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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.
This Letter presents a search for heavy charged long-lived particles produced in proton-proton collisions at $\sqrt{s} = 13$ TeV at the LHC using a data sample corresponding to an integrated luminosity of 36.1 fb$^{-1}$ collected by the ATLAS experiment in 2015 and 2016. These particles are expected to travel with a velocity significantly below the speed of light, and therefore have a specific ionisation higher than any high-momentum Standard Model particle of unit charge. The pixel subsystem of the ATLAS detector is used in this search to measure the ionisation energy loss of all reconstructed charged particles which traverse the pixel detector. Results are interpreted assuming the pair production of $R$-hadrons as composite colourless states of a long-lived gluino and Standard Model partons. No significant deviation from Standard Model background expectations is observed, and lifetime-dependent upper limits on $R$-hadron production cross-sections and gluino masses are set, assuming the gluino always decays in two quarks and a stable neutralino. $R$-hadrons with lifetimes above 1.0 ns are excluded at the 95% confidence level, with lower limits on the gluino mass ranging between 1290 GeV and 2060 GeV. In the case of stable $R$-hadrons, the lower limit on the gluino mass at the 95% confidence level is 1890 GeV.
The number of events in each CR, VR, and SR for the predicted background, for the expected contribution from the signal model normalised to $36.1$ fb$^{-1}$, and in the observed data. The predicted background includes the statistical and systematic uncertainties, respectively. The uncertainty in the signal yield includes all systematic uncertainties except that in the theoretical cross-section.
The number of events in each CR, VR, and SR for the predicted background, for the expected contribution from the signal model normalised to $36.1$ fb$^{-1}$, and in the observed data. The predicted background includes the statistical and systematic uncertainties, respectively. The uncertainty in the signal yield includes all systematic uncertainties except that in the theoretical cross-section.
Expected number of $R$-hadron signal events at different stages of the selection, normalised to $36.1$ fb$^{-1}$. Shown for three different signal points is the number of events expected and the number of events expected in which the selected track has been matched to a generated $R$-hadron. If the gluino decays, it decays to a 100 GeV $\tilde{\chi}^{0}$ and SM quarks.
The observed and expected 95% CL upper limits on model-independent visible cross-sections, along with the observed $p0$ values, for the stable signal region, as a function of different mass windows, for which the lower bound is shown. The upper boundary on the mass window is 5 TeV for all windows.
The observed and expected 95% CL upper limits on model-independent visible cross-sections, along with the observed $p0$ values, for the metastable signal region, as a function of different mass windows, for which the lower bound is shown. The upper boundary on the mass window is 5 TeV for all windows.
For each gluino lifetime and mass in the signal samples, the lower boundary of the mass window in which at least $70\%$ of the reconstructed signal appears. The upper boundary for all mass windows is 5 TeV.
Acceptance and efficiency for a representative set of pair-produced gluino signal samples. The mass of the gluino ($m(\tilde{g})$), its lifetime ($\tau(\tilde{g})$) and the mass of the neutralino ($m(\tilde{\chi}^{0})$) are given in the first three columns. The Pythia 6.4.27 signal samples shown in this table are not reweighted to match the transverse momentum of the gluino-gluino system as simulated by MadGraph5_aMC@NLO. The acceptance is defined as the fraction of events passing a loose set of fiducial requirements. The full simulation efficiency (Full sim. $\epsilon$) is defined as the ratio of the number of reconstructed events, as expected by the full ATLAS simulation, and the number of events passing the fiducial requirements. The parameterised simulation efficiency (Param. sim. $\epsilon$) is defined as the ratio of the number of events estimated using a set of parametrised efficiencies (see auxiliary Figures 9,10,11,12) and the number of events passing the fiducial requirements alone.
The reconstructed candidate track mass distributions for observed data, predicted background, and the expected contribution from two signal models in the metastable R-hadron signal region. The yellow band around the background estimation includes both the statistical and systematic uncertainties.
