href="?table=sttN_Acc_8je4be">sttN_Acc_8je4be</a> <a href="?table=sttN_Eff_8je4be">sttN_Eff_8je4be</a> <li> <b>sttN_9ji4be:</b> <a href="?table=sttN_Acc_9ji4be">sttN_Acc_9ji4be</a> <a href="?table=sttN_Eff_9ji4be">sttN_Eff_9ji4be</a> <li> <b>sttN_6je5bi:</b> <a href="?table=sttN_Acc_6je5bi">sttN_Acc_6je5bi</a> <a href="?table=sttN_Eff_6je5bi">sttN_Eff_6je5bi</a> <li> <b>sttN_7je5bi:</b> <a href="?table=sttN_Acc_7je5bi">sttN_Acc_7je5bi</a> <a href="?table=sttN_Eff_7je5bi">sttN_Eff_7je5bi</a> <li> <b>sttN_8je5bi:</b> <a href="?table=sttN_Acc_8je5bi">sttN_Acc_8je5bi</a> <a href="?table=sttN_Eff_8je5bi">sttN_Eff_8je5bi</a> <li> <b>sttN_9ji5bi:</b> <a href="?table=sttN_Acc_9ji5bi">sttN_Acc_9ji5bi</a> <a href="?table=sttN_Eff_9ji5bi">sttN_Eff_9ji5bi</a> <li> <b>sttN_8ji5bi:</b> <a href="?table=sttN_Acc_8ji5bi">sttN_Acc_8ji5bi</a> <a href="?table=sttN_Eff_8ji5bi">sttN_Eff_8ji5bi</a> </ul> <b>Truth Code snippets</b> and <b>SLHA</a> files are available under "Resources" (purple button on the left)
The observed exclusion contour at 95% CL as a function of the $\it{m}_{\tilde{\chi}^{\pm}_{1}}$ vs. $\it{m}_{\tilde{t}}$. Masses that are within the contours are excluded. Limits are shown for $B(\tilde{t} \rightarrow b \chi^{+}_{1})$ equal to unity.
The expected exclusion contour at 95% CL as a function of the $\it{m}_{\tilde{\chi}^{\pm}_{1}}$ vs. $\it{m}_{\tilde{t}}$. Masses that are within the contour are excluded. Limits are shown for $B(\tilde{t} \rightarrow b \chi^{+}_{1})$ equal to unity.
The observed exclusion contour at 95% CL as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$. Masses that are within the contours are excluded. Limits are shown in the case of a higgsino LSP. The results are constrained by the kinematic limits of the top-squark decay into a chargino and a bottom quark (upper diagonal line) and into a neutralino and a top quark (lower diagonal line), respectively.
The expected exclusion contour at 95% CL as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$. Masses that are within the contours are excluded. Limits are shown in the case of a higgsino LSP. The results are constrained by the kinematic limits of the top-squark decay into a chargino and a bottom quark (upper diagonal line) and into a neutralino and a top quark (lower diagonal line), respectively.
The observed exclusion contour at 95% CL as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$. Masses that are within the contours are excluded. Limits are shown for the region $m_{\tilde{t}} - m_{\tilde{\chi}^0_{1,2}, \tilde{\chi}^\pm_{1}} \geq m_\text{top}$ where $B(\tilde{t} \rightarrow b \chi^{+}_{1}) = B(\tilde{t} \rightarrow t \chi^{0}_{1,2}) = 0.5$.
The expected exclusion contour at 95% CL as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$. Masses that are within the contours are excluded. Limits are shown for the region $m_{\tilde{t}} - m_{\tilde{\chi}^0_{1,2}, \tilde{\chi}^\pm_{1}} \geq m_\text{top}$ where $B(\tilde{t} \rightarrow b \chi^{+}_{1}) = B(\tilde{t} \rightarrow t \chi^{0}_{1,2}) = 0.5$.
Observed model-dependent upper limit on the cross section for the $(\tilde{t},\tilde{\chi}^{\pm}_{1})$ signal grid. Limits are shown for $B(\tilde{t} \rightarrow b \chi^{+}_{1})$ equal to unity.
Observed model-dependent upper limit on the cross section for the $(\tilde{t},\tilde{\chi}^{\pm}_{1} / \tilde{\chi}^{0}_{1,2})$ signal grid. Limits are shown in the case of a higgsino LSP. The results are constrained by the kinematic limits of the top-squark decay into a chargino and a bottom quark (upper diagonal line) and into a neutralino and a top quark (lower diagonal line), respectively.
Expected model-dependent upper limit on the cross section for the $(\tilde{t},\tilde{\chi}^{\pm}_{1})$ signal grid. Limits are shown for $B(\tilde{t} \rightarrow b \chi^{+}_{1})$ equal to unity.
Expected model-dependent upper limit on the cross section for the $(\tilde{t},\tilde{\chi}^{\pm}_{1} / \tilde{\chi}^{0}_{1,2})$ signal grid. Limits are shown in the case of a higgsino LSP. The results are constrained by the kinematic limits of the top-squark decay into a chargino and a bottom quark (upper diagonal line) and into a neutralino and a top quark (lower diagonal line), respectively.
Expected background and observed number of events in different jet and $b$-tag multiplicity bins.
Cut flow for a model of top-squark pair production with the top squark decaying to a $b$-quark and a chargino. The chargino decays through the non-zero RPV coupling $\lambda^{''}_{323}$ via a virtual top squark to $bbs$ quark triplets ($m_{\tilde{t}}$ = 800 GeV, $m_{\tilde{\chi}^{\pm}_{1}}$ = 750 GeV). The multijet trigger consists of four jets satisfying $p_{\text{T}}\geq(100)120$ GeV for the 2015-2016 (2017-2018) data period. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed. The numbers in $N_{\text{weighted}}$ are normalized by the integrated luminosity of 139 fb$^{-1}$.
Signal acceptance for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal efficiency for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the efficiency given in the table is reported in %.
Signal efficiency for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the efficiency given in the table is reported in %.
Signal efficiency for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the efficiency given in the table is reported in %.
Signal efficiency for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the efficiency given in the table is reported in %.
Signal efficiency for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the efficiency given in the table is reported in %.
Signal efficiency for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the efficiency given in the table is reported in %.
Signal efficiency for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the efficiency given in the table is reported in %.
Signal efficiency for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the efficiency given in the table is reported in %.
Signal efficiency for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the efficiency given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.
Several extensions of the Standard Model predict the production of dark matter particles at the LHC. An uncharted signature of dark matter particles produced in association with $VV=W^\pm W^\mp$ or $ZZ$ pairs from a decay of a dark Higgs boson $s$ is searched for using 139 fb$^{-1}$ of $pp$ collisions recorded by the ATLAS detector at a center-of-mass energy of 13 TeV. The $s\to V(q\bar q)V(q\bar q)$ decays are reconstructed with a novel technique aimed at resolving the dense topology from boosted $VV$ pairs using jets in the calorimeter and tracking information. Dark Higgs scenarios with $m_s > 160$ GeV are excluded.
Data overlaid on SM background post-fit yields stacked in each SR and CR category and E<sub>T</sub><sup>miss</sup> bin with the maximum-likelihood estimators set to the conditional values of the CR-only fit, and propagated to SR and CRs. Pre-fit uncertainties cover differences between the data and pre-fit background prediction.
Dominant sources of uncertainty for three dark Higgs scenarios after the fit to Asimov data generated from the expected values of the maximum-likelihood estimators including predicted signals with m<sub>Z'</sub> = 1 TeV and m<sub>s</sub> of (a) 160 GeV, (b) 235 GeV, and (c) 310 GeV. The uncertainty in the fitted signal yield relative to the theory prediction is presented. Total is the quadrature sum of statistical and total systematic uncertainties, which consider correlations.
The ratios (μ) of the 95% C.L. upper limits on the combined s→ W<sup>±</sup>W<sup>∓</sup> and s→ ZZ cross section to simplified model expectations for the m<sub>Z'</sub>=0.5 TeV scenario, for various m<sub>s</sub> hypotheses. The observed limits (solid line) are consistent with the expectation under the SM-only hypothesis (dashed line) within uncertainties (filled band), except for a small excess for m<sub>s</sub>=160 GeV, discussed in the text.
The ratios (μ) of the 95% C.L. upper limits on the combined s→ W<sup>±</sup>W<sup>∓</sup> and s→ ZZ cross section to simplified model expectations for the m<sub>Z'</sub>=1 TeV scenario, for various m<sub>s</sub> hypotheses. The observed limits (solid line) are consistent with the expectation under the SM-only hypothesis (dashed line) within uncertainties (filled band), except for a small excess for m<sub>s</sub>=160 GeV, discussed in the text.
The ratios (μ) of the 95% C.L. upper limits on the combined s→ W<sup>±</sup>W<sup>∓</sup> and s→ ZZ cross section to simplified model expectations for the m<sub>Z'</sub>=1.7 TeV scenario, for various m<sub>s</sub> hypotheses. The observed limits (solid line) are consistent with the expectation under the SM-only hypothesis (dashed line) within uncertainties (filled band), except for a small excess for m<sub>s</sub>=160 GeV, discussed in the text.
Observed upper limits at 95% C.L. on σ(pp → s χχ) × B(s→ VV) for m<sub>Z'</sub>=0.5 TeV signal points. The expected limits, varied up and down by one and two standard deviations, are shown as green and yellow bands, respectively. The observed and expected limits are compared to the theoretical LO cross section for the σ(pp → s χχ) × B(s→ VV) process for m<sub>Z'</sub>=0.5 TeV, shown in dashed blue.
Observed upper limits at 95% C.L. on σ(pp → s χχ) × B(s→ VV) for m<sub>Z'</sub>=1 TeV signal points. The expected limits, varied up and down by one and two standard deviations, are shown as green and yellow bands, respectively. The observed and expected limits are compared to the theoretical LO cross section for the σ(pp → s χχ) × B(s→ VV) process for m<sub>Z'</sub>=1 TeV, shown in dashed blue.
Observed upper limits at 95% C.L. on σ(pp → s χχ) × B(s→ VV) for m<sub>Z'</sub>=1.7 TeV signal points. The expected limits, varied up and down by one and two standard deviations, are shown as green and yellow bands, respectively. The observed and expected limits are compared to the theoretical LO cross section for the σ(pp → s χχ) × B(s→ VV) process for m<sub>Z'</sub>=1.7 TeV, shown in dashed blue.
SM background post-fit yields stacked in each SR and CR category and E<sub>T</sub><sup>miss</sup> bin and data overlaid with the maximum likelihood estimators set to the conditional values of the combined signal and control region fit. The hatched uncertainty band shown includes simulation statistics uncertainties, experimental systematic uncertainties, and V+jets theory modelling systematic uncertainties. Pre-fit uncertainties cover differences between the data and pre-fit background prediction.
Cumulative efficiencies for the merged category for signal samples with m<sub>s</sub>=160 GeV (a), m<sub>s</sub>=235 GeV (b) and m<sub>s</sub>=310 GeV (c), each with m<sub>Z'</sub>=1 TeV. The dark Higgs candidate selection includes stringent jet substructure requirements and typically at most one candidate is present in signal events. Here, Δ φ<sub>jets<sub>1,2,3</sub> E<sub>T</sub><sup>miss</sup></sub> is the smallest azimuthal angle between the E<sub>T</sub><sup>miss</sup> and any of the three highest-p<sub>T</sub> (leading) small-R jets.
Cumulative efficiencies for the intermediate category for signal samples with m<sub>s</sub>=160 GeV (a), m<sub>s</sub>=235 GeV (b) and m<sub>s</sub>=310 GeV (c), each with m<sub>Z'</sub>=1 TeV. The TAR+Comb algorithm reconstructs the dark Higgs candidate from a TAR jet with m<sup>TAR</sup>>60 GeV that is supplemented by up to two additional small-R jets within ΔR<sub>cone</sub>=2.5 of the TAR jet. Here, Δ φ<sub>jets<sub>1,2,3</sub> E<sub>T</sub><sup>miss</sup></sub> is the smallest azimuthal angle between the E<sub>T</sub><sup>miss</sup> and any of the three highest-p<sub>T</sub> (leading) small-R jets. For details see text.
The product of acceptance and efficiency (A × ϵ), defined as the number of signal events satisfying the full set of selection criteria in the merged or intermediate signal regions, divided by the total number of generated signal events, for the s(W<sup>±</sup>W<sup>∓</sup>) dark Higgs signal points with dark Higgs boson mass m<sub>s</sub> and Z' boson mass m<sub>Z'</sub>.
The product of acceptance and efficiency (A × ϵ), defined as the number of signal events satisfying the full set of selection criteria in the merged or intermediate signal regions, divided by the total number of generated signal events, for the s(ZZ) dark Higgs signal points with dark Higgs boson mass m<sub>s</sub> and Z' boson mass m<sub>Z'</sub>.
A search is performed for the rare decay W$^\pm\to\pi^\pm\gamma$ in proton-proton collisions at $\sqrt{s} =$ 13 TeV. Data corresponding to an on W integrated luminosity of 137 fb$^{-1}$ were collected during 2016 to 2018 with the CMS detector. This analysis exploits a novel search strategy based on W boson production in top quark pair events. An inclusive search for the W$^\pm\to\pi^\pm\gamma$ decay is not optimal at the LHC because of the high trigger thresholds. Instead, a trigger selection is exploited in which the W boson originating from one of the top quarks is used to tag the event in a leptonic decay. The W boson emerging from the other top quark is used to search for the W$^\pm\to\pi^\pm\gamma$ signature. Such decays are characterized by an isolated track pointing to a large energy deposit, and by an isolated photon of large transverse momentum. The presence of b quark jets reduces the background from the hadronization of light-flavor quarks and gluons. The W$^\pm\to\pi^\pm\gamma$ decay is not observed. An upper exclusion limit is set to this branching fraction, corresponding to 1.50 $\times$ 10$^{-5}$ at 95% confidence level, whereas the expected upper limit exclusion limit is 0.85 $^{+0.52}_{-0.29}$ $\times$ 10$^{-5}$.
The product of signal efficiency and acceptance per year and per lepton channel (muon or electron).
Expected and observed upper exclusion limits on the branching fraction of the decay of a W boson into a pion and a photon, using 2016 to 2018 data.
The results of a search for direct pair production of top squarks and for dark matter in events with two opposite-charge leptons (electrons or muons), jets and missing transverse momentum are reported, using 139 fb$^{-1}$ of integrated luminosity from proton-proton collisions at $\sqrt{s} = 13$ TeV, collected by the ATLAS detector at the Large Hadron Collider during Run 2 (2015-2018). This search considers the pair production of top squarks and is sensitive across a wide range of mass differences between the top squark and the lightest neutralino. Additionally, spin-0 mediator dark-matter models are considered, in which the mediator is produced in association with a pair of top quarks. The mediator subsequently decays to a pair of dark-matter particles. No significant excess of events is observed above the Standard Model background, and limits are set at 95% confidence level. The results exclude top squark masses up to about 1 TeV, and masses of the lightest neutralino up to about 500 GeV. Limits on dark-matter production are set for scalar (pseudoscalar) mediator masses up to about 250 (300) GeV.
Two-body selection. Distributions of $m_{T2}$ in $SR^{2-body}_{110,\infty}$ for (a) different-flavour and (b) same-flavour events satisfying the selection criteria of the given SR, except the one for the presented variable, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack. ''Others'' includes contributions from $VVV$, $t\bar{t} t$, $t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$ processes. The hatched bands represent the total statistical and systematic uncertainty. The rightmost bin of each plot includes overflow events. Reference dark-matter signal models are overlayed for comparison. Red arrows in the upper panels indicate the signal region selection criteria. The bottom panels show the ratio of the observed data to the total SM background prediction, with hatched bands representing the total uncertainty in the background prediction.
Two-body selection. Distributions of $m_{T2}$ in $SR^{2-body}_{110,\infty}$ for (a) different-flavour and (b) same-flavour events satisfying the selection criteria of the given SR, except the one for the presented variable, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack. ''Others'' includes contributions from $VVV$, $t\bar{t} t$, $t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$ processes. The hatched bands represent the total statistical and systematic uncertainty. The rightmost bin of each plot includes overflow events. Reference dark-matter signal models are overlayed for comparison. Red arrows in the upper panels indicate the signal region selection criteria. The bottom panels show the ratio of the observed data to the total SM background prediction, with hatched bands representing the total uncertainty in the background prediction.
Three-body selection. Distributions of $M_{\Delta}^R$ in (a,b) $SR_{W}^{3-body}$ and (c,d) $SR_{T}^{3-body}$ for (left) same-flavour and (right) different-flavour events satisfying the selection criteria of the given SR, except the one for the presented variable, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack. ''Others'' includes contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$ processes. The hatched bands represent the total statistical and systematic uncertainty. The rightmost bin of each plot includes overflow events. Reference top squark pair production signal models are overlayed for comparison. Red arrows in the upper panels indicate the signal region selection criteria. The bottom panels show the ratio of the observed data to the total SM background prediction, with hatched bands representing the total uncertainty in the background prediction; red arrows show data outside the vertical-axis range.
Three-body selection. Distributions of $M_{\Delta}^R$ in (a,b) $SR_{W}^{3-body}$ and (c,d) $SR_{T}^{3-body}$ for (left) same-flavour and (right) different-flavour events satisfying the selection criteria of the given SR, except the one for the presented variable, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack. ''Others'' includes contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$ processes. The hatched bands represent the total statistical and systematic uncertainty. The rightmost bin of each plot includes overflow events. Reference top squark pair production signal models are overlayed for comparison. Red arrows in the upper panels indicate the signal region selection criteria. The bottom panels show the ratio of the observed data to the total SM background prediction, with hatched bands representing the total uncertainty in the background prediction; red arrows show data outside the vertical-axis range.
Three-body selection. Distributions of $M_{\Delta}^R$ in (a,b) $SR_{W}^{3-body}$ and (c,d) $SR_{T}^{3-body}$ for (left) same-flavour and (right) different-flavour events satisfying the selection criteria of the given SR, except the one for the presented variable, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack. ''Others'' includes contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$ processes. The hatched bands represent the total statistical and systematic uncertainty. The rightmost bin of each plot includes overflow events. Reference top squark pair production signal models are overlayed for comparison. Red arrows in the upper panels indicate the signal region selection criteria. The bottom panels show the ratio of the observed data to the total SM background prediction, with hatched bands representing the total uncertainty in the background prediction; red arrows show data outside the vertical-axis range.
Three-body selection. Distributions of $M_{\Delta}^R$ in (a,b) $SR_{W}^{3-body}$ and (c,d) $SR_{T}^{3-body}$ for (left) same-flavour and (right) different-flavour events satisfying the selection criteria of the given SR, except the one for the presented variable, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack. ''Others'' includes contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$ processes. The hatched bands represent the total statistical and systematic uncertainty. The rightmost bin of each plot includes overflow events. Reference top squark pair production signal models are overlayed for comparison. Red arrows in the upper panels indicate the signal region selection criteria. The bottom panels show the ratio of the observed data to the total SM background prediction, with hatched bands representing the total uncertainty in the background prediction; red arrows show data outside the vertical-axis range.
Four-body selection. (a) distributions of $E_{T}^{miss}$ in $SR^{4-body}_{Small\,\Delta m}$ and (b) distribution of $R_{2\ell 4j}$ in $SR^{4-body}_{Large\,\Delta m}$ for events satisfying the selection criteria of the given SR, except the one for the presented variable, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack. ''Others'' includes contributions from $VVV$, $t\bar{t} t$, $t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$ processes. The hatched bands represent the total statistical and systematic uncertainty. The rightmost bin of each plot includes overflow events. Reference top squark pair production signal models are overlayed for comparison. Red arrows in the upper panel indicate the signal region selection criteria. The bottom panels show the ratio of the observed data to the total SM background prediction, with hatched bands representing the total uncertainty in the background prediction; red arrows show data outside the vertical-axis range.
Four-body selection. (a) distributions of $E_{T}^{miss}$ in $SR^{4-body}_{Small\,\Delta m}$ and (b) distribution of $R_{2\ell 4j}$ in $SR^{4-body}_{Large\,\Delta m}$ for events satisfying the selection criteria of the given SR, except the one for the presented variable, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack. ''Others'' includes contributions from $VVV$, $t\bar{t} t$, $t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$ processes. The hatched bands represent the total statistical and systematic uncertainty. The rightmost bin of each plot includes overflow events. Reference top squark pair production signal models are overlayed for comparison. Red arrows in the upper panel indicate the signal region selection criteria. The bottom panels show the ratio of the observed data to the total SM background prediction, with hatched bands representing the total uncertainty in the background prediction; red arrows show data outside the vertical-axis range.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}_1^0$ with 100% branching ratio, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the expected limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}_1^0$ with 100% branching ratio, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the expected limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}_1^0$ with 100% branching ratio, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the expected limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}_1^0$ with 100% branching ratio, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the Observed limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}_1^0$ with 100% branching ratio, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the expected limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}_1^0$ with 100% branching ratio, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the expected limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}_1^0$ with 100\% branching ratio, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the expected limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}_1^0$ with 100\% branching ratio, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the expected limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}_1^0$ with 100\% branching ratio, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the expected limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}_1^0$ with 100\% branching ratio, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the expected limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}_1^0$ with 100\% branching ratio, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the expected limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}_1^0$ with 100\% branching ratio, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the expected limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.
Exclusion limits for (a) $t\bar{t} + \phi $ scalar and (b) $t\bar{t} + a $ pseudoscalar models as a function of the mediator mass for a DM particle mass of $m(\chi)=1$ GeV. The limits are calculated at 95% CL and are expressed in terms of the ratio of the excluded cross-section to the nominal cross-section for a coupling assumption of $g = g_q = g_{\chi} = 1$. The solid (dashed) lines shows the observed (expected) exclusion limits.
Exclusion limits for (a) $t\bar{t} + \phi $ scalar and (b) $t\bar{t} + a $ pseudoscalar models as a function of the mediator mass for a DM particle mass of $m(\chi)=1$ GeV. The limits are calculated at 95% CL and are expressed in terms of the ratio of the excluded cross-section to the nominal cross-section for a coupling assumption of $g = g_q = g_{\chi} = 1$. The solid (dashed) lines shows the observed (expected) exclusion limits.
Exclusion limits for (a) $t\bar{t} + \phi $ scalar and (b) $t\bar{t} + a $ pseudoscalar models as a function of the mediator mass for a DM particle mass of $m(\chi)=1$ GeV. The limits are calculated at 95% CL and are expressed in terms of the ratio of the excluded cross-section to the nominal cross-section for a coupling assumption of $g = g_q = g_{\chi} = 1$. The solid (dashed) lines shows the observed (expected) exclusion limits.
Exclusion limits for (a) $t\bar{t} + \phi $ scalar and (b) $t\bar{t} + a $ pseudoscalar models as a function of the mediator mass for a DM particle mass of $m(\chi)=1$ GeV. The limits are calculated at 95% CL and are expressed in terms of the ratio of the excluded cross-section to the nominal cross-section for a coupling assumption of $g = g_q = g_{\chi} = 1$. The solid (dashed) lines shows the observed (expected) exclusion limits.
Two-body selection. Background fit results for $\mathrm{CR}^{\mathrm{2-body}}_{t\bar{t}}$, $\mathrm{CR}^{\mathrm{2-body}}_{t\bar{t}Z}$, $\mathrm{VR}^{\mathrm{2-body}}_{t\bar{t}, DF}$, $\mathrm{VR}^{\mathrm{2-body}}_{t\bar{t}, SF}$ and $\mathrm{VR}^{\mathrm{2-body}}_{t\bar{t} Z}$. ''Others'' includes contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$ processes. Combined statistical and systematic uncertainties are given. Entries marked `--' indicate a negligible background contribution (less than 0.001 events). The individual uncertainties can be correlated, and do not necessarily add up in quadrature to the total background uncertainty.
Three-body selection. Background fit results for $\mathrm{CR}^{\mathrm{3-body}}_{t\bar{t}}$, $\mathrm{CR}^{\mathrm{3-body}}_{VV}$, $\mathrm{CR}^{\mathrm{2-body}}_{t\bar{t}Z}$, $\mathrm{VR}^{\mathrm{3-body}}_{VV}$, $\mathrm{VR(1)}^{\mathrm{3-body}}_{t\bar{t}}$ and $\mathrm{VR(2)}^{\mathrm{3-body}}_{t\bar{t}}$. ''Others'' includes contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$ processes. Combined statistical and systematic uncertainties are given. Entries marked `--' indicate a negligible background contribution (less than 0.001 events). The individual uncertainties can be correlated, and do not necessarily add up in quadrature to the total background uncertainty.
Four-body selection. Background fit results for $\mathrm{CR}^{\mathrm{4-body}}_{t\bar{t}}$,$\mathrm{CR}^{\mathrm{4-body}}_{VV}$, $\mathrm{VR}^{\mathrm{4-body}}_{t\bar{t}}$, $VR^{4-body}_{VV}$ and $\mathrm{VR}^{\mathrm{4-body}}_{VV,lll}$. The ''Others'' category contains the contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$. Combined statistical and systematic uncertainties are given. Entries marked `--' indicate a negligible background contribution (less than 0.001 events). The individual uncertainties can be correlated, and do not necessarily add up in quadrature to the total background uncertainty.
Two-body selection. Background fit results for the different-flavour leptons binned SRs. The ''Others'' category contains the contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$. Combined statistical and systematic uncertainties are given. Entries marked `--' indicate a negligible background contribution (less than 0.001 events). The individual uncertainties can be correlated, and do not necessarily add up in quadrature to the total background uncertainty.
Two-body selection. Background fit results for the same-flavour leptons binned SRs. The ''Others'' category contains the contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$. Combined statistical and systematic uncertainties are given. The individual uncertainties can be correlated, and do not necessarily add up in quadrature to the total background uncertainty.
Three-body selection. Observed event yields and background fit results for the three-body selection SRs. The ''Others'' category contains contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$. Combined statistical and systematic uncertainties are given. Entries marked `--' indicate a negligible background contribution (less than 0.001 events). The individual uncertainties can be correlated, and do not necessarily add up in quadrature to the total background uncertainty.
Four-body selection. Observed event yields and background fit results for SR$^{\mathrm{4-body}}_{\mathrm{Small}\,\Delta m}$ and SR$^{\mathrm{4-body}}_{\mathrm{Large}\,\Delta m}$. The ''Others'' category contains the contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$. Combined statistical and systematic uncertainties are given. The individual uncertainties can be correlated, and do not necessarily add up in quadrature to the total background uncertainty.
Exclusion limits contours (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}^0_1$ with 100% branching ratio in $\tilde{t}_1--\tilde{\chi}^0_1$ masses planes. The dashed lines and the shaded bands are the expected limit and its $\pm 1\sigma$ uncertainty. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The exclusion limits contours for the two-body, three-body and four-body selections are respectively shown in blue, green and red.
Exclusion limits contours (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}^0_1$ with 100% branching ratio in $\tilde{t}_1--\tilde{\chi}^0_1$ masses planes. The dashed lines and the shaded bands are the expected limit and its $\pm 1\sigma$ uncertainty. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The exclusion limits contours for the two-body, three-body and four-body selections are respectively shown in blue, green and red.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t \tilde{\chi}_1^0$ with 100% branching ratio, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t \tilde{\chi}_1^0$ with 100% branching ratio, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t \tilde{\chi}_1^0$ with 100% branching ratio, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t \tilde{\chi}_1^0$ with 100% branching ratio, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b W \tilde{\chi}_1^0$ with 100% branching ratio, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b W \tilde{\chi}_1^0$ with 100% branching ratio, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b W \tilde{\chi}_1^0$ with 100% branching ratio, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm 1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b W \tilde{\chi}_1^0$ with 100% branching ratio, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b l \nu \tilde{\chi}_1^0$ with 100% branching ratio, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b l \nu \tilde{\chi}_1^0$ with 100% branching ratio, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b l \nu \tilde{\chi}_1^0$ with 100% branching ratio, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty.The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b l \nu \tilde{\chi}_1^0$ with 100% branching ratio, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty.The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.
Exclusion limits for (a) $t\bar{t} + \phi $ scalar and (b) $t\bar{t} + a $ pseudoscalar models as a function of the DM particle mass for a mediator mass of 10 GeV. The limits are calculated at 95% CL and are expressed in terms of the ratio of the excluded cross-section to the nominal cross-section for a coupling assumption of $g = g_q = g_{\chi} = 1$. The solid (dashed) lines shows the observed (expected) exclusion limits.
Exclusion limits for (a) $t\bar{t} + \phi $ scalar and (b) $t\bar{t} + a $ pseudoscalar models as a function of the DM particle mass for a mediator mass of 10 GeV. The limits are calculated at 95% CL and are expressed in terms of the ratio of the excluded cross-section to the nominal cross-section for a coupling assumption of $g = g_q = g_{\chi} = 1$. The solid (dashed) lines shows the observed (expected) exclusion limits.
Exclusion limits for (a) $t\bar{t} + \phi $ scalar and (b) $t\bar{t} + a $ pseudoscalar models as a function of the DM particle mass for a mediator mass of 10 GeV. The limits are calculated at 95% CL and are expressed in terms of the ratio of the excluded cross-section to the nominal cross-section for a coupling assumption of $g = g_q = g_{\chi} = 1$. The solid (dashed) lines shows the observed (expected) exclusion limits.
Exclusion limits for (a) $t\bar{t} + \phi $ scalar and (b) $t\bar{t} + a $ pseudoscalar models as a function of the DM particle mass for a mediator mass of 10 GeV. The limits are calculated at 95% CL and are expressed in terms of the ratio of the excluded cross-section to the nominal cross-section for a coupling assumption of $g = g_q = g_{\chi} = 1$. The solid (dashed) lines shows the observed (expected) exclusion limits.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Three-body selection efficiency (a) SR-DF$^{3-body}_{t}$, (b) SR-SF$^{3-body}_{t}$, (c) SR-DF$^{3-body}_{W}$, (d) SR-SF$^{3-body}_{W}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Three-body selection efficiency (a) SR-DF$^{3-body}_{t}$, (b) SR-SF$^{3-body}_{t}$, (c) SR-DF$^{3-body}_{W}$, (d) SR-SF$^{3-body}_{W}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Three-body selection efficiency (a) SR-DF$^{3-body}_{t}$, (b) SR-SF$^{3-body}_{t}$, (c) SR-DF$^{3-body}_{W}$, (d) SR-SF$^{3-body}_{W}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Three-body selection efficiency (a) SR-DF$^{3-body}_{t}$, (b) SR-SF$^{3-body}_{t}$, (c) SR-DF$^{3-body}_{W}$, (d) SR-SF$^{3-body}_{W}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Four-body selection Efficiency (a) SR$^{4-body}_{Small \Delta m}$ , (b) $SR^{4-body}_{Large \Delta m}$ for a simplified model assuming $\tilde{t}_1$ pair production.
Four-body selection Efficiency (a) SR$^{4-body}_{Small \Delta m}$ , (b) $SR^{4-body}_{Large \Delta\ m}$ for a simplified model assuming $\tilde{t}_1$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} +\phi$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ t \tilde{t} +\phi$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ t \tilde{t} +\phi$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ t \tilde{t} +\phi$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ t \tilde{t} +\phi$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ t \tilde{t} +\phi$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming t \tilde{t} + a$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Three-body selection acceptance (a) SR-DF$^{3-body}_{t}$, (b) SR-SF$^{3-body}_{t}$, (c) SR-DF$^{3-body}_{W}$, (d) SR-SF$^{3-body}_{W}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Three-body selection acceptance (a) SR-DF$^{3-body}_{t}$, (b) SR-SF$^{3-body}_{t}$, (c) SR-DF$^{3-body}_{W}$, (d) SR-SF$^{3-body}_{W}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Three-body selection acceptance (a) SR-DF$^{3-body}_{t}$, (b) SR-SF$^{3-body}_{t}$, (c) SR-DF$^{3-body}_{W}$, (d) SR-SF$^{3-body}_{W}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Three-body selection acceptance (a) SR-DF$^{3-body}_{t}$, (b) SR-SF$^{3-body}_{t}$, (c) SR-DF$^{3-body}_{W}$, (d) SR-SF$^{3-body}_{W}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Four-body selection acceptance (a) SR$^{4-body}_{Small \Delta m}$ , (b) $SR^{4-body}_{Large \Delta m}$ for a simplified model assuming $\tilde{t}_1$ pair production.
Four-body selection acceptance (a) SR$^{4-body}_{Small \Delta m}$ , (b) $SR^{4-body}_{Large \Delta m}$ for a simplified model assuming $\tilde{t}_1$ pair production.
Two-body selection The numbers indicate the observed upper limits on the signal strenght for (a) a simplified model assuming $\tilde{t}_1$ pair production, (b) for $t\tilde{t} + a $ pseudoscalar models, (c) for $t\tilde{t} + \phi $ scalar models. In Figure (a), the red line corresponds to the observed limit.
Two-body selection The numbers indicate the observed upper limits on the signal strenght for (a) a simplified model assuming $\tilde{t}_1$ pair production, (b) for $t\tilde{t} + a $ pseudoscalar models, (c) for $t\tilde{t} + \phi $ scalar models. In Figure (a), the red line corresponds to the observed limit.
Two-body selection The numbers indicate the observed upper limits on the signal strenght for (a) a simplified model assuming $\tilde{t}_1$ pair production, (b) for $t\tilde{t} + a $ pseudoscalar models, (c) for $t\tilde{t} + \phi $ scalar models. In Figure (a), the red line corresponds to the observed limit.
Three-body selection The numbers indicate the upper limits on the signal strenght for a simplified model assuming $\tilde{t}_1$ pair production. For comparison, the red line corresponds to the observed limit.
Four-body selection The numbers indicate the upper limits on the signal strenght for a simplified model assuming $\tilde{t}_1$ pair production. For comparison, the red line corresponds to the observed limit.
Two-body selection The numbers indicate the upper limits on the signal cross-section for (a) a simplified model assuming $\tilde{t}_1$ pair production, (b) for $t\tilde{t} + a $ pseudoscalar models, (c) for $t\tilde{t} + \phi $ scalar models. In Figure (a), the red line corresponds to the observed limit.
Two-body selection The numbers indicate the upper limits on the signal cross-section for (a) a simplified model assuming $\tilde{t}_1$ pair production, (b) for $t\tilde{t} + a $ pseudoscalar models, (c) for $t\tilde{t} + \phi $ scalar models. In Figure (a), the red line corresponds to the observed limit.
Two-body selection The numbers indicate the upper limits on the signal cross-section for (a) a simplified model assuming $\tilde{t}_1$ pair production, (b) for $t\tilde{t} + a $ pseudoscalar models, (c) for $t\tilde{t} + \phi $ scalar models. In Figure (a), the red line corresponds to the observed limit.
Three-body selection The numbers indicate the upper limits on the signal cross-section for a simplified model assuming $\tilde{t}_1$ pair production. For comparison, the red line corresponds to the observed limit.
Four-body selection The numbers indicate the upper limits on the signal cross-section for a simplified model assuming $\tilde{t}_1$ pair production. For comparison, the red line corresponds to the observed limit.
