Showing 10 of 27 results
A search for long-lived particles decaying into hadrons is presented. The analysis uses 139 fb$^{-1}$ of $pp$ collision data collected at $\sqrt{s} = 13$ TeV by the ATLAS detector at the LHC using events that contain multiple energetic jets and a displaced vertex. The search employs dedicated reconstruction techniques that significantly increase the sensitivity to long-lived particles decaying in the ATLAS inner detector. Background estimates for Standard Model processes and instrumental effects are extracted from data. The observed event yields are compatible with those expected from background processes. The results are used to set limits at 95% confidence level on model-independent cross sections for processes beyond the Standard Model, and on scenarios with pair-production of supersymmetric particles with long-lived electroweakinos that decay via a small $R$-parity-violating coupling. The pair-production of electroweakinos with masses below 1.5 TeV is excluded for mean proper lifetimes in the range from 0.03 ns to 1 ns. When produced in the decay of $m(\tilde{g})=2.4$ TeV gluinos, electroweakinos with $m(\tilde\chi^0_1)=1.5$ TeV are excluded with lifetimes in the range of 0.02 ns to 4 ns.
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.
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.
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 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 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 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-7j80-0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-7j80-1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-7j80-2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-8j80-0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-8j80-1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-8j80-2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-9j80-0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-9j80-1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-9j80-2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-8j50-0b-MJ340. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-8j50-0b-MJ500. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-9j50-0b-MJ340. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-9j50-0b-MJ500. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-10j50-0b-MJ340. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-10j50-0b-MJ500. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
Degree of multijet closure for signal and vaidation regions (prior to the leptonic background fit) for the flavour stream with no b-jet requirement and a minimum transverse momentum of 50 GeV. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).
Degree of multijet closure for signal and vaidation regions (prior to the leptonic background fit) for the flavour stream with one inclusive b-jet required and a minimum transverse momentum of 50 GeV. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).
Degree of multijet closure for signal and vaidation regions (prior to the leptonic background fit) for the flavour stream with two inclusive b-jets required and a minimum transverse momentum of 50 GeV. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).
Degree of multijet closure for signal and vaidation regions (prior to the leptonic background fit) for the flavour stream with no b-jet requirement and a minimum transverse momentum of 80 GeV. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).
Degree of multijet closure for signal and vaidation regions (prior to the leptonic background fit) for the flavour stream with one inclusive b-jet required and a minimum transverse momentum of 80 GeV. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).
Degree of multijet closure for signal and vaidation regions (prior to the leptonic background fit) for the flavour stream with two inclusive b-jets required and a minimum transverse momentum of 80 GeV. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).
Degree of multijet closure for signal and vaidation regions (prior to the leptonic background fit) for the fat-jet stream with MJSigma above 340 GeV. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).
Degree of multijet closure for signal and vaidation regions (prior to the leptonic background fit) for the fat-jet stream with MJSigma above 500 GeV. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).
The best-expected signal region and the corresponding best-observed and best-expected CLs values for the 2Step grid.
The best-expected signal region and the corresponding best-observed and best-expected CLs values for the 2Step grid.
The best-expected signal region and the corresponding best-observed and best-expected CLs values for the 2Step grid.
The best-expected signal region and the corresponding best-observed and best-expected CLs values for the pMSSM grid.
The best-expected signal region and the corresponding best-observed and best-expected CLs values for the pMSSM grid.
The best-expected signal region and the corresponding best-observed and best-expected CLs values for the pMSSM grid.
The best-expected signal region and the corresponding best-observed and best-expected CLs values for the RPV grid.
The best-expected signal region and the corresponding best-observed and best-expected CLs values for the RPV grid.
The best-expected signal region and the corresponding best-observed and best-expected CLs values for the RPV grid.
The best-expected signal region and the corresponding best-observed and best-expected CLs values for the gtt off-shell grid.
The best-expected signal region and the corresponding best-observed and best-expected CLs values for the gtt off-shell grid.
The best-expected signal region and the corresponding best-observed and best-expected CLs values for the gtt off-shell grid.
95% CLs observed upper limit on model cross-section (in fb) for 2Step signal points for the best-expected signal region.
95% CLs observed upper limit on model cross-section (in fb) for RPV signal points for the best-expected signal region.
95% CLs observed upper limit on model cross-section (in fb) for gtt off-shell signal points for the best-expected signal region.
Performance of the SR-8j50-0b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-8j50-0b-MJ340 for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-8j50-0b-MJ500 for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-8j50-1b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-8j50-2b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-9j50-0b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-9j50-0b-MJ340 for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-9j50-0b-MJ500 for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-9j50-1b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-9j50-2b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-10j50-0b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-10j50-0b-MJ340 for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-10j50-0b-MJ500 for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-10j50-1b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-10j50-1b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-10j50-2b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-11j50-0b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-11j50-1b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-11j50-2b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-7j80-0b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-7j80-1b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-7j80-2b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-8j80-0b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-8j80-1b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-8j80-2b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-9j80-0b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-9j80-1b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-9j80-2b for the 2Step grid: fractional acceptance; fractional efficiency.
The results of a search for squarks and gluinos in final states with an isolated electron or muon, multiple jets and large missing transverse momentum using proton--proton collision data at a center-of-mass energy of $\sqrt{s}$ = 13 TeV are presented. The dataset used was recorded during 2015 and 2016 by the ATLAS experiment at the Large Hadron Collider and corresponds to an integrated luminosity of 36.1 $fb^{-1}$. No significant excess beyond the expected background is found. Exclusion limits at 95% confidence level are set in a number of supersymmetric scenarios, reaching masses up to 2.1 TeV for gluino pair production and up to 1.25 TeV for squark pair production.
Observed 95% CL exclusion contours for the gluino one-step x = 1/2 model.
Observed 95% CL exclusion contours for the gluino one-step x = 1/2 model.
Expected 95% CL exclusion contours for the gluino one-step x = 1/2 model.
Expected 95% CL exclusion contours for the gluino one-step x = 1/2 model.
Observed 95% CL exclusion contours for the gluino one-step variable-x model.
Observed 95% CL exclusion contours for the gluino one-step variable-x model.
Expected 95% CL exclusion contours for the gluino one-step variable-x model.
Expected 95% CL exclusion contours for the gluino one-step variable-x model.
Observed 95% CL exclusion contours for the squark one-step x = 1/2 model.
Observed 95% CL exclusion contours for the squark one-step x = 1/2 model.
Expected 95% CL exclusion contours for the squark one-step x = 1/2 model.
Expected 95% CL exclusion contours for the squark one-step x = 1/2 model.
Observed 95% CL exclusion contours for the squark one-step variable-x model.
Observed 95% CL exclusion contours for the squark one-step variable-x model.
Expected 95% CL exclusion contours for the squark one-step variable-x model.
Expected 95% CL exclusion contours for the squark one-step variable-x model.
Observed 95% CL exclusion contours for the gluino two-step model.
Observed 95% CL exclusion contours for the gluino two-step model.
Expected 95% CL exclusion contours for the gluino two-step model.
Expected 95% CL exclusion contours for the gluino two-step model.
Observed 95% CL exclusion contours for pMSSM model.
Observed 95% CL exclusion contours for pMSSM model.
Expected 95% CL exclusion contours for pMSSM model.
Expected 95% CL exclusion contours for pMSSM model.