The reconstructed candidate track mass distributions for observed data, predicted background, and the expected contribution from two signal models in the stable R-hadron signal region. The yellow band around the background estimation includes both the statistical and systematic uncertainties.
The 95% CL upper limit on the cross-section as a function of mass for gluinos with lifetime $\tau = 10$ ns decaying into $q\bar{q}$ and a 100 GeV neutralino, with the observed limit shown as a solid black line. The predicted production cross-section values are shown in purple along with their uncertainty. The expected upper limit in the case of only background is shown by the dashed black line, with a green $\pm 1\sigma$ and a yellow $\pm 2\sigma$ band.
The 95% CL upper limit on the cross-section as a function of mass for stable gluino $R$-hadrons, with the observed limit shown as a solid black line. The predicted production cross-section values are shown in purple along with their uncertainty. The expected upper limit in the case of only background is shown by the dashed black line, with a green $\pm 1\sigma$ and a yellow $\pm 2\sigma$ band.
Observed 95% lower limits on the gluino mass in the gluino lifetime--mass plane. The excluded area is to the left of the curves.
Expected 95% lower limits on the gluino mass in the gluino lifetime--mass plane. The excluded area is to the left of the curves.
The 95% CL upper limit on the cross-section as a function of mass for gluinos with lifetime $\tau = 1$ ns decaying into $q\bar{q}$ and a 100 GeV neutralino, with the observed limit shown as a solid black line. The predicted production cross-section values are shown in purple along with their uncertainty. The expected upper limit in the case of only background is shown by the dashed black line, with a green $\pm 1\sigma$ and a yellow $\pm 2\sigma$ band.
The 95% CL upper limit on the cross-section as a function of mass for gluinos with lifetime $\tau = 3$ ns decaying into $q\bar{q}$ and a 100 GeV neutralino, with the observed limit shown as a solid black line. The predicted production cross-section values are shown in purple along with their uncertainty. The expected upper limit in the case of only background is shown by the dashed black line, with a green $\pm 1\sigma$ and a yellow $\pm 2\sigma$ band.
The 95% CL upper limit on the cross-section as a function of mass for gluinos with lifetime $\tau = 30$ ns decaying into $q\bar{q}$ and a 100 GeV neutralino, with the observed limit shown as a solid black line. The predicted production cross-section values are shown in purple along with their uncertainty. The expected upper limit in the case of only background is shown by the dashed black line, with a green $\pm 1\sigma$ and a yellow $\pm 2\sigma$ band.
The 95% CL upper limit on the cross-section as a function of mass for gluinos with lifetime $\tau = 50$ ns decaying into $q\bar{q}$ and a 100 GeV neutralino, with the observed limit shown as a solid black line. The predicted production cross-section values are shown in purple along with their uncertainty. The expected upper limit in the case of only background is shown by the dashed black line, with a green $\pm 1\sigma$ and a yellow $\pm 2\sigma$ band.
The relationship between generated and reconstructed mass for gluino $R$-hadrons. Above 1500 GeV, the reconstructed mass falls below the generated mass due to bias in the reconstructed momentum. The uncertainty on the reconstructed mass is dominated by momentum uncertainty. The black dots represent the reconstructed mass computed as the most probable value of a Gaussian fit function, with the error bars showing its statistical uncertainty, while the orange band is the full-width at half maximum of the reconstructed mass distribution.
The parameterised efficiency for events to pass metastable event selections (including trigger, E$_{T}^{miss}$, and event cleaning requirements) as a function of the true E$_{T}^{miss}$ in the system, which is calculated at generator level. Event-level efficiencies are evaluated for events which have at least true E$_{T}^{miss} > 50$ GeV. The metastable event efficiencies are evaluated for different radial regions depending on the smallest radial distance, R, at which an R-hadron decays in the detector.
The parameterised efficiency for events to pass metastable event selections (including trigger, E$_{T}^{miss}$, and event cleaning requirements) as a function of the true E$_{T}^{miss}$ in the system, which is calculated at generator level. Event-level efficiencies are evaluated for events which have at least true E$_{T}^{miss} > 50$ GeV. The stable event efficiencies are evaluated for samples in which no R-hadron decays within the detector.
