Showing 10 of 71 results
Inclusive and differential measurements of the top-antitop ($t\bar{t}$) charge asymmetry $A_\text{C}^{t\bar{t}}$ and the leptonic asymmetry $A_\text{C}^{\ell\bar{\ell}}$ are presented in proton-proton collisions at $\sqrt{s} = 13$ TeV recorded by the ATLAS experiment at the CERN Large Hadron Collider. The measurement uses the complete Run 2 dataset, corresponding to an integrated luminosity of 139 fb$^{-1}$, combines data in the single-lepton and dilepton channels, and employs reconstruction techniques adapted to both the resolved and boosted topologies. A Bayesian unfolding procedure is performed to correct for detector resolution and acceptance effects. The combined inclusive $t\bar{t}$ charge asymmetry is measured to be $A_\text{C}^{t\bar{t}} = 0.0068 \pm 0.0015$, which differs from zero by 4.7 standard deviations. Differential measurements are performed as a function of the invariant mass, transverse momentum and longitudinal boost of the $t\bar{t}$ system. Both the inclusive and differential measurements are found to be compatible with the Standard Model predictions, at next-to-next-to-leading order in quantum chromodynamics perturbation theory with next-to-leading-order electroweak corrections. The measurements are interpreted in the framework of the Standard Model effective field theory, placing competitive bounds on several Wilson coefficients.
The unfolded inclusive charge asymmetry. The measured values are given with statistical and systematic uncertainties. The SM theory predictions calculated at NNLO in QCD and NLO in EW theory are listed, and the impact of the linear term of the Wilson coefficient on the $A_C^{t\bar{t}}$ prediction is shown for two different values. The scale uncertainty is obtained by varying renormalisation and factorisation scales independently by a factor of 2 or 0.5 around $\mu_0$ to calculate the maximum and minimum value of the asymmetry, respectively. The nominal value $\mu_0$ is chosen as $H_T/4$. The variations in which one scale is multiplied by 2 while the other scale is divided by 2 are excluded. Finally, the scale and MC integration uncertainties are added in quadrature.
The unfolded differential charge asymmetry as a function of the invariant mass of the top pair system. The measured values are given with statistical and systematic uncertainties. The SM theory predictions calculated at NNLO in QCD and NLO in EW theory are listed, and the impact of the linear term of the Wilson coefficient on the $A_C^{t\bar{t}}$ prediction is shown for two different values. The scale uncertainty is obtained by varying renormalisation and factorisation scales independently by a factor of 2 or 0.5 around $\mu_0$ to calculate the maximum and minimum value of the asymmetry, respectively. The nominal value $\mu_0$ is chosen as $H_T/4$. The variations in which one scale is multiplied by 2 while the other scale is divided by 2 are excluded. Finally, the scale and MC integration uncertainties are added in quadrature.
The unfolded differential charge asymmetry as a function of the transverse momentum of the top pair system. The measured values are given with statistical and systematic uncertainties. The SM theory predictions calculated at NNLO in QCD and NLO in EW theory are listed. The scale uncertainty is obtained by varying renormalisation and factorisation scales independently by a factor of 2 or 0.5 around $\mu_0$ to calculate the maximum and minimum value of the asymmetry, respectively. The nominal value $\mu_0$ is chosen as $H_T/4$. The variations in which one scale is multiplied by 2 while the other scale is divided by 2 are excluded. Finally, the scale and MC integration uncertainties are added in quadrature.
The unfolded differential charge asymmetry as a function of the longitudinal boost of the top pair system. The measured values are given with statistical and systematic uncertainties. The SM theory predictions calculated at NNLO in QCD and NLO in EW theory are listed. The scale uncertainty is obtained by varying renormalisation and factorisation scales independently by a factor of 2 or 0.5 around $\mu_0$ to calculate the maximum and minimum value of the asymmetry, respectively. The nominal value $\mu_0$ is chosen as $H_T/4$. The variations in which one scale is multiplied by 2 while the other scale is divided by 2 are excluded. Finally, the scale and MC integration uncertainties are added in quadrature.
The unfolded inclusive leptonic asymmetry. The unfolded $A_C^{\ell\bar{\ell}}$ is obtained in the reduced phase-space defined by the requirement $|\Delta |\eta_{\ell\bar{\ell}}||<2.5$. The measured values are given with statistical and systematic uncertainties. The SM theory predictions calculated at NLO in QCD and NLO in EW theory are listed. The theory uncertainty is obtained by varying both scales by a factor of 0.5 or 2.0 to calculate the minimum and maximum value of the asymmetry, respectively.
The unfolded differential leptonic asymmetry as a function of the invariant mass of the di-lepton pair. The unfolded $A_C^{\ell\bar{\ell}}$ is obtained in the reduced phase-space defined by the requirement $|\Delta |\eta_{\ell\bar{\ell}}||<2.5$. The measured values are given with statistical and systematic uncertainties. The SM theory predictions calculated at NLO in QCD and NLO in EW theory are listed. The theory uncertainty is obtained by varying both scales by a factor of 0.5 or 2.0 to calculate the minimum and maximum value of the asymmetry, respectively.
The unfolded differential leptonic asymmetry as a function of the transverse momentum of the di-lepton pair. The unfolded $A_C^{\ell\bar{\ell}}$ is obtained in the reduced phase-space defined by the requirement $|\Delta |\eta_{\ell\bar{\ell}}||<2.5$. The measured values are given with statistical and systematic uncertainties. The SM theory predictions calculated at NLO in QCD and NLO in EW theory are listed. The theory uncertainty is obtained by varying both scales by a factor of 0.5 or 2.0 to calculate the minimum and maximum value of the asymmetry, respectively.
The unfolded differential leptonic asymmetry as a function of the longitudinal boost of the di-lepton pair. The unfolded $A_C^{\ell\bar{\ell}}$ is obtained in the reduced phase-space defined by the requirement $|\Delta |\eta_{\ell\bar{\ell}}||<2.5$. The measured values are given with statistical and systematic uncertainties. The SM theory predictions calculated at NLO in QCD and NLO in EW theory are listed. The theory uncertainty is obtained by varying both scales by a factor of 0.5 or 2.0 to calculate the minimum and maximum value of the asymmetry, respectively.
Individual 68% and 95% CL bounds on the relevant Wilson coefficients of the SM Effective Field Theory in units of $\text{TeV}^{-2}$. The bounds are derived from the $A_C^{t\bar{t}}$ inclusive measurement. The experimental uncertainties are accounted for, in the form of the complete covariance matrix that keeps track of correlations between bins for the differential measurement. The theory uncertainty from the NNLO QCD + NLO EW calculation is included by explicitly varying the renormalization and factorization scales, or the parton density functions, in the calculation and registering the variations in the intervals.
Individual 68% and 95% CL bounds on the relevant Wilson coefficients of the SM Effective Field Theory in units of $\text{TeV}^{-2}$. The bounds are derived from the $A_C^{t\bar{t}}$ vs $m_{t\bar{t}}$ measurement. The experimental uncertainties are accounted for, in the form of the complete covariance matrix that keeps track of correlations between bins for the differential measurement. The theory uncertainty from the NNLO QCD + NLO EW calculation is included by explicitly varying the renormalization and factorization scales, or the parton density functions, in the calculation and registering the variations in the intervals.
Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ inclusive measurement. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.
Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $\beta_{z,t\bar{t}}$ measurement for $\beta_{z,t\bar{t}}$ $\in$ [0,0.3]. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.
Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $\beta_{z,t\bar{t}}$ measurement for $\beta_{z,t\bar{t}}$ $\in$ [0.3,0.6]. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.
Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $\beta_{z,t\bar{t}}$ measurement for $\beta_{z,t\bar{t}}$ $\in$ [0.6,0.8]. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.
Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $\beta_{z,t\bar{t}}$ measurement for $\beta_{z,t\bar{t}}$ $\in$ [0.8,1]. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.
Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $m_{t\bar{t}}$ measurement for $m_{t\bar{t}}$ < 500 GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.
Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $m_{t\bar{t}}$ measurement for $m_{t\bar{t}}$ $\in$ [500,750] GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.
Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $m_{t\bar{t}}$ measurement for $m_{t\bar{t}}$ $\in$ [750,1000] GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.
Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $m_{t\bar{t}}$ measurement for $m_{t\bar{t}}$ $\in$ [1000,1500] GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.
Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $m_{t\bar{t}}$ measurement for $m_{t\bar{t}}$ > 1500 GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.
Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $p_{T,t\bar{t}}$ measurement for $p_{T,t\bar{t}}$ < 30 GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.
Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $p_{T,t\bar{t}}$ measurement for $p_{T,t\bar{t}}$ $\in$ [30,120] GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.
Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $p_{T,t\bar{t}}$ measurement for $p_{T,t\bar{t}}$ > 120 GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.
Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ inclusive measurement. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.
Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ vs $\beta_{z,\ell\bar{\ell}}$ measurement for $\beta_{z,\ell\bar{\ell}}$ $\in$[0,0.3]. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.
Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ vs $\beta_{z,\ell\bar{\ell}}$ measurement for $\beta_{z,\ell\bar{\ell}}$ $\in$[0.3,0.6]. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.
Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ vs $\beta_{z,\ell\bar{\ell}}$ measurement for $\beta_{z,\ell\bar{\ell}}$ $\in$[0.6,0.8]. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.
Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ vs $\beta_{z,\ell\bar{\ell}}$ measurement for $\beta_{z,\ell\bar{\ell}}$ $\in$[0.8,1]. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.
Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ vs $m_{\ell\bar{\ell}}$ measurement for $m_{\ell\bar{\ell}}$ < 200 GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.
Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ vs $m_{\ell\bar{\ell}}$ measurement for $m_{\ell\bar{\ell}}$ $\in$ [200,300] GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.
Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ vs $m_{\ell\bar{\ell}}$ measurement for $m_{\ell\bar{\ell}}$ $\in$ [300,400] GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.
Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ vs $m_{\ell\bar{\ell}}$ measurement for $m_{\ell\bar{\ell}}$ > 400 GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.
Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ vs $p_{T,\ell\bar{\ell}}$ measurement for $p_{T,\ell\bar{\ell}}$ < 20 GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.
Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ vs $p_{T,\ell\bar{\ell}}$ measurement for $p_{T,\ell\bar{\ell}}$ $\in$ [20, 70] GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.
Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ vs $p_{T,\ell\bar{\ell}}$ measurement for $p_{T,\ell\bar{\ell}}$ > 70 GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.
Post-marginalisation correlation coefficients $\rho_{ij}$ of nuisance parameters for the $A_C^{t\bar{t}}$ inclusive measurement. Only $|\rho_{ij}| > 0.05$ values are included.
Post-marginalisation correlation coefficients $\rho_{ij}$ of nuisance parameters for the $A_C^{t\bar{t}}$ vs $m_{t\bar{t}}$ measurement. Only $|\rho_{ij}| > 0.05$ values are included.
Post-marginalisation correlation coefficients $\rho_{ij}$ of nuisance parameters for the $A_C^{t\bar{t}}$ vs $p_{T,t\bar{t}}$ measurement. Only $|\rho_{ij}| > 0.05$ values are included.
Post-marginalisation correlation coefficients $\rho_{ij}$ of nuisance parameters for the $A_C^{t\bar{t}}$ vs $\beta_{z,t\bar{t}}$ measurement. Only $|\rho_{ij}| > 0.05$ values are included.
Post-marginalisation correlation coefficients $\rho_{ij}$ of nuisance parameters for the $A_C^{\ell\ell}$ inclusive measurement. Only $|\rho_{ij}| > 0.05$ values are included.
Post-marginalisation correlation coefficients $\rho_{ij}$ of nuisance parameters for the $A_C^{\ell\ell}$ vs $m_{\ell\bar{\ell}}$ measurement. Only $|\rho_{ij}| > 0.05$ values are included.
Post-marginalisation correlation coefficients $\rho_{ij}$ of nuisance parameters for the $A_C^{\ell\ell}$ vs $p_{T,\ell\bar{\ell}}$ measurement. Only $|\rho_{ij}| > 0.05$ values are included.
Post-marginalisation correlation coefficients $\rho_{ij}$ of nuisance parameters for the $A_C^{\ell\ell}$ vs $\beta_{z,\ell\bar{\ell}}$ measurement. Only $|\rho_{ij}| > 0.05$ values are included.
Covariance matrix for the $A_C^{t\bar{t}}$ vs $m_{t\bar{t}}$ measurement.
Covariance matrix for the $A_C^{t\bar{t}}$ vs $p_{T,t\bar{t}}$ measurement.
Covariance matrix for the $A_C^{t\bar{t}}$ vs $\beta_{z,t\bar{t}}$ measurement.
Covariance matrix for the $A_C^{\ell\ell}$ vs $m_{\ell\bar{\ell}}$ measurement.
Covariance matrix for the $A_C^{\ell\ell}$ vs $p_{T,\ell\bar{\ell}}$ measurement.
Covariance matrix for the $A_C^{\ell\ell}$ vs $\beta_{z,\ell\bar{\ell}}$ measurement.
A search for resonant and non-resonant pair production of Higgs bosons in the $b\bar{b}\tau^+\tau^-$ final state is presented. The search uses 36.1 fb$^{-1}$ of $pp$ collision data with $\sqrt{s}= 13$ TeV recorded by the ATLAS experiment at the LHC in 2015 and 2016. The semileptonic and fully hadronic decays of the $\tau$-lepton pair are considered. No significant excess above the expected background is observed in the data. The cross-section times branching ratio for non-resonant Higgs boson pair production is constrained to be less than 30.9 fb, 12.7 times the Standard Model expectation, at 95% confidence level. The data are also analyzed to probe resonant Higgs boson pair production, constraining a model with an extended Higgs sector based on two doublets and a Randall-Sundrum bulk graviton model. Upper limits are placed on the resonant Higgs boson pair production cross-section times branching ratio, excluding resonances $X$ in the mass range $305~{\rm GeV} < m_X < 402~{\rm GeV}$ in the simplified hMSSM minimal supersymmetric model for $\tan\beta=2$ and excluding bulk Randall-Sundrum gravitons $G_{\mathrm{KK}}$ in the mass range $325~{\rm GeV} < m_{G_{\mathrm{KK}}} < 885~{\rm GeV}$ for $k/\overline{M}_{\mathrm{Pl}} = 1$.
Observed and expected limits at 95% CL on the cross-sections of RS Graviton to HH for k/MPl = 1 process
Observed and expected limits at 95% CL on the cross-sections of RS Graviton to HH for k/MPl = 2 process
Observed and expected limits at 95% CL on the cross-sections of hMSSM scalar X to HH process
Acceptance x efficiency versus resonance mass for both lephad and hadhad channels in the RS bulk model with k/MPl = 1
Acceptance x efficiency versus resonance mass for both lephad and hadhad channels in the RS bulk model with k/MPl = 2
Acceptance x efficiency versus resonance mass for both lephad and hadhad channels in the scalar model
Upper limits on the production cross-section times the HH to bbtautau branching ratio for non-resonant HH at 95% CLS and their interpretation as multiples of the SM prediction
Upper limits on the production cross-section times the HH to bbtautau branching ratio divided by the SM prediction for non-resonant HH at 95% CL
Post-fit expected number of signal and background events and observed number of data events after applying the selection criteria and requiring exactly 2 b-tagged jets and assuming a background-only hypothesis
Post-fit expected number of signal and background events and observed number of data events in the last two bins of the non-resonant BDT score distribution of the SM signal after applying the selection criteria and requiring exactly 2 b-tagged jets and assuming a background-only hypothesis
A search for a heavy neutral Higgs boson, $A$, decaying into a $Z$ boson and another heavy Higgs boson, $H$, is performed using a data sample corresponding to an integrated luminosity of 36.1 fb$^{-1}$ from proton-proton collisions at $\sqrt{s} = 13$ TeV recorded in 2015 and 2016 by the ATLAS detector at the Large Hadron Collider. The search considers the $Z$ boson decaying to electrons or muons and the $H$ boson into a pair of $b$-quarks. No evidence for the production of an $A$ boson is found. Considering each production process separately, the 95% confidence-level upper limits on the $pp\rightarrow A\rightarrow ZH$ production cross-section times the branching ratio $H\rightarrow bb$ are in the range of 14-830 fb for the gluon-gluon fusion process and 26-570 fb for the $b$-associated process for the mass ranges 130-700 GeV of the $H$ boson and process for the mass ranges 130-700 GeV of the $H$ boson and 230-800 GeV of the $A$ boson. The results are interpreted in the context of the two-Higgs-doublet model.