Two-body selection. Background fit results for the $inclusive$ SRs. The Others category contains the contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$. Combined statistical and systematic uncertainties are given. Note that the individual uncertainties can be correlated, and do not necessarily add up quadratically to the total background uncertainty.
Cut flow for the simplified signal model $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}^0_1$ with $m(\tilde{t}_1)=600~ GeV$ and $m(\tilde{\chi}^0_1)=400~ GeV$ in the SRs for the two-body selection. The number of events is normalized to the cross-section and to an integrated luminosity of $139~fb^{-1}$.
Cut flow for the scalar signal model $t\bar{t} + \phi $ with $m(\phi)=150~ GeV$ and $m(\chi)=1~ GeV$ in the SRs for the two-body selection. The number of events is normalized to the cross-section and to an integrated luminosity of $139~fb^{-1}$.
Cut flow for the pseudoscalar signal model $t\bar{t} + a $ with $m(a)=150~ GeV$ and $m(\chi)=1~ GeV$ in the SRs for the two-body selection. The number of events is normalized to the cross-section and to an integrated luminosity of $139~fb^{-1}$.
Cut flow for the simplified signal model $\tilde{t}_1 \rightarrow bW\tilde{\chi}^0_1$ with $m(\tilde{t}_1)=550~ GeV$ and $m(\tilde{\chi}^0_1)=385~ GeV$ in the SRs for the three-body selection. The number of events is normalized to the cross-section and to an integrated luminosity of $139~fb^{-1}$.
Cut flow for the simplified signal model $\tilde{t}_1 \rightarrow bW\tilde{\chi}^0_1$ with $m(\tilde{t}_1)=550~ GeV$ and $m(\tilde{\chi}^0_1)=400~ GeV$ in the SRs for the three-body selection. The number of events is normalized to the cross-section and to an integrated luminosity of $139~fb^{-1}$.
Cut flow for the simplified signal model $\tilde{t}_1 \rightarrow bW\tilde{\chi}^0_1$ with $m(\tilde{t}_1)=550~ GeV$ and $m(\tilde{\chi}^0_1)=430~ GeV$ in the SRs for the three-body selection. The number of events is normalized to the cross-section and to an integrated luminosity of $139~fb^{-1}$.
Cut flow for the simplified signal model $\tilde{t}_1 \rightarrow bW\tilde{\chi}^0_1$ with $m(\tilde{t}_1)=550~ GeV$ and $m(\tilde{\chi}^0_1)=460~ GeV$ in the SRs for the three-body selection. The number of events is normalized to the cross-section and to an integrated luminosity of $139~fb^{-1}$.
Cut flow for the simplified signal model $\tilde{t}_1 \rightarrow b l \nu \tilde{\chi}^0_1$ with $m(\tilde{t}_1)=400~ GeV$ and $m(\tilde{\chi}^0_1)=380~ GeV$ in the SRs for the four-body selection. The number of events is normalized to the cross-section and to an integrated luminosity of $139~fb^{-1}$.
Cut flow for the simplified signal model $\tilde{t}_1 \rightarrow b l \nu \tilde{\chi}^0_1$ with $m(\tilde{t}_1)=460~ GeV$ and $m(\tilde{\chi}^0_1)=415~ GeV$ in the SRs for the four-body selection. The number of events is normalized to the cross-section and to an integrated luminosity of $139~fb^{-1}$.
Cut flow for the simplified signal model $\tilde{t}_1 \rightarrow b l \nu \tilde{\chi}^0_1$ with $m(\tilde{t}_1)=400~ GeV$ and $m(\tilde{\chi}^0_1)=320~ GeV$ in the SRs for the four-body selection. The number of events is normalized to the cross-section and to an integrated luminosity of $139~fb^{-1}$.
A search is presented for a heavy vector resonance decaying into a Z boson and the standard model Higgs boson, where the Z boson is identified through its leptonic decays to electrons, muons, or neutrinos, and the Higgs boson is identified through its hadronic decays. The search is performed in a Lorentz-boosted regime and is based on data collected from 2016 to 2018 at the CERN LHC, corresponding to an integrated luminosity of 137 fb$^{-1}$. Upper limits are derived on the production of a narrow heavy resonance Z', and a mass below 3.5 and 3.7 TeV is excluded at 95% confidence level in models where the heavy vector boson couples exclusively to fermions and to bosons, respectively. These are the most stringent limits placed on the Heavy Vector Triplet Z' model to date. If the heavy vector boson couples exclusively to standard model bosons, upper limits on the product of the cross section and branching fraction are set between 23 and 0.3 fb for a Z' mass between 0.8 and 4.6 TeV, respectively. This is the first limit set on a heavy vector boson coupling exclusively to standard model bosons in its production and decay.
The product of signal acceptance and efficiency in the 0l categories for the signal produced via qqbar annihilation.
The product of signal acceptance and efficiency in the 2l categories for the signal produced via qqbar annihilation.
The product of signal acceptance and efficiency in the 0l categories for the signal produced via vector boson fusion.
The product of signal acceptance and efficiency in the 2l categories for the signal produced via vector boson fusion.
$m_{X}^{T}$ distribution in data in the 0l 2b non-VBF category. The data is shown as Events/10 GeV. The distribution is shown up 4000 GeV, which corresponds to the event with the highest $m_{X}^{T}$ observed in the SR.
$m_{X}^{T}$ distribution in data in the 0l $\leq$1b non-VBF category. The data is shown as Events/10 GeV. The distribution is shown up 4000 GeV, which corresponds to the event with the highest $m_{X}^{T}$ observed in the SR.
$m_{X}$ distribution in data in the 2e 2b non-VBF category. The data is shown as Events/10 GeV. The distribution is shown up 4000 GeV, which corresponds to the event with the highest $m_{X}$ observed in the SR.
$m_{X}$ distribution in data in the 2e $\leq$1b non-VBF category. The data is shown as Events/10 GeV. The distribution is shown up 4000 GeV, which corresponds to the event with the highest $m_{X}$ observed in the SR.
$m_{X}$ distribution in data in the 2$\mu$ 2b non-VBF category. The data is shown as Events/10 GeV. The distribution is shown up 4000 GeV, which corresponds to the event with the highest $m_{X}$ observed in the SR.
$m_{X}$ distribution in data in the 2$\mu$ $\leq$1b non-VBF category. The data is shown as Events/10 GeV. The distribution is shown up 4000 GeV, which corresponds to the event with the highest $m_{X}$ observed in the SR.
$m_{X}^{T}$ distribution in data in the 0l 2b VBF category. The data is shown as Events/10 GeV. The distribution is shown up 4000 GeV, which corresponds to the event with the highest $m_{X}^{T}$ observed in the SR.
$m_{X}^{T}$ distribution in data in the 0l $\leq$1b VBF category. The data is shown as Events/10 GeV. The distribution is shown up 4000 GeV, which corresponds to the event with the highest $m_{X}^{T}$ observed in the SR.
$m_{X}$ distribution in data in the 2e 2b VBF category. The data is shown as Events/10 GeV. The distribution is shown up 4000 GeV, which corresponds to the event with the highest $m_{X}$ observed in the SR.
$m_{X}$ distribution in data in the 2e $\leq$1b VBF category. The data is shown as Events/10 GeV. The distribution is shown up 4000 GeV, which corresponds to the event with the highest $m_{X}$ observed in the SR.
$m_{X}$ distribution in data in the 2$\mu$ 2b VBF category. The data is shown as Events/10 GeV. The distribution is shown up 4000 GeV, which corresponds to the event with the highest $m_{X}$ observed in the SR.
$m_{X}$ distribution in data in the 2$\mu$ $\leq$1b VBF category. The data is shown as Events/10 GeV. The distribution is shown up 4000 GeV, which corresponds to the event with the highest $m_{X}$ observed in the SR.
Observed and expected 95% CL upper limit on $\sigma \mathcal{B}$(Z'-> ZH) with all categories combined for the non-VBF signal, including all statistical and systematic uncertainties. The inner green band and the outer yellow band indicate the regions containing 68 and 95%, respectively, of the distribution of expected limits under the background-only hypothesis. The CMS search for a heavy resonance using 2016 data and the same final state [JHEP 11 (2018) 172] is shown as a comparison.
Observed and expected 95% CL upper limit on $\sigma \mathcal{B}$(Z'-> ZH) with all categories combined for the VBF signal, including all statistical and systematic uncertainties. The inner green band and the outer yellow band indicate the regions containing 68 and 95%, respectively, of the distribution of expected limits under the background-only hypothesis.
Observed exclusion limit in the space of the HVT model parameters [$g_{V}c_{H}$, $g^{2}c_{F}/g_{V}$] for mass hypotheses of 2 TeV for the non-VBF signal.
Observed exclusion limit in the space of the HVT model parameters [$g_{V}c_{H}$, $g^{2}c_{F}/g_{V}$] for mass hypotheses of 3 TeV for the non-VBF signal.
Observed exclusion limit in the space of the HVT model parameters [$g_{V}c_{H}$, $g^{2}c_{F}/g_{V}$] for mass hypotheses of 4 TeV for the non-VBF signal.
A search for pair production of bottom squarks in events with hadronically decaying $\tau$-leptons, $b$-tagged jets and large missing transverse momentum is presented. The analyzed dataset is based on proton-proton collisions at $\sqrt{s}$ = 13 TeV delivered by the Large Hadron Collider and recorded by the ATLAS detector from 2015 to 2018, and corresponds to an integrated luminosity of 139 fb$^{-1}$. The observed data are compatible with the expected Standard Model background. Results are interpreted in a simplified model where each bottom squark is assumed to decay into the second-lightest neutralino $\tilde \chi_2^0$ and a bottom quark, with $\tilde \chi_2^0$ decaying into a Higgs boson and the lightest neutralino $\tilde \chi_1^0$. The search focuses on final states where at least one Higgs boson decays into a pair of hadronically decaying $\tau$-leptons. This allows the acceptance and thus the sensitivity to be significantly improved relative to the previous results at low masses of the $\tilde \chi_2^0$, where bottom-squark masses up to 850 GeV are excluded at the 95% confidence level, assuming a mass difference of 130 GeV between $\tilde \chi_2^0$ and $\tilde \chi_1^0$. Model-independent upper limits are also set on the cross section of processes beyond the Standard Model.
The expected exclusion contour at $95\%$ CL as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV. Masses within the contour are excluded.
The observed exclusion contour at $95\%$ CL as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV. Masses within the contour are excluded.
Acceptance in the Single-bin SR as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV. Keep in mind that the acceptance is given in units of $10^{-4}$.
Efficiency in the Single-bin SR as a function of the M(Sbottom) vs. M(N2) with the $\Delta$ M(N2,N1) $= 130$ GeV. Keep in mind that the efficiency is given in units of $10^{-2}$.
Acceptance in the Multi-bin SR, $\min_{\Theta} < 0.5$ bin as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV. Keep in mind that the acceptance is given in units of $10^{-4}$.
Efficiency in the Multi-bin SR, $\min_{\Theta} < 0.5$ bin as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV. Keep in mind that the efficiency is given in units of $10^{-2}$.
Acceptance in the Multi-bin SR, $0.5 < \min_{\Theta} < 1.0$ bin as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV. Keep in mind that the acceptance is given in units of $10^{-4}$.
Efficiency in the Multi-bin SR, $0.5 < \min_{\Theta} < 1.0$ bin as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV. Keep in mind that the efficiency is given in units of $10^{-2}$.
Acceptance in the Multi-bin SR, $\min_{\Theta} > 1.0$ bin as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV. Keep in mind that the acceptance is given in units of $10^{-4}$.
Efficiency in the Multi-bin SR, $\min_{\Theta} > 1.0$ bin as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV. Keep in mind that the efficiency is given in units of $10^{-2}$.
Observed upper limits on the signal cross section as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV.
Expected upper limits on the signal cross section as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV.
Cutflows for the bechmarl signal point M(Sbottom) = 800 GeV, M(N2) = 180 GeV. Weighted event yields are reported starting with the "Preselection" line, normalized to an integrated luminosity of $139$ fb$^{−1}$.
Comparison of the expected and observed event yields in the signal regions. The top-quark and Z(mumu) background contributions are scaled with the normalization factors obtained from the background-only fit. The other contribution includes all the backgrounds not explicitly listed in the legend (V+jets except Z(mumu)+jets, di-/triboson, multijet). The hatched band indicates the total statistical and systematic uncertainties in the SM background. The contributions from three signal models to the signal regions are also displayed, where the masses M(Sbottom) and M(N2) are given in GeV in the legend. The lower panel shows the significance of the deviation of the observed yield from the expected background yield.
Dominant systematic uncertainties in the background prediction for the signal regions after the fit to the control regions. “Other” includes the uncertainties arising from muons, jet-vertex tagging, modeling of pile-up, the $E_{T}^{miss}$ computation, multijet background, and luminosity. The individual uncertainties can be correlated and do not necessarily add up quadratically to the total uncertainty.
A search for chargino$-$neutralino pair production in three-lepton final states with missing transverse momentum is presented. The study is based on a dataset of $\sqrt{s} = 13$ TeV $pp$ collisions recorded with the ATLAS detector at the LHC, corresponding to an integrated luminosity of 139 fb$^{-1}$. No significant excess relative to the Standard Model predictions is found in data. The results are interpreted in simplified models of supersymmetry, and statistically combined with results from a previous ATLAS search for compressed spectra in two-lepton final states. Various scenarios for the production and decay of charginos ($\tilde\chi^\pm_1$) and neutralinos ($\tilde\chi^0_2$) are considered. For pure higgsino $\tilde\chi^\pm_1\tilde\chi^0_2$ pair-production scenarios, exclusion limits at 95% confidence level are set on $\tilde\chi^0_2$ masses up to 210 GeV. Limits are also set for pure wino $\tilde\chi^\pm_1\tilde\chi^0_2$ pair production, on $\tilde\chi^0_2$ masses up to 640 GeV for decays via on-shell $W$ and $Z$ bosons, up to 300 GeV for decays via off-shell $W$ and $Z$ bosons, and up to 190 GeV for decays via $W$ and Standard Model Higgs bosons.
This is the HEPData space for the ATLAS SUSY EWK three-lepton search. The full resolution figures can be found at https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/SUSY-2019-09/ The full statistical likelihoods have been provided for this analysis. They can be downloaded by clicking on the purple 'Resources' button above and selecting the 'Common Resources' category. <b>Region yields:</b> <ul display="inline-block"> <li><a href="?table=Tab%2012%20Onshell%20WZ%20Signal%20Region%20Yields%20Table">Tab 12 Onshell WZ Signal Region Yields Table</a> <li><a href="?table=Tab%2013%20Onshell%20Wh%20Signal%20Region%20Yields%20Table">Tab 13 Onshell Wh Signal Region Yields Table</a> <li><a href="?table=Tab%2014%20Offshell%20low-$E_{T}^{miss}$%20Signal%20Region%20Yields%20Table">Tab 14 Offshell low-$E_{T}^{miss}$ Signal Region Yields Table</a> <li><a href="?table=Tab%2015%20Offshell%20high-$E_{T}^{miss}$%20Signal%20Region%20Yields%20Table">Tab 15 Offshell high-$E_{T}^{miss}$ Signal Region Yields Table</a> <li><a href="?table=Tab%2020%20RJR%20Signal%20Region%20Yields%20Table">Tab 20 RJR Signal Region Yields Table</a> <li><a href="?table=Fig%204%20Onshell%20Control%20and%20Validation%20Region%20Yields">Fig 4 Onshell Control and Validation Region Yields</a> <li><a href="?table=Fig%208%20Offshell%20Control%20and%20Validation%20Region%20Yields">Fig 8 Offshell Control and Validation Region Yields</a> <li><a href="?table=Fig%2010%20Onshell%20WZ%20Signal%20Region%20Yields">Fig 10 Onshell WZ Signal Region Yields</a> <li><a href="?table=Fig%2011%20Onshell%20Wh%20Signal%20Region%20Yields">Fig 11 Onshell Wh Signal Region Yields</a> <li><a href="?table=Fig%2012%20Offshell%20Signal%20Region%20Yields">Fig 12 Offshell Signal Region Yields</a> <li><a href="?table=Fig%2018%20RJR%20Control%20and%20Validation%20Region%20Yields">Fig 18 RJR Control and Validation Region Yields</a> </ul> <b>Exclusion contours:</b> <ul display="inline-block"> <li><a href="?table=Fig%2016a%20WZ%20Exclusion:%20Wino-bino(%2b),%20Obs">Fig 16a WZ Exclusion: Wino-bino(+), Obs</a> <li><a href="?table=Fig%2016a%20WZ%20Exclusion:%20Wino-bino(%2b),%20Obs_Up">Fig 16a WZ Exclusion: Wino-bino(+), Obs_Up</a> <li><a href="?table=Fig%2016a%20WZ%20Exclusion:%20Wino-bino(%2b),%20Obs_Down">Fig 16a WZ Exclusion: Wino-bino(+), Obs_Down</a> <li><a href="?table=Fig%2016a%20WZ%20Exclusion:%20Wino-bino(%2b),%20Exp">Fig 16a WZ Exclusion: Wino-bino(+), Exp</a> <li><a href="?table=Fig%2016a%20WZ%20Exclusion:%20Wino-bino(%2b),%20Exp_Up">Fig 16a WZ Exclusion: Wino-bino(+), Exp_Up</a> <li><a href="?table=Fig%2016a%20WZ%20Exclusion:%20Wino-bino(%2b),%20Exp_Down">Fig 16a WZ Exclusion: Wino-bino(+), Exp_Down</a> <li><a href="?table=Fig%2016a%20WZ%20Exclusion:%20Wino-bino(%2b),%20compressed_Obs">Fig 16a WZ Exclusion: Wino-bino(+), compressed_Obs</a> <li><a href="?table=Fig%2016a%20WZ%20Exclusion:%20Wino-bino(%2b),%20compressed_Exp">Fig 16a WZ Exclusion: Wino-bino(+), compressed_Exp</a> <li><a href="?table=Fig%2016a%20WZ%20Exclusion:%20Wino-bino(%2b),%20offshell_Obs">Fig 16a WZ Exclusion: Wino-bino(+), offshell_Obs</a> <li><a href="?table=Fig%2016a%20WZ%20Exclusion:%20Wino-bino(%2b),%20offshell_Exp">Fig 16a WZ Exclusion: Wino-bino(+), offshell_Exp</a> <li><a href="?table=Fig%2016a%20WZ%20Exclusion:%20Wino-bino(%2b),%20onshell_Obs">Fig 16a WZ Exclusion: Wino-bino(+), onshell_Obs</a> <li><a href="?table=Fig%2016a%20WZ%20Exclusion:%20Wino-bino(%2b),%20onshell_Exp">Fig 16a WZ Exclusion: Wino-bino(+), onshell_Exp</a> <li><a href="?table=Fig%2016b%20WZ%20Exclusion:%20Wino-bino(%2b)%20($\Delta%20m$),%20Obs">Fig 16b WZ Exclusion: Wino-bino(+) ($\Delta m$), Obs</a> <li><a href="?table=Fig%2016b%20WZ%20Exclusion:%20Wino-bino(%2b)%20($\Delta%20m$),%20Obs_Up">Fig 16b WZ Exclusion: Wino-bino(+) ($\Delta m$), Obs_Up</a> <li><a href="?table=Fig%2016b%20WZ%20Exclusion:%20Wino-bino(%2b)%20($\Delta%20m$),%20Obs_Down">Fig 16b WZ Exclusion: Wino-bino(+) ($\Delta m$), Obs_Down</a> <li><a href="?table=Fig%2016b%20WZ%20Exclusion:%20Wino-bino(%2b)%20($\Delta%20m$),%20Exp">Fig 16b WZ Exclusion: Wino-bino(+) ($\Delta m$), Exp</a> <li><a href="?table=Fig%2016b%20WZ%20Exclusion:%20Wino-bino(%2b)%20($\Delta%20m$),%20Exp_Up">Fig 16b WZ Exclusion: Wino-bino(+) ($\Delta m$), Exp_Up</a> <li><a href="?table=Fig%2016b%20WZ%20Exclusion:%20Wino-bino(%2b)%20($\Delta%20m$),%20Exp_Down">Fig 16b WZ Exclusion: Wino-bino(+) ($\Delta m$), Exp_Down</a> <li><a href="?table=Fig%2016b%20WZ%20Exclusion:%20Wino-bino(%2b)%20($\Delta%20m$),%20compressed_Obs">Fig 16b WZ Exclusion: Wino-bino(+) ($\Delta m$), compressed_Obs</a> <li><a href="?table=Fig%2016b%20WZ%20Exclusion:%20Wino-bino(%2b)%20($\Delta%20m$),%20compressed_Exp">Fig 16b WZ Exclusion: Wino-bino(+) ($\Delta m$), compressed_Exp</a> <li><a href="?table=Fig%2016b%20WZ%20Exclusion:%20Wino-bino(%2b)%20($\Delta%20m$),%20offshell_Obs">Fig 16b WZ Exclusion: Wino-bino(+) ($\Delta m$), offshell_Obs</a> <li><a href="?table=Fig%2016b%20WZ%20Exclusion:%20Wino-bino(%2b)%20($\Delta%20m$),%20offshell_Exp">Fig 16b WZ Exclusion: Wino-bino(+) ($\Delta m$), offshell_Exp</a> <li><a href="?table=Fig%2016b%20WZ%20Exclusion:%20Wino-bino(%2b)%20($\Delta%20m$),%20onshell_Obs">Fig 16b WZ Exclusion: Wino-bino(+) ($\Delta m$), onshell_Obs</a> <li><a href="?table=Fig%2016b%20WZ%20Exclusion:%20Wino-bino(%2b)%20($\Delta%20m$),%20onshell_Exp">Fig 16b WZ Exclusion: Wino-bino(+) ($\Delta m$), onshell_Exp</a> <li><a href="?table=Fig%2016c%20WZ%20Exclusion:%20Wino-bino(-)%20($\Delta%20m$),%20Obs">Fig 16c WZ Exclusion: Wino-bino(-) ($\Delta m$), Obs</a> <li><a href="?table=Fig%2016c%20WZ%20Exclusion:%20Wino-bino(-)%20($\Delta%20m$),%20Obs_Up">Fig 16c WZ Exclusion: Wino-bino(-) ($\Delta m$), Obs_Up</a> <li><a href="?table=Fig%2016c%20WZ%20Exclusion:%20Wino-bino(-)%20($\Delta%20m$),%20Obs_Down">Fig 16c WZ Exclusion: Wino-bino(-) ($\Delta m$), Obs_Down</a> <li><a href="?table=Fig%2016c%20WZ%20Exclusion:%20Wino-bino(-)%20($\Delta%20m$),%20Exp">Fig 16c WZ Exclusion: Wino-bino(-) ($\Delta m$), Exp</a> <li><a href="?table=Fig%2016c%20WZ%20Exclusion:%20Wino-bino(-)%20($\Delta%20m$),%20Exp_Up">Fig 16c WZ Exclusion: Wino-bino(-) ($\Delta m$), Exp_Up</a> <li><a href="?table=Fig%2016c%20WZ%20Exclusion:%20Wino-bino(-)%20($\Delta%20m$),%20Exp_Down">Fig 16c WZ Exclusion: Wino-bino(-) ($\Delta m$), Exp_Down</a> <li><a href="?table=Fig%2016c%20WZ%20Exclusion:%20Wino-bino(-)%20($\Delta%20m$),%20compressed_Obs">Fig 16c WZ Exclusion: Wino-bino(-) ($\Delta m$), compressed_Obs</a> <li><a href="?table=Fig%2016c%20WZ%20Exclusion:%20Wino-bino(-)%20($\Delta%20m$),%20compressed_Exp">Fig 16c WZ Exclusion: Wino-bino(-) ($\Delta m$), compressed_Exp</a> <li><a href="?table=Fig%2016c%20WZ%20Exclusion:%20Wino-bino(-)%20($\Delta%20m$),%20offshell_Obs">Fig 16c WZ Exclusion: Wino-bino(-) ($\Delta m$), offshell_Obs</a> <li><a href="?table=Fig%2016c%20WZ%20Exclusion:%20Wino-bino(-)%20($\Delta%20m$),%20offshell_Exp">Fig 16c WZ Exclusion: Wino-bino(-) ($\Delta m$), offshell_Exp</a> <li><a href="?table=Fig%2016d%20WZ%20Exclusion:%20Higgsino%20($\Delta%20m$),%20Obs">Fig 16d WZ Exclusion: Higgsino ($\Delta m$), Obs</a> <li><a href="?table=Fig%2016d%20WZ%20Exclusion:%20Higgsino%20($\Delta%20m$),%20Obs_Up">Fig 16d WZ Exclusion: Higgsino ($\Delta m$), Obs_Up</a> <li><a href="?table=Fig%2016d%20WZ%20Exclusion:%20Higgsino%20($\Delta%20m$),%20Obs_Down">Fig 16d WZ Exclusion: Higgsino ($\Delta m$), Obs_Down</a> <li><a href="?table=Fig%2016d%20WZ%20Exclusion:%20Higgsino%20($\Delta%20m$),%20Exp">Fig 16d WZ Exclusion: Higgsino ($\Delta m$), Exp</a> <li><a href="?table=Fig%2016d%20WZ%20Exclusion:%20Higgsino%20($\Delta%20m$),%20Exp_Up">Fig 16d WZ Exclusion: Higgsino ($\Delta m$), Exp_Up</a> <li><a href="?table=Fig%2016d%20WZ%20Exclusion:%20Higgsino%20($\Delta%20m$),%20Exp_Down">Fig 16d WZ Exclusion: Higgsino ($\Delta m$), Exp_Down</a> <li><a href="?table=Fig%2016d%20WZ%20Exclusion:%20Higgsino%20($\Delta%20m$),%20compressed_Obs">Fig 16d WZ Exclusion: Higgsino ($\Delta m$), compressed_Obs</a> <li><a href="?table=Fig%2016d%20WZ%20Exclusion:%20Higgsino%20($\Delta%20m$),%20compressed_Exp">Fig 16d WZ Exclusion: Higgsino ($\Delta m$), compressed_Exp</a> <li><a href="?table=Fig%2016d%20WZ%20Exclusion:%20Higgsino%20($\Delta%20m$),%20offshell_Obs">Fig 16d WZ Exclusion: Higgsino ($\Delta m$), offshell_Obs</a> <li><a href="?table=Fig%2016d%20WZ%20Exclusion:%20Higgsino%20($\Delta%20m$),%20offshell_Exp">Fig 16d WZ Exclusion: Higgsino ($\Delta m$), offshell_Exp</a> <li><a href="?table=Fig%2017%20Wh%20Exclusion,%20Obs">Fig 17 Wh Exclusion, Obs</a> <li><a href="?table=Fig%2017%20Wh%20Exclusion,%20Obs_Up">Fig 17 Wh Exclusion, Obs_Up</a> <li><a href="?table=Fig%2017%20Wh%20Exclusion,%20Obs_Down">Fig 17 Wh Exclusion, Obs_Down</a> <li><a href="?table=Fig%2017%20Wh%20Exclusion,%20Exp">Fig 17 Wh Exclusion, Exp</a> <li><a href="?table=Fig%2017%20Wh%20Exclusion,%20Exp_Up">Fig 17 Wh Exclusion, Exp_Up</a> <li><a href="?table=Fig%2017%20Wh%20Exclusion,%20Exp_Down">Fig 17 Wh Exclusion, Exp_Down</a> </ul> <b>Upper limits:</b> <ul display="inline-block"> <li><a href="?table=AuxFig%208a%20WZ%20Excl.%20Upper%20Limit%20Obs.%20Wino-bino(%2b)%20($\Delta%20m$)">AuxFig 8a WZ Excl. Upper Limit Obs. Wino-bino(+) ($\Delta m$)</a> <li><a href="?table=AuxFig%208b%20WZ%20Excl.%20Upper%20Limit%20Exp.%20Wino-bino(%2b)%20($\Delta%20m$)">AuxFig 8b WZ Excl. Upper Limit Exp. Wino-bino(+) ($\Delta m$)</a> <li><a href="?table=AuxFig%208c%20WZ%20Excl.%20Upper%20Limit%20Obs.%20Wino-bino(%2b)%20($\Delta%20m$)">AuxFig 8c WZ Excl. Upper Limit Obs. Wino-bino(+) ($\Delta m$)</a> <li><a href="?table=AuxFig%208d%20WZ%20Excl.%20Upper%20Limit%20Exp.%20Wino-bino(%2b)%20($\Delta%20m$)">AuxFig 8d WZ Excl. Upper Limit Exp. Wino-bino(+) ($\Delta m$)</a> <li><a href="?table=AuxFig%208e%20WZ%20Excl.%20Upper%20Limit%20Obs.%20Wino-bino(-)%20($\Delta%20m$)">AuxFig 8e WZ Excl. Upper Limit Obs. Wino-bino(-) ($\Delta m$)</a> <li><a href="?table=AuxFig%208f%20WZ%20Excl.%20Upper%20Limit%20Exp.%20Wino-bino(-)%20($\Delta%20m$)">AuxFig 8f WZ Excl. Upper Limit Exp. Wino-bino(-) ($\Delta m$)</a> <li><a href="?table=AuxFig%208g%20WZ%20Excl.%20Upper%20Limit%20Obs.%20Higgsino%20($\Delta%20m$)">AuxFig 8g WZ Excl. Upper Limit Obs. Higgsino ($\Delta m$)</a> <li><a href="?table=AuxFig%208h%20WZ%20Excl.%20Upper%20Limit%20Exp.%20Higgsino%20($\Delta%20m$)">AuxFig 8h WZ Excl. Upper Limit Exp. Higgsino ($\Delta m$)</a> <li><a href="?table=AuxFig%209a%20Wh%20Excl.%20Upper%20Limit%20Obs.">AuxFig 9a Wh Excl. Upper Limit Obs.</a> <li><a href="?table=AuxFig%209b%20Wh%20Excl.%20Upper%20Limit%20Exp.">AuxFig 9b Wh Excl. Upper Limit Exp.</a> </ul> <b>Model-independent discovery fits:</b> <ul display="inline-block"> <li><a href="?table=Tab%2018%20Onshell%20Discovery%20Fit%20Table">Tab 18 Onshell Discovery Fit Table</a> <li><a href="?table=Tab%2019%20Offshell%20Discovery%20Fit%20Table">Tab 19 Offshell Discovery Fit Table</a> <li><a href="?table=Tab%2021%20RJR%20Discovery%20Fit%20Table">Tab 21 RJR Discovery Fit Table</a> </ul> <b>Kinematic distributions:</b> <ul display="inline-block"> <li><a href="?table=Fig%2013a%20SR$_{DFOS}^{Wh}$-1%20($\Delta%20R_{OS,%20near}$)">Fig 13a SR$_{DFOS}^{Wh}$-1 ($\Delta R_{OS, near}$)</a> <li><a href="?table=Fig%2013b%20SR$_{DFOS}^{Wh}$-2%20(3rd%20Lep.