$m_{\mathrm{eff}}$ distribution in 2J b-veto signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{eff}}$ distribution in 2J b-veto signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{eff}}$ distribution in 4J low-x b-veto signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{eff}}$ distribution in 4J low-x b-veto signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{eff}}$ distribution in 4J high-x b-veto signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{eff}}$ distribution in 4J high-x b-veto signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{eff}}$ distribution in 6J b-veto signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{eff}}$ distribution in 6J b-veto signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{eff}}$ distribution in 2J b-tag signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{eff}}$ distribution in 2J b-tag signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{eff}}$ distribution in 4J low-x b-tag signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{eff}}$ distribution in 4J low-x b-tag signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{eff}}$ distribution in 4J high-x b-tag signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{eff}}$ distribution in 4J high-x b-tag signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{eff}}$ distribution in 6J b-tag signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{eff}}$ distribution in 6J b-tag signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{eff}}$ distribution in 9J signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{eff}}$ distribution in 9J signal regions after fit. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{T}}$ distribution for events satisfying all the 2J b-veto signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{T}}$ distribution for events satisfying all the 2J b-veto signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$E_{\mathrm T}^{\mathrm{miss}}$ distribution for events satisfying all the 2J b-veto signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$E_{\mathrm T}^{\mathrm{miss}}$ distribution for events satisfying all the 2J b-veto signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{T}}$ distribution for events satisfying all the 2J b-tag signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{T}}$ distribution for events satisfying all the 2J b-tag signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$E_{\mathrm T}^{\mathrm{miss}}$ distribution for events satisfying all the 2J b-tag signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$E_{\mathrm T}^{\mathrm{miss}}$ distribution for events satisfying all the 2J b-tag signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{T}}$ distribution for events satisfying all the 4J low-x b-veto signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{T}}$ distribution for events satisfying all the 4J low-x b-veto signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$E_{\mathrm T}^{\mathrm{miss}}$ distribution for events satisfying all the 4J low-x b-veto signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$E_{\mathrm T}^{\mathrm{miss}}$ distribution for events satisfying all the 4J low-x b-veto signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{T}}$ distribution for events satisfying all the 4J low-x b-tag signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{T}}$ distribution for events satisfying all the 4J low-x b-tag signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$E_{\mathrm T}^{\mathrm{miss}}$ distribution for events satisfying all the 4J low-x b-tag signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$E_{\mathrm T}^{\mathrm{miss}}$ distribution for events satisfying all the 4J low-x b-tag signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{T}}$ distribution for events satisfying all the 4J high-x b-veto signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{T}}$ distribution for events satisfying all the 4J high-x b-veto signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$E_{\mathrm T}^{\mathrm{miss}}$ distribution for events satisfying all the 4J high-x b-veto signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$E_{\mathrm T}^{\mathrm{miss}}$ distribution for events satisfying all the 4J high-x b-veto signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{T}}$ distribution for events satisfying all the 4J high-x b-tag signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{T}}$ distribution for events satisfying all the 4J high-x b-tag signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$E_{\mathrm T}^{\mathrm{miss}}$ distribution for events satisfying all the 4J high-x b-tag signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$E_{\mathrm T}^{\mathrm{miss}}$ distribution for events satisfying all the 4J high-x b-tag signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{T}}$ distribution for events satisfying all the 6J b-veto signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{T}}$ distribution for events satisfying all the 6J b-veto signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$E_{\mathrm T}^{\mathrm{miss}}$ distribution for events satisfying all the 6J b-veto signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$E_{\mathrm T}^{\mathrm{miss}}$ distribution for events satisfying all the 6J b-veto signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{T}}$ distribution for events satisfying all the 6J b-tag signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{T}}$ distribution for events satisfying all the 6J b-tag signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$E_{\mathrm T}^{\mathrm{miss}}$ distribution for events satisfying all the 6J b-tag signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$E_{\mathrm T}^{\mathrm{miss}}$ distribution for events satisfying all the 6J b-tag signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{T}}$ distribution for events satisfying all the 9J signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
$m_{\mathrm{T}}$ distribution for events satisfying all the 9J signal region selections but for the one on the variable shown in the figure. The uncertainty bands plotted include all statistical and systematic uncertainties. The dashed lines stand for the benchmark signal samples.
Observed upper limits on the signal cross-section for gluino one-step x = 1/2 model.
Observed upper limits on the signal cross-section for gluino one-step x = 1/2 model.
Observed upper limits on the signal cross-section for gluino one-step variable-x model.
Observed upper limits on the signal cross-section for gluino one-step variable-x model.
Observed upper limits on the signal cross-section for squark one-step x = 1/2 model.
Observed upper limits on the signal cross-section for squark one-step x = 1/2 model.
Observed upper limits on the signal cross-section for squark one-step variable-x model.
Observed upper limits on the signal cross-section for squark one-step variable-x model.
Observed upper limits on the signal cross-section for gluino two-step model.
Observed upper limits on the signal cross-section for gluino two-step model.
Observed upper limits on the signal cross-section for pMSSM model.
Observed upper limits on the signal cross-section for pMSSM model.
Acceptance in 2J discovery signal region for gluino one-step x = 1/2 model.
Acceptance in 2J discovery signal region for gluino one-step x = 1/2 model.
Acceptance in 2J discovery signal region for squark one-step x = 1/2 model.
Acceptance in 2J discovery signal region for squark one-step x = 1/2 model.
Acceptance in 4J low-x discovery signal region for gluino one-step variable-x model.
Acceptance in 4J low-x discovery signal region for gluino one-step variable-x model.
Acceptance in 4J low-x discovery signal region for squark one-step variable-x model.
Acceptance in 4J low-x discovery signal region for squark one-step variable-x model.
Acceptance in 4J high-x discovery signal region for gluino one-step variable-x model.
Acceptance in 4J high-x discovery signal region for gluino one-step variable-x model.
Acceptance in 4J high-x discovery signal region for squark one-step variable-x model.
Acceptance in 4J high-x discovery signal region for squark one-step variable-x model.
Acceptance in 6J discovery signal region for gluino one-step x = 1/2 model.
Acceptance in 6J discovery signal region for gluino one-step x = 1/2 model.
Acceptance in 6J discovery signal region for squark one-step x = 1/2 model.
Acceptance in 6J discovery signal region for squark one-step x = 1/2 model.
Acceptance in 9J discovery signal region for pMSSM model.
Acceptance in 9J discovery signal region for pMSSM model.
Acceptance in 9J discovery signal region for gluino two-step model.
Acceptance in 9J discovery signal region for gluino two-step model.
Efficiency in 2J discovery signal region for gluino one-step x = 1/2 model.
Efficiency in 2J discovery signal region for gluino one-step x = 1/2 model.
Efficiency in 2J discovery signal region for squark one-step x = 1/2 model.
Efficiency in 2J discovery signal region for squark one-step x = 1/2 model.
Efficiency in 4J low-x discovery signal region for gluino one-step variable-x model.
Efficiency in 4J low-x discovery signal region for gluino one-step variable-x model.
Efficiency in 4J low-x discovery signal region for squark one-step variable-x model.
Efficiency in 4J low-x discovery signal region for squark one-step variable-x model.
Efficiency in 4J high-x discovery signal region for gluino one-step variable-x model.
Efficiency in 4J high-x discovery signal region for gluino one-step variable-x model.
Efficiency in 4J high-x discovery signal region for squark one-step variable-x model.
Efficiency in 4J high-x discovery signal region for squark one-step variable-x model.
Efficiency in 6J discovery signal region for gluino one-step x = 1/2 model.
Efficiency in 6J discovery signal region for gluino one-step x = 1/2 model.
Efficiency in 6J discovery signal region for squark one-step x = 1/2 model.
Efficiency in 6J discovery signal region for squark one-step x = 1/2 model.
Efficiency in 9J discovery signal region for pMSSM model.
Efficiency in 9J discovery signal region for pMSSM model.
