Showing 10 of 27 results
Results are presented of a search for supersymmetric particles in events with large missing transverse momentum and at least one heavy flavour jet candidate in sqrt{s} = 7 TeV proton-proton collisions. In a data sample corresponding to an integrated luminosity of 35 pb-1 recorded by the ATLAS experiment at the Large Hadron Collider, no significant excess is observed with respect to the prediction for Standard Model processes. For R-parity conserving models in which sbottoms (stops) are the only squarks to appear in the gluino decay cascade, gluino masses below 590 GeV (520 GeV) are excluded at the 95% C.L. The results are also interpreted in an MSUGRA/CMSSM supersymmetry breaking scenario with tan(beta)=40 and in an SO(10) model framework.
Distribution of the effective mass for data and the SM expectation in the zero-lepton plus 3 jet channel.
Distribution of the missing ET for data and the SM expectation in the zero-lepton plus 3 jet channel.
Distribution of the effective mass for data and the SM expectation in the one-lepton plus 2 jet channel.
Distribution of the missing ET for data and the SM expectation in the one-lepton plus 2 jet channel.
Observed 95 PCT exclusion limit in the M(gluino), M(sbottom) plane obtained with the zero-lepton channel data.
Expected 95 PCT exclusion limit in the M(gluino), M(sbottom) plane obtained with the zero-lepton channel data.
Observed and expected 95 PCT CL upper limits on the gluino-mediated and stop pair production cross section as a function of the gluino mass for a stop mass od 180 GeV, for the one-lepton analysis.
Observed and expected 95 PCT CL upper limits on the gluino-mediated and stop pair production cross section as a function of the gluino mass for a stop mass od 210 GeV, for the one-lepton analysis.
Observed 95 PCT CL exclusion limits from the zero-lepton analysis on the MSUGRA/CMSSM scenario with tan(beta) = 40, A0 = 0 and MU > 0.
Expected 95 PCT CL exclusion limits from the zero-lepton analysis on the MSUGRA/CMSSM scenario with tan(beta) = 40, A0 = 0 and MU > 0.
Observed 95 PCT CL exclusion limits from the one-lepton analysis on the MSUGRA/CMSSM scenario with tan(beta) = 40, A0 = 0 and MU > 0.
Expected 95 PCT CL exclusion limits from the one-lepton analysis on the MSUGRA/CMSSM scenario with tan(beta) = 40, A0 = 0 and MU > 0.
Observed 95 PCT CL exclusion limits from the combined zero and one-lepton analyses on the MSUGRA/CMSSM scenario with tan(beta) = 40, A0 = 0 and MU > 0.
Expected 95 PCT CL exclusion limits from the combined zero and one-lepton analyses on the MSUGRA/CMSSM scenario with tan(beta) = 40, A0 = 0 and MU > 0.
The results of a search for the stop, the supersymmetric partner of the top quark, in final states with one isolated electron or muon, jets, and missing transverse momentum are reported. The search uses the 2015 LHC $pp$ collision data at a center-of-mass energy of $\sqrt{s}=13$ TeV recorded by the ATLAS detector and corresponding to an integrated luminosity of 3.2 fb${}^{-1}$. The analysis targets two types of signal models: gluino-mediated pair production of stops with a nearly mass-degenerate stop and neutralino; and direct pair production of stops, decaying to the top quark and the lightest neutralino. The experimental signature in both signal scenarios is similar to that of a top quark pair produced in association with large missing transverse momentum. No significant excess over the Standard Model background prediction is observed, and exclusion limits on gluino and stop masses are set at 95% confidence level. The results extend the LHC Run-1 exclusion limit on the gluino mass up to 1460 GeV in the gluino-mediated scenario in the high gluino and low stop mass region, and add an excluded stop mass region from 745 to 780 GeV for the direct stop model with a massless lightest neutralino. The results are also reinterpreted to set exclusion limits in a model of vector-like top quarks.
Comparison of data with estimated backgrounds in the $am_\text{T2}$ distribution with the STCR1 event selection except for the requirement on $am_\text{T2}$. The predicted backgrounds are scaled with normalization factors. The uncertainty band includes statistical and all experimental systematic uncertainties. The last bin includes overflow.
Comparison of data with estimated backgrounds in the $b$-tagged jet multiplicity with the STCR1 event selection except for the requirement on the $b$-tagged jet multiplicity. Furthermore, the $\Delta R(b_1,b_2)$ requirement is dropped. The predicted backgrounds are scaled with normalization factors. The uncertainty band includes statistical and all experimental systematic uncertainties. The last bin includes overflow.
Comparison of data with estimated backgrounds in the $\Delta R(b_1,b_2)$ distribution with the STCR1 event selection except for the requirement on $\Delta R(b_1,b_2)$. The predicted backgrounds are scaled with normalization factors. The uncertainty band includes statistical and all experimental systematic uncertainties. The last bin includes overflow.
Comparison of data with estimated backgrounds in the $\tilde{E}_\text{T}^\text{miss}$ distribution with the TZCR1 event selection except for the requirement on $\tilde{E}_\text{T}^\text{miss}$. The variables $\tilde{E}_\text{T}^\text{miss}$ and $\tilde{m}_\text{T}$ are constructed in the same way as $E_\text{T}^\text{miss}$ and $m_\text{T}$ but treating the leading photon transverse momentum as invisible. The predicted backgrounds are scaled with normalization factors. The uncertainty band includes statistical and all experimental systematic uncertainties. The last bin includes overflow.
Comparison of data with estimated backgrounds in the $\tilde{m}_\text{T}$ distribution with the TZCR1 event selection except for the requirement on $\tilde{m}_\text{T}$. The variables $\tilde{E}_\text{T}^\text{miss}$ and $\tilde{m}_\text{T}$ are constructed in the same way as $E_\text{T}^\text{miss}$ and $m_\text{T}$ but treating the leading photon transverse momentum as invisible. The predicted backgrounds are scaled with normalization factors. The uncertainty band includes statistical and all experimental systematic uncertainties. The last bin includes overflow.
Comparison of the observed data ($n_\text{obs}$) with the predicted background ($n_\text{exp}$) in the validation and signal regions. The background predictions are obtained using the background-only fit configuration. The bottom panel shows the significance of the difference between data and predicted background, where the significance is based on the total uncertainty ($\sigma_\text{tot}$).
Jet multiplicity distributions for events where exactly two signal leptons are selected. No correction factors are included in the background normalizations. The uncertainty band includes statistical and all experimental systematic uncertainties. The last bin includes overflow.
Jet multiplicity distributions for events where exactly one lepton plus one $\tau$ candidate are selected. No correction factors are included in the background normalizations. The uncertainty band includes statistical and all experimental systematic uncertainties. The last bin includes overflow.
The $E_\text{T}^\text{miss}$ distribution in SR1. In the plot, the full event selection in the corresponding signal region is applied, except for the requirement on $E_\text{T}^\text{miss}$. The predicted backgrounds are scaled with normalization factors. The uncertainty band includes statistical and all experimental systematic uncertainties. The last bin contains the overflow. Benchmark signal models are overlaid for comparison. The benchmark models are specified by the gluino and stop masses, given in TeV in the table.
The $m_\text{T}$ distribution in SR1. In the plot, the full event selection in the corresponding signal region is applied, except for the requirement on $m_\text{T}$. The predicted backgrounds are scaled with normalization factors. The uncertainty band includes statistical and all experimental systematic uncertainties. The last bin contains the overflow. Benchmark signal models are overlaid for comparison. The benchmark models are specified by the gluino and stop masses, given in TeV in the table.
Expected (black dashed) 95% excluded regions in the plane of $m_{\tilde{g}}$ versus $m_{\tilde{t}_1}$ for gluino-mediated stop production.
Observed (red solid) 95% excluded regions in the plane of $m_{\tilde{g}}$ versus $m_{\tilde{t}_1}$ for gluino-mediated stop production.
Expected (black dashed) 95% excluded regions in the plane of $m_{\tilde{t}_1}$ versus $m_{\tilde{\chi}_1^0}$ for direct stop production.
Observed (red solid) 95% excluded regions in the plane of $m_{\tilde{t}_1}$ versus $m_{\tilde{\chi}_1^0}$ for direct stop production.
The expected upper limits on $T$ quark pair production times the squared branching ratio for $T \rightarrow tZ$ as a function of the $T$ quark mass.
The observed upper limits on $T$ quark pair production times the squared branching ratio for $T \rightarrow tZ$ as a function of the $T$ quark mass.
The expected limits on $T$ quarks as a function of the branching ratios $B\left(T \rightarrow bW\right)$ and $B\left(T \rightarrow tH\right)$ for a $T$ quark with a mass of 800 GeV. The $T$ is assumed to decay in three possible ways: $T \to tZ$, $T \to tH$, and $T \to bW$.
The observed limits on $T$ quarks as a function of the branching ratios $B\left(T \rightarrow bW\right)$ and $B\left(T \rightarrow tH\right)$ for a $T$ quark with a mass of 800 GeV. The $T$ is assumed to decay in three possible ways: $T \to tZ$, $T \to tH$, and $T \to bW$.
The $m_\text{T}$ distribution in the WVR2-tail validation region which has the same preselection and jet $p_\text{T}$ requirements as SR2.
The $am_\text{T2}$ distribution in the WVR2-tail validation region which has the same preselection and jet $p_\text{T}$ requirements as SR2.
Large-radius jet mass ($R=1.2$), decomposed into the number of small-radius jet constituents. The lower panel shows the ratio of the total data to the total prediction (summed over all jet multiplicities). Events are required to have one lepton, four jets with $p_\text{T}>80,50,40,40$ GeV, at least one $b$-tagged jet, $E_\text{T}^\text{miss}>200$ GeV, and $m_\text{T}>30$ GeV.
Distribution of $m_\text{T2}^\tau$ in data for a selection enriched in $t\bar{t}$ events with one hadronically decaying $\tau$. Events that have no hadronic $\tau$ candidate (that passes the Loose identification criteria, as well as other requirements) are not shown in the plot.
Upper limits on the model cross-section in units of pb for the gluino-mediated stop models.
Upper limits on the model cross-section in units of pb for the models with direct stop pair production.
Illustration of the best expected signal region per signal grid point for the gluino-mediated stop models. This mapping is used for the final combined exclusion limits.
Illustration of the best expected signal region per signal grid point for models with direct stop pair production. This mapping is used for the final combined exclusion limits.
Expected $CL_s$ values for the gluino-mediated stop models.
Observed $CL_s$ values for the gluino-mediated stop models.
Expected $CL_s$ values for the direct stop pair production models.
Observed $CL_s$ values for the direct stop pair production models.
Expected limit using SR1 for models with direct stop pair production and an unpolarized stop (and bino LSP).
Expected limit using SR1 for models with direct stop pair production with $\tilde{t}_1=\tilde{t}_L$ (and bino LSP).
Expected limit using SR1 for models with direct stop pair production with $\tilde{t}_1\sim\tilde{t}_R$ (and bino LSP).
Observed limit using SR1 for models with direct stop pair production and an unpolarized stop (and bino LSP).
Observed limit using SR1 for models with direct stop pair production with $\tilde{t}_1=\tilde{t}_L$ (and bino LSP).
Observed limit using SR1 for models with direct stop pair production with $\tilde{t}_1\sim\tilde{t}_R$ (and bino LSP).
Expected limit using SR2 for models with direct stop pair production and an unpolarized stop (and bino LSP).
Expected limit using SR2 for models with direct stop pair production with $\tilde{t}_1=\tilde{t}_L$ (and bino LSP).
Expected limit using SR2 for models with direct stop pair production with $\tilde{t}_1\sim\tilde{t}_R$ (and bino LSP).
Observed limit using SR2 for models with direct stop pair production and an unpolarized stop (and bino LSP).
Observed limit using SR2 for models with direct stop pair production with $\tilde{t}_1=\tilde{t}_L$ (and bino LSP).
Observed limit using SR2 for models with direct stop pair production with $\tilde{t}_1\sim\tilde{t}_R$ (and bino LSP).
Expected limit using SR1+SR2 (best expected) for models with direct stop pair production and an unpolarized stop (and bino LSP).
Expected limit using SR1+SR2 (best expected) for models with direct stop pair production with $\tilde{t}_1=\tilde{t}_L$ (and bino LSP).
Expected limit using SR1+SR2 (best expected) for models with direct stop pair production with $\tilde{t}_1\sim\tilde{t}_R$ (and bino LSP).
