Showing 10 of 719 results
Measurements of transverse energy$-$energy correlations and their associated azimuthal asymmetries in multijet events are presented. The analysis is performed using a data sample corresponding to 139 $\mbox{fb\(^{-1}\)}$ of proton$-$proton collisions at a centre-of-mass energy of $\sqrt{s} = 13$ TeV, collected with the ATLAS detector at the Large Hadron Collider. The measurements are presented in bins of the scalar sum of the transverse momenta of the two leading jets and unfolded to particle level. They are then compared to next-to-next-to-leading-order perturbative QCD calculations for the first time, which feature a significant reduction in the theoretical uncertainties estimated using variations of the renormalisation and factorisation scales. The agreement between data and theory is good, thus providing a precision test of QCD at large momentum transfers $Q$. The strong coupling constant $\alpha_s$ is extracted differentially as a function of $Q$, showing a good agreement with the renormalisation group equation and with previous analyses. A simultaneous fit to all transverse energy$-$energy correlation distributions across different kinematic regions yields a value of $\alpha_\mathrm{s}(m_Z) = 0.1175 \pm 0.0006 \mbox{ (exp.)} ^{+0.0034}_{-0.0017} \mbox{ (theo.)}$, while the global fit to the asymmetry distributions yields $\alpha_{\mathrm{s}}(m_Z) = 0.1185 \pm 0.0009 \mbox{ (exp.)} ^{+0.0025}_{-0.0012} \mbox{ (theo.)}$.
Particle-level TEEC results
Particle-level TEEC results for the first HT2 bin
Particle-level TEEC results for the second HT2 bin
Particle-level TEEC results for the third HT2 bin
Particle-level TEEC results for the fourth HT2 bin
Particle-level TEEC results for the fifth HT2 bin
Particle-level TEEC results for the sixth HT2 bin
Particle-level TEEC results for the seventh HT2 bin
Particle-level TEEC results for the eighth HT2 bin
Particle-level TEEC results for the ninth HT2 bin
Particle-level TEEC results for the tenth HT2 bin
Particle-level ATEEC results
Particle-level ATEEC results for the first HT2 bin
Particle-level ATEEC results for the second HT2 bin
Particle-level ATEEC results for the third HT2 bin
Particle-level ATEEC results for the fourth HT2 bin
Particle-level ATEEC results for the fifth HT2 bin
Particle-level ATEEC results for the sixth HT2 bin
Particle-level ATEEC results for the seventh HT2 bin
Particle-level ATEEC results for the eighth HT2 bin
Particle-level ATEEC results for the ninth HT2 bin
Particle-level ATEEC results for the tenth HT2 bin
Particle-level TEEC predictions
Particle-level TEEC predictions for the first HT2 bin
Particle-level TEEC predictions for the second HT2 bin
Particle-level TEEC predictions for the third HT2 bin
Particle-level TEEC predictions for the fourth HT2 bin
Particle-level TEEC predictions for the fifth HT2 bin
Particle-level TEEC predictions for the sixth HT2 bin
Particle-level TEEC predictions for the seventh HT2 bin
Particle-level TEEC predictions for the eighth HT2 bin
Particle-level TEEC predictions for the ninth HT2 bin
Particle-level TEEC predictions for the tenth HT2 bin
Particle-level ATEEC predictions
Particle-level ATEEC predictions for the first HT2 bin
Particle-level ATEEC predictions for the second HT2 bin
Particle-level ATEEC predictions for the third HT2 bin
Particle-level ATEEC predictions for the fourth HT2 bin
Particle-level ATEEC predictions for the fifth HT2 bin
Particle-level ATEEC predictions for the sixth HT2 bin
Particle-level ATEEC predictions for the seventh HT2 bin
Particle-level ATEEC predictions for the eighth HT2 bin
Particle-level ATEEC predictions for the ninth HT2 bin
Particle-level ATEEC predictions for the tenth HT2 bin
Fitted values for the strong coupling constant extracted from TEEC with MMHT 2014 PDF
Fitted values for the strong coupling constant extracted from TEEC with NNPDF 3.0
Fitted values for the strong coupling constant extracted from TEEC with CT14 PDF
Fitted values for the strong coupling constant extracted from ATEEC with MMHT 2014 PDF
Fitted values for the strong coupling constant extracted from ATEEC with NNPDF 3.0
Fitted values for the strong coupling constant extracted from ATEEC with CT14 PDF
This paper presents results of searches for electroweak production of supersymmetric particles in models with compressed mass spectra. The searches use 139 fb$^{-1}$ of $\sqrt{s}=13$ TeV proton-proton collision data collected by the ATLAS experiment at the Large Hadron Collider. Events with missing transverse momentum and two same-flavor, oppositely charged, low transverse momentum leptons are selected, and are further categorized by the presence of hadronic activity from initial-state radiation or a topology compatible with vector-boson fusion processes. The data are found to be consistent with predictions from the Standard Model. The results are interpreted using simplified models of $R$-parity-conserving supersymmetry in which the lightest supersymmetric partner is a neutralino with a mass similar to the lightest chargino, the second-to-lightest neutralino or the slepton. Lower limits on the masses of charginos in different simplified models range from 193 GeV to 240 GeV for moderate mass splittings, and extend down to mass splittings of 1.5 GeV to 2.4 GeV at the LEP chargino bounds (92.4 GeV). Similar lower limits on degenerate light-flavor sleptons extend up to masses of 251 GeV and down to mass splittings of 550 MeV. Constraints on vector-boson fusion production of electroweak SUSY states are also presented.
Expected 95% CL exclusion sensitivity for simplified models of direct higgsino production.
Expected 95% CL exclusion sensitivity for simplified models of direct higgsino production.
Expected 95% CL exclusion sensitivity for simplified models of direct higgsino production.
Expected 95% CL exclusion sensitivity for simplified models of direct higgsino production.
Expected 95% CL exclusion sensitivity for simplified models of direct higgsino production.
Observed 95% CL exclusion sensitivity for simplified models of direct higgsino production.
Observed 95% CL exclusion sensitivity for simplified models of direct higgsino production.
Observed 95% CL exclusion sensitivity for simplified models of direct higgsino production.
Observed 95% CL exclusion sensitivity for simplified models of direct higgsino production.
Observed 95% CL exclusion sensitivity for simplified models of direct higgsino production.
Expected 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Expected 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Expected 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Expected 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Expected 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Expected 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Expected 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Expected 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Expected 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Expected 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Expected 95% CL exclusion sensitivity for simplified models of VBF wino-bino production.
Expected 95% CL exclusion sensitivity for simplified models of VBF wino-bino production.
Expected 95% CL exclusion sensitivity for simplified models of VBF wino-bino production.
Expected 95% CL exclusion sensitivity for simplified models of VBF wino-bino production.
Expected 95% CL exclusion sensitivity for simplified models of VBF wino-bino production.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production.
Observed 95% CL exclusion sensitivity for simplified models of direct wino-bino production.
Expected 95% CL exclusion sensitivity for simplified models of direct slepton production.
Expected 95% CL exclusion sensitivity for simplified models of direct slepton production.
Expected 95% CL exclusion sensitivity for simplified models of direct slepton production.
Expected 95% CL exclusion sensitivity for simplified models of direct slepton production.
Expected 95% CL exclusion sensitivity for simplified models of direct slepton production.
Observed 95% CL exclusion sensitivity for simplified models of direct slepton production.
Observed 95% CL exclusion sensitivity for simplified models of direct slepton production.
Observed 95% CL exclusion sensitivity for simplified models of direct slepton production.
Observed 95% CL exclusion sensitivity for simplified models of direct slepton production.
Observed 95% CL exclusion sensitivity for simplified models of direct slepton production.
Expected 95% CL exclusion sensitivity for simplified models of direct LH smuon production.
Expected 95% CL exclusion sensitivity for simplified models of direct LH smuon production.
Expected 95% CL exclusion sensitivity for simplified models of direct smuon production.
Expected 95% CL exclusion sensitivity for simplified models of direct smuon production.
Expected 95% CL exclusion sensitivity for simplified models of direct smuon production.
Observed 95% CL exclusion sensitivity for simplified models of direct LH smuon production.
Observed 95% CL exclusion sensitivity for simplified models of direct LH smuon production.
Observed 95% CL exclusion sensitivity for simplified models of direct smuon production.
Observed 95% CL exclusion sensitivity for simplified models of direct smuon production.
Observed 95% CL exclusion sensitivity for simplified models of direct smuon production.
Expected 95% CL exclusion sensitivity for simplified models of direct RH smuon production.
Expected 95% CL exclusion sensitivity for simplified models of direct RH smuon production.
Expected 95% CL exclusion sensitivity for simplified models of direct selectron production.
Expected 95% CL exclusion sensitivity for simplified models of direct selectron production.
Expected 95% CL exclusion sensitivity for simplified models of direct selectron production.
Observed 95% CL exclusion sensitivity for simplified models of direct RH smuon production.
Observed 95% CL exclusion sensitivity for simplified models of direct RH smuon production.
Observed 95% CL exclusion sensitivity for simplified models of direct selectron production.
Observed 95% CL exclusion sensitivity for simplified models of direct selectron production.
Observed 95% CL exclusion sensitivity for simplified models of direct selectron production.
Expected 95% CL exclusion sensitivity for simplified models of direct LH selectron production.
Expected 95% CL exclusion sensitivity for simplified models of direct LH selectron production.
Expected 95% CL exclusion sensitivity for simplified models of direct LH slepton production.
Expected 95% CL exclusion sensitivity for simplified models of direct LH slepton production.
Expected 95% CL exclusion sensitivity for simplified models of direct LH slepton production.
Observed 95% CL exclusion sensitivity for simplified models of direct LH selectron production.
Observed 95% CL exclusion sensitivity for simplified models of direct LH selectron production.
Observed 95% CL exclusion sensitivity for simplified models of direct LH slepton production.
Observed 95% CL exclusion sensitivity for simplified models of direct LH slepton production.
Observed 95% CL exclusion sensitivity for simplified models of direct LH slepton production.
Expected 95% CL exclusion sensitivity for simplified models of direct RH selectron production.
Expected 95% CL exclusion sensitivity for simplified models of direct RH selectron production.
Expected 95% CL exclusion sensitivity for simplified models of direct RH slepton production.
Expected 95% CL exclusion sensitivity for simplified models of direct RH slepton production.
Expected 95% CL exclusion sensitivity for simplified models of direct RH slepton production.
Observed 95% CL exclusion sensitivity for simplified models of direct RH selectron production.
Observed 95% CL exclusion sensitivity for simplified models of direct RH selectron production.
Observed 95% CL exclusion sensitivity for simplified models of direct RH slepton production.
Observed 95% CL exclusion sensitivity for simplified models of direct RH slepton production.
Observed 95% CL exclusion sensitivity for simplified models of direct RH slepton production.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Expected 95% CL exclusion sensitivity for simplified models of direct LH smuon production.
Expected 95% CL exclusion sensitivity for simplified models of direct LH smuon production.
Expected 95% CL exclusion sensitivity for simplified models of direct LH smuon production.
Efficiency for the C1C1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Observed 95% CL exclusion sensitivity for simplified models of direct LH smuon production.
Observed 95% CL exclusion sensitivity for simplified models of direct LH smuon production.
Observed 95% CL exclusion sensitivity for simplified models of direct LH smuon production.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Expected 95% CL exclusion sensitivity for simplified models of direct RH smuon production.
Expected 95% CL exclusion sensitivity for simplified models of direct RH smuon production.
Expected 95% CL exclusion sensitivity for simplified models of direct RH smuon production.
Efficiency for the C1C1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Observed 95% CL exclusion sensitivity for simplified models of direct RH smuon production.
Observed 95% CL exclusion sensitivity for simplified models of direct RH smuon production.
Observed 95% CL exclusion sensitivity for simplified models of direct RH smuon production.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Expected 95% CL exclusion sensitivity for simplified models of direct LH selectron production.
Expected 95% CL exclusion sensitivity for simplified models of direct LH selectron production.
Expected 95% CL exclusion sensitivity for simplified models of direct LH selectron production.
Efficiency for the C1C1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Observed 95% CL exclusion sensitivity for simplified models of direct LH selectron production.
Observed 95% CL exclusion sensitivity for simplified models of direct LH selectron production.
Observed 95% CL exclusion sensitivity for simplified models of direct LH selectron production.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Expected 95% CL exclusion sensitivity for simplified models of direct RH selectron production.
Expected 95% CL exclusion sensitivity for simplified models of direct RH selectron production.
Expected 95% CL exclusion sensitivity for simplified models of direct RH selectron production.
Efficiency for the N2N1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Observed 95% CL exclusion sensitivity for simplified models of direct RH selectron production.
Observed 95% CL exclusion sensitivity for simplified models of direct RH selectron production.