The signal efficiency for the production modes (gluon-gluon fusion and b-associated production) and the signal regions used in the analysis. The efficiency denominator has the total number of generated MC events. The numerator includes the events passing the full signal region selection, including the mbb window cuts. The table shows for each signal mass pair (mA, mH) 3 efficiencies corresponding to the two production modes in the two categories, 2tag and 3tag. These corresponds to "nb = 2 category" and "nb >= 3 category", respectively, of the preprint. No numbers for gluon-gluon fusion in the 3tag category are provided since those are not used in the analysis. The efficiencies are given in fractions.
The cross section times BR(A->ZH) times BR(H->bb) limits for a narrow width A boson produced via gluon-gluon fusion. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The result refers to the nb=2 category only.
The cross section times BR(A->ZH) times BR(H->bb) limits for a narrow width A boson produced in association with b-quarks. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The result refers to the combination of the nb=2 and nb>=3 categories.
The cross section times BR(A->ZH) times BR(H->bb) limits for an A boson in the type-I, tanbeta 1, 2HDM. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used. For type-I only gluon-gluon fusion is used and the nb=2 category only.
The cross section times BR(A->ZH) times BR(H->bb) limits for an A boson in the type-I, tanbeta 5, 2HDM. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used. For type-I only gluon-gluon fusion is used and the nb=2 category only.
The cross section times BR(A->ZH) times BR(H->bb) limits for an A boson in the type-I, tanbeta 10, 2HDM. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used. For type-I only gluon-gluon fusion is used and the nb=2 category only.
The cross section times BR(A->ZH) times BR(H->bb) limits for an A boson in the type-I, tanbeta 20, 2HDM. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used. For type-I only gluon-gluon fusion is used and the nb=2 category only.
The cross section times BR(A->ZH) times BR(H->bb) limits for an A boson in the type-II, tanbeta 1, 2HDM. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used. For type-II both gluon-gluon fusion and b-associated production are used and the nb=2 and nb>=3 categories are combined.
The cross section times BR(A->ZH) times BR(H->bb) limits for an A boson in the type-II, tanbeta 5, 2HDM. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used. For type-II both gluon-gluon fusion and b-associated production are used and the nb=2 and nb>=3 categories are combined.
The cross section times BR(A->ZH) times BR(H->bb) limits for an A boson in the type-II, tanbeta 10, 2HDM. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used. For type-II both gluon-gluon fusion and b-associated production are used and the nb=2 and nb>=3 categories are combined.
The cross section times BR(A->ZH) times BR(H->bb) limits for an A boson in the type-II, tanbeta 20, 2HDM. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used. For type-II both gluon-gluon fusion and b-associated production are used and the nb=2 and nb>=3 categories are combined.
The cross section times BR(A->ZH) times BR(H->bb) limits for an A boson in the lepton specific, tanbeta 1, 2HDM. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used. For lepton specific only gluon-gluon fusion is used and the nb=2 category only.
The cross section times BR(A->ZH) times BR(H->bb) limits for an A boson in the lepton specific, tanbeta 2, 2HDM. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used. For lepton specific only gluon-gluon fusion is used and the nb=2 category only.
The cross section times BR(A->ZH) times BR(H->bb) limits for an A boson in the lepton specific, tanbeta 3, 2HDM. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used. For lepton specific only gluon-gluon fusion is used and the nb=2 category only.
The cross section times BR(A->ZH) times BR(H->bb) limits for an A boson in the flipped, tanbeta 1, 2HDM. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used. For flipped both gluon-gluon fusion and b-associated production are used and the nb=2 and nb>=3 categories are combined.
The cross section times BR(A->ZH) times BR(H->bb) limits for an A boson in the flipped, tanbeta 5, 2HDM. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used. For flipped both gluon-gluon fusion and b-associated production are used and the nb=2 and nb>=3 categories are combined.
The cross section times BR(A->ZH) times BR(H->bb) limits for an A boson in the flipped, tanbeta 10, 2HDM. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used. For flipped both gluon-gluon fusion and b-associated production are used and the nb=2 and nb>=3 categories are combined.
The cross section times BR(A->ZH) times BR(H->bb) limits for an A boson in the flipped, tanbeta 20, 2HDM. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used. For flipped both gluon-gluon fusion and b-associated production are used and the nb=2 and nb>=3 categories are combined.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 130 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 130 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 140 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 140 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 150 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 150 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 160 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 160 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 170 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 170 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 180 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 180 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 190 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 230 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 230 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 240 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 240 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 250 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 250 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 260 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 260 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 270 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 270 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 280 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 280 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 290 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 290 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 310 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 310 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 320 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 320 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 330 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 330 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 340 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 340 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 350 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 350 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 360 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 360 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 370 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 370 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 380 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 380 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 390 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 390 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 400 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 400 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 410 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 410 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 420 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 420 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 430 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 430 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 440 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 440 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 450 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 450 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 460 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 460 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 470 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 470 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 480 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 480 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 490 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 490 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 510 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 510 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 520 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 520 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 530 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 530 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 540 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 540 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 550 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 550 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 560 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 560 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 570 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 570 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 580 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 580 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 590 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 590 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 600 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 600 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 610 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 610 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 620 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 620 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 630 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 630 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 640 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 640 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 650 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 650 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 660 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 660 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 670 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 670 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 680 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 680 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 690 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 690 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 700 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 700 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 200 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 200 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 300 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 300 GeV for the nb >= 3 (3 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 500 GeV for the nb = 2 (2 tag) category.
The mass distribution of the llbb system used in the fit to derive the limits for the mbb window centered at 500 GeV for the nb >= 3 (3 tag) category.
A search for supersymmetry in events with large missing transverse momentum, jets, and at least one hadronically decaying tau lepton has been performed using 3.2 fb$^{-1}$ of proton-proton collision data at $\sqrt{s}=13$ TeV recorded by the ATLAS detector at the Large Hadron Collider in 2015. Two exclusive final states are considered, with either exactly one or at least two tau leptons. No excess over the Standard Model prediction is observed in the data. Results are interpreted in the context of gauge-mediated supersymmetry breaking and a simplified model of gluino pair production with tau-rich cascade decays, substantially improving on previous limits. In the GMSB model considered, supersymmetry-breaking scale ($\Lambda$) values below 92 TeV are excluded at the 95% confidence level, corresponding to gluino masses below 2000 GeV. For large values of $\tan\beta$, values of $\Lambda$ up to 107 TeV and gluino masses up to 2300 GeV are excluded. In the simplified model, gluino masses are excluded up to 1570 GeV for neutralino masses around 100 GeV. Neutralino masses up to 700 GeV are excluded for all gluino masses between 800 GeV and 1500 GeV, while the strongest exclusion of 750 GeV is achieved for gluino masses around 1400 GeV.
mTtau distributions for "extended SR selections" of the 1 tau channel, for the Compressed SR selection without the mTtau > 80 GeV requirement. The last bin includes overflow events. Uncertainties are statistical only. Signal predictions are overlaid for several benchmark models, normalised to their predicted cross sections. For the simplified model, "LM" refers to a low mass splitting, or compressed scenario, with m(gluino)=665 GeV and m(neutralino)=585 GeV; "MM" stands for a medium mass splitting, with m(gluino)=1145 GeV and m(neutralino)=265 GeV; "HM" denotes a high mass splitting scenario, with m(gluino)=1305 GeV and m(neutralino)=105 GeV.