%20$p_{T}$)">Fig 13b SR$_{DFOS}^{Wh}$-2 (3rd Lep. $p_{T}$)</a> <li><a href="?table=Fig%2013c%20SR$_{0j}^{WZ}$%20($E_{T}^{miss}$)">Fig 13c SR$_{0j}^{WZ}$ ($E_{T}^{miss}$)</a> <li><a href="?table=Fig%2013d%20SR$_{0j}^{WZ}$%20($m_{T}$)">Fig 13d SR$_{0j}^{WZ}$ ($m_{T}$)</a> <li><a href="?table=Fig%2014a%20SR$^{offWZ}_{LowETmiss}$-0j%20($m_{T}^{minmll}$)">Fig 14a SR$^{offWZ}_{LowETmiss}$-0j ($m_{T}^{minmll}$)</a> <li><a href="?table=Fig%2014b%20SR$^{offWZ}_{LowETmiss}$-nj%20($m_{T}^{minmll}$)">Fig 14b SR$^{offWZ}_{LowETmiss}$-nj ($m_{T}^{minmll}$)</a> <li><a href="?table=Fig%2014c%20SR$^{offWZ}_{HighETmiss}$-0j%20($m_{T}^{minmll}$)">Fig 14c SR$^{offWZ}_{HighETmiss}$-0j ($m_{T}^{minmll}$)</a> <li><a href="?table=Fig%2014d%20SR$^{offWZ}_{HighETmiss}$-nj%20($p_T^l%20\div%20E_T^{miss}$)">Fig 14d SR$^{offWZ}_{HighETmiss}$-nj ($p_T^l \div E_T^{miss}$)</a> <li><a href="?table=Fig%2020a%20RJR%20SR3$\ell$-Low%20($p_{T}^{\ell%201}$)">Fig 20a RJR SR3$\ell$-Low ($p_{T}^{\ell 1}$)</a> <li><a href="?table=Fig%2020b%20RJR%20SR3$\ell$-Low%20($H_{3,1}^{PP}$)">Fig 20b RJR SR3$\ell$-Low ($H_{3,1}^{PP}$)</a> <li><a href="?table=Fig%2020c%20RJR%20SR3$\ell$-ISR%20($p_{T~ISR}^{CM}$)">Fig 20c RJR SR3$\ell$-ISR ($p_{T~ISR}^{CM}$)</a> <li><a href="?table=Fig%2020d%20RJR%20SR3$\ell$-ISR%20($R_{ISR}$)">Fig 20d RJR SR3$\ell$-ISR ($R_{ISR}$)</a> </ul> <b>Cutflows:</b> <ul display="inline-block"> <li><a href="?table=AuxTab%205%20Cutflow:%20Onshell%20WZ">AuxTab 5 Cutflow: Onshell WZ</a> <li><a href="?table=AuxTab%206%20Cutflow:%20Onshell%20Wh">AuxTab 6 Cutflow: Onshell Wh</a> <li><a href="?table=AuxTab%207%20Cutflow:%20Offshell%20Wino-bino(%2b)%20(250,235)">AuxTab 7 Cutflow: Offshell Wino-bino(+) (250,235)</a> <li><a href="?table=AuxTab%208%20Cutflow:%20Offshell%20Wino-bino(%2b)%20(125,85)">AuxTab 8 Cutflow: Offshell Wino-bino(+) (125,85)</a> <li><a href="?table=AuxTab%209%20Cutflow:%20Offshell%20Wino-bino(%2b)%20(250,170)">AuxTab 9 Cutflow: Offshell Wino-bino(+) (250,170)</a> <li><a href="?table=AuxTab%2010%20Cutflow:%20Offshell%20Wino-bino(-)%20(250,235)">AuxTab 10 Cutflow: Offshell Wino-bino(-) (250,235)</a> <li><a href="?table=AuxTab%2011%20Cutflow:%20Offshell%20Wino-bino(-)%20(125,85)">AuxTab 11 Cutflow: Offshell Wino-bino(-) (125,85)</a> <li><a href="?table=AuxTab%2012%20Cutflow:%20Offshell%20Wino-bino(-)%20(250,170)">AuxTab 12 Cutflow: Offshell Wino-bino(-) (250,170)</a> <li><a href="?table=AuxTab%2013%20Cutflow:%20Offshell%20Higgsino%20(120,100)">AuxTab 13 Cutflow: Offshell Higgsino (120,100)</a> <li><a href="?table=AuxTab%2014%20Cutflow:%20Offshell%20Higgsino%20(100,40)">AuxTab 14 Cutflow: Offshell Higgsino (100,40)</a> <li><a href="?table=AuxTab%2015%20Cutflow:%20Offshell%20Higgsino%20(185,125)">AuxTab 15 Cutflow: Offshell Higgsino (185,125)</a> </ul> <b>Acceptances and Efficiencies:</b> <ul display="inline-block"> <li><a href="?table=AuxFig%2010a%20Acc:%20Onshell%20SR$_{0j}^{WZ}$">AuxFig 10a Acc: Onshell SR$_{0j}^{WZ}$</a> <li><a href="?table=AuxFig%2010b%20Eff:%20Onshell%20SR$_{0j}^{WZ}$">AuxFig 10b Eff: Onshell SR$_{0j}^{WZ}$</a> <li><a href="?table=AuxFig%2010c%20Acc:%20Onshell%20SR$_{nj}^{WZ}$">AuxFig 10c Acc: Onshell SR$_{nj}^{WZ}$</a> <li><a href="?table=AuxFig%2010d%20Eff:%20Onshell%20SR$_{nj}^{WZ}$">AuxFig 10d Eff: Onshell SR$_{nj}^{WZ}$</a> <li><a href="?table=AuxFig%2011a%20Acc:%20Onshell%20SR$_{low-m_{ll}-0j}^{Wh}$">AuxFig 11a Acc: Onshell SR$_{low-m_{ll}-0j}^{Wh}$</a> <li><a href="?table=AuxFig%2011b%20Eff:%20Onshell%20SR$_{low-m_{ll}-0j}^{Wh}$">AuxFig 11b Eff: Onshell SR$_{low-m_{ll}-0j}^{Wh}$</a> <li><a href="?table=AuxFig%2011c%20Acc:%20Onshell%20SR$_{low-m_{ll}-nj}^{Wh}$">AuxFig 11c Acc: Onshell SR$_{low-m_{ll}-nj}^{Wh}$</a> <li><a href="?table=AuxFig%2011d%20Eff:%20Onshell%20SR$_{low-m_{ll}-nj}^{Wh}$">AuxFig 11d Eff: Onshell SR$_{low-m_{ll}-nj}^{Wh}$</a> <li><a href="?table=AuxFig%2011e%20Acc:%20Onshell%20SR$_{DFOS}^{Wh}$">AuxFig 11e Acc: Onshell SR$_{DFOS}^{Wh}$</a> <li><a href="?table=AuxFig%2011f%20Eff:%20Onshell%20SR$_{DFOS}^{Wh}$">AuxFig 11f Eff: Onshell SR$_{DFOS}^{Wh}$</a> <li><a href="?table=AuxFig%2012a%20Acc:%20Off.%20Wino-bino(%2b)%20SR$^{offWZ}_{lowETmiss}$-0j">AuxFig 12a Acc: Off. Wino-bino(+) SR$^{offWZ}_{lowETmiss}$-0j</a> <li><a href="?table=AuxFig%2012b%20Eff:%20Off.%20Wino-bino(%2b)%20SR$^{offWZ}_{lowETmiss}$-0j">AuxFig 12b Eff: Off. Wino-bino(+) SR$^{offWZ}_{lowETmiss}$-0j</a> <li><a href="?table=AuxFig%2012c%20Acc:%20Off.%20Wino-bino(%2b)%20SR$^{offWZ}_{highETmiss}$-0j">AuxFig 12c Acc: Off. Wino-bino(+) SR$^{offWZ}_{highETmiss}$-0j</a> <li><a href="?table=AuxFig%2012d%20Eff:%20Off.%20Wino-bino(%2b)%20SR$^{offWZ}_{highETmiss}$-0j">AuxFig 12d Eff: Off. Wino-bino(+) SR$^{offWZ}_{highETmiss}$-0j</a> <li><a href="?table=AuxFig%2012e%20Acc:%20Off.%20Wino-bino(%2b)%20SR$^{offWZ}_{lowETmiss}$-nj">AuxFig 12e Acc: Off. Wino-bino(+) SR$^{offWZ}_{lowETmiss}$-nj</a> <li><a href="?table=AuxFig%2012f%20Eff:%20Off.%20Wino-bino(%2b)%20SR$^{offWZ}_{lowETmiss}$-nj">AuxFig 12f Eff: Off. Wino-bino(+) SR$^{offWZ}_{lowETmiss}$-nj</a> <li><a href="?table=AuxFig%2012g%20Acc:%20Off.%20Wino-bino(%2b)%20SR$^{offWZ}_{highETmiss}$-nj">AuxFig 12g Acc: Off. Wino-bino(+) SR$^{offWZ}_{highETmiss}$-nj</a> <li><a href="?table=AuxFig%2012h%20Eff:%20Off.%20Wino-bino(%2b)%20SR$^{offWZ}_{highETmiss}$-nj">AuxFig 12h Eff: Off. Wino-bino(+) SR$^{offWZ}_{highETmiss}$-nj</a> <li><a href="?table=AuxFig%2013a%20Acc:%20Off.%20Wino-bino(-)%20SR$^{offWZ}_{lowETmiss}$-0j">AuxFig 13a Acc: Off. Wino-bino(-) SR$^{offWZ}_{lowETmiss}$-0j</a> <li><a href="?table=AuxFig%2013b%20Eff:%20Off.%20Wino-bino(-)%20SR$^{offWZ}_{lowETmiss}$-0j">AuxFig 13b Eff: Off. Wino-bino(-) SR$^{offWZ}_{lowETmiss}$-0j</a> <li><a href="?table=AuxFig%2013c%20Acc:%20Off.%20Wino-bino(-)%20SR$^{offWZ}_{highETmiss}$-0j">AuxFig 13c Acc: Off. Wino-bino(-) SR$^{offWZ}_{highETmiss}$-0j</a> <li><a href="?table=AuxFig%2013d%20Eff:%20Off.%20Wino-bino(-)%20SR$^{offWZ}_{highETmiss}$-0j">AuxFig 13d Eff: Off. Wino-bino(-) SR$^{offWZ}_{highETmiss}$-0j</a> <li><a href="?table=AuxFig%2013e%20Acc:%20Off.%20Wino-bino(-)%20SR$^{offWZ}_{lowETmiss}$-nj">AuxFig 13e Acc: Off. Wino-bino(-) SR$^{offWZ}_{lowETmiss}$-nj</a> <li><a href="?table=AuxFig%2013f%20Eff:%20Off.%20Wino-bino(-)%20SR$^{offWZ}_{lowETmiss}$-nj">AuxFig 13f Eff: Off. Wino-bino(-) SR$^{offWZ}_{lowETmiss}$-nj</a> <li><a href="?table=AuxFig%2013g%20Acc:%20Off.%20Wino-bino(-)%20SR$^{offWZ}_{highETmiss}$-nj">AuxFig 13g Acc: Off. Wino-bino(-) SR$^{offWZ}_{highETmiss}$-nj</a> <li><a href="?table=AuxFig%2013h%20Eff:%20Off.%20Wino-bino(-)%20SR$^{offWZ}_{highETmiss}$-nj">AuxFig 13h Eff: Off. Wino-bino(-) SR$^{offWZ}_{highETmiss}$-nj</a> <li><a href="?table=AuxFig%2014a%20Acc:%20Off.%20Higgsino%20SR$^{offWZ}_{lowETmiss}$-0j">AuxFig 14a Acc: Off. Higgsino SR$^{offWZ}_{lowETmiss}$-0j</a> <li><a href="?table=AuxFig%2014b%20Eff:%20Off.%20Higgsino%20SR$^{offWZ}_{lowETmiss}$-0j">AuxFig 14b Eff: Off. Higgsino SR$^{offWZ}_{lowETmiss}$-0j</a> <li><a href="?table=AuxFig%2014c%20Acc:%20Off.%20Higgsino%20SR$^{offWZ}_{highETmiss}$-0j">AuxFig 14c Acc: Off. Higgsino SR$^{offWZ}_{highETmiss}$-0j</a> <li><a href="?table=AuxFig%2014d%20Eff:%20Off.%20Higgsino%20SR$^{offWZ}_{highETmiss}$-0j">AuxFig 14d Eff: Off. Higgsino SR$^{offWZ}_{highETmiss}$-0j</a> <li><a href="?table=AuxFig%2014e%20Acc:%20Off.%20Higgsino%20SR$^{offWZ}_{lowETmiss}$-nj">AuxFig 14e Acc: Off. Higgsino SR$^{offWZ}_{lowETmiss}$-nj</a> <li><a href="?table=AuxFig%2014f%20Eff:%20Off.%20Higgsino%20SR$^{offWZ}_{lowETmiss}$-nj">AuxFig 14f Eff: Off. Higgsino SR$^{offWZ}_{lowETmiss}$-nj</a> <li><a href="?table=AuxFig%2014g%20Acc:%20Off.%20Higgsino%20SR$^{offWZ}_{highETmiss}$-nj">AuxFig 14g Acc: Off. Higgsino SR$^{offWZ}_{highETmiss}$-nj</a> <li><a href="?table=AuxFig%2014h%20Eff:%20Off.%20Higgsino%20SR$^{offWZ}_{highETmiss}$-nj">AuxFig 14h Eff: Off. Higgsino SR$^{offWZ}_{highETmiss}$-nj</a> </ul>
This is the HEPData space for the ATLAS SUSY EWK three-lepton search. The full resolution figures can be found at https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/SUSY-2019-09/ The full statistical likelihoods have been provided for this analysis. They can be downloaded by clicking on the purple 'Resources' button above and selecting the 'Common Resources' category. <b>Region yields:</b> <ul display="inline-block"> <li><a href="?table=Tab%2012%20Onshell%20WZ%20Signal%20Region%20Yields%20Table">Tab 12 Onshell WZ Signal Region Yields Table</a> <li><a href="?table=Tab%2013%20Onshell%20Wh%20Signal%20Region%20Yields%20Table">Tab 13 Onshell Wh Signal Region Yields Table</a> <li><a href="?table=Tab%2014%20Offshell%20low-$E_{T}^{miss}$%20Signal%20Region%20Yields%20Table">Tab 14 Offshell low-$E_{T}^{miss}$ Signal Region Yields Table</a> <li><a href="?table=Tab%2015%20Offshell%20high-$E_{T}^{miss}$%20Signal%20Region%20Yields%20Table">Tab 15 Offshell high-$E_{T}^{miss}$ Signal Region Yields Table</a> <li><a href="?table=Tab%2020%20RJR%20Signal%20Region%20Yields%20Table">Tab 20 RJR Signal Region Yields Table</a> <li><a href="?table=Fig%204%20Onshell%20Control%20and%20Validation%20Region%20Yields">Fig 4 Onshell Control and Validation Region Yields</a> <li><a href="?table=Fig%208%20Offshell%20Control%20and%20Validation%20Region%20Yields">Fig 8 Offshell Control and Validation Region Yields</a> <li><a href="?table=Fig%2010%20Onshell%20WZ%20Signal%20Region%20Yields">Fig 10 Onshell WZ Signal Region Yields</a> <li><a href="?table=Fig%2011%20Onshell%20Wh%20Signal%20Region%20Yields">Fig 11 Onshell Wh Signal Region Yields</a> <li><a href="?table=Fig%2012%20Offshell%20Signal%20Region%20Yields">Fig 12 Offshell Signal Region Yields</a> <li><a href="?table=Fig%2018%20RJR%20Control%20and%20Validation%20Region%20Yields">Fig 18 RJR Control and Validation Region Yields</a> </ul> <b>Exclusion contours:</b> <ul display="inline-block"> <li><a href="?table=Fig%2016a%20WZ%20Exclusion:%20Wino-bino(%2b),%20Obs">Fig 16a WZ Exclusion: Wino-bino(+), Obs</a> <li><a href="?table=Fig%2016a%20WZ%20Exclusion:%20Wino-bino(%2b),%20Obs_Up">Fig 16a WZ Exclusion: Wino-bino(+), Obs_Up</a> <li><a href="?table=Fig%2016a%20WZ%20Exclusion:%20Wino-bino(%2b),%20Obs_Down">Fig 16a WZ Exclusion: Wino-bino(+), Obs_Down</a> <li><a href="?table=Fig%2016a%20WZ%20Exclusion:%20Wino-bino(%2b),%20Exp">Fig 16a WZ Exclusion: Wino-bino(+), Exp</a> <li><a href="?table=Fig%2016a%20WZ%20Exclusion:%20Wino-bino(%2b),%20Exp_Up">Fig 16a WZ Exclusion: Wino-bino(+), Exp_Up</a> <li><a href="?table=Fig%2016a%20WZ%20Exclusion:%20Wino-bino(%2b),%20Exp_Down">Fig 16a WZ Exclusion: Wino-bino(+), Exp_Down</a> <li><a href="?table=Fig%2016a%20WZ%20Exclusion:%20Wino-bino(%2b),%20compressed_Obs">Fig 16a WZ Exclusion: Wino-bino(+), compressed_Obs</a> <li><a href="?table=Fig%2016a%20WZ%20Exclusion:%20Wino-bino(%2b),%20compressed_Exp">Fig 16a WZ Exclusion: Wino-bino(+), compressed_Exp</a> <li><a href="?table=Fig%2016a%20WZ%20Exclusion:%20Wino-bino(%2b),%20offshell_Obs">Fig 16a WZ Exclusion: Wino-bino(+), offshell_Obs</a> <li><a href="?table=Fig%2016a%20WZ%20Exclusion:%20Wino-bino(%2b),%20offshell_Exp">Fig 16a WZ Exclusion: Wino-bino(+), offshell_Exp</a> <li><a href="?table=Fig%2016a%20WZ%20Exclusion:%20Wino-bino(%2b),%20onshell_Obs">Fig 16a WZ Exclusion: Wino-bino(+), onshell_Obs</a> <li><a href="?table=Fig%2016a%20WZ%20Exclusion:%20Wino-bino(%2b),%20onshell_Exp">Fig 16a WZ Exclusion: Wino-bino(+), onshell_Exp</a> <li><a href="?table=Fig%2016b%20WZ%20Exclusion:%20Wino-bino(%2b)%20($\Delta%20m$),%20Obs">Fig 16b WZ Exclusion: Wino-bino(+) ($\Delta m$), Obs</a> <li><a href="?table=Fig%2016b%20WZ%20Exclusion:%20Wino-bino(%2b)%20($\Delta%20m$),%20Obs_Up">Fig 16b WZ Exclusion: Wino-bino(+) ($\Delta m$), Obs_Up</a> <li><a href="?table=Fig%2016b%20WZ%20Exclusion:%20Wino-bino(%2b)%20($\Delta%20m$),%20Obs_Down">Fig 16b WZ Exclusion: Wino-bino(+) ($\Delta m$), Obs_Down</a> <li><a href="?table=Fig%2016b%20WZ%20Exclusion:%20Wino-bino(%2b)%20($\Delta%20m$),%20Exp">Fig 16b WZ Exclusion: Wino-bino(+) ($\Delta m$), Exp</a> <li><a href="?table=Fig%2016b%20WZ%20Exclusion:%20Wino-bino(%2b)%20($\Delta%20m$),%20Exp_Up">Fig 16b WZ Exclusion: Wino-bino(+) ($\Delta m$), Exp_Up</a> <li><a href="?table=Fig%2016b%20WZ%20Exclusion:%20Wino-bino(%2b)%20($\Delta%20m$),%20Exp_Down">Fig 16b WZ Exclusion: Wino-bino(+) ($\Delta m$), Exp_Down</a> <li><a href="?table=Fig%2016b%20WZ%20Exclusion:%20Wino-bino(%2b)%20($\Delta%20m$),%20compressed_Obs">Fig 16b WZ Exclusion: Wino-bino(+) ($\Delta m$), compressed_Obs</a> <li><a href="?table=Fig%2016b%20WZ%20Exclusion:%20Wino-bino(%2b)%20($\Delta%20m$),%20compressed_Exp">Fig 16b WZ Exclusion: Wino-bino(+) ($\Delta m$), compressed_Exp</a> <li><a href="?table=Fig%2016b%20WZ%20Exclusion:%20Wino-bino(%2b)%20($\Delta%20m$),%20offshell_Obs">Fig 16b WZ Exclusion: Wino-bino(+) ($\Delta m$), offshell_Obs</a> <li><a href="?table=Fig%2016b%20WZ%20Exclusion:%20Wino-bino(%2b)%20($\Delta%20m$),%20offshell_Exp">Fig 16b WZ Exclusion: Wino-bino(+) ($\Delta m$), offshell_Exp</a> <li><a href="?table=Fig%2016b%20WZ%20Exclusion:%20Wino-bino(%2b)%20($\Delta%20m$),%20onshell_Obs">Fig 16b WZ Exclusion: Wino-bino(+) ($\Delta m$), onshell_Obs</a> <li><a href="?table=Fig%2016b%20WZ%20Exclusion:%20Wino-bino(%2b)%20($\Delta%20m$),%20onshell_Exp">Fig 16b WZ Exclusion: Wino-bino(+) ($\Delta m$), onshell_Exp</a> <li><a href="?table=Fig%2016c%20WZ%20Exclusion:%20Wino-bino(-)%20($\Delta%20m$),%20Obs">Fig 16c WZ Exclusion: Wino-bino(-) ($\Delta m$), Obs</a> <li><a href="?table=Fig%2016c%20WZ%20Exclusion:%20Wino-bino(-)%20($\Delta%20m$),%20Obs_Up">Fig 16c WZ Exclusion: Wino-bino(-) ($\Delta m$), Obs_Up</a> <li><a href="?table=Fig%2016c%20WZ%20Exclusion:%20Wino-bino(-)%20($\Delta%20m$),%20Obs_Down">Fig 16c WZ Exclusion: Wino-bino(-) ($\Delta m$), Obs_Down</a> <li><a href="?table=Fig%2016c%20WZ%20Exclusion:%20Wino-bino(-)%20($\Delta%20m$),%20Exp">Fig 16c WZ Exclusion: Wino-bino(-) ($\Delta m$), Exp</a> <li><a href="?table=Fig%2016c%20WZ%20Exclusion:%20Wino-bino(-)%20($\Delta%20m$),%20Exp_Up">Fig 16c WZ Exclusion: Wino-bino(-) ($\Delta m$), Exp_Up</a> <li><a href="?table=Fig%2016c%20WZ%20Exclusion:%20Wino-bino(-)%20($\Delta%20m$),%20Exp_Down">Fig 16c WZ Exclusion: Wino-bino(-) ($\Delta m$), Exp_Down</a> <li><a href="?table=Fig%2016c%20WZ%20Exclusion:%20Wino-bino(-)%20($\Delta%20m$),%20compressed_Obs">Fig 16c WZ Exclusion: Wino-bino(-) ($\Delta m$), compressed_Obs</a> <li><a href="?table=Fig%2016c%20WZ%20Exclusion:%20Wino-bino(-)%20($\Delta%20m$),%20compressed_Exp">Fig 16c WZ Exclusion: Wino-bino(-) ($\Delta m$), compressed_Exp</a> <li><a href="?table=Fig%2016c%20WZ%20Exclusion:%20Wino-bino(-)%20($\Delta%20m$),%20offshell_Obs">Fig 16c WZ Exclusion: Wino-bino(-) ($\Delta m$), offshell_Obs</a> <li><a href="?table=Fig%2016c%20WZ%20Exclusion:%20Wino-bino(-)%20($\Delta%20m$),%20offshell_Exp">Fig 16c WZ Exclusion: Wino-bino(-) ($\Delta m$), offshell_Exp</a> <li><a href="?table=Fig%2016d%20WZ%20Exclusion:%20Higgsino%20($\Delta%20m$),%20Obs">Fig 16d WZ Exclusion: Higgsino ($\Delta m$), Obs</a> <li><a href="?table=Fig%2016d%20WZ%20Exclusion:%20Higgsino%20($\Delta%20m$),%20Obs_Up">Fig 16d WZ Exclusion: Higgsino ($\Delta m$), Obs_Up</a> <li><a href="?table=Fig%2016d%20WZ%20Exclusion:%20Higgsino%20($\Delta%20m$),%20Obs_Down">Fig 16d WZ Exclusion: Higgsino ($\Delta m$), Obs_Down</a> <li><a href="?table=Fig%2016d%20WZ%20Exclusion:%20Higgsino%20($\Delta%20m$),%20Exp">Fig 16d WZ Exclusion: Higgsino ($\Delta m$), Exp</a> <li><a href="?table=Fig%2016d%20WZ%20Exclusion:%20Higgsino%20($\Delta%20m$),%20Exp_Up">Fig 16d WZ Exclusion: Higgsino ($\Delta m$), Exp_Up</a> <li><a href="?table=Fig%2016d%20WZ%20Exclusion:%20Higgsino%20($\Delta%20m$),%20Exp_Down">Fig 16d WZ Exclusion: Higgsino ($\Delta m$), Exp_Down</a> <li><a href="?table=Fig%2016d%20WZ%20Exclusion:%20Higgsino%20($\Delta%20m$),%20compressed_Obs">Fig 16d WZ Exclusion: Higgsino ($\Delta m$), compressed_Obs</a> <li><a href="?table=Fig%2016d%20WZ%20Exclusion:%20Higgsino%20($\Delta%20m$),%20compressed_Exp">Fig 16d WZ Exclusion: Higgsino ($\Delta m$), compressed_Exp</a> <li><a href="?table=Fig%2016d%20WZ%20Exclusion:%20Higgsino%20($\Delta%20m$),%20offshell_Obs">Fig 16d WZ Exclusion: Higgsino ($\Delta m$), offshell_Obs</a> <li><a href="?table=Fig%2016d%20WZ%20Exclusion:%20Higgsino%20($\Delta%20m$),%20offshell_Exp">Fig 16d WZ Exclusion: Higgsino ($\Delta m$), offshell_Exp</a> <li><a href="?table=Fig%2017%20Wh%20Exclusion,%20Obs">Fig 17 Wh Exclusion, Obs</a> <li><a href="?table=Fig%2017%20Wh%20Exclusion,%20Obs_Up">Fig 17 Wh Exclusion, Obs_Up</a> <li><a href="?table=Fig%2017%20Wh%20Exclusion,%20Obs_Down">Fig 17 Wh Exclusion, Obs_Down</a> <li><a href="?table=Fig%2017%20Wh%20Exclusion,%20Exp">Fig 17 Wh Exclusion, Exp</a> <li><a href="?table=Fig%2017%20Wh%20Exclusion,%20Exp_Up">Fig 17 Wh Exclusion, Exp_Up</a> <li><a href="?table=Fig%2017%20Wh%20Exclusion,%20Exp_Down">Fig 17 Wh Exclusion, Exp_Down</a> </ul> <b>Upper limits:</b> <ul display="inline-block"> <li><a href="?table=AuxFig%208a%20WZ%20Excl.%20Upper%20Limit%20Obs.%20Wino-bino(%2b)%20($\Delta%20m$)">AuxFig 8a WZ Excl. Upper Limit Obs. Wino-bino(+) ($\Delta m$)</a> <li><a href="?table=AuxFig%208b%20WZ%20Excl.%20Upper%20Limit%20Exp.%20Wino-bino(%2b)%20($\Delta%20m$)">AuxFig 8b WZ Excl. Upper Limit Exp. Wino-bino(+) ($\Delta m$)</a> <li><a href="?table=AuxFig%208c%20WZ%20Excl.%20Upper%20Limit%20Obs.%20Wino-bino(%2b)%20($\Delta%20m$)">AuxFig 8c WZ Excl. Upper Limit Obs. Wino-bino(+) ($\Delta m$)</a> <li><a href="?table=AuxFig%208d%20WZ%20Excl.%20Upper%20Limit%20Exp.%20Wino-bino(%2b)%20($\Delta%20m$)">AuxFig 8d WZ Excl. Upper Limit Exp. Wino-bino(+) ($\Delta m$)</a> <li><a href="?table=AuxFig%208e%20WZ%20Excl.%20Upper%20Limit%20Obs.%20Wino-bino(-)%20($\Delta%20m$)">AuxFig 8e WZ Excl. Upper Limit Obs. Wino-bino(-) ($\Delta m$)</a> <li><a href="?table=AuxFig%208f%20WZ%20Excl.%20Upper%20Limit%20Exp.%20Wino-bino(-)%20($\Delta%20m$)">AuxFig 8f WZ Excl. Upper Limit Exp. Wino-bino(-) ($\Delta m$)</a> <li><a href="?table=AuxFig%208g%20WZ%20Excl.%20Upper%20Limit%20Obs.%20Higgsino%20($\Delta%20m$)">AuxFig 8g WZ Excl. Upper Limit Obs. Higgsino ($\Delta m$)</a> <li><a href="?table=AuxFig%208h%20WZ%20Excl.%20Upper%20Limit%20Exp.%20Higgsino%20($\Delta%20m$)">AuxFig 8h WZ Excl. Upper Limit Exp. Higgsino ($\Delta m$)</a> <li><a href="?table=AuxFig%209a%20Wh%20Excl.%20Upper%20Limit%20Obs.">AuxFig 9a Wh Excl. Upper Limit Obs.</a> <li><a href="?table=AuxFig%209b%20Wh%20Excl.%20Upper%20Limit%20Exp.">AuxFig 9b Wh Excl. Upper Limit Exp.</a> </ul> <b>Model-independent discovery fits:</b> <ul display="inline-block"> <li><a href="?table=Tab%2018%20Onshell%20Discovery%20Fit%20Table">Tab 18 Onshell Discovery Fit Table</a> <li><a href="?table=Tab%2019%20Offshell%20Discovery%20Fit%20Table">Tab 19 Offshell Discovery Fit Table</a> <li><a href="?table=Tab%2021%20RJR%20Discovery%20Fit%20Table">Tab 21 RJR Discovery Fit Table</a> </ul> <b>Kinematic distributions:</b> <ul display="inline-block"> <li><a href="?table=Fig%2013a%20SR$_{DFOS}^{Wh}$-1%20($\Delta%20R_{OS,%20near}$)">Fig 13a SR$_{DFOS}^{Wh}$-1 ($\Delta R_{OS, near}$)</a> <li><a href="?table=Fig%2013b%20SR$_{DFOS}^{Wh}$-2%20(3rd%20Lep.%20$p_{T}$)">Fig 13b SR$_{DFOS}^{Wh}$-2 (3rd Lep. $p_{T}$)</a> <li><a href="?table=Fig%2013c%20SR$_{0j}^{WZ}$%20($E_{T}^{miss}$)">Fig 13c SR$_{0j}^{WZ}$ ($E_{T}^{miss}$)</a> <li><a href="?table=Fig%2013d%20SR$_{0j}^{WZ}$%20($m_{T}$)">Fig 13d SR$_{0j}^{WZ}$ ($m_{T}$)</a> <li><a href="?table=Fig%2014a%20SR$^{offWZ}_{LowETmiss}$-0j%20($m_{T}^{minmll}$)">Fig 14a SR$^{offWZ}_{LowETmiss}$-0j ($m_{T}^{minmll}$)</a> <li><a href="?table=Fig%2014b%20SR$^{offWZ}_{LowETmiss}$-nj%20($m_{T}^{minmll}$)">Fig 14b SR$^{offWZ}_{LowETmiss}$-nj ($m_{T}^{minmll}$)</a> <li><a href="?table=Fig%2014c%20SR$^{offWZ}_{HighETmiss}$-0j%20($m_{T}^{minmll}$)">Fig 14c SR$^{offWZ}_{HighETmiss}$-0j ($m_{T}^{minmll}$)</a> <li><a href="?table=Fig%2014d%20SR$^{offWZ}_{HighETmiss}$-nj%20($p_T^l%20\div%20E_T^{miss}$)">Fig 14d SR$^{offWZ}_{HighETmiss}$-nj ($p_T^l \div E_T^{miss}$)</a> <li><a href="?table=Fig%2020a%20RJR%20SR3$\ell$-Low%20($p_{T}^{\ell%201}$)">Fig 20a RJR SR3$\ell$-Low ($p_{T}^{\ell 1}$)</a> <li><a href="?table=Fig%2020b%20RJR%20SR3$\ell$-Low%20($H_{3,1}^{PP}$)">Fig 20b RJR SR3$\ell$-Low ($H_{3,1}^{PP}$)</a> <li><a href="?table=Fig%2020c%20RJR%20SR3$\ell$-ISR%20($p_{T~ISR}^{CM}$)">Fig 20c RJR SR3$\ell$-ISR ($p_{T~ISR}^{CM}$)</a> <li><a href="?table=Fig%2020d%20RJR%20SR3$\ell$-ISR%20($R_{ISR}$)">Fig 20d RJR SR3$\ell$-ISR ($R_{ISR}$)</a> </ul> <b>Cutflows:</b> <ul display="inline-block"> <li><a href="?table=AuxTab%205%20Cutflow:%20Onshell%20WZ">AuxTab 5 Cutflow: Onshell WZ</a> <li><a href="?table=AuxTab%206%20Cutflow:%20Onshell%20Wh">AuxTab 6 Cutflow: Onshell Wh</a> <li><a href="?table=AuxTab%207%20Cutflow:%20Offshell%20Wino-bino(%2b)%20(250,235)">AuxTab 7 Cutflow: Offshell Wino-bino(+) (250,235)</a> <li><a href="?table=AuxTab%208%20Cutflow:%20Offshell%20Wino-bino(%2b)%20(125,85)">AuxTab 8 Cutflow: Offshell Wino-bino(+) (125,85)</a> <li><a href="?table=AuxTab%209%20Cutflow:%20Offshell%20Wino-bino(%2b)%20(250,170)">AuxTab 9 Cutflow: Offshell Wino-bino(+) (250,170)</a> <li><a href="?table=AuxTab%2010%20Cutflow:%20Offshell%20Wino-bino(-)%20(250,235)">AuxTab 10 Cutflow: Offshell Wino-bino(-) (250,235)</a> <li><a href="?table=AuxTab%2011%20Cutflow:%20Offshell%20Wino-bino(-)%20(125,85)">AuxTab 11 Cutflow: Offshell Wino-bino(-) (125,85)</a> <li><a href="?table=AuxTab%2012%20Cutflow:%20Offshell%20Wino-bino(-)%20(250,170)">AuxTab 12 Cutflow: Offshell Wino-bino(-) (250,170)</a> <li><a href="?table=AuxTab%2013%20Cutflow:%20Offshell%20Higgsino%20(120,100)">AuxTab 13 Cutflow: Offshell Higgsino (120,100)</a> <li><a href="?table=AuxTab%2014%20Cutflow:%20Offshell%20Higgsino%20(100,40)">AuxTab 14 Cutflow: Offshell Higgsino (100,40)</a> <li><a href="?table=AuxTab%2015%20Cutflow:%20Offshell%20Higgsino%20(185,125)">AuxTab 15 Cutflow: Offshell Higgsino (185,125)</a> </ul> <b>Acceptances and Efficiencies:</b> <ul display="inline-block"> <li><a href="?table=AuxFig%2010a%20Acc:%20Onshell%20SR$_{0j}^{WZ}$">AuxFig 10a Acc: Onshell SR$_{0j}^{WZ}$</a> <li><a href="?table=AuxFig%2010b%20Eff:%20Onshell%20SR$_{0j}^{WZ}$">AuxFig 10b Eff: Onshell SR$_{0j}^{WZ}$</a> <li><a href="?table=AuxFig%2010c%20Acc:%20Onshell%20SR$_{nj}^{WZ}$">AuxFig 10c Acc: Onshell SR$_{nj}^{WZ}$</a> <li><a href="?table=AuxFig%2010d%20Eff:%20Onshell%20SR$_{nj}^{WZ}$">AuxFig 10d Eff: Onshell SR$_{nj}^{WZ}$</a> <li><a href="?table=AuxFig%2011a%20Acc:%20Onshell%20SR$_{low-m_{ll}-0j}^{Wh}$">AuxFig 11a Acc: Onshell SR$_{low-m_{ll}-0j}^{Wh}$</a> <li><a href="?table=AuxFig%2011b%20Eff:%20Onshell%20SR$_{low-m_{ll}-0j}^{Wh}$">AuxFig 11b Eff: Onshell SR$_{low-m_{ll}-0j}^{Wh}$</a> <li><a href="?table=AuxFig%2011c%20Acc:%20Onshell%20SR$_{low-m_{ll}-nj}^{Wh}$">AuxFig 11c Acc: Onshell SR$_{low-m_{ll}-nj}^{Wh}$</a> <li><a href="?table=AuxFig%2011d%20Eff:%20Onshell%20SR$_{low-m_{ll}-nj}^{Wh}$">AuxFig 11d Eff: Onshell SR$_{low-m_{ll}-nj}^{Wh}$</a> <li><a href="?table=AuxFig%2011e%20Acc:%20Onshell%20SR$_{DFOS}^{Wh}$">AuxFig 11e Acc: Onshell SR$_{DFOS}^{Wh}$</a> <li><a href="?table=AuxFig%2011f%20Eff:%20Onshell%20SR$_{DFOS}^{Wh}$">AuxFig 11f Eff: Onshell SR$_{DFOS}^{Wh}$</a> <li><a href="?table=AuxFig%2012a%20Acc:%20Off.%20Wino-bino(%2b)%20SR$^{offWZ}_{lowETmiss}$-0j">AuxFig 12a Acc: Off. Wino-bino(+) SR$^{offWZ}_{lowETmiss}$-0j</a> <li><a href="?table=AuxFig%2012b%20Eff:%20Off.%20Wino-bino(%2b)%20SR$^{offWZ}_{lowETmiss}$-0j">AuxFig 12b Eff: Off. Wino-bino(+) SR$^{offWZ}_{lowETmiss}$-0j</a> <li><a href="?table=AuxFig%2012c%20Acc:%20Off.%20Wino-bino(%2b)%20SR$^{offWZ}_{lowETmiss}$-nj">AuxFig 12c Acc: Off. Wino-bino(+) SR$^{offWZ}_{lowETmiss}$-nj</a> <li><a href="?table=AuxFig%2012d%20Eff:%20Off.%20Wino-bino(%2b)%20SR$^{offWZ}_{lowETmiss}$-nj">AuxFig 12d Eff: Off. Wino-bino(+) SR$^{offWZ}_{lowETmiss}$-nj</a> <li><a href="?table=AuxFig%2012e%20Acc:%20Off.%20Wino-bino(%2b)%20SR$^{offWZ}_{highETmiss}$-0j">AuxFig 12e Acc: Off. Wino-bino(+) SR$^{offWZ}_{highETmiss}$-0j</a> <li><a href="?table=AuxFig%2012f%20Eff:%20Off.%20Wino-bino(%2b)%20SR$^{offWZ}_{highETmiss}$-0j">AuxFig 12f Eff: Off. Wino-bino(+) SR$^{offWZ}_{highETmiss}$-0j</a> <li><a href="?table=AuxFig%2012g%20Acc:%20Off.%20Wino-bino(%2b)%20SR$^{offWZ}_{highETmiss}$-nj">AuxFig 12g Acc: Off. Wino-bino(+) SR$^{offWZ}_{highETmiss}$-nj</a> <li><a href="?table=AuxFig%2012h%20Eff:%20Off.%20Wino-bino(%2b)%20SR$^{offWZ}_{highETmiss}$-nj">AuxFig 12h Eff: Off. Wino-bino(+) SR$^{offWZ}_{highETmiss}$-nj</a> <li><a href="?table=AuxFig%2013a%20Acc:%20Off.%20Wino-bino(-)%20SR$^{offWZ}_{lowETmiss}$-0j">AuxFig 13a Acc: Off. Wino-bino(-) SR$^{offWZ}_{lowETmiss}$-0j</a> <li><a href="?table=AuxFig%2013b%20Eff:%20Off.%20Wino-bino(-)%20SR$^{offWZ}_{lowETmiss}$-0j">AuxFig 13b Eff: Off. Wino-bino(-) SR$^{offWZ}_{lowETmiss}$-0j</a> <li><a href="?table=AuxFig%2013c%20Acc:%20Off.%20Wino-bino(-)%20SR$^{offWZ}_{lowETmiss}$-nj">AuxFig 13c Acc: Off. Wino-bino(-) SR$^{offWZ}_{lowETmiss}$-nj</a> <li><a href="?table=AuxFig%2013d%20Eff:%20Off.%20Wino-bino(-)%20SR$^{offWZ}_{lowETmiss}$-nj">AuxFig 13d Eff: Off. Wino-bino(-) SR$^{offWZ}_{lowETmiss}$-nj</a> <li><a href="?table=AuxFig%2013e%20Acc:%20Off.%20Wino-bino(-)%20SR$^{offWZ}_{highETmiss}$-0j">AuxFig 13e Acc: Off. Wino-bino(-) SR$^{offWZ}_{highETmiss}$-0j</a> <li><a href="?table=AuxFig%2013f%20Eff:%20Off.%20Wino-bino(-)%20SR$^{offWZ}_{highETmiss}$-0j">AuxFig 13f Eff: Off. Wino-bino(-) SR$^{offWZ}_{highETmiss}$-0j</a> <li><a href="?table=AuxFig%2013g%20Acc:%20Off.%20Wino-bino(-)%20SR$^{offWZ}_{highETmiss}$-nj">AuxFig 13g Acc: Off. Wino-bino(-) SR$^{offWZ}_{highETmiss}$-nj</a> <li><a href="?table=AuxFig%2013h%20Eff:%20Off.%20Wino-bino(-)%20SR$^{offWZ}_{highETmiss}$-nj">AuxFig 13h Eff: Off. Wino-bino(-) SR$^{offWZ}_{highETmiss}$-nj</a> <li><a href="?table=AuxFig%2014a%20Acc:%20Off.%20Higgsino%20SR$^{offWZ}_{lowETmiss}$-0j">AuxFig 14a Acc: Off. Higgsino SR$^{offWZ}_{lowETmiss}$-0j</a> <li><a href="?table=AuxFig%2014b%20Eff:%20Off.%20Higgsino%20SR$^{offWZ}_{lowETmiss}$-0j">AuxFig 14b Eff: Off. Higgsino SR$^{offWZ}_{lowETmiss}$-0j</a> <li><a href="?table=AuxFig%2014c%20Acc:%20Off.%20Higgsino%20SR$^{offWZ}_{lowETmiss}$-nj">AuxFig 14c Acc: Off. Higgsino SR$^{offWZ}_{lowETmiss}$-nj</a> <li><a href="?table=AuxFig%2014d%20Eff:%20Off.%20Higgsino%20SR$^{offWZ}_{lowETmiss}$-nj">AuxFig 14d Eff: Off. Higgsino SR$^{offWZ}_{lowETmiss}$-nj</a> <li><a href="?table=AuxFig%2014e%20Acc:%20Off.%20Higgsino%20SR$^{offWZ}_{highETmiss}$-0j">AuxFig 14e Acc: Off. Higgsino SR$^{offWZ}_{highETmiss}$-0j</a> <li><a href="?table=AuxFig%2014f%20Eff:%20Off.%20Higgsino%20SR$^{offWZ}_{highETmiss}$-0j">AuxFig 14f Eff: Off. Higgsino SR$^{offWZ}_{highETmiss}$-0j</a> <li><a href="?table=AuxFig%2014g%20Acc:%20Off.%20Higgsino%20SR$^{offWZ}_{highETmiss}$-nj">AuxFig 14g Acc: Off. Higgsino SR$^{offWZ}_{highETmiss}$-nj</a> <li><a href="?table=AuxFig%2014h%20Eff:%20Off.%20Higgsino%20SR$^{offWZ}_{highETmiss}$-nj">AuxFig 14h Eff: Off. Higgsino SR$^{offWZ}_{highETmiss}$-nj</a> </ul>
Comparison of the observed data and expected SM background yields in the CRs (pre-fit) and VRs (post-fit) of the onshell $W\!Z$ and $W\!h$ selections. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. The hatched band indicates the combined theoretical, experimental, and MC statistical uncertainties. The bottom panel shows the relative difference between the observed data and expected yields for the CRs and the significance of the difference for the VRs, calculated with the profile likelihood method from [169], adding a minus sign if the yield is below the prediction.