Efficiency in 9J discovery signal region for gluino two-step model.
Efficiency in 9J discovery signal region for gluino two-step model.
Cutflow table for the 2J discovery signal region with a representative target signal model. The weighted numbers are normalized to 36.1 fb$^{-1}$ and rounded to the statistical error. The selection called "Filter" is introduced for initial data reduction. It selects events with at least one soft electron or muon ($3.5 < p_\mathrm{T} < 25$ GeV for muons and $4.5 < p_\mathrm{T} < 25$ GeV for electrons) in which an $E_\mathrm{T}^\mathrm{miss}$ trigger has fired or events with at least one hard electron or muon ($p_\mathrm{T} >$25 GeV).
Cutflow table for the 2J discovery signal region with a representative target signal model. The weighted numbers are normalized to 36.1 fb$^{-1}$ and rounded to the statistical error. The selection called "Filter" is introduced for initial data reduction. It selects events with at least one soft electron or muon ($3.5 < p_\mathrm{T} < 25$ GeV for muons and $4.5 < p_\mathrm{T} < 25$ GeV for electrons) in which an $E_\mathrm{T}^\mathrm{miss}$ trigger has fired or events with at least one hard electron or muon ($p_\mathrm{T} >$25 GeV).
Cutflow table for the 4J high-x discovery signal region with a representative target signal model. The weighted numbers are normalized to 36.1 fb$^{-1}$ and rounded to the statistical error. The selection called "Filter" is introduced for initial data reduction. It selects events with at least one soft electron or muon ($3.5 < p_\mathrm{T} < 25$ GeV for muons and $4.5 < p_\mathrm{T} < 25$ GeV for electrons) in which an $E_\mathrm{T}^\mathrm{miss}$ trigger has fired or events with at least one hard electron or muon ($p_\mathrm{T} >$25 GeV).
Cutflow table for the 4J high-x discovery signal region with a representative target signal model. The weighted numbers are normalized to 36.1 fb$^{-1}$ and rounded to the statistical error. The selection called "Filter" is introduced for initial data reduction. It selects events with at least one soft electron or muon ($3.5 < p_\mathrm{T} < 25$ GeV for muons and $4.5 < p_\mathrm{T} < 25$ GeV for electrons) in which an $E_\mathrm{T}^\mathrm{miss}$ trigger has fired or events with at least one hard electron or muon ($p_\mathrm{T} >$25 GeV).
Cutflow table for the 4J low-x discovery signal region (targetting gluino decays) with a representative target signal model. The weighted numbers are normalized to 36.1 fb$^{-1}$ and rounded to the statistical error. The selection called "Filter" is introduced for initial data reduction. It selects events with at least one soft electron or muon ($3.5 < p_\mathrm{T} < 25$ GeV for muons and $4.5 < p_\mathrm{T} < 25$ GeV for electrons) in which an $E_\mathrm{T}^\mathrm{miss}$ trigger has fired or events with at least one hard electron or muon ($p_\mathrm{T} >$25 GeV).
Cutflow table for the 4J low-x discovery signal region (targetting gluino decays) with a representative target signal model. The weighted numbers are normalized to 36.1 fb$^{-1}$ and rounded to the statistical error. The selection called "Filter" is introduced for initial data reduction. It selects events with at least one soft electron or muon ($3.5 < p_\mathrm{T} < 25$ GeV for muons and $4.5 < p_\mathrm{T} < 25$ GeV for electrons) in which an $E_\mathrm{T}^\mathrm{miss}$ trigger has fired or events with at least one hard electron or muon ($p_\mathrm{T} >$25 GeV).
Cutflow table for the 4J low-x discovery signal region (targetting squark decays) with a representative target signal model. The weighted numbers are normalized to 36.1 fb$^{-1}$ and rounded to the statistical error. The selection called "Filter" is introduced for initial data reduction. It selects events with at least one soft electron or muon ($3.5 < p_\mathrm{T} < 25$ GeV for muons and $4.5 < p_\mathrm{T} < 25$ GeV for electrons) in which an $E_\mathrm{T}^\mathrm{miss}$ trigger has fired or events with at least one hard electron or muon ($p_\mathrm{T} >$25 GeV).
Cutflow table for the 4J low-x discovery signal region (targetting squark decays) with a representative target signal model. The weighted numbers are normalized to 36.1 fb$^{-1}$ and rounded to the statistical error. The selection called "Filter" is introduced for initial data reduction. It selects events with at least one soft electron or muon ($3.5 < p_\mathrm{T} < 25$ GeV for muons and $4.5 < p_\mathrm{T} < 25$ GeV for electrons) in which an $E_\mathrm{T}^\mathrm{miss}$ trigger has fired or events with at least one hard electron or muon ($p_\mathrm{T} >$25 GeV).
Cutflow table for the 6J discovery signal region (targetting gluino decays) with a representative target signal model. The weighted numbers are normalized to 36.1 fb$^{-1}$ and rounded to the statistical error. The selection called "Filter" is introduced for initial data reduction. It selects events with at least one soft electron or muon ($3.5 < p_\mathrm{T} < 25$ GeV for muons and $4.5 < p_\mathrm{T} < 25$ GeV for electrons) in which an $E_\mathrm{T}^\mathrm{miss}$ trigger has fired or events with at least one hard electron or muon ($p_\mathrm{T} >$25 GeV).
Cutflow table for the 6J discovery signal region (targetting gluino decays) with a representative target signal model. The weighted numbers are normalized to 36.1 fb$^{-1}$ and rounded to the statistical error. The selection called "Filter" is introduced for initial data reduction. It selects events with at least one soft electron or muon ($3.5 < p_\mathrm{T} < 25$ GeV for muons and $4.5 < p_\mathrm{T} < 25$ GeV for electrons) in which an $E_\mathrm{T}^\mathrm{miss}$ trigger has fired or events with at least one hard electron or muon ($p_\mathrm{T} >$25 GeV).
Cutflow table for the 6J discovery signal region (targetting squark decays) with a representative target signal model. The weighted numbers are normalized to 36.1 fb$^{-1}$ and rounded to the statistical error. The selection called "Filter" is introduced for initial data reduction. It selects events with at least one soft electron or muon ($3.5 < p_\mathrm{T} < 25$ GeV for muons and $4.5 < p_\mathrm{T} < 25$ GeV for electrons) in which an $E_\mathrm{T}^\mathrm{miss}$ trigger has fired or events with at least one hard electron or muon ($p_\mathrm{T} >$25 GeV).
Cutflow table for the 6J discovery signal region (targetting squark decays) with a representative target signal model. The weighted numbers are normalized to 36.1 fb$^{-1}$ and rounded to the statistical error. The selection called "Filter" is introduced for initial data reduction. It selects events with at least one soft electron or muon ($3.5 < p_\mathrm{T} < 25$ GeV for muons and $4.5 < p_\mathrm{T} < 25$ GeV for electrons) in which an $E_\mathrm{T}^\mathrm{miss}$ trigger has fired or events with at least one hard electron or muon ($p_\mathrm{T} >$25 GeV).
Cutflow table for the 9J discovery signal region with a representative target signal model. The weighted numbers are normalized to 36.1 fb$^{-1}$ and rounded to the statistical error. The selection called "Filter" is introduced for initial data reduction. It selects events with at least one soft electron or muon ($3.5 < p_\mathrm{T} < 25$ GeV for muons and $4.5 < p_\mathrm{T} < 25$ GeV for electrons) in which an $E_\mathrm{T}^\mathrm{miss}$ trigger has fired or events with at least one hard electron or muon ($p_\mathrm{T} >$25 GeV).
