Showing 10 of 18 results
A search for Supersymmetry involving the pair production of gluinos decaying via third-generation squarks to the lightest neutralino is reported. It uses an LHC proton--proton dataset at a center-of-mass energy $\sqrt{s} = 13$ TeV with an integrated luminosity of 3.2 fb$^{-1}$ collected with the ATLAS detector in 2015. The signal is searched for in events containing several energetic jets, of which at least three must be identified as $b$-jets, large missing transverse momentum and, potentially, isolated electrons or muons. Large-radius jets with a high mass are also used to identify highly boosted top quarks. No excess is found above the predicted background. For neutralino masses below approximately 700 GeV, gluino masses of less than 1.78 TeV and 1.76 TeV are excluded at the 95% CL in simplified models of the pair production of gluinos decaying via sbottom and stop, respectively. These results significantly extend the exclusion limits obtained with the $\sqrt{s} = 8$ TeV dataset.
Distribution of missing transverse energy for SR-Gbb-B.
Distribution of missing transverse energy for SR-Gtt-0L-C.
Distribution of missing transverse energy for SR-Gtt-1L-A.
Expected 95% CL exclusion contour for the Gbb signal.
Observed 95% CL exclusion contour for the Gbb signal.
Expected 95% CL exclusion contour for the Gtt combination.
Observed 95% CL exclusion contour for the Gtt combination.
Acceptances for the Gbb model in SR-Gbb-A. Acceptance is evaluated at truth level, with only leptons from heavy bosons and taus considered, and no further quality or isolation criteria applied in their selection.
Acceptances for the Gbb model in SR-Gbb-B. Acceptance is evaluated at truth level, with only leptons from heavy bosons and taus considered, and no further quality or isolation criteria applied in their selection.
Acceptances for the Gbb model in SR-Gbb-C. Acceptance is evaluated at truth level, with only leptons from heavy bosons and taus considered, and no further quality or isolation criteria applied in their selection.
Acceptances for the Gtt model in SR-Gtt-0L-A. Acceptance is evaluated at truth level, with only leptons from heavy bosons and taus considered, and no further quality or isolation criteria applied in their selection.
Acceptances for the Gtt model in SR-Gtt-0L-B. Acceptance is evaluated at truth level, with only leptons from heavy bosons and taus considered, and no further quality or isolation criteria applied in their selection.
Acceptances for the Gtt model in SR-Gtt-0L-C. Acceptance is evaluated at truth level, with only leptons from heavy bosons and taus considered, and no further quality or isolation criteria applied in their selection.
Acceptances for the Gtt model in SR-Gtt-1L-A. Acceptance is evaluated at truth level, with only leptons from heavy bosons and taus considered, and no further quality or isolation criteria applied in their selection.
Acceptances for the Gtt model in SR-Gtt-1L-B. Acceptance is evaluated at truth level, with only leptons from heavy bosons and taus considered, and no further quality or isolation criteria applied in their selection.
Acceptance times efficiency for the Gbb model in SR-Gbb-A.
Acceptance times efficiency for the Gbb model in SR-Gbb-B.
Acceptance times efficiency for the Gbb model in SR-Gbb-C.
Acceptance times efficiency for the Gtt model in SR-Gtt-0L-A.
Acceptance times efficiency for the Gtt model in SR-Gtt-0L-B.
Acceptance times efficiency for the Gtt model in SR-Gtt-0L-C.
Acceptance times efficiency for the Gtt model in SR-Gtt-1L-A.
Acceptance times efficiency for the Gtt model in SR-Gtt-1L-B.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gbb model in SR-Gbb-A.
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-C.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-0L-A.
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-C.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-1L-A.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-1L-B.
Signal region yielding the best expected sensitivity for each point of the parameter space in the Gbb model.
Signal region yielding the best expected sensitivity for each point of the parameter space in the Gtt model for the 0-lepton channel.
Signal region yielding the best expected sensitivity for each point of the parameter space in the Gtt model for the 1-lepton channel.
Combination of two 0-lepton and 1-lepton signal regions yielding the best expected sensitivity for each point of the parameter space in the Gtt model.
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 for strongly produced supersymmetric particles is conducted using signatures involving multiple energetic jets and either two isolated leptons ($e$ or $\mu$) with the same electric charge or at least three isolated leptons. The search also utilises $b$-tagged jets, missing transverse momentum and other observables to extend its sensitivity. The analysis uses a data sample of proton-proton collisions at $\sqrt{s}=13$ TeV recorded with the ATLAS detector at the Large Hadron Collider in 2015 corresponding to a total integrated luminosity of 3.2 fb$^{-1}$. No significant excess over the Standard Model expectation is observed. The results are interpreted in several simplified supersymmetric models and extend the exclusion limits from previous searches. In the context of exclusive production and simplified decay modes, gluino masses are excluded at 95% confidence level up to 1.1-1.3 TeV for light neutralinos (depending on the decay channel), and bottom squark masses are also excluded up to 540 GeV. In the former scenarios, neutralino masses are also excluded up to 550-850 GeV for gluino masses around 1 TeV.
Missing transverse momentum distribution after SR0b3j selection, beside the $E_\mathrm{T}^\mathrm{miss}$ requirement. The results in the signal region correspond to the last inclusive bin. The systematic uncertainties include theory uncertainties for the backgrounds with prompt SS/3L and the full systematic uncertainties for data-driven backgrounds. For illustration the distribution for a benchmark SUSY scenario ($pp\to \tilde g\tilde g$, $\tilde g\to qq(\tilde\ell\ell/\tilde\nu\nu)$, $m_{\tilde g}=1.3$ TeV, $m_{\tilde\chi_1^0}=0.5$ TeV) is also shown.
Missing transverse momentum distribution after SR0b5j selection, beside the $E_\mathrm{T}^\mathrm{miss}$ requirement. The results in the signal region correspond to the last inclusive bin. The systematic uncertainties include theory uncertainties for the backgrounds with prompt SS/3L and the full systematic uncertainties for data-driven backgrounds. For illustration the distribution for a benchmark SUSY scenario ($pp\to \tilde g\tilde g$, $\tilde g\to qqWZ\tilde\chi_1^0$, $m_{\tilde g}=1.1$ TeV, $m_{\tilde\chi_1^0}=0.4$ TeV) is also shown.
Missing transverse momentum distribution after SR1b selection, beside the $E_\mathrm{T}^\mathrm{miss}$ requirement. The results in the signal region correspond to the last inclusive bin. The systematic uncertainties include theory uncertainties for the backgrounds with prompt SS/3L and the full systematic uncertainties for data-driven backgrounds. For illustration the distribution for a benchmark SUSY scenario ($pp\to \tilde b_1\tilde b_1^*$, $\tilde b_1\to tW\tilde\chi_1^0$, $m_{\tilde b_1}=600$ GeV, $m_{\tilde\chi_1^0}=50$ GeV) is also shown.
Missing transverse momentum distribution after SR3b selection, beside the $E_\mathrm{T}^\mathrm{miss}$ requirement. The results in the signal region correspond to the last inclusive bin. The systematic uncertainties include theory uncertainties for the backgrounds with prompt SS/3L and the full systematic uncertainties for data-driven backgrounds. For illustration the distribution for a benchmark SUSY scenario ($pp\to \tilde g\tilde g$, $\tilde g\to t\bar t\tilde\chi_1^0$, $m_{\tilde g}=1.2$ TeV, $m_{\tilde\chi_1^0}=0.7$ TeV) is also shown.