Observed 95% CL exclusion sensitivity for simplified models of direct RH selectron production.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2N1 higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1p higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the slepton process in the SR-S region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the slepton process in the SR-S region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-high region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S-high region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S-high region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the slepton process in the SR-S-high region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the slepton process in the SR-S-high region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-low region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S-low region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S-low region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the slepton process in the SR-S-low region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the slepton process in the SR-S-low region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-med region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Efficiency for the N2C1m higgsino process in the SR-E-1l1T region. Truth dilepton invariant mass is constrained to be within the range [0.5,60] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the slepton process in the SR-S region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the slepton process in the SR-S region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the slepton process in the SR-S region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S-high region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S-high region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S-high region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the slepton process in the SR-S-high region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the slepton process in the SR-S-high region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the slepton process in the SR-S-high region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S-low region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S-low region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-3}$) for the slepton process in the SR-S-low region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the slepton process in the SR-S-low region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the slepton process in the SR-S-low region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Efficiency for the slepton process in the SR-S-low region. Truth stransverse mass is constrained to be within the range [100,140] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the C1C1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the C1C1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2N1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2N1 VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Observed and Expected upper cross-section limits for wino-bino scenarios, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Observed and Expected upper cross-section limits for wino-bino scenarios, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1p VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Observed and Expected upper cross-section limits for wino-bino scenarios, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Observed and Expected upper cross-section limits for wino-bino scenarios, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1p VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Observed and Expected upper cross-section limits for higgsino scenarios.
Observed and Expected upper cross-section limits for higgsino scenarios.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Observed and Expected upper cross-section limits for higgsino scenarios, assuming VBF production..
Observed and Expected upper cross-section limits for higgsino scenarios, assuming VBF production..
Efficiency for the N2C1m VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF-high region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Observed and Expected upper cross-section limits for direct slepton scenarios.
Observed and Expected upper cross-section limits for direct slepton scenarios.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Observed and Expected upper cross-section limits for direct LH slepton scenarios.
Observed and Expected upper cross-section limits for direct LH slepton scenarios.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF-low region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Observed and Expected upper cross-section limits for direct RH slepton scenarios.
Observed and Expected upper cross-section limits for direct RH slepton scenarios.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Acceptance (note the $z$-axis is in units of $10^{-4}$) for the N2C1m VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Observed and Expected upper cross-section limits for direct smuon scenarios.
Observed and Expected upper cross-section limits for direct smuon scenarios.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Efficiency for the N2C1m VBF higgsino process in the SR-VBF region. Truth dilepton invariant mass is constrained to be within the range [1,40] GeV.
Observed and Expected upper cross-section limits for direct LH smuon scenarios.
Observed and Expected upper cross-section limits for direct LH smuon scenarios.
Observed and Expected upper cross-section limits for wino-bino scenarios, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Observed and Expected upper cross-section limits for wino-bino scenarios, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Observed and Expected upper cross-section limits for wino-bino scenarios, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})>0$.
Observed and Expected upper cross-section limits for direct RH smuon scenarios.
Observed and Expected upper cross-section limits for direct RH smuon scenarios.
Observed and Expected upper cross-section limits for wino-bino scenarios, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Observed and Expected upper cross-section limits for wino-bino scenarios, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Observed and Expected upper cross-section limits for wino-bino scenarios, assuming $m(\tilde{\chi}_{2}^{0}) \times m(\tilde{\chi}_{1}^{0})<0$.
Observed and Expected upper cross-section limits for direct selectron scenarios.
Observed and Expected upper cross-section limits for direct selectron scenarios.
Observed and Expected upper cross-section limits for higgsino scenarios.
Observed and Expected upper cross-section limits for higgsino scenarios.
Observed and Expected upper cross-section limits for higgsino scenarios.
Observed and Expected upper cross-section limits for direct LH selectron scenarios.
Observed and Expected upper cross-section limits for direct LH selectron scenarios.
Observed and Expected upper cross-section limits for higgsino scenarios, assuming VBF production..
Observed and Expected upper cross-section limits for higgsino scenarios, assuming VBF production..
Observed and Expected upper cross-section limits for higgsino scenarios, assuming VBF production..
Observed and Expected upper cross-section limits for direct RH selectron scenarios.
Observed and Expected upper cross-section limits for direct RH selectron scenarios.
Observed and Expected upper cross-section limits for direct slepton scenarios.
Observed and Expected upper cross-section limits for direct slepton scenarios.
Observed and Expected upper cross-section limits for direct slepton scenarios.
Number of signal events in SR-E-1L1T for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-1L1T for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Observed and Expected upper cross-section limits for direct LH slepton scenarios.
Observed and Expected upper cross-section limits for direct LH slepton scenarios.
Observed and Expected upper cross-section limits for direct LH slepton scenarios.
Number of signal events in SR-E-high for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-high for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Observed and Expected upper cross-section limits for direct RH slepton scenarios.
Observed and Expected upper cross-section limits for direct RH slepton scenarios.
Observed and Expected upper cross-section limits for direct RH slepton scenarios.
Number of signal events in SR-E-low for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-low for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Observed and Expected upper cross-section limits for direct smuon scenarios.
Observed and Expected upper cross-section limits for direct smuon scenarios.
Observed and Expected upper cross-section limits for direct smuon scenarios.
Number of signal events in SR-E-med for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-med for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Observed and Expected upper cross-section limits for direct LH smuon scenarios.
Observed and Expected upper cross-section limits for direct LH smuon scenarios.
Observed and Expected upper cross-section limits for direct LH smuon scenarios.
Number of signal events in SR-S-high for the (m($\tilde{\ell}$),m($\tilde{\chi}_{1}^{0}$)) = (150 GeV, 140 GeV) Slepton signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-S-high for the (m($\tilde{\ell}$),m($\tilde{\chi}_{1}^{0}$)) = (150 GeV, 140 GeV) Slepton signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Observed and Expected upper cross-section limits for direct RH smuon scenarios.
Observed and Expected upper cross-section limits for direct RH smuon scenarios.
Observed and Expected upper cross-section limits for direct RH smuon scenarios.
Number of signal events in SR-S-low for the (m($\tilde{\ell}$),m($\tilde{\chi}_{1}^{0}$)) = (150 GeV, 140 GeV) Slepton signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-S-low for the (m($\tilde{\ell}$),m($\tilde{\chi}_{1}^{0}$)) = (150 GeV, 140 GeV) Slepton signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Observed and Expected upper cross-section limits for direct selectron scenarios.
Observed and Expected upper cross-section limits for direct selectron scenarios.
Observed and Expected upper cross-section limits for direct selectron scenarios.
Number of signal events in SR-VBF for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (100 GeV, 95 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-VBF for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (100 GeV, 95 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Observed and Expected upper cross-section limits for direct LH selectron scenarios.
Observed and Expected upper cross-section limits for direct LH selectron scenarios.
Observed and Expected upper cross-section limits for direct LH selectron scenarios.
Observed and Expected upper cross-section limits for direct RH selectron scenarios.
Observed and Expected upper cross-section limits for direct RH selectron scenarios.
Observed and Expected upper cross-section limits for direct RH selectron scenarios.
Number of signal events in SR-E-1L1T for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-1L1T for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-1L1T for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-high for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-high for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-high for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-low for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-low for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-low for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-med for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-med for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-E-med for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (155 GeV, 150 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-S-high for the (m($\tilde{\ell}$),m($\tilde{\chi}_{1}^{0}$)) = (150 GeV, 140 GeV) Slepton signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-S-high for the (m($\tilde{\ell}$),m($\tilde{\chi}_{1}^{0}$)) = (150 GeV, 140 GeV) Slepton signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-S-high for the (m($\tilde{\ell}$),m($\tilde{\chi}_{1}^{0}$)) = (150 GeV, 140 GeV) Slepton signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-S-low for the (m($\tilde{\ell}$),m($\tilde{\chi}_{1}^{0}$)) = (150 GeV, 140 GeV) Slepton signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-S-low for the (m($\tilde{\ell}$),m($\tilde{\chi}_{1}^{0}$)) = (150 GeV, 140 GeV) Slepton signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-S-low for the (m($\tilde{\ell}$),m($\tilde{\chi}_{1}^{0}$)) = (150 GeV, 140 GeV) Slepton signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-VBF for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (100 GeV, 95 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-VBF for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (100 GeV, 95 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Number of signal events in SR-VBF for the (m($\tilde{\chi}_{2}^{0}$),m($\tilde{\chi}_{1}^{0}$)) = (100 GeV, 95 GeV) Higgsino signal model at different stages of selection before and after weighting events to correspond to 140/fb.
Constraints on the Higgs boson self-coupling are set by combining double-Higgs boson analyses in the $b\bar{b}b\bar{b}$, $b\bar{b}\tau^+\tau^-$ and $b\bar{b} \gamma \gamma$ decay channels with single-Higgs boson analyses targeting the $\gamma \gamma$, $ZZ^*$, $WW^*$, $\tau^+ \tau^-$ and $b\bar{b}$ decay channels. The data used in these analyses were recorded by the ATLAS detector at the LHC in proton$-$proton collisions at $\sqrt{s}=13$ TeV and correspond to an integrated luminosity of 126$-$139 fb$^{-1}$. The combination of the double-Higgs analyses sets an upper limit of $\mu_{HH} < 2.4$ at 95% confidence level on the double-Higgs production cross-section normalised to its Standard Model prediction. Combining the single-Higgs and double-Higgs analyses, with the assumption that new physics affects only the Higgs boson self-coupling ($\lambda_{HHH}$), values outside the interval $-0.4< \kappa_{\lambda}=(\lambda_{HHH}/\lambda_{HHH}^{\textrm{SM}})< 6.3$ are excluded at 95% confidence level. The combined single-Higgs and double-Higgs analyses provide results with fewer assumptions, by adding in the fit more coupling modifiers introduced to account for the Higgs boson interactions with the other Standard Model particles. In this relaxed scenario, the constraint becomes $-1.4 < \kappa_{\lambda} < 6.1$ at 95% CL.
Observed and expected 95% CL upper limits on the signal strength for double-Higgs production from the bbbb, bb$\tau\tau$ and bb$\gamma\gamma$ decay channels, and their statistical combination. The value $m_H$ = 125.09 GeV is assumed when deriving the predicted SM cross-section. The expected limit and the corresponding error bands are derived assuming the absence of the HH process and with all nuisance parameters profiled to the observed data.
Observed and expected 95% CL exclusion limits on the production cross-sections of the combined ggF HH and VBF HH processes as a function of $\kappa_\lambda$, for the three double-Higgs search channels and their combination. The expected limits assume no HH production. The red line shows the theory prediction for the combined ggF HH and VBF HH cross-section as a function of $\kappa_\lambda$ where all parameters and couplings are set to their SM values except for $\kappa_\lambda$. The band surrounding the red cross-section lines indicate the theoretical uncertainty of the predicted cross-section.
Observed and expected 95% CL exclusion limits on the production cross-sections of the VBF HH process as a function of $\kappa_{2V}$, for the three double-Higgs search channels and their combination. The expected limits assume no VBF HH production. The red line shows the predicted VBF HH cross-section as a function of $\kappa_{2V}$. The bands surrounding the red cross-section lines indicate the theoretical uncertainty of the predicted cross-section. The uncertainty band is smaller than the width of the plotted line.
Observed values of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_\lambda$ parameter for the single-Higgs and double-Higgs analyses combination, with all other coupling modifiers fixed to unity.
Observed values of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_\lambda$ parameter for the double-Higgs analyses, with all other coupling modifiers fixed to unity.
Observed values of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_\lambda$ parameter for the single-Higgs analyses, with all other coupling modifiers fixed to unity.
Observed values of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_\lambda$ parameter for the single-Higgs and double-Higgs combination for the generic model (free floating $\kappa_t$, $\kappa_b$, $\kappa_V$ and $\kappa_\tau$). The observed best-fit value of $\kappa_\lambda$ for the generic model is shifted slightly relative to the other models because of its correlation with the best-fit values of the $\kappa_b$, $\kappa_t$ and $\kappa_\tau$ parameters, which are slightly below, but compatible with unity.
Expected values of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_\lambda$ parameter for the single-Higgs and double-Higgs analyses combination derived from the combined single-Higgs and double-Higgs analyses, with all other coupling modifiers fixed to unity.
Expected values of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_\lambda$ parameter for the double-Higgs analyses.
Expected values of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_\lambda$ parameter for the single-Higgs analyses, with all other coupling modifiers fixed to unity.
Expected values of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_\lambda$ parameter for the single-Higgs and double-Higgs analyses for the generic model (free floating $\kappa_t$, $\kappa_b$, $\kappa_V$ and $\kappa_\tau$).
Observed constraints in the $\kappa_\lambda$–$\kappa_t$ plane from single-Higgs and double-Higgs combination. The solid lines show the 68% CL contours. The observed constraint for the single- and double-Higgs combination for $\kappa_t$ values below unity is slightly less stringent than that for the single-Higgs fit alone due to the slightly higher best-fit value for this coupling modifier.