mTtau distributions for "extended SR selections" of the 1 tau channel, for the Medium Mass SR selection without the mTtau > 200 GeV requirement. The last bin includes overflow events. Uncertainties are statistical only. Signal predictions are overlaid for several benchmark models, normalised to their predicted cross sections. For the simplified model, "LM" refers to a low mass splitting, or compressed scenario, with m(gluino)=665 GeV and m(neutralino)=585 GeV; "MM" stands for a medium mass splitting, with m(gluino)=1145 GeV and m(neutralino)=265 GeV; "HM" denotes a high mass splitting scenario, with m(gluino)=1305 GeV and m(neutralino)=105 GeV.
mTtau distributions for "extended SR selections" of the 1 tau channel, for the High Mass SR selection without the mTtau > 200 GeV requirement. The last bin includes overflow events. Uncertainties are statistical only. Signal predictions are overlaid for several benchmark models, normalised to their predicted cross sections. For the simplified model, "LM" refers to a low mass splitting, or compressed scenario, with m(gluino)=665 GeV and m(neutralino)=585 GeV; "MM" stands for a medium mass splitting, with m(gluino)=1145 GeV and m(neutralino)=265 GeV; "HM" denotes a high mass splitting scenario, with m(gluino)=1305 GeV and m(neutralino)=105 GeV.
Kinematic distributions for "extended SR selections" of the 2-tau channel, for mTsum in the Compressed SR selection without the mTsum>1400 GeV requirement. The last bin includes overflow events. Cited uncertainties are statistical uncertainties only. Signal predictions are overlaid for several benchmark models, normalised to their predicted cross sections. For the simplified model, "MM" refers to a medium mass splitting, with m(gluino)=1145 GeV and m(neutralino)=265 GeV; "HM" denotes a high mass splitting scenario, with m(gluino)=1305 GeV and m(neutralino)=105 GeV. The GMSB benchmark model corresponds to Lambda = 90 TeV and tanbeta = 40.
Kinematic distributions for "extended SR selections" of the 2-tau channel, for mTtau1+mTtau2 in the High-Mass SR selection without the mTtau1+mTtau2>350GeV requirement. The last bin includes overflow events. Cited uncertainties are statistical uncertainties only. Signal predictions are overlaid for several benchmark models, normalised to their predicted cross sections. For the simplified model, "MM" refers to a medium mass splitting, with m(gluino)=1145 GeV and m(neutralino)=265 GeV; "HM" denotes a high mass splitting scenario, with m(gluino)=1305 GeV and m(neutralino)=105 GeV. The GMSB benchmark model corresponds to Lambda = 90 TeV and tanbeta = 40.
Kinematic distributions for "extended SR selections" of the 2-tau channel, for HT in the GMSB SR selection without the HT > 1700 GeV requirement. The last bin includes overflow events. Cited uncertainties are statistical uncertainties only. Signal predictions are overlaid for several benchmark models, normalised to their predicted cross sections. For the simplified model, "MM" refers to a medium mass splitting, with m(gluino)=1145 GeV and m(neutralino)=265 GeV; "HM" denotes a high mass splitting scenario, with m(gluino)=1305 GeV and m(neutralino)=105 GeV. The GMSB benchmark model corresponds to Lambda = 90 TeV and tanbeta = 40.
Expected exclusion contour at the 95% confidence level for the simplified model of gluino pair production, based on the combined results from the 1tau and 2tau channel. The result is obtained using 3.2 fb-1 of sqrt(s) = 13 TeV ATLAS data.
Observed exclusion contour at the 95% confidence level for the simplified model of gluino pair production, based on the combined results from the 1tau and 2tau channel. The result is obtained using 3.2 fb-1 of sqrt(s) = 13 TeV ATLAS data.
Expected exclusion contour at the 95% confidence level for the simplified model of gluino pair production, based on results from the 2tau channel. The result is obtained using 3.2 fb-1 of sqrt(s) = 13 TeV ATLAS data.
Expected exclusion contour at the 95% confidence level for the simplified model of gluino pair production, based on results from the 1tau channel. The result is obtained using 3.2 fb-1 of sqrt(s) = 13 TeV ATLAS data.
Observed exclusion contours at the 95% confidence level for the gauge-mediated supersymmetry-breaking model, based on results from the 2 tau channel. The result is obtained using 3.2 fb-1 of sqrt(s) = 13 TeV ATLAS data. Additional model parameters are M(mess) = 250 TeV, N5 = 3, mu>0 and Cgrav =1.
Expected exclusion contours at the 95% confidence level for the gauge-mediated supersymmetry-breaking model, based on results from the 2 tau channel. The result is obtained using 3.2 fb-1 of sqrt(s) = 13 TeV ATLAS data. Additional model parameters are M(mess) = 250 TeV, N5 = 3, mu>0 and Cgrav =1.
Observed upper cross section limits in pb for the simplified model of gluino pair production for the combination of all SRs.
Best expected signal region for the simplified model of gluino pair production. The respective SR has been used in the combination of the results.
Acceptance for the gluino production simplified model grid in the Compressed 1tau signal region.
Efficiency for the gluino production simplified model grid in the Compressed 1tau signal region.
Acceptance times Efficiency for the gluino production simplified model grid in the Compressed 1tau signal region.
Acceptance for the gluino production simplified model grid in the medium mass 1tau signal region.
Efficiency for the gluino production simplified model grid in the medium mass 1tau signal region.
Acceptance times Efficiency for the gluino production simplified model grid in the medium mass 1tau signal region.
Acceptance for the gluino production simplified model grid in the high mass 1tau signal region.
Efficiency for the gluino production simplified model grid in the high mass 1tau signal region.
Acceptance times Efficiency for the gluino production simplified model grid in the high mass 1tau signal region.
Acceptance for the gluino production simplified model grid in the compressed 2tau signal region.
Efficiency for the gluino production simplified model grid in the compressed 2tau signal region.
Acceptance times Efficiency for the gluino production simplified model grid in the compressed 2tau signal region.
Acceptance for the gluino production simplified model grid in the high mass 2tau signal region.
Efficiency for the gluino production simplified model grid in the high mass 2tau signal region.
Acceptance times Efficiency for the gluino production simplified model grid in the high mass 2tau signal region.
Acceptance for the GMSB model grid in the 2tau signal region.
Efficiency for the GMSB model grid in the 2tau signal region.
Acceptance times Efficiency for the GMSB model grid in the 2tau signal region.
Charged Higgs bosons produced either in top-quark decays or in association with a top-quark, subsequently decaying via $H^{\pm} \to \tau^{\pm}\nu_{\tau}$, are searched for in 36.1 fb$^{-1}$ of proton-proton collision data at $\sqrt{s}=13$ TeV recorded with the ATLAS detector. Depending on whether the top-quark produced together with $H^{\pm}$ decays hadronically or leptonically, the search targets $\tau$+jets and $\tau$+lepton final states, in both cases with a hadronically decaying $\tau$-lepton. No evidence of a charged Higgs boson is found. For the mass range of $m_{H^{\pm}}$ = 90-2000 GeV, upper limits at the 95% confidence level are set on the production cross-section of the charged Higgs boson times the branching fraction $\mathrm{B}(H^{\pm} \to \tau^{\pm}\nu_{\tau})$ in the range 4.2-0.0025 pb. In the mass range 90-160 GeV, assuming the Standard Model cross-section for $t\overline{t}$ production, this corresponds to upper limits between 0.25% and 0.031% for the branching fraction $\mathrm{B}(t\to bH^{\pm}) \times \mathrm{B}(H^{\pm} \to \tau^{\pm}\nu_{\tau})$.