The parameterised efficiency for particles to pass full track selections in the metastable signal region, as function of the particle’s $\beta$, in different bins of transverse momentum, $p_{T}$, and for different radial decay positions of the particle. The efficiency is evaluated for particles which pass a loose set of fiducial requirements at generator level.
The parameterised efficiency for particles to pass full track selections in the metastable signal region, as function of the particle’s $\beta$, in different bins of transverse momentum, $p_{T}$, and for different radial decay positions of the particle. The efficiency is evaluated for particles which pass a loose set of fiducial requirements at generator level.
The parameterised efficiency for particles to pass full track selections in the metastable signal region, as function of the particle’s $\beta$, in different bins of transverse momentum, $p_{T}$, and for different radial decay positions of the particle. The efficiency is evaluated for particles which pass a loose set of fiducial requirements at generator level.
The parameterised efficiency for particles to pass full track selections in the metastable signal region, as function of the particle’s $\beta$, in different bins of transverse momentum, $p_{T}$, and for different radial decay positions of the particle. The efficiency is evaluated for particles which pass a loose set of fiducial requirements at generator level.
The parameterised efficiency for particles to pass full track selections in the metastable signal region, as function of the particle’s $\beta$, in different bins of transverse momentum, $p_{T}$, and for different radial decay positions of the particle. The efficiency is evaluated for particles which pass a loose set of fiducial requirements at generator level.
The parameterised efficiency for particles to pass full track selections in the metastable signal region, as function of the particle’s $\beta$, in different bins of transverse momentum, $p_{T}$. The stable efficiency is evaluated for samples which do not decay within the detector. The efficiency is evaluated for particles which pass a loose set of fiducial requirements at generator level.
This paper presents a search for direct electroweak gaugino or gluino pair production with a chargino nearly mass-degenerate with a stable neutralino. It is based on an integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ of $pp$ collisions at $\sqrt{s} = 13$ TeV collected by the ATLAS experiment at the LHC. The final state of interest is a disappearing track accompanied by at least one jet with high transverse momentum from initial-state radiation or by four jets from the gluino decay chain. The use of short track segments reconstructed from the innermost tracking layers significantly improves the sensitivity to short chargino lifetimes. The results are found to be consistent with Standard Model predictions. Exclusion limits are set at 95% confidence level on the mass of charginos and gluinos for different chargino lifetimes. For a pure wino with a lifetime of about 0.2 ns, chargino masses up to 460 GeV are excluded. For the strong production channel, gluino masses up to 1.65 TeV are excluded assuming a chargino mass of 460 GeV and lifetime of 0.2 ns.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the low-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($\tau_{\tilde{\chi}_{1}^{\pm}}$ = 0.2 ns and $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV) in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in electroweak channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of fake tracklet in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of muon background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of hadron and electron background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of signal ($m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}} = 500 GeV$) in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of total background in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the high-Emiss region.
Pixel-tracklet $p_{T}$ spectrum of observed data in strong channel in the high-Emiss region.
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 0.2 ns.
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Expected exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Observed exclusion limit at 95% CL obtained in the strong production channel in terms of the gluino and chargino masses. The limit is shown assuming a chargino lifetime 1.0 ns.
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Expected exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Observed exclusion limit at 95% CL obtained in the electroweak production channel in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Model dependent upper limits on cross-section (fb) for the electroweak production are shown by grey numbers in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Model dependent upper limits on cross-section (pb) for the electroweak production are shown by grey numbers in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Model dependent upper limits on cross-section (pb) for the electroweak production are shown by grey numbers in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Model dependent upper limits on cross-section (pb) for the electroweak production are shown by grey numbers in terms of the chargino lifetime ($\tau_{\tilde{\chi}_{1}^{\pm}}$) and mass ($m_{\tilde{\chi}_{1}^{\pm}}$).