Observed exclusion limits on the $\tilde g$ and $\tilde\chi_1^0$ masses in the context of SUSY scenarios with simplified mass spectra featuring $\tilde g\tilde g$ pair production with exclusive $\tilde g\to qq(\tilde\ell\ell/\tilde\nu\nu)$ decays. All limits are computed at 95% CL.
Expected exclusion limits on the $\tilde g$ and $\tilde\chi_1^0$ masses in the context of SUSY scenarios with simplified mass spectra featuring $\tilde g\tilde g$ pair production with exclusive $\tilde g\to qq(\tilde\ell\ell/\tilde\nu\nu)$ decays. All limits are computed at 95% CL.
Upper limits on signal cross-sections as function of the $\tilde g$ and $\tilde\chi_1^0$ masses in the context of SUSY scenarios with simplified mass spectra featuring $\tilde g\tilde g$ pair production with exclusive $\tilde g\to qq(\tilde\ell\ell/\tilde\nu\nu)$ decays, obtained using the signal efficiency and acceptance specific to each model. All limits are computed at 95% CL.
Observed exclusion limits on the $\tilde g$ and $\tilde\chi_1^0$ masses in the context of SUSY scenarios with simplified mass spectra featuring $\tilde g\tilde g$ pair production with exclusive $\tilde g\to qqWZ\tilde\chi_1^0$ decays. All limits are computed at 95% CL.
Expected exclusion limits on the $\tilde g$ and $\tilde\chi_1^0$ masses in the context of SUSY scenarios with simplified mass spectra featuring $\tilde g\tilde g$ pair production with exclusive $\tilde g\to qqWZ\tilde\chi_1^0$ decays. All limits are computed at 95% CL.
Upper limits on signal cross-sections as function of the $\tilde g$ and $\tilde\chi_1^0$ masses in the context of SUSY scenarios with simplified mass spectra featuring $\tilde g\tilde g$ pair production with exclusive $\tilde g\to qqWZ\tilde\chi_1^0$ decays, obtained using the signal efficiency and acceptance specific to each model. All limits are computed at 95% CL.
Observed exclusion limits on the $\tilde b_1$ and $\tilde\chi_1^0$ masses in the context of SUSY scenarios with simplified mass spectra featuring $\tilde b_1\tilde b_1^*$ pair production with exclusive $\tilde b_1\to t\tilde\chi_1^-$ decays. All limits are computed at 95% CL.
Expected exclusion limits on the $\tilde b_1$ and $\tilde\chi_1^0$ masses in the context of SUSY scenarios with simplified mass spectra featuring $\tilde b_1\tilde b_1^*$ pair production with exclusive $\tilde b_1\to t\tilde\chi_1^-$ decays. All limits are computed at 95% CL.
Upper limits on signal cross-sections as function of the $\tilde b_1$ and $\tilde\chi_1^0$ masses in the context of SUSY scenarios with simplified mass spectra featuring $\tilde b_1\tilde b_1^*$ pair production with exclusive $\tilde b_1\to t\tilde\chi_1^-$ decays, obtained using the signal efficiency and acceptance specific to each model. All limits are computed at 95% CL.
Observed exclusion limits on the $\tilde g$ and $\tilde\chi_1^0$ masses in the context of SUSY scenarios with simplified mass spectra featuring $\tilde g\tilde g$ pair production with exclusive $\tilde g\to t\bar t\tilde\chi_1^0$ decays. All limits are computed at 95% CL.
Expected exclusion limits on the $\tilde g$ and $\tilde\chi_1^0$ masses in the context of SUSY scenarios with simplified mass spectra featuring $\tilde g\tilde g$ pair production with exclusive $\tilde g\to t\bar t\tilde\chi_1^0$ decays. All limits are computed at 95% CL.
Upper limits on signal cross-sections as function of the $\tilde g$ and $\tilde\chi_1^0$ masses in the context of SUSY scenarios with simplified mass spectra featuring $\tilde g\tilde g$ pair production with exclusive $\tilde g\to t\bar t\tilde\chi_1^0$ decays, obtained using the signal efficiency and acceptance specific to each model. All limits are computed at 95% CL.
SUSY scenario with $\tilde g\tilde g$ production and $\tilde g\to q\bar q(\tilde\ell\ell/\tilde\nu\nu)$ decay: signal acceptance (in %) in the signal region SR0b3j. The benchmark scenarios used to set exclusion limits are materialized by black dot markers. Acceptance and efficiency are defined as in appendix A of [JHEP 06 (2014) 124, arXiv: 1403.4853v1 [hep-ex]].
SUSY scenario with $\tilde g\tilde g$ production and $\tilde g\to q\bar q(\tilde\ell\ell/\tilde\nu\nu)$ decay: reconstruction efficiency (in %) in the signal region SR0b3j. The benchmark scenarios used to set exclusion limits are materialized by black dot markers. Acceptance and efficiency are defined as in appendix A of [JHEP 06 (2014) 124, arXiv: 1403.4853v1 [hep-ex]].
SUSY scenario with $\tilde g\tilde g$ production and $\tilde g\to q\bar qWZ\tilde\chi_1^0$ decay: signal acceptance (in %) in the signal region SR0b5j. The benchmark scenarios used to set exclusion limits are materialized by black dot markers. Acceptance and efficiency are defined as in appendix A of [JHEP 06 (2014) 124, arXiv: 1403.4853v1 [hep-ex]].
SUSY scenario with $\tilde g\tilde g$ production and $\tilde g\to q\bar qWZ\tilde\chi_1^0$ decay: reconstruction efficiency (in %) in the signal region SR0b5j. The benchmark scenarios used to set exclusion limits are materialized by black dot markers. Acceptance and efficiency are defined as in appendix A of [JHEP 06 (2014) 124, arXiv: 1403.4853v1 [hep-ex]].
SUSY scenario with $\tilde b_1\tilde b_1^*$ production and $\tilde b_1\to tW\tilde\chi_1^0$ decay: signal acceptance (in %) in the signal region SR1b. The benchmark scenarios used to set exclusion limits are materialized by black dot markers. Acceptance and efficiency are defined as in appendix A of [JHEP 06 (2014) 124, arXiv: 1403.4853v1 [hep-ex]].
SUSY scenario with $\tilde b_1\tilde b_1^*$ production and $\tilde b_1\to tW\tilde\chi_1^0$ decay: reconstruction efficiency (in %) in the signal region SR1b. The benchmark scenarios used to set exclusion limits are materialized by black dot markers. Acceptance and efficiency are defined as in appendix A of [JHEP 06 (2014) 124, arXiv: 1403.4853v1 [hep-ex]].
SUSY scenario with $\tilde g\tilde g$ production and $\tilde g\to t\bar t\tilde\chi_1^0$ decay: signal acceptance (in %) in the signal region SR3b. The benchmark scenarios used to set exclusion limits are materialized by black dot markers. Acceptance and efficiency are defined as in appendix A of [JHEP 06 (2014) 124, arXiv: 1403.4853v1 [hep-ex]].