Cutflow table for the 9J discovery signal region with a representative target signal model. The weighted numbers are normalized to 36.1 fb$^{-1}$ and rounded to the statistical error. The selection called "Filter" is introduced for initial data reduction. It selects events with at least one soft electron or muon ($3.5 < p_\mathrm{T} < 25$ GeV for muons and $4.5 < p_\mathrm{T} < 25$ GeV for electrons) in which an $E_\mathrm{T}^\mathrm{miss}$ trigger has fired or events with at least one hard electron or muon ($p_\mathrm{T} >$25 GeV).
A search for supersymmetry involving the pair production of gluinos decaying via third-generation squarks into the lightest neutralino ($\displaystyle\tilde\chi^0_1$) is reported. It uses LHC proton--proton collision data at a centre-of-mass energy $\sqrt{s} = 13$ TeV with an integrated luminosity of 36.1 fb$^{-1}$ collected with the ATLAS detector in 2015 and 2016. The search is performed in events containing large missing transverse momentum and several energetic jets, at least three of which must be identified as originating from $b$-quarks. To increase the sensitivity, the sample is divided into subsamples based on the presence or absence of electrons or muons. No excess is found above the predicted background. For $\displaystyle\tilde\chi^0_1$ masses below approximately 300 GeV, gluino masses of less than 1.97 (1.92) TeV are excluded at 95% confidence level in simplified models involving the pair production of gluinos that decay via top (bottom) squarks. An interpretation of the limits in terms of the branching ratios of the gluinos into third-generation squarks is also provided. These results improve upon the exclusion limits obtained with the 3.2 fb$^{-1}$ of data collected in 2015.
Observed 95% CL exclusion contour for Gtt model.
Observed 95% CL exclusion contour for Gtt model.
Observed 95% CL exclusion contour for Gtt model.
Observed 95% CL exclusion contour for Gtt model.
Expected 95% CL exclusion contour for Gtt model.
Expected 95% CL exclusion contour for Gtt model.
Expected 95% CL exclusion contour for Gtt model.
Expected 95% CL exclusion contour for Gtt model.
Observed 95% CL exclusion contour for Gbb model.
Observed 95% CL exclusion contour for Gbb model.
Observed 95% CL exclusion contour for Gbb model.
Observed 95% CL exclusion contour for Gbb model.
Expected 95% CL exclusion contour for Gbb model.
Expected 95% CL exclusion contour for Gbb model.
Expected 95% CL exclusion contour for Gbb model.
Expected 95% CL exclusion contour for Gbb model.
Expected 95% CL exclusion contour for Gluino mass = 1.8 TeV, Neutralino mass = 1 GeV.
Expected 95% CL exclusion contour for Gluino mass = 1.8 TeV, Neutralino mass = 1 GeV.
Expected 95% CL exclusion contour for Gluino mass = 1.8 TeV, Neutralino mass = 1 GeV.
Expected 95% CL exclusion contour for Gluino mass = 1.8 TeV, Neutralino mass = 1 GeV.
Observed 95% CL exclusion contour for Gluino mass = 1.8 TeV, Neutralino mass = 1 GeV.
Observed 95% CL exclusion contour for Gluino mass = 1.8 TeV, Neutralino mass = 1 GeV.
Observed 95% CL exclusion contour for Gluino mass = 1.8 TeV, Neutralino mass = 1 GeV.
Observed 95% CL exclusion contour for Gluino mass = 1.8 TeV, Neutralino mass = 1 GeV.
Expected 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 GeV.
Expected 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 GeV.
Expected 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 GeV.
Expected 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 GeV.
Observed 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 GeV.
Observed 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 GeV.
Observed 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 GeV.
Observed 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 GeV.
Expected 95% CL exclusion contour for Gluino mass = 2.0 TeV, Neutralino mass = 1 GeV.
Expected 95% CL exclusion contour for Gluino mass = 2.0 TeV, Neutralino mass = 1 GeV.
Expected 95% CL exclusion contour for Gluino mass = 2.0 TeV, Neutralino mass = 1 GeV.
Expected 95% CL exclusion contour for Gluino mass = 2.0 TeV, Neutralino mass = 1 GeV.
Observed 95% CL exclusion contour for Gluino mass = 2.0 TeV, Neutralino mass = 1 GeV.
Observed 95% CL exclusion contour for Gluino mass = 2.0 TeV, Neutralino mass = 1 GeV.
Observed 95% CL exclusion contour for Gluino mass = 2.0 TeV, Neutralino mass = 1 GeV.
Observed 95% CL exclusion contour for Gluino mass = 2.0 TeV, Neutralino mass = 1 GeV.
Expected 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 GeV.
Expected 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 GeV.
Expected 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 GeV.
Expected 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 GeV.
Observed 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 GeV.
Observed 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 GeV.
Observed 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 GeV.
Observed 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 GeV.
Expected 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 600 GeV.
Expected 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 600 GeV.
Expected 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 600 GeV.
Expected 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 600 GeV.
Observed 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 600 GeV.
Observed 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 600 GeV.
Observed 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 600 GeV.
Observed 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 600 GeV.
Expected 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 TeV.
Expected 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 TeV.
Expected 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 TeV.
Expected 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 TeV.
Observed 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 TeV.
Observed 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 TeV.
Observed 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 TeV.
Observed 95% CL exclusion contour for Gluino mass = 1.9 TeV, Neutralino mass = 1 TeV.
Distribution of ETMISS for SR-Gbb-VC.
Distribution of ETMISS for SR-Gbb-VC.
Distribution of ETMISS for SR-Gbb-VC.
Distribution of ETMISS for SR-Gbb-VC.
Distribution of ETMISS for SR-Gtt-1l-B.
Distribution of ETMISS for SR-Gtt-1l-B.
Distribution of ETMISS for SR-Gtt-1l-B.
Distribution of ETMISS for SR-Gtt-1l-B.
Distribution of ETMISS for SR-1L-II.
Distribution of ETMISS for SR-1L-II.
Distribution of ETMISS for SR-1L-II.
Distribution of ETMISS for SR-1L-II.
Distribution of ETMISS for SR-0L-HI.
Distribution of ETMISS for SR-0L-HI.
Distribution of ETMISS for SR-0L-HI.
Distribution of ETMISS for SR-0L-HI.
Distribution of ETMISS for SR-0L-HH.
Distribution of ETMISS for SR-0L-HH.
Distribution of ETMISS for SR-0L-HH.
Distribution of ETMISS for SR-0L-HH.
Acceptances for Gbb model in SR-Gbb-B.
Acceptances for Gbb model in SR-Gbb-B.
Acceptances for Gbb model in SR-Gbb-B.
Acceptances for Gbb model in SR-Gbb-B.
Acceptances for Gbb model in SR-Gbb-M.
Acceptances for Gbb model in SR-Gbb-M.
Acceptances for Gbb model in SR-Gbb-M.
Acceptances for Gbb model in SR-Gbb-M.
Acceptances for Gbb model in SR-Gbb-C.
Acceptances for Gbb model in SR-Gbb-C.
Acceptances for Gbb model in SR-Gbb-C.
Acceptances for Gbb model in SR-Gbb-C.
Acceptances for Gbb model in SR-Gbb-VC.
Acceptances for Gbb model in SR-Gbb-VC.
Acceptances for Gbb model in SR-Gbb-VC.
Acceptances for Gbb model in SR-Gbb-VC.
Acceptances for Gtt model in SR-Gtt-0l-B.
Acceptances for Gtt model in SR-Gtt-0l-B.
Acceptances for Gtt model in SR-Gtt-0l-B.
Acceptances for Gtt model in SR-Gtt-0l-B.
Acceptances for Gtt model in SR-Gtt-0l-M.
Acceptances for Gtt model in SR-Gtt-0l-M.