Observed limit using SR1+SR2 (best expected) for models with direct stop pair production and an unpolarized stop (and bino LSP).
Observed limit using SR1+SR2 (best expected) for models with direct stop pair production with $\tilde{t}_1=\tilde{t}_L$ (and bino LSP).
Observed limit using SR1+SR2 (best expected) for models with direct stop pair production with $\tilde{t}_1\sim\tilde{t}_R$ (and bino LSP).
Acceptance for SR1 in the gluino-mediated stop models. The acceptance is defined as the fraction of signal events that pass the analysis selection performed on generator-level objects, therefore emulating an ideal detector with perfect particle identification and no measurement resolution effects.
Acceptance for SR1 in the direct stop pair production. The acceptance is defined as the fraction of signal events that pass the analysis selection performed on generator-level objects, therefore emulating an ideal detector with perfect particle identification and no measurement resolution effects.
Acceptance for SR2 in the gluino-mediated stop models. The acceptance is defined as the fraction of signal events that pass the analysis selection performed on generator-level objects, therefore emulating an ideal detector with perfect particle identification and no measurement resolution effects.
Acceptance for SR2 in the direct stop pair production. The acceptance is defined as the fraction of signal events that pass the analysis selection performed on generator-level objects, therefore emulating an ideal detector with perfect particle identification and no measurement resolution effects.
Acceptance for SR3 in the gluino-mediated stop models. The acceptance is defined as the fraction of signal events that pass the analysis selection performed on generator-level objects, therefore emulating an ideal detector with perfect particle identification and no measurement resolution effects.
Acceptance for SR3 in the direct stop pair production. The acceptance is defined as the fraction of signal events that pass the analysis selection performed on generator-level objects, therefore emulating an ideal detector with perfect particle identification and no measurement resolution effects.
Efficiency for SR1 in the gluino-mediated stop models. The efficiency is the ratio between the expected signal rate calculated with simulated data passing all the reconstruction level cuts applied to reconstructed objects, and the signal rate for an ideal detector (with perfect particle identification and no measurement resolution effects).
Efficiency for SR1 in the direct stop pair production. The efficiency is the ratio between the expected signal rate calculated with simulated data passing all the reconstruction level cuts applied to reconstructed objects, and the signal rate for an ideal detector (with perfect particle identification and no measurement resolution effects).
Efficiency for SR2 in the gluino-mediated stop models. The efficiency is the ratio between the expected signal rate calculated with simulated data passing all the reconstruction level cuts applied to reconstructed objects, and the signal rate for an ideal detector (with perfect particle identification and no measurement resolution effects).
Efficiency for SR2 in the direct stop pair production. The efficiency is the ratio between the expected signal rate calculated with simulated data passing all the reconstruction level cuts applied to reconstructed objects, and the signal rate for an ideal detector (with perfect particle identification and no measurement resolution effects).
Efficiency for SR3 in the gluino-mediated stop models. The efficiency is the ratio between the expected signal rate calculated with simulated data passing all the reconstruction level cuts applied to reconstructed objects, and the signal rate for an ideal detector (with perfect particle identification and no measurement resolution effects).
Efficiency for SR3 in the direct stop pair production. The efficiency is the ratio between the expected signal rate calculated with simulated data passing all the reconstruction level cuts applied to reconstructed objects, and the signal rate for an ideal detector (with perfect particle identification and no measurement resolution effects).
A search is presented for particles that decay producing a large jet multiplicity and invisible particles. The event selection applies a veto on the presence of isolated electrons or muons and additional requirements on the number of b-tagged jets and the scalar sum of masses of large-radius jets. Having explored the full ATLAS 2015-2016 dataset of LHC proton-proton collisions at $\sqrt{s}=13~\mathrm{TeV}$, which corresponds to 36.1 fb$^{-1}$ of integrated luminosity, no evidence is found for physics beyond the Standard Model. The results are interpreted in the context of simplified models inspired by R-parity-conserving and R-parity-violating supersymmetry, where gluinos are pair-produced. More generic models within the phenomenological minimal supersymmetric Standard Model are also considered.
Post-fit yields for each signal region in the multijets analysis. Summary of all 27 signal regions (post-fit).
Observed 95% CL limit for the pMSSM grid.
Observed 95% CL limit for the pMSSM grid when the signal cross section is increased by one standard deviation.
Observed 95% CL limit for the pMSSM grid when the signal cross section is decreased by one standard deviation.
Expected 95% CL limit for the pMSSM grid.
Expected 95% CL limit for the pMSSM grid with an up variation of the uncertainties.
Expected 95% CL limit for the pMSSM grid with a down variation of the uncertainties.
Observed 95% CL limit for the 2Step grid.
Observed 95% CL limit for the 2Step grid when the signal cross section is increased by one standard deviation.
Observed 95% CL limit for the 2Step grid when the signal cross section is decreased by one standard deviation.
Expected 95% CL limit for the 2Step grid.
Expected 95% CL limit for the 2Step grid with an up variation of the uncertainties.
Expected 95% CL limit for the 2Step grid with a down variation of the uncertainties.
Observed 95% CL limit for the gtt off-shell grid.
Observed 95% CL limit for the gtt off-shell grid when the signal cross section is increased by one standard deviation.
Observed 95% CL limit for the gtt off-shell grid when the signal cross section is decreased by one standard deviation.
Expected 95% CL limit for the gtt off-shell grid.
Expected 95% CL limit for the gtt off-shell grid with an up variation of the uncertainties.
Expected 95% CL limit for the gtt off-shell grid with a down variation of the uncertainties.
Observed 95% CL limit for the RPV grid.
Observed 95% CL limit for the RPV grid when the signal cross section is increased by one standard deviation.
Observed 95% CL limit for the RPV grid when the signal cross section is decreased by one standard deviation.
Expected 95% CL limit for the RPV grid.
Expected 95% CL limit for the RPV grid with an up variation of the uncertainties.
Expected 95% CL limit for the RPV grid with a down variation of the uncertainties.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-7j80-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-7j80-1b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-7j80-2b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-8j80-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-8j80-1b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-8j80-2b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-9j80-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-9j80-1b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-9j80-2b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-8j50-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-8j50-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-8j50-1b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-8j50-2b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-9j50-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-9j50-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-9j50-1b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-9j50-2b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-10j50-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-10j50-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-10j50-1b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-10j50-2b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-11j50-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-11j50-1b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-11j50-2b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-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 SR-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 SR-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 SR-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 SR-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 SR-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 SR-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 SR-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 SR-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 SR-11j50-0b. 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 SR-11j50-1b. 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 SR-11j50-2b. 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 SR-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 SR-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 SR-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 SR-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 SR-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 SR-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 SR-9j80-0b. 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 SR-9j80-1b. 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 SR-9j80-2b. 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 SR-8j50-0b-MJ340. 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 SR-8j50-0b-MJ500. 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 SR-9j50-0b-MJ340. 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 SR-9j50-0b-MJ500. 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 SR-10j50-0b-MJ340. 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 SR-10j50-0b-MJ500. 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 (prior to the leptonic background fit) for the flavour stream with no b-jet requirement and a minimum transverse momentum of 50 GeV. 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 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 (prior to the leptonic background fit) for the flavour stream with one inclusive b-jet required and a minimum transverse momentum of 50 GeV. 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 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 (prior to the leptonic background fit) for the flavour stream with two inclusive b-jets required and a minimum transverse momentum of 50 GeV. 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 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 (prior to the leptonic background fit) for the flavour stream with no b-jet requirement and a minimum transverse momentum of 80 GeV. 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 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 (prior to the leptonic background fit) for the flavour stream with one inclusive b-jet required and a minimum transverse momentum of 80 GeV. 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 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 (prior to the leptonic background fit) for the flavour stream with two inclusive b-jets required and a minimum transverse momentum of 80 GeV. 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 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 (prior to the leptonic background fit) for the fat-jet stream with MJSigma above 340 GeV. 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 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 (prior to the leptonic background fit) for the fat-jet stream with MJSigma above 500 GeV. 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 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).
The best-expected signal region and the corresponding best-observed and best-expected CLs values for the 2Step grid.
The best-expected signal region and the corresponding best-observed and best-expected CLs values for the 2Step grid.
The best-expected signal region and the corresponding best-observed and best-expected CLs values for the 2Step grid.
The best-expected signal region and the corresponding best-observed and best-expected CLs values for the pMSSM grid.
The best-expected signal region and the corresponding best-observed and best-expected CLs values for the pMSSM grid.
The best-expected signal region and the corresponding best-observed and best-expected CLs values for the pMSSM grid.
The best-expected signal region and the corresponding best-observed and best-expected CLs values for the RPV grid.
The best-expected signal region and the corresponding best-observed and best-expected CLs values for the RPV grid.
The best-expected signal region and the corresponding best-observed and best-expected CLs values for the RPV grid.
The best-expected signal region and the corresponding best-observed and best-expected CLs values for the gtt off-shell grid.
The best-expected signal region and the corresponding best-observed and best-expected CLs values for the gtt off-shell grid.
The best-expected signal region and the corresponding best-observed and best-expected CLs values for the gtt off-shell grid.
95% CLs observed upper limit on model cross-section (in fb) for 2Step signal points for the best-expected signal region.
95% CLs observed upper limit on model cross-section (in fb) for RPV signal points for the best-expected signal region.
95% CLs observed upper limit on model cross-section (in fb) for gtt off-shell signal points for the best-expected signal region.
Performance of the SR-8j50-0b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-8j50-0b-MJ340 for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-8j50-0b-MJ500 for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-8j50-1b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-8j50-2b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-9j50-0b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-9j50-0b-MJ340 for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-9j50-0b-MJ500 for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-9j50-1b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-9j50-2b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-10j50-0b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-10j50-0b-MJ340 for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-10j50-0b-MJ500 for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-10j50-1b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-10j50-2b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-11j50-0b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-11j50-1b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-11j50-2b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-7j80-0b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-7j80-1b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-7j80-2b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-8j80-0b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-8j80-1b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-8j80-2b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-9j80-0b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-9j80-1b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-9j80-2b for the 2Step grid: fractional acceptance; fractional efficiency.
The results of a search for squarks and gluinos in final states with an isolated electron or muon, multiple jets and large missing transverse momentum using proton--proton collision data at a center-of-mass energy of $\sqrt{s}$ = 13 TeV are presented. The dataset used was recorded during 2015 and 2016 by the ATLAS experiment at the Large Hadron Collider and corresponds to an integrated luminosity of 36.1 $fb^{-1}$. No significant excess beyond the expected background is found. Exclusion limits at 95% confidence level are set in a number of supersymmetric scenarios, reaching masses up to 2.1 TeV for gluino pair production and up to 1.25 TeV for squark pair production.
Observed 95% CL exclusion contours for the gluino one-step x = 1/2 model.
Observed 95% CL exclusion contours for the gluino one-step x = 1/2 model.
Expected 95% CL exclusion contours for the gluino one-step x = 1/2 model.
Expected 95% CL exclusion contours for the gluino one-step x = 1/2 model.
Observed 95% CL exclusion contours for the gluino one-step variable-x model.
Observed 95% CL exclusion contours for the gluino one-step variable-x model.
Expected 95% CL exclusion contours for the gluino one-step variable-x model.
Expected 95% CL exclusion contours for the gluino one-step variable-x model.
Observed 95% CL exclusion contours for the squark 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 squark one-step x = 1/2 model.
Expected 95% CL exclusion contours for the squark one-step x = 1/2 model.
Observed 95% CL exclusion contours for the squark one-step variable-x model.
Observed 95% CL exclusion contours for the squark one-step variable-x model.
Expected 95% CL exclusion contours for the squark one-step variable-x model.
Expected 95% CL exclusion contours for the squark one-step variable-x model.
Observed 95% CL exclusion contours for the gluino two-step model.
Observed 95% CL exclusion contours for the gluino two-step model.
Expected 95% CL exclusion contours for the gluino two-step model.
Expected 95% CL exclusion contours for the gluino two-step model.
Observed 95% CL exclusion contours for pMSSM model.
Observed 95% CL exclusion contours for pMSSM model.
Expected 95% CL exclusion contours for pMSSM model.
Expected 95% CL exclusion contours for pMSSM model.