SUSY scenario with $\tilde g\tilde g$ production and $\tilde g\to t\bar t\tilde\chi_1^0$ decay: reconstruction efficiency (in %) in the signal region SR3b. The benchmark scenarios used to set exclusion limits are materialized by black dot markers. Acceptance and efficiency are defined as in appendix A of [JHEP 06 (2014) 124, arXiv: 1403.4853v1 [hep-ex]].
A search for supersymmetry in events with large missing transverse momentum, jets, and at least one hadronically decaying $\tau$-lepton is presented. Two exclusive final states with either exactly one or at least two $\tau$-leptons are considered. The analysis is based on proton-proton collisions at $\sqrt{s}$ = 13 TeV corresponding to an integrated luminosity of 36.1 fb$^{-1}$ delivered by the Large Hadron Collider and recorded by the ATLAS detector in 2015 and 2016. No significant excess is observed over the Standard Model expectation. At 95% confidence level, model-independent upper limits on the cross section are set and exclusion limits are provided for two signal scenarios: a simplified model of gluino pair production with $\tau$-rich cascade decays, and a model with gauge-mediated supersymmetry breaking (GMSB). In the simplified model, gluino masses up to 2000 GeV are excluded for low values of the mass of the lightest supersymmetric particle (LSP), while LSP masses up to 1000 GeV are excluded for gluino masses around 1400 GeV. In the GMSB model, values of the supersymmetry-breaking scale are excluded below 110 TeV for all values of $\tan\beta$ in the range $2 \leq \tan\beta \leq 60$, and below 120 TeV for $\tan\beta>30$.
1$\tau$ Compressed SR eff.
1$\tau$ Compressed SR eff.
1$\tau$ MediumMass SR eff.
1$\tau$ MediumMass SR eff.
2$\tau$ Compressed SR eff.
2$\tau$ Compressed SR eff.
2$\tau$ HighMass SR eff.
2$\tau$ HighMass SR eff.
2$\tau$ multibin SR eff.
2$\tau$ multibin SR eff.
2$\tau$ GMSB SR eff.
2$\tau$ GMSB SR eff.
1$\tau$ Compressed SR eff.
1$\tau$ Compressed SR eff.
1$\tau$ MediumMass SR eff.
1$\tau$ MediumMass SR eff.
2$\tau$ Compressed SR eff.
2$\tau$ Compressed SR eff.
2$\tau$ HighMass SR eff.
2$\tau$ HighMass SR eff.
2$\tau$ multibin SR eff.
2$\tau$ multibin SR eff.
2$\tau$ GMSB SR eff.
2$\tau$ GMSB SR eff.
1$\tau$ Compressed SR acceptance.
1$\tau$ Compressed SR acceptance.
1$\tau$ MediumMass SR acceptance.
1$\tau$ MediumMass SR acceptance.
2$\tau$ Compressed SR acceptance.
2$\tau$ Compressed SR acceptance.
2$\tau$ HighMass SR acceptance.
2$\tau$ HighMass SR acceptance.
2$\tau$ multibin SR acceptance.
2$\tau$ multibin SR acceptance.
2$\tau$ GMSB SR acceptance.
2$\tau$ GMSB SR acceptance.
1$\tau$ Compressed SR acceptance.
1$\tau$ Compressed SR acceptance.
1$\tau$ MediumMass SR acceptance.
1$\tau$ MediumMass SR acceptance.
2$\tau$ Compressed SR acceptance.
2$\tau$ Compressed SR acceptance.
2$\tau$ HighMass SR acceptance.
2$\tau$ HighMass SR acceptance.
2$\tau$ multibin SR acceptance.
2$\tau$ multibin SR acceptance.
2$\tau$ GMSB SR acceptance.
2$\tau$ GMSB SR acceptance.
Cutflow table of the $1\tau$ compressed SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.
Cutflow table of the $1\tau$ compressed SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.
Cutflow table of the $1\tau$ medium-mass SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.
Cutflow table of the $1\tau$ medium-mass SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.
Cutflow table of the $2\tau$ compressed SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.
Cutflow table of the $2\tau$ compressed SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.
Cutflow table of the $2\tau$ high-mass SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.
Cutflow table of the $2\tau$ high-mass SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.
Cutflow table of the $2\tau$ multibin SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.
Cutflow table of the $2\tau$ multibin SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.
Cutflow table of the $2\tau$ GMSB SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.
Cutflow table of the $2\tau$ GMSB SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.
Best performing fit setups entering the final combination as a function of the LSP mass and the gluino mass. 'S' marks the simultaneous fit of the four simplified model single-bin SRs, 'M' denotes the simultaneous fit of the two $1\tau$ SRs and the $2\tau$ multibin SR.
Best performing fit setups entering the final combination as a function of the LSP mass and the gluino mass. 'S' marks the simultaneous fit of the four simplified model single-bin SRs, 'M' denotes the simultaneous fit of the two $1\tau$ SRs and the $2\tau$ multibin SR.
Observed exclusion contour at 95% CL as a function of tanBeta and the SUSY-breaking mass scale Lambda.
Observed exclusion contour at 95% CL as a function of tanBeta and the SUSY-breaking mass scale Lambda.
Expected exclusion contour at 95% CL as a function of tanBeta and the SUSY-breaking mass scale Lambda.
Expected exclusion contour at 95% CL as a function of tanBeta and the SUSY-breaking mass scale Lambda.
Observed exclusion contour at 95% CL as a function of the LSP mass and the gluino mass.
Observed exclusion contour at 95% CL as a function of the LSP mass and the gluino mass.
Expected exclusion contour at 95% CL as a function of the LSP mass and the gluino mass.
Expected exclusion contour at 95% CL as a function of the LSP mass and the gluino mass.
Observed upper limits on the production cross section at 95% CL in pb as a function of tanBeta and SUSY breaking mass scale Lambda.
Observed upper limits on the production cross section at 95% CL in pb as a function of tanBeta and SUSY breaking mass scale Lambda.
Observed upper limits on the production cross section at 95% CL in pb as a function of the LSP mass and the gluino mass.
Observed upper limits on the production cross section at 95% CL in pb as a function of the LSP mass and the gluino mass.
Yields of the expected background from the SM in the bins of the multibin SR of the $2\tau$ channel with all bins being simultaneously used to constrain the background prediction. Expectation is given with the scalings computed in the combined fit applied. Uncertainties are statistial plus systematrics. Only the subsamples contributing the respective region are considered.
Yields of the expected background from the SM in the bins of the multibin SR of the $2\tau$ channel with all bins being simultaneously used to constrain the background prediction. Expectation is given with the scalings computed in the combined fit applied. Uncertainties are statistial plus systematrics. Only the subsamples contributing the respective region are considered.