Total acceptance $\times$ efficiency of the electroweak channel. The total signal acceptance $\times$ efficiency is defined as the probability of an event passing the signal region selection when an electroweak gaugino pair is produced in a pp collision.
Total acceptance $\times$ efficiency of the electroweak channel. The total signal acceptance $\times$ efficiency is defined as the probability of an event passing the signal region selection when an electroweak gaugino pair is produced in a pp collision.
Total acceptance $\times$ efficiency of the electroweak channel. The total signal acceptance $\times$ efficiency is defined as the probability of an event passing the signal region selection when an electroweak gaugino pair is produced in a pp collision.
Total acceptance $\times$ efficiency of the electroweak channel. The total signal acceptance $\times$ efficiency is defined as the probability of an event passing the signal region selection when an electroweak gaugino pair is produced in a pp collision.
Total acceptance $\times$ efficiency of the strong channel. In white regions, no simulation sample is available. The left-upper triangle region is not allowed kinematically in wino-LSP scenarios. The total signal acceptance $\times$ efficiency is calculated relative to events in which the gluinos decay into electroweak gaugino pairs.
Total acceptance $\times$ efficiency of the strong channel. In white regions, no simulation sample is available. The left-upper triangle region is not allowed kinematically in wino-LSP scenarios. The total signal acceptance $\times$ efficiency is calculated relative to events in which the gluinos decay into electroweak gaugino pairs.
Total acceptance $\times$ efficiency of the strong channel. In white regions, no simulation sample is available. The left-upper triangle region is not allowed kinematically in wino-LSP scenarios. The total signal acceptance $\times$ efficiency is calculated relative to events in which the gluinos decay into electroweak gaugino pairs.
Total acceptance $\times$ efficiency of the strong channel. In white regions, no simulation sample is available. The left-upper triangle region is not allowed kinematically in wino-LSP scenarios. The total signal acceptance $\times$ efficiency is calculated relative to events in which the gluinos decay into electroweak gaugino pairs.
The generator-level acceptance after reconstruction, for selecting and reconstructing charginos as a function of the chargino $eta$ and chargino decay radius (at generator level).
The generator-level acceptance for charginos produced in the electroweak channel as a function of the chargino $eta$ and chargino decay radius (at generator level).
The generator-level acceptance for charginos produced in the electroweak channel as a function of the chargino $eta$ and chargino decay radius (at generator level).
The generator-level acceptance for charginos produced in the electroweak channel as a function of the chargino $eta$ and chargino decay radius (at generator level).
The generator-level acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
The acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos produced in the electroweak channel as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
The acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos produced in the electroweak channel as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
The acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos produced in the electroweak channel as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
The generator-level acceptance after reconstruction, for selecting and reconstructing charginos as a function of the chargino $\eta$ and chargino decay radius (at generator level).
The generator-level acceptance for charginos produced in the strong channel as a function of the chargino $\eta$ and chargino decay radius (at generator level).
The generator-level acceptance for charginos produced in the strong channel as a function of the chargino $\eta$ and chargino decay radius (at generator level).
The generator-level acceptance for charginos produced in the strong channel as a function of the chargino $\eta$ and chargino decay radius (at generator level).
The generator-level acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
The acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos produced in the strong channel as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
The acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos produced in the strong channel as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
The acceptance $\times$ efficiency after reconstruction, for selecting and reconstructing charginos produced in the strong channel as a function of the chargino $\eta$ and chargino decay radius (at generator level). The acceptance $\times$ efficiency after reconstruction is the probability of a signal event, which passes all the event-level requirements, passing all the track/tracklet requirements after reconstruction.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in direct electroweak production with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in direct electroweak production with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in direct electroweak production with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in direct electroweak production with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in the strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in the strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in the strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
Summary of the selection criteria, and the corresponding observed number of events in data as well as the expected number of signal events in simulation for two benchmark models: a chargino produced in the strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. The expected number of signal events is normalised to 36.1 fb${}^{-1}$. The signal selection efficiencies are also shown in parentheses. The first row shows the number of events after the application of detector and data quality conditions. Requirements below the dashed line are applied to tracks and tracklets.