Observed constraints in the $\kappa_\lambda$–$\kappa_t$ plane from single-Higgs and double-Higgs combination. The dashed lines show the 95% CL contours. The observed constraint for the single- and double-Higgs combination for $\kappa_t$ values below unity is slightly less stringent than that for the single-Higgs fit alone due to the slightly higher best-fit value for this coupling modifier.
Observed constraints in the $\kappa_\lambda$–$\kappa_t$ plane from double-Higgs analysis. The solid lines show the 68% CL contours. The double-Higgs contours are shown for values of $\kappa_t$ smaller than 1.2.
Observed constraints in the $\kappa_\lambda$–$\kappa_t$ plane from double-Higgs analysis. The dashed lines show the 95% CL contours. The double-Higgs contours are shown for values of $\kappa_t$ smaller than 1.2.
Observed constraints in the $\kappa_\lambda$–$\kappa_t$ plane from single-Higgs analysis. The solid lines show the 68% CL contours.
Observed constraints in the $\kappa_\lambda$–$\kappa_t$ plane from single-Higgs analysis. The dashed lines show the 95% CL contours.
Expected constraints in the $\kappa_\lambda$–$\kappa_t$ plane from single-Higgs and double-Higgs combination. The solid lines show the 68% CL contours. The double-Higgs contours are shown for values of $\kappa_t$ smaller than 1.2.
Expected constraints in the $\kappa_\lambda$–$\kappa_t$ plane from single-Higgs and double-Higgs combination. The dashed lines show the 95% CL contours. The double-Higgs contours are shown for values of $\kappa_t$ smaller than 1.2.
Expected constraints in the $\kappa_\lambda$–$\kappa_t$ plane from double-Higgs analyses. The solid lines show the 68% CL contours. The double-Higgs contours are shown for values of $\kappa_t$ smaller than 1.2.
Expected constraints in the $\kappa_\lambda$–$\kappa_t$ plane from double-Higgs analyses. The dashed lines show the 95% CL contours. The double-Higgs contours are shown for values of $\kappa_t$ smaller than 1.2.
Expected constraints in the $\kappa_\lambda$–$\kappa_t$ plane from single-Higgs analyses. The solid lines show the 68% CL contours.
Expected constraints in the $\kappa_\lambda$–$\kappa_t$ plane from single-Higgs analyses. The dashed lines show the 95% CL contours.
Observed and expected 95% CL upper limits on the sum of the ggF HH and VBF HH production cross-section from the bbbb, bb$\tau\tau$ and bb$\gamma\gamma$ decay channels, and their statistical combination. The value $m_H$=125.09 GeV is assumed when deriving the predicted SM cross section. The expected limit and the corresponding error bands are derived assuming the absence of the HH process with all nuisance parameters profiled to the observed data. The SM prediction together with its theoretical uncertainty is also shown (red vertical band).
Observed value of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_\lambda$ parameter for the HH to bbbb analysis. All other coupling modifiers are fixed to their SM value.
Observed value of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_\lambda$ parameter for the HH to bb$\tau\tau$ analysis. All other coupling modifiers are fixed to their SM value.
Observed value of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_\lambda$ parameter for the HH to bb$\gamma\gamma$ analysis. All other coupling modifiers are fixed to their SM value.
Observed value of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_\lambda$ parameter for the double-Higgs combination. All other coupling modifiers are fixed to their SM value.
Expected value of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_\lambda$ parameter for HH to bbbb analysis. All other coupling modifiers are fixed to their SM value.
Expected value of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_\lambda$ parameter for HH to bb$\tau\tau$ analysis. All other coupling modifiers are fixed to their SM value.
Expected value of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_\lambda$ parameter for HH to bb$\gamma\gamma$ analysis. All other coupling modifiers are fixed to their SM value.
Expected value of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_\lambda$ parameter for double-Higgs combination. All other coupling modifiers are fixed to their SM value.
Observed value of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_{2V}$ parameter for the HH to bbbb analysis. All other coupling modifiers are fixed to their SM value.
Observed value of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_{2V}$ parameter for the HH to bb$\tau\tau$ analysis. All other coupling modifiers are fixed to their SM value.
Observed value of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_{2V}$ parameter for the HH to bb$\gamma\gamma$ analysis. All other coupling modifiers are fixed to their SM value.
Observed value of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_{2V}$ parameter for the double-Higgs combination. All other coupling modifiers are fixed to their SM value.
Expected value of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_{2V}$ parameter for the HH to bbbb analysis. All other coupling modifiers are fixed to their SM value.
Expected value of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_{2V}$ parameter for the HH to bb$\tau\tau$ analysis. All other coupling modifiers are fixed to their SM value.
Expected value of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_{2V}$ parameter for the HH to bb$\gamma\gamma$ analysis. All other coupling modifiers are fixed to their SM value.
Expected value of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_{2V}$ parameter for the double-Higgs combination. All other coupling modifiers are fixed to their SM value.
Observed constraints in the $\kappa_{2V}$–$\kappa_{V}$ plane from double-Higgs combination. The solid lines show the 68% (95%) CL contours.
Observed constraints in the $\kappa_{2V}$–$\kappa_{V}$ plane from double-Higgs combination. The dashed lines show the 68% (95%) CL contours.
Expected constraints in the $\kappa_{2V}$-$\kappa_{V}$ plane from double-Higgs combination. The solid lines show the 68% CL contours.
Expected constraints in the $\kappa_{2V}$-$\kappa_{V}$ plane from double-Higgs combination. The dashed lines show the 95% CL contours.
A search is presented for displaced production of Higgs bosons or $Z$ bosons, originating from the decay of a neutral long-lived particle (LLP) and reconstructed in the decay modes $H\rightarrow \gamma\gamma$ and $Z\rightarrow ee$. The analysis uses the full Run 2 data set of proton$-$proton collisions delivered by the LHC at an energy of $\sqrt{s}=13$ TeV between 2015 and 2018 and recorded by the ATLAS detector, corresponding to an integrated luminosity of 139 fb$^{-1}$. Exploiting the capabilities of the ATLAS liquid argon calorimeter to precisely measure the arrival times and trajectories of electromagnetic objects, the analysis searches for the signature of pairs of photons or electrons which arise from a common displaced vertex and which arrive after some delay at the calorimeter. The results are interpreted in a gauge-mediated supersymmetry breaking model with pair-produced higgsinos that decay to LLPs, and each LLP subsequently decays into either a Higgs boson or a $Z$ boson. The final state includes at least two particles that escape direct detection, giving rise to missing transverse momentum. No significant excess is observed above the background expectation. The results are used to set upper limits on the cross section for higgsino pair production, up to a $\tilde\chi^0_1$ mass of 369 (704) GeV for decays with 100% branching ratio of $\tilde\chi^0_1$ to Higgs ($Z$) bosons for a $\tilde\chi^0_1$ lifetime of 2 ns. A model-independent limit is also set on the production of pairs of photons or electrons with a significant delay in arrival at the calorimeter.
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 $\tilde{\chi}_1^+\tilde{\chi}_1^-$ 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.
This article presents a search for new resonances decaying into a $Z$ or $W$ boson and a 125 GeV Higgs boson $h$, and it targets the $\nu\bar{\nu}b\bar{b}$, $\ell^+\ell^-b\bar{b}$, or $\ell^{\pm}{\nu}b\bar{b}$ final states, where $\ell=e$ or $\mu$, in proton-proton collisions at $\sqrt{s}=13$ TeV. The data used correspond to a total integrated luminosity of 139 fb$^{-1}$ collected by the ATLAS detector during Run 2 of the LHC at CERN. The search is conducted by examining the reconstructed invariant or transverse mass distributions of $Zh$ or $Wh$ candidates for evidence of a localised excess in the mass range from 220 GeV to 5 TeV. No significant excess is observed and 95% confidence-level upper limits between 1.3 pb and 0.3 fb are placed on the production cross section times branching fraction of neutral and charged spin-1 resonances and CP-odd scalar bosons. These limits are converted into constraints on the parameter space of the Heavy Vector Triplet model and the two-Higgs-doublet model.
Acceptance * reconstruction efficiency for the P P --> Zprime --> Zh --> vvbb/cc signals in the 0-lepton channel.
Acceptance * reconstruction efficiency for the P P --> Zprime --> Zh --> vvbb/cc signals in the 0-lepton channel.
Acceptance * reconstruction efficiency for the P P --> Zprime --> Zh --> llbb/cc signals in the 2-lepton channel.
Acceptance * reconstruction efficiency for the P P --> Zprime --> Zh --> llbb/cc signals in the 2-lepton channel.
Acceptance * reconstruction efficiency for the P P --> bbA --> Zh --> vvbb signals in the 0-lepton channel.
Acceptance * reconstruction efficiency for the P P --> bbA --> Zh --> vvbb signals in the 0-lepton channel.
Acceptance * reconstruction efficiency for the P P --> bbA --> Zh --> llbb signals in the 2-lepton channel.
Acceptance * reconstruction efficiency for the P P --> bbA --> Zh --> llbb signals in the 2-lepton channel.
Acceptance * reconstruction efficiency for the P P --> Wprime --> Zh --> lvbb/cc signals in the 0-lepton channel.
Acceptance * reconstruction efficiency for the P P --> Wprime --> Zh --> lvbb/cc signals in the 0-lepton channel.
Acceptance * reconstruction efficiency for the P P --> Wprime --> Zh --> lvbb/cc signals in the 1-lepton channel.
Acceptance * reconstruction efficiency for the P P --> Wprime --> Zh --> lvbb/cc signals in the 1-lepton channel.