Acceptances for Gtt model in SR-Gtt-0l-M.
Acceptances for Gtt model in SR-Gtt-0l-M.
Acceptances for Gtt model in SR-Gtt-0l-C.
Acceptances for Gtt model in SR-Gtt-0l-C.
Acceptances for Gtt model in SR-Gtt-0l-C.
Acceptances for Gtt model in SR-Gtt-0l-C.
Acceptances for Gtt model in SR-Gtt-1l-B.
Acceptances for Gtt model in SR-Gtt-1l-B.
Acceptances for Gtt model in SR-Gtt-1l-B.
Acceptances for Gtt model in SR-Gtt-1l-B.
Acceptances for Gtt model in SR-Gtt-1l-M.
Acceptances for Gtt model in SR-Gtt-1l-M.
Acceptances for Gtt model in SR-Gtt-1l-M.
Acceptances for Gtt model in SR-Gtt-1l-M.
Acceptances for Gtt model in SR-Gtt-1l-C.
Acceptances for Gtt model in SR-Gtt-1l-C.
Acceptances for Gtt model in SR-Gtt-1l-C.
Acceptances for Gtt model in SR-Gtt-1l-C.
Experimental efficiencies for Gbb model in SR-Gbb-B.
Experimental efficiencies for Gbb model in SR-Gbb-B.
Experimental efficiencies for Gbb model in SR-Gbb-B.
Experimental efficiencies for Gbb model in SR-Gbb-B.
Experimental efficiencies for Gbb model in SR-Gbb-M.
Experimental efficiencies for Gbb model in SR-Gbb-M.
Experimental efficiencies for Gbb model in SR-Gbb-M.
Experimental efficiencies for Gbb model in SR-Gbb-M.
Experimental efficiencies for Gbb model in SR-Gbb-C.
Experimental efficiencies for Gbb model in SR-Gbb-C.
Experimental efficiencies for Gbb model in SR-Gbb-C.
Experimental efficiencies for Gbb model in SR-Gbb-C.
Experimental efficiencies for Gbb model in SR-Gbb-VC.
Experimental efficiencies for Gbb model in SR-Gbb-VC.
Experimental efficiencies for Gbb model in SR-Gbb-VC.
Experimental efficiencies for Gbb model in SR-Gbb-VC.
Experimental efficiencies for Gtt model in SR-Gtt-0l-B.
Experimental efficiencies for Gtt model in SR-Gtt-0l-B.
Experimental efficiencies for Gtt model in SR-Gtt-0l-B.
Experimental efficiencies for Gtt model in SR-Gtt-0l-B.
Experimental efficiencies for Gtt model in SR-Gtt-0l-M.
Experimental efficiencies for Gtt model in SR-Gtt-0l-M.
Experimental efficiencies for Gtt model in SR-Gtt-0l-M.
Experimental efficiencies for Gtt model in SR-Gtt-0l-M.
Experimental efficiencies for Gtt model in SR-Gtt-0l-C.
Experimental efficiencies for Gtt model in SR-Gtt-0l-C.
Experimental efficiencies for Gtt model in SR-Gtt-0l-C.
Experimental efficiencies for Gtt model in SR-Gtt-0l-C.
Experimental efficiencies for Gtt model in SR-Gtt-1l-B.
Experimental efficiencies for Gtt model in SR-Gtt-1l-B.
Experimental efficiencies for Gtt model in SR-Gtt-1l-B.
Experimental efficiencies for Gtt model in SR-Gtt-1l-B.
Experimental efficiencies for Gtt model in SR-Gtt-1l-M.
Experimental efficiencies for Gtt model in SR-Gtt-1l-M.
Experimental efficiencies for Gtt model in SR-Gtt-1l-M.
Experimental efficiencies for Gtt model in SR-Gtt-1l-M.
Experimental efficiencies for Gtt model in SR-Gtt-0l-C.
Experimental efficiencies for Gtt model in SR-Gtt-0l-C.
Experimental efficiencies for Gtt model in SR-Gtt-0l-C.
Experimental efficiencies for Gtt model in SR-Gtt-0l-C.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gbb model.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gbb model.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gbb model.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gbb model.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gbb model in SR-Gbb-B.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gbb model in SR-Gbb-B.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gbb model in SR-Gbb-B.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gbb model in SR-Gbb-B.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gbb model in SR-Gbb-M.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gbb model in SR-Gbb-M.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gbb model in SR-Gbb-M.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gbb model in SR-Gbb-M.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gbb model in SR-Gbb-C.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gbb model in SR-Gbb-C.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gbb model in SR-Gbb-C.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gbb model in SR-Gbb-C.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gbb model in SR-Gbb-VC.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gbb model in SR-Gbb-VC.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gbb model in SR-Gbb-VC.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gbb model in SR-Gbb-VC.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-0l-B.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-0l-B.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-0l-B.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-0l-B.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-0l-M.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-0l-M.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-0l-M.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-0l-M.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-0l-C.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-0l-C.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-0l-C.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-0l-C.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-1l-B.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-1l-B.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-1l-B.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-1l-B.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-1l-M.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-1l-M.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-1l-M.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-1l-M.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-1l-C.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-1l-C.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-1l-C.
95% CL upper limit on the cross-section times branching ratio (in fb) for the Gtt model in SR-Gtt-1l-C.
Observed 95% CL exclusion contour for Gbb model in SR-Gbb-B.
Observed 95% CL exclusion contour for Gbb model in SR-Gbb-B.
Observed 95% CL exclusion contour for Gbb model in SR-Gbb-B.
Observed 95% CL exclusion contour for Gbb model in SR-Gbb-B.
Expected 95% CL exclusion contour for Gbb model in SR-Gbb-B.
Expected 95% CL exclusion contour for Gbb model in SR-Gbb-B.
Expected 95% CL exclusion contour for Gbb model in SR-Gbb-B.
Expected 95% CL exclusion contour for Gbb model in SR-Gbb-B.
Observed 95% CL exclusion contour for Gbb model in SR-Gbb-M.
Observed 95% CL exclusion contour for Gbb model in SR-Gbb-M.
Observed 95% CL exclusion contour for Gbb model in SR-Gbb-M.
Observed 95% CL exclusion contour for Gbb model in SR-Gbb-M.
Expected 95% CL exclusion contour for Gbb model in SR-Gbb-M.
Expected 95% CL exclusion contour for Gbb model in SR-Gbb-M.
Expected 95% CL exclusion contour for Gbb model in SR-Gbb-M.
Expected 95% CL exclusion contour for Gbb model in SR-Gbb-M.
Observed 95% CL exclusion contour for Gbb model in SR-Gbb-C.
Observed 95% CL exclusion contour for Gbb model in SR-Gbb-C.
Observed 95% CL exclusion contour for Gbb model in SR-Gbb-C.
Observed 95% CL exclusion contour for Gbb model in SR-Gbb-C.
Expected 95% CL exclusion contour for Gbb model in SR-Gbb-C.
Expected 95% CL exclusion contour for Gbb model in SR-Gbb-C.
Expected 95% CL exclusion contour for Gbb model in SR-Gbb-C.
Expected 95% CL exclusion contour for Gbb model in SR-Gbb-C.
Observed 95% CL exclusion contour for Gbb model in SR-Gbb-VC.
Observed 95% CL exclusion contour for Gbb model in SR-Gbb-VC.
Observed 95% CL exclusion contour for Gbb model in SR-Gbb-VC.
Observed 95% CL exclusion contour for Gbb model in SR-Gbb-VC.
Expected 95% CL exclusion contour for Gbb model in SR-Gbb-VC.
Expected 95% CL exclusion contour for Gbb model in SR-Gbb-VC.