Comparison of the observed data and expected SM background yields in the CRs (pre-fit) and VRs (post-fit) of the onshell $W\!Z$ and $W\!h$ selections. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. The hatched band indicates the combined theoretical, experimental, and MC statistical uncertainties. The bottom panel shows the relative difference between the observed data and expected yields for the CRs and the significance of the difference for the VRs, calculated with the profile likelihood method from [169], adding a minus sign if the yield is below the prediction.
Comparison of the observed data and expected SM background yields in the CRs and VRs of the offshell $W\!Z$ selection. The SM prediction is taken from the background-only fit. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. The hatched band indicates the combined theoretical, experimental, and MC statistical uncertainties. The bottom panel shows the significance of the difference between the observed and expected yields, calculated with the profile likelihood method from [169], adding a minus sign if the yield is below the prediction.
Comparison of the observed data and expected SM background yields in the CRs and VRs of the offshell $W\!Z$ selection. The SM prediction is taken from the background-only fit. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. The hatched band indicates the combined theoretical, experimental, and MC statistical uncertainties. The bottom panel shows the significance of the difference between the observed and expected yields, calculated with the profile likelihood method from [169], adding a minus sign if the yield is below the prediction.
Observed and expected yields after the background-only fit in the SRs for the onshell $W\!Z$ selection. The normalization factors of the $W\!Z$ sample are extracted separately for the 0j, low-H<sub>T</sub> and high-H<sub>T</sub> regions, and are treated separately in the combined fit. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. Combined statistical and systematic uncertainties are presented.
Observed and expected yields after the background-only fit in the SRs for the onshell $W\!Z$ selection. The normalization factors of the $W\!Z$ sample are extracted separately for the 0j, low-H<sub>T</sub> and high-H<sub>T</sub> regions, and are treated separately in the combined fit. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. Combined statistical and systematic uncertainties are presented.
Observed and expected yields after the background-only fit in the SRs for the $W\!h$ selection. The normalization factors of the $W\!Z$ sample are extracted separately for the 0j, low-H<sub>T</sub> and high-H<sub>T</sub> regions, and are treated separately in the combined fit. The "Others" category contains the single-top, WW, tt̄+X and rare top processes. Combined statistical and systematic uncertainties are presented.
Observed and expected yields after the background-only fit in the SRs for the $W\!h$ selection. The normalization factors of the $W\!Z$ sample are extracted separately for the 0j, low-H<sub>T</sub> and high-H<sub>T</sub> regions, and are treated separately in the combined fit. The "Others" category contains the single-top, WW, tt̄+X and rare top processes. Combined statistical and systematic uncertainties are presented.
Comparison of the observed data and expected SM background yields in the SRs of the onshell $W\!Z$ selection. The SM prediction is taken from the background-only fit. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. The hatched band indicates the combined theoretical, experimental, and MC statistical uncertainties. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the significance of the difference between the observed and expected yields, calculated with the profile likelihood method from [169], adding a minus sign if the yield is below the prediction.
Comparison of the observed data and expected SM background yields in the SRs of the onshell $W\!Z$ selection. The SM prediction is taken from the background-only fit. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. The hatched band indicates the combined theoretical, experimental, and MC statistical uncertainties. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the significance of the difference between the observed and expected yields, calculated with the profile likelihood method from [169], adding a minus sign if the yield is below the prediction.
Comparison of the observed data and expected SM background yields in the SRs of the $W\!h$ selection. The SM prediction is taken from the background-only fit. The "Others" category contains the single-top, WW, tt̄+X and rare top processes. The hatched band indicates the combined theoretical, experimental, and MC statistical uncertainties. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!h$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the significance of the difference between the observed and expected yields, calculated with the profile likelihood method from [169], adding a minus sign if the yield is below the prediction.
Comparison of the observed data and expected SM background yields in the SRs of the $W\!h$ selection. The SM prediction is taken from the background-only fit. The "Others" category contains the single-top, WW, tt̄+X and rare top processes. The hatched band indicates the combined theoretical, experimental, and MC statistical uncertainties. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!h$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the significance of the difference between the observed and expected yields, calculated with the profile likelihood method from [169], adding a minus sign if the yield is below the prediction.
Observed and expected yields after the background-only fit in SR<sup>offWZ</sup><sub>lowETmiss</sub>. The normalization factors of the $W\!Z$ sample extracted separately for 0j and nj, and are treated separately in the combined fit. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. Combined statistical and systematic uncertainties are presented.
Observed and expected yields after the background-only fit in SR<sup>offWZ</sup><sub>lowETmiss</sub>. The normalization factors of the $W\!Z$ sample extracted separately for 0j and nj, and are treated separately in the combined fit. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. Combined statistical and systematic uncertainties are presented.
Observed and expected yields after the background-only fit in SR<sup>offWZ</sup><sub>highETmiss</sub>. The normalization factors of the $W\!Z$ sample extracted separately for 0j and nj, and are treated separately in the combined fit. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. Combined statistical and systematic uncertainties are presented.
Observed and expected yields after the background-only fit in SR<sup>offWZ</sup><sub>highETmiss</sub>. The normalization factors of the $W\!Z$ sample extracted separately for 0j and nj, and are treated separately in the combined fit. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. Combined statistical and systematic uncertainties are presented.
Comparison of the observed data and expected SM background yields in the SRs of the offshell $W\!Z$ selection. The SM prediction is taken from the background-only fit. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. The hatched band indicates the combined theoretical, experimental, and MC statistical uncertainties. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W^{*}\!Z^{*}$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the significance of the difference between the observed and expected yields, calculated with the profile likelihood method from [169], adding a minus sign if the yield is below the prediction.
Comparison of the observed data and expected SM background yields in the SRs of the offshell $W\!Z$ selection. The SM prediction is taken from the background-only fit. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. The hatched band indicates the combined theoretical, experimental, and MC statistical uncertainties. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W^{*}\!Z^{*}$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the significance of the difference between the observed and expected yields, calculated with the profile likelihood method from [169], adding a minus sign if the yield is below the prediction.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the onshell $W\!Z$ and $W\!h$ selections. The figure shows (a) the ΔR<sub>OS,near</sub> distribution in SR<sup>Wh</sup><sub>DF</sub>-1, (b) the 3rd leading lepton p<sub>T</sub> in SR<sup>Wh</sup><sub>DF</sub>-2, and the (c) E<sub>T</sub><sup>miss</sup> and (d) m<sub>T</sub> distributions in SR<sup>WZ</sup><sub>0j</sub> (with all SR-i bins of SR<sup>WZ</sup><sub>0j</sub> summed up). The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes, except in the top panels, where triboson and Higgs production contributions are shown separately, and tt̄+X is merged into Others. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$/$W\!h$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the onshell $W\!Z$ and $W\!h$ selections. The figure shows (a) the ΔR<sub>OS,near</sub> distribution in SR<sup>Wh</sup><sub>DF</sub>-1, (b) the 3rd leading lepton p<sub>T</sub> in SR<sup>Wh</sup><sub>DF</sub>-2, and the (c) E<sub>T</sub><sup>miss</sup> and (d) m<sub>T</sub> distributions in SR<sup>WZ</sup><sub>0j</sub> (with all SR-i bins of SR<sup>WZ</sup><sub>0j</sub> summed up). The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes, except in the top panels, where triboson and Higgs production contributions are shown separately, and tt̄+X is merged into Others. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$/$W\!h$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the onshell $W\!Z$ and $W\!h$ selections. The figure shows (a) the ΔR<sub>OS,near</sub> distribution in SR<sup>Wh</sup><sub>DF</sub>-1, (b) the 3rd leading lepton p<sub>T</sub> in SR<sup>Wh</sup><sub>DF</sub>-2, and the (c) E<sub>T</sub><sup>miss</sup> and (d) m<sub>T</sub> distributions in SR<sup>WZ</sup><sub>0j</sub> (with all SR-i bins of SR<sup>WZ</sup><sub>0j</sub> summed up). The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes, except in the top panels, where triboson and Higgs production contributions are shown separately, and tt̄+X is merged into Others. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$/$W\!h$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the onshell $W\!Z$ and $W\!h$ selections. The figure shows (a) the ΔR<sub>OS,near</sub> distribution in SR<sup>Wh</sup><sub>DF</sub>-1, (b) the 3rd leading lepton p<sub>T</sub> in SR<sup>Wh</sup><sub>DF</sub>-2, and the (c) E<sub>T</sub><sup>miss</sup> and (d) m<sub>T</sub> distributions in SR<sup>WZ</sup><sub>0j</sub> (with all SR-i bins of SR<sup>WZ</sup><sub>0j</sub> summed up). The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes, except in the top panels, where triboson and Higgs production contributions are shown separately, and tt̄+X is merged into Others. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$/$W\!h$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the onshell $W\!Z$ and $W\!h$ selections. The figure shows (a) the ΔR<sub>OS,near</sub> distribution in SR<sup>Wh</sup><sub>DF</sub>-1, (b) the 3rd leading lepton p<sub>T</sub> in SR<sup>Wh</sup><sub>DF</sub>-2, and the (c) E<sub>T</sub><sup>miss</sup> and (d) m<sub>T</sub> distributions in SR<sup>WZ</sup><sub>0j</sub> (with all SR-i bins of SR<sup>WZ</sup><sub>0j</sub> summed up). The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes, except in the top panels, where triboson and Higgs production contributions are shown separately, and tt̄+X is merged into Others. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$/$W\!h$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the onshell $W\!Z$ and $W\!h$ selections. The figure shows (a) the ΔR<sub>OS,near</sub> distribution in SR<sup>Wh</sup><sub>DF</sub>-1, (b) the 3rd leading lepton p<sub>T</sub> in SR<sup>Wh</sup><sub>DF</sub>-2, and the (c) E<sub>T</sub><sup>miss</sup> and (d) m<sub>T</sub> distributions in SR<sup>WZ</sup><sub>0j</sub> (with all SR-i bins of SR<sup>WZ</sup><sub>0j</sub> summed up). The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes, except in the top panels, where triboson and Higgs production contributions are shown separately, and tt̄+X is merged into Others. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$/$W\!h$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the onshell $W\!Z$ and $W\!h$ selections. The figure shows (a) the ΔR<sub>OS,near</sub> distribution in SR<sup>Wh</sup><sub>DF</sub>-1, (b) the 3rd leading lepton p<sub>T</sub> in SR<sup>Wh</sup><sub>DF</sub>-2, and the (c) E<sub>T</sub><sup>miss</sup> and (d) m<sub>T</sub> distributions in SR<sup>WZ</sup><sub>0j</sub> (with all SR-i bins of SR<sup>WZ</sup><sub>0j</sub> summed up). The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes, except in the top panels, where triboson and Higgs production contributions are shown separately, and tt̄+X is merged into Others. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$/$W\!h$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the onshell $W\!Z$ and $W\!h$ selections. The figure shows (a) the ΔR<sub>OS,near</sub> distribution in SR<sup>Wh</sup><sub>DF</sub>-1, (b) the 3rd leading lepton p<sub>T</sub> in SR<sup>Wh</sup><sub>DF</sub>-2, and the (c) E<sub>T</sub><sup>miss</sup> and (d) m<sub>T</sub> distributions in SR<sup>WZ</sup><sub>0j</sub> (with all SR-i bins of SR<sup>WZ</sup><sub>0j</sub> summed up). The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes, except in the top panels, where triboson and Higgs production contributions are shown separately, and tt̄+X is merged into Others. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$/$W\!h$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the offshell $W\!Z$ selection. The figure shows the m<sub>T</sub><sup>m<sub>ll</sub>min</sup> distribution in (a) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj and (c) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and the |p<sub>T</sub><sup>lep</sup>|/E<sub>T</sub><sup>miss</sup> distribution in (d) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj. The contributing m<sub>ll</sub><sup>min</sup> mass bins within each SR<sup>offWZ</sup> category are summed together. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the offshell $W\!Z$ selection. The figure shows the m<sub>T</sub><sup>m<sub>ll</sub>min</sup> distribution in (a) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj and (c) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and the |p<sub>T</sub><sup>lep</sup>|/E<sub>T</sub><sup>miss</sup> distribution in (d) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj. The contributing m<sub>ll</sub><sup>min</sup> mass bins within each SR<sup>offWZ</sup> category are summed together. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the offshell $W\!Z$ selection. The figure shows the m<sub>T</sub><sup>m<sub>ll</sub>min</sup> distribution in (a) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj and (c) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and the |p<sub>T</sub><sup>lep</sup>|/E<sub>T</sub><sup>miss</sup> distribution in (d) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj. The contributing m<sub>ll</sub><sup>min</sup> mass bins within each SR<sup>offWZ</sup> category are summed together. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the offshell $W\!Z$ selection. The figure shows the m<sub>T</sub><sup>m<sub>ll</sub>min</sup> distribution in (a) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj and (c) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and the |p<sub>T</sub><sup>lep</sup>|/E<sub>T</sub><sup>miss</sup> distribution in (d) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj. The contributing m<sub>ll</sub><sup>min</sup> mass bins within each SR<sup>offWZ</sup> category are summed together. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the offshell $W\!Z$ selection. The figure shows the m<sub>T</sub><sup>m<sub>ll</sub>min</sup> distribution in (a) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj and (c) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and the |p<sub>T</sub><sup>lep</sup>|/E<sub>T</sub><sup>miss</sup> distribution in (d) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj. The contributing m<sub>ll</sub><sup>min</sup> mass bins within each SR<sup>offWZ</sup> category are summed together. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the offshell $W\!Z$ selection. The figure shows the m<sub>T</sub><sup>m<sub>ll</sub>min</sup> distribution in (a) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj and (c) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and the |p<sub>T</sub><sup>lep</sup>|/E<sub>T</sub><sup>miss</sup> distribution in (d) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj. The contributing m<sub>ll</sub><sup>min</sup> mass bins within each SR<sup>offWZ</sup> category are summed together. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the offshell $W\!Z$ selection. The figure shows the m<sub>T</sub><sup>m<sub>ll</sub>min</sup> distribution in (a) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj and (c) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and the |p<sub>T</sub><sup>lep</sup>|/E<sub>T</sub><sup>miss</sup> distribution in (d) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj. The contributing m<sub>ll</sub><sup>min</sup> mass bins within each SR<sup>offWZ</sup> category are summed together. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the offshell $W\!Z$ selection. The figure shows the m<sub>T</sub><sup>m<sub>ll</sub>min</sup> distribution in (a) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj and (c) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and the |p<sub>T</sub><sup>lep</sup>|/E<sub>T</sub><sup>miss</sup> distribution in (d) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj. The contributing m<sub>ll</sub><sup>min</sup> mass bins within each SR<sup>offWZ</sup> category are summed together. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Observed (N<sub>obs</sub>) yields after the discovery-fit and expected (N<sub>exp</sub>) after the background-only fit, for the inclusive SRs of the onshell $W\!Z$ and $W\!h$ selections. The third and fourth column list the 95 CL upper limits on the visible cross-section (σ<sub>vis</sub><sup>95</sup>) and on the number of signal events (S<sub>obs</sub><sup>95</sup>). The fifth column (S<sub>exp</sub><sup>95</sup>) shows the 95 CL upper limit on the number of signal events, given the expected number (and ± 1σ excursions on the expectation) of background events. The last two columns indicate the CLb value, i.e. the confidence level observed for the background-only hypothesis, and the discovery p-value (p(s = 0)). If the observed yield is below the expected yield, the p-value is capped at 0.5.
Observed (N<sub>obs</sub>) yields after the discovery-fit and expected (N<sub>exp</sub>) after the background-only fit, for the inclusive SRs of the onshell $W\!Z$ and $W\!h$ selections. The third and fourth column list the 95 CL upper limits on the visible cross-section (σ<sub>vis</sub><sup>95</sup>) and on the number of signal events (S<sub>obs</sub><sup>95</sup>). The fifth column (S<sub>exp</sub><sup>95</sup>) shows the 95 CL upper limit on the number of signal events, given the expected number (and ± 1σ excursions on the expectation) of background events. The last two columns indicate the CLb value, i.e. the confidence level observed for the background-only hypothesis, and the discovery p-value (p(s = 0)). If the observed yield is below the expected yield, the p-value is capped at 0.5.
Observed (N<sub>obs</sub>) yields after the discovery-fit and expected (N<sub>exp</sub>) after the background-only fit, for the inclusive SRs of the offshell $W\!Z$ selection. The third and fourth column list the 95 CL upper limits on the visible cross section (σ<sub>vis</sub><sup>95</sup>) and on the number of signal events (S<sub>obs</sub><sup>95</sup>). The fifth column (S<sub>exp</sub><sup>95</sup>) shows the 95 CL upper limit on the number of signal events, given the expected number (and ± 1σ excursions on the expectation) of background events. The last two columns indicate the CLb value, i.e. the confidence level observed for the background-only hypothesis, and the discovery p-value (p(s = 0)). If the observed yield is below the expected yield, the p-value is capped at 0.5.
Observed (N<sub>obs</sub>) yields after the discovery-fit and expected (N<sub>exp</sub>) after the background-only fit, for the inclusive SRs of the offshell $W\!Z$ selection. The third and fourth column list the 95 CL upper limits on the visible cross section (σ<sub>vis</sub><sup>95</sup>) and on the number of signal events (S<sub>obs</sub><sup>95</sup>). The fifth column (S<sub>exp</sub><sup>95</sup>) shows the 95 CL upper limit on the number of signal events, given the expected number (and ± 1σ excursions on the expectation) of background events. The last two columns indicate the CLb value, i.e. the confidence level observed for the background-only hypothesis, and the discovery p-value (p(s = 0)). If the observed yield is below the expected yield, the p-value is capped at 0.5.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!h$med in the wino/bino (+) scenario, calculated using the $W\!h$ SRs and projected onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>{exp}</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties.
Exclusion limits obtained for the $W\!h$med in the wino/bino (+) scenario, calculated using the $W\!h$ SRs and projected onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>{exp}</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties.
Exclusion limits obtained for the $W\!h$med in the wino/bino (+) scenario, calculated using the $W\!h$ SRs and projected onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>{exp}</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties.
Exclusion limits obtained for the $W\!h$med in the wino/bino (+) scenario, calculated using the $W\!h$ SRs and projected onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>{exp}</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties.
Exclusion limits obtained for the $W\!h$med in the wino/bino (+) scenario, calculated using the $W\!h$ SRs and projected onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>{exp}</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties.
Exclusion limits obtained for the $W\!h$med in the wino/bino (+) scenario, calculated using the $W\!h$ SRs and projected onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>{exp}</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties.
Exclusion limits obtained for the $W\!h$med in the wino/bino (+) scenario, calculated using the $W\!h$ SRs and projected onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>{exp}</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties.
Exclusion limits obtained for the $W\!h$med in the wino/bino (+) scenario, calculated using the $W\!h$ SRs and projected onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>{exp}</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties.
Exclusion limits obtained for the $W\!h$med in the wino/bino (+) scenario, calculated using the $W\!h$ SRs and projected onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>{exp}</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties.
Exclusion limits obtained for the $W\!h$med in the wino/bino (+) scenario, calculated using the $W\!h$ SRs and projected onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>{exp}</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties.
Exclusion limits obtained for the $W\!h$med in the wino/bino (+) scenario, calculated using the $W\!h$ SRs and projected onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>{exp}</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties.
Exclusion limits obtained for the $W\!h$med in the wino/bino (+) scenario, calculated using the $W\!h$ SRs and projected onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>{exp}</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties.
Comparison of the observed data and expected SM background yields in the CRs and VRs of the RJR selection. The SM prediction is taken from the background-only fit. The "FNP leptons" category contains backgrounds from tt̄, tW, WW and Z+jets processes. The "Others" category contains backgrounds from Higgs and rare top processes. The hatched band indicates the combined theoretical, experimental, and MC statistical uncertainties. The bottom panel shows the significance of the difference between the observed and expected yields, calculated with the profile likelihood method from [169], adding a minus sign if the yield is below the prediction.
Comparison of the observed data and expected SM background yields in the CRs and VRs of the RJR selection. The SM prediction is taken from the background-only fit. The "FNP leptons" category contains backgrounds from tt̄, tW, WW and Z+jets processes. The "Others" category contains backgrounds from Higgs and rare top processes. The hatched band indicates the combined theoretical, experimental, and MC statistical uncertainties. The bottom panel shows the significance of the difference between the observed and expected yields, calculated with the profile likelihood method from [169], adding a minus sign if the yield is below the prediction.
Observed and expected yields after the background-only fit in the SRs for the RJR selection. The "FNP leptons" category contains backgrounds from tt̄, tW, WW and Z+jets processes. The "Others" category contains backgrounds from Higgs and rare top processes. Combined statistical and systematic uncertainties are presented.
Observed and expected yields after the background-only fit in the SRs for the RJR selection. The "FNP leptons" category contains backgrounds from tt̄, tW, WW and Z+jets processes. The "Others" category contains backgrounds from Higgs and rare top processes. Combined statistical and systematic uncertainties are presented.
Example of kinematic distributions after the background-only fit, showing the data and the post-fit expected background, in regions of the RJR selection. The figure shows the (a) p<sub>T</sub><sup>ℓ<sub>1</sub></sup> and (b) H<sup>PP</sup><sub>3,1</sub> distributions in SR3ℓ-Low, and the (c) p<sup>CM</sup><sub>T ISR</sub> and (d) R<sub>ISR</sub> distributions in SR3ℓ-ISR. The last bin includes overflow. The "FNP leptons" category contains backgrounds from tt̄, tW, WW and Z+jets processes. The "Others" category contains backgrounds from Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Example of kinematic distributions after the background-only fit, showing the data and the post-fit expected background, in regions of the RJR selection. The figure shows the (a) p<sub>T</sub><sup>ℓ<sub>1</sub></sup> and (b) H<sup>PP</sup><sub>3,1</sub> distributions in SR3ℓ-Low, and the (c) p<sup>CM</sup><sub>T ISR</sub> and (d) R<sub>ISR</sub> distributions in SR3ℓ-ISR. The last bin includes overflow. The "FNP leptons" category contains backgrounds from tt̄, tW, WW and Z+jets processes. The "Others" category contains backgrounds from Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Example of kinematic distributions after the background-only fit, showing the data and the post-fit expected background, in regions of the RJR selection. The figure shows the (a) p<sub>T</sub><sup>ℓ<sub>1</sub></sup> and (b) H<sup>PP</sup><sub>3,1</sub> distributions in SR3ℓ-Low, and the (c) p<sup>CM</sup><sub>T ISR</sub> and (d) R<sub>ISR</sub> distributions in SR3ℓ-ISR. The last bin includes overflow. The "FNP leptons" category contains backgrounds from tt̄, tW, WW and Z+jets processes. The "Others" category contains backgrounds from Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Example of kinematic distributions after the background-only fit, showing the data and the post-fit expected background, in regions of the RJR selection. The figure shows the (a) p<sub>T</sub><sup>ℓ<sub>1</sub></sup> and (b) H<sup>PP</sup><sub>3,1</sub> distributions in SR3ℓ-Low, and the (c) p<sup>CM</sup><sub>T ISR</sub> and (d) R<sub>ISR</sub> distributions in SR3ℓ-ISR. The last bin includes overflow. The "FNP leptons" category contains backgrounds from tt̄, tW, WW and Z+jets processes. The "Others" category contains backgrounds from Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Example of kinematic distributions after the background-only fit, showing the data and the post-fit expected background, in regions of the RJR selection. The figure shows the (a) p<sub>T</sub><sup>ℓ<sub>1</sub></sup> and (b) H<sup>PP</sup><sub>3,1</sub> distributions in SR3ℓ-Low, and the (c) p<sup>CM</sup><sub>T ISR</sub> and (d) R<sub>ISR</sub> distributions in SR3ℓ-ISR. The last bin includes overflow. The "FNP leptons" category contains backgrounds from tt̄, tW, WW and Z+jets processes. The "Others" category contains backgrounds from Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Example of kinematic distributions after the background-only fit, showing the data and the post-fit expected background, in regions of the RJR selection. The figure shows the (a) p<sub>T</sub><sup>ℓ<sub>1</sub></sup> and (b) H<sup>PP</sup><sub>3,1</sub> distributions in SR3ℓ-Low, and the (c) p<sup>CM</sup><sub>T ISR</sub> and (d) R<sub>ISR</sub> distributions in SR3ℓ-ISR. The last bin includes overflow. The "FNP leptons" category contains backgrounds from tt̄, tW, WW and Z+jets processes. The "Others" category contains backgrounds from Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Example of kinematic distributions after the background-only fit, showing the data and the post-fit expected background, in regions of the RJR selection. The figure shows the (a) p<sub>T</sub><sup>ℓ<sub>1</sub></sup> and (b) H<sup>PP</sup><sub>3,1</sub> distributions in SR3ℓ-Low, and the (c) p<sup>CM</sup><sub>T ISR</sub> and (d) R<sub>ISR</sub> distributions in SR3ℓ-ISR. The last bin includes overflow. The "FNP leptons" category contains backgrounds from tt̄, tW, WW and Z+jets processes. The "Others" category contains backgrounds from Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Example of kinematic distributions after the background-only fit, showing the data and the post-fit expected background, in regions of the RJR selection. The figure shows the (a) p<sub>T</sub><sup>ℓ<sub>1</sub></sup> and (b) H<sup>PP</sup><sub>3,1</sub> distributions in SR3ℓ-Low, and the (c) p<sup>CM</sup><sub>T ISR</sub> and (d) R<sub>ISR</sub> distributions in SR3ℓ-ISR. The last bin includes overflow. The "FNP leptons" category contains backgrounds from tt̄, tW, WW and Z+jets processes. The "Others" category contains backgrounds from Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
{Results of the discovery-fit for the SRs of the RJR selection, calculated using pseudo-experiments.} The first and second column list the 95 CL upper limits on the visible cross section (σ<sub>vis</sub><sup>95</sup>) and on the number of signal events (S<sub>obs</sub><sup>95</sup>). The third column (S<sub>exp</sub><sup>95</sup>) shows the 95 CL upper limit on the number of signal events, given the expected number (and ± 1σ excursions on the expectation) of background events. The last two columns indicate the CLb value, i.e. the confidence level observed for the background-only hypothesis, and the discovery p-value (p(s = 0)). If the observed yield is below the expected yield, the p-value is capped at 0.5. vspace{0.5em}
{Results of the discovery-fit for the SRs of the RJR selection, calculated using pseudo-experiments.} The first and second column list the 95 CL upper limits on the visible cross section (σ<sub>vis</sub><sup>95</sup>) and on the number of signal events (S<sub>obs</sub><sup>95</sup>). The third column (S<sub>exp</sub><sup>95</sup>) shows the 95 CL upper limit on the number of signal events, given the expected number (and ± 1σ excursions on the expectation) of background events. The last two columns indicate the CLb value, i.e. the confidence level observed for the background-only hypothesis, and the discovery p-value (p(s = 0)). If the observed yield is below the expected yield, the p-value is capped at 0.5. vspace{0.5em}
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!h$-mediated model, for the wino/bino (+) scenario, as in Figure 17. The black numbers represent the observed (a,c,e,g) and expected (b,d,f,h) upper cross-section limits.
Exclusion limits obtained for the $W\!h$-mediated model, for the wino/bino (+) scenario, as in Figure 17. The black numbers represent the observed (a,c,e,g) and expected (b,d,f,h) upper cross-section limits.
Exclusion limits obtained for the $W\!h$-mediated model, for the wino/bino (+) scenario, as in Figure 17. The black numbers represent the observed (a,c,e,g) and expected (b,d,f,h) upper cross-section limits.
Exclusion limits obtained for the $W\!h$-mediated model, for the wino/bino (+) scenario, as in Figure 17. The black numbers represent the observed (a,c,e,g) and expected (b,d,f,h) upper cross-section limits.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c) truth-level acceptances and (b,d) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>WZ</sup><sub>0j</sub>, (c,d) SR<sup>WZ</sup><sub>nj</sub> regions of the onshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c) truth-level acceptances and (b,d) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>WZ</sup><sub>0j</sub>, (c,d) SR<sup>WZ</sup><sub>nj</sub> regions of the onshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c) truth-level acceptances and (b,d) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>WZ</sup><sub>0j</sub>, (c,d) SR<sup>WZ</sup><sub>nj</sub> regions of the onshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c) truth-level acceptances and (b,d) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>WZ</sup><sub>0j</sub>, (c,d) SR<sup>WZ</sup><sub>nj</sub> regions of the onshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c) truth-level acceptances and (b,d) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>WZ</sup><sub>0j</sub>, (c,d) SR<sup>WZ</sup><sub>nj</sub> regions of the onshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c) truth-level acceptances and (b,d) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>WZ</sup><sub>0j</sub>, (c,d) SR<sup>WZ</sup><sub>nj</sub> regions of the onshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c) truth-level acceptances and (b,d) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>WZ</sup><sub>0j</sub>, (c,d) SR<sup>WZ</sup><sub>nj</sub> regions of the onshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c) truth-level acceptances and (b,d) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>WZ</sup><sub>0j</sub>, (c,d) SR<sup>WZ</sup><sub>nj</sub> regions of the onshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e) truth-level acceptances and (b,d,f) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-0j</sub>, (c,d) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-nj</sub>, and (e,f) SR<sup>Wh</sup><sub>DF</sub> regions of the $W\!h$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e) truth-level acceptances and (b,d,f) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-0j</sub>, (c,d) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-nj</sub>, and (e,f) SR<sup>Wh</sup><sub>DF</sub> regions of the $W\!h$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e) truth-level acceptances and (b,d,f) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-0j</sub>, (c,d) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-nj</sub>, and (e,f) SR<sup>Wh</sup><sub>DF</sub> regions of the $W\!h$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e) truth-level acceptances and (b,d,f) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-0j</sub>, (c,d) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-nj</sub>, and (e,f) SR<sup>Wh</sup><sub>DF</sub> regions of the $W\!h$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e) truth-level acceptances and (b,d,f) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-0j</sub>, (c,d) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-nj</sub>, and (e,f) SR<sup>Wh</sup><sub>DF</sub> regions of the $W\!h$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e) truth-level acceptances and (b,d,f) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-0j</sub>, (c,d) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-nj</sub>, and (e,f) SR<sup>Wh</sup><sub>DF</sub> regions of the $W\!h$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e) truth-level acceptances and (b,d,f) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-0j</sub>, (c,d) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-nj</sub>, and (e,f) SR<sup>Wh</sup><sub>DF</sub> regions of the $W\!h$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e) truth-level acceptances and (b,d,f) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-0j</sub>, (c,d) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-nj</sub>, and (e,f) SR<sup>Wh</sup><sub>DF</sub> regions of the $W\!h$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e) truth-level acceptances and (b,d,f) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-0j</sub>, (c,d) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-nj</sub>, and (e,f) SR<sup>Wh</sup><sub>DF</sub> regions of the $W\!h$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e) truth-level acceptances and (b,d,f) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-0j</sub>, (c,d) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-nj</sub>, and (e,f) SR<sup>Wh</sup><sub>DF</sub> regions of the $W\!h$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e) truth-level acceptances and (b,d,f) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-0j</sub>, (c,d) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-nj</sub>, and (e,f) SR<sup>Wh</sup><sub>DF</sub> regions of the $W\!h$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e) truth-level acceptances and (b,d,f) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-0j</sub>, (c,d) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-nj</sub>, and (e,f) SR<sup>Wh</sup><sub>DF</sub> regions of the $W\!h$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
Summary of onshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (300,200) GeV and m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (600,100) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal points, for the wino/bino (+) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks per inclusive regions, and then further for each SR. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5.