The event and tracklet generator-level acceptance and selection efficiency for a few electroweak signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
The event and tracklet generator-level acceptance and selection efficiency for a few electroweak signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
The event and tracklet generator-level acceptance and selection efficiency for a few electroweak signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
The event and tracklet generator-level acceptance and selection efficiency for a few electroweak signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
The event and tracklet generator-level acceptance and selection efficiency for a few strong signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
The event and tracklet generator-level acceptance and selection efficiency for a few strong signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
The event and tracklet generator-level acceptance and selection efficiency for a few strong signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
The event and tracklet generator-level acceptance and selection efficiency for a few strong signal models studied in this search. The last column shows the probability ($P$) for a reconstructed tracklet to have $p_{T}$ greater than 100 GeV.
Systematic uncertainties in the signal event yields at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. The uncertainty in the cross-section of the strong production is large due to the large effect from the PDF uncertainty.
Systematic uncertainties in the signal event yields at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. The uncertainty in the cross-section of the strong production is large due to the large effect from the PDF uncertainty.
Systematic uncertainties in the signal event yields at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. The uncertainty in the cross-section of the strong production is large due to the large effect from the PDF uncertainty.
Systematic uncertainties in the signal event yields at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. The uncertainty in the cross-section of the strong production is large due to the large effect from the PDF uncertainty.
Observed events, expected background for null signal, and expected signal yields for two benchmark models: electroweak channel with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) and strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. Also shown are the probability of a background-only experiment being more signal-like than observed ($p_0$) and the upper limit on the model-independent visible cross-section at 95\% CL. The uncertainty in the total background yield is different from the sum of uncertainties in quadrature due to anticorrelation between different backgrounds.
Observed events, expected background for null signal, and expected signal yields for two benchmark models: electroweak channel with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) and strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. Also shown are the probability of a background-only experiment being more signal-like than observed ($p_0$) and the upper limit on the model-independent visible cross-section at 95\% CL. The uncertainty in the total background yield is different from the sum of uncertainties in quadrature due to anti-correlation between different backgrounds.
Observed events, expected background for null signal, and expected signal yields for two benchmark models: electroweak channel with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) and strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. Also shown are the probability of a background-only experiment being more signal-like than observed ($p_0$) and the upper limit on the model-independent visible cross-section at 95\% CL. The uncertainty in the total background yield is different from the sum of uncertainties in quadrature due to anti-correlation between different backgrounds.
Observed events, expected background for null signal, and expected signal yields for two benchmark models: electroweak channel with ($m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (400 GeV, 0.2 ns) and strong channel with ($m_{\tilde{g}}$, $m_{\tilde{\chi}_{1}^{\pm}}$, $\tau_{\tilde{\chi}_{1}^{\pm}}$) = (1600 GeV, 500 GeV, 0.2 ns) in the high-Emiss region. Also shown are the probability of a background-only experiment being more signal-like than observed ($p_0$) and the upper limit on the model-independent visible cross-section at 95\% CL. The uncertainty in the total background yield is different from the sum of uncertainties in quadrature due to anti-correlation between different backgrounds.
Effects of systematic uncertainties on the signal exclusion significance at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. Effects of uncertainties on the fake-tracklet background is smaller in the strong channel analysis because the estimated number of the fake-tracket background events is small.
Effects of systematic uncertainties on the signal exclusion significance at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. Effects of uncertainties on the fake-tracklet background is smaller in the strong channel analysis because the estimated number of the fake-tracklet background events is small.
Effects of systematic uncertainties on the signal exclusion significance at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. Effects of uncertainties on the fake-tracklet background is smaller in the strong channel analysis because the estimated number of the fake-tracklet background events is small.
Effects of systematic uncertainties on the signal exclusion significance at $m_{\tilde{\chi}_{1}^{\pm}}$ = 400 GeV for the electroweak channel and at $m_{\tilde{g}}$ = 1600 GeV, $m_{\tilde{\chi}_{1}^{\pm}}$ = 500 GeV for the strong channel. The lifetime of the chargino is not relevant here. Effects of uncertainties on the fake-tracklet background is smaller in the strong channel analysis because the estimated number of the fake-tracklet background events is small.