Event distributions of $m_{T,Vh}$ for the 0-lepton channel in the resolved 1 b-tag signal region. The background prediction is shown after a background-only maximum-likelihood Z' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 0-lepton channel in the resolved 1 b-tag signal region. The background prediction is shown after a background-only maximum-likelihood Z' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 0-lepton channel in the resolved 2 b-tag signal region. The background prediction is shown after a background-only maximum-likelihood Z' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 0-lepton channel in the resolved 2 b-tag signal region. The background prediction is shown after a background-only maximum-likelihood Z' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{Vh}$ for the 2-lepton channel in the resolved 1 b-tag signal region. The background prediction is shown after a background-only maximum-likelihood Z' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{Vh}$ for the 2-lepton channel in the resolved 1 b-tag signal region. The background prediction is shown after a background-only maximum-likelihood Z' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{Vh}$ for the 2-lepton channel in the resolved 2 b-tag signal region. The background prediction is shown after a background-only maximum-likelihood Z' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{Vh}$ for the 2-lepton channel in the resolved 2 b-tag signal region. The background prediction is shown after a background-only maximum-likelihood Z' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 0-lepton channel in the merged 1 b-tag signal region. The background prediction is shown after a background-only maximum-likelihood Z' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 0-lepton channel in the merged 1 b-tag signal region. The background prediction is shown after a background-only maximum-likelihood Z' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 0-lepton channel in the merged 2 b-tag signal region. The background prediction is shown after a background-only maximum-likelihood Z' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 0-lepton channel in the merged 2 b-tag signal region. The background prediction is shown after a background-only maximum-likelihood Z' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{Vh}$ for the 2-lepton channel in the merged 1 b-tag signal region. The background prediction is shown after a background-only maximum-likelihood Z' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{Vh}$ for the 2-lepton channel in the merged 1 b-tag signal region. The background prediction is shown after a background-only maximum-likelihood Z' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{Vh}$ for the 2-lepton channel in the merged 2 b-tag signal region. The background prediction is shown after a background-only maximum-likelihood Z' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{Vh}$ for the 2-lepton channel in the merged 2 b-tag signal region. The background prediction is shown after a background-only maximum-likelihood Z' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 1-lepton channel in the resolved 1 b-tag signal region. The background prediction is shown after a background-only maximum-likelihood W' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 1-lepton channel in the resolved 1 b-tag signal region. The background prediction is shown after a background-only maximum-likelihood W' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 1-lepton channel in the resolved 2 b-tag signal region. The background prediction is shown after a background-only maximum-likelihood W' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 1-lepton channel in the resolved 2 b-tag signal region. The background prediction is shown after a background-only maximum-likelihood W' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 1-lepton channel in the merged 1 b-tag signal region. The background prediction is shown after a background-only maximum-likelihood W' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 1-lepton channel in the merged 1 b-tag signal region. The background prediction is shown after a background-only maximum-likelihood W' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 1-lepton channel in the merged 2 b-tag signal region. The background prediction is shown after a background-only maximum-likelihood W' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 1-lepton channel in the merged 2 b-tag signal region. The background prediction is shown after a background-only maximum-likelihood W' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 0-lepton channel in the resolved 3+ b-tag signal region. The background prediction is shown after a background-only maximum-likelihood bbA fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 0-lepton channel in the resolved 3+ b-tag signal region. The background prediction is shown after a background-only maximum-likelihood bbA fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{Vh}$ for the 2-lepton channel in the resolved 3+ b-tag signal region. The background prediction is shown after a background-only maximum-likelihood bbA fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{Vh}$ for the 2-lepton channel in the resolved 3+ b-tag signal region. The background prediction is shown after a background-only maximum-likelihood bbA fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 0-lepton channel in the merged 2 b-tag signal region with additional b-tagged track jets not associated with the large-R jet. The background prediction is shown after a background-only maximum-likelihood bbA fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 0-lepton channel in the merged 2 b-tag signal region with additional b-tagged track jets not associated with the large-R jet. The background prediction is shown after a background-only maximum-likelihood bbA fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{Vh}$ for the 2-lepton channel in the merged 1+2 b-tag signal region with additional b-tagged track jets not associated with the large-R jet. The background prediction is shown after a background-only maximum-likelihood bbA fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{Vh}$ for the 2-lepton channel in the merged 1+2 b-tag signal region with additional b-tagged track jets not associated with the large-R jet. The background prediction is shown after a background-only maximum-likelihood bbA fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 0-lepton channel in the resolved 1 b-tag sideband control region. The background prediction is shown after a background-only maximum-likelihood W' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 0-lepton channel in the resolved 1 b-tag sideband control region. The background prediction is shown after a background-only maximum-likelihood W' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 0-lepton channel in the resolved 2 b-tag sideband control region. The background prediction is shown after a background-only maximum-likelihood W' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 0-lepton channel in the resolved 2 b-tag sideband control region. The background prediction is shown after a background-only maximum-likelihood W' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 1-lepton channel in the resolved 1 b-tag sideband control region. The background prediction is shown after a background-only maximum-likelihood W' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 1-lepton channel in the resolved 1 b-tag sideband control region. The background prediction is shown after a background-only maximum-likelihood W' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 1-lepton channel in the resolved 2 b-tag sideband control region. The background prediction is shown after a background-only maximum-likelihood W' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 1-lepton channel in the resolved 2 b-tag sideband control region. The background prediction is shown after a background-only maximum-likelihood W' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 0-lepton channel in the merged 1 b-tag sideband control region. The background prediction is shown after a background-only maximum-likelihood W' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 0-lepton channel in the merged 1 b-tag sideband control region. The background prediction is shown after a background-only maximum-likelihood W' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 0-lepton channel in the merged 2 b-tag sideband control region. The background prediction is shown after a background-only maximum-likelihood W' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 0-lepton channel in the merged 2 b-tag sideband control region. The background prediction is shown after a background-only maximum-likelihood W' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 1-lepton channel in the merged 1 b-tag sideband control region. The background prediction is shown after a background-only maximum-likelihood W' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 1-lepton channel in the merged 1 b-tag sideband control region. The background prediction is shown after a background-only maximum-likelihood W' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 1-lepton channel in the merged 2 b-tag sideband control region. The background prediction is shown after a background-only maximum-likelihood W' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 1-lepton channel in the merged 2 b-tag sideband control region. The background prediction is shown after a background-only maximum-likelihood W' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 0-lepton channel in the resolved 1 b-tag sideband control region. The background prediction is shown after a background-only maximum-likelihood Z' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 0-lepton channel in the resolved 1 b-tag sideband control region. The background prediction is shown after a background-only maximum-likelihood Z' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 0-lepton channel in the resolved 2 b-tag sideband control region. The background prediction is shown after a background-only maximum-likelihood Z' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 0-lepton channel in the resolved 2 b-tag sideband control region. The background prediction is shown after a background-only maximum-likelihood Z' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{Vh}$ for the 2-lepton channel in the resolved top control region. The background prediction is shown after a background-only maximum-likelihood Z' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{Vh}$ for the 2-lepton channel in the resolved top control region. The background prediction is shown after a background-only maximum-likelihood Z' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 0-lepton channel in the merged 1 b-tag sideband control region. The background prediction is shown after a background-only maximum-likelihood Z' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 0-lepton channel in the merged 1 b-tag sideband control region. The background prediction is shown after a background-only maximum-likelihood Z' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 0-lepton channel in the merged 2 b-tag sideband control region. The background prediction is shown after a background-only maximum-likelihood Z' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 0-lepton channel in the merged 2 b-tag sideband control region. The background prediction is shown after a background-only maximum-likelihood Z' fit to the data. In the plot, the last bin contains the overflow.
Upper limits on Zprime to Z h production cross section times branching fraction in pb.
Upper limits on Zprime to Z h production cross section times branching fraction in pb.
Upper limits on Wprime to W h production cross section times branching fraction in pb.
Upper limits on Wprime to W h production cross section times branching fraction in pb.
Upper limits on ggA to Z h production cross section times branching fraction in pb.
Upper limits on ggA to Z h production cross section times branching fraction in pb.
Upper limits on bbA to Z h production cross section times branching fraction in pb.
Upper limits on bbA to Z h production cross section times branching fraction in pb.
Expected and observed two-dimensional likelihood scans of the b-associated production cross section times branching fraction vs the gluon-fusion production cross section times branching fraction at $m_{A}$ = 220 GeV.
Expected and observed two-dimensional likelihood scans of the b-associated production cross section times branching fraction vs the gluon-fusion production cross section times branching fraction at $m_{A}$ = 220 GeV.
Expected and observed two-dimensional likelihood scans of the b-associated production cross section times branching fraction vs the gluon-fusion production cross section times branching fraction at $m_{A}$ = 260 GeV.
Expected and observed two-dimensional likelihood scans of the b-associated production cross section times branching fraction vs the gluon-fusion production cross section times branching fraction at $m_{A}$ = 260 GeV.
Expected and observed two-dimensional likelihood scans of the b-associated production cross section times branching fraction vs the gluon-fusion production cross section times branching fraction at $m_{A}$ = 300 GeV.
Expected and observed two-dimensional likelihood scans of the b-associated production cross section times branching fraction vs the gluon-fusion production cross section times branching fraction at $m_{A}$ = 300 GeV.
Expected and observed two-dimensional likelihood scans of the b-associated production cross section times branching fraction vs the gluon-fusion production cross section times branching fraction at $m_{A}$ = 340 GeV.
Expected and observed two-dimensional likelihood scans of the b-associated production cross section times branching fraction vs the gluon-fusion production cross section times branching fraction at $m_{A}$ = 340 GeV.
Expected and observed two-dimensional likelihood scans of the b-associated production cross section times branching fraction vs the gluon-fusion production cross section times branching fraction at $m_{A}$ = 380 GeV.
Expected and observed two-dimensional likelihood scans of the b-associated production cross section times branching fraction vs the gluon-fusion production cross section times branching fraction at $m_{A}$ = 380 GeV.
Expected and observed two-dimensional likelihood scans of the b-associated production cross section times branching fraction vs the gluon-fusion production cross section times branching fraction at $m_{A}$ = 400 GeV.
Expected and observed two-dimensional likelihood scans of the b-associated production cross section times branching fraction vs the gluon-fusion production cross section times branching fraction at $m_{A}$ = 400 GeV.
Expected and observed two-dimensional likelihood scans of the b-associated production cross section times branching fraction vs the gluon-fusion production cross section times branching fraction at $m_{A}$ = 420 GeV.
Expected and observed two-dimensional likelihood scans of the b-associated production cross section times branching fraction vs the gluon-fusion production cross section times branching fraction at $m_{A}$ = 420 GeV.
Expected and observed two-dimensional likelihood scans of the b-associated production cross section times branching fraction vs the gluon-fusion production cross section times branching fraction at $m_{A}$ = 440 GeV.
Expected and observed two-dimensional likelihood scans of the b-associated production cross section times branching fraction vs the gluon-fusion production cross section times branching fraction at $m_{A}$ = 440 GeV.
Expected and observed two-dimensional likelihood scans of the b-associated production cross section times branching fraction vs the gluon-fusion production cross section times branching fraction at $m_{A}$ = 460 GeV.
Expected and observed two-dimensional likelihood scans of the b-associated production cross section times branching fraction vs the gluon-fusion production cross section times branching fraction at $m_{A}$ = 460 GeV.
Expected and observed two-dimensional likelihood scans of the b-associated production cross section times branching fraction vs the gluon-fusion production cross section times branching fraction at $m_{A}$ = 500 GeV.
Expected and observed two-dimensional likelihood scans of the b-associated production cross section times branching fraction vs the gluon-fusion production cross section times branching fraction at $m_{A}$ = 500 GeV.
Expected and observed two-dimensional likelihood scans of the b-associated production cross section times branching fraction vs the gluon-fusion production cross section times branching fraction at $m_{A}$ = 600 GeV.
Expected and observed two-dimensional likelihood scans of the b-associated production cross section times branching fraction vs the gluon-fusion production cross section times branching fraction at $m_{A}$ = 600 GeV.
Expected and observed two-dimensional likelihood scans of the b-associated production cross section times branching fraction vs the gluon-fusion production cross section times branching fraction at $m_{A}$ = 700 GeV.
Expected and observed two-dimensional likelihood scans of the b-associated production cross section times branching fraction vs the gluon-fusion production cross section times branching fraction at $m_{A}$ = 700 GeV.
Expected and observed two-dimensional likelihood scans of the b-associated production cross section times branching fraction vs the gluon-fusion production cross section times branching fraction at $m_{A}$ = 800 GeV.
Expected and observed two-dimensional likelihood scans of the b-associated production cross section times branching fraction vs the gluon-fusion production cross section times branching fraction at $m_{A}$ = 800 GeV.
Expected and observed two-dimensional likelihood scans of the b-associated production cross section times branching fraction vs the gluon-fusion production cross section times branching fraction at $m_{A}$ = 900 GeV.
Expected and observed two-dimensional likelihood scans of the b-associated production cross section times branching fraction vs the gluon-fusion production cross section times branching fraction at $m_{A}$ = 900 GeV.
Expected and observed two-dimensional likelihood scans of the b-associated production cross section times branching fraction vs the gluon-fusion production cross section times branching fraction at $m_{A}$ = 1000 GeV.
Expected and observed two-dimensional likelihood scans of the b-associated production cross section times branching fraction vs the gluon-fusion production cross section times branching fraction at $m_{A}$ = 1000 GeV.
Expected and observed two-dimensional likelihood scans of the b-associated production cross section times branching fraction vs the gluon-fusion production cross section times branching fraction at $m_{A}$ = 1200 GeV.
Expected and observed two-dimensional likelihood scans of the b-associated production cross section times branching fraction vs the gluon-fusion production cross section times branching fraction at $m_{A}$ = 1200 GeV.
Expected and observed two-dimensional likelihood scans of the b-associated production cross section times branching fraction vs the gluon-fusion production cross section times branching fraction at $m_{A}$ = 1400 GeV.
Expected and observed two-dimensional likelihood scans of the b-associated production cross section times branching fraction vs the gluon-fusion production cross section times branching fraction at $m_{A}$ = 1400 GeV.
Expected and observed two-dimensional likelihood scans of the b-associated production cross section times branching fraction vs the gluon-fusion production cross section times branching fraction at $m_{A}$ = 1600 GeV.
Expected and observed two-dimensional likelihood scans of the b-associated production cross section times branching fraction vs the gluon-fusion production cross section times branching fraction at $m_{A}$ = 1600 GeV.
Expected and observed two-dimensional likelihood scans of the b-associated production cross section times branching fraction vs the gluon-fusion production cross section times branching fraction at $m_{A}$ = 2000 GeV.
Expected and observed two-dimensional likelihood scans of the b-associated production cross section times branching fraction vs the gluon-fusion production cross section times branching fraction at $m_{A}$ = 2000 GeV.
Acceptance * reconstruction efficiency for the P P --> A --> Zh --> vvbb signal in the 0-lepton channel.
Acceptance * reconstruction efficiency for the P P --> A --> Zh --> vvbb signal in the 0-lepton channel.
Acceptance * reconstruction efficiency for the P P --> A --> Zh --> llbb signal in the 2-lepton channel.
Acceptance * reconstruction efficiency for the P P --> A --> Zh --> llbb signal in the 2-lepton channel.
Event distributions of $m_{T,Vh}$ for the 0-lepton channel in the resolved 1 b-tag signal region. The background prediction is shown after a background-only maximum-likelihood W' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 0-lepton channel in the resolved 1 b-tag signal region. The background prediction is shown after a background-only maximum-likelihood W' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 0-lepton channel in the resolved 2 b-tag signal region. The background prediction is shown after a background-only maximum-likelihood W' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 0-lepton channel in the resolved 2 b-tag signal region. The background prediction is shown after a background-only maximum-likelihood W' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 0-lepton channel in the merged 1 b-tag signal region. The background prediction is shown after a background-only maximum-likelihood W' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 0-lepton channel in the merged 1 b-tag signal region. The background prediction is shown after a background-only maximum-likelihood W' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 0-lepton channel in the merged 2 b-tag signal region. The background prediction is shown after a background-only maximum-likelihood W' fit to the data. In the plot, the last bin contains the overflow.