$m_{\mathrm{eff}}$ distribution in 2J b-veto signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{eff}}$ distribution in 2J b-veto signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{eff}}$ distribution in 4J low-x b-veto signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{eff}}$ distribution in 4J low-x b-veto signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{eff}}$ distribution in 4J high-x b-veto signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{eff}}$ distribution in 4J high-x b-veto signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{eff}}$ distribution in 6J b-veto signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{eff}}$ distribution in 6J b-veto signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{eff}}$ distribution in 2J b-tag signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{eff}}$ distribution in 2J b-tag signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{eff}}$ distribution in 4J low-x b-tag signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{eff}}$ distribution in 4J low-x b-tag signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{eff}}$ distribution in 4J high-x b-tag signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{eff}}$ distribution in 4J high-x b-tag signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{eff}}$ distribution in 6J b-tag signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{eff}}$ distribution in 6J b-tag signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{eff}}$ distribution in 9J signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{eff}}$ distribution in 9J signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{T}}$ distribution for events satisfying all the 2J b-veto signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{T}}$ distribution for events satisfying all the 2J b-veto signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$E_{\mathrm T}^{\mathrm{miss}}$ distribution for events satisfying all the 2J b-veto signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$E_{\mathrm T}^{\mathrm{miss}}$ distribution for events satisfying all the 2J b-veto signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{T}}$ distribution for events satisfying all the 2J b-tag signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{T}}$ distribution for events satisfying all the 2J b-tag signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$E_{\mathrm T}^{\mathrm{miss}}$ distribution for events satisfying all the 2J b-tag signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$E_{\mathrm T}^{\mathrm{miss}}$ distribution for events satisfying all the 2J b-tag signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{T}}$ distribution for events satisfying all the 4J low-x b-veto signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{T}}$ distribution for events satisfying all the 4J low-x b-veto signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$E_{\mathrm T}^{\mathrm{miss}}$ distribution for events satisfying all the 4J low-x b-veto signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$E_{\mathrm T}^{\mathrm{miss}}$ distribution for events satisfying all the 4J low-x b-veto signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{T}}$ distribution for events satisfying all the 4J low-x b-tag signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{T}}$ distribution for events satisfying all the 4J low-x b-tag signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$E_{\mathrm T}^{\mathrm{miss}}$ distribution for events satisfying all the 4J low-x b-tag signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$E_{\mathrm T}^{\mathrm{miss}}$ distribution for events satisfying all the 4J low-x b-tag signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{T}}$ distribution for events satisfying all the 4J high-x b-veto signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{T}}$ distribution for events satisfying all the 4J high-x b-veto signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$E_{\mathrm T}^{\mathrm{miss}}$ distribution for events satisfying all the 4J high-x b-veto signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$E_{\mathrm T}^{\mathrm{miss}}$ distribution for events satisfying all the 4J high-x b-veto signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{T}}$ distribution for events satisfying all the 4J high-x b-tag signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{T}}$ distribution for events satisfying all the 4J high-x b-tag signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$E_{\mathrm T}^{\mathrm{miss}}$ distribution for events satisfying all the 4J high-x b-tag signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$E_{\mathrm T}^{\mathrm{miss}}$ distribution for events satisfying all the 4J high-x b-tag signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{T}}$ distribution for events satisfying all the 6J b-veto signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{T}}$ distribution for events satisfying all the 6J b-veto signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$E_{\mathrm T}^{\mathrm{miss}}$ distribution for events satisfying all the 6J b-veto signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$E_{\mathrm T}^{\mathrm{miss}}$ distribution for events satisfying all the 6J b-veto signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{T}}$ distribution for events satisfying all the 6J b-tag signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{T}}$ distribution for events satisfying all the 6J b-tag signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$E_{\mathrm T}^{\mathrm{miss}}$ distribution for events satisfying all the 6J b-tag signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$E_{\mathrm T}^{\mathrm{miss}}$ distribution for events satisfying all the 6J b-tag signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{T}}$ distribution for events satisfying all the 9J signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{T}}$ distribution for events satisfying all the 9J signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
Observed upper limits on the signal cross-section for gluino one-step x = 1/2 model.
Observed upper limits on the signal cross-section for gluino one-step x = 1/2 model.
Observed upper limits on the signal cross-section for gluino one-step variable-x model.
Observed upper limits on the signal cross-section for gluino one-step variable-x model.
Observed upper limits on the signal cross-section for squark one-step x = 1/2 model.
Observed upper limits on the signal cross-section for squark one-step x = 1/2 model.
Observed upper limits on the signal cross-section for squark one-step variable-x model.
Observed upper limits on the signal cross-section for squark one-step variable-x model.
Observed upper limits on the signal cross-section for gluino two-step model.
Observed upper limits on the signal cross-section for gluino two-step model.
Observed upper limits on the signal cross-section for pMSSM model.
Observed upper limits on the signal cross-section for pMSSM model.
Acceptance in 2J discovery signal region for gluino one-step x = 1/2 model.
Acceptance in 2J discovery signal region for gluino one-step x = 1/2 model.
Acceptance in 2J discovery signal region for squark one-step x = 1/2 model.
Acceptance in 2J discovery signal region for squark one-step x = 1/2 model.
Acceptance in 4J low-x discovery signal region for gluino one-step variable-x model.
Acceptance in 4J low-x discovery signal region for gluino one-step variable-x model.
Acceptance in 4J low-x discovery signal region for squark one-step variable-x model.
Acceptance in 4J low-x discovery signal region for squark one-step variable-x model.
Acceptance in 4J high-x discovery signal region for gluino one-step variable-x model.
Acceptance in 4J high-x discovery signal region for gluino one-step variable-x model.
Acceptance in 4J high-x discovery signal region for squark one-step variable-x model.
Acceptance in 4J high-x discovery signal region for squark one-step variable-x model.
Acceptance in 6J discovery signal region for gluino one-step x = 1/2 model.
Acceptance in 6J discovery signal region for gluino one-step x = 1/2 model.
Acceptance in 6J discovery signal region for squark one-step x = 1/2 model.
Acceptance in 6J discovery signal region for squark one-step x = 1/2 model.
Acceptance in 9J discovery signal region for pMSSM model.
Acceptance in 9J discovery signal region for pMSSM model.
Acceptance in 9J discovery signal region for gluino two-step model.
Acceptance in 9J discovery signal region for gluino two-step model.
Efficiency in 2J discovery signal region for gluino one-step x = 1/2 model.
Efficiency in 2J discovery signal region for gluino one-step x = 1/2 model.
Efficiency in 2J discovery signal region for squark one-step x = 1/2 model.
Efficiency in 2J discovery signal region for squark one-step x = 1/2 model.
Efficiency in 4J low-x discovery signal region for gluino one-step variable-x model.
Efficiency in 4J low-x discovery signal region for gluino one-step variable-x model.
Efficiency in 4J low-x discovery signal region for squark one-step variable-x model.
Efficiency in 4J low-x discovery signal region for squark one-step variable-x model.
Efficiency in 4J high-x discovery signal region for gluino one-step variable-x model.
Efficiency in 4J high-x discovery signal region for gluino one-step variable-x model.
Efficiency in 4J high-x discovery signal region for squark one-step variable-x model.
Efficiency in 4J high-x discovery signal region for squark one-step variable-x model.
Efficiency in 6J discovery signal region for gluino one-step x = 1/2 model.
Efficiency in 6J discovery signal region for gluino one-step x = 1/2 model.
Efficiency in 6J discovery signal region for squark one-step x = 1/2 model.
Efficiency in 6J discovery signal region for squark one-step x = 1/2 model.
Efficiency in 9J discovery signal region for pMSSM model.
Efficiency in 9J discovery signal region for pMSSM model.
Efficiency in 9J discovery signal region for gluino two-step model.
Efficiency in 9J discovery signal region for gluino two-step model.
Cutflow table for the 2J discovery signal region with a representative target signal model. The weighted numbers are normalized to 36.1 fb$^{-1}$ and rounded to the statistical error. The selection called "Filter" is introduced for initial data reduction. It selects events with at least one soft electron or muon ($3.5 < p_\mathrm{T} < 25$ GeV for muons and $4.5 < p_\mathrm{T} < 25$ GeV for electrons) in which an $E_\mathrm{T}^\mathrm{miss}$ trigger has fired or events with at least one hard electron or muon ($p_\mathrm{T} >$25 GeV).
Cutflow table for the 2J discovery signal region with a representative target signal model. The weighted numbers are normalized to 36.1 fb$^{-1}$ and rounded to the statistical error. The selection called "Filter" is introduced for initial data reduction. It selects events with at least one soft electron or muon ($3.5 < p_\mathrm{T} < 25$ GeV for muons and $4.5 < p_\mathrm{T} < 25$ GeV for electrons) in which an $E_\mathrm{T}^\mathrm{miss}$ trigger has fired or events with at least one hard electron or muon ($p_\mathrm{T} >$25 GeV).
Cutflow table for the 4J high-x discovery signal region with a representative target signal model. The weighted numbers are normalized to 36.1 fb$^{-1}$ and rounded to the statistical error. The selection called "Filter" is introduced for initial data reduction. It selects events with at least one soft electron or muon ($3.5 < p_\mathrm{T} < 25$ GeV for muons and $4.5 < p_\mathrm{T} < 25$ GeV for electrons) in which an $E_\mathrm{T}^\mathrm{miss}$ trigger has fired or events with at least one hard electron or muon ($p_\mathrm{T} >$25 GeV).
Cutflow table for the 4J high-x discovery signal region with a representative target signal model. The weighted numbers are normalized to 36.1 fb$^{-1}$ and rounded to the statistical error. The selection called "Filter" is introduced for initial data reduction. It selects events with at least one soft electron or muon ($3.5 < p_\mathrm{T} < 25$ GeV for muons and $4.5 < p_\mathrm{T} < 25$ GeV for electrons) in which an $E_\mathrm{T}^\mathrm{miss}$ trigger has fired or events with at least one hard electron or muon ($p_\mathrm{T} >$25 GeV).
Cutflow table for the 4J low-x discovery signal region (targetting gluino decays) with a representative target signal model. The weighted numbers are normalized to 36.1 fb$^{-1}$ and rounded to the statistical error. The selection called "Filter" is introduced for initial data reduction. It selects events with at least one soft electron or muon ($3.5 < p_\mathrm{T} < 25$ GeV for muons and $4.5 < p_\mathrm{T} < 25$ GeV for electrons) in which an $E_\mathrm{T}^\mathrm{miss}$ trigger has fired or events with at least one hard electron or muon ($p_\mathrm{T} >$25 GeV).
Cutflow table for the 4J low-x discovery signal region (targetting gluino decays) with a representative target signal model. The weighted numbers are normalized to 36.1 fb$^{-1}$ and rounded to the statistical error. The selection called "Filter" is introduced for initial data reduction. It selects events with at least one soft electron or muon ($3.5 < p_\mathrm{T} < 25$ GeV for muons and $4.5 < p_\mathrm{T} < 25$ GeV for electrons) in which an $E_\mathrm{T}^\mathrm{miss}$ trigger has fired or events with at least one hard electron or muon ($p_\mathrm{T} >$25 GeV).
Cutflow table for the 4J low-x discovery signal region (targetting squark decays) with a representative target signal model. The weighted numbers are normalized to 36.1 fb$^{-1}$ and rounded to the statistical error. The selection called "Filter" is introduced for initial data reduction. It selects events with at least one soft electron or muon ($3.5 < p_\mathrm{T} < 25$ GeV for muons and $4.5 < p_\mathrm{T} < 25$ GeV for electrons) in which an $E_\mathrm{T}^\mathrm{miss}$ trigger has fired or events with at least one hard electron or muon ($p_\mathrm{T} >$25 GeV).
Cutflow table for the 4J low-x discovery signal region (targetting squark decays) with a representative target signal model. The weighted numbers are normalized to 36.1 fb$^{-1}$ and rounded to the statistical error. The selection called "Filter" is introduced for initial data reduction. It selects events with at least one soft electron or muon ($3.5 < p_\mathrm{T} < 25$ GeV for muons and $4.5 < p_\mathrm{T} < 25$ GeV for electrons) in which an $E_\mathrm{T}^\mathrm{miss}$ trigger has fired or events with at least one hard electron or muon ($p_\mathrm{T} >$25 GeV).