Expected 95% CL exclusion contour for Gbb model in SR-Gbb-VC.
Expected 95% CL exclusion contour for Gbb model in SR-Gbb-VC.
Observed 95% CL exclusion contour for Gtt model in SR-Gtt-0l-B.
Observed 95% CL exclusion contour for Gtt model in SR-Gtt-0l-B.
Observed 95% CL exclusion contour for Gtt model in SR-Gtt-0l-B.
Observed 95% CL exclusion contour for Gtt model in SR-Gtt-0l-B.
Expected 95% CL exclusion contour for Gtt model in SR-Gtt-0l-B.
Expected 95% CL exclusion contour for Gtt model in SR-Gtt-0l-B.
Expected 95% CL exclusion contour for Gtt model in SR-Gtt-0l-B.
Expected 95% CL exclusion contour for Gtt model in SR-Gtt-0l-B.
Observed 95% CL exclusion contour for Gtt model in SR-Gtt-0l-M.
Observed 95% CL exclusion contour for Gtt model in SR-Gtt-0l-M.
Observed 95% CL exclusion contour for Gtt model in SR-Gtt-0l-M.
Observed 95% CL exclusion contour for Gtt model in SR-Gtt-0l-M.
Expected 95% CL exclusion contour for Gtt model in SR-Gtt-0l-M.
Expected 95% CL exclusion contour for Gtt model in SR-Gtt-0l-M.
Expected 95% CL exclusion contour for Gtt model in SR-Gtt-0l-M.
Expected 95% CL exclusion contour for Gtt model in SR-Gtt-0l-M.
Observed 95% CL exclusion contour for Gtt model in SR-Gtt-0l-C.
Observed 95% CL exclusion contour for Gtt model in SR-Gtt-0l-C.
Observed 95% CL exclusion contour for Gtt model in SR-Gtt-0l-C.
Observed 95% CL exclusion contour for Gtt model in SR-Gtt-0l-C.
Expected 95% CL exclusion contour for Gtt model in SR-Gtt-0l-C.
Expected 95% CL exclusion contour for Gtt model in SR-Gtt-0l-C.
Expected 95% CL exclusion contour for Gtt model in SR-Gtt-0l-C.
Expected 95% CL exclusion contour for Gtt model in SR-Gtt-0l-C.
Observed 95% CL exclusion contour for Gtt model in SR-Gtt-1l-B.
Observed 95% CL exclusion contour for Gtt model in SR-Gtt-1l-B.
Observed 95% CL exclusion contour for Gtt model in SR-Gtt-1l-B.
Observed 95% CL exclusion contour for Gtt model in SR-Gtt-1l-B.
Expected 95% CL exclusion contour for Gtt model in SR-Gtt-1l-B.
Expected 95% CL exclusion contour for Gtt model in SR-Gtt-1l-B.
Expected 95% CL exclusion contour for Gtt model in SR-Gtt-1l-B.
Expected 95% CL exclusion contour for Gtt model in SR-Gtt-1l-B.
Observed 95% CL exclusion contour for Gtt model in SR-Gtt-1l-M.
Observed 95% CL exclusion contour for Gtt model in SR-Gtt-1l-M.
Observed 95% CL exclusion contour for Gtt model in SR-Gtt-1l-M.
Observed 95% CL exclusion contour for Gtt model in SR-Gtt-1l-M.
Expected 95% CL exclusion contour for Gtt model in SR-Gtt-1l-M.
Expected 95% CL exclusion contour for Gtt model in SR-Gtt-1l-M.
Expected 95% CL exclusion contour for Gtt model in SR-Gtt-1l-M.
Expected 95% CL exclusion contour for Gtt model in SR-Gtt-1l-M.
Observed 95% CL exclusion contour for Gtt model in SR-Gtt-1l-C.
Observed 95% CL exclusion contour for Gtt model in SR-Gtt-1l-C.
Observed 95% CL exclusion contour for Gtt model in SR-Gtt-1l-C.
Observed 95% CL exclusion contour for Gtt model in SR-Gtt-1l-C.
Expected 95% CL exclusion contour for Gtt model in SR-Gtt-1l-C.
Expected 95% CL exclusion contour for Gtt model in SR-Gtt-1l-C.
Expected 95% CL exclusion contour for Gtt model in SR-Gtt-1l-C.
Expected 95% CL exclusion contour for Gtt model in SR-Gtt-1l-C.
Expected number of signal events after each step of the Gbb-0L-B selection for a Gbb signal point (MGLUON,MNEUTRALINO) = (1900,1400) GeV.
Expected number of signal events after each step of the Gbb-0L-B selection for a Gbb signal point (MGLUON,MNEUTRALINO) = (1900,1400) GeV.
Expected number of signal events after each step of the Gbb-0L-B selection for a Gbb signal point (MGLUON,MNEUTRALINO) = (1900,1400) GeV.
Expected number of signal events after each step of the Gbb-0L-B selection for a Gbb signal point (MGLUON,MNEUTRALINO) = (1900,1400) GeV.
Expected number of signal events after each step of the Gbb-0L-M selection for a Gbb signal point (MGLUON,MNEUTRALINO) = (1900,1400) GeV.
Expected number of signal events after each step of the Gbb-0L-M selection for a Gbb signal point (MGLUON,MNEUTRALINO) = (1900,1400) GeV.
Expected number of signal events after each step of the Gbb-0L-M selection for a Gbb signal point (MGLUON,MNEUTRALINO) = (1900,1400) GeV.
Expected number of signal events after each step of the Gbb-0L-M selection for a Gbb signal point (MGLUON,MNEUTRALINO) = (1900,1400) GeV.
Expected number of signal events after each step of the Gbb-0L-C selection for a Gbb signal point (MGLUON,MNEUTRALINO) = (1900,1400) GeV.
Expected number of signal events after each step of the Gbb-0L-C selection for a Gbb signal point (MGLUON,MNEUTRALINO) = (1900,1400) GeV.
Expected number of signal events after each step of the Gbb-0L-C selection for a Gbb signal point (MGLUON,MNEUTRALINO) = (1900,1400) GeV.
Expected number of signal events after each step of the Gbb-0L-C selection for a Gbb signal point (MGLUON,MNEUTRALINO) = (1900,1400) GeV.
Expected number of signal events after each step of the Gbb-0L-VC selection for a Gbb signal point (MGLUON,MNEUTRALINO) = (1900,1400) GeV.
Expected number of signal events after each step of the Gbb-0L-VC selection for a Gbb signal point (MGLUON,MNEUTRALINO) = (1900,1400) GeV.
Expected number of signal events after each step of the Gbb-0L-VC selection for a Gbb signal point (MGLUON,MNEUTRALINO) = (1900,1400) GeV.
Expected number of signal events after each step of the Gbb-0L-VC selection for a Gbb signal point (MGLUON,MNEUTRALINO) = (1900,1400) GeV.
Expected number of signal events after each step of the Gtt-1L-B selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.
Expected number of signal events after each step of the Gtt-1L-B selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.
Expected number of signal events after each step of the Gtt-1L-B selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.
Expected number of signal events after each step of the Gtt-1L-B selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.
Expected number of signal events after each step of the Gtt-1L-M selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.
Expected number of signal events after each step of the Gtt-1L-M selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.
Expected number of signal events after each step of the Gtt-1L-M selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.
Expected number of signal events after each step of the Gtt-1L-M selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.
Expected number of signal events after each step of the Gtt-1L-C selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.
Expected number of signal events after each step of the Gtt-1L-C selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.
Expected number of signal events after each step of the Gtt-1L-C selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.
Expected number of signal events after each step of the Gtt-1L-C selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.
Expected number of signal events after each step of the Gtt-0L-B selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.