Observed and expected 95% CL exclusion limits on $\sigma(pp\to tbH^+)\times \mathrm{\cal{B}}(H^+\to\tau\nu)$ as a function of the charged Higgs boson mass in 36.1 fb$^{-1}$ of $pp$ collision data at $\sqrt{s} = 13$ TeV, after combination of the $\tau_{\rm had-vis}$+jets and $\tau_{\rm had-vis}$+lepton final states.
Observed and expected 95% CL exclusion limits on $\mathrm{\cal{B}}(t\to bH^+)\times\mathrm{\cal{B}}(H^+\to\tau\nu)$ as a function of the charged Higgs boson mass in 36.1 fb$^{-1}$ of $pp$ collision data at $\sqrt{s} = 13$ TeV, after combination of the $\tau_{\rm had-vis}$+jets and $\tau_{\rm had-vis}$+lepton final states.
Observed 95% CL exclusion contour in the tan$\beta$ - $m_H$ plane shown in the context of the hMSSM, for the regions in which theoretical predictions are available (0.5$\leq\text{tan}\beta\leq60$).
Expected 95% CL exclusion contour in the tan$\beta$ - $m_H$ plane shown in the context of the hMSSM, for the regions in which theoretical predictions are available (0.5$\leq\text{tan}\beta\leq60$).
Observed a95% CL exclusion contour in the tan$\beta$ - $m_H$ plane shown in the context of the $m_{H}^{mod-}$ scenario, for the regions in which theoretical predictions are available (0.5$\leq\text{tan}\beta\leq60$).
Expected 95% CL exclusion contour in the tan$\beta$ - $m_H$ plane shown in the context of the $m_{H}^{mod-}$ scenario, for the regions in which theoretical predictions are available (0.5$\leq\text{tan}\beta\leq60$).
Results are reported of a search for new phenomena, such as supersymmetric particle production, that could be observed in high-energy proton--proton collisions. Events with large numbers of jets, together with missing transverse momentum from unobserved particles, are selected. The data analysed were recorded by the ATLAS experiment during 2015 using the 13 TeV centre-of-mass proton--proton collisions at the Large Hadron Collider, and correspond to an integrated luminosity of 3.2 fb$^{-1}$. The search selected events with various jet multiplicities from $\ge 7$ to $\ge 10$ jets, and with various $b$-jet multiplicity requirements to enhance sensitivity. No excess above Standard Model expectations is observed. The results are interpreted within two supersymmetry models, where gluino masses up to 1400 GeV are excluded at 95% confidence level, significantly extending previous limits.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in validation region 7ej50 0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in validation region 6ej80 0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 10j50 0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 10j50 2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 8j80 0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 8j80 2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 8j50 0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 8j50 1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 8j50 2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 9j50 0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 9j50 1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 9j50 2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 10j50 0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 10j50 1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 10j50 2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 7j80 0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 7j80 1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 7j80 2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 8j80 0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 8j80 1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 8j80 2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
Degree of multijet closure for signal and vaidation regions with at no b-jet requirement. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The bins labelled in bold are signal regions, while the others are validation regions. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).
Degree of multijet closure for signal and vaidation regions with at least 1 b-jet. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The bins labelled in bold are signal regions, while the others are validation regions. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).
Degree of multijet closure for signal and vaidation regions with at least 2 b-jets. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The bins labelled in bold are signal regions, while the others are validation regions. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).
Summary of all 15 signal regions (post-fit).
Signal region yielding the best-expected CLs value, the best expected CLs value, and the corresponding observed CLs value for the 2Step grid.
Signal region yielding the best-expected CLs value, the best expected CLs value, and the corresponding observed CLs value for the pMSSM grid.
95% CLs observed upper limit on model cross-section for 2-step signal points for the best-expected signal region.
Performance of the 8j50-0b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 8j50-1b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 8j50-2b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 9j50-0b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 9j50-1b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 9j50-2b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 10j50-0b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 10j50-1b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 10j50-2b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 7j80-0b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 7j80-1b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 7j80-2b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 8j80-0b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 8j80-1b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 8j80-2b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 8j50-0b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 8j50-1b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 8j50-2b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 9j50-0b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 9j50-1b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 9j50-2b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 10j50-0b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 10j50-1b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 10j50-2b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 7j80-0b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 7j80-1b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 7j80-2b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 8j80-0b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 8j80-1b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 8j80-2b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
The results of a search for vector-like top quarks using events with exactly one lepton, at least four jets, and large missing transverse momentum are reported. The search is optimised for pair production of vector-like top quarks in the $Z(\rightarrow \! \! \nu \nu) \, t + X$ decay channel. LHC pp collision data at a centre-of-mass energy of $\sqrt{s}=13$ TeV recorded by the ATLAS detector in 2015 and 2016 are used, corresponding to an integrated luminosity of 36.1 $\mathrm{fb}^{-1}$. No significant excess over the Standard Model expectation is seen and upper limits on the production cross-section of a vector-like $T$ quark pair as a function of the $T$ quark mass are derived. The observed (expected) 95% CL lower limits on the $T$ mass are 870 GeV (890 GeV) for the weak-isospin singlet model, 1.05 TeV (1.06 TeV) for the weak-isospin doublet model and 1.16 TeV (1.17 TeV) for the pure $Zt$ decay mode. Limits are also set on the mass as a function of the decay branching ratios, excluding large parts of the parameter space for masses below 1 TeV.
Expected and observed 95% CL upper limit on the cross-section times branching ratio for VLQ $T$ pair production as a function of the $T$ mass for BR($T \rightarrow Zt$) = 100%.
Expected and observed 95% CL upper limit on the cross-section times branching ratio for VLQ $T$ pair production as a function of the $T$ mass for branching ratios according to the singlet model.
Expected and observed 95% CL upper limit on the cross-section times branching ratio for VLQ $T$ pair production as a function of the $T$ mass for branching ratios according to the doublet model. Contributions from the $X$ or $B$ quark in the $(X^{5/3}, T)$ or $(T, B)$ doublet models are neglected, leading to very conservative limits.
Expected 95% CL lower limit on the VLQ $T$ mass as a function of the decay branching ratios into $W b$ and $Ht$.
Observed 95% CL lower limit on the VLQ $T$ mass as a function of the decay branching ratios into $W b$ and $Ht$.
A search for squarks and gluinos in final states containing hadronic jets, missing transverse momentum but no electrons or muons is presented. The data were recorded in 2015 by the ATLAS experiment in $\sqrt{s}=$ 13 TeV proton--proton collisions at the Large Hadron Collider. No excess above the Standard Model background expectation was observed in 3.2 fb$^{-1}$ of analyzed data. Results are interpreted within simplified models that assume R-parity is conserved and the neutralino is the lightest supersymmetric particle. An exclusion limit at the 95% confidence level on the mass of the gluino is set at 1.51 TeV for a simplified model incorporating only a gluino octet and the lightest neutralino, assuming the lightest neutralino is massless. For a simplified model involving the strong production of mass-degenerate first- and second-generation squarks, squark masses below 1.03 TeV are excluded for a massless lightest neutralino. These limits substantially extend the region of supersymmetric parameter space excluded by previous measurements with the ATLAS detector.
Observed and expected background effective mass distributions in control region CRgamma for SR4jt.
Observed and expected background effective mass distributions in control region CRW for SR4jt.
Observed and expected background effective mass distributions in control region CRT for SR4jt.
Observed and expected background and signal effective mass distributions for SR2jl. For signal, a squark direct decay model with $m(\tilde q)=800$ GeV and $m(\tilde\chi^0_1)=400$ GeV is shown.
Observed and expected background and signal effective mass distributions for SR2jm. For signal, a gluino direct decay model with $m(\tilde g)=750$ GeV and $m(\tilde\chi^0_1)=660$ GeV is shown.
Observed and expected background and signal effective mass distributions for SR2jt. For signal, a squark direct decay model with $m(\tilde q)=1200$ GeV and $m(\tilde\chi^0_1)=0$ GeV is shown.
Observed and expected background and signal effective mass distributions for SR4jt. For signal, a gluino direct decay model with $m(\tilde g)=1400$ GeV and $m(\tilde\chi^0_1)=0$ GeV is shown.