Cutflow table for the 6J discovery signal region (targetting gluino decays) with a representative target signal model. The weighted numbers are normalized to 36.1 fb$^{-1}$ and rounded to the statistical error. The selection called "Filter" is introduced for initial data reduction. It selects events with at least one soft electron or muon ($3.5 < p_\mathrm{T} < 25$ GeV for muons and $4.5 < p_\mathrm{T} < 25$ GeV for electrons) in which an $E_\mathrm{T}^\mathrm{miss}$ trigger has fired or events with at least one hard electron or muon ($p_\mathrm{T} >$25 GeV).
Cutflow table for the 6J discovery signal region (targetting gluino decays) with a representative target signal model. The weighted numbers are normalized to 36.1 fb$^{-1}$ and rounded to the statistical error. The selection called "Filter" is introduced for initial data reduction. It selects events with at least one soft electron or muon ($3.5 < p_\mathrm{T} < 25$ GeV for muons and $4.5 < p_\mathrm{T} < 25$ GeV for electrons) in which an $E_\mathrm{T}^\mathrm{miss}$ trigger has fired or events with at least one hard electron or muon ($p_\mathrm{T} >$25 GeV).
Cutflow table for the 6J discovery signal region (targetting squark decays) with a representative target signal model. The weighted numbers are normalized to 36.1 fb$^{-1}$ and rounded to the statistical error. The selection called "Filter" is introduced for initial data reduction. It selects events with at least one soft electron or muon ($3.5 < p_\mathrm{T} < 25$ GeV for muons and $4.5 < p_\mathrm{T} < 25$ GeV for electrons) in which an $E_\mathrm{T}^\mathrm{miss}$ trigger has fired or events with at least one hard electron or muon ($p_\mathrm{T} >$25 GeV).
Cutflow table for the 6J discovery signal region (targetting squark decays) with a representative target signal model. The weighted numbers are normalized to 36.1 fb$^{-1}$ and rounded to the statistical error. The selection called "Filter" is introduced for initial data reduction. It selects events with at least one soft electron or muon ($3.5 < p_\mathrm{T} < 25$ GeV for muons and $4.5 < p_\mathrm{T} < 25$ GeV for electrons) in which an $E_\mathrm{T}^\mathrm{miss}$ trigger has fired or events with at least one hard electron or muon ($p_\mathrm{T} >$25 GeV).
Cutflow table for the 9J discovery signal region with a representative target signal model. The weighted numbers are normalized to 36.1 fb$^{-1}$ and rounded to the statistical error. The selection called "Filter" is introduced for initial data reduction. It selects events with at least one soft electron or muon ($3.5 < p_\mathrm{T} < 25$ GeV for muons and $4.5 < p_\mathrm{T} < 25$ GeV for electrons) in which an $E_\mathrm{T}^\mathrm{miss}$ trigger has fired or events with at least one hard electron or muon ($p_\mathrm{T} >$25 GeV).
Cutflow table for the 9J discovery signal region with a representative target signal model. The weighted numbers are normalized to 36.1 fb$^{-1}$ and rounded to the statistical error. The selection called "Filter" is introduced for initial data reduction. It selects events with at least one soft electron or muon ($3.5 < p_\mathrm{T} < 25$ GeV for muons and $4.5 < p_\mathrm{T} < 25$ GeV for electrons) in which an $E_\mathrm{T}^\mathrm{miss}$ trigger has fired or events with at least one hard electron or muon ($p_\mathrm{T} >$25 GeV).
A search for supersymmetry involving the pair production of gluinos decaying via third-generation squarks into the lightest neutralino ($\displaystyle\tilde\chi^0_1$) is reported. It uses LHC proton--proton collision data at a centre-of-mass energy $\sqrt{s} = 13$ TeV with an integrated luminosity of 36.1 fb$^{-1}$ collected with the ATLAS detector in 2015 and 2016. The search is performed in events containing large missing transverse momentum and several energetic jets, at least three of which must be identified as originating from $b$-quarks. To increase the sensitivity, the sample is divided into subsamples based on the presence or absence of electrons or muons. No excess is found above the predicted background. For $\displaystyle\tilde\chi^0_1$ masses below approximately 300 GeV, gluino masses of less than 1.97 (1.92) TeV are excluded at 95% confidence level in simplified models involving the pair production of gluinos that decay via top (bottom) squarks. An interpretation of the limits in terms of the branching ratios of the gluinos into third-generation squarks is also provided. These results improve upon the exclusion limits obtained with the 3.2 fb$^{-1}$ of data collected in 2015.
Observed 95% CL exclusion contour for Gtt model.
Observed 95% CL exclusion contour for Gtt model.
Observed 95% CL exclusion contour for Gtt model.
Observed 95% CL exclusion contour for Gtt model.
Expected 95% CL exclusion contour for Gtt model.
Expected 95% CL exclusion contour for Gtt model.
Expected 95% CL exclusion contour for Gtt model.
Expected 95% CL exclusion contour for Gtt model.
Observed 95% CL exclusion contour for Gbb model.
Observed 95% CL exclusion contour for Gbb model.
Observed 95% CL exclusion contour for Gbb model.
Observed 95% CL exclusion contour for Gbb model.
Expected 95% CL exclusion contour for Gbb model.
Expected 95% CL exclusion contour for Gbb model.
Expected 95% CL exclusion contour for Gbb model.
Expected 95% CL exclusion contour for Gbb model.
Expected 95% CL exclusion contour for Gluino mass = 1.8 TeV, Neutralino mass = 1 GeV.
Expected 95% CL exclusion contour for Gluino mass = 1.8 TeV, Neutralino mass = 1 GeV.
Expected 95% CL exclusion contour for Gluino mass = 1.8 TeV, Neutralino mass = 1 GeV.
Expected 95% CL exclusion contour for Gluino mass = 1.8 TeV, Neutralino mass = 1 GeV.
Observed 95% CL exclusion contour for Gluino mass = 1.8 TeV, Neutralino mass = 1 GeV.
Observed 95% CL exclusion contour for Gluino mass = 1.8 TeV, Neutralino mass = 1 GeV.
Observed 95% CL exclusion contour for Gluino mass = 1.8 TeV, Neutralino mass = 1 GeV.
Observed 95% CL exclusion contour for Gluino mass = 1.8 TeV, Neutralino mass = 1 GeV.
Expected 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 GeV.
Expected 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 GeV.
Expected 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 GeV.
Expected 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 GeV.
Observed 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 GeV.
Observed 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 GeV.
Observed 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 GeV.
Observed 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 GeV.
Expected 95% CL exclusion contour for Gluino mass = 2.0 TeV, Neutralino mass = 1 GeV.
Expected 95% CL exclusion contour for Gluino mass = 2.0 TeV, Neutralino mass = 1 GeV.
Expected 95% CL exclusion contour for Gluino mass = 2.0 TeV, Neutralino mass = 1 GeV.
Expected 95% CL exclusion contour for Gluino mass = 2.0 TeV, Neutralino mass = 1 GeV.
Observed 95% CL exclusion contour for Gluino mass = 2.0 TeV, Neutralino mass = 1 GeV.
Observed 95% CL exclusion contour for Gluino mass = 2.0 TeV, Neutralino mass = 1 GeV.
Observed 95% CL exclusion contour for Gluino mass = 2.0 TeV, Neutralino mass = 1 GeV.
Observed 95% CL exclusion contour for Gluino mass = 2.0 TeV, Neutralino mass = 1 GeV.
Expected 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 GeV.
Expected 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 GeV.
Expected 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 GeV.
Expected 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 GeV.
Observed 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 GeV.
Observed 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 GeV.
Observed 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 GeV.
Observed 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 GeV.
Expected 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 600 GeV.
Expected 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 600 GeV.
Expected 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 600 GeV.
Expected 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 600 GeV.
Observed 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 600 GeV.
Observed 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 600 GeV.
Observed 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 600 GeV.
Observed 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 600 GeV.
Expected 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 TeV.
Expected 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 TeV.
Expected 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 TeV.
Expected 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 TeV.
Observed 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 TeV.
Observed 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 TeV.
Observed 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 TeV.
Observed 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 TeV.
Distribution of ETMISS for SR-Gbb-VC.
Distribution of ETMISS for SR-Gbb-VC.
Distribution of ETMISS for SR-Gbb-VC.
Distribution of ETMISS for SR-Gbb-VC.
Distribution of ETMISS for SR-Gtt-1l-B.
Distribution of ETMISS for SR-Gtt-1l-B.
Distribution of ETMISS for SR-Gtt-1l-B.
Distribution of ETMISS for SR-Gtt-1l-B.
Distribution of ETMISS for SR-1L-II.
Distribution of ETMISS for SR-1L-II.
Distribution of ETMISS for SR-1L-II.
Distribution of ETMISS for SR-1L-II.
Distribution of ETMISS for SR-0L-HI.
Distribution of ETMISS for SR-0L-HI.
Distribution of ETMISS for SR-0L-HI.
Distribution of ETMISS for SR-0L-HI.
Distribution of ETMISS for SR-0L-HH.
Distribution of ETMISS for SR-0L-HH.
Distribution of ETMISS for SR-0L-HH.
Distribution of ETMISS for SR-0L-HH.
Acceptances for Gbb model in SR-Gbb-B.
Acceptances for Gbb model in SR-Gbb-B.
Acceptances for Gbb model in SR-Gbb-B.
Acceptances for Gbb model in SR-Gbb-B.
Acceptances for Gbb model in SR-Gbb-M.
Acceptances for Gbb model in SR-Gbb-M.
Acceptances for Gbb model in SR-Gbb-M.
Acceptances for Gbb model in SR-Gbb-M.
Acceptances for Gbb model in SR-Gbb-C.
Acceptances for Gbb model in SR-Gbb-C.
Acceptances for Gbb model in SR-Gbb-C.
Acceptances for Gbb model in SR-Gbb-C.
Acceptances for Gbb model in SR-Gbb-VC.
Acceptances for Gbb model in SR-Gbb-VC.
Acceptances for Gbb model in SR-Gbb-VC.
Acceptances for Gbb model in SR-Gbb-VC.
Acceptances for Gtt model in SR-Gtt-0l-B.
Acceptances for Gtt model in SR-Gtt-0l-B.
Acceptances for Gtt model in SR-Gtt-0l-B.
Acceptances for Gtt model in SR-Gtt-0l-B.
Acceptances for Gtt model in SR-Gtt-0l-M.
Acceptances for Gtt model in SR-Gtt-0l-M.
Acceptances for Gtt model in SR-Gtt-0l-M.
Acceptances for Gtt model in SR-Gtt-0l-M.
Acceptances for Gtt model in SR-Gtt-0l-C.
Acceptances for Gtt model in SR-Gtt-0l-C.
Acceptances for Gtt model in SR-Gtt-0l-C.
Acceptances for Gtt model in SR-Gtt-0l-C.
Acceptances for Gtt model in SR-Gtt-1l-B.
Acceptances for Gtt model in SR-Gtt-1l-B.
Acceptances for Gtt model in SR-Gtt-1l-B.
Acceptances for Gtt model in SR-Gtt-1l-B.
Acceptances for Gtt model in SR-Gtt-1l-M.
Acceptances for Gtt model in SR-Gtt-1l-M.
Acceptances for Gtt model in SR-Gtt-1l-M.
Acceptances for Gtt model in SR-Gtt-1l-M.
Acceptances for Gtt model in SR-Gtt-1l-C.
Acceptances for Gtt model in SR-Gtt-1l-C.
Acceptances for Gtt model in SR-Gtt-1l-C.
Experimental efficiencies for Gbb model in SR-Gbb-B.
Experimental efficiencies for Gbb model in SR-Gbb-B.
Experimental efficiencies for Gbb model in SR-Gbb-B.
Experimental efficiencies for Gbb model in SR-Gbb-M.
Experimental efficiencies for Gbb model in SR-Gbb-M.
Experimental efficiencies for Gbb model in SR-Gbb-M.
Experimental efficiencies for Gbb model in SR-Gbb-C.
Experimental efficiencies for Gbb model in SR-Gbb-C.
Experimental efficiencies for Gbb model in SR-Gbb-C.
Experimental efficiencies for Gbb model in SR-Gbb-VC.
Experimental efficiencies for Gbb model in SR-Gbb-VC.
Experimental efficiencies for Gbb model in SR-Gbb-VC.
Experimental efficiencies for Gtt model in SR-Gtt-0l-B.
Experimental efficiencies for Gtt model in SR-Gtt-0l-B.
Experimental efficiencies for Gtt model in SR-Gtt-0l-B.
Experimental efficiencies for Gtt model in SR-Gtt-0l-M.