Event distributions of $m_{T,Vh}$ for the 0-lepton channel in the merged 2 b-tag signal region. The background prediction is shown after a background-only maximum-likelihood W' fit to the data. In the plot, the last bin contains the overflow.
Distributions of expected upper limits at 95% confidence level on the cross section of P P --> A --> Zh as a function of bbA fraction an signal mass.
Distributions of expected upper limits at 95% confidence level on the cross section of P P --> A --> Zh as a function of bbA fraction an signal mass.
Distributions of observed upper limits at 95% confidence level on the cross section of P P --> A --> Zh as a function of bbA fraction an signal mass.
Distributions of observed upper limits at 95% confidence level on the cross section of P P --> A --> Zh as a function of bbA fraction an signal mass.
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.
Searches are performed for nonresonant and resonant di-Higgs boson production in the $b\bar{b}\gamma\gamma$ final state. The data set used corresponds to an integrated luminosity of 139 fb$^{-1}$ of proton-proton collisions at a center-of-mass energy of 13 TeV recorded by the ATLAS detector at the CERN Large Hadron Collider. No excess above the expected background is found and upper limits on the di-Higgs boson production cross sections are set. A 95% confidence-level upper limit of 4.2 times the cross section predicted by the Standard Model is set on $pp \rightarrow HH$ nonresonant production, where the expected limit is 5.7 times the Standard Model predicted value. The expected constraints are obtained for a background hypothesis excluding $pp \rightarrow HH$ production. The observed (expected) constraints on the Higgs boson trilinear coupling modifier $\kappa_{\lambda}$ are determined to be $[-1.5, 6.7]$ $([-2.4, 7.7])$ at 95% confidence level, where the expected constraints on $\kappa_{\lambda}$ are obtained excluding $pp \rightarrow HH$ production from the background hypothesis. For resonant production of a new hypothetical scalar particle $X$ ($X \rightarrow HH \rightarrow b\bar{b}\gamma\gamma$), limits on the cross section for $pp \to X \to HH$ are presented in the narrow-width approximation as a function of $m_{X}$ in the range $251 \leq m_{X} \leq 1000$ GeV. The observed (expected) limits on the cross section for $pp \to X \to HH$ range from 640 fb to 44 fb (391 fb to 46 fb) over the considered mass range.
The BDT distribution of the di-Higgs ggF signal for two different values of $\kappa_{\lambda}$ and the main backgrounds in the low mass region ($m^{*}_{b\bar{b}\gamma\gamma} < 350$ GeV). Distributions are normalized to unit area. The dotted lines denote the category boundaries. Events with a BDT score below 0.881 in the low mass region are discarded.
The BDT distribution of the di-Higgs ggF signal for two different values of $\kappa_{\lambda}$ and the main backgrounds in the low mass region ($m^{*}_{b\bar{b}\gamma\gamma} < 350$ GeV). Distributions are normalized to unit area. The dotted lines denote the category boundaries. Events with a BDT score below 0.881 in the low mass region are discarded.
The BDT distribution of the di-Higgs ggF signal for two different values of $\kappa_{\lambda}$ and the main backgrounds in the low mass region ($m^{*}_{b\bar{b}\gamma\gamma} < 350$ GeV). Distributions are normalized to unit area. The dotted lines denote the category boundaries. Events with a BDT score below 0.881 in the low mass region are discarded.
The BDT distribution of the di-Higgs ggF signal for two different values of $\kappa_{\lambda}$ and the main backgrounds in the low mass region ($m^{*}_{b\bar{b}\gamma\gamma} < 350$ GeV). Distributions are normalized to unit area. The dotted lines denote the category boundaries. Events with a BDT score below 0.881 in the low mass region are discarded.
The BDT distribution (with x-axis zoomed in) of the di-Higgs ggF signal for two different values of $\kappa_{\lambda}$ and the main backgrounds in the low mass region ($m^{*}_{b\bar{b}\gamma\gamma} < 350$ GeV). Distributions are normalized to unit area. The dotted lines denote the category boundaries. Events with a BDT score below 0.881 in the low mass region are discarded. The range of BDT scores is from 0.8 to 1.
The BDT distribution (with x-axis zoomed in) of the di-Higgs ggF signal for two different values of $\kappa_{\lambda}$ and the main backgrounds in the low mass region ($m^{*}_{b\bar{b}\gamma\gamma} < 350$ GeV). Distributions are normalized to unit area. The dotted lines denote the category boundaries. Events with a BDT score below 0.881 in the low mass region are discarded. The range of BDT scores is from 0.8 to 1.
The BDT distribution (with x-axis zoomed in) of the di-Higgs ggF signal for two different values of $\kappa_{\lambda}$ and the main backgrounds in the low mass region ($m^{*}_{b\bar{b}\gamma\gamma} < 350$ GeV). Distributions are normalized to unit area. The dotted lines denote the category boundaries. Events with a BDT score below 0.881 in the low mass region are discarded. The range of BDT scores is from 0.8 to 1.
The BDT distribution (with x-axis zoomed in) of the di-Higgs ggF signal for two different values of $\kappa_{\lambda}$ and the main backgrounds in the low mass region ($m^{*}_{b\bar{b}\gamma\gamma} < 350$ GeV). Distributions are normalized to unit area. The dotted lines denote the category boundaries. Events with a BDT score below 0.881 in the low mass region are discarded. The range of BDT scores is from 0.8 to 1.
The BDT distribution of the di-Higgs ggF signal for two different values of $\kappa_{\lambda}$ and the main backgrounds in the high mass region ($m^{*}_{b\bar{b}\gamma\gamma} > 350$ GeV). Distributions are normalized to unit area. The dotted lines denote the category boundaries. Events with a BDT score below 0.857 in the high mass region are discarded.
The BDT distribution of the di-Higgs ggF signal for two different values of $\kappa_{\lambda}$ and the main backgrounds in the high mass region ($m^{*}_{b\bar{b}\gamma\gamma} > 350$ GeV). Distributions are normalized to unit area. The dotted lines denote the category boundaries. Events with a BDT score below 0.857 in the high mass region are discarded.
The BDT distribution of the di-Higgs ggF signal for two different values of $\kappa_{\lambda}$ and the main backgrounds in the high mass region ($m^{*}_{b\bar{b}\gamma\gamma} > 350$ GeV). Distributions are normalized to unit area. The dotted lines denote the category boundaries. Events with a BDT score below 0.857 in the high mass region are discarded.
The BDT distribution of the di-Higgs ggF signal for two different values of $\kappa_{\lambda}$ and the main backgrounds in the high mass region ($m^{*}_{b\bar{b}\gamma\gamma} > 350$ GeV). Distributions are normalized to unit area. The dotted lines denote the category boundaries. Events with a BDT score below 0.857 in the high mass region are discarded.
The BDT distribution (with x-axis zoomed in) of the di-Higgs ggF signal for two different values of $\kappa_{\lambda}$ and the main backgrounds in the high mass region ($m^{*}_{b\bar{b}\gamma\gamma} > 350$ GeV). Distributions are normalized to unit area. The dotted lines denote the category boundaries. Events with a BDT score below 0.857 in the high mass region are discarded. The range of BDT scores is from 0.8 to 1.
The BDT distribution (with x-axis zoomed in) of the di-Higgs ggF signal for two different values of $\kappa_{\lambda}$ and the main backgrounds in the high mass region ($m^{*}_{b\bar{b}\gamma\gamma} > 350$ GeV). Distributions are normalized to unit area. The dotted lines denote the category boundaries. Events with a BDT score below 0.857 in the high mass region are discarded. The range of BDT scores is from 0.8 to 1.
The BDT distribution (with x-axis zoomed in) of the di-Higgs ggF signal for two different values of $\kappa_{\lambda}$ and the main backgrounds in the high mass region ($m^{*}_{b\bar{b}\gamma\gamma} > 350$ GeV). Distributions are normalized to unit area. The dotted lines denote the category boundaries. Events with a BDT score below 0.857 in the high mass region are discarded. The range of BDT scores is from 0.8 to 1.
The BDT distribution (with x-axis zoomed in) of the di-Higgs ggF signal for two different values of $\kappa_{\lambda}$ and the main backgrounds in the high mass region ($m^{*}_{b\bar{b}\gamma\gamma} > 350$ GeV). Distributions are normalized to unit area. The dotted lines denote the category boundaries. Events with a BDT score below 0.857 in the high mass region are discarded. The range of BDT scores is from 0.8 to 1.
The $BDT_{tot}$ score for the benchmark signal $m_{X}$ = 300 GeV and for the main backgrounds. Distributions are normalized to unit area. The dotted line denotes the event selection threshold. Events with a $BDT_{tot}$ score below 0.85 for $m_{X}$ = 300 GeV are discarded.
The $BDT_{tot}$ score for the benchmark signal $m_{X}$ = 300 GeV and for the main backgrounds. Distributions are normalized to unit area. The dotted line denotes the event selection threshold. Events with a $BDT_{tot}$ score below 0.85 for $m_{X}$ = 300 GeV are discarded.
The $BDT_{tot}$ score for the benchmark signal $m_{X}$ = 300 GeV and for the main backgrounds. Distributions are normalized to unit area. The dotted line denotes the event selection threshold. Events with a $BDT_{tot}$ score below 0.85 for $m_{X}$ = 300 GeV are discarded.
The $BDT_{tot}$ score for the benchmark signal $m_{X}$ = 300 GeV and for the main backgrounds. Distributions are normalized to unit area. The dotted line denotes the event selection threshold. Events with a $BDT_{tot}$ score below 0.85 for $m_{X}$ = 300 GeV are discarded.
The $BDT_{tot}$ score for the benchmark signal $m_{X}$ = 500 GeV and for the main backgrounds. Distributions are normalized to unit area. The dotted line denotes the event selection threshold. Events with a $BDT_{tot}$ score below 0.75 for $m_{X}$ = 500 GeV are discarded.
The $BDT_{tot}$ score for the benchmark signal $m_{X}$ = 500 GeV and for the main backgrounds. Distributions are normalized to unit area. The dotted line denotes the event selection threshold. Events with a $BDT_{tot}$ score below 0.75 for $m_{X}$ = 500 GeV are discarded.
The $BDT_{tot}$ score for the benchmark signal $m_{X}$ = 500 GeV and for the main backgrounds. Distributions are normalized to unit area. The dotted line denotes the event selection threshold. Events with a $BDT_{tot}$ score below 0.75 for $m_{X}$ = 500 GeV are discarded.
The $BDT_{tot}$ score for the benchmark signal $m_{X}$ = 500 GeV and for the main backgrounds. Distributions are normalized to unit area. The dotted line denotes the event selection threshold. Events with a $BDT_{tot}$ score below 0.75 for $m_{X}$ = 500 GeV are discarded.
Distributions of $m_{\gamma\gamma}$ in high mass BDT tight category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.
Distributions of $m_{\gamma\gamma}$ in high mass BDT tight category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.
Distributions of $m_{\gamma\gamma}$ in high mass BDT tight category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.
Distributions of $m_{\gamma\gamma}$ in high mass BDT tight category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.
Distributions of $m_{\gamma\gamma}$ in high mass BDT loose category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.
Distributions of $m_{\gamma\gamma}$ in high mass BDT loose category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.
Distributions of $m_{\gamma\gamma}$ in high mass BDT loose category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.
Distributions of $m_{\gamma\gamma}$ in high mass BDT loose category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.
Distributions of $m_{\gamma\gamma}$ in low mass BDT tight category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.
Distributions of $m_{\gamma\gamma}$ in low mass BDT tight category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.
Distributions of $m_{\gamma\gamma}$ in low mass BDT tight category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.
Distributions of $m_{\gamma\gamma}$ in low mass BDT tight category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.
Distributions of $m_{\gamma\gamma}$ in low mass BDT loose category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.
Distributions of $m_{\gamma\gamma}$ in low mass BDT loose category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.
Distributions of $m_{\gamma\gamma}$ in low mass BDT loose category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.
Distributions of $m_{\gamma\gamma}$ in low mass BDT loose category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.
Distributions of $m_{\gamma\gamma}$ for the selections used for the resonance mass point $m_{X}$ = 300 GeV for the resonant search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband. The scalar resonance signal is scaled to a total production cross section $\sigma(pp \rightarrow X \rightarrow HH)$ = 370 fb.
Distributions of $m_{\gamma\gamma}$ for the selections used for the resonance mass point $m_{X}$ = 300 GeV for the resonant search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband. The scalar resonance signal is scaled to a total production cross section $\sigma(pp \rightarrow X \rightarrow HH)$ = 370 fb.
Distributions of $m_{\gamma\gamma}$ for the selections used for the resonance mass point $m_{X}$ = 300 GeV for the resonant search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband. The scalar resonance signal is scaled to a total production cross section $\sigma(pp \rightarrow X \rightarrow HH)$ = 370 fb.