$m_{\mathrm{T}}^{\tau}$ in the compressed $m_{\mathrm{T}}^{\tau}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$m_{\mathrm{T}}^{\tau}$ in the compressed $m_{\mathrm{T}}^{\tau}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$E_{\mathrm{T}}^{\mathrm{miss}}$ in the compressed $E_{\mathrm{T}}^{\mathrm{miss}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$E_{\mathrm{T}}^{\mathrm{miss}}$ in the compressed $E_{\mathrm{T}}^{\mathrm{miss}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$m_{\mathrm{T}}^{\tau}$ in the medium-mass $m_{\mathrm{T}}^{\tau}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$m_{\mathrm{T}}^{\tau}$ in the medium-mass $m_{\mathrm{T}}^{\tau}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$E_{\mathrm{T}}^{\mathrm{miss}}$ in the medium-mass $E_{\mathrm{T}}^{\mathrm{miss}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$E_{\mathrm{T}}^{\mathrm{miss}}$ in the medium-mass $E_{\mathrm{T}}^{\mathrm{miss}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$H_{\mathrm{T}}$ in the medium-mass $H_{\mathrm{T}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$H_{\mathrm{T}}$ in the medium-mass $H_{\mathrm{T}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$m_{\mathrm{T}}^{\tau_1}$ + $m_{\mathrm{T}}^{\tau_2}$ in the top VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$m_{\mathrm{T}}^{\tau_1}$ + $m_{\mathrm{T}}^{\tau_2}$ in the top VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$H_{\mathrm{T}}$ in the $W$ VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$H_{\mathrm{T}}$ in the $W$ VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$m_{\mathrm{T}}^{\tau_1}$ + $m_{\mathrm{T}}^{\tau_2}$ in the $Z$ VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$m_{\mathrm{T}}^{\tau_1}$ + $m_{\mathrm{T}}^{\tau_2}$ in the $Z$ VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.
$m_{\mathrm{T}}^{\tau}$ in the compressed SR of the $1\tau$ channel before application of the $m_{\mathrm{T}}^{\tau}$ > 80 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.
$m_{\mathrm{T}}^{\tau}$ in the compressed SR of the $1\tau$ channel before application of the $m_{\mathrm{T}}^{\tau}$ > 80 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.
$H_{\mathrm{T}}$ in the medium-mass SR of the $1\tau$ channel before application of the $H_{\mathrm{T}}$ > 1000 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.
$H_{\mathrm{T}}$ in the medium-mass SR of the $1\tau$ channel before application of the $H_{\mathrm{T}}$ > 1000 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.
$m_{\mathrm{T}}^{\mathrm{sum}}$ in the compressed SR of the $2\tau$ channel before application of the $m_{\mathrm{T}}^{\mathrm{sum}}$ > 1600 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.
$m_{\mathrm{T}}^{\mathrm{sum}}$ in the compressed SR of the $2\tau$ channel before application of the $m_{\mathrm{T}}^{\mathrm{sum}}$ > 1600 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.
$H_{\mathrm{T}}$ in the high-mass SR of the $2\tau$ channel before application of the $H_{\mathrm{T}}$ > 1100 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.
$H_{\mathrm{T}}$ in the high-mass SR of the $2\tau$ channel before application of the $H_{\mathrm{T}}$ > 1100 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.
mT(tau_1) + mT(tau_2) in the multibin SR of the 2T channel. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.
mT(tau_1) + mT(tau_2) in the multibin SR of the 2T channel. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.
$H_{\mathrm{T}}$ in the GMSB SR of the $2\tau$ channel before application of the $H_{\mathrm{T}}$ > 1900 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.
$H_{\mathrm{T}}$ in the GMSB SR of the $2\tau$ channel before application of the $H_{\mathrm{T}}$ > 1900 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.
This Letter presents a search for heavy charged long-lived particles produced in proton-proton collisions at $\sqrt{s} = 13$ TeV at the LHC using a data sample corresponding to an integrated luminosity of 36.1 fb$^{-1}$ collected by the ATLAS experiment in 2015 and 2016. These particles are expected to travel with a velocity significantly below the speed of light, and therefore have a specific ionisation higher than any high-momentum Standard Model particle of unit charge. The pixel subsystem of the ATLAS detector is used in this search to measure the ionisation energy loss of all reconstructed charged particles which traverse the pixel detector. Results are interpreted assuming the pair production of $R$-hadrons as composite colourless states of a long-lived gluino and Standard Model partons. No significant deviation from Standard Model background expectations is observed, and lifetime-dependent upper limits on $R$-hadron production cross-sections and gluino masses are set, assuming the gluino always decays in two quarks and a stable neutralino. $R$-hadrons with lifetimes above 1.0 ns are excluded at the 95% confidence level, with lower limits on the gluino mass ranging between 1290 GeV and 2060 GeV. In the case of stable $R$-hadrons, the lower limit on the gluino mass at the 95% confidence level is 1890 GeV.
The number of events in each CR, VR, and SR for the predicted background, for the expected contribution from the signal model normalised to $36.1$ fb$^{-1}$, and in the observed data. The predicted background includes the statistical and systematic uncertainties, respectively. The uncertainty in the signal yield includes all systematic uncertainties except that in the theoretical cross-section.
The number of events in each CR, VR, and SR for the predicted background, for the expected contribution from the signal model normalised to $36.1$ fb$^{-1}$, and in the observed data. The predicted background includes the statistical and systematic uncertainties, respectively. The uncertainty in the signal yield includes all systematic uncertainties except that in the theoretical cross-section.
Expected number of $R$-hadron signal events at different stages of the selection, normalised to $36.1$ fb$^{-1}$. Shown for three different signal points is the number of events expected and the number of events expected in which the selected track has been matched to a generated $R$-hadron. If the gluino decays, it decays to a 100 GeV $\tilde{\chi}^{0}$ and SM quarks.
The observed and expected 95% CL upper limits on model-independent visible cross-sections, along with the observed $p0$ values, for the stable signal region, as a function of different mass windows, for which the lower bound is shown. The upper boundary on the mass window is 5 TeV for all windows.
The observed and expected 95% CL upper limits on model-independent visible cross-sections, along with the observed $p0$ values, for the metastable signal region, as a function of different mass windows, for which the lower bound is shown. The upper boundary on the mass window is 5 TeV for all windows.
For each gluino lifetime and mass in the signal samples, the lower boundary of the mass window in which at least $70\%$ of the reconstructed signal appears. The upper boundary for all mass windows is 5 TeV.
Acceptance and efficiency for a representative set of pair-produced gluino signal samples. The mass of the gluino ($m(\tilde{g})$), its lifetime ($\tau(\tilde{g})$) and the mass of the neutralino ($m(\tilde{\chi}^{0})$) are given in the first three columns. The Pythia 6.4.27 signal samples shown in this table are not reweighted to match the transverse momentum of the gluino-gluino system as simulated by MadGraph5_aMC@NLO. The acceptance is defined as the fraction of events passing a loose set of fiducial requirements. The full simulation efficiency (Full sim. $\epsilon$) is defined as the ratio of the number of reconstructed events, as expected by the full ATLAS simulation, and the number of events passing the fiducial requirements. The parameterised simulation efficiency (Param. sim. $\epsilon$) is defined as the ratio of the number of events estimated using a set of parametrised efficiencies (see auxiliary Figures 9,10,11,12) and the number of events passing the fiducial requirements alone.
The reconstructed candidate track mass distributions for observed data, predicted background, and the expected contribution from two signal models in the metastable R-hadron signal region. The yellow band around the background estimation includes both the statistical and systematic uncertainties.
The reconstructed candidate track mass distributions for observed data, predicted background, and the expected contribution from two signal models in the stable R-hadron signal region. The yellow band around the background estimation includes both the statistical and systematic uncertainties.
The 95% CL upper limit on the cross-section as a function of mass for gluinos with lifetime $\tau = 10$ ns decaying into $q\bar{q}$ and a 100 GeV neutralino, with the observed limit shown as a solid black line. The predicted production cross-section values are shown in purple along with their uncertainty. The expected upper limit in the case of only background is shown by the dashed black line, with a green $\pm 1\sigma$ and a yellow $\pm 2\sigma$ band.