Experimental efficiencies for Gtt model in SR-Gtt-0l-M.
Experimental efficiencies for Gtt model in SR-Gtt-0l-M.
Experimental efficiencies for Gtt model in SR-Gtt-0l-C.
Experimental efficiencies for Gtt model in SR-Gtt-0l-C.
Experimental efficiencies for Gtt model in SR-Gtt-0l-C.
Experimental efficiencies for Gtt model in SR-Gtt-1l-B.
Experimental efficiencies for Gtt model in SR-Gtt-1l-B.
Experimental efficiencies for Gtt model in SR-Gtt-1l-B.
Experimental efficiencies for Gtt model in SR-Gtt-1l-M.
Experimental efficiencies for Gtt model in SR-Gtt-1l-M.
Experimental efficiencies for Gtt model in SR-Gtt-1l-M.
Experimental efficiencies for Gtt model in SR-Gtt-0l-C.
Experimental efficiencies for Gtt model in SR-Gtt-0l-C.
Experimental efficiencies for Gtt model in SR-Gtt-0l-C.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gbb model.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gbb model.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gbb model.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gbb model in SR-Gbb-B.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gbb model in SR-Gbb-B.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gbb model in SR-Gbb-B.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gbb model in SR-Gbb-M.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gbb model in SR-Gbb-M.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gbb model in SR-Gbb-M.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gbb model in SR-Gbb-C.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gbb model in SR-Gbb-C.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gbb model in SR-Gbb-C.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gbb model in SR-Gbb-VC.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gbb model in SR-Gbb-VC.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gbb model in SR-Gbb-VC.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-0l-B.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-0l-B.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-0l-B.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-0l-M.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-0l-M.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-0l-M.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-0l-C.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-0l-C.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-0l-C.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-1l-B.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-1l-B.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-1l-B.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-1l-M.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-1l-M.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-1l-M.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-1l-C.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-1l-C.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-1l-C.
Observed 95% CL exclusion contour for Gbb model in SR-Gbb-B.
Observed 95% CL exclusion contour for Gbb model in SR-Gbb-B.
Observed 95% CL exclusion contour for Gbb model in SR-Gbb-B.
Expected 95% CL exclusion contour for Gbb model in SR-Gbb-B.
Expected 95% CL exclusion contour for Gbb model in SR-Gbb-B.
Expected 95% CL exclusion contour for Gbb model in SR-Gbb-B.
Observed 95% CL exclusion contour for Gbb model in SR-Gbb-M.
Observed 95% CL exclusion contour for Gbb model in SR-Gbb-M.
Observed 95% CL exclusion contour for Gbb model in SR-Gbb-M.
Expected 95% CL exclusion contour for Gbb model in SR-Gbb-M.
Expected 95% CL exclusion contour for Gbb model in SR-Gbb-M.
Expected 95% CL exclusion contour for Gbb model in SR-Gbb-M.
Observed 95% CL exclusion contour for Gbb model in SR-Gbb-C.
Observed 95% CL exclusion contour for Gbb model in SR-Gbb-C.
Observed 95% CL exclusion contour for Gbb model in SR-Gbb-C.
Expected 95% CL exclusion contour for Gbb model in SR-Gbb-C.
Expected 95% CL exclusion contour for Gbb model in SR-Gbb-C.
Expected 95% CL exclusion contour for Gbb model in SR-Gbb-C.
Observed 95% CL exclusion contour for Gbb model in SR-Gbb-VC.
Observed 95% CL exclusion contour for Gbb model in SR-Gbb-VC.
Observed 95% CL exclusion contour for Gbb model in SR-Gbb-VC.
Expected 95% CL exclusion contour for Gbb model in SR-Gbb-VC.
Expected 95% CL exclusion contour for Gbb model in SR-Gbb-VC.
Expected 95% CL exclusion contour for Gbb model in SR-Gbb-VC.
Observed 95% CL exclusion contour for Gtt model in SR-Gtt-0l-B.
Observed 95% CL exclusion contour for Gtt model in SR-Gtt-0l-B.
Observed 95% CL exclusion contour for Gtt model in SR-Gtt-0l-B.
Expected 95% CL exclusion contour for Gtt model in SR-Gtt-0l-B.
Expected 95% CL exclusion contour for Gtt model in SR-Gtt-0l-B.
Expected 95% CL exclusion contour for Gtt model in SR-Gtt-0l-B.
Observed 95% CL exclusion contour for Gtt model in SR-Gtt-0l-M.
Observed 95% CL exclusion contour for Gtt model in SR-Gtt-0l-M.
Observed 95% CL exclusion contour for Gtt model in SR-Gtt-0l-M.
Expected 95% CL exclusion contour for Gtt model in SR-Gtt-0l-M.
Expected 95% CL exclusion contour for Gtt model in SR-Gtt-0l-M.
Expected 95% CL exclusion contour for Gtt model in SR-Gtt-0l-M.
Observed 95% CL exclusion contour for Gtt model in SR-Gtt-0l-C.
Observed 95% CL exclusion contour for Gtt model in SR-Gtt-0l-C.
Observed 95% CL exclusion contour for Gtt model in SR-Gtt-0l-C.
Expected 95% CL exclusion contour for Gtt model in SR-Gtt-0l-C.
Expected 95% CL exclusion contour for Gtt model in SR-Gtt-0l-C.
Expected 95% CL exclusion contour for Gtt model in SR-Gtt-0l-C.
Observed 95% CL exclusion contour for Gtt model in SR-Gtt-1l-B.
Observed 95% CL exclusion contour for Gtt model in SR-Gtt-1l-B.
Observed 95% CL exclusion contour for Gtt model in SR-Gtt-1l-B.
Expected 95% CL exclusion contour for Gtt model in SR-Gtt-1l-B.
Expected 95% CL exclusion contour for Gtt model in SR-Gtt-1l-B.
Expected 95% CL exclusion contour for Gtt model in SR-Gtt-1l-B.
Observed 95% CL exclusion contour for Gtt model in SR-Gtt-1l-M.
Observed 95% CL exclusion contour for Gtt model in SR-Gtt-1l-M.
Observed 95% CL exclusion contour for Gtt model in SR-Gtt-1l-M.
Expected 95% CL exclusion contour for Gtt model in SR-Gtt-1l-M.
Expected 95% CL exclusion contour for Gtt model in SR-Gtt-1l-M.
Expected 95% CL exclusion contour for Gtt model in SR-Gtt-1l-M.
Observed 95% CL exclusion contour for Gtt model in SR-Gtt-1l-C.
Observed 95% CL exclusion contour for Gtt model in SR-Gtt-1l-C.
Observed 95% CL exclusion contour for Gtt model in SR-Gtt-1l-C.
Expected 95% CL exclusion contour for Gtt model in SR-Gtt-1l-C.
Expected 95% CL exclusion contour for Gtt model in SR-Gtt-1l-C.
Expected 95% CL exclusion contour for Gtt model in SR-Gtt-1l-C.
Expected number of signal events after each step of the Gbb-0L-B selection for a Gbb signal point (MGLUON,MNEUTRALINO) = (1900,1400) GeV.
Expected number of signal events after each step of the Gbb-0L-B selection for a Gbb signal point (MGLUON,MNEUTRALINO) = (1900,1400) GeV.
Expected number of signal events after each step of the Gbb-0L-B selection for a Gbb signal point (MGLUON,MNEUTRALINO) = (1900,1400) GeV.
Expected number of signal events after each step of the Gbb-0L-M selection for a Gbb signal point (MGLUON,MNEUTRALINO) = (1900,1400) GeV.
Expected number of signal events after each step of the Gbb-0L-M selection for a Gbb signal point (MGLUON,MNEUTRALINO) = (1900,1400) GeV.
Expected number of signal events after each step of the Gbb-0L-M selection for a Gbb signal point (MGLUON,MNEUTRALINO) = (1900,1400) GeV.
Expected number of signal events after each step of the Gbb-0L-C selection for a Gbb signal point (MGLUON,MNEUTRALINO) = (1900,1400) GeV.
Expected number of signal events after each step of the Gbb-0L-C selection for a Gbb signal point (MGLUON,MNEUTRALINO) = (1900,1400) GeV.
Expected number of signal events after each step of the Gbb-0L-C selection for a Gbb signal point (MGLUON,MNEUTRALINO) = (1900,1400) GeV.
Expected number of signal events after each step of the Gbb-0L-VC selection for a Gbb signal point (MGLUON,MNEUTRALINO) = (1900,1400) GeV.
Expected number of signal events after each step of the Gbb-0L-VC selection for a Gbb signal point (MGLUON,MNEUTRALINO) = (1900,1400) GeV.
Expected number of signal events after each step of the Gbb-0L-VC selection for a Gbb signal point (MGLUON,MNEUTRALINO) = (1900,1400) GeV.
Expected number of signal events after each step of the Gtt-1L-B selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.
Expected number of signal events after each step of the Gtt-1L-B selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.
Expected number of signal events after each step of the Gtt-1L-B selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.
Expected number of signal events after each step of the Gtt-1L-M selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.
Expected number of signal events after each step of the Gtt-1L-M selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.
Expected number of signal events after each step of the Gtt-1L-M selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.
Expected number of signal events after each step of the Gtt-1L-C selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.
Expected number of signal events after each step of the Gtt-1L-C selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.
Expected number of signal events after each step of the Gtt-1L-C selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.
Expected number of signal events after each step of the Gtt-0L-B selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.
Expected number of signal events after each step of the Gtt-0L-B selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.
Expected number of signal events after each step of the Gtt-0L-B selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.
Expected number of signal events after each step of the Gtt-0L-M selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.
Expected number of signal events after each step of the Gtt-0L-M selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.
Expected number of signal events after each step of the Gtt-0L-M selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.
Expected number of signal events after each step of the Gtt-0L-C selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.
Expected number of signal events after each step of the Gtt-0L-C selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.
Expected number of signal events after each step of the Gtt-0L-C selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.
A search for strongly produced supersymmetric particles using signatures involving multiple energetic jets and either two isolated same-sign leptons ($e$ or $\mu$), or at least three isolated leptons, is presented. The analysis relies on the identification of $b$-jets and high missing transverse momentum to achieve good sensitivity. A data sample of proton--proton collisions at $\sqrt{s}= 13$ TeV recorded with the ATLAS detector at the Large Hadron Collider in 2015 and 2016, corresponding to a total integrated luminosity of 36.1 fb$^{-1}$, is used for the search. No significant excess over the Standard Model prediction is observed. The results are interpreted in several simplified supersymmetric models featuring $R$-parity conservation or $R$-parity violation, extending the exclusion limits from previous searches. In models considering gluino pair production, gluino masses are excluded up to 1.87 TeV at 95% confidence level. When bottom squarks are pair-produced and decay to a chargino and a top quark, models with bottom squark masses below 700 GeV and light neutralinos are excluded at 95% confidence level. In addition, model-independent limits are set on a possible contribution of new phenomena to the signal region yields.
Observed 95% CL exclusion contours on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay directly into the lightest neutralino via an offshell top squark, $\tilde g\to t\bar{t}\tilde{\chi}_1^0$.
Expected 95% CL exclusion contours on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay directly into the lightest neutralino via an offshell top squark, $\tilde g\to t\bar{t}\tilde{\chi}_1^0$.
Observed 95% CL exclusion contours on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Expected 95% CL exclusion contours on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Observed 95% CL exclusion contours on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade involving sleptons, $\tilde g\to q\bar{q}\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde\ell\ell/\tilde\nu\nu$ and $\tilde\ell/\tilde\nu\to \ell/\nu\tilde{\chi}_1^0$.
Expected 95% CL exclusion contours on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade involving sleptons, $\tilde g\to q\bar{q}\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde\ell\ell/\tilde\nu\nu$ and $\tilde\ell/\tilde\nu\to \ell/\nu\tilde{\chi}_1^0$.
Observed 95% CL exclusion contours on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Expected 95% CL exclusion contours on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Observed 95% CL exclusion contours on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an antitop squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$ or $\lambda^{''}_{323}$, $\tilde g\to \bar{t}\tilde{t}_1$ followed by $\tilde{t}_1\to \bar b\bar d / \bar b \bar s$.
Expected 95% CL exclusion contours on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an antitop squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$ or $\lambda^{''}_{323}$, $\tilde g\to \bar{t}\tilde{t}_1$ followed by $\tilde{t}_1\to \bar b\bar d / \bar b \bar s$.