Distributions of $m_{\gamma\gamma}$ for the selections used for the resonance mass point $m_{X}$ = 300 GeV for the resonant search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband. The scalar resonance signal is scaled to a total production cross section $\sigma(pp \rightarrow X \rightarrow HH)$ = 370 fb.
Distributions of $m_{\gamma\gamma}$ for the selections used for the resonance mass point $m_{X}$ = 500 GeV for the resonant search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband. The scalar resonance signal is scaled to a total production cross section $\sigma(pp \rightarrow X \rightarrow HH)$ = 67 fb.
Distributions of $m_{\gamma\gamma}$ for the selections used for the resonance mass point $m_{X}$ = 500 GeV for the resonant search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband. The scalar resonance signal is scaled to a total production cross section $\sigma(pp \rightarrow X \rightarrow HH)$ = 67 fb.
Distributions of $m_{\gamma\gamma}$ for the selections used for the resonance mass point $m_{X}$ = 500 GeV for the resonant search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband. The scalar resonance signal is scaled to a total production cross section $\sigma(pp \rightarrow X \rightarrow HH)$ = 67 fb.
Distributions of $m_{\gamma\gamma}$ for the selections used for the resonance mass point $m_{X}$ = 500 GeV for the resonant search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband. The scalar resonance signal is scaled to a total production cross section $\sigma(pp \rightarrow X \rightarrow HH)$ = 67 fb.
The number of data events observed in the 120 GeV < $m_{\gamma\gamma}$ < 130 GeV window, the number of $HH$ signal events expected for $\kappa_{\lambda}$ = 1 and for $\kappa_{\lambda}$ = 10, and events expected for single Higgs boson production (estimated using MC simulation), as well as for continuum background. For the single Higgs boson, Rest includes VBF, $WH$, $tHqb$, and $tHW$. The values are obtained from a fit of the Asimov data set generated under the SM signal-plus-background hypothesis, $\kappa_{\lambda}$ = 1. The continuum background component of the Asimov data set is obtained from the fit of the data sideband. The uncertainties in $HH$ signals and single Higgs boson background include the systematic uncertainties discussed in Section 6. The uncertainty in the continuum background is given by the sum in quadrature of the statistical uncertainty from the fit to the data and the spurious-signal uncertainty.
The number of data events observed in the 120 GeV < $m_{\gamma\gamma}$ < 130 GeV window, the number of $HH$ signal events expected for $\kappa_{\lambda}$ = 1 and for $\kappa_{\lambda}$ = 10, and events expected for single Higgs boson production (estimated using MC simulation), as well as for continuum background. For the single Higgs boson, Rest includes VBF, $WH$, $tHqb$, and $tHW$. The values are obtained from a fit of the Asimov data set generated under the SM signal-plus-background hypothesis, $\kappa_{\lambda}$ = 1. The continuum background component of the Asimov data set is obtained from the fit of the data sideband. The uncertainties in $HH$ signals and single Higgs boson background include the systematic uncertainties discussed in Section 6. The uncertainty in the continuum background is given by the sum in quadrature of the statistical uncertainty from the fit to the data and the spurious-signal uncertainty.
The number of data events observed in the 120 GeV < $m_{\gamma\gamma}$ < 130 GeV window, the number of $HH$ signal events expected for $\kappa_{\lambda}$ = 1 and for $\kappa_{\lambda}$ = 10, and events expected for single Higgs boson production (estimated using MC simulation), as well as for continuum background. For the single Higgs boson, Rest includes VBF, $WH$, $tHqb$, and $tHW$. The values are obtained from a fit of the Asimov data set generated under the SM signal-plus-background hypothesis, $\kappa_{\lambda}$ = 1. The continuum background component of the Asimov data set is obtained from the fit of the data sideband. The uncertainties in $HH$ signals and single Higgs boson background include the systematic uncertainties discussed in Section 6. The uncertainty in the continuum background is given by the sum in quadrature of the statistical uncertainty from the fit to the data and the spurious-signal uncertainty.
The number of data events observed in the 120 GeV < $m_{\gamma\gamma}$ < 130 GeV window, the number of $HH$ signal events expected for $\kappa_{\lambda}$ = 1 and for $\kappa_{\lambda}$ = 10, and events expected for single Higgs boson production (estimated using MC simulation), as well as for continuum background. For the single Higgs boson, Rest includes VBF, $WH$, $tHqb$, and $tHW$. The values are obtained from a fit of the Asimov data set generated under the SM signal-plus-background hypothesis, $\kappa_{\lambda}$ = 1. The continuum background component of the Asimov data set is obtained from the fit of the data sideband. The uncertainties in $HH$ signals and single Higgs boson background include the systematic uncertainties discussed in Section 6. The uncertainty in the continuum background is given by the sum in quadrature of the statistical uncertainty from the fit to the data and the spurious-signal uncertainty.
Observed and expected limits at 95% CL on the cross section of nonresonant Higgs boson pair production as a function of the Higgs boson self-coupling modifier $\kappa_{\lambda}= \lambda_{HHH}/\lambda^{\textrm{SM}}_{HHH}$. The expected constraints on $\kappa_{\lambda}$ are obtained with a background hypothesis excluding $pp \rightarrow HH$ production. The $\pm 1\sigma$ and $\pm 2\sigma$ variations about the expected limit due to statistical and systematic uncertainties are also shown. The theory prediction curve represents the scenario where all parameters and couplings are set to their SM values except for $\kappa_{\lambda}$. The uncertainty band of the theory prediction curve shows the cross-section uncertainty.
Observed and expected limits at 95% CL on the cross section of nonresonant Higgs boson pair production as a function of the Higgs boson self-coupling modifier $\kappa_{\lambda}= \lambda_{HHH}/\lambda^{\textrm{SM}}_{HHH}$. The expected constraints on $\kappa_{\lambda}$ are obtained with a background hypothesis excluding $pp \rightarrow HH$ production. The $\pm 1\sigma$ and $\pm 2\sigma$ variations about the expected limit due to statistical and systematic uncertainties are also shown. The theory prediction curve represents the scenario where all parameters and couplings are set to their SM values except for $\kappa_{\lambda}$. The uncertainty band of the theory prediction curve shows the cross-section uncertainty.
Observed and expected limits at 95% CL on the cross section of nonresonant Higgs boson pair production as a function of the Higgs boson self-coupling modifier $\kappa_{\lambda}= \lambda_{HHH}/\lambda^{\textrm{SM}}_{HHH}$. The expected constraints on $\kappa_{\lambda}$ are obtained with a background hypothesis excluding $pp \rightarrow HH$ production. The $\pm 1\sigma$ and $\pm 2\sigma$ variations about the expected limit due to statistical and systematic uncertainties are also shown. The theory prediction curve represents the scenario where all parameters and couplings are set to their SM values except for $\kappa_{\lambda}$. The uncertainty band of the theory prediction curve shows the cross-section uncertainty.
Observed and expected limits at 95% CL on the cross section of nonresonant Higgs boson pair production as a function of the Higgs boson self-coupling modifier $\kappa_{\lambda}= \lambda_{HHH}/\lambda^{\textrm{SM}}_{HHH}$. The expected constraints on $\kappa_{\lambda}$ are obtained with a background hypothesis excluding $pp \rightarrow HH$ production. The $\pm 1\sigma$ and $\pm 2\sigma$ variations about the expected limit due to statistical and systematic uncertainties are also shown. The theory prediction curve represents the scenario where all parameters and couplings are set to their SM values except for $\kappa_{\lambda}$. The uncertainty band of the theory prediction curve shows the cross-section uncertainty.
Values of the negative log-profile-likelihood ratio ($-2ln\Lambda$) as a function of $\kappa_{\lambda}$ evaluated for the combination of all the categories of the nonresonant search. The coupling of the Higgs boson to fermions and gauge bosons is set to SM values in the profile likelihood calculation. The Asimov data set is generated under the SM signal-plus-background hypothesis, $\kappa_{\lambda}$= 1. All systematic uncertainties, including the theoretical uncertainties in the di-Higgs boson production cross section, are included. The intersections of the solid curves and the horizontal dashed lines indicate the 1$\sigma$ and 2$\sigma$ confidence-level intervals.
Values of the negative log-profile-likelihood ratio ($-2ln\Lambda$) as a function of $\kappa_{\lambda}$ evaluated for the combination of all the categories of the nonresonant search. The coupling of the Higgs boson to fermions and gauge bosons is set to SM values in the profile likelihood calculation. The Asimov data set is generated under the SM signal-plus-background hypothesis, $\kappa_{\lambda}$= 1. All systematic uncertainties, including the theoretical uncertainties in the di-Higgs boson production cross section, are included. The intersections of the solid curves and the horizontal dashed lines indicate the 1$\sigma$ and 2$\sigma$ confidence-level intervals.
Values of the negative log-profile-likelihood ratio ($-2ln\Lambda$) as a function of $\kappa_{\lambda}$ evaluated for the combination of all the categories of the nonresonant search. The coupling of the Higgs boson to fermions and gauge bosons is set to SM values in the profile likelihood calculation. The Asimov data set is generated under the SM signal-plus-background hypothesis, $\kappa_{\lambda}$= 1. All systematic uncertainties, including the theoretical uncertainties in the di-Higgs boson production cross section, are included. The intersections of the solid curves and the horizontal dashed lines indicate the 1$\sigma$ and 2$\sigma$ confidence-level intervals.
Values of the negative log-profile-likelihood ratio ($-2ln\Lambda$) as a function of $\kappa_{\lambda}$ evaluated for the combination of all the categories of the nonresonant search. The coupling of the Higgs boson to fermions and gauge bosons is set to SM values in the profile likelihood calculation. The Asimov data set is generated under the SM signal-plus-background hypothesis, $\kappa_{\lambda}$= 1. All systematic uncertainties, including the theoretical uncertainties in the di-Higgs boson production cross section, are included. The intersections of the solid curves and the horizontal dashed lines indicate the 1$\sigma$ and 2$\sigma$ confidence-level intervals.
The number of events observed in the 120 < $m_{\gamma\gamma}$ < 130 GeV window in data, the number of events expected for scalar resonance signals of masses $m_{X}$ = 300 GeV and $m_{X}$ = 500 GeV assuming a total production cross section $\sigma(pp \rightarrow X \rightarrow HH)$ equal to the observed exclusion limits of Figure 15, and events expected for SM $HH$ and single Higgs boson production (estimated using MC simulation), as well as for continuum background. The values are obtained from a fit of the Asimov data set generated under the signal-plus-background hypothesis. The continuum background component of the Asimov data set is obtained from the fit of the data sideband. The uncertainties in the resonant signals and the SM $HH$ and single-Higgs-boson backgrounds include the systematic uncertainties discussed in Section 6. The uncertainty in the continuum background is given by the sum in quadrature of the statistical uncertainty from the fit to the data and the spurious-signal uncertainty.
The number of events observed in the 120 < $m_{\gamma\gamma}$ < 130 GeV window in data, the number of events expected for scalar resonance signals of masses $m_{X}$ = 300 GeV and $m_{X}$ = 500 GeV assuming a total production cross section $\sigma(pp \rightarrow X \rightarrow HH)$ equal to the observed exclusion limits of Figure 15, and events expected for SM $HH$ and single Higgs boson production (estimated using MC simulation), as well as for continuum background. The values are obtained from a fit of the Asimov data set generated under the signal-plus-background hypothesis. The continuum background component of the Asimov data set is obtained from the fit of the data sideband. The uncertainties in the resonant signals and the SM $HH$ and single-Higgs-boson backgrounds include the systematic uncertainties discussed in Section 6. The uncertainty in the continuum background is given by the sum in quadrature of the statistical uncertainty from the fit to the data and the spurious-signal uncertainty.
The number of events observed in the 120 < $m_{\gamma\gamma}$ < 130 GeV window in data, the number of events expected for scalar resonance signals of masses $m_{X}$ = 300 GeV and $m_{X}$ = 500 GeV assuming a total production cross section $\sigma(pp \rightarrow X \rightarrow HH)$ equal to the observed exclusion limits of Figure 15, and events expected for SM $HH$ and single Higgs boson production (estimated using MC simulation), as well as for continuum background. The values are obtained from a fit of the Asimov data set generated under the signal-plus-background hypothesis. The continuum background component of the Asimov data set is obtained from the fit of the data sideband. The uncertainties in the resonant signals and the SM $HH$ and single-Higgs-boson backgrounds include the systematic uncertainties discussed in Section 6. The uncertainty in the continuum background is given by the sum in quadrature of the statistical uncertainty from the fit to the data and the spurious-signal uncertainty.