Observed and expected background and signal effective mass distributions for SR5j. For signal, a gluino one-step decay model with $m(\tilde g)=1265$ GeV, $m(\tilde\chi^\pm_1)=945$ GeV and $m(\tilde\chi^0_1)=625$ GeV is shown.
Observed and expected background and signal effective mass distributions for SR6jm. For signal, a gluino one-step decay model with $m(\tilde g)=1265$ GeV, $m(\tilde\chi^\pm_1)=945$ GeV and $m(\tilde\chi^0_1)=625$ GeV is shown.
Observed and expected background and signal effective mass distributions for SR6jt. For signal, a gluino one-step decay model with $m(\tilde g)=1385$ GeV, $m(\tilde\chi^\pm_1)=705$ GeV and $m(\tilde\chi^0_1)=25$ GeV is shown.
Expected limit at 95% CL for squark direct decay model grid.
Expected limits at 95% CL +1 sigma excursion due to experimental and background-only theoretical uncertainties for squark direct decay model grid.
Expected limits at 95% CL -1 sigma excursion due to experimental and background-only theoretical uncertainties for squark direct decay model grid.
Observed limits at 95% CL for squark direct decay model grid.
Observed limits at 95% CL +1 sigma excursion due to the signal cross-section uncertainty for squark direct decay model grid.
Observed limits at 95% CL -1 sigma excursion due to the signal cross-section uncertainty for squark direct decay model grid.
Expected limit at 95% CL for gluino direct decay model grid.
Expected limits at 95% CL +1 sigma excursion due to experimental and background-only theoretical uncertainties for gluino direct decay model grid.
Expected limits at 95% CL -1 sigma excursion due to experimental and background-only theoretical uncertainties for gluino direct decay model grid.
Observed limits at 95% CL for gluino direct decay model grid.
Observed limits at 95% CL +1 sigma excursion due to the signal cross-section uncertainty for gluino direct decay model grid.
Observed limits at 95% CL -1 sigma excursion due to the signal cross-section uncertainty for gluino direct decay model grid.
Expected limit at 95% CL for gluino one-step decay model grid.
Expected limits at 95% CL +1 sigma excursion due to experimental and background-only theoretical uncertainties for gluino one-step decay model grid.
Expected limits at 95% CL -1 sigma excursion due to experimental and background-only theoretical uncertainties for gluino one-step decay model grid.
Observed limits at 95% CL for gluino one-step decay model grid.
Observed limits at 95% CL +1 sigma excursion due to the signal cross-section uncertainty for gluino one-step decay model grid.
Observed limits at 95% CL -1 sigma excursion due to the signal cross-section uncertainty for gluino one-step decay model grid.
Observed and expected background effective mass distributions in control region CRgamma for SR2jl.
Observed and expected background effective mass distributions in validation region VRZ for SR2jl.
Observed and expected background effective mass distributions in control region CRW for SR2jl.
Observed and expected background effective mass distributions in control region CRT for SR2jl.
Observed and expected background effective mass distributions in control region CRgamma for SR2jm.
Observed and expected background effective mass distributions in validation region VRZ for SR2jm.
Observed and expected background effective mass distributions in control region CRW for SR2jm.
Observed and expected background effective mass distributions in control region CRT for SR2jm.
Observed and expected background effective mass distributions in control region CRgamma for SR2jt.
Observed and expected background effective mass distributions in validation region VRZ for SR2jt.
Observed and expected background effective mass distributions in control region CRW for SR2jt.
Observed and expected background effective mass distributions in control region CRT for SR2jt.
Observed and expected background effective mass distributions in control region CRgamma for SR4jt.
Observed and expected background effective mass distributions in validation region VRZ for SR4jt.
Observed and expected background effective mass distributions in control region CRW for SR4jt.
Observed and expected background effective mass distributions in control region CRT for SR4jt.
Observed and expected background effective mass distributions in control region CRgamma for SR5j.
Observed and expected background effective mass distributions in validation region VRZ for SR5j.
Observed and expected background effective mass distributions in control region CRW for SR5j.
Observed and expected background effective mass distributions in control region CRT for SR5j.
Observed and expected background effective mass distributions in control region CRgamma for SR6jm.
Observed and expected background effective mass distributions in validation region VRZ for SR6jm.
Observed and expected background effective mass distributions in control region CRW for SR6jm.
Observed and expected background effective mass distributions in control region CRT for SR6jm.
Observed and expected background effective mass distributions in control region CRgamma for SR6jt.
Observed and expected background effective mass distributions in validation region VRZ for SR6jt.
Observed and expected background effective mass distributions in control region CRW for SR6jt.
Observed and expected background effective mass distributions in control region CRT for SR6jt.
Observed and expected event yields in VRZ as a function of signal region.
Observed and expected event yields in VRW as a function of signal region.
Observed and expected event yields in VRWv as a function of signal region.
Observed and expected event yields in VRT as a function of signal region.
Observed and expected event yields in VRTv as a function of signal region.
Observed and expected event yields in VRQa as a function of signal region.
Observed and expected event yields in VRQb as a function of signal region.
Signal acceptance for SR2jl in squark direct decay model grid.
Signal acceptance times efficiency for SR2jl in squark direct decay model grid.
Signal acceptance for SR2jm in squark direct decay model grid.
Signal acceptance times efficiency for SR2jm in squark direct decay model grid.
Signal acceptance for SR2jt in squark direct decay model grid.
Signal acceptance times efficiency for SR2jt in squark direct decay model grid.
Signal acceptance for SR4jt in squark direct decay model grid.
Signal acceptance times efficiency for SR4jt in squark direct decay model grid.
Signal acceptance for SR5j in squark direct decay model grid.
Signal acceptance times efficiency for SR5j in squark direct decay model grid.
Signal acceptance for SR6jm in squark direct decay model grid.
Signal acceptance times efficiency for SR6jm in squark direct decay model grid.
Signal acceptance for SR6jt in squark direct decay model grid.
Signal acceptance times efficiency for SR6jt in squark direct decay model grid.
Signal acceptance for SR2jl in gluino direct decay model grid.
Signal acceptance times efficiency for SR2jl in gluino direct decay model grid.
Signal acceptance for SR2jm in gluino direct decay model grid.
Signal acceptance times efficiency for SR2jm in gluino direct decay model grid.
Signal acceptance for SR2jt in gluino direct decay model grid.
Signal acceptance times efficiency for SR2jt in gluino direct decay model grid.
Signal acceptance for SR4jt in gluino direct decay model grid.
Signal acceptance times efficiency for SR4jt in gluino direct decay model grid.
Signal acceptance for SR5j in gluino direct decay model grid.
Signal acceptance times efficiency for SR5j in gluino direct decay model grid.
Signal acceptance for SR6jm in gluino direct decay model grid.
Signal acceptance times efficiency for SR6jm in gluino direct decay model grid.
Signal acceptance for SR6jt in gluino direct decay model grid.
Signal acceptance times efficiency for SR6jt in gluino direct decay model grid.
Signal acceptance for SR2jl in gluino one-step decay model grid.
Signal acceptance times efficiency for SR2jl in gluino one-step decay model grid.
Signal acceptance for SR2jm in gluino one-step decay model grid.
Signal acceptance times efficiency for SR2jm in gluino one-step decay model grid.
Signal acceptance for SR2j5 in gluino one-step decay model grid.
Signal acceptance times efficiency for SR2jt in gluino one-step decay model grid.
Signal acceptance for SR4jt in gluino one-step decay model grid.
Signal acceptance times efficiency for SR4jt in gluino one-step decay model grid.
Signal acceptance for SR5j in gluino one-step decay model grid.
Signal acceptance times efficiency for SR5j in gluino one-step decay model grid.
Signal acceptance for SR6jm in gluino one-step decay model grid.
Signal acceptance times efficiency for SR6jm in gluino one-step decay model grid.
Signal acceptance for SR6jt in gluino one-step decay model grid.