Expected number of signal events after each step of the Gtt-0L-B selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.
Expected number of signal events after each step of the Gtt-0L-B selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.
Expected number of signal events after each step of the Gtt-0L-B selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.
Expected number of signal events after each step of the Gtt-0L-M selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.
Expected number of signal events after each step of the Gtt-0L-M selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.
Expected number of signal events after each step of the Gtt-0L-M selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.
Expected number of signal events after each step of the Gtt-0L-M selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.
Expected number of signal events after each step of the Gtt-0L-C selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.
Expected number of signal events after each step of the Gtt-0L-C selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.
Expected number of signal events after each step of the Gtt-0L-C selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.
Expected number of signal events after each step of the Gtt-0L-C selection for a Gtt signal point (MGLUON,MNEUTRALINO) = (1900,1) GeV.
A search for strongly produced supersymmetric particles using signatures involving multiple energetic jets and either two isolated same-sign leptons ($e$ or $\mu$), or at least three isolated leptons, is presented. The analysis relies on the identification of $b$-jets and high missing transverse momentum to achieve good sensitivity. A data sample of proton--proton collisions at $\sqrt{s}= 13$ TeV recorded with the ATLAS detector at the Large Hadron Collider in 2015 and 2016, corresponding to a total integrated luminosity of 36.1 fb$^{-1}$, is used for the search. No significant excess over the Standard Model prediction is observed. The results are interpreted in several simplified supersymmetric models featuring $R$-parity conservation or $R$-parity violation, extending the exclusion limits from previous searches. In models considering gluino pair production, gluino masses are excluded up to 1.87 TeV at 95% confidence level. When bottom squarks are pair-produced and decay to a chargino and a top quark, models with bottom squark masses below 700 GeV and light neutralinos are excluded at 95% confidence level. In addition, model-independent limits are set on a possible contribution of new phenomena to the signal region yields.
Observed 95% CL exclusion contours on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay directly into the lightest neutralino via an offshell top squark, $\tilde g\to t\bar{t}\tilde{\chi}_1^0$.
Expected 95% CL exclusion contours on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay directly into the lightest neutralino via an offshell top squark, $\tilde g\to t\bar{t}\tilde{\chi}_1^0$.
Observed 95% CL exclusion contours on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Expected 95% CL exclusion contours on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Observed 95% CL exclusion contours on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade involving sleptons, $\tilde g\to q\bar{q}\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde\ell\ell/\tilde\nu\nu$ and $\tilde\ell/\tilde\nu\to \ell/\nu\tilde{\chi}_1^0$.
Expected 95% CL exclusion contours on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade involving sleptons, $\tilde g\to q\bar{q}\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde\ell\ell/\tilde\nu\nu$ and $\tilde\ell/\tilde\nu\to \ell/\nu\tilde{\chi}_1^0$.
Observed 95% CL exclusion contours on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Expected 95% CL exclusion contours on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Observed 95% CL exclusion contours on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an antitop squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$ or $\lambda^{''}_{323}$, $\tilde g\to \bar{t}\tilde{t}_1$ followed by $\tilde{t}_1\to \bar b\bar d / \bar b \bar s$.
Expected 95% CL exclusion contours on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an antitop squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$ or $\lambda^{''}_{323}$, $\tilde g\to \bar{t}\tilde{t}_1$ followed by $\tilde{t}_1\to \bar b\bar d / \bar b \bar s$.
Observed 95% CL exclusion contours on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an antitop squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{321}$, $\lambda^{''}_{311}$ or $\lambda^{''}_{322}$, $\tilde g\to \bar{t}\tilde{t}_1$ followed by $\tilde{t}_1\to \bar s\bar d /\bar d \bar d/\bar s \bar s$.
Expected 95% CL exclusion contours on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an antitop squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{321}$, $\lambda^{''}_{311}$ or $\lambda^{''}_{322}$, $\tilde g\to \bar{t}\tilde{t}_1$ followed by $\tilde{t}_1\to \bar s\bar d /\bar d \bar d/\bar s \bar s$.
Observed 95% CL exclusion contours on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay directly into the lightest neutralino, which in turn decays via non-zero baryon- and lepton-number-violating RPV couplings $\lambda^{'}_{ijk}$, $\tilde g\to q\bar{q}\tilde{\chi}_1^0$ followed by $\tilde{\chi}_1^0\to q\bar{q}^{'}\ell$.
Expected 95% CL exclusion contours on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay directly into the lightest neutralino, which in turn decays via non-zero baryon- and lepton-number-violating RPV couplings $\lambda^{'}_{ijk}$, $\tilde g\to q\bar{q}\tilde{\chi}_1^0$ followed by $\tilde{\chi}_1^0\to q\bar{q}^{'}\ell$.
Observed 95% CL exclusion contours on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay directly into a pair of top-antitop quarks and the lightest neutralino, which in turn decays into light quarks via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{ijk}$, $\tilde g\to t\bar{t}\tilde{\chi}_1^0$ followed by $\tilde{\chi}_1^0\to qqq$.
Expected 95% CL exclusion contours on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay directly into a pair of top-antitop quarks and the lightest neutralino, which in turn decays into light quarks via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{ijk}$, $\tilde g\to t\bar{t}\tilde{\chi}_1^0$ followed by $\tilde{\chi}_1^0\to qqq$.
Observed 95% CL upper limits on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay directly into the lightest neutralino via an offshell top squark, $\tilde g\to t\bar{t}\tilde{\chi}_1^0$. The table also shows the signal acceptance and reconstruction efficiency for the signal region(s) with sensitivity to this scenario.
Observed 95% CL upper limits on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$. The table also shows the signal acceptance and reconstruction efficiency for the signal region(s) with sensitivity to this scenario.
Observed 95% CL upper limits on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade involving sleptons, $\tilde g\to q\bar{q}\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde\ell\ell/\tilde\nu\nu$ and $\tilde\ell/\tilde\nu\to \ell/\nu\tilde{\chi}_1^0$. The table also shows the signal acceptance and reconstruction efficiency for the signal region(s) with sensitivity to this scenario.
Observed 95% CL upper limits on $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The table also shows the signal acceptance and reconstruction efficiency for the signal region(s) with sensitivity to this scenario.
Observed 95% CL upper limits on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an antitop squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$ or $\lambda^{''}_{323}$, $\tilde g\to \bar{t}\tilde{t}_1$ followed by $\tilde{t}_1\to \bar b\bar d / \bar b \bar s$. The table also shows the signal acceptance and reconstruction efficiency for the signal region(s) with sensitivity to this scenario.
Observed 95% CL upper limits on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an antitop squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{321}$, $\lambda^{''}_{311}$ or $\lambda^{''}_{322}$, $\tilde g\to \bar{t}\tilde{t}_1$ followed by $\tilde{t}_1\to \bar s\bar d /\bar d \bar d/\bar s \bar s$. The table also shows the signal acceptance and reconstruction efficiency for the signal region(s) with sensitivity to this scenario.
Observed 95% CL upper limits on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay directly into the lightest neutralino, which in turn decays via non-zero baryon- and lepton-number-violating RPV couplings $\lambda^{'}_{ijk}$, $\tilde g\to q\bar{q}\tilde{\chi}_1^0$ followed by $\tilde{\chi}_1^0\to q\bar{q}^{'}\ell$. The table also shows the signal acceptance and reconstruction efficiency for the signal region(s) with sensitivity to this scenario.
Observed 95% CL upper limits on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay directly into a pair of top-antitop quarks and the lightest neutralino, which in turn decays into light quarks via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{ijk}$, $\tilde g\to t\bar{t}\tilde{\chi}_1^0$ followed by $\tilde{\chi}_1^0\to qqq$. The table also shows the signal acceptance and reconstruction efficiency for the signal region(s) with sensitivity to this scenario.