The number of events observed in the 120 < $m_{\gamma\gamma}$ < 130 GeV window in data, the number of events expected for scalar resonance signals of masses $m_{X}$ = 300 GeV and $m_{X}$ = 500 GeV assuming a total production cross section $\sigma(pp \rightarrow X \rightarrow HH)$ equal to the observed exclusion limits of Figure 15, and events expected for SM $HH$ and single Higgs boson production (estimated using MC simulation), as well as for continuum background. The values are obtained from a fit of the Asimov data set generated under the signal-plus-background hypothesis. The continuum background component of the Asimov data set is obtained from the fit of the data sideband. The uncertainties in the resonant signals and the SM $HH$ and single-Higgs-boson backgrounds include the systematic uncertainties discussed in Section 6. The uncertainty in the continuum background is given by the sum in quadrature of the statistical uncertainty from the fit to the data and the spurious-signal uncertainty.
Observed and expected limits at 95% CL on the production cross section of a narrow-width scalar resonance $X$ as a function of the mass $m_{X}$ of the hypothetical scalar particle. The black solid line represents the observed upper limits. The dashed line represents the expected upper limits. The $\pm 1\sigma$ and $\pm 2\sigma$ variations about the expected limit due to statistical and systematic uncertainties are also shown.
Observed and expected limits at 95% CL on the production cross section of a narrow-width scalar resonance $X$ as a function of the mass $m_{X}$ of the hypothetical scalar particle. The black solid line represents the observed upper limits. The dashed line represents the expected upper limits. The $\pm 1\sigma$ and $\pm 2\sigma$ variations about the expected limit due to statistical and systematic uncertainties are also shown.
Observed and expected limits at 95% CL on the production cross section of a narrow-width scalar resonance $X$ as a function of the mass $m_{X}$ of the hypothetical scalar particle. The black solid line represents the observed upper limits. The dashed line represents the expected upper limits. The $\pm 1\sigma$ and $\pm 2\sigma$ variations about the expected limit due to statistical and systematic uncertainties are also shown.
Observed and expected limits at 95% CL on the production cross section of a narrow-width scalar resonance $X$ as a function of the mass $m_{X}$ of the hypothetical scalar particle. The black solid line represents the observed upper limits. The dashed line represents the expected upper limits. The $\pm 1\sigma$ and $\pm 2\sigma$ variations about the expected limit due to statistical and systematic uncertainties are also shown.
Breakdown of the dominant systematic uncertainties. The impact of the uncertainties is defined according to the statistical analysis described in Section 7. It corresponds to the relative variation of the expected upper limit on the cross section when re-evaluating the profile likelihood ratio after fixing the nuisance parameter in question to its best-fit value, while all remaining nuisance parameters remain free to float. The impact is shown in %. Only systematic uncertainties with an impact of at least 0.2% are shown. Uncertainties of the "Norm. + Shape" type affect both the normalization and the parameters of the functional form. The rest of the uncertainties affect only the yields.
Breakdown of the dominant systematic uncertainties. The impact of the uncertainties is defined according to the statistical analysis described in Section 7. It corresponds to the relative variation of the expected upper limit on the cross section when re-evaluating the profile likelihood ratio after fixing the nuisance parameter in question to its best-fit value, while all remaining nuisance parameters remain free to float. The impact is shown in %. Only systematic uncertainties with an impact of at least 0.2% are shown. Uncertainties of the "Norm. + Shape" type affect both the normalization and the parameters of the functional form. The rest of the uncertainties affect only the yields.
Breakdown of the dominant systematic uncertainties. The impact of the uncertainties is defined according to the statistical analysis described in Section 7. It corresponds to the relative variation of the expected upper limit on the cross section when re-evaluating the profile likelihood ratio after fixing the nuisance parameter in question to its best-fit value, while all remaining nuisance parameters remain free to float. The impact is shown in %. Only systematic uncertainties with an impact of at least 0.2% are shown. Uncertainties of the "Norm. + Shape" type affect both the normalization and the parameters of the functional form. The rest of the uncertainties affect only the yields.
Breakdown of the dominant systematic uncertainties. The impact of the uncertainties is defined according to the statistical analysis described in Section 7. It corresponds to the relative variation of the expected upper limit on the cross section when re-evaluating the profile likelihood ratio after fixing the nuisance parameter in question to its best-fit value, while all remaining nuisance parameters remain free to float. The impact is shown in %. Only systematic uncertainties with an impact of at least 0.2% are shown. Uncertainties of the "Norm. + Shape" type affect both the normalization and the parameters of the functional form. The rest of the uncertainties affect only the yields.
Cutflow for nonresonant di-Higgs ggF signal sample, yields are normalized to 139 $fb^{-1}$.
Cutflow for nonresonant di-Higgs ggF signal sample, yields are normalized to 139 $fb^{-1}$.
Cutflow for nonresonant di-Higgs ggF signal sample, yields are normalized to 139 $fb^{-1}$.
Cutflow for nonresonant di-Higgs ggF signal sample, yields are normalized to 139 $fb^{-1}$.
Cutflow for resonant signal sample, with $m_{X}$ = 300 GeV, yields are normalized to 139 $fb^{-1}$.
Cutflow for resonant signal sample, with $m_{X}$ = 300 GeV, yields are normalized to 139 $fb^{-1}$.
Cutflow for resonant signal sample, with $m_{X}$ = 300 GeV, yields are normalized to 139 $fb^{-1}$.
Cutflow for resonant signal sample, with $m_{X}$ = 300 GeV, yields are normalized to 139 $fb^{-1}$.
Cutflow for resonant signal sample, with $m_{X}$ = 500 GeV, yields are normalized to 139 $fb^{-1}$.
Cutflow for resonant signal sample, with $m_{X}$ = 500 GeV, yields are normalized to 139 $fb^{-1}$.
Cutflow for resonant signal sample, with $m_{X}$ = 500 GeV, yields are normalized to 139 $fb^{-1}$.
Cutflow for resonant signal sample, with $m_{X}$ = 500 GeV, yields are normalized to 139 $fb^{-1}$.
Comparison of $m_{b\bar{b}}$ distributions when applying the specific b-jet energy calibration and the nominal jet energy calibration. The distributions are fitted using a Bukin function, and the values of the peak position, resolution and the relative improvement are reported in the legend.
Comparison of $m_{b\bar{b}}$ distributions when applying the specific b-jet energy calibration and the nominal jet energy calibration. The distributions are fitted using a Bukin function, and the values of the peak position, resolution and the relative improvement are reported in the legend.
Comparison of $m_{b\bar{b}}$ distributions when applying the specific b-jet energy calibration and the nominal jet energy calibration. The distributions are fitted using a Bukin function, and the values of the peak position, resolution and the relative improvement are reported in the legend.
Comparison of $m_{b\bar{b}}$ distributions when applying the specific b-jet energy calibration and the nominal jet energy calibration. The distributions are fitted using a Bukin function, and the values of the peak position, resolution and the relative improvement are reported in the legend.
Fit results of $m_{b\bar{b}}$ distributions when applying the specific b-jet energy calibration and the nominal jet energy calibration. The distributions are fitted using a Bukin function, and the values of the peak position, resolution and the relative improvement are reported in the legend.
Fit results of $m_{b\bar{b}}$ distributions when applying the specific b-jet energy calibration and the nominal jet energy calibration. The distributions are fitted using a Bukin function, and the values of the peak position, resolution and the relative improvement are reported in the legend.
Fit results of $m_{b\bar{b}}$ distributions when applying the specific b-jet energy calibration and the nominal jet energy calibration. The distributions are fitted using a Bukin function, and the values of the peak position, resolution and the relative improvement are reported in the legend.
Fit results of $m_{b\bar{b}}$ distributions when applying the specific b-jet energy calibration and the nominal jet energy calibration. The distributions are fitted using a Bukin function, and the values of the peak position, resolution and the relative improvement are reported in the legend.
The relative amount (purity) of expected events from SM $HH$ and single Higgs boson production processes for each of the four categories of the nonresonant search. The Higgs boson pair production with $k_{\lambda} = 1$ is considered as signal in (a), while the case with $k_{\lambda} = 10$ is considered as signal in (b).
The relative amount (purity) of expected events from SM $HH$ and single Higgs boson production processes for each of the four categories of the nonresonant search. The Higgs boson pair production with $k_{\lambda} = 1$ is considered as signal in (a), while the case with $k_{\lambda} = 10$ is considered as signal in (b).
The relative amount (purity) of expected events from SM $HH$ and single Higgs boson production processes for each of the four categories of the nonresonant search. The Higgs boson pair production with $k_{\lambda} = 1$ is considered as signal in (a), while the case with $k_{\lambda} = 10$ is considered as signal in (b).
The relative amount (purity) of expected events from SM $HH$ and single Higgs boson production processes for each of the four categories of the nonresonant search. The Higgs boson pair production with $k_{\lambda} = 1$ is considered as signal in (a), while the case with $k_{\lambda} = 10$ is considered as signal in (b).
The expected significance in each of the four categories of the nonresonant search. The Higgs boson pair production with $k_{\lambda} = 1$ is considered as signal in (a), while the case with $k_{\lambda} = 10$ is considered as signal in (b). The single Higgs boson processes and the di-photon continuum spectrum are considered as background.
The expected significance in each of the four categories of the nonresonant search. The Higgs boson pair production with $k_{\lambda} = 1$ is considered as signal in (a), while the case with $k_{\lambda} = 10$ is considered as signal in (b). The single Higgs boson processes and the di-photon continuum spectrum are considered as background.
The expected significance in each of the four categories of the nonresonant search. The Higgs boson pair production with $k_{\lambda} = 1$ is considered as signal in (a), while the case with $k_{\lambda} = 10$ is considered as signal in (b). The single Higgs boson processes and the di-photon continuum spectrum are considered as background.
The expected significance in each of the four categories of the nonresonant search. The Higgs boson pair production with $k_{\lambda} = 1$ is considered as signal in (a), while the case with $k_{\lambda} = 10$ is considered as signal in (b). The single Higgs boson processes and the di-photon continuum spectrum are considered as background.
Spurious signal result for the exponential pdf for the various ggF nonresonant di-Higgs categories. In each category, the spurious signal value ($n_{sp}$) and its ratio to the expected statistical error ($Z_{spur}$) from data are shown.
Spurious signal result for the exponential pdf for the various ggF nonresonant di-Higgs categories. In each category, the spurious signal value ($n_{sp}$) and its ratio to the expected statistical error ($Z_{spur}$) from data are shown.
Spurious signal result for the exponential pdf for the various ggF nonresonant di-Higgs categories. In each category, the spurious signal value ($n_{sp}$) and its ratio to the expected statistical error ($Z_{spur}$) from data are shown.
Spurious signal result for the exponential pdf for the various ggF nonresonant di-Higgs categories. In each category, the spurious signal value ($n_{sp}$) and its ratio to the expected statistical error ($Z_{spur}$) from data are shown.
Spurious signal result for the exponential pdf as function of the resonant di-Higgs signal mass. The spurious signal value and its ratio to the expected statistical error from data are shown.
Spurious signal result for the exponential pdf as function of the resonant di-Higgs signal mass. The spurious signal value and its ratio to the expected statistical error from data are shown.
Spurious signal result for the exponential pdf as function of the resonant di-Higgs signal mass. The spurious signal value and its ratio to the expected statistical error from data are shown.
Spurious signal result for the exponential pdf as function of the resonant di-Higgs signal mass. The spurious signal value and its ratio to the expected statistical error from data are shown.
Distributions of the signal efficiency as a function of $\kappa_{\lambda}$, for the di-Higgs boson ggF nonresonant production mode. The range of $\kappa_{\lambda}$ in the table is from -10 to 10.
Distributions of the signal efficiency as a function of $\kappa_{\lambda}$, for the di-Higgs boson ggF nonresonant production mode. The range of $\kappa_{\lambda}$ in the table is from -10 to 10.
Distributions of the signal efficiency as a function of $\kappa_{\lambda}$, for the di-Higgs boson ggF nonresonant production mode. The range of $\kappa_{\lambda}$ in the table is from -10 to 10.
Distributions of the signal efficiency as a function of $\kappa_{\lambda}$, for the di-Higgs boson ggF nonresonant production mode. The range of $\kappa_{\lambda}$ in the table is from -10 to 10.
Distributions of the signal efficiency as a function of $\kappa_{\lambda}$, for the di-Higgs boson VBF nonresonant production mode. The range of $\kappa_{\lambda}$ in the table is from -10 to 10.
Distributions of the signal efficiency as a function of $\kappa_{\lambda}$, for the di-Higgs boson VBF nonresonant production mode. The range of $\kappa_{\lambda}$ in the table is from -10 to 10.
Distributions of the signal efficiency as a function of $\kappa_{\lambda}$, for the di-Higgs boson VBF nonresonant production mode. The range of $\kappa_{\lambda}$ in the table is from -10 to 10.
Distributions of the signal efficiency as a function of $\kappa_{\lambda}$, for the di-Higgs boson VBF nonresonant production mode. The range of $\kappa_{\lambda}$ in the table is from -10 to 10.