The 95% CL upper limit on the cross-section as a function of mass for stable gluino $R$-hadrons, with the observed limit shown as a solid black line. The predicted production cross-section values are shown in purple along with their uncertainty. The expected upper limit in the case of only background is shown by the dashed black line, with a green $\pm 1\sigma$ and a yellow $\pm 2\sigma$ band.
Observed 95% lower limits on the gluino mass in the gluino lifetime--mass plane. The excluded area is to the left of the curves.
Expected 95% lower limits on the gluino mass in the gluino lifetime--mass plane. The excluded area is to the left of the curves.
The 95% CL upper limit on the cross-section as a function of mass for gluinos with lifetime $\tau = 1$ ns decaying into $q\bar{q}$ and a 100 GeV neutralino, with the observed limit shown as a solid black line. The predicted production cross-section values are shown in purple along with their uncertainty. The expected upper limit in the case of only background is shown by the dashed black line, with a green $\pm 1\sigma$ and a yellow $\pm 2\sigma$ band.
The 95% CL upper limit on the cross-section as a function of mass for gluinos with lifetime $\tau = 3$ ns decaying into $q\bar{q}$ and a 100 GeV neutralino, with the observed limit shown as a solid black line. The predicted production cross-section values are shown in purple along with their uncertainty. The expected upper limit in the case of only background is shown by the dashed black line, with a green $\pm 1\sigma$ and a yellow $\pm 2\sigma$ band.
The 95% CL upper limit on the cross-section as a function of mass for gluinos with lifetime $\tau = 30$ ns decaying into $q\bar{q}$ and a 100 GeV neutralino, with the observed limit shown as a solid black line. The predicted production cross-section values are shown in purple along with their uncertainty. The expected upper limit in the case of only background is shown by the dashed black line, with a green $\pm 1\sigma$ and a yellow $\pm 2\sigma$ band.
The 95% CL upper limit on the cross-section as a function of mass for gluinos with lifetime $\tau = 50$ ns decaying into $q\bar{q}$ and a 100 GeV neutralino, with the observed limit shown as a solid black line. The predicted production cross-section values are shown in purple along with their uncertainty. The expected upper limit in the case of only background is shown by the dashed black line, with a green $\pm 1\sigma$ and a yellow $\pm 2\sigma$ band.
The relationship between generated and reconstructed mass for gluino $R$-hadrons. Above 1500 GeV, the reconstructed mass falls below the generated mass due to bias in the reconstructed momentum. The uncertainty on the reconstructed mass is dominated by momentum uncertainty. The black dots represent the reconstructed mass computed as the most probable value of a Gaussian fit function, with the error bars showing its statistical uncertainty, while the orange band is the full-width at half maximum of the reconstructed mass distribution.
The parameterised efficiency for events to pass metastable event selections (including trigger, E$_{T}^{miss}$, and event cleaning requirements) as a function of the true E$_{T}^{miss}$ in the system, which is calculated at generator level. Event-level efficiencies are evaluated for events which have at least true E$_{T}^{miss} > 50$ GeV. The metastable event efficiencies are evaluated for different radial regions depending on the smallest radial distance, R, at which an R-hadron decays in the detector.
The parameterised efficiency for events to pass metastable event selections (including trigger, E$_{T}^{miss}$, and event cleaning requirements) as a function of the true E$_{T}^{miss}$ in the system, which is calculated at generator level. Event-level efficiencies are evaluated for events which have at least true E$_{T}^{miss} > 50$ GeV. The stable event efficiencies are evaluated for samples in which no R-hadron decays within the detector.
The parameterised efficiency for particles to pass full track selections in the metastable signal region, as function of the particle’s $\beta$, in different bins of transverse momentum, $p_{T}$, and for different radial decay positions of the particle. The efficiency is evaluated for particles which pass a loose set of fiducial requirements at generator level.
The parameterised efficiency for particles to pass full track selections in the metastable signal region, as function of the particle’s $\beta$, in different bins of transverse momentum, $p_{T}$, and for different radial decay positions of the particle. The efficiency is evaluated for particles which pass a loose set of fiducial requirements at generator level.
The parameterised efficiency for particles to pass full track selections in the metastable signal region, as function of the particle’s $\beta$, in different bins of transverse momentum, $p_{T}$, and for different radial decay positions of the particle. The efficiency is evaluated for particles which pass a loose set of fiducial requirements at generator level.
The parameterised efficiency for particles to pass full track selections in the metastable signal region, as function of the particle’s $\beta$, in different bins of transverse momentum, $p_{T}$, and for different radial decay positions of the particle. The efficiency is evaluated for particles which pass a loose set of fiducial requirements at generator level.
The parameterised efficiency for particles to pass full track selections in the metastable signal region, as function of the particle’s $\beta$, in different bins of transverse momentum, $p_{T}$, and for different radial decay positions of the particle. The efficiency is evaluated for particles which pass a loose set of fiducial requirements at generator level.
The parameterised efficiency for particles to pass full track selections in the metastable signal region, as function of the particle’s $\beta$, in different bins of transverse momentum, $p_{T}$. The stable efficiency is evaluated for samples which do not decay within the detector. The efficiency is evaluated for particles which pass a loose set of fiducial requirements at generator level.
Results are reported of a search for new phenomena, such as supersymmetric particle production, that could be observed in high-energy proton--proton collisions. Events with large numbers of jets, together with missing transverse momentum from unobserved particles, are selected. The data analysed were recorded by the ATLAS experiment during 2015 using the 13 TeV centre-of-mass proton--proton collisions at the Large Hadron Collider, and correspond to an integrated luminosity of 3.2 fb$^{-1}$. The search selected events with various jet multiplicities from $\ge 7$ to $\ge 10$ jets, and with various $b$-jet multiplicity requirements to enhance sensitivity. No excess above Standard Model expectations is observed. The results are interpreted within two supersymmetry models, where gluino masses up to 1400 GeV are excluded at 95% confidence level, significantly extending previous limits.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in validation region 7ej50 0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in validation region 6ej80 0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 10j50 0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 10j50 2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 8j80 0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 8j80 2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
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.
+1 sigma excursion of the expected 95% CL limit for the pMSSM grid.
-1 sigma excursion of the expected 95% CL limit for the pMSSM grid.
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.
+1 sigma excursion of the expected 95% CL limit for the 2Step grid.
-1 sigma excursion of the expected 95% CL limit for the 2Step grid.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 8j50 0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 8j50 1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 8j50 2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 9j50 0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 9j50 1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 9j50 2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 10j50 0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 10j50 1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 10j50 2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 7j80 0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 7j80 1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 7j80 2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 8j80 0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 8j80 1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 8j80 2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
Degree of multijet closure for signal and vaidation regions with at no b-jet requirement. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The bins labelled in bold are signal regions, while the others are validation regions. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).
Degree of multijet closure for signal and vaidation regions with at least 1 b-jet. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The bins labelled in bold are signal regions, while the others are validation regions. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).
Degree of multijet closure for signal and vaidation regions with at least 2 b-jets. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The bins labelled in bold are signal regions, while the others are validation regions. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).
Summary of all 15 signal regions (post-fit).