Signal acceptance times efficiency for SR6jt in gluino one-step decay model grid.
The results of a search for gluino and squark pair production with the pairs decaying via the lightest charginos into a final state consisting of two $W$ bosons, the lightest neutralinos ($\tilde\chi^0_1$), and quarks, are presented. The signal is characterised by the presence of a single charged lepton ($e^{\pm}$ or $\mu^{\pm}$) from a $W$ boson decay, jets, and missing transverse momentum. The analysis is performed using 139 fb$^{-1}$ of proton-proton collision data taken at a centre-of-mass energy $\sqrt{s}=13$ TeV delivered by the Large Hadron Collider and recorded by the ATLAS experiment. No statistically significant excess of events above the Standard Model expectation is found. Limits are set on the direct production of squarks and gluinos in simplified models. Masses of gluino (squark) up to 2.2 TeV (1.4 TeV) are excluded at 95% confidence level for a light $\tilde\chi^0_1$.
Post-fit $m_{T}$ distribution in the SR 2J b-veto N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{T}$ distribution in the SR 2J b-veto N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{T}$ distribution in the SR 2J b-tag N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{T}$ distribution in the SR 2J b-tag N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{T}$ distribution in the SR 4J b-veto N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{T}$ distribution in the SR 4J b-veto N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{T}$ distribution in the SR 4J b-tag N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{T}$ distribution in the SR 4J b-tag N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{T}$ distribution in the SR 6J b-veto N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{T}$ distribution in the SR 6J b-veto N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{T}$ distribution in the SR 6J b-tag N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{T}$ distribution in the SR 6J b-tag N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 2J b-tag signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Pre-fit $m_{eff}$ distribution in the TR6J control region. Uncertainties include statistical and systematic uncertainties (added in quadrature). The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 2J b-veto signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Pre-fit $m_{eff}$ distribution in the WR6J control region. Uncertainties include statistical and systematic uncertainties (added in quadrature). The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 4J low-x b-tag signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the TR6J control region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 4J low-x b-veto signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the WR6J control region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 4J high-x b-tag signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 2J b-tag signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 4J high-x b-veto signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 2J b-veto signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 6J b-tag signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 4J low-x b-tag signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 6J b-veto signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 4J low-x b-veto signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Observed 95% CL exclusion contours for the gluino one-step x = 1/2 model.
Post-fit $m_{eff}$ distribution in the 4J high-x b-tag signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Expected 95% CL exclusion contours for the gluino one-step x = 1/2 model. space.
Post-fit $m_{eff}$ distribution in the 4J high-x b-veto signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Observed 95% CL exclusion contours for the gluino one-step variable-x
Post-fit $m_{eff}$ distribution in the 6J b-tag signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Expected 95% CL exclusion contours for the gluino one-step variable-x
Post-fit $m_{eff}$ distribution in the 6J b-veto signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Observed 95% CL exclusion contours for the squark one-step x = 1/2 model.
Observed 95% CL exclusion contours for the gluino one-step x = 1/2 model.
Observed 95% CL exclusion contours for the squark one-step x = 1/2 model.
Expected 95% CL exclusion contours for the gluino one-step x = 1/2 model. space.
Observed 95% CL exclusion contours for one-flavour schemes in one-step x = 1/2 model.
Observed 95% CL exclusion contours for the gluino one-step variable-x
Expected 95% CL exclusion contours for the gluino one-step variable-x
Expected 95% CL exclusion contours for the squark one-step variable-x
Observed 95% CL exclusion contours for the squark one-step x = 1/2 model.
Expected 95% CL exclusion contours for the squark one-step variable-x
Observed 95% CL exclusion contours for the squark one-step x = 1/2 model.
Expected 95% CL exclusion contours for the squark one-flavour schemes in variable-x
Observed 95% CL exclusion contours for one-flavour schemes in one-step x = 1/2 model.
Expected 95% CL exclusion contours for the squark one-flavour schemes in variable-x
Expected 95% CL exclusion contours for the squark one-step variable-x
Expected 95% CL exclusion contours for the squark one-step variable-x
Expected 95% CL exclusion contours for the squark one-flavour schemes in variable-x
Expected 95% CL exclusion contours for the squark one-flavour schemes in variable-x
Post-fit $m_{eff}$ distribution in the 2J b-tag validation region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 2J b-veto validation region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 4J b-tag validation region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 4J b-veto validation region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 6J b-tag validation region. Uncertainties include statistical and systematic uncertainties.
Post-fit $m_{eff}$ distribution in the TR2J control region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 6J b-veto validation region. Uncertainties include statistical and systematic uncertainties.
Post-fit $m_{eff}$ distribution in the WR2J control region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Event selection cutflow for two representative signal samples for the SR2JBT. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.
Post-fit $m_{eff}$ distribution in the TR4J control region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Event selection cutflow for two representative signal samples for the SR2JBV. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.
Post-fit $m_{eff}$ distribution in the WR4J control region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Event selection cutflow for two representative signal samples for the SR4JBT. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.
Post-fit $m_{eff}$ distribution in the 2J b-tag validation region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Event selection cutflow for two representative signal samples for the SR4JBV. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.
Post-fit $m_{eff}$ distribution in the 2J b-veto validation region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Event selection cutflow for two representative signal samples for the SR6JBT. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.
Post-fit $m_{eff}$ distribution in the 4J b-tag validation region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Event selection cutflow for two representative signal samples for the SR6JBV. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.
Post-fit $m_{eff}$ distribution in the 4J b-veto validation region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Signal acceptance in SR2J b-Tag bin1 region for gluino production one-step x = 1/2 simplified models
Post-fit $m_{eff}$ distribution in the 6J b-tag validation region. Uncertainties include statistical and systematic uncertainties.
Signal acceptance in SR2J b-Tag bin2 region for gluino production one-step x = 1/2 simplified models
Post-fit $m_{eff}$ distribution in the 6J b-veto validation region. Uncertainties include statistical and systematic uncertainties.
Signal acceptance in SR2J b-Tag bin3 region for gluino production one-step x = 1/2 simplified models
Event selection cutflow for two representative signal samples for the SR2JBT. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.
Signal acceptance in SR2J b-Veto bin1 region for gluino production one-step x = 1/2 simplified models
Event selection cutflow for two representative signal samples for the SR2JBV. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.
Signal acceptance in SR2J b-Veto bin2 region for gluino production one-step x = 1/2 simplified models
Event selection cutflow for two representative signal samples for the SR4JBT. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.
Signal acceptance in SR2J b-Veto bin3 region for gluino production one-step x = 1/2 simplified models
Event selection cutflow for two representative signal samples for the SR4JBV. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.
Signal acceptance in SR2J discovery high region for gluino production one-step x = 1/2 simplified models
Event selection cutflow for two representative signal samples for the SR6JBT. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.
Signal acceptance in SR2J discovery low region for gluino production one-step x = 1/2 simplified models
Event selection cutflow for two representative signal samples for the SR6JBV. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.