Observed and expected 95% CL upper limits on $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate. The table also shows the signal acceptance and reconstruction efficiency for the signal region(s) with sensitivity to this scenario.
Observed and expected 95% CL upper limits on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario with non-universal Higgs masses (NUHM2, see the publication Refs. [31-32]). The table also shows the signal acceptance and reconstruction efficiency for the signal region(s) with sensitivity to this scenario.
Observed and expected 95% CL upper limits on $pp\to \tilde{d}^{}_\mathrm{R}\tilde{d}^{*}_\mathrm{R}$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an antitop squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$ or $\lambda^{''}_{323}$, $\tilde g\to \bar{t}\tilde{t}_1$ followed by $\tilde{t}_1\to \bar b\bar d / \bar b \bar s$. The table also shows the signal acceptance and reconstruction efficiency for the signal region(s) with sensitivity to this scenario.
Observed and expected 95% CL upper limits on $pp\to \tilde{d}^{}_\mathrm{R}\tilde{d}^{*}_\mathrm{R}$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an antitop squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{321}$, $\lambda^{''}_{311}$ or $\lambda^{''}_{322}$, $\tilde g\to \bar{t}\tilde{t}_1$ followed by $\tilde{t}_1\to \bar s\bar d /\bar d \bar d/\bar s \bar s$. The table also shows the signal acceptance and reconstruction efficiency for the signal region(s) with sensitivity to this scenario.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L2bS, in a SUSY scenario where gluinos are produced in pairs and decay directly into the lightest neutralino via an offshell top squark, $\tilde g\to t\bar{t}\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1500 GeV and $m(\tilde \chi_1^0)$ = 800 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L2bH, in a SUSY scenario where gluinos are produced in pairs and decay directly into the lightest neutralino via an offshell top squark, $\tilde g\to t\bar{t}\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1700 GeV and $m(\tilde \chi_1^0)$ = 200 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2Lsoft1b, in a SUSY scenario where gluinos are produced in pairs and decay directly into the lightest neutralino via offshell top squark and top quark, $\tilde g\to t\bar{b}W^{-}\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1200 GeV and $m(\tilde \chi_1^0)$ = 940 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2Lsoft2b, in a SUSY scenario where gluinos are produced in pairs and decay directly into the lightest neutralino via offshell top squark and top quark, $\tilde g\to t\bar{b}W^{-}\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1200 GeV and $m(\tilde \chi_1^0)$ = 900 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L0bS, in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1200 GeV, $m(\tilde \chi_1^\pm)$ = 1050 GeV, $m(\tilde \chi_2^0)$ = 975 GeV and $m(\tilde \chi_1^0)$ = 900 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L0bH, in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde \chi_1^\pm)$ = 850 GeV, $m(\tilde \chi_2^0)$ = 475 GeV and $m(\tilde \chi_1^0)$ = 100 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region Rpc3L0bS, in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade involving sleptons, $\tilde g\to q\bar{q}\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde\ell\ell/\tilde\nu\nu$ and $\tilde\ell/\tilde\nu\to \ell/\nu\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1400 GeV, $m(\tilde \chi_2^0)$ = 1250 GeV, $m(\tilde\ell)=m(\tilde\nu)$ = 1175 GeV and $m(\tilde \chi_1^0)$ = 1100 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region Rpc3L0bH, in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade involving sleptons, $\tilde g\to q\bar{q}\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde\ell\ell/\tilde\nu\nu$ and $\tilde\ell/\tilde\nu\to \ell/\nu\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1800 GeV, $m(\tilde \chi_2^0)$ = 950 GeV, $m(\tilde\ell)=m(\tilde\nu)$ = 475 GeV and $m(\tilde \chi_1^0)$ = 100 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L1bS, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 600 GeV, $m(\tilde \chi_1^\pm)$ = 350 GeV and $m(\tilde \chi_1^0)$ = 250 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L1bH, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 750 GeV, $m(\tilde \chi_1^\pm)$ = 200 GeV and $m(\tilde \chi_1^0)$ = 100 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region Rpc3LSS1b, in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate. The masses of the superpartners involved in the process are set to $m(\tilde{t}^{}_1)$ = 700 GeV, $m(\tilde \chi_2^0)$ = 525 GeV, $m(\tilde \chi_1^\pm)\approx m(\tilde \chi_1^0)$ = 425 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region Rpv2L1bH, in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an antitop squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{321}$, $\lambda^{''}_{311}$ or $\lambda^{''}_{322}$, $\tilde g\to \bar{t}\tilde{t}_1$ followed by $\tilde{t}_1\to \bar s\bar d /\bar d \bar d/\bar s \bar s$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1400 GeV, $m(\tilde{t}^{}_{1})$ = 800 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region Rpv2L0b, in a SUSY scenario where gluinos are produced in pairs and decay directly into the lightest neutralino, which in turn decays via non-zero baryon- and lepton-number-violating RPV couplings $\lambda^{'}_{ijk}$, $\tilde g\to q\bar{q}\tilde{\chi}_1^0$ followed by $\tilde{\chi}_1^0\to q\bar{q}^{'}\ell$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1400 GeV, $m(\tilde{\chi}_1^0)$ = 500 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region Rpv2L2bH, in a SUSY scenario where gluinos are produced in pairs and decay directly into a pair of top-antitop quarks and the lightest neutralino, which in turn decays into light quarks via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{ijk}$, $\tilde g\to t\bar{t}\tilde{\chi}_1^0$ followed by $\tilde{\chi}_1^0\to qqq$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1800 GeV, $m(\tilde{\chi}_1^0)$ = 200 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region Rpv2L2bS, in a SUSY scenario where pairs of down-down squark-rights are produced and decay into a pair of top and bottom quarks via a non-zero baryon-number-violating RPV coupling $\lambda^{''}_{331}$, $\tilde{d}^{}_\mathrm{R}\to \bar t\bar b$. The masses of the superpartners involved in the process are set to $m(\tilde{d}^{}_\mathrm{R})$ = 600 GeV, $m(\tilde g)$ = 2000 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region Rpv2L1bS, in a SUSY scenario where pairs of down-down squarks are produced and decay into a pair of top and a light quarks via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{321}$ or $\lambda^{''}_{322}$, $\tilde{d}^{}_\mathrm{R}\to \bar t\bar s/\bar t\bar d$. The masses of the superpartners involved in the process are set to $m(\tilde{d}^{}_\mathrm{R})$ = 600 GeV, $m(\tilde g)$ = 2000 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region Rpv2L1bM, in a SUSY scenario where pairs of down-down squarks are produced and decay into a pair of top and a light quarks via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{321}$ or $\lambda^{''}_{322}$, $\tilde{d}^{}_\mathrm{R}\to \bar t\bar s/\bar t\bar d$. The masses of the superpartners involved in the process are set to $m(\tilde{d}^{}_\mathrm{R})$ = 1000 GeV, $m(\tilde g)$ = 2000 GeV. Only statistical uncertainties are shown.
When you search on a word, e.g. 'collisions', we will automatically search across everything we store about a record. But, sometimes you may wish to be more specific. Here we show you how.
Guidance and examples on the query string syntax can be found in the Elasticsearch documentation.
About HEPData Submitting to HEPData HEPData File Formats HEPData Coordinators HEPData Terms of Use HEPData Cookie Policy
Status
Email
Forum
Twitter
GitHub
Copyright ~1975-Present, HEPData | Powered by Invenio, funded by STFC, hosted and originally developed at CERN, supported and further developed at IPPP Durham.