Signal region yielding the best-expected CLs value, the best expected CLs value, and the corresponding observed CLs value for the 2Step grid.
Signal region yielding the best-expected CLs value, the best expected CLs value, and the corresponding observed CLs value for the pMSSM grid.
95% CLs observed upper limit on model cross-section for 2-step signal points for the best-expected signal region.
Performance of the 8j50-0b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 8j50-1b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 8j50-2b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 9j50-0b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 9j50-1b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 9j50-2b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 10j50-0b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 10j50-1b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 10j50-2b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 7j80-0b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 7j80-1b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 7j80-2b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 8j80-0b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 8j80-1b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 8j80-2b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 8j50-0b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 8j50-1b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 8j50-2b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 9j50-0b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 9j50-1b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 9j50-2b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 10j50-0b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 10j50-1b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 10j50-2b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 7j80-0b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 7j80-1b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 7j80-2b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 8j80-0b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 8j80-1b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 8j80-2b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
A search for squarks and gluinos in final states containing hadronic jets, missing transverse momentum but no electrons or muons is presented. The data were recorded in 2015 by the ATLAS experiment in $\sqrt{s}=$ 13 TeV proton--proton collisions at the Large Hadron Collider. No excess above the Standard Model background expectation was observed in 3.2 fb$^{-1}$ of analyzed data. Results are interpreted within simplified models that assume R-parity is conserved and the neutralino is the lightest supersymmetric particle. An exclusion limit at the 95% confidence level on the mass of the gluino is set at 1.51 TeV for a simplified model incorporating only a gluino octet and the lightest neutralino, assuming the lightest neutralino is massless. For a simplified model involving the strong production of mass-degenerate first- and second-generation squarks, squark masses below 1.03 TeV are excluded for a massless lightest neutralino. These limits substantially extend the region of supersymmetric parameter space excluded by previous measurements with the ATLAS detector.
Observed and expected background effective mass distributions in control region CRgamma for SR4jt.
Observed and expected background effective mass distributions in control region CRW for SR4jt.
Observed and expected background effective mass distributions in control region CRT for SR4jt.
Observed and expected background and signal effective mass distributions for SR2jl. For signal, a squark direct decay model with $m(\tilde q)=800$ GeV and $m(\tilde\chi^0_1)=400$ GeV is shown.
Observed and expected background and signal effective mass distributions for SR2jm. For signal, a gluino direct decay model with $m(\tilde g)=750$ GeV and $m(\tilde\chi^0_1)=660$ GeV is shown.
Observed and expected background and signal effective mass distributions for SR2jt. For signal, a squark direct decay model with $m(\tilde q)=1200$ GeV and $m(\tilde\chi^0_1)=0$ GeV is shown.
Observed and expected background and signal effective mass distributions for SR4jt. For signal, a gluino direct decay model with $m(\tilde g)=1400$ GeV and $m(\tilde\chi^0_1)=0$ GeV is shown.
Observed and expected background and signal effective mass distributions for SR5j. For signal, a gluino one-step decay model with $m(\tilde g)=1265$ GeV, $m(\tilde\chi^\pm_1)=945$ GeV and $m(\tilde\chi^0_1)=625$ GeV is shown.
Observed and expected background and signal effective mass distributions for SR6jm. For signal, a gluino one-step decay model with $m(\tilde g)=1265$ GeV, $m(\tilde\chi^\pm_1)=945$ GeV and $m(\tilde\chi^0_1)=625$ GeV is shown.
Observed and expected background and signal effective mass distributions for SR6jt. For signal, a gluino one-step decay model with $m(\tilde g)=1385$ GeV, $m(\tilde\chi^\pm_1)=705$ GeV and $m(\tilde\chi^0_1)=25$ GeV is shown.
Expected limit at 95% CL for squark direct decay model grid.
Expected limits at 95% CL +1 sigma excursion due to experimental and background-only theoretical uncertainties for squark direct decay model grid.
Expected limits at 95% CL -1 sigma excursion due to experimental and background-only theoretical uncertainties for squark direct decay model grid.
Observed limits at 95% CL for squark direct decay model grid.
Observed limits at 95% CL +1 sigma excursion due to the signal cross-section uncertainty for squark direct decay model grid.
Observed limits at 95% CL -1 sigma excursion due to the signal cross-section uncertainty for squark direct decay model grid.
Expected limit at 95% CL for gluino direct decay model grid.
Expected limits at 95% CL +1 sigma excursion due to experimental and background-only theoretical uncertainties for gluino direct decay model grid.
Expected limits at 95% CL -1 sigma excursion due to experimental and background-only theoretical uncertainties for gluino direct decay model grid.
Observed limits at 95% CL for gluino direct decay model grid.
Observed limits at 95% CL +1 sigma excursion due to the signal cross-section uncertainty for gluino direct decay model grid.
Observed limits at 95% CL -1 sigma excursion due to the signal cross-section uncertainty for gluino direct decay model grid.
Expected limit at 95% CL for gluino one-step decay model grid.
Expected limits at 95% CL +1 sigma excursion due to experimental and background-only theoretical uncertainties for gluino one-step decay model grid.
Expected limits at 95% CL -1 sigma excursion due to experimental and background-only theoretical uncertainties for gluino one-step decay model grid.
Observed limits at 95% CL for gluino one-step decay model grid.
Observed limits at 95% CL +1 sigma excursion due to the signal cross-section uncertainty for gluino one-step decay model grid.
Observed limits at 95% CL -1 sigma excursion due to the signal cross-section uncertainty for gluino one-step decay model grid.
Observed and expected background effective mass distributions in control region CRgamma for SR2jl.
Observed and expected background effective mass distributions in validation region VRZ for SR2jl.
Observed and expected background effective mass distributions in control region CRW for SR2jl.
Observed and expected background effective mass distributions in control region CRT for SR2jl.
Observed and expected background effective mass distributions in control region CRgamma for SR2jm.
Observed and expected background effective mass distributions in validation region VRZ for SR2jm.
Observed and expected background effective mass distributions in control region CRW for SR2jm.
Observed and expected background effective mass distributions in control region CRT for SR2jm.
Observed and expected background effective mass distributions in control region CRgamma for SR2jt.
Observed and expected background effective mass distributions in validation region VRZ for SR2jt.
Observed and expected background effective mass distributions in control region CRW for SR2jt.
Observed and expected background effective mass distributions in control region CRT for SR2jt.
Observed and expected background effective mass distributions in control region CRgamma for SR4jt.
Observed and expected background effective mass distributions in validation region VRZ for SR4jt.
Observed and expected background effective mass distributions in control region CRW for SR4jt.
Observed and expected background effective mass distributions in control region CRT for SR4jt.
Observed and expected background effective mass distributions in control region CRgamma for SR5j.
Observed and expected background effective mass distributions in validation region VRZ for SR5j.
Observed and expected background effective mass distributions in control region CRW for SR5j.
Observed and expected background effective mass distributions in control region CRT for SR5j.
Observed and expected background effective mass distributions in control region CRgamma for SR6jm.
Observed and expected background effective mass distributions in validation region VRZ for SR6jm.
Observed and expected background effective mass distributions in control region CRW for SR6jm.
Observed and expected background effective mass distributions in control region CRT for SR6jm.
Observed and expected background effective mass distributions in control region CRgamma for SR6jt.
Observed and expected background effective mass distributions in validation region VRZ for SR6jt.