Values of the negative log-profile-likelihood ($-2ln\Lambda$) as a function of $\kappa_{\lambda}$ evaluated for the combination of all the categories of the nonresonant search. The coupling of the Higgs boson to fermions and gauge bosons is set to SM values in the profile likelihood calculation. The Asimov data set is generated under the SM signal-plus-background hypothesis, $\kappa_{\lambda}$= 1. All systematic uncertainties, including the theoretical uncertainties on the di-Higgs boson production cross section, are included. The intersections of the solid curves and the horizontal dashed lines indicate the 1$\sigma$ and 2$\sigma$ confidence level intervals. The best fit value corresponds to $\kappa_{\lambda}$ = $2.8^{+2.0}_{-2.2}(^{+3.8}_{-4.3})$ for the 1$\sigma$(2$\sigma$) confidence interval. The expected value corresponds to $\kappa_{\lambda}$ = $1.0^{+5.5}_{-2.4}(^{+7.3}_{-4.2})$ for the 1$\sigma$(2$\sigma$) confidence interval. The dashed curves represent values of the negative log-profile-likelihood where the Higgs boson branching fractions and the cross section of the production modes are varied as a function of $\kappa_{\lambda}$. In this case,the best fit value corresponds to $\kappa_{\lambda}$ = $2.7^{+2.0}_{-2.2}(^{+3.8}_{-4.3})$ and the expected value corresponds to $\kappa_{\lambda}$ = $1.0^{+5.4}_{-2.5}(^{+7.3}_{-4.3})$ for the 1$\sigma$(2$\sigma$) confidence interval.
Values of the negative log-profile-likelihood ($-2ln\Lambda$) as a function of $\kappa_{\lambda}$ evaluated for the combination of all the categories of the nonresonant search. The coupling of the Higgs boson to fermions and gauge bosons is set to SM values in the profile likelihood calculation. The Asimov data set is generated under the SM signal-plus-background hypothesis, $\kappa_{\lambda}$= 1. All systematic uncertainties, including the theoretical uncertainties on the di-Higgs boson production cross section, are included. The intersections of the solid curves and the horizontal dashed lines indicate the 1$\sigma$ and 2$\sigma$ confidence level intervals. The best fit value corresponds to $\kappa_{\lambda}$ = $2.8^{+2.0}_{-2.2}(^{+3.8}_{-4.3})$ for the 1$\sigma$(2$\sigma$) confidence interval. The expected value corresponds to $\kappa_{\lambda}$ = $1.0^{+5.5}_{-2.4}(^{+7.3}_{-4.2})$ for the 1$\sigma$(2$\sigma$) confidence interval. The dashed curves represent values of the negative log-profile-likelihood where the Higgs boson branching fractions and the cross section of the production modes are varied as a function of $\kappa_{\lambda}$. In this case,the best fit value corresponds to $\kappa_{\lambda}$ = $2.7^{+2.0}_{-2.2}(^{+3.8}_{-4.3})$ and the expected value corresponds to $\kappa_{\lambda}$ = $1.0^{+5.4}_{-2.5}(^{+7.3}_{-4.3})$ for the 1$\sigma$(2$\sigma$) confidence interval.
Values of the negative log-profile-likelihood ($-2ln\Lambda$) as a function of $\kappa_{\lambda}$ evaluated for the combination of all the categories of the nonresonant search. The coupling of the Higgs boson to fermions and gauge bosons is set to SM values in the profile likelihood calculation. The Asimov data set is generated under the SM signal-plus-background hypothesis, $\kappa_{\lambda}$= 1. All systematic uncertainties, including the theoretical uncertainties on the di-Higgs boson production cross section, are included. The intersections of the solid curves and the horizontal dashed lines indicate the 1$\sigma$ and 2$\sigma$ confidence level intervals. The best fit value corresponds to $\kappa_{\lambda}$ = $2.8^{+2.0}_{-2.2}(^{+3.8}_{-4.3})$ for the 1$\sigma$(2$\sigma$) confidence interval. The expected value corresponds to $\kappa_{\lambda}$ = $1.0^{+5.5}_{-2.4}(^{+7.3}_{-4.2})$ for the 1$\sigma$(2$\sigma$) confidence interval. The dashed curves represent values of the negative log-profile-likelihood where the Higgs boson branching fractions and the cross section of the production modes are varied as a function of $\kappa_{\lambda}$. In this case,the best fit value corresponds to $\kappa_{\lambda}$ = $2.7^{+2.0}_{-2.2}(^{+3.8}_{-4.3})$ and the expected value corresponds to $\kappa_{\lambda}$ = $1.0^{+5.4}_{-2.5}(^{+7.3}_{-4.3})$ for the 1$\sigma$(2$\sigma$) confidence interval.
Values of the negative log-profile-likelihood ($-2ln\Lambda$) as a function of $\kappa_{\lambda}$ evaluated for the combination of all the categories of the nonresonant search. The coupling of the Higgs boson to fermions and gauge bosons is set to SM values in the profile likelihood calculation. The Asimov data set is generated under the SM signal-plus-background hypothesis, $\kappa_{\lambda}$= 1. All systematic uncertainties, including the theoretical uncertainties on the di-Higgs boson production cross section, are included. The intersections of the solid curves and the horizontal dashed lines indicate the 1$\sigma$ and 2$\sigma$ confidence level intervals. The best fit value corresponds to $\kappa_{\lambda}$ = $2.8^{+2.0}_{-2.2}(^{+3.8}_{-4.3})$ for the 1$\sigma$(2$\sigma$) confidence interval. The expected value corresponds to $\kappa_{\lambda}$ = $1.0^{+5.5}_{-2.4}(^{+7.3}_{-4.2})$ for the 1$\sigma$(2$\sigma$) confidence interval. The dashed curves represent values of the negative log-profile-likelihood where the Higgs boson branching fractions and the cross section of the production modes are varied as a function of $\kappa_{\lambda}$. In this case,the best fit value corresponds to $\kappa_{\lambda}$ = $2.7^{+2.0}_{-2.2}(^{+3.8}_{-4.3})$ and the expected value corresponds to $\kappa_{\lambda}$ = $1.0^{+5.4}_{-2.5}(^{+7.3}_{-4.3})$ for the 1$\sigma$(2$\sigma$) confidence interval.
Minimum BDT value of the events passing the selection criteria of the resonant search. The combined BDT score is formed using as coefficients $C_{1}$ = 0.65 and $C_{2}$ = 1 − $C_{1}$. The selection efficiency for the resonant $X \rightarrow HH$ signal is also shown.
Minimum BDT value of the events passing the selection criteria of the resonant search. The combined BDT score is formed using as coefficients $C_{1}$ = 0.65 and $C_{2}$ = 1 − $C_{1}$. The selection efficiency for the resonant $X \rightarrow HH$ signal is also shown.
Minimum BDT value of the events passing the selection criteria of the resonant search. The combined BDT score is formed using as coefficients $C_{1}$ = 0.65 and $C_{2}$ = 1 − $C_{1}$. The selection efficiency for the resonant $X \rightarrow HH$ signal is also shown.
Minimum BDT value of the events passing the selection criteria of the resonant search. The combined BDT score is formed using as coefficients $C_{1}$ = 0.65 and $C_{2}$ = 1 − $C_{1}$. The selection efficiency for the resonant $X \rightarrow HH$ signal is also shown.
A search for flavour-changing neutral-current decays of a top quark into an up-type quark (either up or charm) and a light scalar particle $X$ decaying into a bottom anti-bottom quark pair is presented. The search focuses on top-quark pair production where one top quark decays to $qX$, with $X \rightarrow b\bar{b}$, and the other top quark decays according to the Standard Model, with the $W$ boson decaying leptonically. The final state is thus characterised by an isolated electron or muon and at least four jets. Events are categorised according to the multiplicity of jets and jets tagged as originating from $b$-quarks, and a neural network is used to discriminate between signal and background processes. The data analysed correspond to 139 fb$^{-1}$ of proton-proton collisions at a centre-of-mass energy of 13 TeV, recorded with the ATLAS detector at the LHC. The 95% confidence-level upper limits between 0.019% and 0.062% are derived for the branching fraction $\mathcal{B}$($t \rightarrow uX$) and between 0.018% and 0.078% for the branching fraction $\mathcal{B}$($t \rightarrow cX$), for masses of the scalar particle $X$ between 20 and 160 GeV.
Expected and observed 95% CL upper limits for $\mathcal{B}$($t \rightarrow uX$) $\times$ $\mathcal{B}$($X \rightarrow b\bar{b}$). The bands surrounding the expected limits show the 68% and 95% confidence intervals, respectively.
Expected and observed 95% CL upper limits for $\mathcal{B}$($t \rightarrow cX$) $\times$ $\mathcal{B}$($X \rightarrow b\bar{b}$). The bands surrounding the expected limits show the 68% and 95% confidence intervals, respectively.
Expected and observed 95% CL upper limits for $\mathcal{B}$($t \rightarrow uH$) $\times$ $\mathcal{B}$($X \rightarrow b\bar{b}$) and $\mathcal{B}$($t \rightarrow cH$) $\times$ $\mathcal{B}$($X \rightarrow b\bar{b}$).
Event yields of the signal and SM background processes in the six analysis regions after the fit to the data under the $t \rightarrow uX$ hypothesis assuming $m_X = 30$ GeV. Total includes signal and background.The quoted uncertainties take into account correlations and constraints of the nuisance parameters and include both the statistical and systematic uncertainties. Negative correlations between the $t\bar{t} +$ light, $t\bar{t} + \geq1b$ and $t\bar{t} + \geq1c$ modelling uncertainties can make the uncertainty in the total yields smaller than in the individual components.
Event yields of the signal and SM background processes in the six analysis regions after the fit to the data under the $t \rightarrow cX$ hypothesis assuming $m_X = 30$ GeV. Total includes signal and background.The quoted uncertainties take into account correlations and constraints of the nuisance parameters and include both the statistical and systematic uncertainties. Negative correlations between the $t\bar{t} +$ light, $t\bar{t} + \geq1b$ and $t\bar{t} + \geq1c$ modelling uncertainties can make the uncertainty in the total yields smaller than in the individual components.
Event acceptance times efficiency in percent for every $t\rightarrow uX$ and $t\rightarrow cX$ mass signal sample.
Cut flow for the scalar signal in the $t\rightarrow uX$ decay combining both quark and anti-quark samples. Shown for each signal are the corresponding mass, the number of generated events, the number of reconstructed ("Reco") events, the events that pass the lepton triggers, the events that have only one electron ("el") or only one muon ("mu") with p$_{\text{T}}$ larger than 27 GeV, the number of events with at least four jets with p$_{\text{T}}$ larger than 25 GeV, the number of events with at least three $b$-tagged jets at the 70% efficiency working point, and the number of events with at least two $b$-tagged jets at the 60% efficiency working point and at least another one at the 70%. The quoted yields do not include reweighting.
Cut flow for the scalar signal in the $t\rightarrow cX$ decay combining both quark and anti-quark samples. Shown for each signal are the corresponding mass, the number of generated events, the number of reconstructed ("Reco") events, the events that pass the lepton triggers, the events that have only one electron ("el") or only one muon ("mu") with p$_{\text{T}}$ larger than 27 GeV, the number of events with at least four jets with p$_{\text{T}}$ larger than 25 GeV, the number of events with at least three $b$-tagged jets at the 70% efficiency working point, and the number of events with at least two $b$-tagged jets at the 60% efficiency working point and at least another one at the 70%. The quoted yields do not include reweighting.
Electroweak symmetry breaking explains the origin of the masses of elementary particles through their interactions with the Higgs field. Besides the measurements of the Higgs boson properties, the study of the scattering of massive vector bosons with spin one allows the nature of electroweak symmetry breaking to be probed. Among all processes related to vector-boson scattering, the electroweak production of two jets and a $Z$-boson pair is a rare and important one. Here we report the observation of this process from proton-proton collision data corresponding to an integrated luminosity of 139/fb recorded at a centre-of-mass energy of 13 TeV with the ATLAS detector at the Large Hadron Collider. We consider two different final states originating from the decays of the $Z$-boson pair - one containing four charged leptons and the other containing two charged leptons and two neutrinos. The hypothesis of no electroweak production is rejected with a statistical significance of 5.7 $\sigma$, and the measured cross-section for electroweak production is consistent with the standard model prediction. In addition, we report cross-sections for inclusive production of a $Z$-boson pair and two jets for the two final states.
Measured and predicted fiducial cross-sections in both the lllljj and ll$\nu\nu$jj channels for the inclusive ZZjj processes. Uncertainties due to different sources are presented
Signal strength and significance of EW ZZjj processes
Measured and predicted fiducial cross-sections in both the lllljj and ll$\nu\nu$jj channels for the inclusive ZZjj processes. Uncertainties due to different sources are presented.
Observed and expected multivariate discriminant distribution in the $\ell\ell\ell\ell jj$ QCD CR.
Observed and expected multivariate discriminant distribution in the $\ell\ell\ell\ell jj$ SR.
Observed and expected multivariate discriminant distribution in the $\ell\ell\nu\nu jj$ SR.
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