Observed 95% CL exclusion contours on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an antitop squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{321}$, $\lambda^{''}_{311}$ or $\lambda^{''}_{322}$, $\tilde g\to \bar{t}\tilde{t}_1$ followed by $\tilde{t}_1\to \bar s\bar d /\bar d \bar d/\bar s \bar s$.
Expected 95% CL exclusion contours on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an antitop squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{321}$, $\lambda^{''}_{311}$ or $\lambda^{''}_{322}$, $\tilde g\to \bar{t}\tilde{t}_1$ followed by $\tilde{t}_1\to \bar s\bar d /\bar d \bar d/\bar s \bar s$.
Observed 95% CL exclusion contours on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay directly into the lightest neutralino, which in turn decays via non-zero baryon- and lepton-number-violating RPV couplings $\lambda^{'}_{ijk}$, $\tilde g\to q\bar{q}\tilde{\chi}_1^0$ followed by $\tilde{\chi}_1^0\to q\bar{q}^{'}\ell$.
Expected 95% CL exclusion contours on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay directly into the lightest neutralino, which in turn decays via non-zero baryon- and lepton-number-violating RPV couplings $\lambda^{'}_{ijk}$, $\tilde g\to q\bar{q}\tilde{\chi}_1^0$ followed by $\tilde{\chi}_1^0\to q\bar{q}^{'}\ell$.
Observed 95% CL exclusion contours on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay directly into a pair of top-antitop quarks and the lightest neutralino, which in turn decays into light quarks via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{ijk}$, $\tilde g\to t\bar{t}\tilde{\chi}_1^0$ followed by $\tilde{\chi}_1^0\to qqq$.
Expected 95% CL exclusion contours on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay directly into a pair of top-antitop quarks and the lightest neutralino, which in turn decays into light quarks via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{ijk}$, $\tilde g\to t\bar{t}\tilde{\chi}_1^0$ followed by $\tilde{\chi}_1^0\to qqq$.
Observed 95% CL upper limits on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay directly into the lightest neutralino via an offshell top squark, $\tilde g\to t\bar{t}\tilde{\chi}_1^0$. The table also shows the signal acceptance and reconstruction efficiency for the signal region(s) with sensitivity to this scenario.
Observed 95% CL upper limits on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$. The table also shows the signal acceptance and reconstruction efficiency for the signal region(s) with sensitivity to this scenario.
Observed 95% CL upper limits on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade involving sleptons, $\tilde g\to q\bar{q}\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde\ell\ell/\tilde\nu\nu$ and $\tilde\ell/\tilde\nu\to \ell/\nu\tilde{\chi}_1^0$. The table also shows the signal acceptance and reconstruction efficiency for the signal region(s) with sensitivity to this scenario.
Observed 95% CL upper limits on $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The table also shows the signal acceptance and reconstruction efficiency for the signal region(s) with sensitivity to this scenario.
Observed 95% CL upper limits on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an antitop squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$ or $\lambda^{''}_{323}$, $\tilde g\to \bar{t}\tilde{t}_1$ followed by $\tilde{t}_1\to \bar b\bar d / \bar b \bar s$. The table also shows the signal acceptance and reconstruction efficiency for the signal region(s) with sensitivity to this scenario.
Observed 95% CL upper limits on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an antitop squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{321}$, $\lambda^{''}_{311}$ or $\lambda^{''}_{322}$, $\tilde g\to \bar{t}\tilde{t}_1$ followed by $\tilde{t}_1\to \bar s\bar d /\bar d \bar d/\bar s \bar s$. The table also shows the signal acceptance and reconstruction efficiency for the signal region(s) with sensitivity to this scenario.
Observed 95% CL upper limits on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay directly into the lightest neutralino, which in turn decays via non-zero baryon- and lepton-number-violating RPV couplings $\lambda^{'}_{ijk}$, $\tilde g\to q\bar{q}\tilde{\chi}_1^0$ followed by $\tilde{\chi}_1^0\to q\bar{q}^{'}\ell$. The table also shows the signal acceptance and reconstruction efficiency for the signal region(s) with sensitivity to this scenario.
Observed 95% CL upper limits on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay directly into a pair of top-antitop quarks and the lightest neutralino, which in turn decays into light quarks via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{ijk}$, $\tilde g\to t\bar{t}\tilde{\chi}_1^0$ followed by $\tilde{\chi}_1^0\to qqq$. The table also shows the signal acceptance and reconstruction efficiency for the signal region(s) with sensitivity to this scenario.
Observed and expected 95% CL upper limits on $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate. The table also shows the signal acceptance and reconstruction efficiency for the signal region(s) with sensitivity to this scenario.
Observed and expected 95% CL upper limits on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario with non-universal Higgs masses (NUHM2, see the publication Refs. [31-32]). The table also shows the signal acceptance and reconstruction efficiency for the signal region(s) with sensitivity to this scenario.
Observed and expected 95% CL upper limits on $pp\to \tilde{d}^{}_\mathrm{R}\tilde{d}^{*}_\mathrm{R}$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an antitop squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$ or $\lambda^{''}_{323}$, $\tilde g\to \bar{t}\tilde{t}_1$ followed by $\tilde{t}_1\to \bar b\bar d / \bar b \bar s$. The table also shows the signal acceptance and reconstruction efficiency for the signal region(s) with sensitivity to this scenario.
Observed and expected 95% CL upper limits on $pp\to \tilde{d}^{}_\mathrm{R}\tilde{d}^{*}_\mathrm{R}$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an antitop squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{321}$, $\lambda^{''}_{311}$ or $\lambda^{''}_{322}$, $\tilde g\to \bar{t}\tilde{t}_1$ followed by $\tilde{t}_1\to \bar s\bar d /\bar d \bar d/\bar s \bar s$. The table also shows the signal acceptance and reconstruction efficiency for the signal region(s) with sensitivity to this scenario.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L2bS, in a SUSY scenario where gluinos are produced in pairs and decay directly into the lightest neutralino via an offshell top squark, $\tilde g\to t\bar{t}\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1500 GeV and $m(\tilde \chi_1^0)$ = 800 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L2bH, in a SUSY scenario where gluinos are produced in pairs and decay directly into the lightest neutralino via an offshell top squark, $\tilde g\to t\bar{t}\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1700 GeV and $m(\tilde \chi_1^0)$ = 200 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2Lsoft1b, in a SUSY scenario where gluinos are produced in pairs and decay directly into the lightest neutralino via offshell top squark and top quark, $\tilde g\to t\bar{b}W^{-}\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1200 GeV and $m(\tilde \chi_1^0)$ = 940 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2Lsoft2b, in a SUSY scenario where gluinos are produced in pairs and decay directly into the lightest neutralino via offshell top squark and top quark, $\tilde g\to t\bar{b}W^{-}\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1200 GeV and $m(\tilde \chi_1^0)$ = 900 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L0bS, in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1200 GeV, $m(\tilde \chi_1^\pm)$ = 1050 GeV, $m(\tilde \chi_2^0)$ = 975 GeV and $m(\tilde \chi_1^0)$ = 900 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L0bH, in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde \chi_1^\pm)$ = 850 GeV, $m(\tilde \chi_2^0)$ = 475 GeV and $m(\tilde \chi_1^0)$ = 100 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region Rpc3L0bS, in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade involving sleptons, $\tilde g\to q\bar{q}\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde\ell\ell/\tilde\nu\nu$ and $\tilde\ell/\tilde\nu\to \ell/\nu\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1400 GeV, $m(\tilde \chi_2^0)$ = 1250 GeV, $m(\tilde\ell)=m(\tilde\nu)$ = 1175 GeV and $m(\tilde \chi_1^0)$ = 1100 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region Rpc3L0bH, in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade involving sleptons, $\tilde g\to q\bar{q}\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde\ell\ell/\tilde\nu\nu$ and $\tilde\ell/\tilde\nu\to \ell/\nu\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1800 GeV, $m(\tilde \chi_2^0)$ = 950 GeV, $m(\tilde\ell)=m(\tilde\nu)$ = 475 GeV and $m(\tilde \chi_1^0)$ = 100 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L1bS, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 600 GeV, $m(\tilde \chi_1^\pm)$ = 350 GeV and $m(\tilde \chi_1^0)$ = 250 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L1bH, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 750 GeV, $m(\tilde \chi_1^\pm)$ = 200 GeV and $m(\tilde \chi_1^0)$ = 100 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region Rpc3LSS1b, in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate. The masses of the superpartners involved in the process are set to $m(\tilde{t}^{}_1)$ = 700 GeV, $m(\tilde \chi_2^0)$ = 525 GeV, $m(\tilde \chi_1^\pm)\approx m(\tilde \chi_1^0)$ = 425 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region Rpv2L1bH, in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an antitop squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{321}$, $\lambda^{''}_{311}$ or $\lambda^{''}_{322}$, $\tilde g\to \bar{t}\tilde{t}_1$ followed by $\tilde{t}_1\to \bar s\bar d /\bar d \bar d/\bar s \bar s$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1400 GeV, $m(\tilde{t}^{}_{1})$ = 800 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region Rpv2L0b, in a SUSY scenario where gluinos are produced in pairs and decay directly into the lightest neutralino, which in turn decays via non-zero baryon- and lepton-number-violating RPV couplings $\lambda^{'}_{ijk}$, $\tilde g\to q\bar{q}\tilde{\chi}_1^0$ followed by $\tilde{\chi}_1^0\to q\bar{q}^{'}\ell$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1400 GeV, $m(\tilde{\chi}_1^0)$ = 500 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region Rpv2L2bH, in a SUSY scenario where gluinos are produced in pairs and decay directly into a pair of top-antitop quarks and the lightest neutralino, which in turn decays into light quarks via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{ijk}$, $\tilde g\to t\bar{t}\tilde{\chi}_1^0$ followed by $\tilde{\chi}_1^0\to qqq$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1800 GeV, $m(\tilde{\chi}_1^0)$ = 200 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region Rpv2L2bS, in a SUSY scenario where pairs of down-down squark-rights are produced and decay into a pair of top and bottom quarks via a non-zero baryon-number-violating RPV coupling $\lambda^{''}_{331}$, $\tilde{d}^{}_\mathrm{R}\to \bar t\bar b$. The masses of the superpartners involved in the process are set to $m(\tilde{d}^{}_\mathrm{R})$ = 600 GeV, $m(\tilde g)$ = 2000 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region Rpv2L1bS, in a SUSY scenario where pairs of down-down squarks are produced and decay into a pair of top and a light quarks via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{321}$ or $\lambda^{''}_{322}$, $\tilde{d}^{}_\mathrm{R}\to \bar t\bar s/\bar t\bar d$. The masses of the superpartners involved in the process are set to $m(\tilde{d}^{}_\mathrm{R})$ = 600 GeV, $m(\tilde g)$ = 2000 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region Rpv2L1bM, in a SUSY scenario where pairs of down-down squarks are produced and decay into a pair of top and a light quarks via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{321}$ or $\lambda^{''}_{322}$, $\tilde{d}^{}_\mathrm{R}\to \bar t\bar s/\bar t\bar d$. The masses of the superpartners involved in the process are set to $m(\tilde{d}^{}_\mathrm{R})$ = 1000 GeV, $m(\tilde g)$ = 2000 GeV. Only statistical uncertainties are shown.
This paper presents a search for direct electroweak gaugino or gluino pair production with a chargino nearly mass-degenerate with a stable neutralino. It is based on an integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ of $pp$ collisions at $\sqrt{s} = 13$ TeV collected by the ATLAS experiment at the LHC. The final state of interest is a disappearing track accompanied by at least one jet with high transverse momentum from initial-state radiation or by four jets from the gluino decay chain. The use of short track segments reconstructed from the innermost tracking layers significantly improves the sensitivity to short chargino lifetimes. The results are found to be consistent with Standard Model predictions. Exclusion limits are set at 95% confidence level on the mass of charginos and gluinos for different chargino lifetimes. For a pure wino with a lifetime of about 0.2 ns, chargino masses up to 460 GeV are excluded. For the strong production channel, gluino masses up to 1.65 TeV are excluded assuming a chargino mass of 460 GeV and lifetime of 0.2 ns.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the high-Emiss region.