Observed and expected background effective mass distributions in control region CRW for SR6jt.
Observed and expected background effective mass distributions in control region CRT for SR6jt.
Observed and expected event yields in VRZ as a function of signal region.
Observed and expected event yields in VRW as a function of signal region.
Observed and expected event yields in VRWv as a function of signal region.
Observed and expected event yields in VRT as a function of signal region.
Observed and expected event yields in VRTv as a function of signal region.
Observed and expected event yields in VRQa as a function of signal region.
Observed and expected event yields in VRQb as a function of signal region.
Signal acceptance for SR2jl in squark direct decay model grid.
Signal acceptance times efficiency for SR2jl in squark direct decay model grid.
Signal acceptance for SR2jm in squark direct decay model grid.
Signal acceptance times efficiency for SR2jm in squark direct decay model grid.
Signal acceptance for SR2jt in squark direct decay model grid.
Signal acceptance times efficiency for SR2jt in squark direct decay model grid.
Signal acceptance for SR4jt in squark direct decay model grid.
Signal acceptance times efficiency for SR4jt in squark direct decay model grid.
Signal acceptance for SR5j in squark direct decay model grid.
Signal acceptance times efficiency for SR5j in squark direct decay model grid.
Signal acceptance for SR6jm in squark direct decay model grid.
Signal acceptance times efficiency for SR6jm in squark direct decay model grid.
Signal acceptance for SR6jt in squark direct decay model grid.
Signal acceptance times efficiency for SR6jt in squark direct decay model grid.
Signal acceptance for SR2jl in gluino direct decay model grid.
Signal acceptance times efficiency for SR2jl in gluino direct decay model grid.
Signal acceptance for SR2jm in gluino direct decay model grid.
Signal acceptance times efficiency for SR2jm in gluino direct decay model grid.
Signal acceptance for SR2jt in gluino direct decay model grid.
Signal acceptance times efficiency for SR2jt in gluino direct decay model grid.
Signal acceptance for SR4jt in gluino direct decay model grid.
Signal acceptance times efficiency for SR4jt in gluino direct decay model grid.
Signal acceptance for SR5j in gluino direct decay model grid.
Signal acceptance times efficiency for SR5j in gluino direct decay model grid.
Signal acceptance for SR6jm in gluino direct decay model grid.
Signal acceptance times efficiency for SR6jm in gluino direct decay model grid.
Signal acceptance for SR6jt in gluino direct decay model grid.
Signal acceptance times efficiency for SR6jt in gluino direct decay model grid.
Signal acceptance for SR2jl in gluino one-step decay model grid.
Signal acceptance times efficiency for SR2jl in gluino one-step decay model grid.
Signal acceptance for SR2jm in gluino one-step decay model grid.
Signal acceptance times efficiency for SR2jm in gluino one-step decay model grid.
Signal acceptance for SR2j5 in gluino one-step decay model grid.
Signal acceptance times efficiency for SR2jt in gluino one-step decay model grid.
Signal acceptance for SR4jt in gluino one-step decay model grid.
Signal acceptance times efficiency for SR4jt in gluino one-step decay model grid.
Signal acceptance for SR5j in gluino one-step decay model grid.
Signal acceptance times efficiency for SR5j in gluino one-step decay model grid.
Signal acceptance for SR6jm in gluino one-step decay model grid.
Signal acceptance times efficiency for SR6jm in gluino one-step decay model grid.
Signal acceptance for SR6jt in gluino one-step decay model grid.
Signal acceptance times efficiency for SR6jt in gluino one-step decay model grid.
A search for new phenomena in final states containing an $e^+e^-$ or $\mu^+\mu^-$ pair, jets, and large missing transverse momentum is presented. This analysis makes use of proton--proton collision data with an integrated luminosity of $36.1 \; \mathrm{fb}^{-1}$, collected during 2015 and 2016 at a centre-of-mass energy $\sqrt{s}$ = 13 TeV with the ATLAS detector at the Large Hadron Collider. The search targets the pair production of supersymmetric coloured particles (squarks or gluinos) and their decays into final states containing an $e^+e^-$ or $\mu^+\mu^-$ pair and the lightest neutralino ($\tilde{\chi}_1^0$) via one of two next-to-lightest neutralino ($\tilde{\chi}_2^0$) decay mechanisms: $\tilde{\chi}_2^0 \rightarrow Z \tilde{\chi}_1^0$, where the $Z$ boson decays leptonically leading to a peak in the dilepton invariant mass distribution around the $Z$ boson mass; and $\tilde{\chi}_2^0 \rightarrow \ell^+\ell^- \tilde{\chi}_1^0$ with no intermediate $\ell^+\ell^-$ resonance, yielding a kinematic endpoint in the dilepton invariant mass spectrum. The data are found to be consistent with the Standard Model expectation. Results are interpreted using simplified models, and exclude gluinos and squarks with masses as large as 1.85 TeV and 1.3 TeV at 95% confidence level, respectively.
Observed and expected dilepton mass distributions, with the bin boundaries considered for the interpretation, in SR-low. All statistical and systematic uncertainties of the expected background are included in the hatched band. An example signal from the slepton model with m(gluino) = 1200 GeV and m(neutralino1) = 900 GeV is overlaid.
Observed and expected dilepton mass distributions, with the bin boundaries considered for the interpretation, in SR-med. All statistical and systematic uncertainties of the expected background are included in the hatched band. An example signal from the slepton model with m(gluino) = 1600 GeV and m(neutralino1) = 900 GeV, and from an on-$Z$ model with m(gluino) = 1640 GeV and m(neutralino1) = 1160 GeV, is overlaid.
Observed and expected dilepton mass distributions, with the bin boundaries considered for the interpretation, in SR-high. All statistical and systematic uncertainties of the expected background are included in the hatched band. An example signal from the slepton model with m(gluino) = 1800 GeV and m(neutralino1) = 500 GeV, and from an on-$Z$ model with m(gluino) = 1650 GeV and m(neutralino1) = 550 GeV, is overlaid.
Observed and expected dilepton mass distributions, with the bin boundaries considered for the interpretation, in SRC of the low-pT edge search. All statistical and systematic uncertainties of the expected background are included in the hatched band. An example signal from the $Z^{*}$ model with m(gluino) = 1000 GeV and m(neutralino1) = 900 GeV is overlaid.
Observed and expected dilepton mass distributions, with the bin boundaries considered for the interpretation, in SRC-MET of the low-pT edge search. All statistical and systematic uncertainties of the expected background are included in the hatched band. An example signal from the $Z^{*}$ model with m(gluino) = 1000 GeV and m(neutralino1) = 900 GeV is overlaid.
Observed 95% CL exclusion contours on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.
Expected 95% CL exclusion contours on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.
Observed 95% CL exclusion contours from the low-p$_{T}$ signal regions on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.
Expected 95% CL exclusion contours from the low-p$_{T}$ signal regions on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.
Observed 95% CL exclusion contours on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay to an on- or off-shell $Z$ boson and the lightest neutralino.
Expected 95% CL exclusion contours on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay to an on- or off-shell $Z$ boson and the lightest neutralino.
Observed 95% CL exclusion contours from the low-p$_{T}$ signal regions on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay to an on- or off-shell $Z$ boson and the lightest neutralino.