Signal acceptance in SR4Jhx discovery region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Tag bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Tag bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Tag bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Veto bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Veto bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Veto bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J discovery high region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx discovery region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J discovery low region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Tag bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx discovery region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Tag bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Tag bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Tag bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Tag bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Veto bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Tag bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Veto bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Veto bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Veto bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Veto bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Veto bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx discovery region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Tag bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin4 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Tag bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Tag bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Veto bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Veto bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin4 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Veto bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J discovery high region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J discovery low region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin4 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin4 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J discovery high region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J discovery high region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J discovery low region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J discovery low region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx discovery region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Tag bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Tag bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Tag bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Veto bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Veto bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Veto bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J discovery high region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx discovery region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J discovery low region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx discovery region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx discovery region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin4 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin4 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J discovery high region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J discovery low region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Tag bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Tag bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin4 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Tag bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Veto bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Veto bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Veto bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin4 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J discovery high region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J discovery high region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J discovery low region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J discovery low region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx discovery region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Tag bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Tag bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Tag bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Veto bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Veto bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Veto bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J discovery high region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx discovery region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J discovery low region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Tag bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx discovery region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Tag bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Tag bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Tag bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Tag bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Veto bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Tag bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Veto bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Veto bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Veto bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Veto bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Veto bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx discovery region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Tag bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin4 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Tag bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Tag bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Veto bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Veto bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin4 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Veto bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J discovery high region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J discovery low region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin4 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin4 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J discovery high region for squark production one-step variable-x simplified models
Signal acceptance in SR6J discovery high region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J discovery low region for squark production one-step variable-x simplified models
Signal acceptance in SR6J discovery low region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx discovery region for squark production one-step variable-x simplified models
Signal acceptance in SR2J b-Tag bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR2J b-Tag bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR2J b-Tag bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR2J b-Veto bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR2J b-Veto bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR2J b-Veto bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR2J discovery high region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx discovery region for squark production one-step variable-x simplified models
Signal acceptance in SR2J discovery low region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx discovery region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx discovery region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin4 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin4 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J discovery high region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J discovery low region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin2 region for squark production one-step variable-x simplified models
Signal efficiency in SR2J b-Tag bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal acceptance in SR6J b-Tag bin3 region for squark production one-step variable-x simplified models
Signal efficiency in SR2J b-Tag bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal acceptance in SR6J b-Tag bin4 region for squark production one-step variable-x simplified models
Signal efficiency in SR2J b-Tag bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal acceptance in SR6J b-Veto bin1 region for squark production one-step variable-x simplified models
Signal efficiency in SR2J b-Veto bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal acceptance in SR6J b-Veto bin2 region for squark production one-step variable-x simplified models
Signal efficiency in SR2J b-Veto bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal acceptance in SR6J b-Veto bin3 region for squark production one-step variable-x simplified models
Signal efficiency in SR2J b-Veto bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal acceptance in SR6J b-Veto bin4 region for squark production one-step variable-x simplified models
Signal efficiency in SR2J discovery high region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal acceptance in SR6J discovery high region for squark production one-step variable-x simplified models
Signal efficiency in SR2J discovery low region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal acceptance in SR6J discovery low region for squark production one-step variable-x simplified models
Signal efficiency in SR4Jhx discovery region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery high region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx discovery region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery low region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx discovery region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx discovery region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin4 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin4 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery high region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery low region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin4 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin4 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery high region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery high region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery low region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery low region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx discovery region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery high region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx discovery region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery low region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx discovery region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx discovery region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin4 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin4 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery high region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery low region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin4 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin4 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery high region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery high region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery low region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery low region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx discovery region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery high region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx discovery region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery low region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx discovery region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx discovery region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin4 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin4 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery high region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery low region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin4 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin4 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery high region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery high region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery low region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery low region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx discovery region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery high region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx discovery region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery low region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx discovery region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx discovery region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin4 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin4 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery high region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery low region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin4 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin4 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery high region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery low region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
A measurement of the energy asymmetry in jet-associated top-quark pair production is presented using 139 $\mathrm{fb}^{-1}$ of data collected by the ATLAS detector at the Large Hadron Collider during $pp$ collisions at $\sqrt{s}=13$ TeV. The observable measures the different probability of top and antitop quarks to have the higher energy as a function of the jet scattering angle with respect to the beam axis. The energy asymmetry is measured in the semileptonic $t\bar{t}$ decay channel, and the hadronically decaying top quark must have transverse momentum above $350$ GeV. The results are corrected for detector effects to particle level in three bins of the scattering angle of the associated jet. The measurement agrees with the SM prediction at next-to-leading-order accuracy in quantum chromodynamics in all three bins. In the bin with the largest expected asymmetry, where the jet is emitted perpendicular to the beam, the energy asymmetry is measured to be $-0.043\pm0.020$, in agreement with the SM prediction of $-0.037\pm0.003$. Interpreting this result in the framework of the Standard Model effective field theory (SMEFT), it is shown that the energy asymmetry is sensitive to the top-quark chirality in four-quark operators and is therefore a valuable new observable in global SMEFT fits.
Data measurements and predictions of the energy asymmetry in three bins of the jet angle $\theta_j$. The SM prediction was obtained from simulations of $t\bar{t}j$ events with MadGraph5_aMC@NLO + Pythia 8 at NLO in QCD for $t\bar{t}j$ + PS, including MC statistical and scale uncertainties.
Data Measurements and predictions of the energy asymmetry in three bins of the jet angle $\theta_j$. The SM prediction was obtained from simulations of $t\bar{t}j$ events with MadGraph5_aMC@NLO + Pythia 8 at NLO in QCD for $t\bar{t}j$ + PS, including MC statistical and scale uncertainties.
Correlation coefficients $\rho_{i,j}$ for the statistical and systematic uncertainties between the $i$-th and $j$-th bin of the differential $A_E$ measurement as a function of the jet scattering angle $\theta_j$
Correlation coefficients $\rho_{i,j}$ for the statistical and systematic uncertainties between the $i$-th and $j$-th bin of the differential $A_E$ measurement as a function of the jet scattering angle $\theta_j$
The effects on the energy asymmetry of $1\sigma$ variations in its influencing nuisance parameters for the three $\theta_j$ bins. These are extracted from the samples of the posterior distribution with $\sigma_i^{(j)} = c_{ij}/\sqrt{c_{jj}}$ being the estimated shift of bin $i$ in conjunction with a shift $\Delta\theta_j$ of nuisance parameter $j$. The data statistical (Data stat.) uncertainty is obtained from running the unfolding with all nuisance parameters being fixed to their post-marginalised values, the MC statistical uncertainty on the response matrix ($t\bar{t}$ response MC stat.) is evaluated using a bootstrapping method from the covariance matrix of the ensemble of repeated unfolding results with varied response matrices. The $\gamma$ variations denote the statistical uncertainties of the background predictions in the corresponding bin of the $\Delta E$ vs $\theta_{j}$ distribution. The numbers appended to the $W$+jets PDF variations denote the corresponding NNPDF3.0 PDF sets.
The effects on the energy asymmetry of $1\sigma$ variations in its influencing nuisance parameters for the three $\theta_j$ bins. These are extracted from the samples of the posterior distribution with $\sigma_i^{(j)} = c_{ij}/\sqrt{c_{jj}}$ being the estimated shift of bin $i$ in conjunction with a shift $\Delta\theta_j$ of nuisance parameter $j$. The data statistical (Data stat.) uncertainty is obtained from running the unfolding with all nuisance parameters being fixed to their post-marginalised values, the MC statistical uncertainty on the response matrix ($t\bar{t}$ response MC stat.) is evaluated using a bootstrapping method from the covariance matrix of the ensemble of repeated unfolding results with varied response matrices. The $\gamma$ variations denote the statistical uncertainties of the background predictions in the corresponding bin of the $\Delta E$ vs $\theta_{j}$ distribution. The numbers appended to the $W$+jets PDF variations denote the corresponding NNPDF3.0 PDF sets.
Covariances $c_{ij}$ for the highest ranked systematic uncertainties in the energy asymmetry measurement differential in $\theta_j$.
Covariances $c_{ij}$ for the highest ranked systematic uncertainties in the energy asymmetry measurement differential in $\theta_j$.
Definition of the fiducial phase space with lepton candidate ($\ell$), hadronic top candidate ($j_h$), leptonic top candidate ($j_l$) and associated jet candidate ($j_a$).
Definition of the fiducial phase space with lepton candidate ($\ell$), hadronic top candidate ($j_h$), leptonic top candidate ($j_l$) and associated jet candidate ($j_a$).
Bounds on individual Wilson coefficients $C($TeV$/\Lambda)^2$ from the energy asymmetry, obtained from a combined fit to its values in all three $\theta_j$ bins.
Bounds on individual Wilson coefficients $C($TeV$/\Lambda)^2$ from the energy asymmetry, obtained from a combined fit to its values in all three $\theta_j$ bins.
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