Summary of onshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (300,200) GeV and m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (600,100) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal points, for the wino/bino (+) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks per inclusive regions, and then further for each SR. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5.
Summary of $W\!h$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (190,60) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (+) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks per inclusive regions, and then further for each SR. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5.
Summary of $W\!h$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (190,60) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (+) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks per inclusive regions, and then further for each SR. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (250,235) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (+) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (250,235) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (+) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (125,85) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (+) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (125,85) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (+) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (250,170) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (+) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (250,170) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (+) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (250,235) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (-) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (250,235) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (-) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (125,85) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (-) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (125,85) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (-) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (250,170) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (-) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (250,170) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (-) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (120,100) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the higgsino interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (120,100) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the higgsino interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (100,40) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the higgsino interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (100,40) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the higgsino interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (185,125) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the higgsino interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (185,125) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the higgsino interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
A search for long-lived particles (LLPs) produced in decays of standard model (SM) Higgs bosons is presented. The data sample consists of 137 fb$^{-1}$ of proton-proton collisions at $\sqrt{s} =$ 13 TeV, recorded at the LHC in 2016-2018. A novel technique is employed to reconstruct decays of LLPs in the endcap muon detectors. The search is sensitive to a broad range of LLP decay modes and to masses as low as a few GeV. No excess of events above the SM background is observed. The most stringent limits to date on the branching fraction of the Higgs boson to LLPs subsequently decaying to quarks and $\tau^+\tau^-$ are found for proper decay lengths greater than 6, 20, and 40 m, for LLP masses of 7, 15, and 40 GeV, respectively.
The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 7 GeV mass and $ S \rightarrow d\bar{d}$ decay mode.
The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 7 GeV mass and $ S \rightarrow d\bar{d}$ decay mode.
The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 15 GeV mass and $ S \rightarrow d\bar{d}$ decay mode.
The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 15 GeV mass and $ S \rightarrow d\bar{d}$ decay mode.
The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 40 GeV mass and $ S \rightarrow d\bar{d}$ decay mode.
The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 40 GeV mass and $ S \rightarrow d\bar{d}$ decay mode.
The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 55 GeV mass and $ S \rightarrow d\bar{d}$ decay mode.
The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 55 GeV mass and $ S \rightarrow d\bar{d}$ decay mode.
The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 7 GeV mass and $ S \rightarrow \tau^{+} \tau^{-}$ decay mode.
The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 7 GeV mass and $ S \rightarrow \tau^{+} \tau^{-}$ decay mode.
The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 15 GeV mass and $ S \rightarrow \tau^{+} \tau^{-}$ decay mode.
The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 15 GeV mass and $ S \rightarrow \tau^{+} \tau^{-}$ decay mode.
The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 40 GeV mass and $ S \rightarrow \tau^{+} \tau^{-}$ decay mode.
The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 40 GeV mass and $ S \rightarrow \tau^{+} \tau^{-}$ decay mode.
The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 55 GeV mass and $ S \rightarrow \tau^{+} \tau^{-}$ decay mode.
The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 55 GeV mass and $ S \rightarrow \tau^{+} \tau^{-}$ decay mode.
The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 15 GeV mass and $ S \rightarrow b\bar{b}$ decay mode.
The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 15 GeV mass and $ S \rightarrow b\bar{b}$ decay mode.
The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 40 GeV mass and $ S \rightarrow b\bar{b}$ decay mode.
The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 40 GeV mass and $ S \rightarrow b\bar{b}$ decay mode.
The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 55 GeV mass and $ S \rightarrow b\bar{b}$ decay mode.
The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 55 GeV mass and $ S \rightarrow b\bar{b}$ decay mode.
The cluster efficiency in bins of hadronic and EM energy in region A. Region A is defined as 391 cm $< r <$ 695.5 cm and 400 cm $< |z| <$ 671 cm. The cluster efficiency is estimated with LLPs decaying to $\tau^{+} \tau^{-}$. The sample contains equal fractions of events with LLP mass of 7, 15, 40, and 55 GeV and LLP lifetime of 0.1, 1, 10, and 100m. The first hadronic energy bins correspond to LLPs that decayed leptonically with 0 hadronic energy. The cluster efficiency includes all cluster-level selections described in the paper, except for the jet veto, time cut, and $\Delta\phi$ cut. The full simulation signal yield prediction for samples with various LLP mass between 7 - 55 GeV, lifetime between 0.1 - 100 m, and decay mode to $d\bar{d}$ and $\tau^{+} \tau^{-}$ can be reproduced using this parameterization to within 35% and 20% for region A and B, respectively.
The cluster efficiency in bins of hadronic and EM energy in region A. Region A is defined as 391 cm $< r <$ 695.5 cm and 400 cm $< |z| <$ 671 cm. The cluster efficiency is estimated with LLPs decaying to $\tau^{+} \tau^{-}$. The sample contains equal fractions of events with LLP mass of 7, 15, 40, and 55 GeV and LLP lifetime of 0.1, 1, 10, and 100m. The first hadronic energy bins correspond to LLPs that decayed leptonically with 0 hadronic energy. The cluster efficiency includes all cluster-level selections described in the paper, except for the jet veto, time cut, and $\Delta\phi$ cut. The full simulation signal yield prediction for samples with various LLP mass between 7 - 55 GeV, lifetime between 0.1 - 100 m, and decay mode to $d\bar{d}$ and $\tau^{+} \tau^{-}$ can be reproduced using this parameterization to within 35% and 20% for region A and B, respectively.
The cluster efficiency in bins of hadronic and EM energy in region B. Region B is defined as 671 cm $< |z| <$ 1100 cm, $r <$ 695.5 cm, and $|\eta| <$ 2. The cluster efficiency is estimated with LLPs decaying to $\tau^{+} \tau^{-}$. The sample contains equal fractions of events with LLP mass of 7, 15, 40, and 55 GeV and LLP lifetime of 0.1, 1, 10, and 100m. The first hadronic energy bins correspond to LLPs that decayed leptonically with 0 hadronic energy. The cluster efficiency includes all cluster-level selections described in the paper, except for the jet veto, time cut, and $\Delta\phi$ cut. The full simulation signal yield prediction for samples with various LLP mass between 7 - 55 GeV, lifetime between 0.1 - 100 m, and decay mode to $d\bar{d}$ and $\tau^{+} \tau^{-}$ can be reproduced using this parameterization to within 35% and 20% for region A and B, respectively.
The cluster efficiency in bins of hadronic and EM energy in region B. Region B is defined as 671 cm $< |z| <$ 1100 cm, $r <$ 695.5 cm, and $|\eta| <$ 2. The cluster efficiency is estimated with LLPs decaying to $\tau^{+} \tau^{-}$. The sample contains equal fractions of events with LLP mass of 7, 15, 40, and 55 GeV and LLP lifetime of 0.1, 1, 10, and 100m. The first hadronic energy bins correspond to LLPs that decayed leptonically with 0 hadronic energy. The cluster efficiency includes all cluster-level selections described in the paper, except for the jet veto, time cut, and $\Delta\phi$ cut. The full simulation signal yield prediction for samples with various LLP mass between 7 - 55 GeV, lifetime between 0.1 - 100 m, and decay mode to $d\bar{d}$ and $\tau^{+} \tau^{-}$ can be reproduced using this parameterization to within 35% and 20% for region A and B, respectively.
The efficiency of $N_{station} > 1$ requirement in bins of hadronic energy in region B. Region B is defined as 671 cm $< |z| <$ 1100 cm, $r <$ 695.5 cm, and $|\eta| <$ 2. The cluster efficiency is estimated with LLPs decaying to $\tau^{+} \tau^{-}$. The sample contains equal fractions of events with LLP mass of 7, 15, 40, and 55 GeV and LLP lifetime of 0.1, 1, 10, and 100m. The first hadronic energy bin corresponds to LLPs that decayed leptonically with 0 hadronic energy. The efficiency is calculated with respect to clusters that pass all cluster-level cuts described in the paper, except for the jet veto, time cut, and $\Delta\phi$ cut. The full simulation signal yield prediction for samples with various LLP mass between 7 - 55 GeV, lifetime between 0.1 - 100 m, and decay mode to $d\bar{d}$ and $\tau^{+} \tau^{-}$ can be reproduced using this parameterization to within 10%.
The efficiency of $N_{station} > 1$ requirement in bins of hadronic energy in region B. Region B is defined as 671 cm $< |z| <$ 1100 cm, $r <$ 695.5 cm, and $|\eta| <$ 2. The cluster efficiency is estimated with LLPs decaying to $\tau^{+} \tau^{-}$. The sample contains equal fractions of events with LLP mass of 7, 15, 40, and 55 GeV and LLP lifetime of 0.1, 1, 10, and 100m. The first hadronic energy bin corresponds to LLPs that decayed leptonically with 0 hadronic energy. The efficiency is calculated with respect to clusters that pass all cluster-level cuts described in the paper, except for the jet veto, time cut, and $\Delta\phi$ cut. The full simulation signal yield prediction for samples with various LLP mass between 7 - 55 GeV, lifetime between 0.1 - 100 m, and decay mode to $d\bar{d}$ and $\tau^{+} \tau^{-}$ can be reproduced using this parameterization to within 10%.
The geometric signal acceptance as a function of $c\tau$. The acceptance is shown for four different LLP mass hypotheses: 7, 15, 40, and 55 GeV. The acceptance is defined by requiring at least 1 LLP to decay in the region defined as 400 cm $< |z| <$ 1100 cm, $r < $ 695.5 cm, and $|\eta| <$ 2.4.
A search is presented for new particles produced at the LHC in proton-proton collisions at $\sqrt{s} =$ 13 TeV, using events with energetic jets and large missing transverse momentum. The analysis is based on a data sample corresponding to an integrated luminosity of 101 fb$^{-1}$, collected in 2017-2018 with the CMS detector. Machine learning techniques are used to define separate categories for events with narrow jets from initial-state radiation and events with large-radius jets consistent with a hadronic decay of a W or Z boson. A statistical combination is made with an earlier search based on a data sample of 36 fb$^{-1}$, collected in 2016. No significant excess of events is observed with respect to the standard model background expectation determined from control samples in data. The results are interpreted in terms of limits on the branching fraction of an invisible decay of the Higgs boson, as well as constraints on simplified models of dark matter, on first-generation scalar leptoquarks decaying to quarks and neutrinos, and on models with large extra dimensions. Several of the new limits, specifically for spin-1 dark matter mediators, pseudoscalar mediators, colored mediators, and leptoquarks, are the most restrictive to date.
Differential signal yields for various signal hypotheses.
Differential signal yields for various signal hypotheses.
Differential signal yields for various signal hypotheses.
Differential signal yields for various signal hypotheses.
Differential signal yields for various signal hypotheses.
Differential signal yields for various signal hypotheses.
Differential signal yields for various signal hypotheses.
Differential signal yields for various signal hypotheses.
Differential signal yields for various signal hypotheses.
Differential signal yields for various signal hypotheses.
Differential signal yields for various signal hypotheses.
Differential signal yields for various signal hypotheses.
Differential signal yields for various signal hypotheses.
Differential signal yields for various signal hypotheses.
Differential signal yields for various signal hypotheses.
Differential signal yields for various signal hypotheses.
Background and data yields in the control and signal region bins. The prediction before ("prefit") and after the background only fit ("b-only") are given separately.
Background and data yields in the control and signal region bins. The prediction before ("prefit") and after the background only fit ("b-only") are given separately.
Background and data yields in the control and signal region bins. The prediction before ("prefit") and after the background only fit ("b-only") are given separately.
Background and data yields in the control and signal region bins. The prediction before ("prefit") and after the background only fit ("b-only") are given separately.
Background and data yields in the control and signal region bins. The prediction before ("prefit") and after the background only fit ("b-only") are given separately.
Background and data yields in the control and signal region bins. The prediction before ("prefit") and after the background only fit ("b-only") are given separately.
Matrix of covariance coefficients between signal region bins. The coefficients are obtained from the background-only fit to the control regions, and serve as input to the simplified likelihood reinterpretation scheme.
Matrix of covariance coefficients between signal region bins. The coefficients are obtained from the background-only fit to the control regions, and serve as input to the simplified likelihood reinterpretation scheme.
Background prediction and observed data yields in the signal region bins. The background yields are obtained from the background-only fit to the corresponding control regions, and serve as input to the simplified likelihood reinterpretation scheme.
Background prediction and observed data yields in the signal region bins. The background yields are obtained from the background-only fit to the corresponding control regions, and serve as input to the simplified likelihood reinterpretation scheme.
Matrix of covariance coefficients between signal region bins. The coefficients are obtained from the background-only fit to the control regions, and serve as input to the simplified likelihood reinterpretation scheme.
Matrix of covariance coefficients between signal region bins. The coefficients are obtained from the background-only fit to the control regions, and serve as input to the simplified likelihood reinterpretation scheme.
Background prediction and observed data yields in the signal region bins. The background yields are obtained from the background-only fit to the corresponding control regions, and serve as input to the simplified likelihood reinterpretation scheme.
Background prediction and observed data yields in the signal region bins. The background yields are obtained from the background-only fit to the corresponding control regions, and serve as input to the simplified likelihood reinterpretation scheme.
Matrix of covariance coefficients between signal region bins. The coefficients are obtained from the background-only fit to the control regions, and serve as input to the simplified likelihood reinterpretation scheme.
Matrix of covariance coefficients between signal region bins. The coefficients are obtained from the background-only fit to the control regions, and serve as input to the simplified likelihood reinterpretation scheme.
Background prediction and observed data yields in the signal region bins. The background yields are obtained from the background-only fit to the corresponding control regions, and serve as input to the simplified likelihood reinterpretation scheme.
Background prediction and observed data yields in the signal region bins. The background yields are obtained from the background-only fit to the corresponding control regions, and serve as input to the simplified likelihood reinterpretation scheme.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.
Median Expected exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with axial couplings.
Median Expected exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with axial couplings.
Observed exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with axial couplings.
Observed exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with axial couplings.
Expected plus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with axial couplings.
Expected plus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with axial couplings.
Expected minus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with axial couplings.
Expected minus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with axial couplings.
Median Expected exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with vector couplings.
Median Expected exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with vector couplings.
Observed exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with vector couplings.
Observed exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with vector couplings.
Expected plus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with vector couplings.
Expected plus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with vector couplings.
Expected minus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with vector couplings.
Expected minus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with vector couplings.
Upper limits on the coupling $g_{\chi}$ in the simplified model with a axial mediator.
Upper limits on the coupling $g_{\chi}$ in the simplified model with a axial mediator.
Upper limits on the coupling $g_{q}$ in the simplified model with a axial mediator.
Upper limits on the coupling $g_{q}$ in the simplified model with a axial mediator.
Upper limits on the coupling $g_{\chi}$ in the simplified model with a vector mediator.
Upper limits on the coupling $g_{\chi}$ in the simplified model with a vector mediator.
Upper limits on the coupling $g_{q}$ in the simplified model with a vector mediator.
Upper limits on the coupling $g_{q}$ in the simplified model with a vector mediator.
Exclusion limits on the signal strength in the simplified model with scalar couplings.
Exclusion limits on the signal strength in the simplified model with scalar couplings.
Exclusion limits on the signal strength in the simplified model with pseudoscalar couplings.
Exclusion limits on the signal strength in the simplified model with pseudoscalar couplings.
Exclusion limits on the fundamental Planck scale $M_{D}$ as a function of the number of extra dimensions $d$.
Exclusion limits on the fundamental Planck scale $M_{D}$ as a function of the number of extra dimensions $d$.
Median Expected exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the fermion portal model.
Median Expected exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the fermion portal model.
Observed exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the fermion portal model.
Observed exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the fermion portal model.
Expected plus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the fermion portal model.
Expected plus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the fermion portal model.
Expected minus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the fermion portal model.
Expected minus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the fermion portal model.
Tagging efficiency for AK8 jets. The efficiency includes the effect of the machine-learning based DeepAK8 tagger, as well as the application of the mass window requirement on the jet. The efficiency is split depending on the matching generator-level object. For reinterpretation purposes, this efficiency can directly be applied to any AK8 jet that is matched to a given type of generator-level object, with no prior selection on the jet mass. Other acceptance requirements on jet $\p_{T}$ and $\eta$ should still be applied.
Tagging efficiency for AK8 jets. The efficiency includes the effect of the machine-learning based DeepAK8 tagger, as well as the application of the mass window requirement on the jet. The efficiency is split depending on the matching generator-level object. For reinterpretation purposes, this efficiency can directly be applied to any AK8 jet that is matched to a given type of generator-level object, with no prior selection on the jet mass. Other acceptance requirements on jet $\p_{T}$ and $\eta$ should still be applied.
A search for new phenomena in final states with hadronically decaying tau leptons, $b$-jets, and missing transverse momentum is presented. The analyzed dataset comprises $pp$~collision data at a center-of-mass energy of $\sqrt s = 13$ TeV with an integrated luminosity of 139/fb, delivered by the Large Hadron Collider and recorded with the ATLAS detector from 2015 to 2018. The observed data are compatible with the expected Standard Model background. The results are interpreted in simplified models for two different scenarios. The first model is based on supersymmetry and considers pair production of top squarks, each of which decays into a $b$-quark, a neutrino and a tau slepton. Each tau slepton in turn decays into a tau lepton and a nearly massless gravitino. Within this model, top-squark masses up to 1.4 TeV can be excluded at the 95% confidence level over a wide range of tau-slepton masses. The second model considers pair production of leptoquarks with decays into third-generation leptons and quarks. Depending on the branching fraction into charged leptons, leptoquarks with masses up to around 1.25 TeV can be excluded at the 95% confidence level for the case of scalar leptoquarks and up to 1.8 TeV (1.5 TeV) for vector leptoquarks in a Yang--Mills (minimal-coupling) scenario. In addition, model-independent upper limits are set on the cross section of processes beyond the Standard Model.
Relative systematic uncertainties in the estimated number of background events in the signal regions. In the lower part of the table, a breakdown of the total uncertainty into different categories is given. For the multi-bin SR, the breakdown refers to the integral over all three $p_{\text{T}}(\tau)$ bins. As the individual uncertainties are correlated, they do not add in quadrature to equal the total background uncertainty.
Distributions of $m_{\text{T}2}(\tau_{1},\tau_{2})$ in the di-tau SR. The stacked histograms show the various SM background contributions. The hatched band indicates the total statistical and systematic uncertainty of the SM background. The $t\bar{t}$ (2 real $\tau$) and $t\bar{t}$ (1 real $\tau$) as well as the single-top background contributions are scaled with the normalization factors obtained from the background-only fit. Minor backgrounds are grouped together and denoted as 'Other'. This includes $t\bar{t}$-fake, single top, and other top (di-tau channel) or $t\bar{t}$-fake, $t\bar{t}+H$, multiboson, and other top (single-tau channel). The overlaid dotted lines show the additional contributions for signal scenarios close to the expected exclusion contour with the particle type and the mass and $\beta$ parameters for the simplified models indicated in the legend. For the leptoquark signal model the shapes of the distributions for $\text{LQ}_{3}^{\text{d}}$ and $\text{LQ}_{3}^{\text{v}}$ (not shown) are similar to that of $\text{LQ}_{3}^{\text{u}}$. The rightmost bin includes the overflow.
Distributions of $E_{\text{T}}^{\text{miss}}$ in the di-tau SR. The stacked histograms show the various SM background contributions. The hatched band indicates the total statistical and systematic uncertainty of the SM background. The $t\bar{t}$ (2 real $\tau$) and $t\bar{t}$ (1 real $\tau$) as well as the single-top background contributions are scaled with the normalization factors obtained from the background-only fit. Minor backgrounds are grouped together and denoted as 'Other'. This includes $t\bar{t}$-fake, single top, and other top (di-tau channel) or $t\bar{t}$-fake, $t\bar{t}+H$, multiboson, and other top (single-tau channel). The overlaid dotted lines show the additional contributions for signal scenarios close to the expected exclusion contour with the particle type and the mass and $\beta$ parameters for the simplified models indicated in the legend. For the leptoquark signal model the shapes of the distributions for $\text{LQ}_{3}^{\text{d}}$ and $\text{LQ}_{3}^{\text{v}}$ (not shown) are similar to that of $\text{LQ}_{3}^{\text{u}}$. The rightmost bin includes the overflow.
Distributions of $s_{\text{T}}$ in the single-tau one-bin SR. The stacked histograms show the various SM background contributions. The hatched band indicates the total statistical and systematic uncertainty of the SM background. The $t\bar{t}$ (2 real $\tau$) and $t\bar{t}$ (1 real $\tau$) as well as the single-top background contributions are scaled with the normalization factors obtained from the background-only fit. Minor backgrounds are grouped together and denoted as 'Other'. This includes $t\bar{t}$-fake, single top, and other top (di-tau channel) or $t\bar{t}$-fake, $t\bar{t}+H$, multiboson, and other top (single-tau channel). The overlaid dotted lines show the additional contributions for signal scenarios close to the expected exclusion contour with the particle type and the mass and $\beta$ parameters for the simplified models indicated in the legend. For the leptoquark signal model the shapes of the distributions for $\text{LQ}_{3}^{\text{d}}$ and $\text{LQ}_{3}^{\text{v}}$ (not shown) are similar to that of $\text{LQ}_{3}^{\text{u}}$. The rightmost bin includes the overflow.
Distributions of $m_{\text{T}}(\tau)$ in the single-tau one-bin SR. The stacked histograms show the various SM background contributions. The hatched band indicates the total statistical and systematic uncertainty of the SM background. The $t\bar{t}$ (2 real $\tau$) and $t\bar{t}$ (1 real $\tau$) as well as the single-top background contributions are scaled with the normalization factors obtained from the background-only fit. Minor backgrounds are grouped together and denoted as 'Other'. This includes $t\bar{t}$-fake, single top, and other top (di-tau channel) or $t\bar{t}$-fake, $t\bar{t}+H$, multiboson, and other top (single-tau channel). The overlaid dotted lines show the additional contributions for signal scenarios close to the expected exclusion contour with the particle type and the mass and $\beta$ parameters for the simplified models indicated in the legend. For the leptoquark signal model the shapes of the distributions for $\text{LQ}_{3}^{\text{d}}$ and $\text{LQ}_{3}^{\text{v}}$ (not shown) are similar to that of $\text{LQ}_{3}^{\text{u}}$. The rightmost bin includes the overflow.
Distributions of $\Sigma m_{\text{T}}(b_{1,2})$ in the single-tau $p_{\text{T}}(\tau)$-binned SR. The stacked histograms show the various SM background contributions. The hatched band indicates the total statistical and systematic uncertainty of the SM background. The $t\bar{t}$ (2 real $\tau$) and $t\bar{t}$ (1 real $\tau$) as well as the single-top background contributions are scaled with the normalization factors obtained from the background-only fit. Minor backgrounds are grouped together and denoted as 'Other'. This includes $t\bar{t}$-fake, single top, and other top (di-tau channel) or $t\bar{t}$-fake, $t\bar{t}+H$, multiboson, and other top (single-tau channel). The overlaid dotted lines show the additional contributions for signal scenarios close to the expected exclusion contour with the particle type and the mass and $\beta$ parameters for the simplified models indicated in the legend. For the leptoquark signal model the shapes of the distributions for $\text{LQ}_{3}^{\text{d}}$ and $\text{LQ}_{3}^{\text{v}}$ (not shown) are similar to that of $\text{LQ}_{3}^{\text{u}}$. The rightmost bin includes the overflow.
Distributions of $p_{\text{T}}(\tau)$ in the single-tau $p_{\text{T}}(\tau)$-binned SR. The stacked histograms show the various SM background contributions. The hatched band indicates the total statistical and systematic uncertainty of the SM background. The $t\bar{t}$ (2 real $\tau$) and $t\bar{t}$ (1 real $\tau$) as well as the single-top background contributions are scaled with the normalization factors obtained from the background-only fit. Minor backgrounds are grouped together and denoted as 'Other'. This includes $t\bar{t}$-fake, single top, and other top (di-tau channel) or $t\bar{t}$-fake, $t\bar{t}+H$, multiboson, and other top (single-tau channel). The overlaid dotted lines show the additional contributions for signal scenarios close to the expected exclusion contour with the particle type and the mass and $\beta$ parameters for the simplified models indicated in the legend. For the leptoquark signal model the shapes of the distributions for $\text{LQ}_{3}^{\text{d}}$ and $\text{LQ}_{3}^{\text{v}}$ (not shown) are similar to that of $\text{LQ}_{3}^{\text{u}}$. The rightmost bin includes the overflow.
Observed event yields in data ('Observed') and expected event yields for SM background processes obtained from the background-only fit ('Total bkg.' and rows below) in the signal regions of the di-tau and single-tau channels. The quoted uncertainties include both the statistical and systematic uncertainties and are truncated at zero yield. By construction, no $t\bar{t}$ (2 real $\tau$) events can pass the selections in the single-tau channel. As the individual uncertainties are correlated, they do not add in quadrature to equal the total background uncertainty.
From left to right: upper limits at the 95% confidence level (CL) on the visible cross section ($\sigma_\text{vis}$) and on the number of signal events ($S_{\text{obs}}^{95}$). The third column ($S_{\text{exp}}^{95}$) shows the upper limit at the 95% CL on the number of signal events, given the expected number (and $\pm 1\,\sigma$ excursions on the expectation) of background events. The last two columns indicate the confidence level observed for the background-only hypothesis ($\text{CL}_{b}$), the discovery $p$-value ($p(s=0)$) and the significance ($Z$). In the di-tau SR, where fewer events are observed than predicted by the fitted background estimate, the $p$-value is capped at 0.5.
Expected and observed exclusion contours at the 95% confidence level for the vector third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{v}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ into a quark and a charged lepton. The plot shows the exclusion contour for the minimal-coupling scenario. The limits are derived from the binned single-tau signal region.
Expected and observed exclusion contours at the 95% confidence level for the vector third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{v}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ into a quark and a charged lepton. The plot shows the exclusion contour for the minimal-coupling scenario. The limits are derived from the binned single-tau signal region.
Expected and observed exclusion contours at the 95% confidence level for the vector third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{v}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ into a quark and a charged lepton. The plot shows the exclusion contour for vector leptoquarks with additional gauge couplings. The limits are derived from the binned single-tau signal region.
Expected and observed exclusion contours at the 95% confidence level for the vector third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{v}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ into a quark and a charged lepton. The plot shows the exclusion contour for vector leptoquarks with additional gauge couplings. The limits are derived from the binned single-tau signal region.
Exclusion contours at the 95% confidence level for the stop-stau signal model as a function of the masses of the top squark $m(\tilde{t}_{1})$ and of the tau slepton $m(\tilde{\tau}_{1})$. Expected and observed limits are shown for the present search in comparison to observed limits from previous ATLAS analyses based on data from Run-1 of the LHC at $\sqrt{s} = 8$ TeV [Eur. Phys. J. C 76 (2016)] and on a partial dataset from Run 2 at $\sqrt{s} = 13$ TeV [Phys. Rev. D 98 (2018) 032008]. The green band indicates the limit on the mass of the tau slepton (for a massless LSP) from the LEP experiments.
Exclusion contours at the 95% confidence level for the stop-stau signal model as a function of the masses of the top squark $m(\tilde{t}_{1})$ and of the tau slepton $m(\tilde{\tau}_{1})$. Expected and observed limits are shown for the present search in comparison to observed limits from previous ATLAS analyses based on data from Run-1 of the LHC at $\sqrt{s} = 8$ TeV [Eur. Phys. J. C 76 (2016)] and on a partial dataset from Run 2 at $\sqrt{s} = 13$ TeV [Phys. Rev. D 98 (2018) 032008]. The green band indicates the limit on the mass of the tau slepton (for a massless LSP) from the LEP experiments.
Expected and observed exclusion contours at the 95% confidence level for the scalar third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{u}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow q\ell)$ into a quark and a charged lepton. The plot shows the exclusion contour for up-type leptoquarks $\text{LQ}_{3}^{\text{u}})$ with charge $+2/3e$. The limits are derived from the binned single-tau signal region. Shown in gray for comparison are the observed exclusion-limit contours from the previous ATLAS publication that targets the same leptoquark models but is based on a subset of the Run-2 data [JHEP 06 (2019) 144]. In this previous publication five different analyses are considered that target not only the final state studied here but also the final states that correspond to a branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow q\ell)$ of 0 or 1, leading to the concave shapes of the gray exclusion contours.
Expected and observed exclusion contours at the 95% confidence level for the scalar third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{u}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow q\ell)$ into a quark and a charged lepton. The plot shows the exclusion contour for up-type leptoquarks $\text{LQ}_{3}^{\text{u}})$ with charge $+2/3e$. The limits are derived from the binned single-tau signal region. Shown in gray for comparison are the observed exclusion-limit contours from the previous ATLAS publication that targets the same leptoquark models but is based on a subset of the Run-2 data [JHEP 06 (2019) 144]. In this previous publication five different analyses are considered that target not only the final state studied here but also the final states that correspond to a branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow q\ell)$ of 0 or 1, leading to the concave shapes of the gray exclusion contours.
Expected and observed exclusion contours at the 95% confidence level for the scalar third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{d}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow q\ell)$ into a quark and a charged lepton. The plot shows the exclusion contour for down-type leptoquarks $\text{LQ}_{3}^{\text{d}})$ with charge $-1/3e$. The limits are derived from the binned single-tau signal region. Shown in gray for comparison are the observed exclusion-limit contours from the previous ATLAS publication that targets the same leptoquark models but is based on a subset of the Run-2 data [JHEP 06 (2019) 144]. In this previous publication five different analyses are considered that target not only the final state studied here but also the final states that correspond to a branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow q\ell)$ of 0 or 1, leading to the concave shapes of the gray exclusion contours.
Expected and observed exclusion contours at the 95% confidence level for the scalar third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{d}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow q\ell)$ into a quark and a charged lepton. The plot shows the exclusion contour for down-type leptoquarks $\text{LQ}_{3}^{\text{d}})$ with charge $-1/3e$. The limits are derived from the binned single-tau signal region. Shown in gray for comparison are the observed exclusion-limit contours from the previous ATLAS publication that targets the same leptoquark models but is based on a subset of the Run-2 data [JHEP 06 (2019) 144]. In this previous publication five different analyses are considered that target not only the final state studied here but also the final states that correspond to a branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow q\ell)$ of 0 or 1, leading to the concave shapes of the gray exclusion contours.
Upper limits on the signal cross section at the 95 % confidence level for the stop-stau signal model.
Upper limits on the signal cross section at the 95 % confidence level for the scalar third-generation leptoquark signal model with up-type leptoquarks.
Upper limits on the signal cross section at the 95 % confidence level for the scalar third-generation leptoquark signal model with down-type leptoquarks.
Upper limits on the signal cross section at the 95 % confidence level for the vector third-generation leptoquark signal model with minimal coupling (MC).
Upper limits on the signal cross section at the 95 % confidence level for the vector third-generation leptoquark signal model with additional gauge couplings (YM).
Acceptance of the one-bin signal region of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$.
Efficiency of the one-bin signal region of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$.
Efficiency of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$.
Efficiency of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$.
Efficiency of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the signal region of the di-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$.
Efficiency of the signal region of the di-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow b\tau)$ of 0 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the one-bin signal region of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$.
Efficiency of the one-bin signal region of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow t\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$.
Efficiency of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow t\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$.
Efficiency of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow t\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$.
Efficiency of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow t\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the signal region of the di-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$.
Efficiency of the signal region of the di-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow t\tau)$ of 0 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the one-bin signal region of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario.
Efficiency of the one-bin signal region of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario.
Efficiency of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario.
Efficiency of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario.
Efficiency of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the signal region of the di-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario.
Efficiency of the signal region of the di-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the one-bin signal region of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings.
Efficiency of the one-bin signal region of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings.
Efficiency of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings.
Efficiency of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings.
Efficiency of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the signal region of the di-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings.
Efficiency of the signal region of the di-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the one-bin signal region of the single-tau channel for pair production of top squarks with decays via tau sleptons.
Efficiency of the one-bin signal region of the single-tau channel for pair production of top squarks with decays via tau sleptons.
Acceptance of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of top squarks with decays via tau sleptons.
Efficiency of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of top squarks with decays via tau sleptons.
Acceptance of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of top squarks with decays via tau sleptons.
Efficiency of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of top squarks with decays via tau sleptons.
Acceptance of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of top squarks with decays via tau sleptons.
Efficiency of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of top squarks with decays via tau sleptons.
Acceptance of the signal region of the di-tau channel for pair production of top squarks with decays via tau sleptons.
Efficiency of the signal region of the di-tau channel for pair production of top squarks with decays via tau sleptons.
Cutflow for the benchmark signal model $m(\tilde{t}_{1}) = 1350$ GeV, $m(\tilde{\tau}_{1}) = 1090$ GeV for the di-tau SR. The simulated sample contains 30,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the di-tau channel.
Cutflow for the benchmark signal model $m(\tilde{t}_{1}) = 1350$ GeV, $m(\tilde{\tau}_{1}) = 1090$ GeV for the single-tau one-bin SR. The simulated sample contains 30,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.
Cutflow for the benchmark signal model $m(\tilde{t}_{1}) = 1350$ GeV, $m(\tilde{\tau}_{1}) = 1090$ GeV for the single-tau multi-bin SR. The simulated sample contains 30,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.
Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{u}}) = 1.2$ TeV, $\beta = 0.5$ for the di-tau SR. The simulated sample contains 210,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the di-tau channel.
Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{u}}) = 1.2$ TeV, $\beta = 0.5$ for the single-tau one-bin SR. The simulated sample contains 210,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.
Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{u}}) = 1.2$ TeV, $\beta = 0.5$ for the single-tau multi-bin SR. The simulated sample contains 210,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.
Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{d}}) = 1.2$ TeV, $\beta = 0.5$ for the di-tau SR. The simulated sample contains 210,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the di-tau channel.
Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{d}}) = 1.2$ TeV, $\beta = 0.5$ for the single-tau one-bin SR. The simulated sample contains 210,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.
Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{d}}) = 1.2$ TeV, $\beta = 0.5$ for the single-tau multi-bin SR. The simulated sample contains 210,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.
Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{v}}) = 1.4$ TeV, $\beta = 0.5$ in the minimal-coupling scenario for the di-tau SR. The simulated sample contains 50,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the di-tau channel.
Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{v}}) = 1.4$ TeV, $\beta = 0.5$ in the minimal-coupling scenario for the single-tau one-bin SR. The simulated sample contains 50,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.
Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{v}}) = 1.4$ TeV, $\beta = 0.5$ in the minimal-coupling scenario for the single-tau multi-bin SR. The simulated sample contains 50,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.
Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{v}}) = 1.4$ TeV, $\beta = 0.5$ in the Yang--Mills scenario for the di-tau SR. The simulated sample contains 50,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the di-tau channel.
Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{v}}) = 1.4$ TeV, $\beta = 0.5$ in the Yang--Mills scenario for the single-tau one-bin SR. The simulated sample contains 50,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.
Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{v}}) = 1.4$ TeV, $\beta = 0.5$ in the Yang--Mills scenario for the single-tau multi-bin SR. The simulated sample contains 50,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.
The associated production of a W and a Z boson is studied in final states with multiple leptons produced in proton-proton (pp) collisions at a centre-of-mass energy of 13 TeV using 137 fb$^{-1}$ of data collected with the CMS detector at the LHC. A measurement of the total inclusive production cross section yields $\sigma_{\text{tot}}$(pp $\to$ WZ) = 50.6 $\pm$ 0.8 (stat) $\pm$ 1.5 (syst) $\pm$ 1.1 (lumi) $\pm$ 0.5 (theo) pb. Measurements of the fiducial and differential cross sections for several key observables are also performed in all the final-state lepton flavour and charge compositions with a total of three charged leptons, which can be electrons or muons. All results are compared with theoretical predictions computed up to next-to-next-to-leading order in quantum chromodynamics plus next-to-leading order in electroweak theory and for various sets of parton distribution functions. The results include direct measurements of the charge asymmetry and the W and Z vector boson polarization. The first observation of longitudinally polarized W bosons in WZ production is reported. Anomalous gauge couplings are searched for, leading to new constraints on beyond-the-standard-model contributions to the WZ triple gauge coupling.
Distribution of the three leading leptons flavour in the CR-ZZ with uncertainties evaluated after the inclusive cross section fit
Distribution of the jet multiplicity in the CR-ttZ with uncertainties evaluated after the inclusive cross section fit
Distribution of the three leading leptons flavour in the CR-conv with uncertainties evaluated after the inclusive cross section fit
Distribution of the three leading leptons flavour in the SR-WZ with uncertainties evaluated after the inclusive cross section fit
Efficiency, acceptance, and proportion of events with leptonic tau decays in WZ production
WZ fiducial cross section in the four flavour exclusive and the flavour inclusive channels
WZ total cross section extrapolated from the four flavour exclusive and the flavour inclusive channels
Distribution of the total lepton charge in the SR-WZ with uncertainties evaluated after the inclusive cross section fit
W$^{+}$Z fiducial cross section in the four flavour exclusive and the flavour inclusive channels
W$^{-}$Z fiducial cross section in the four flavour exclusive and the flavour inclusive channels
WZ charge asymmetry ratio measured on each of the four flavour exclusive and the flavour inclusive channels
Distribution of the cosine of the W polarization angle times total lepton charge in the SR-WZ with uncertainties evaluated after the W polarization fit
Distribution of the cosine of the Z polarization angle in the SR-WZ with uncertainties evaluated after the Z polarization fit
Best fits to the W and Z polarization fractions
2D confidence regions at the 68, 95, and 99% CL in the $f_O^W$-$f_{L}^W-f_R^W$ plane
2D confidence regions at the 68, 95, and 99% CL in the $f_O^Z$-$f_{L}^Z-f_R^Z$ plane
Distribution of the invariant mass of the WZ system in the SR-WZ with uncertainties evaluated after the inclusive cross section fit
Best fit values and one dimensional confidence regions in several EFT coefficients obtained from the EFT fit considering both the SM interferences and purely BSM (order $\Lambda^{-2}$ and $\Lambda^{-4}$) terms
2D confidence regions at the 68, 95, and 99% CL in the $c_{www}$-$c_{w}$ plane
2D confidence regions at the 68, 95, and 99% CL in the $c_{w}$-$c_{b}$ plane
2D confidence regions at the 68, 95, and 99% CL in the $c_{www}$-$c_{w}$ plane
Best fit values and one dimensional confidence regions in several EFT coefficients obtained from the EFT fit considering only the SM-EFT interference (order $\Lambda^{-2}$) terms
Evolution of the best fit and expected and observed 95% CI for the $c_{w}$ parameter as a function of the cutoff scale
Evolution of the best fit and expected and observed 95% CI for the $c_{b}$ parameter as a function of the cutoff scale
Evolution of the best fit and expected and observed 95% CI for the $c_{www}$ parameter as a function of the cutoff scale
Evolution of the best fit and expected and observed 95% CI for the $\tilde{c}_{www}$ parameter as a function of the cutoff scale
Evolution of the best fit and expected and observed 95% CI for the $\tilde{c}_{w}$ parameter as a function of the cutoff scale
Differential cross section with respect to the transverse momentum of the Z boson
Correlation matrix for the unfolded results obtained using NNLO bias, area con-straint, and no additional regularization for the $p_{T}$ of the Z boson
Response matrix for the $p_{T}$ of the Z boson obtained with POWHEG
Differential cross section with respect to the transverse momentum of the leading jet
Correlation matrix for the unfolded results obtained using NNLO bias, area con-straint, and no additional regularization for the $p_{T}$ of the leading jet
Response matrix for the $p_{T}$ of the leading jet obtained with POWHEG
Differential cross section with respect to the jet multiplicity
Correlation matrix for the unfolded results obtained using NNLO bias, area con-straint, and no additional regularization for the jet multiplicity
Response matrix for the jet multiplicity obtained with POWHEG
Differential cross section with respect to the invariant mass of the WZ system
Correlation matrix for the unfolded results obtained using NNLO bias, area con-straint, and no additional regularization for the invariant mass of the WZ system
Response matrix for the invariant mass of the WZ system obtained with POWHEG
Differential cross section with respect to the transverse momentum of the lepton associated to the W boson
Correlation matrix for the unfolded results obtained using NNLO bias, area con-straint, and no additional regularization for the $p_{T}$ of the lepton associated to the W boson
Response matrix for the $p_{T}$ of the lepton associated to the W boson obtained with POWHEG
Differential cross section with respect to the transverse momentum of the lepton associated to the W boson, W$^{+}$Z only
Correlation matrix for the unfolded results obtained using NNLO bias, area con-straint, and no additional regularization for the $p_{T}$ of the lepton associated to the W boson, W$^{+}$Z only
Differential cross section with respect to the transverse momentum of the lepton associated to the W boson, W$^{-}$Z only
Correlation matrix for the unfolded results obtained using NNLO bias, area con-straint, and no additional regularization for the $p_{T}$ of the lepton associated to the W boson, W$^{-}$Z only
Differential cross section with respect to the cosine of the W polarization angle times total lepton charge
Correlation matrix for the unfolded results obtained using NNLO bias, area con-straint, and no additional regularization for the cosine of the W polarization angle times total lepton charge
Response matrix for the cosine of the W polarization angle times total lepton charge obtained with POWHEG
Differential cross section with respect to the cosine of the W polarization angle times total lepton charge, W$^{+}$Z only
Correlation matrix for the unfolded results obtained using NNLO bias, area con-straint, and no additional regularization for the cosine of the W polarization angle times total lepton charge, W$^{+}$Z only
Differential cross section with respect to the cosine of the W polarization angle times total lepton charge, W$^{-}$Z only
Correlation matrix for the unfolded results obtained using NNLO bias, area con-straint, and no additional regularization for the cosine of the W polarization angle times total lepton charge, W$^{-}$Z only
Differential cross section with respect to the cosine of the Z polarization angle
Correlation matrix for the unfolded results obtained using NNLO bias, area con-straint, and no additional regularization for the cosine of the Z polarization angle
Response matrix for the cosine of the Z polarization angle obtained with POWHEG
Differential cross section with respect to the cosine of the Z polarization angle, W$^{+}$Z only
Correlation matrix for the unfolded results obtained using NNLO bias, area con-straint, and no additional regularization for the cosine of the Z polarization angle, W$^{+}$Z only
Differential cross section with respect to the cosine of the Z polarization angle, W$^{-}$Z only
Correlation matrix for the unfolded results obtained using NNLO bias, area con-straint, and no additional regularization for the cosine of the Z polarization angle, W$^{-}$Z only
The associated production of a Higgs boson and a top-quark pair is measured in events characterised by the presence of one or two electrons or muons. The Higgs boson decay into a $b$-quark pair is used. The analysed data, corresponding to an integrated luminosity of 139 fb$^{-1}$, were collected in proton-proton collisions at the Large Hadron Collider between 2015 and 2018 at a centre-of-mass energy of $\sqrt{s}=13$ TeV. The measured signal strength, defined as the ratio of the measured signal yield to that predicted by the Standard Model, is $0.35^{+0.36}_{-0.34}$. This result is compatible with the Standard Model prediction and corresponds to an observed (expected) significance of 1.0 (2.7) standard deviations. The signal strength is also measured differentially in bins of the Higgs boson transverse momentum in the simplified template cross-section framework, including a bin for specially selected boosted Higgs bosons with transverse momentum above 300 GeV.
Comparison between data and prediction for the DNN $P(H)$ output for the Higgs boson candidate prior to any fit to the data in the single-lepton boosted channel for $300\le p_T^H<450$ GeV. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Comparison between data and prediction for the DNN $P(H)$ output for the Higgs boson candidate prior to any fit to the data in the single-lepton boosted channel for $p_{{T}}^{H}\ge 450$ GeV. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Performance of the Higgs boson reconstruction algorithms. For each row of `truth' ${\hat{p}_{{T}}^{H}}$, the matrix shows (in percentages) the fraction of all Higgs boson candidates with reconstructed $p_T^H$ in the various bins of the dilepton (left), single-lepton resolved (middle) and boosted (right) channels.
Pre-fit distribution of the reconstructed Higgs boson candidate $p_T^H$ for the dilepton $SR^{\geq 4j}_{\geq 4b}$ signal region. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations, except for the uncertainty in the $k({t\bar {t}+{\geq }1b})$ normalisation factor which is not defined pre-fit. The last bin includes the overflow.
Pre-fit distribution of the reconstructed Higgs boson candidate $p_T^H$ for the single-lepton resolved $SR^{\geq 6j}_{\geq 4b}$ signal region. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations, except for the uncertainty in the $k({t\bar {t}+{\geq }1b})$ normalisation factor which is not defined pre-fit. The last bin includes the overflow.
Pre-fit distribution of the reconstructed Higgs boson candidate $p_T^H$ for the single-lepton boosted ${{SR}_{{boosted}}}$ signal region. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations, except for the uncertainty in the $k({t\bar {t}+{\geq }1b})$ normalisation factor which is not defined pre-fit. The last bin includes the overflow.
Comparison of predicted and observed event yields in each of the control and signal regions in the dilepton channel after the fit to the data. The uncertainty band includes all uncertainties and their correlations.
Comparison of predicted and observed event yields in each of the control and signal regions in the single-lepton channels after the fit to the data. The uncertainty band includes all uncertainties and their correlations.
Comparison between data and prediction for the BDT discriminant in the dilepton SRs after the inclusive fit to the data for $0\le p_T^H<120$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Comparison between data and prediction for the BDT discriminant in the dilepton SRs after the inclusive fit to the data for $120\le p_T^H<200$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Comparison between data and prediction for the BDT discriminant in the dilepton SRs after the inclusive fit to the data for $200\le p_T^H<300$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Comparison between data and prediction for the BDT discriminant in the dilepton SRs after the inclusive fit to the data for $p_{{T}}^{H}\ge 300$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Comparison between data and prediction for the BDT discriminant in the single-lepton resolved SRs after the inclusive fit to the data for $0\le p_T^H<120$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Comparison between data and prediction for the BDT discriminant in the single-lepton resolved SRs after the inclusive fit to the data for $120\le p_T^H<200$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Comparison between data and prediction for the BDT discriminant in the single-lepton resolved SRs after the inclusive fit to the data for $200\le p_T^H<300$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Comparison between data and prediction for the BDT discriminant in the single-lepton resolved SRs after the inclusive fit to the data for $300\le p_T^H<450$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Comparison between data and prediction for the BDT discriminant in the single-lepton resolved SRs after the inclusive fit to the data for $p_{{T}}^{H}\ge 450$ GeV (yield only). The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Comparison between data and prediction for the BDT discriminant in the single-lepton boosted SRs after the inclusive fit to the data for $300\le p_T^H<450$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Comparison between data and prediction for the BDT discriminant in the single-lepton boosted SRs after the inclusive fit to the data for $p_{{T}}^{H}\ge 450$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Comparison between data and prediction for ${\Delta R^{{avg}}_{bb}}$ after the inclusive fit to the data in the single-lepton $CR^{5j}_{{\geq}4b\ lo}$ control region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The first (last) bin includes the underflow (overflow).
Comparison between data and prediction for ${\Delta R^{{avg}}_{bb}}$ after the inclusive fit to the data in the single-lepton $CR^{5j}_{{\geq}4b\ hi}$ control region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The first (last) bin includes the underflow (overflow).
Post-fit yields of signal ($S$) and total background ($B$) as a function of $\log (S/B)$, compared with data. Final-discriminant bins in all dilepton and single-lepton analysis regions are combined into bins of $\log (S/B)$, with the signal normalised to the SM prediction used for the computation of $\log (S/B)$. The signal is then shown normalised to the best-fit value and the SM prediction. The lower frame reports the ratio of data to background, and this is compared with the expected ${t\bar {t}H}$-signal-plus-background yield divided by the background-only yield for the best-fit signal strength (solid red line) and the SM prediction (dashed orange line).
Comparison between data and prediction for the reconstruction BDT score for the Higgs boson candidate identified using Higgs boson information, after the inclusive fit to the data in the dilepton resolved channel for $0\le p_T^H<120$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Comparison between data and prediction for the average $\Delta \eta $ between $b$-tagged jets, after the inclusive fit to the data in the dilepton resolved channel for $0\le p_T^H<120$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Comparison between data and prediction for the likelihood discriminant, after the inclusive fit to the data in the single-lepton resolved channel for $0\le p_T^H<120$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Comparison between data and prediction for the average $\Delta R$ for all possible combinations of $b$-tagged jet pairs, after the inclusive fit to the data in the single-lepton resolved channel for $0\le p_T^H<120$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Comparison between data and prediction for the DNN $P(H)$ output for the Higgs boson candidate after the inclusive fit to the data in the single-lepton boosted channel for $300\le p_T^H<450$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Comparison between data and prediction for the DNN $P(H)$ output for the Higgs boson candidate after the inclusive fit to the data in the single-lepton boosted channel for $p_{{T}}^{H}\ge 450$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Post-fit distribution of the reconstructed Higgs boson candidate mass for the dilepton $SR^{\geq 4j}_{\geq 4b}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The first (last) bin includes the underflow (overflow).
Post-fit distribution of the reconstructed Higgs boson candidate mass for the single-lepton resolved $SR^{\geq 6j}_{\geq 4b}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The first (last) bin includes the underflow (overflow).
Post-fit distribution of the reconstructed Higgs boson candidate mass for the single-lepton boosted ${{SR}_{{boosted}}}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The first (last) bin includes the underflow (overflow).
Fitted values of the ${t\bar {t}H}$ signal strength parameter in the individual channels and in the inclusive signal-strength measurement.
Ranking of the 20 nuisance parameters with the largest post-fit impact on $\mu $ in the fit. Nuisance parameters corresponding to statistical uncertainties in the simulated event samples are not included. The empty blue rectangles correspond to the pre-fit impact on $\mu $ and the filled blue ones to the post-fit impact on $\mu $, both referring to the upper scale. The impact of each nuisance parameter, $\Delta \mu $, is computed by comparing the nominal best-fit value of $\mu $ with the result of the fit when fixing the considered nuisance parameter to its best-fit value, $\hat{\theta }$, shifted by its pre-fit (post-fit) uncertainties $\pm \Delta \theta $ ($\pm \Delta \hat{\theta }$). The black points show the pulls of the nuisance parameters relative to their nominal values, $\theta _0$. These pulls and their relative post-fit errors, $\Delta \hat{\theta }/\Delta \theta $, refer to the lower scale. The `ljets' (`dilep') label refers to the single-lepton (dilepton) channel.
Pre-fit distribution of the number of jets in the dilepton $SR^{\geq 4j}_{\geq 4b}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the Standard Model expectation. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations, except the uncertainty in the $k({t\bar {t}+{\geq }1b})$ normalisation factor that is not defined pre-fit.
Pre-fit distribution of the number of jets in the single-lepton resolved $SR^{\geq 6j}_{\geq 4b}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the Standard Model expectation. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations, except the uncertainty in the $k({t\bar {t}+{\geq }1b})$ normalisation factor that is not defined pre-fit.
Pre-fit distribution of the number of jets in the single-lepton boosted ${{SR}_{{boosted}}}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the Standard Model expectation. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations, except the uncertainty in the $k({t\bar {t}+{\geq }1b})$ normalisation factor that is not defined pre-fit.
Post-fit distribution of the number of jets in the dilepton $SR^{\geq 4j}_{\geq 4b}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Post-fit distribution of the number of jets in the single-lepton resolved $SR^{\geq 6j}_{\geq 4b}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Post-fit distribution of the number of jets in the single-lepton boosted ${{SR}_{{boosted}}}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Post-fit distribution of the reconstructed Higgs boson candidate $p_T^H$ for the dilepton $SR^{\geq 4j}_{\geq 4b}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The last bin includes the overflow.
Post-fit distribution of the reconstructed Higgs boson candidate $p_T^H$ for the single-lepton resolved $SR^{\geq 6j}_{\geq 4b}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The last bin includes the overflow.
Post-fit distribution of the reconstructed Higgs boson candidate $p_T^H$ for the single-lepton boosted ${{SR}_{{boosted}}}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The last bin includes the overflow.
Signal-strength measurements in the individual STXS ${\hat{p}_{{T}}^{H}}$ bins, as well as the inclusive signal strength.
95% CL simplified template cross-section upper limits in the individual STXS ${\hat{p}_{{T}}^{H}}$ bins, as well as the inclusive limit. The observed limits are shown (solid black lines), together with the expected limits both in the background-only hypothesis (dotted black lines) and in the SM hypothesis (dotted red lines). In the case of the expected limits in the background-only hypothesis, one- and two-standard-deviation uncertainty bands are also shown. The hatched uncertainty bands correspond to the theory uncertainty in the fiducial cross-section prediction in each bin.
The ratios $S/B$ (black solid line, referring to the vertical axis on the left) and $S/\sqrt{B}$ (red dashed line, referring to the vertical axis on the right) for each category in the inclusive analysis in the dilepton channel (left) and in the single-lepton channels (right), where $S$ ($B$) is the number of selected signal (background) events predicted by the simulation and normalised to a luminosity of 139 fb$^{-1}$ .
Comparison between data and prediction for the $\Delta R$ between the Higgs candidate and the ${t\bar {t}}$ candidate system, after the inclusive fit to the data in the dilepton resolved channel for $0\le p_T^H<120$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Comparison between data and prediction for the number of $b$-tagged jet pairs with an invariant mass within 30 GeV of 125 GeV, after the inclusive fit to the data in the dilepton resolved channel for $0\le p_T^H<120$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Comparison between data and prediction for the reconstruction BDT score for the Higgs boson candidate identified using Higgs boson information, after the inclusive fit to the data in the single-lepton resolved channel for $0\le p_T^H<120$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Comparison between data and prediction for the $\Delta R$ between the two highest ${p_{{T}}}$ $b$-tagged jets, after the inclusive fit to the data in the single-lepton resolved channel for $0\le p_T^H<120$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Comparison between data and prediction for the sum of $b$-tagging discriminants of jets from Higgs, hadronic top and leptonic top candidates, after the inclusive fit to the data in the single-lepton boosted channel for $300\le p_T^H<450$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The first (last) bin includes the underflow (overflow).
Comparison between data and prediction for the sum of $b$-tagging discriminants of jets from Higgs, hadronic top and leptonic top candidates, after the inclusive fit to the data in the single-lepton boosted channel for $p_{{T}}^{H}\ge 450$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The first (last) bin includes the underflow (overflow).
Comparison between data and prediction for the hadronic top candidate invariant mass, after the inclusive fit to the data in the single-lepton boosted channel for $300\le p_T^H<450$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The first (last) bin includes the underflow (overflow).
Comparison between data and prediction for the hadronic top candidate invariant mass, after the inclusive fit to the data in the single-lepton boosted channel for $p_{{T}}^{H}\ge 450$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The first (last) bin includes the underflow (overflow).
Comparison between data and prediction for the fraction of the sum of $b$-tagging discriminants of all jets not associated to the Higgs or hadronic top candidates, after the inclusive fit to the data in the single-lepton boosted channel for $300\le p_T^H<450$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The first (last) bin includes the underflow (overflow).
Comparison between data and prediction for the fraction of the sum of $b$-tagging discriminants of all jets not associated to the Higgs or hadronic top candidates, after the inclusive fit to the data in the single-lepton boosted channel for $p_{{T}}^{H}\ge 450$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The first (last) bin includes the underflow (overflow).
Ranking of the 20 nuisance parameters with the largest post-fit impact on $\mu $ in the STXS fit for $0\le {\hat{p}_{{T}}^{H}}<120$ GeV. Nuisance parameters corresponding to statistical uncertainties in the simulated event samples are not included. The empty blue rectangles correspond to the pre-fit impact on $\mu $ and the filled blue ones to the post-fit impact on $\mu $, both referring to the upper scale. The impact of each nuisance parameter, $\Delta \mu $, is computed by comparing the nominal best-fit value of $\mu $ with the result of the fit when fixing the considered nuisance parameter to its best-fit value, $\hat{\theta }$, shifted by its pre-fit (post-fit) uncertainties $\pm \Delta \theta $ ($\pm \Delta \hat{\theta }$). The black points show the pulls of the nuisance parameters relative to their nominal values, $\theta _0$. These pulls and their relative post-fit errors, $\Delta \hat{\theta }/\Delta \theta $, refer to the lower scale. For experimental uncertainties that are decomposed into several independent sources, NP X corresponds to the X$^{th}$ nuisance parameter, ordered by their impact on $\mu $. The `ljets' (`dilep') label refers to the single-lepton (dilepton) channel.
Ranking of the 20 nuisance parameters with the largest post-fit impact on $\mu $ in the STXS fit for $120\le {\hat{p}_{{T}}^{H}}<200$ GeV. Nuisance parameters corresponding to statistical uncertainties in the simulated event samples are not included. The empty blue rectangles correspond to the pre-fit impact on $\mu $ and the filled blue ones to the post-fit impact on $\mu $, both referring to the upper scale. The impact of each nuisance parameter, $\Delta \mu $, is computed by comparing the nominal best-fit value of $\mu $ with the result of the fit when fixing the considered nuisance parameter to its best-fit value, $\hat{\theta }$, shifted by its pre-fit (post-fit) uncertainties $\pm \Delta \theta $ ($\pm \Delta \hat{\theta }$). The black points show the pulls of the nuisance parameters relative to their nominal values, $\theta _0$. These pulls and their relative post-fit errors, $\Delta \hat{\theta }/\Delta \theta $, refer to the lower scale. For experimental uncertainties that are decomposed into several independent sources, NP X corresponds to the X$^{th}$ nuisance parameter, ordered by their impact on $\mu $. The `ljets' (`dilep') label refers to the single-lepton (dilepton) channel.
Ranking of the 20 nuisance parameters with the largest post-fit impact on $\mu $ in the STXS fit for $200\le {\hat{p}_{{T}}^{H}}<300$ GeV. Nuisance parameters corresponding to statistical uncertainties in the simulated event samples are not included. The empty blue rectangles correspond to the pre-fit impact on $\mu $ and the filled blue ones to the post-fit impact on $\mu $, both referring to the upper scale. The impact of each nuisance parameter, $\Delta \mu $, is computed by comparing the nominal best-fit value of $\mu $ with the result of the fit when fixing the considered nuisance parameter to its best-fit value, $\hat{\theta }$, shifted by its pre-fit (post-fit) uncertainties $\pm \Delta \theta $ ($\pm \Delta \hat{\theta }$). The black points show the pulls of the nuisance parameters relative to their nominal values, $\theta _0$. These pulls and their relative post-fit errors, $\Delta \hat{\theta }/\Delta \theta $, refer to the lower scale. For experimental uncertainties that are decomposed into several independent sources, NP X corresponds to the X$^{th}$ nuisance parameter, ordered by their impact on $\mu $. The `ljets' (`dilep') label refers to the single-lepton (dilepton) channel.
Ranking of the 20 nuisance parameters with the largest post-fit impact on $\mu $ in the STXS fit for $300\le {\hat{p}_{{T}}^{H}}<450$ GeV. Nuisance parameters corresponding to statistical uncertainties in the simulated event samples are not included. The empty blue rectangles correspond to the pre-fit impact on $\mu $ and the filled blue ones to the post-fit impact on $\mu $, both referring to the upper scale. The impact of each nuisance parameter, $\Delta \mu $, is computed by comparing the nominal best-fit value of $\mu $ with the result of the fit when fixing the considered nuisance parameter to its best-fit value, $\hat{\theta }$, shifted by its pre-fit (post-fit) uncertainties $\pm \Delta \theta $ ($\pm \Delta \hat{\theta }$). The black points show the pulls of the nuisance parameters relative to their nominal values, $\theta _0$. These pulls and their relative post-fit errors, $\Delta \hat{\theta }/\Delta \theta $, refer to the lower scale. For experimental uncertainties that are decomposed into several independent sources, NP X corresponds to the X$^{th}$ nuisance parameter, ordered by their impact on $\mu $. The `ljets' (`dilep') label refers to the single-lepton (dilepton) channel.
Ranking of the 20 nuisance parameters with the largest post-fit impact on $\mu $ in the STXS fit for ${\hat{p}_{{T}}^{H}}\ge 450$ GeV. Nuisance parameters corresponding to statistical uncertainties in the simulated event samples are not included. The empty blue rectangles correspond to the pre-fit impact on $\mu $ and the filled blue ones to the post-fit impact on $\mu $, both referring to the upper scale. The impact of each nuisance parameter, $\Delta \mu $, is computed by comparing the nominal best-fit value of $\mu $ with the result of the fit when fixing the considered nuisance parameter to its best-fit value, $\hat{\theta }$, shifted by its pre-fit (post-fit) uncertainties $\pm \Delta \theta $ ($\pm \Delta \hat{\theta }$). The black points show the pulls of the nuisance parameters relative to their nominal values, $\theta _0$. These pulls and their relative post-fit errors, $\Delta \hat{\theta }/\Delta \theta $, refer to the lower scale. For experimental uncertainties that are decomposed into several independent sources, NP X corresponds to the X$^{th}$ nuisance parameter, ordered by their impact on $\mu $. The `ljets' (`dilep') label refers to the single-lepton (dilepton) channel.
95% confidence level upper limits on signal-strength measurements in the individual STXS ${\hat{p}_{{T}}^{H}}$ bins, as well as the inclusive signal-strength limit, after the fit used to extract multiple signal-strength parameters. The observed limits are shown (solid black lines), together with the expected limits both in the background-only hypothesis (dotted black lines) and in the SM hypothesis (dotted red lines). In the case of the expected limits in the background-only hypothesis, one- and two-standard-deviation uncertainty bands are also shown.
Post-fit correlation matrix (in percentages) between the $\mu $ values obtained in the STXS bins.
Performance of the Higgs boson reconstruction algorithms. For each row of `truth' ${\hat{p}_{{T}}^{H}}$, the matrix shows (in percentages) the fraction of Higgs boson candidates which are truth-matched to ${b\bar {b}}$ decays, with reconstructed $p_T^H$ in the various bins of the dilepton (left), single lepton resolved (middle) and boosted (right) channels.
Pre-fit event yields in the dilepton signal regions and control regions. All uncertainties are included except the $k({t\bar {t}+{\geq }1b})$ uncertainty that is not defined pre-fit. For the ${t\bar {t}H}$ signal, the pre-fit yield values correspond to the theoretical prediction and corresponding uncertainties. `Other sources' refers to s-channel, t-channel, $tW$, $tWZ$, $tZq$, $Z+$ jets and diboson events.
Post-fit event yields in the dilepton signal regions and control regions, after the inclusive fit in all channels. All uncertainties are included, taking into account correlations. For the ${t\bar {t}H}$ signal, the post-fit yield and uncertainties correspond to those in the inclusive signal-strength measurement. `Other sources' refers to s-channel, t-channel, $tW$, $tWZ$, $tZq$, $Z+$ jets and diboson events.
Pre-fit event yields in the single-lepton resolved and boosted signal regions and control regions. All uncertainties are included except the $k({t\bar {t}+{\geq }1b})$ uncertainty that is not defined pre-fit. For the ${t\bar {t}H}$ signal, the pre-fit yield values correspond to the theoretical prediction and corresponding uncertainties. `Other top sources' refers to s-channel, t-channel, $tWZ$ and $tZq$ events.
Post-fit event yields in the single-lepton resolved and boosted signal regions and control regions, after the inclusive fit in all channels. All uncertainties are included, taking into account correlations. For the ${t\bar {t}H}$ signal, the post-fit yield and uncertainties correspond to those in the inclusive signal-strength measurement. `Other top sources' refers to s-channel, t-channel, $tWZ$ and $tZq$ events.
Breakdown of the contributions to the uncertainties in $\mu$. The contributions from the different sources of uncertainty are evaluated after the fit. The $\Delta \mu $ values are obtained by repeating the fit after having fixed a certain set of nuisance parameters corresponding to a group of systematic uncertainties, and then evaluating $(\Delta \mu)^2$ by subtracting the resulting squared uncertainty of $\mu $ from its squared uncertainty found in the full fit. The same procedure is followed when quoting the effect of the ${t\bar {t}+{\geq }1b}$ normalisation. The total uncertainty is different from the sum in quadrature of the different components due to correlations between nuisance parameters existing in the fit.
Fraction (in percentages) of signal events, after SR and CR selections, originating from $b\bar {b}$, $WW$ and other remaining Higgs boson decay modes in the dilepton channel.
Fraction (in percentages) of signal events, after SR and CR selections, originating from $b\bar {b}$, $WW$ and other remaining Higgs boson decay modes in the single-lepton channels.
Predicted SM ${t\bar {t}H}$ cross-section in each of the five STXS ${\hat{p}_{{T}}^{H}}$ bins and signal acceptance times efficiency (including all event selection criteria) in each STXS bin as well as for the inclusive ${\hat{p}_{{T}}^{H}}$ range.
Number of expected signal events before the fit, after each selection requirement applied to enter the dilepton channel $SR^{\geq 4j}_{\geq 4b}$ region. All ${t\bar {t}H}$ signal events are included, regardless of the $H$ or ${t\bar {t}H}$ decay mode. All object corrections are applied, except for the initial number of events which is calculated using the NLO QCD+EW theoretical prediction. All quoted numbers are rounded to unity. More details on the selection criteria can be found in the text.
Number of expected signal events before the fit, after each selection requirement applied to enter the single-lepton channel resolved $SR^{\geq 6j}_{\geq 4b}$ region. All ${t\bar {t}H}$ signal events are included, regardless of the $H$ or ${t\bar {t}H}$ decay mode. All object corrections are applied, except for the initial number of events which is calculated using the NLO QCD+EW theoretical prediction. All quoted numbers are rounded to unity. More details on the selection criteria can be found in the text.
Number of expected signal events before the fit, after each selection requirement applied to enter the single-lepton channel boosted $SR_{boosted}$ region. All ${t\bar {t}H}$ signal events are included, regardless of the $H$ or ${t\bar {t}H}$ decay mode. All object corrections are applied, except for the initial number of events which is calculated using the NLO QCD+EW theoretical prediction. All quoted numbers are rounded to unity. More details on the selection criteria can be found in the text.
The first collider search for dark matter arising from a strongly coupled hidden sector is presented and uses a data sample corresponding to 138 fb$^{-1}$, collected with the CMS detector at the CERN LHC, at $\sqrt{s} =$ 13 TeV. The hidden sector is hypothesized to couple to the standard model (SM) via a heavy leptophobic Z' mediator produced as a resonance in proton-proton collisions. The mediator decay results in two "semivisible" jets, containing both visible matter and invisible dark matter. The final state therefore includes moderate missing energy aligned with one of the jets, a signature ignored by most dark matter searches. No structure in the dijet transverse mass spectra compatible with the signal is observed. Assuming the Z' has a universal coupling of 0.25 to the SM quarks, an inclusive search, relevant to any model that exhibits this kinematic behavior, excludes mediator masses of 1.5-4.0 TeV at 95% confidence level, depending on the other signal model parameters. To enhance the sensitivity of the search for this particular class of hidden sector models, a boosted decision tree (BDT) is trained using jet substructure variables to distinguish between semivisible jets and SM jets from background processes. When the BDT is employed to identify each jet in the dijet system as semivisible, the mediator mass exclusion increases to 5.1 TeV, for wider ranges of the other signal model parameters. These limits exclude a wide range of strongly coupled hidden sector models for the first time.
The normalized distribution of the characteristic variable $R_{\text{T}}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the characteristic variable $R_{\text{T}}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the characteristic variable $R_{\text{T}}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the characteristic variable $\Delta\phi_{\text{min}}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the characteristic variable $\Delta\phi_{\text{min}}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the characteristic variable $\Delta\phi_{\text{min}}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $m_{\text{SD}}$ for the two highest $p_{\text{T}}$ jets from the simulated SM backgrounds and several signal models. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $m_{\text{SD}}$ for the two highest $p_{\text{T}}$ jets from the simulated SM backgrounds and several signal models. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $m_{\text{SD}}$ for the two highest $p_{\text{T}}$ jets from the simulated SM backgrounds and several signal models. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $D_{p_{\text{T}}}$ for the two highest $p_{\text{T}}$ jets from the simulated SM backgrounds and several signal models. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $D_{p_{\text{T}}}$ for the two highest $p_{\text{T}}$ jets from the simulated SM backgrounds and several signal models. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $D_{p_{\text{T}}}$ for the two highest $p_{\text{T}}$ jets from the simulated SM backgrounds and several signal models. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized BDT discriminator distribution for the two highest $p_{\text{T}}$ jets from the simulated SM backgrounds and several signal models.
The normalized BDT discriminator distribution for the two highest $p_{\text{T}}$ jets from the simulated SM backgrounds and several signal models.