Expected 95% CL exclusion contours from the low-p$_{T}$ signal regions on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay to an on- or off-shell $Z$ boson and the lightest neutralino.
Observed 95% CL exclusion contours from the on-Z signal regions on the gluino and next-to-lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino.
Expected 95% CL exclusion contours from the on-Z signal regions on the gluino and next-to-lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino.
Observed 95% CL exclusion contours from the on-Z signal regions on the squark and next-to-lightest neutralino masses in a SUSY scenario where squarks are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino.
Expected 95% CL exclusion contours from the on-Z signal regions on the squark and next-to-lightest neutralino masses in a SUSY scenario where squarks are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino.
Observed 95% CL exclusion contours from the on-Z signal regions on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson the lightest neutralino.
Expected 95% CL exclusion contours from the on-Z signal regions on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson and the lightest neutralino.
Acceptance and efficiency in the on-Z bin for SR-medium for the SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino.
Acceptance and efficiency in the on-Z bin for SR-high for the SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino.
Acceptance and efficiency over the full $m_{ll}$ range for SR-low for a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.
Acceptance and efficiency over the full $m_{ll}$ range for SR-medium for a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.
Acceptance and efficiency over the full $m_{ll}$ range for SR-high for a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.
Acceptance and efficiency over the full $m_{ll}$ range for SRC for a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.
Acceptance and efficiency over the full $m_{ll}$ range for SRC-MET for a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.
The grey numbers show the 95% CL upper limits on the production cross section at each model point, derived from the best expected combination of results in the on-Z $m_{ll}$ windows of SR-medium and SR-high, SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino.
The grey numbers show the 95% CL upper limits on the production cross section at each model point, derived from the best expected combination of results in the on-Z $m_{ll}$ windows of SR-medium and SR-high, SUSY scenario where squarks are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino.
The grey numbers show the 95% CL upper limits on the production cross section at each model point, derived from the best expected combination of results in the on-Z $m_{ll}$ windows of SR-medium and SR-high, in a SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson the lightest neutralino.
The grey numbers show the 95% CL upper limits on the production cross section at each model point, derived from the best expected combination of results in the signal regions, in a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.
The grey numbers show the 95% CL upper limits on the production cross section at each model point, derived from the best expected combination of results in the low-p$_{T}$ signal regions, in a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.
The grey numbers show the 95% CL upper limits on the production cross section at each model point, derived from the best expected combination of results in the signal regions, in a SUSYscenario where gluinos are produced in pairs and decay to an on- or off-shell $Z$ boson.
The grey numbers show the 95% CL upper limits on the production cross section at each model point, derived from the best expected combination of results in the low-p$_{T}$ signal regions, in a SUSY scenario where gluinos are produced in pairs and decay to an on- or off-shell $Z$ boson.
Cutflow table for three benchmark signal points from the SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino, with m(gluino) = 1395 GeV and m(neutralino2) = 505 GeV, m(gluino) = 920 GeV and m(neutralino2) = 230 GeV and m(gluino) = 940 GeV and m(neutralino2) = 660 GeV, in the on-$Z$ $m_{ll}$ bins of SR-medium and SR-high for the electron and muon channels separately. The numbers are normalized to a luminosity of 36.1 fb$^{-1}$.
Cutflow table for a signal point from the SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino, with m(gluino) = 1000 GeV and m(neutralino1) = 800 GeV, m(gluino) = 1200 GeV and m(neutralino1) = 500 GeV and m(gluino) = 1400 GeV and m(neutralino1) = 100 GeV, in all m_{ll}$ bins of SR-low, SR-medium and SR-high for the electron and muon channels separately. The numbers are normalized to a luminosity of 36.1 fb$^{-1}$.
Cutflow table for a signal point from the SUSY scenario where gluinos are produced in pairs and decay to an on- or off-shell $Z$ boson, with m(gluino) = 600 GeV and m(neutralino1) = 560 GeV and m(gluino) = 1000 GeV and m(neutralino1) = 960 GeV, in all $m_{ll}$ bins of SRC and SRC-MET for the electron and muon channels separately. The numbers are normalized to a luminosity of 36.1 fb$^{-1}$.
Signal region used to derive the exclusion limit for the SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino, corresponding to the SR determined to give the best expected limit for a given signal point.
Signal region used to derive the exclusion limit for the SUSY scenario where squarks are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino, corresponding to the SR determined to give the best expected limit for a given signal point.
Signal region used to derive the exclusion limit for the SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson the lightest neutralino, corresponding to the SR determined to give the best expected limit for a given signal point.
Signal region used to derive the exclusion limit for the SUSY scenario where gluinos are produced in pairs and decay to an on- or off-shell $Z$ boson, corresponding to the SR determined to give the best expected limit for a given signal point.
Low-$p_{T}$ signal region used to derive the exclusion limit in the compressed region for the SUSY scenario where gluinos are produced in pairs and decay to an on- or off-shell $Z$ boson, corresponding to the SR determined to give the best expected limit for a given signal point.
Signal region used to derive the exclusion limit for the SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino, corresponding to the SR determined to give the best expected limit for a given signal point.
Low-$p_{T}$ signal region used to derive the exclusion limit for the SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino, corresponding to the SR determined to give the best expected limit for a given signal point.
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 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).
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.
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 increased by one standard deviation.
Observed 95% CL limit for the pMSSM grid when the signal cross section is decreased 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.
Expected 95% CL limit for the pMSSM grid with an up variation of the uncertainties.
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.
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.
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 increased by one standard deviation.
Observed 95% CL limit for the 2Step grid when the signal cross section is decreased 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.
Expected 95% CL limit for the 2Step grid with an up variation of the uncertainties.
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.
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.
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 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.
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.
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 an up variation of the uncertainties.
Expected 95% CL limit for the gtt off-shell grid with a down 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.
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 increased by one standard deviation.
Observed 95% CL limit for the RPV grid when the signal cross section is decreased 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.
Expected 95% CL limit for the RPV grid with an up variation of the uncertainties.
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.
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-7j80-0b 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-7j80-1b 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-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-8j80-0b 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-8j80-1b 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-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-9j80-0b 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-9j80-1b 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-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-8j50-0b 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-8j50-1b 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-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-9j50-0b 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-9j50-1b 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-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-10j50-0b 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-10j50-1b 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-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-11j50-0b 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-11j50-1b 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.
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-8j50-0b. 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-8j50-1b. 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-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-9j50-0b. 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-9j50-1b. 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-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-10j50-0b. 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-10j50-1b. 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-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-11j50-0b. 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-11j50-1b. 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-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-7j80-0b. 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-7j80-1b. 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-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-8j80-0b. 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-8j80-1b. 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-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-9j80-0b. 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-9j80-1b. 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-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-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-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-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-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-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.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ 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 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 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 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 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 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 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 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).
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 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 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 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.
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 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 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.
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 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-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-8j50-0b-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-8j50-1b 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-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 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-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-9j50-0b-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-9j50-1b 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-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 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-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-10j50-0b-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-10j50-1b 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-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-11j50-0b 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-11j50-1b 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-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-7j80-0b 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-7j80-1b 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-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-8j80-0b 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-8j80-1b 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-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-9j80-0b 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-9j80-1b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-9j80-2b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-9j80-2b for the 2Step grid: fractional acceptance; fractional efficiency.
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