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Model dependent upper limits on cross-section (fb) for the electroweak production are shown by grey numbers in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Model dependent upper limits on cross-section (pb) for the electroweak production are shown by grey numbers in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Model dependent upper limits on cross-section (pb) for the electroweak production are shown by grey numbers in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Model dependent upper limits on cross-section (pb) for the electroweak production are shown by grey numbers in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Total acceptance $\times$ efficiency of the electroweak channel. The total signal acceptance $\times$ efficiency is defined as the probability of an event passing the signal region selection when an electroweak gaugino pair is produced in a pp collision.
Total acceptance $\times$ efficiency of the electroweak channel. The total signal acceptance $\times$ efficiency is defined as the probability of an event passing the signal region selection when an electroweak gaugino pair is produced in a pp collision.
Total acceptance $\times$ efficiency of the electroweak channel. The total signal acceptance $\times$ efficiency is defined as the probability of an event passing the signal region selection when an electroweak gaugino pair is produced in a pp collision.
Total acceptance $\times$ efficiency of the electroweak channel. The total signal acceptance $\times$ efficiency is defined as the probability of an event passing the signal region selection when an electroweak gaugino pair is produced in a pp collision.
Total acceptance $\times$ efficiency of the strong channel. In white regions, no simulation sample is available. The left-upper triangle region is not allowed kinematically in wino-LSP scenarios. The total signal acceptance $\times$ efficiency is calculated relative to events in which the gluinos decay into electroweak gaugino pairs.
Total acceptance $\times$ efficiency of the strong channel. In white regions, no simulation sample is available. The left-upper triangle region is not allowed kinematically in wino-LSP scenarios. The total signal acceptance $\times$ efficiency is calculated relative to events in which the gluinos decay into electroweak gaugino pairs.
Total acceptance $\times$ efficiency of the strong channel. In white regions, no simulation sample is available. The left-upper triangle region is not allowed kinematically in wino-LSP scenarios. The total signal acceptance $\times$ efficiency is calculated relative to events in which the gluinos decay into electroweak gaugino pairs.
Total acceptance $\times$ efficiency of the strong channel. In white regions, no simulation sample is available. The left-upper triangle region is not allowed kinematically in wino-LSP scenarios. The total signal acceptance $\times$ efficiency is calculated relative to events in which the gluinos decay into electroweak gaugino pairs.
The generator-level acceptance after reconstruction, for selecting and reconstructing charginos as a function of the chargino $eta$ and chargino decay radius (at generator level).
The generator-level acceptance for charginos produced in the electroweak channel as a function of the chargino $eta$ and chargino decay radius (at generator level).
The generator-level acceptance for charginos produced in the electroweak channel as a function of the chargino $eta$ and chargino decay radius (at generator level).
The generator-level acceptance for charginos produced in the electroweak channel as a function of the chargino $eta$ and chargino decay radius (at generator level).
The generator-level acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
The acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos produced in the electroweak channel as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
The acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos produced in the electroweak channel as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
The acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos produced in the electroweak channel as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
The generator-level acceptance after reconstruction, for selecting and reconstructing charginos as a function of the chargino $\eta$ and chargino decay radius (at generator level).
The generator-level acceptance for charginos produced in the strong channel as a function of the chargino $\eta$ and chargino decay radius (at generator level).
The generator-level acceptance for charginos produced in the strong channel as a function of the chargino $\eta$ and chargino decay radius (at generator level).
The generator-level acceptance for charginos produced in the strong channel as a function of the chargino $\eta$ and chargino decay radius (at generator level).
The generator-level acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
The acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos produced in the strong channel as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
The acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos produced in the strong channel as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
The acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos produced in the strong channel as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in direct electroweak production with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in direct electroweak production with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in direct electroweak production with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in direct electroweak production with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in the strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in the strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in the strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in the strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
The event and tracklet generator-level acceptance and selection efficiency for a few electroweak signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
The event and tracklet generator-level acceptance and selection efficiency for a few electroweak signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
The event and tracklet generator-level acceptance and selection efficiency for a few electroweak signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
The event and tracklet generator-level acceptance and selection efficiency for a few electroweak signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
The event and tracklet generator-level acceptance and selection efficiency for a few strong signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
The event and tracklet generator-level acceptance and selection efficiency for a few strong signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
The event and tracklet generator-level acceptance and selection efficiency for a few strong signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
The event and tracklet generator-level acceptance and selection efficiency for a few strong signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
Systematic uncertainties in the signal event yields at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. The uncertainty in the cross-section of the strong production is large due to the large effect from the PDF uncertainty.
Systematic uncertainties in the signal event yields at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. The uncertainty in the cross-section of the strong production is large due to the large effect from the PDF uncertainty.
Systematic uncertainties in the signal event yields at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. The uncertainty in the cross-section of the strong production is large due to the large effect from the PDF uncertainty.
Systematic uncertainties in the signal event yields at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. The uncertainty in the cross-section of the strong production is large due to the large effect from the PDF uncertainty.
Observed events, expected background for null signal, and expected signal yields for two benchmark models: electroweak channel with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) and strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. Also shown are the probability of a background-only experiment being more signal-like than observed ($p_0$) and the upper limit on the model-independent visible cross-section at 95\% CL. The uncertainty in the total background yield is different from the sum of uncertainties in quadrature due to anticorrelation between different backgrounds.
Observed events, expected background for null signal, and expected signal yields for two benchmark models: electroweak channel with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) and strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. Also shown are the probability of a background-only experiment being more signal-like than observed ($p_0$) and the upper limit on the model-independent visible cross-section at 95\% CL. The uncertainty in the total background yield is different from the sum of uncertainties in quadrature due to anti-correlation between different backgrounds.
Observed events, expected background for null signal, and expected signal yields for two benchmark models: electroweak channel with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) and strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. Also shown are the probability of a background-only experiment being more signal-like than observed ($p_0$) and the upper limit on the model-independent visible cross-section at 95\% CL. The uncertainty in the total background yield is different from the sum of uncertainties in quadrature due to anti-correlation between different backgrounds.
Observed events, expected background for null signal, and expected signal yields for two benchmark models: electroweak channel with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) and strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. Also shown are the probability of a background-only experiment being more signal-like than observed ($p_0$) and the upper limit on the model-independent visible cross-section at 95\% CL. The uncertainty in the total background yield is different from the sum of uncertainties in quadrature due to anti-correlation between different backgrounds.
Effects of systematic uncertainties on the signal exclusion significance at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. Effects of uncertainties on the fake-tracklet background is smaller in the strong channel analysis because the estimated number of the fake-tracket background events is small.
Effects of systematic uncertainties on the signal exclusion significance at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. Effects of uncertainties on the fake-tracklet background is smaller in the strong channel analysis because the estimated number of the fake-tracklet background events is small.
Effects of systematic uncertainties on the signal exclusion significance at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. Effects of uncertainties on the fake-tracklet background is smaller in the strong channel analysis because the estimated number of the fake-tracklet background events is small.
Effects of systematic uncertainties on the signal exclusion significance at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. Effects of uncertainties on the fake-tracklet background is smaller in the strong channel analysis because the estimated number of the fake-tracklet background events is small.
Cross-section upper limits for the strong production, presented in unit of fb. Left-upper triangle region is unphysical because the wino mass is larger than the gluino mass.
Cross-section upper limits for the strong production, presented in unit of fb. Left-upper triangle region is unphysical because the wino mass is larger than the gluino mass.
Cross-section upper limits for the strong production, presented in unit of fb. Left-upper triangle region is unphysical because the wino mass is larger than the gluino mass.
Cross-section upper limits for the strong production, presented in unit of fb. Left-upper triangle region is unphysical because the wino mass is larger than the gluino mass.
A search for the supersymmetric partners of quarks and gluons (squarks and gluinos) in final states containing hadronic jets and missing transverse momentum, but no electrons or muons, is presented. The data used in this search were recorded in 2015 and 2016 by the ATLAS experiment in $\sqrt{s}$=13 TeV proton--proton collisions at the Large Hadron Collider, corresponding to an integrated luminosity of 36.1 fb$^{-1}$. The results are interpreted in the context of various models where squarks and gluinos are pair-produced 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 2.03 TeV for a simplified model incorporating only a gluino 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 1.55 TeV are excluded if the lightest neutralino is massless. These limits substantially extend the region of supersymmetric parameter space previously excluded by searches with the ATLAS detector.
A search for new phenomena in final states characterized by high jet multiplicity, an isolated lepton (electron or muon) and either zero or at least three $b$-tagged jets is presented. The search uses 36.1 fb$^{-1}$ of $\sqrt{s}$ = 13 TeV proton-proton collision data collected by the ATLAS experiment at the Large Hadron Collider in 2015 and 2016. The dominant sources of background are estimated using parameterized extrapolations, based on observables at medium jet multiplicity, to predict the $b$-tagged jet multiplicity distribution at the higher jet multiplicities used in the search. No significant excess over the Standard Model expectation is observed and 95% confidence-level limits are extracted constraining four simplified models of $R$-parity-violating supersymmetry that feature either gluino or top-squark pair production. The exclusion limits reach as high as 2.1 TeV in gluino mass and 1.2 TeV in top-squark mass in the models considered. In addition, an upper limit is set on the cross-section for Standard Model $t\bar{t}t\bar{t}$ production of 60 fb (6.5 $\times$ the Standard Model prediction) at 95% confidence level. Finally, model-independent limits are set on the contribution from new phenomena to the signal-region yields.
The expected background and observed data with five jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with five jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with six jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with six jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with seven jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with seven jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with eight jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with eight jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with nine jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with nine jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with ten jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with ten jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with eleven jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with eleven jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with twelve-or-more jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with twelve-or-more jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with five jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with five jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with six jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with six jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with seven jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with seven jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with eight jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with eight jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with nine jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with nine jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with ten-or-more jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with ten-or-more jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with five jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with five jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with six jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with six jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with seven jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with seven jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with eight jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with eight jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with nine jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with nine jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with ten-or-more jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with ten-or-more jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
Observed exclusion contours on the gluino and neutralino masses in a model where the gluino decays via a virtual top squark to two top quarks and the lightest neutralino, with the neutralino decaying to three light quarks (neutralino --> uds) via the RPV coupling lambda''_112.
Observed exclusion contours on the gluino and neutralino masses in a model where the gluino decays via a virtual top squark to two top quarks and the lightest neutralino, with the neutralino decaying to three light quarks (neutralino --> uds) via the RPV coupling lambda''_112.
Expected exclusion contours on the gluino and neutralino masses in a model where the gluino decays via a virtual top squark to two top quarks and the lightest neutralino, with the neutralino decaying to three light quarks (neutralino --> uds) via the RPV coupling lambda''_112.
Expected exclusion contours on the gluino and neutralino masses in a model where the gluino decays via a virtual top squark to two top quarks and the lightest neutralino, with the neutralino decaying to three light quarks (neutralino --> uds) via the RPV coupling lambda''_112.
Observed exclusion contours on the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.
Observed exclusion contours on the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.
Expected exclusion contours on the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.
Expected exclusion contours on the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.
Observed exclusion contours on the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.
Observed exclusion contours on the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.
Expected exclusion contours on the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.
Expected exclusion contours on the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.
Observed exclusion contours on the stop and neutralino masses in a model where the stop decays to a third-generation quark and a higgsino, which decays via the RPV coupling lambda''_323.
Observed exclusion contours on the stop and neutralino masses in a model where the stop decays to a third-generation quark and a higgsino, which decays via the RPV coupling lambda''_323.
Expected exclusion contours on the stop and neutralino masses in a model where the stop decays to a third-generation quark and a higgsino, which decays via the RPV coupling lambda''_323.
Expected exclusion contours on the stop and neutralino masses in a model where the stop decays to a third-generation quark and a higgsino, which decays via the RPV coupling lambda''_323.
Observed exclusion contours on the stop and neutralino masses in a model where the stop decays to a top and a bino-like neutralino, which decays via the RPV coupling lambda''_323.
Observed exclusion contours on the stop and neutralino masses in a model where the stop decays to a top and a bino-like neutralino, which decays via the RPV coupling lambda''_323.
Expected exclusion contours on the stop and neutralino masses in a model where the stop decays to a top and a bino-like neutralino, which decays via the RPV coupling lambda''_323.
Expected exclusion contours on the stop and neutralino masses in a model where the stop decays to a top and a bino-like neutralino, which decays via the RPV coupling lambda''_323.
Observed upper limits on the model cross-section in units of pb as a function of the gluino and neutralino masses in a model where the gluino decays via a virtual top squark to two top quarks and the lightest neutralino, with the neutralino decaying to three light quarks (neutralino --> uds) via the RPV coupling lambda''_112.