The normalized BDT discriminator distribution for the two highest $p_{\text{T}}$ jets from the simulated SM backgrounds and several signal models.
The BDT ROC curves for the two highest $p_{\text{T}}$ jets, comparing the simulated SM backgrounds with one signal model with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$.
The BDT ROC curves for the two highest $p_{\text{T}}$ jets, comparing the simulated SM backgrounds with one signal model with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$.
The BDT ROC curves for the two highest $p_{\text{T}}$ jets, comparing the simulated SM backgrounds with one signal model with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$.
The BDT ROC curves for the two highest $p_{\text{T}}$ jets, comparing the simulated SM backgrounds with one signal model with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$.
The BDT ROC curves for the two highest $p_{\text{T}}$ jets, comparing the simulated SM backgrounds with one signal model with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$.
The BDT ROC curves for the two highest $p_{\text{T}}$ jets, comparing the simulated SM backgrounds with one signal model with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$.
The BDT ROC curves for the two highest $p_{\text{T}}$ jets, comparing the simulated SM backgrounds with one signal model with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$.
The BDT ROC curves for the two highest $p_{\text{T}}$ jets, comparing the simulated SM backgrounds with one signal model with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$.
The BDT ROC curves for the two highest $p_{\text{T}}$ jets, comparing the simulated SM backgrounds with one signal model with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$.
The BDT ROC curves for the two highest $p_{\text{T}}$ jets, comparing the simulated SM backgrounds with one signal model with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$.
The BDT ROC curves for the two highest $p_{\text{T}}$ jets, comparing the simulated SM backgrounds with one signal model with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$.
The BDT ROC curves for the two highest $p_{\text{T}}$ jets, comparing the simulated SM backgrounds with one signal model with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$.
The $m_{\text{T}}$ distribution for the high-$R_{\text{T}}$ signal region, comparing the observed data to the background prediction from the analytic fit ($g_{3}(x) = \exp(p_{1}x)x^{p_{2}(1+p_{3}\ln(x))}$, $x = m_{\text{T}}/\sqrt{s}$). The distributions from several example signal models, with cross sections corresponding to the observed limits, are superimposed.
The $m_{\text{T}}$ distribution for the high-$R_{\text{T}}$ signal region, comparing the observed data to the background prediction from the analytic fit ($g_{3}(x) = \exp(p_{1}x)x^{p_{2}(1+p_{3}\ln(x))}$, $x = m_{\text{T}}/\sqrt{s}$). The distributions from several example signal models, with cross sections corresponding to the observed limits, are superimposed.
The $m_{\text{T}}$ distribution for the high-$R_{\text{T}}$ signal region, comparing the observed data to the background prediction from the analytic fit ($g_{3}(x) = \exp(p_{1}x)x^{p_{2}(1+p_{3}\ln(x))}$, $x = m_{\text{T}}/\sqrt{s}$). The distributions from several example signal models, with cross sections corresponding to the observed limits, are superimposed.
The $m_{\text{T}}$ distribution for the low-$R_{\text{T}}$ signal region, comparing the observed data to the background prediction from the analytic fit ($g_{2}(x) = \exp(p_{1}x)x^{p_{2}}$, $x = m_{\text{T}}/\sqrt{s}$). The distributions from several example signal models, with cross sections corresponding to the observed limits, are superimposed.
The $m_{\text{T}}$ distribution for the low-$R_{\text{T}}$ signal region, comparing the observed data to the background prediction from the analytic fit ($g_{2}(x) = \exp(p_{1}x)x^{p_{2}}$, $x = m_{\text{T}}/\sqrt{s}$). The distributions from several example signal models, with cross sections corresponding to the observed limits, are superimposed.
The $m_{\text{T}}$ distribution for the low-$R_{\text{T}}$ signal region, comparing the observed data to the background prediction from the analytic fit ($g_{2}(x) = \exp(p_{1}x)x^{p_{2}}$, $x = m_{\text{T}}/\sqrt{s}$). The distributions from several example signal models, with cross sections corresponding to the observed limits, are superimposed.
The $m_{\text{T}}$ distribution for the high-SVJ2 signal region, comparing the observed data to the background prediction from the analytic fit ($g_{2}(x) = \exp(p_{1}x)x^{p_{2}}$, $x = m_{\text{T}}/\sqrt{s}$). The distributions from several example signal models, with cross sections corresponding to the observed limits, are superimposed.
The $m_{\text{T}}$ distribution for the high-SVJ2 signal region, comparing the observed data to the background prediction from the analytic fit ($g_{2}(x) = \exp(p_{1}x)x^{p_{2}}$, $x = m_{\text{T}}/\sqrt{s}$). The distributions from several example signal models, with cross sections corresponding to the observed limits, are superimposed.
The $m_{\text{T}}$ distribution for the high-SVJ2 signal region, comparing the observed data to the background prediction from the analytic fit ($g_{2}(x) = \exp(p_{1}x)x^{p_{2}}$, $x = m_{\text{T}}/\sqrt{s}$). The distributions from several example signal models, with cross sections corresponding to the observed limits, are superimposed.
The $m_{\text{T}}$ distribution for the low-SVJ2 signal region, comparing the observed data to the background prediction from the analytic fit ($g_{2}(x) = \exp(p_{1}x)x^{p_{2}}$, $x = m_{\text{T}}/\sqrt{s}$). The distributions from several example signal models, with cross sections corresponding to the observed limits, are superimposed.
The $m_{\text{T}}$ distribution for the low-SVJ2 signal region, comparing the observed data to the background prediction from the analytic fit ($g_{2}(x) = \exp(p_{1}x)x^{p_{2}}$, $x = m_{\text{T}}/\sqrt{s}$). The distributions from several example signal models, with cross sections corresponding to the observed limits, are superimposed.
The $m_{\text{T}}$ distribution for the low-SVJ2 signal region, comparing the observed data to the background prediction from the analytic fit ($g_{2}(x) = \exp(p_{1}x)x^{p_{2}}$, $x = m_{\text{T}}/\sqrt{s}$). The distributions from several example signal models, with cross sections corresponding to the observed limits, are superimposed.
The 95% CL observed upper limits on the product of the cross section and branching fraction from the inclusive search for variations of the mediator mass and the dark hadron mass.
The 95% CL observed upper limits on the product of the cross section and branching fraction from the inclusive search for variations of the mediator mass and the dark hadron mass.
The 95% CL observed upper limits on the product of the cross section and branching fraction from the inclusive search for variations of the mediator mass and the dark hadron mass.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The 95% CL observed upper limits on the product of the cross section and branching fraction from the inclusive search for variations of the mediator mass and the invisible fraction.
The 95% CL observed upper limits on the product of the cross section and branching fraction from the inclusive search for variations of the mediator mass and the invisible fraction.
The 95% CL observed upper limits on the product of the cross section and branching fraction from the inclusive search for variations of the mediator mass and the invisible fraction.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The 95% CL observed upper limits on the product of the cross section and branching fraction from the BDT-based search for variations of the mediator mass and the dark hadron mass.
The 95% CL observed upper limits on the product of the cross section and branching fraction from the BDT-based search for variations of the mediator mass and the dark hadron mass.
The 95% CL observed upper limits on the product of the cross section and branching fraction from the BDT-based search for variations of the mediator mass and the dark hadron mass.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The 95% CL observed upper limits on the product of the cross section and branching fraction from the BDT-based search for variations of the mediator mass and the invisible fraction.
The 95% CL observed upper limits on the product of the cross section and branching fraction from the BDT-based search for variations of the mediator mass and the invisible fraction.
The 95% CL observed upper limits on the product of the cross section and branching fraction from the BDT-based search for variations of the mediator mass and the invisible fraction.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The observed exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 68% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The lower 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The upper 95% expected exclusion for the nominal $\text{Z}^{\prime}$ cross section.
The 95% CL upper limits on the product of the cross section and branching fraction from the inclusive search for the $\alpha_{\text{dark}}$ variations.
The 95% CL upper limits on the product of the cross section and branching fraction from the inclusive search for the $\alpha_{\text{dark}}$ variations.
The 95% CL upper limits on the product of the cross section and branching fraction from the inclusive search for the $\alpha_{\text{dark}}$ variations.
The 95% CL upper limits on the product of the cross section and branching fraction from the BDT-based search for the $\alpha_{\text{dark}}$ variations.
The 95% CL upper limits on the product of the cross section and branching fraction from the BDT-based search for the $\alpha_{\text{dark}}$ variations.
The 95% CL upper limits on the product of the cross section and branching fraction from the BDT-based search for the $\alpha_{\text{dark}}$ variations.
The three two-dimensional signal model parameter scans.
The three two-dimensional signal model parameter scans.
The three two-dimensional signal model parameter scans.
Metrics representing the performance of the BDT for the benchmark signal model ($m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$), compared to each of the major SM background processes.
Metrics representing the performance of the BDT for the benchmark signal model ($m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$), compared to each of the major SM background processes.
Metrics representing the performance of the BDT for the benchmark signal model ($m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$), compared to each of the major SM background processes.
The range of effects on the signal yield for each systematic uncertainty and the total. Values less than 0.01% are rounded to 0.0%.
The range of effects on the signal yield for each systematic uncertainty and the total. Values less than 0.01% are rounded to 0.0%.
The range of effects on the signal yield for each systematic uncertainty and the total. Values less than 0.01% are rounded to 0.0%.
The normalized distribution of the variable $m_{\text{T}}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the variable $m_{\text{T}}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the variable $m_{\text{T}}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the variable $\Delta\eta(\text{J}_{1},\text{J}_{2})$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the variable $\Delta\eta(\text{J}_{1},\text{J}_{2})$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the variable $\Delta\eta(\text{J}_{1},\text{J}_{2})$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the variable $p_{\text{T}}^{\text{miss}}$ for the simulated SM backgrounds and several signal models. The $R_{\text{T}}$ requirement is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the variable $p_{\text{T}}^{\text{miss}}$ for the simulated SM backgrounds and several signal models. The $R_{\text{T}}$ requirement is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the variable $p_{\text{T}}^{\text{miss}}$ for the simulated SM backgrounds and several signal models. The $R_{\text{T}}$ requirement is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the variable $N_{\text{e}}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the variable $N_{\text{e}}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the variable $N_{\text{e}}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the variable $N_{\mu}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the variable $N_{\mu}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of the variable $N_{\mu}$ for the simulated SM backgrounds and several signal models. The requirement on this variable is omitted, but all other preselection requirements are applied. The last bin of each histogram includes the overflow events.
The normalized distribution of $\Delta\eta(\text{J}_{1},\text{J}_{2})$ vs. $R_{\text{T}}$ for the simulated QCD background. The preselection requirements on both variables are omitted, but all other preselection requirements are applied.
The normalized distribution of $\Delta\eta(\text{J}_{1},\text{J}_{2})$ vs. $R_{\text{T}}$ for the simulated QCD background. The preselection requirements on both variables are omitted, but all other preselection requirements are applied.
The normalized distribution of $\Delta\eta(\text{J}_{1},\text{J}_{2})$ vs. $R_{\text{T}}$ for the simulated QCD background. The preselection requirements on both variables are omitted, but all other preselection requirements are applied.
The normalized distribution of $p_{\text{T}}^{\text{miss}}$ vs. $m_{\text{T}}$ for the simulated QCD background. All selection requirements are omitted, except for the requirement of two high-$p_{\text{T}}$ wide jets.
The normalized distribution of $p_{\text{T}}^{\text{miss}}$ vs. $m_{\text{T}}$ for the simulated QCD background. All selection requirements are omitted, except for the requirement of two high-$p_{\text{T}}$ wide jets.
The normalized distribution of $p_{\text{T}}^{\text{miss}}$ vs. $m_{\text{T}}$ for the simulated QCD background. All selection requirements are omitted, except for the requirement of two high-$p_{\text{T}}$ wide jets.
The normalized distribution of $R_{\text{T}}$ vs. $m_{\text{T}}$ for the simulated QCD background. All selection requirements are omitted, except for the requirement of two high-$p_{\text{T}}$ wide jets.
The normalized distribution of $R_{\text{T}}$ vs. $m_{\text{T}}$ for the simulated QCD background. All selection requirements are omitted, except for the requirement of two high-$p_{\text{T}}$ wide jets.
The normalized distribution of $R_{\text{T}}$ vs. $m_{\text{T}}$ for the simulated QCD background. All selection requirements are omitted, except for the requirement of two high-$p_{\text{T}}$ wide jets.
The normalized distributions of the BDT input variable $\tau_{21}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{dark}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $\tau_{21}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{dark}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $\tau_{21}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{dark}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $\tau_{32}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{dark}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $\tau_{32}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{dark}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $\tau_{32}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{dark}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $N_{2}^{(1)}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{dark}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $N_{2}^{(1)}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{dark}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $N_{2}^{(1)}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{dark}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $N_{3}^{(1)}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{dark}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $N_{3}^{(1)}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{dark}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $N_{3}^{(1)}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{dark}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $g_{\text{jet}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $r_{\text{inv}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $g_{\text{jet}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $r_{\text{inv}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $g_{\text{jet}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $r_{\text{inv}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $\sigma_{\text{major}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $r_{\text{inv}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $\sigma_{\text{major}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $r_{\text{inv}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $\sigma_{\text{major}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $r_{\text{inv}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $\sigma_{\text{minor}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $r_{\text{inv}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $\sigma_{\text{minor}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $r_{\text{inv}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $\sigma_{\text{minor}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $r_{\text{inv}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $\Delta\phi(\vec{J},\vec{p}_{\text{T}}^{\text{miss}})$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $r_{\text{inv}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $\Delta\phi(\vec{J},\vec{p}_{\text{T}}^{\text{miss}})$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $r_{\text{inv}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $\Delta\phi(\vec{J},\vec{p}_{\text{T}}^{\text{miss}})$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $r_{\text{inv}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $f_{\text{h}^{\pm}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $f_{\text{h}^{\pm}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $f_{\text{h}^{\pm}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $f_{\text{e}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $f_{\text{e}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $f_{\text{e}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $f_{\mu}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $f_{\mu}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $f_{\mu}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $f_{\text{h}^{0}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $f_{\text{h}^{0}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $f_{\text{h}^{0}}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $f_{\gamma}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $f_{\gamma}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The normalized distributions of the BDT input variable $f_{\gamma}$ for the two highest $p_{\text{T}}$ wide jets from the simulated SM backgrounds and several signal models with varying $m_{\text{Z}^{\prime}}$ values. Each sample's jet $p_{\text{T}}$ distribution is weighted to match a reference distribution (see text). The last bin of each histogram includes the overflow events.
The product of signal acceptance and efficiency in the high-$R_{\text{T}}$ signal region, for variations of the mediator mass and the dark hadron mass.
The product of signal acceptance and efficiency in the high-$R_{\text{T}}$ signal region, for variations of the mediator mass and the dark hadron mass.
The product of signal acceptance and efficiency in the high-$R_{\text{T}}$ signal region, for variations of the mediator mass and the dark hadron mass.
The product of signal acceptance and efficiency in the high-$R_{\text{T}}$ signal region, for variations of the mediator mass and the invisible fraction.
The product of signal acceptance and efficiency in the high-$R_{\text{T}}$ signal region, for variations of the mediator mass and the invisible fraction.
The product of signal acceptance and efficiency in the high-$R_{\text{T}}$ signal region, for variations of the mediator mass and the invisible fraction.
The product of signal acceptance and efficiency in the high-$R_{\text{T}}$ signal region, for variations of the mediator mass and the dark coupling strength.
The product of signal acceptance and efficiency in the high-$R_{\text{T}}$ signal region, for variations of the mediator mass and the dark coupling strength.
The product of signal acceptance and efficiency in the high-$R_{\text{T}}$ signal region, for variations of the mediator mass and the dark coupling strength.
The product of signal acceptance and efficiency in the low-$R_{\text{T}}$ signal region, for variations of the mediator mass and the dark hadron mass.
The product of signal acceptance and efficiency in the low-$R_{\text{T}}$ signal region, for variations of the mediator mass and the dark hadron mass.
The product of signal acceptance and efficiency in the low-$R_{\text{T}}$ signal region, for variations of the mediator mass and the dark hadron mass.
The product of signal acceptance and efficiency in the low-$R_{\text{T}}$ signal region, for variations of the mediator mass and the invisible fraction.
The product of signal acceptance and efficiency in the low-$R_{\text{T}}$ signal region, for variations of the mediator mass and the invisible fraction.
The product of signal acceptance and efficiency in the low-$R_{\text{T}}$ signal region, for variations of the mediator mass and the invisible fraction.
The product of signal acceptance and efficiency in the low-$R_{\text{T}}$ signal region, for variations of the mediator mass and the dark coupling strength.
The product of signal acceptance and efficiency in the low-$R_{\text{T}}$ signal region, for variations of the mediator mass and the dark coupling strength.
The product of signal acceptance and efficiency in the low-$R_{\text{T}}$ signal region, for variations of the mediator mass and the dark coupling strength.
The product of signal acceptance and efficiency in the high-SVJ2 signal region, for variations of the mediator mass and the dark hadron mass.
The product of signal acceptance and efficiency in the high-SVJ2 signal region, for variations of the mediator mass and the dark hadron mass.
The product of signal acceptance and efficiency in the high-SVJ2 signal region, for variations of the mediator mass and the dark hadron mass.
The product of signal acceptance and efficiency in the high-SVJ2 signal region, for variations of the mediator mass and the invisible fraction.
The product of signal acceptance and efficiency in the high-SVJ2 signal region, for variations of the mediator mass and the invisible fraction.
The product of signal acceptance and efficiency in the high-SVJ2 signal region, for variations of the mediator mass and the invisible fraction.
The product of signal acceptance and efficiency in the high-SVJ2 signal region, for variations of the mediator mass and the dark coupling strength.
The product of signal acceptance and efficiency in the high-SVJ2 signal region, for variations of the mediator mass and the dark coupling strength.
The product of signal acceptance and efficiency in the high-SVJ2 signal region, for variations of the mediator mass and the dark coupling strength.
The product of signal acceptance and efficiency in the low-SVJ2 signal region, for variations of the mediator mass and the dark hadron mass.
The product of signal acceptance and efficiency in the low-SVJ2 signal region, for variations of the mediator mass and the dark hadron mass.
The product of signal acceptance and efficiency in the low-SVJ2 signal region, for variations of the mediator mass and the dark hadron mass.
The product of signal acceptance and efficiency in the low-SVJ2 signal region, for variations of the mediator mass and the invisible fraction.
The product of signal acceptance and efficiency in the low-SVJ2 signal region, for variations of the mediator mass and the invisible fraction.
The product of signal acceptance and efficiency in the low-SVJ2 signal region, for variations of the mediator mass and the invisible fraction.
The product of signal acceptance and efficiency in the low-SVJ2 signal region, for variations of the mediator mass and the dark coupling strength.
The product of signal acceptance and efficiency in the low-SVJ2 signal region, for variations of the mediator mass and the dark coupling strength.
The product of signal acceptance and efficiency in the low-SVJ2 signal region, for variations of the mediator mass and the dark coupling strength.
Comparison of different the dijet mass $m_{\text{J}\text{J}}$, the transverse mass $m_{\text{T}}$, and the Monte Carlo (MC) mass $m_{\text{MC}}$ for a signal model with $m_{\text{Z}^{\prime}} = 2.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. No selection is applied, except that there must be at least two jets. $m_{\text{MC}}$ is computed by adding the generator-level four-vectors for invisible particles to the dijet system, to represent the achievable resolution if the invisible component were fully measured. The last bin of each histogram includes the overflow events.
Comparison of different the dijet mass $m_{\text{J}\text{J}}$, the transverse mass $m_{\text{T}}$, and the Monte Carlo (MC) mass $m_{\text{MC}}$ for a signal model with $m_{\text{Z}^{\prime}} = 2.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. No selection is applied, except that there must be at least two jets. $m_{\text{MC}}$ is computed by adding the generator-level four-vectors for invisible particles to the dijet system, to represent the achievable resolution if the invisible component were fully measured. The last bin of each histogram includes the overflow events.
Comparison of different the dijet mass $m_{\text{J}\text{J}}$, the transverse mass $m_{\text{T}}$, and the Monte Carlo (MC) mass $m_{\text{MC}}$ for a signal model with $m_{\text{Z}^{\prime}} = 2.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. No selection is applied, except that there must be at least two jets. $m_{\text{MC}}$ is computed by adding the generator-level four-vectors for invisible particles to the dijet system, to represent the achievable resolution if the invisible component were fully measured. The last bin of each histogram includes the overflow events.
$m_{\text{T}}$ distributions for signal models with different $m_{\text{dark}}$ values for the high-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $m_{\text{dark}}$ values for the high-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $m_{\text{dark}}$ values for the high-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $m_{\text{dark}}$ values for the low-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $m_{\text{dark}}$ values for the low-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $m_{\text{dark}}$ values for the low-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $r_{\text{inv}}$ values for the high-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $r_{\text{inv}}$ values for the high-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $r_{\text{inv}}$ values for the high-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $r_{\text{inv}}$ values for the low-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $r_{\text{inv}}$ values for the low-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $r_{\text{inv}}$ values for the low-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $\alpha_{\text{dark}}$ values for the high-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $\alpha_{\text{dark}}$ values for the high-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $\alpha_{\text{dark}}$ values for the high-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $\alpha_{\text{dark}}$ values for the low-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $\alpha_{\text{dark}}$ values for the low-$R_{\text{T}}$ inclusive signal region.
$m_{\text{T}}$ distributions for signal models with different $\alpha_{\text{dark}}$ values for the low-$R_{\text{T}}$ inclusive signal region.
The proportions of each SM background process in the high-$R_{\text{T}}$ signal region.
The proportions of each SM background process in the high-$R_{\text{T}}$ signal region.
The proportions of each SM background process in the high-$R_{\text{T}}$ signal region.
The proportions of each SM background process in the low-$R_{\text{T}}$ signal region.
The proportions of each SM background process in the low-$R_{\text{T}}$ signal region.
The proportions of each SM background process in the low-$R_{\text{T}}$ signal region.
The proportions of each SM background process in the high-SVJ2 signal region.
The proportions of each SM background process in the high-SVJ2 signal region.
The proportions of each SM background process in the high-SVJ2 signal region.
The proportions of each SM background process in the low-SVJ2 signal region.
The proportions of each SM background process in the low-SVJ2 signal region.
The proportions of each SM background process in the low-SVJ2 signal region.
The 95% CL expected upper limits on the product of the cross section and branching fraction from the inclusive search for variations of the mediator mass and the dark hadron mass.
The 95% CL expected upper limits on the product of the cross section and branching fraction from the inclusive search for variations of the mediator mass and the dark hadron mass.
The 95% CL expected upper limits on the product of the cross section and branching fraction from the inclusive search for variations of the mediator mass and the dark hadron mass.
The 95% CL expected upper limits on the product of the cross section and branching fraction from the inclusive search for variations of the mediator mass and the invisible fraction.
The 95% CL expected upper limits on the product of the cross section and branching fraction from the inclusive search for variations of the mediator mass and the invisible fraction.
The 95% CL expected upper limits on the product of the cross section and branching fraction from the inclusive search for variations of the mediator mass and the invisible fraction.
The 95% CL expected upper limits on the product of the cross section and branching fraction from the BDT-based search for variations of the mediator mass and the dark hadron mass.
The 95% CL expected upper limits on the product of the cross section and branching fraction from the BDT-based search for variations of the mediator mass and the dark hadron mass.
The 95% CL expected upper limits on the product of the cross section and branching fraction from the BDT-based search for variations of the mediator mass and the dark hadron mass.
The 95% CL expected upper limits on the product of the cross section and branching fraction from the BDT-based search for variations of the mediator mass and the invisible fraction.
The 95% CL expected upper limits on the product of the cross section and branching fraction from the BDT-based search for variations of the mediator mass and the invisible fraction.
The 95% CL expected upper limits on the product of the cross section and branching fraction from the BDT-based search for variations of the mediator mass and the invisible fraction.
Relative efficiencies in % for each step of the event selection process for the major background processes. Statistical uncertainties, at most 1.8%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for the major background processes. Statistical uncertainties, at most 1.8%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for the major background processes. Statistical uncertainties, at most 1.8%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 2.1\,\text{TeV}$, varying $m_{\text{dark}}$ values, $r_{\text{inv}} = 0.3$, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 0.5%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 2.1\,\text{TeV}$, varying $m_{\text{dark}}$ values, $r_{\text{inv}} = 0.3$, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 0.5%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 2.1\,\text{TeV}$, varying $m_{\text{dark}}$ values, $r_{\text{inv}} = 0.3$, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 0.5%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, varying $m_{\text{dark}}$ values, $r_{\text{inv}} = 0.3$, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, varying $m_{\text{dark}}$ values, $r_{\text{inv}} = 0.3$, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, varying $m_{\text{dark}}$ values, $r_{\text{inv}} = 0.3$, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 4.1\,\text{TeV}$, varying $m_{\text{dark}}$ values, $r_{\text{inv}} = 0.3$, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 4.1\,\text{TeV}$, varying $m_{\text{dark}}$ values, $r_{\text{inv}} = 0.3$, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 4.1\,\text{TeV}$, varying $m_{\text{dark}}$ values, $r_{\text{inv}} = 0.3$, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 2.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, varying $r_{\text{inv}}$ values, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 2.6%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 2.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, varying $r_{\text{inv}}$ values, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 2.6%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 2.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, varying $r_{\text{inv}}$ values, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 2.6%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, varying $r_{\text{inv}}$ values, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 1.2%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, varying $r_{\text{inv}}$ values, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 1.2%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, varying $r_{\text{inv}}$ values, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 1.2%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 4.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, varying $r_{\text{inv}}$ values, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 0.9%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 4.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, varying $r_{\text{inv}}$ values, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 0.9%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 4.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, varying $r_{\text{inv}}$ values, and $\alpha_{\text{dark}} = \alpha_{\text{dark}}^{\text{peak}}$. Statistical uncertainties, at most 0.9%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 2.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, and varying $\alpha_{\text{dark}}$ values. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 2.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, and varying $\alpha_{\text{dark}}$ values. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 2.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, and varying $\alpha_{\text{dark}}$ values. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, and varying $\alpha_{\text{dark}}$ values. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, and varying $\alpha_{\text{dark}}$ values. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 3.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, and varying $\alpha_{\text{dark}}$ values. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 4.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, and varying $\alpha_{\text{dark}}$ values. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 4.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, and varying $\alpha_{\text{dark}}$ values. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
Relative efficiencies in % for each step of the event selection process for signals with $m_{\text{Z}^{\prime}} = 4.1\,\text{TeV}$, $m_{\text{dark}} = 20\,\text{GeV}$, $r_{\text{inv}} = 0.3$, and varying $\alpha_{\text{dark}}$ values. Statistical uncertainties, at most 0.4%, are omitted. The line "Efficiency [%]" is the absolute efficiency after the final selection. The subsequent lines show the efficiency for each signal region, relative to the final selection.
A search is presented for single production of a vector-like T quark with charge 2/3 $e$, in the decay channel featuring a top quark and a Z boson, with the top quark decaying hadronically and the Z boson decaying to neutrinos. The search uses data collected by the CMS experiment in proton-proton collisions at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 137 fb$^{-1}$ recorded at the CERN LHC in 2016-2018. The search is sensitive to a T quark mass between 0.6 and 1.8 TeV with decay widths ranging from negligibly small up to 30% of the T quark mass. Reconstruction strategies for the top quark are based on the degree of Lorentz boosting of its final state. At 95% confidence level, the upper limit on the product of the cross section and branching fraction for a T quark of small decay width varies between 15 and 602 fb, depending on its mass. For a T quark with decay widths between 10 and 30% of its mass, this upper limit ranges between 16 and 836 fb. For most of the studied range, the results provide the best limits to date. This is the first search for single T quark production based on the full Run 2 data set of the LHC.
Product of efficiency and acceptance of the event selection for T signal events as a function of the particle mass $m_\mathrm{T}$ and width $\Gamma$ for the different hypotheses considered.
Product of efficiency and acceptance of the event selection for T signal events as a function of the particle mass $m_\mathrm{T}$ and width $\Gamma$ for the different hypotheses considered.
Product of efficiency and acceptance of the event selection for T signal events as a function of the particle mass $m_\mathrm{T}$ and width $\Gamma$ for the different hypotheses considered.
Product of efficiency and acceptance of the event selection for T signal events as a function of the particle mass $m_\mathrm{T}$ and width $\Gamma$ for the different hypotheses considered.
Product of efficiency and acceptance of the event selection for T signal events as a function of the particle mass $m_\mathrm{T}$ and width $\Gamma$ for the different hypotheses considered.
Product of efficiency and acceptance of the event selection for T signal events as a function of the particle mass $m_\mathrm{T}$ and width $\Gamma$ for the different hypotheses considered.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the merged validation region with 0 forward jets. Data are compared to backgrounds are after the data-driven extraction is performed.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the merged validation region with at least 1 forward jet. Data are compared to backgrounds are after the data-driven extraction is performed.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the merged validation region with 0 forward jets. Data are compared to backgrounds are after the data-driven extraction is performed.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the merged validation region with at least 1 forward jet. Data are compared to backgrounds are after the data-driven extraction is performed.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the merged validation region with 0 forward jets. Data are compared to backgrounds are after the data-driven extraction is performed.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the merged validation region with at least 1 forward jet. Data are compared to backgrounds are after the data-driven extraction is performed.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the resolved validation region with 0 forward jets. Data are compared to backgrounds are after the data-driven extraction is performed.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the resolved validation region with at least 1 forward jet. Data are compared to backgrounds are after the data-driven extraction is performed.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the resolved validation region with 0 forward jets. Data are compared to backgrounds are after the data-driven extraction is performed.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the resolved validation region with at least 1 forward jet. Data are compared to backgrounds are after the data-driven extraction is performed.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the resolved validation region with 0 forward jets. Data are compared to backgrounds are after the data-driven extraction is performed.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the resolved validation region with at least 1 forward jet. Data are compared to backgrounds are after the data-driven extraction is performed.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the merged region with 0 forward jets. Data are compared to backgrounds obtained post-fit.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the merged region with at least 1 forward jet. Data are compared to backgrounds obtained post-fit.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the merged region with 0 forward jets. Data are compared to backgrounds obtained post-fit.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the merged region with at least 1 forward jet. Data are compared to backgrounds obtained post-fit.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the merged region with 0 forward jets. Data are compared to backgrounds obtained post-fit.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the merged region with at least 1 forward jet. Data are compared to backgrounds obtained post-fit.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the partially merged region with 0 forward jets. Data are compared to backgrounds obtained post-fit.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the partially merged region with at least 1 forward jet. Data are compared to backgrounds obtained post-fit.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the partially merged region with 0 forward jets. Data are compared to backgrounds obtained post-fit.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the partially merged region with at least 1 forward jet. Data are compared to backgrounds obtained post-fit.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the partially merged region with 0 forward jets. Data are compared to backgrounds obtained post-fit.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the partially merged region with at least 1 forward jet. Data are compared to backgrounds obtained post-fit.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the resolved region with 0 forward jets. Data are compared to backgrounds obtained post-fit.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the resolved region with at least 1 forward jet. Data are compared to backgrounds obtained post-fit.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the resolved region with 0 forward jets. Data are compared to backgrounds obtained post-fit.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the resolved region with at least 1 forward jet. Data are compared to backgrounds obtained post-fit.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the resolved region with 0 forward jets. Data are compared to backgrounds obtained post-fit.
Distribution of the transverse mass $M_T$ reconstructed from the top quark and the missing transverse energy in the resolved region with at least 1 forward jet. Data are compared to backgrounds obtained post-fit.
Observed and expected 95% CL upper limits on the product of the cross section and branching fraction of a T decaying to a hadronic top quark and a Z boson to neutrinos as a function of the T mass, for a T with a width of 0.01 $ imes$ its mass.
Observed and expected 95% CL upper limits on the product of the cross section and branching fraction of a T decaying to a hadronic top quark and a Z boson to neutrinos as a function of the T mass, for a T with a width of 0.1 $ imes$ its mass.
Observed and expected 95% CL upper limits on the product of the cross section and branching fraction of a T decaying to a hadronic top quark and a Z boson to neutrinos as a function of the T mass, for a T with a width of 0.2 $ imes$ its mass.
Observed and expected 95% CL upper limits on the product of the cross section and branching fraction of a T decaying to a hadronic top quark and a Z boson to neutrinos as a function of the T mass, for a T with a width of 0.3 $ imes$ its mass.
Model independent observed 95% CL upper limits on the product of the cross section and branching fraction of a T decaying to a top quark and a Z boson as a function of the T mass and width.
Singlet model 95% CL excluded values of the product of the cross section and branching fraction for a T decaying to a top quark and a Z boson.
A search is reported for pairs of light Higgs bosons (H$_1$) produced in supersymmetric cascade decays in final states with small missing transverse momentum. A data set of LHC pp collisions collected with the CMS detector at $\sqrt{s}$ = 13 TeV and corresponding to an integrated luminosity of 138 fb$^{-1}$ is used. The search targets events where both H$_1$ bosons decay into $\mathrm{b\bar{b}}$ pairs that are reconstructed as large-radius jets using substructure techniques. No evidence is found for an excess of events beyond the background expectations of the standard model (SM). Results from the search are interpreted in the next-to-minimal supersymmetric extension of the SM, where a "singlino" of small mass leads to squark and gluino cascade decays that can predominantly end in a highly Lorentz-boosted singlet-like H$_1$ and a singlino-like neutralino of small transverse momentum. Upper limits are set on the product of the squark or gluino pair production cross section and the square of the $\mathrm{b\bar{b}}$ branching fraction of the H$_1$ in a benchmark model containing almost mass-degenerate gluinos and light-flavour squarks. Under the assumption of an SM-like H$_1$$\to$$\mathrm{b\bar{b}}$ branching fraction, H$_1$ bosons with masses in the range 40-120 GeV arising from the decays of squarks or gluinos with a mass of 1200 to 2500 GeV are excluded at 95% confidence level.
Reference acceptance times efficiency values for the kinematic selection and $H_T>3500\;\mathrm{GeV}$ requirements ($A_{\mathrm{kin}}$) for the benchmark signal model with different values of $m_{\mathrm{SUSY}}$. These values are independent of $m_{\mathrm{H_1}}$ within 2% in the range $30 \le m_{\mathrm{H_1}} \le 125\;\mathrm{GeV}$.
Upper limits at 95% CL on $\sigma\times\mathcal{B}^2(\mathrm{H}_1\rightarrow b\bar{b}) \times A_{\mathrm{kin}}$ as a function of $m_{\mathrm{H_1}}$. The results are independent of $m_{\mathrm{SUSY}}$ within 10% in the range $1600<m_{\mathrm{SUSY}}<2800\;\mathrm{GeV}$.
Upper limits at 95% CL on $\sigma\times\mathcal{B}^2(\mathrm{H}_1\rightarrow b\bar{b})$ as a function of $m_{\mathrm{H_1}}$ for $m_{\mathrm{SUSY}}=1200\;\mathrm{GeV}$.
Upper limits at 95% CL on $\sigma\times\mathcal{B}^2(\mathrm{H}_1\rightarrow b\bar{b})$ as a function of $m_{\mathrm{H_1}}$ for $m_{\mathrm{SUSY}}=1600\;\mathrm{GeV}$.
Upper limits at 95% CL on $\sigma\times\mathcal{B}^2(\mathrm{H}_1\rightarrow b\bar{b})$ as a function of $m_{\mathrm{H_1}}$ for $m_{\mathrm{SUSY}}=2000\;\mathrm{GeV}$.
Upper limits at 95% CL on $\sigma\times\mathcal{B}^2(\mathrm{H}_1\rightarrow b\bar{b})$ as a function of $m_{\mathrm{H_1}}$ for $m_{\mathrm{SUSY}}=2200\;\mathrm{GeV}$.
Upper limits at 95% CL on $\sigma\times\mathcal{B}^2(\mathrm{H}_1\rightarrow b\bar{b})$ as a function of $m_{\mathrm{H_1}}$ for $m_{\mathrm{SUSY}}=2400\;\mathrm{GeV}$.
Upper limits at 95% CL on $\sigma\times\mathcal{B}^2(\mathrm{H}_1\rightarrow b\bar{b})$ as a function of $m_{\mathrm{H_1}}$ for $m_{\mathrm{SUSY}}=2600\;\mathrm{GeV}$.
Upper limits at 95% CL on $\sigma\times\mathcal{B}^2(\mathrm{H}_1\rightarrow b\bar{b})$ as a function of $m_{\mathrm{H_1}}$ for $m_{\mathrm{SUSY}}=2800\;\mathrm{GeV}$.
A search for new phenomena has been performed in final states with at least one isolated high-momentum photon, jets and missing transverse momentum in proton--proton collisions at a centre-of-mass energy of $\sqrt{s} = 13$ TeV. The data, collected by the ATLAS experiment at the CERN LHC, correspond to an integrated luminosity of 139 $fb^{-1}$. The experimental results are interpreted in a supersymmetric model in which pair-produced gluinos decay into neutralinos, which in turn decay into a gravitino, at least one photon, and jets. No significant deviations from the predictions of the Standard Model are observed. Upper limits are set on the visible cross section due to physics beyond the Standard Model, and lower limits are set on the masses of the gluinos and neutralinos, all at 95% confidence level. Visible cross sections greater than 0.022 fb are excluded and pair-produced gluinos with masses up to 2200 GeV are excluded for most of the NLSP masses investigated.
The observed and expected (post-fit) yields in the control and validation regions. The lower panel shows the difference in standard deviations between the observed and expected yields, considering both the systematic and statistical uncertainties on the background expectation.
Observed (points with error bars) and expected background (solid histograms) distributions for $E_{T}^{miss}$ in the signal region (a) SRL, (b) SRM and (c) SRH after the background-only fit applied to the CRs. The predicted signal distributions for the two models with a gluino mass of 2000 GeV and neutralino mass of 250 GeV (SRL), 1050 GeV (SRM) or 1950 GeV (SRH) are also shown for comparison. The uncertainties in the SM background are only statistical.
Observed (points with error bars) and expected background (solid histograms) distributions for $E_{T}^{miss}$ in the signal region (a) SRL, (b) SRM and (c) SRH after the background-only fit applied to the CRs. The predicted signal distributions for the two models with a gluino mass of 2000 GeV and neutralino mass of 250 GeV (SRL), 1050 GeV (SRM) or 1950 GeV (SRH) are also shown for comparison. The uncertainties in the SM background are only statistical.
Observed (points with error bars) and expected background (solid histograms) distributions for $E_{T}^{miss}$ in the signal region (a) SRL, (b) SRM and (c) SRH after the background-only fit applied to the CRs. The predicted signal distributions for the two models with a gluino mass of 2000 GeV and neutralino mass of 250 GeV (SRL), 1050 GeV (SRM) or 1950 GeV (SRH) are also shown for comparison. The uncertainties in the SM background are only statistical.
Observed and expected exclusion limit in the gluino-neutralino mass plane at 95% CL combined using the signal region with the best expected sensitivity at each point, for the full Run-2 dataset corresponding to an integrated luminosity of $139~\mathrm{fb}^{-1}$, for $\gamma/Z$ (a) and $\gamma/h$ (b) signal models. The black solid line corresponds to the expected limits at 95% CL, with the light (yellow) bands indicating the 1$\sigma$ exclusions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves, the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties. For each point in the higgsino-bino parameter space, the labels indicate the best-expected signal region, where L, M and H mean SRL, SRM and SRH, respectively.
Observed and expected exclusion limit in the gluino-neutralino mass plane at 95% CL combined using the signal region with the best expected sensitivity at each point, for the full Run-2 dataset corresponding to an integrated luminosity of $139~\mathrm{fb}^{-1}$, for $\gamma/Z$ (a) and $\gamma/h$ (b) signal models. The black solid line corresponds to the expected limits at 95% CL, with the light (yellow) bands indicating the 1$\sigma$ exclusions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves, the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties. For each point in the higgsino-bino parameter space, the labels indicate the best-expected signal region, where L, M and H mean SRL, SRM and SRH, respectively.
Acceptance (left) and efficiency (right) for the $\gamma/Z$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).
Acceptance (left) and efficiency (right) for the $\gamma/Z$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).
Acceptance (left) and efficiency (right) for the $\gamma/Z$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).
Acceptance (left) and efficiency (right) for the $\gamma/Z$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).
Acceptance (left) and efficiency (right) for the $\gamma/Z$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).
Acceptance (left) and efficiency (right) for the $\gamma/Z$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).
Acceptance (left) and efficiency (right) for the $\gamma/h$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).
Acceptance (left) and efficiency (right) for the $\gamma/h$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).
Acceptance (left) and efficiency (right) for the $\gamma/h$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).
Acceptance (left) and efficiency (right) for the $\gamma/h$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).
Acceptance (left) and efficiency (right) for the $\gamma/h$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).
Acceptance (left) and efficiency (right) for the $\gamma/h$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).
Cutflow for the SRL selection, for two relevant signal points for both $\gamma/Z$ and $\gamma/h$ models, where the gluinos have mass of 2000 GeV and the neutralinos have a mass of 250 GeV (10000 generated events). The numbers are normalized to a luminosity of 139 $fb^{-1}$.
Cutflow for the SRM selection, for two relevant signal points for both $\gamma/Z$ and $\gamma/h$ models, where the gluinos have mass of 2000 GeV and the neutralinos have a mass of 1050 GeV (10000 generated events). The numbers are normalized to a luminosity of 139 $fb^{-1}$.
Cutflow for the SRH selection, for two relevant signal points for both $\gamma/Z$ and $\gamma/h$ models, where the gluinos have mass of 2000 GeV and the neutralinos have a mass of 1950 GeV (10000 generated events). The numbers are normalized to a luminosity of 139 $fb^{-1}$.
Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.
Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.
Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.
Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.
Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.
Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.
Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.
Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.
Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.
Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.
Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.
Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.
A search for the electroweak production of pairs of charged sleptons or charginos decaying into two-lepton final states with missing transverse momentum is presented. Two simplified models of $R$-parity-conserving supersymmetry are considered: direct pair-production of sleptons ($\tilde{\ell}\tilde{\ell}$), with each decaying into a charged lepton and a $\tilde{\chi}_1^0$ neutralino, and direct pair-production of the lightest charginos $(\tilde{\chi}_1^\pm\tilde{\chi}_1^\mp)$, with each decaying into a $W$-boson and a $\tilde{\chi}_1^0$. The lightest neutralino ($\tilde{\chi}_1^0$) is assumed to be the lightest supersymmetric particle (LSP). The analyses target the experimentally challenging mass regions where $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and $m(\tilde{\chi}_1^\pm)-m(\tilde{\chi}_1^0)$ are close to the $W$-boson mass (`moderately compressed' regions). The search uses 139 fb$^{-1}$ of $\sqrt{s}=13$ TeV proton-proton collisions recorded by the ATLAS detector at the Large Hadron Collider. No significant excesses over the expected background are observed. Exclusion limits on the simplified models under study are reported in the ($\tilde{\ell},\tilde{\chi}_1^0$) and ($\tilde{\chi}_1^\pm,\tilde{\chi}_1^0$) mass planes at 95% confidence level (CL). Sleptons with masses up to 150 GeV are excluded at 95% CL for the case of a mass-splitting between sleptons and the LSP of 50 GeV. Chargino masses up to 140 GeV are excluded at 95% CL for the case of a mass-splitting between the chargino and the LSP down to about 100 GeV.
<b>- - - - - - - - Overview of HEPData Record - - - - - - - -</b> <b>Title: </b><em>Search for direct pair production of sleptons and charginos decaying to two leptons and neutralinos with mass splittings near the $W$ boson mass in $\sqrt{s}=13$ TeV $pp$ collisions with the ATLAS detector</em> <b>Paper website:</b> <a href="https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/SUSY-2019-02/">SUSY-2019-02</a> <b>Exclusion contours</b> <ul><li><b>Sleptons:</b> <a href=?table=excl_comb_obs_nominal>Combined Observed Nominal</a> <a href=?table=excl_comb_obs_up>Combined Observed Up</a> <a href=?table=excl_comb_obs_down>Combined Observed Down</a> <a href=?table=excl_comb_exp_nominal>Combined Expected Nominal</a> <a href=?table=excl_comb_exp_up>Combined Expected Up</a> <a href=?table=excl_comb_exp_down>Combined Expected Down</a> <a href=?table=excl_comb_obs_nominal_dM>Combined Observed Nominal $(\Delta m)$</a> <a href=?table=excl_comb_obs_up_dM>Combined Observed Up $(\Delta m)$</a> <a href=?table=excl_comb_obs_down_dM>Combined Observed Down $(\Delta m)$</a> <a href=?table=excl_comb_exp_nominal_dM>Combined Expected Nominal $(\Delta m)$</a> <a href=?table=excl_comb_exp_up_dM>Combined Expected Up $(\Delta m)$</a> <a href=?table=excl_comb_exp_down_dM>Combined Expected Down $(\Delta m)$</a> <a href=?table=excl_ee_obs_nominal>$\tilde{e}_\mathrm{L,R}$ Observed Nominal</a> <a href=?table=excl_ee_exp_nominal>$\tilde{e}_\mathrm{L,R}$ Expected Nominal</a> <a href=?table=excl_eLeL_obs_nominal>$\tilde{e}_\mathrm{L}$ Observed Nominal</a> <a href=?table=excl_eLeL_exp_nominal>$\tilde{e}_\mathrm{L}$ Expected Nominal</a> <a href=?table=excl_eReR_obs_nominal>$\tilde{e}_\mathrm{R}$ Observed Nominal</a> <a href=?table=excl_eReR_exp_nominal>$\tilde{e}_\mathrm{R}$ Expected Nominal</a> <a href=?table=excl_ee_obs_nominal_dM>$\tilde{e}_\mathrm{L,R}$ Observed Nominal $(\Delta m)$</a> <a href=?table=excl_ee_exp_nominal_dM>$\tilde{e}_\mathrm{L,R}$ Expected Nominal $(\Delta m)$</a> <a href=?table=excl_eLeL_obs_nominal_dM>$\tilde{e}_\mathrm{L}$ Observed Nominal $(\Delta m)$</a> <a href=?table=excl_eLeL_exp_nominal_dM>$\tilde{e}_\mathrm{L}$ Expected Nominal $(\Delta m)$</a> <a href=?table=excl_eReR_obs_nominal_dM>$\tilde{e}_\mathrm{R}$ Observed Nominal $(\Delta m)$</a> <a href=?table=excl_eReR_exp_nominal_dM>$\tilde{e}_\mathrm{R}$ Expected Nominal $(\Delta m)$</a> <a href=?table=excl_mm_obs_nominal>$\tilde{\mu}_\mathrm{L,R}$ Observed Nominal</a> <a href=?table=excl_mm_exp_nominal>$\tilde{\mu}_\mathrm{L,R}$ Expected Nominal</a> <a href=?table=excl_mLmL_obs_nominal>$\tilde{\mu}_\mathrm{L}$ Observed Nominal</a> <a href=?table=excl_mLmL_exp_nominal>$\tilde{\mu}_\mathrm{L}$ Expected Nominal</a> <a href=?table=excl_mRmR_obs_nominal>$\tilde{\mu}_\mathrm{R}$ Observed Nominal</a> <a href=?table=excl_mRmR_exp_nominal>$\tilde{\mu}_\mathrm{R}$ Expected Nominal</a> <a href=?table=excl_mm_obs_nominal_dM>$\tilde{\mu}_\mathrm{L,R}$ Observed Nominal $(\Delta m)$</a> <a href=?table=excl_mm_exp_nominal_dM>$\tilde{\mu}_\mathrm{L,R}$ Expected Nominal $(\Delta m)$</a> <a href=?table=excl_mLmL_obs_nominal_dM>$\tilde{\mu}_\mathrm{L}$ Observed Nominal $(\Delta m)$</a> <a href=?table=excl_mLmL_exp_nominal_dM>$\tilde{\mu}_\mathrm{L}$ Expected Nominal $(\Delta m)$</a> <a href=?table=excl_mRmR_obs_nominal_dM>$\tilde{\mu}_\mathrm{R}$ Observed Nominal $(\Delta m)$</a> <a href=?table=excl_mRmR_exp_nominal_dM>$\tilde{\mu}_\mathrm{R}$ Expected Nominal $(\Delta m)$</a> <a href=?table=excl_comb_obs_nominal_SR0j>Combined Observed Nominal SR-0j</a> <a href=?table=excl_comb_exp_nominal_SR0j>Combined Expected Nominal SR-0j</a> <a href=?table=excl_comb_obs_nominal_SR1j>Combined Observed Nominal SR-1j</a> <a href=?table=excl_comb_exp_nominal_SR1j>Combined Expected Nominal SR-1j</a> <li><b>Charginos:</b> <a href=?table=excl_c1c1_obs_nominal>Observed Nominal</a> <a href=?table=excl_c1c1_obs_up>Observed Up</a> <a href=?table=excl_c1c1_obs_down>Observed Down</a> <a href=?table=excl_c1c1_exp_nominal>Expected Nominal</a> <a href=?table=excl_c1c1_exp_nominal>Expected Up</a> <a href=?table=excl_c1c1_exp_nominal>Expected Down</a> <a href=?table=excl_c1c1_obs_nominal_dM>Observed Nominal $(\Delta m)$</a> <a href=?table=excl_c1c1_obs_up_dM>Observed Up $(\Delta m)$</a> <a href=?table=excl_c1c1_obs_down_dM>Observed Down $(\Delta m)$</a> <a href=?table=excl_c1c1_exp_nominal_dM>Expected Nominal $(\Delta m)$</a> <a href=?table=excl_c1c1_exp_nominal_dM>Expected Up $(\Delta m)$</a> <a href=?table=excl_c1c1_exp_nominal_dM>Expected Down $(\Delta m)$</a> </ul> <b>Upper Limits</b> <ul><li><b>Sleptons:</b> <a href=?table=UL_slep>ULs</a> <li><b>Charginos:</b> <a href=?table=UL_c1c1>ULs</a> </ul> <b>Pull Plots</b> <ul><li><b>Sleptons:</b> <a href=?table=pullplot_slep>SRs summary plot</a> <li><b>Charginos:</b> <a href=?table=pullplot_c1c1>SRs summary plot</a> </ul> <b>Cutflows</b> <ul><li><b>Sleptons:</b> <a href=?table=Cutflow_slep_SR0j>Towards SR-0J</a> <a href=?table=Cutflow_slep_SR1j>Towards SR-1J</a> <li><b>Charginos:</b> <a href=?table=Cutflow_SRs>Towards SRs</a> </ul> <b>Acceptance and Efficiencies</b> <ul><li><b>Sleptons:</b> <a href=?table=Acceptance_SR0j_MT2_100_infty>SR-0J $m_{\mathrm{T2}}^{100} \in[100,\infty)$ Acceptance</a> <a href=?table=Efficiency_SR0j_MT2_100_infty>SR-0J $m_{\mathrm{T2}}^{100} \in[100,\infty)$ Efficiency</a> <a href=?table=Acceptance_SR0j_MT2_110_infty>SR-0J $m_{\mathrm{T2}}^{100} \in[110,\infty)$ Acceptance</a> <a href=?table=Efficiency_SR0j_MT2_110_infty>SR-0J $m_{\mathrm{T2}}^{100} \in[110,\infty)$ Efficiency</a> <a href=?table=Acceptance_SR0j_MT2_120_infty>SR-0J $m_{\mathrm{T2}}^{100} \in[120,\infty)$ Acceptance</a> <a href=?table=Efficiency_SR0j_MT2_120_infty>SR-0J $m_{\mathrm{T2}}^{100} \in[120,\infty)$ Efficiency</a> <a href=?table=Acceptance_SR0j_MT2_130_infty>SR-0J $m_{\mathrm{T2}}^{100} \in[130,\infty)$ Acceptance</a> <a href=?table=Efficiency_SR0j_MT2_130_infty>SR-0J $m_{\mathrm{T2}}^{100} \in[130,\infty)$ Efficiency</a> <a href=?table=Acceptance_SR0j_MT2_100_105>SR-0J $m_{\mathrm{T2}}^{100} \in[100,105)$ Acceptance</a> <a href=?table=Efficiency_SR0j_MT2_100_105>SR-0J $m_{\mathrm{T2}}^{100} \in[100,105)$ Efficiency</a> <a href=?table=Acceptance_SR0j_MT2_105_110>SR-0J $m_{\mathrm{T2}}^{100} \in[105,110)$ Acceptance</a> <a href=?table=Efficiency_SR0j_MT2_105_110>SR-0J $m_{\mathrm{T2}}^{100} \in[105,110)$ Efficiency</a> <a href=?table=Acceptance_SR0j_MT2_110_115>SR-0J $m_{\mathrm{T2}}^{100} \in[110,115)$ Acceptance</a> <a href=?table=Efficiency_SR0j_MT2_110_115>SR-0J $m_{\mathrm{T2}}^{100} \in[110,115)$ Efficiency</a> <a href=?table=Acceptance_SR0j_MT2_115_120>SR-0J $m_{\mathrm{T2}}^{100} \in[115,120)$ Acceptance</a> <a href=?table=Efficiency_SR0j_MT2_115_120>SR-0J $m_{\mathrm{T2}}^{100} \in[115,120)$ Efficiency</a> <a href=?table=Acceptance_SR0j_MT2_120_125>SR-0J $m_{\mathrm{T2}}^{100} \in[120,125)$ Acceptance</a> <a href=?table=Efficiency_SR0j_MT2_125_130>SR-0J $m_{\mathrm{T2}}^{100} \in[125,130)$ Efficiency</a> <a href=?table=Acceptance_SR0j_MT2_130_140>SR-0J $m_{\mathrm{T2}}^{100} \in[130,140)$ Acceptance</a> <a href=?table=Efficiency_SR0j_MT2_130_140>SR-0J $m_{\mathrm{T2}}^{100} \in[130,140)$ Efficiency</a> <a href=?table=Acceptance_SR0j_MT2_140_infty>SR-0J $m_{\mathrm{T2}}^{100} \in[140,\infty)$ Acceptance</a> <a href=?table=Efficiency_SR0j_MT2_140_infty>SR-0J $m_{\mathrm{T2}}^{100} \in[140,\infty)$ Efficiency</a> <a href=?table=Acceptance_SR1j_MT2_100_infty>SR-1j $m_{\mathrm{T2}}^{100} \in[100,\infty)$ Acceptance</a> <a href=?table=Efficiency_SR1j_MT2_100_infty>SR-1j $m_{\mathrm{T2}}^{100} \in[100,\infty)$ Efficiency</a> <a href=?table=Acceptance_SR1j_MT2_110_infty>SR-1j $m_{\mathrm{T2}}^{100} \in[110,\infty)$ Acceptance</a> <a href=?table=Efficiency_SR1j_MT2_110_infty>SR-1j $m_{\mathrm{T2}}^{100} \in[110,\infty)$ Efficiency</a> <a href=?table=Acceptance_SR1j_MT2_120_infty>SR-1j $m_{\mathrm{T2}}^{100} \in[120,\infty)$ Acceptance</a> <a href=?table=Efficiency_SR1j_MT2_120_infty>SR-1j $m_{\mathrm{T2}}^{100} \in[120,\infty)$ Efficiency</a> <a href=?table=Acceptance_SR1j_MT2_130_infty>SR-1j $m_{\mathrm{T2}}^{100} \in[130,\infty)$ Acceptance</a> <a href=?table=Efficiency_SR1j_MT2_130_infty>SR-1j $m_{\mathrm{T2}}^{100} \in[130,\infty)$ Efficiency</a> <a href=?table=Acceptance_SR1j_MT2_100_105>SR-1j $m_{\mathrm{T2}}^{100} \in[100,105)$ Acceptance</a> <a href=?table=Efficiency_SR1j_MT2_100_105>SR-1j $m_{\mathrm{T2}}^{100} \in[100,105)$ Efficiency</a> <a href=?table=Acceptance_SR1j_MT2_105_110>SR-1j $m_{\mathrm{T2}}^{100} \in[105,110)$ Acceptance</a> <a href=?table=Efficiency_SR1j_MT2_105_110>SR-1j $m_{\mathrm{T2}}^{100} \in[105,110)$ Efficiency</a> <a href=?table=Acceptance_SR1j_MT2_110_115>SR-1j $m_{\mathrm{T2}}^{100} \in[110,115)$ Acceptance</a> <a href=?table=Efficiency_SR1j_MT2_110_115>SR-1j $m_{\mathrm{T2}}^{100} \in[110,115)$ Efficiency</a> <a href=?table=Acceptance_SR1j_MT2_115_120>SR-1j $m_{\mathrm{T2}}^{100} \in[115,120)$ Acceptance</a> <a href=?table=Efficiency_SR1j_MT2_115_120>SR-1j $m_{\mathrm{T2}}^{100} \in[115,120)$ Efficiency</a> <a href=?table=Acceptance_SR1j_MT2_120_125>SR-1j $m_{\mathrm{T2}}^{100} \in[120,125)$ Acceptance</a> <a href=?table=Efficiency_SR1j_MT2_125_130>SR-1j $m_{\mathrm{T2}}^{100} \in[125,130)$ Efficiency</a> <a href=?table=Acceptance_SR1j_MT2_130_140>SR-1j $m_{\mathrm{T2}}^{100} \in[130,140)$ Acceptance</a> <a href=?table=Efficiency_SR1j_MT2_130_140>SR-1j $m_{\mathrm{T2}}^{100} \in[130,140)$ Efficiency</a> <a href=?table=Acceptance_SR1j_MT2_140_infty>SR-1j $m_{\mathrm{T2}}^{100} \in[140,\infty)$ Acceptance</a> <a href=?table=Efficiency_SR1j_MT2_140_infty>SR-1j $m_{\mathrm{T2}}^{100} \in[140,\infty)$ Efficiency</a> <li><b>Charginos:</b> <a href=?table=Acceptance_SR_DF_81_1_SF_77_1>SR$^{\text{-DF BDT-signal}\in(0.81,1]}_{\text{-SF BDT-signal}\in(0.77,1]}$ Acceptance</a> <a href=?table=Efficiency_SR_DF_81_1_SF_77_1>SR$^{\text{-DF BDT-signal}\in(0.81,1]}_{\text{-SF BDT-signal}\in(0.77,1]}$ Efficiency</a> <a href=?table=Acceptance_SR_DF_81_1>SR-DF BDT-signal$\in(0.81,1]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_81_1>SR-DF BDT-signal$\in(0.81,1]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_82_1>SR-DF BDT-signal$\in(0.82,1]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_82_1>SR-DF BDT-signal$\in(0.82,1]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_83_1>SR-DF BDT-signal$\in(0.83,1]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_83_1>SR-DF BDT-signal$\in(0.83,1]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_84_1>SR-DF BDT-signal$\in(0.84,1]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_84_1>SR-DF BDT-signal$\in(0.84,1]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_85_1>SR-DF BDT-signal$\in(0.85,1]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_85_1>SR-DF BDT-signal$\in(0.85,1]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_81_8125>SR-DF BDT-signal$\in(0.81,8125]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_81_8125>SR-DF BDT-signal$\in(0.81,8125]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_8125_815>SR-DF BDT-signal$\in(0.8125,815]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_8125_815>SR-DF BDT-signal$\in(0.8125,815]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_815_8175>SR-DF BDT-signal$\in(0.815,8175]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_815_8175>SR-DF BDT-signal$\in(0.815,8175]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_8175_82>SR-DF BDT-signal$\in(0.8175,82]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_8175_82>SR-DF BDT-signal$\in(0.8175,82]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_82_8225>SR-DF BDT-signal$\in(0.82,8225]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_82_8225>SR-DF BDT-signal$\in(0.82,8225]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_8225_825>SR-DF BDT-signal$\in(0.8225,825]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_8225_825>SR-DF BDT-signal$\in(0.8225,825]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_825_8275>SR-DF BDT-signal$\in(0.825,8275]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_825_8275>SR-DF BDT-signal$\in(0.825,8275]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_8275_83>SR-DF BDT-signal$\in(0.8275,83]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_8275_83>SR-DF BDT-signal$\in(0.8275,83]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_83_8325>SR-DF BDT-signal$\in(0.83,8325]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_83_8325>SR-DF BDT-signal$\in(0.83,8325]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_8325_835>SR-DF BDT-signal$\in(0.8325,835]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_8325_835>SR-DF BDT-signal$\in(0.8325,835]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_835_8375>SR-DF BDT-signal$\in(0.835,8375]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_835_8375>SR-DF BDT-signal$\in(0.835,8375]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_8375_84>SR-DF BDT-signal$\in(0.8375,84]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_8375_84>SR-DF BDT-signal$\in(0.8375,84]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_84_845>SR-DF BDT-signal$\in(0.85,845]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_84_845>SR-DF BDT-signal$\in(0.85,845]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_845_85>SR-DF BDT-signal$\in(0.845,85]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_845_85>SR-DF BDT-signal$\in(0.845,85]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_85_86>SR-DF BDT-signal$\in(0.85,86]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_85_86>SR-DF BDT-signal$\in(0.85,86]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_86_1>SR-DF BDT-signal$\in(0.86,1]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_86_1>SR-DF BDT-signal$\in(0.86,1]$ Efficiency</a> <a href=?table=Acceptance_SR_SF_77_1>SR-SF BDT-signal$\in(0.77,1]$ Acceptance</a> <a href=?table=Efficiency_SR_SF_77_1>SR-SF BDT-signal$\in(0.77,1]$ Efficiency</a> <a href=?table=Acceptance_SR_SF_78_1>SR-SF BDT-signal$\in(0.78,1]$ Acceptance</a> <a href=?table=Efficiency_SR_SF_78_1>SR-SF BDT-signal$\in(0.78,1]$ Efficiency</a> <a href=?table=Acceptance_SR_SF_79_1>SR-SF BDT-signal$\in(0.79,1]$ Acceptance</a> <a href=?table=Efficiency_SR_SF_79_1>SR-SF BDT-signal$\in(0.79,1]$ Efficiency</a> <a href=?table=Acceptance_SR_SF_80_1>SR-SF BDT-signal$\in(0.80,1]$ Acceptance</a> <a href=?table=Efficiency_SR_SF_80_1>SR-SF BDT-signal$\in(0.80,1]$ Efficiency</a> <a href=?table=Acceptance_SR_SF_77_775>SR-SF BDT-signal$\in(0.77,0.775]$ Acceptance</a> <a href=?table=Efficiency_SR_SF_77_775>SR-SF BDT-signal$\in(0.77,0.775]$ Efficiency</a> <a href=?table=Acceptance_SR_SF_775_78>SR-SF BDT-signal$\in(0.775,0.78]$ Acceptance</a> <a href=?table=Efficiency_SR_SF_775_78>SR-SF BDT-signal$\in(0.775,0.78]$ Efficiency</a> <a href=?table=Acceptance_SR_SF_78_785>SR-SF BDT-signal$\in(0.78,0.785]$ Acceptance</a> <a href=?table=Efficiency_SR_SF_78_785>SR-SF BDT-signal$\in(0.78,0.785]$ Efficiency</a> <a href=?table=Acceptance_SR_SF_785_79>SR-SF BDT-signal$\in(0.785,0.79]$ Acceptance</a> <a href=?table=Efficiency_SR_SF_785_79>SR-SF BDT-signal$\in(0.785,0.79]$ Efficiency</a> <a href=?table=Acceptance_SR_SF_79_795>SR-SF BDT-signal$\in(0.79,0.795]$ Acceptance</a> <a href=?table=Efficiency_SR_SF_79_795>SR-SF BDT-signal$\in(0.79,0.795]$ Efficiency</a> <a href=?table=Acceptance_SR_SF_795_80>SR-SF BDT-signal$\in(0.795,0.80]$ Acceptance</a> <a href=?table=Efficiency_SR_SF_795_80>SR-SF BDT-signal$\in(0.795,0.80]$ Efficiency</a> <a href=?table=Acceptance_SR_SF_80_81>SR-SF BDT-signal$\in(0.80,0.81]$ Acceptance</a> <a href=?table=Efficiency_SR_SF_80_81>SR-SF BDT-signal$\in(0.80,0.81]$ Efficiency</a> <a href=?table=Acceptance_SR_SF_81_1>SR-SF BDT-signal$\in(0.81,1]$ Acceptance</a> <a href=?table=Efficiency_SR_SF_81_1>SR-SF BDT-signal$\in(0.81,1]$ Efficiency</a></ul> <b>Truth Code snippets</b>, <b>SLHA</b> and <b>machine learning</b> files are available under "Resources" (purple button on the left)
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[100,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[100,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[110,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[110,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[120,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[120,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[130,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[130,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[100,105)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[100,105)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[105,110)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[105,110)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[110,115)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[110,115)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[115,120)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[115,120)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[120,125)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[120,125)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[125,130)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[125,130)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[130,140)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[130,140)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[140,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[140,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[100,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[100,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[110,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[110,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[120,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[120,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[130,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[130,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[100,105)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[100,105)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[105,110)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[105,110)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[110,115)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[110,115)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[115,120)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[115,120)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[120,125)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[120,125)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[125,130)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[125,130)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[130,140)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[130,140)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[140,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[140,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
Cutflow table for the slepton signal sample with $m(\tilde{\ell},\tilde{\chi}_1^0) = (100,70)$ GeV, in the SR-0J $m_{\mathrm{T2}}^{100} \in [100,\infty)$ region. The yields include the process cross section and are weighted to the 139 fb$^{-1}$ luminosity. 246000 events were generated for the sample.
Cutflow table for the slepton signal sample with $m(\tilde{\ell},\tilde{\chi}_1^0) = (100,70)$ GeV, in the SR-1J $m_{\mathrm{T2}}^{100} \in [100,\infty)$ region. The yields include the process cross section and are weighted to the 139 fb$^{-1}$ luminosity. 246000 events were generated for the sample.
Observed and expected exclusion limits on SUSY simplified models, with observed upper limits on signal cross-section (fb) overlaid, for slepton-pair production in the $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ plane. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ plane. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The red contour shows the exclusion limits obtained using both the SR-0J and SR-1J region, as presented in Figure 6. The blue and green contours correspond to the result obtained considering only SR-0J and SR-1J region respectively. All limits are computed at 95% CL. The observed limits obtained by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ plane. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The red contour shows the exclusion limits obtained using both the SR-0J and SR-1J region, as presented in Figure 6. The blue and green contours correspond to the result obtained considering only SR-0J and SR-1J region respectively. All limits are computed at 95% CL. The observed limits obtained by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ plane. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The red contour shows the exclusion limits obtained using both the SR-0J and SR-1J region, as presented in Figure 6. The blue and green contours correspond to the result obtained considering only SR-0J and SR-1J region respectively. All limits are computed at 95% CL. The observed limits obtained by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ plane. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The red contour shows the exclusion limits obtained using both the SR-0J and SR-1J region, as presented in Figure 6. The blue and green contours correspond to the result obtained considering only SR-0J and SR-1J region respectively. All limits are computed at 95% CL. The observed limits obtained by the ATLAS experiment in previous searches are also shown.
The upper panel shows the observed number of events in each of the binned SRs defined in Table 3, together with the expected SM backgrounds obtained after applying the efficiency correction method to compute the number of expected FSB events. `Others' include the non-dominant background sources, e.g. $t \bar{t}$+$V$, Higgs boson and Drell--Yan events. The uncertainty band includes systematic and statistical errors from all sources. The distributions of two signal points with mass splittings $\Delta m(\tilde{\ell},\tilde{\chi}_1^0) = m(\tilde{\ell})-m(\tilde{\chi}_1^0) = 30$ GeV and $\Delta m(\tilde{\ell},\tilde{\chi}_1^0) = m(\tilde{\ell})-m(\tilde{\chi}_1^0) = 50$ GeV are overlaid. The lower panel shows the significance as defined in Ref. [115].
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR$^{\text{-DF BDT-signal}\in(0.81,1]}_{\text{-SF BDT-signal}\in(0.77,1]}$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR$^{\text{-DF BDT-signal}\in(0.81,1]}_{\text{-SF BDT-signal}\in(0.77,1]}$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.81,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.81,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.82,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.82,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.83,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.83,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.84,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.84,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.85,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.85,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.81,0.8125]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.81,0.8125]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8125,0.815]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8125,0.815]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.815,0.8175]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.815,0.8175]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8175,0.82]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8175,0.82]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.82,0.8225]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.82,0.8225]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8225,0.825]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8225,0.825]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.825,0.8275]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.825,0.8275]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8275,0.83]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8275,0.83]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.83,0.8325]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.83,0.8325]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8325,0.835]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8325,0.835]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.835,0.8375]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.835,0.8375]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8375,0.84]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8375,0.84]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.84,0.845]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.84,0.845]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.845,0.85]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.845,0.85]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.85,0.86]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.85,0.86]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.86,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.86,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.77,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.77,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.78,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.78,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.79,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.79,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.80,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.80,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.77,0.775]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.77,0.775]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.775,0.78]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.775,0.78]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.78,0.785]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.78,0.785]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.785,0.79]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.785,0.79]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.79,0.795]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.79,0.795]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.795,0.80]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.795,0.80]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.80,0.81]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.80,0.81]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.81,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.81,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
Cutflow table for the chargino signal sample with $m\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0=(125,25)$ GeV, in the SR-SF BDT-signal$\in (0.77,1]$ and SR-DF BDT-signal$\in (0.81,1]$ regions. The yields include the process cross-section and are weighted to the 139 fb$^{-1}$ luminosity. 170000 events were generated for the sample.
Observed and expected exclusion limits on SUSY simplified models, with observed upper limits on signal cross-section (fb) overlaid, for chargino-pair production with $W$-boson-mediated decays in the $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ plane. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.
Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.
Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.
Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.
Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.
Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.
Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.
Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.
Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.
Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.
Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.
Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.
Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.
The upper panel shows the observed number of events in the SRs defined in Table 3, together with the expected SM backgrounds obtained after the background fit in the CRs. `Others' include the non-dominant background sources, e.g.$t \bar{t}$+$V$, Higgs boson and Drell--Yan events. The uncertainty band includes systematic and statistical errors from all sources. Distributions for three benchmark signal points are overlaid for comparison. The lower panel shows the significance as defined in Ref. [115].
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