Observed upper limits on the model cross-section in units of pb as a function of the gluino and neutralino masses in a model where the gluino decays via a virtual top squark to two top quarks and the lightest neutralino, with the neutralino decaying to three light quarks (neutralino --> uds) via the RPV coupling lambda''_112.
Observed upper limits on the model cross-section in units of pb as a function of the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.
Observed upper limits on the model cross-section in units of pb as a function of the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.
Observed upper limits on the model cross-section in units of pb as a function of the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.
Observed upper limits on the model cross-section in units of pb as a function of the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.
Observed upper limits on the model cross-section in units of pb as a function of the stop and neutralino masses in a model where the stop decays to a third-generation quark and a higgsino, which decays via the RPV coupling lambda''_323.
Observed upper limits on the model cross-section in units of pb as a function of the stop and neutralino masses in a model where the stop decays to a third-generation quark and a higgsino, which decays via the RPV coupling lambda''_323.
Observed upper limits on the model cross-section in units of pb as a function of the stop and neutralino masses in a model where the stop decays to a top and a bino-like neutralino, which decays via the RPV coupling lambda''_323.
Observed upper limits on the model cross-section in units of pb as a function of the stop and neutralino masses in a model where the stop decays to a top and a bino-like neutralino, which decays via the RPV coupling lambda''_323.
Acceptance as a function of the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.
Acceptance as a function of the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.
Efficiency as a function of the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.
Efficiency as a function of the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.
Acceptance as a function of the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.
Acceptance as a function of the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.
Efficiency as a function of the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.
Efficiency as a function of the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.
Cut flow for a model of gluino pair production where the gluino decays to two (u, d, s, c) quarks and the neutralino, which then decays to two (u, d, s, c) quarks and a lepton via a lambda' RPV coupling, where each RPV decay can produce any of the four first and second generation leptons (e, mu, nu_e, nu_mu) with equal probability (m_gluino = 1800 GeV, m_neutralino = 900 GeV). The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies pT > 25 GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed.
Cut flow for a model of gluino pair production where the gluino decays to two (u, d, s, c) quarks and the neutralino, which then decays to two (u, d, s, c) quarks and a lepton via a lambda' RPV coupling, where each RPV decay can produce any of the four first and second generation leptons (e, mu, nu_e, nu_mu) with equal probability (m_gluino = 1800 GeV, m_neutralino = 900 GeV). The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies pT > 25 GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed.
Cut flow for a model of gluino pair production where each gluino decays to a top quark and a top squark, with the top squark decaying to an s- and a b- quark via a non-zero lambda''_323 RPV coupling (m_gluino = 1600 GeV, m_stop = 1000 GeV). The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies pT > 25 GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed.
Cut flow for a model of gluino pair production where each gluino decays to a top quark and a top squark, with the top squark decaying to an s- and a b- quark via a non-zero lambda''_323 RPV coupling (m_gluino = 1600 GeV, m_stop = 1000 GeV). The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies pT > 25 GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed.
Cut flow for a model of gluino pair production where each gluino decays via an off-shell top squark to two top quarks and the lightest neutralino, with the neutralino decaying to three light quarks (neutralino -> uds) via the RPV coupling lambda''_112 (m_gluino = 2000 GeV, m_neutralino = 941 GeV). The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies pT > 25 GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed.
Cut flow for a model of gluino pair production where each gluino decays via an off-shell top squark to two top quarks and the lightest neutralino, with the neutralino decaying to three light quarks (neutralino -> uds) via the RPV coupling lambda''_112 (m_gluino = 2000 GeV, m_neutralino = 941 GeV). The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies pT > 25 GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed.
Cut flow for a model of right-handed top squark pair production with the top squark decaying to the lightest supersymmetric particle (LSP) which is considered to be purely higgsino. The higgsino-like LSP decays through the non-zero RPV coupling lambda''_323 (m_stop = 975 GeV, m_neutralino = 600 GeV). The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies pT > 25 GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed.
Cut flow for a model of right-handed top squark pair production with the top squark decaying to the lightest supersymmetric particle (LSP) which is considered to be purely higgsino. The higgsino-like LSP decays through the non-zero RPV coupling lambda''_323 (m_stop = 975 GeV, m_neutralino = 600 GeV). The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies pT > 25 GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed.
Two searches for supersymmetric particles in final states containing a same-flavour opposite-sign lepton pair, jets and large missing transverse momentum are presented. The proton-proton collision data used in these searches were collected at a centre-of-mass energy $\sqrt{s}=8$ TeV by the ATLAS detector at the Large Hadron Collider and corresponds to an integrated luminosity of 20.3 fb$^{-1}$. Two leptonic production mechanisms are considered: decays of squarks and gluinos with $Z$ bosons in the final state, resulting in a peak in the dilepton invariant mass distribution around the $Z$-boson mass; and decays of neutralinos (e.g. $\tilde{\chi}^{0}_{2} \rightarrow \ell^{+}\ell^{-}\tilde{\chi}^{0}_{1}$), resulting in a kinematic endpoint in the dilepton invariant mass distribution. For the former, an excess of events above the expected Standard Model background is observed, with a significance of 3 standard deviations. In the latter case, the data are well-described by the expected Standard Model background. The results from each channel are interpreted in the context of several supersymmetric models involving the production of squarks and gluinos.
The observed and expected dielectron invariant mass distribution in SR-Z. The negigible estimated contribution from Z+jets is omitted in these distributions.
The observed and expected dimuon invariant mass distribution in SR-Z. The negigible estimated contribution from Z+jets is omitted in these distributions.
The observed and expected $E_T^{miss}$ distribution in the dielectron SR-Z. The negigible estimated contribution from Z+jets is omitted in these distributions. The last bin contains the overflow.
The observed and expected $E_T^{miss}$ distribution in the dimuon SR-Z. The negigible estimated contribution from Z+jets is omitted in these distributions. The last bin contains the overflow.
The observed and expected dielectron invariant mass distribution in SR-loose. The last bin contains the overflow.
The observed and expected dimuon invariant mass distribution in SR-loose. The last bin contains the overflow.
The observed and expected dielectron invariant mass distribution in the two-jet $b$-veto SR. The last bin contains the overflow.
The observed and expected dimuon invariant mass distribution in the two-jet $b$-veto SR. The last bin contains the overflow.
The observed and expected dielectron invariant mass distribution in the four jet b-veto SR. The last bin contains the overflow.
The observed and expected dimuon invariant mass distribution in the four-jet $b$-veto SR. The last bin contains the overflow.
The observed and expected dielectron invariant mass distribution in the two-jet $b$-tag SR. The last bin contains the overflow.
The observed and expected dimuon invariant mass distribution in two-jet $b$-tag SR. The last bin contains the overflow.
The observed and expected dielectron invariant mass distribution in the four-jet $b$-tag SR. The last bin contains the overflow.
The observed and expected dimuon invariant mass distribution in the four-jet $b$-tag SR. The last bin contains the overflow.
Expected 95% exclusion contour for the GGM model with $\tan(\beta)=1.5$ in SR-Z.
Observed 95% exclusion contour for the GGM model with $\tan(\beta)=1.5$ in SR-Z.
Expected 95% exclusion contour for the GGM model with $\tan(\beta)=30$ in SR-Z.
Observed 95% exclusion contour for the GGM model with $\tan(\beta)=30$ in SR-Z.
Expected 95% exclusion contour for the two-step first- and second-generation squark simplified model with sleptons in the two-jet $b$-veto SR.
Observed 95% exclusion contour for the two-step first- and second-generation squark simplified model with sleptons in the two-jet $b$-veto SR.
Expected 95% exclusion contour for the two-step gluino simplified model with sleptons in the four-jet $b$-veto SR.
Observed 95% exclusion contour for the two-step gluino simplified model with sleptons in the four-jet $b$-veto SR.
Number of generated events in the two-step gluino simplified model with sleptons.
Production cross-section in the two-step gluino simplified model with sleptons.
Number of generated events in the two-step first- and second-generation squark simplified model with sleptons.
Production cross-section in the two-step first- and second-generation squark simplified model with sleptons.
Number of generated events in the GGM model with $\tan(\beta)=1.5$.
Production cross-section in the GGM model with $\tan(\beta)=1.5$.
Number of generated events in the GGM model with $\tan(\beta)=30$.
Production cross-section in the GGM model with $\tan(\beta)=30$.
Total experimental uncertainty [%] for the two-step gluino simplified model with sleptons.
Total experimental uncertainty [%] for the GGM model with $\tan(\beta)=1.5$.
Total experimental uncertainty for the GGM model with $\tan(\beta)=30$.
Signal acceptance for the GGM model with $\tan(\beta)=1.5$ in the combined electron and muon SR-Z.
Signal acceptance for the GGM model with $\tan(\beta)=30$ in the combined electron and muon SR-Z.
Signal efficiency for the GGM model with $\tan(\beta)=1.5$ in the dielectron SR-Z.
Signal efficiency for the GGM model with $\tan(\beta)=30$ in the dielectron SR-Z.
Signal efficiency for the GGM model with $\tan(\beta)=1.5$ in the dimuon SR-Z.
Signal efficiency for the GGM model with $\tan(\beta)=30$ in the dimuon SR-Z.
Signal efficiency for the GGM model with $\tan(\beta)=1.5$ in the electron and muon combined SR-Z.
Signal efficiency for the GGM model with $\tan(\beta)=30$ in the the electron and muon combined SR-Z.
Signal acceptance for the two-step first- and second-generation squarks simplified model with sleptons in the two-jet $b$-veto SR.
Signal acceptance for the two-step gluino simplified model with sleptons in the four-jet $b$-veto SR.
Signal efficiency for the two-step first- and second-generation squarks simplified model with sleptons in the two-jet $b$-veto SR.
Signal efficiency for the two-step gluino simplified model with sleptons in the four-jet $b$-veto SR.
Upper limits on the signal cross-section at 95% CL for the GGM model with $\tan(\beta)=1.5$.
Observed CL$_{\text{S}}$ for the GGM model with $\tan(\beta)=1.5$.
Expected CL$_{\text{S}}$ for the GGM model with $\tan(\beta)=1.5$.
Upper limits on the signal cross-section at 95% CL for the GGM model with $\tan(\beta)=30$.
Observed CL$_{\text{S}}$ for the GGM model with $\tan(\beta)=30$.
Expected CL$_{\text{S}}$ for the GGM model with $\tan(\beta)=30$.
Upper limits on the signal stength at 95% CL for the two-step first- and second-generation squark simplified model with sleptons. The excluded signal strength is defined as the ratio of the observed excluded production cross section to the expected production cross section calculated at NLO+NLL.
Upper limits on the signal stength at 95% CL for the two-step gluino simplified model with sleptons. The excluded signal strength is defined as the ratio of the observed excluded production cross section to the expected production cross section calculated at NLO+NLL.
Observed CL$_{\text{S}}$ for the two-step first- and second-generation squark simplified model with sleptons.
Expected CL$_{\text{S}}$ for the two-step first- and second-generation squark simplified model with sleptons.
Observed CL$_{\text{S}}$ for the two-step gluino simplified model with sleptons.
Expected CL$_{\text{S}}$ for the two-step gluino simplified model with sleptons.
Cutflow table for three benchmark signal points in SR-Z for the $ee$ and $\mu\mu$ channels separately. The three signal points are taken from the $\tan\beta = 1.5$ grid. 100000 events were generated for each of these points. Shown here are both the unweighted number of events and the number of events normalised to 20.3 fb$^{-1}$. The total experimental systematic uncertainty on the signal yields is indicated at the last cut, along with the corresponding observed and expected $CL_S$ values.
Cutflow table for three benchmark signal points in the two jet b-veto SR of the off-$Z$ search for the $ee$ and $\mu\mu$ channels separately. Shown here are both the unweighted number of events and the number of events normalised to 20.3$^{-1}$. Except for the last two rows indicating the dilepton mass requirements, quoted event yields include all requirements from the top of the table down to the given row.
Cutflow table for three benchmark signal points in the four jet b-veto SR of the off-$Z$ search for the $ee$ and $\mu\mu$ channels separately. Shown here are both the unweighted number of events and the number of events normalised to 20.3 fb$^{-1}$. Except for the last two rows indicating the dilepton mass requirements, quoted event yields include all requirements from the top of the table down to the given row.
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