Cross-section upper limits for the strong production, presented in unit of fb. Left-upper triangle region is unphysical because the wino mass is larger than the gluino mass.
Cross-section upper limits for the strong production, presented in unit of fb. Left-upper triangle region is unphysical because the wino mass is larger than the gluino mass.
Cross-section upper limits for the strong production, presented in unit of fb. Left-upper triangle region is unphysical because the wino mass is larger than the gluino mass.
Cross-section upper limits for the strong production, presented in unit of fb. Left-upper triangle region is unphysical because the wino mass is larger than the gluino mass.
A search for 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.
Many extensions of the Standard Model predict the existence of charged heavy long-lived particles, such as $R$-hadrons or charginos. These particles, if produced at the Large Hadron Collider, should be moving non-relativistically and are therefore identifiable through the measurement of an anomalously large specific energy loss in the ATLAS pixel detector. Measuring heavy long-lived particles through their track parameters in the vicinity of the interaction vertex provides sensitivity to metastable particles with lifetimes from 0.6 ns to 30 ns. A search for such particles with the ATLAS detector at the Large Hadron Collider is presented, based on a data sample corresponding to an integrated luminosity of 18.4 fb$^{-1}$ of $pp$ collisions at $\sqrt{s}$ = 8 TeV. No significant deviation from the Standard Model background expectation is observed, and lifetime-dependent upper limits on $R$-hadrons and chargino production are set. Gluino $R$-hadrons with 10 ns lifetime and masses up to 1185 GeV are excluded at 95$\%$ confidence level, and so are charginos with 15 ns lifetime and masses up to 482 GeV.
Ratio of the reconstructed mass, computed as the most probable value of a fit to a Landau distribution convolved with a Gaussian, to the generated mass, as a function of the generated mass for stable gluino R-hadrons, along with the half-width at half maximum of the reconstructed mass distribution normalised to the generated mass.
Efficiency for the calorimetric MET>80 GeV trigger as a function of the stable R-hadron mass.
Efficiency for the calorimetric MET>80 GeV trigger as a function of the metastable R-hadron mass. The R-hadron decays to g/qq plus neutralino of mass 100 GeV with a lifetime of 1 ns.
Efficiency for the calorimetric MET>80 GeV trigger as a function of the metastable R-hadron mass. The R-hadron decays to g/qq plus neutralino of mass = m(gluino) - 100 GeV with a lifetime of 1 ns.
Efficiency for the calorimetric MET>80 GeV trigger as a function of the metastable R-hadron mass. The R-hadron decays to g/qq plus neutralino of mass 100 GeV with a lifetime of 1 ns.
Efficiency for the calorimetric MET>80 GeV trigger as a function of the stable chargino mass.
Total selection efficiency as a function of the stable R-hadron mass.
Total selection efficiency as a function of the metastable R-hadron mass. The R-hadron decays to g/qq plus neutralino of mass 100 GeV with a lifetime of 10 ns.
Total selection efficiency as a function of the metastable R-hadron mass. The R-hadron decays to g/qq plus neutralino of mass = m(gluino) - 100 GeV with a lifetime of 10 ns.
Total selection efficiency as a function of the metastable R-hadron mass. The R-hadron decays to g/qq plus neutralino of mass 100 GeV with a lifetime of 1 ns.
Total selection efficiency as a function of the stable chargino mass.
Ionisation distribution of all the CR2 tracks, and those not matched to a reconstructed muon. The two distributions are normalised to their total number of entries.
Distribution of the mass of selected candidates, derived from the specific ionisation loss, for an example of gluino R-hadron signal, for searches for stable particles. The signal distributions are stacked on the expected background, and a narrower binning is used for them to allow the signal shape to be seen more clearly. The number of signal events is that expected according to the theoretical cross sections.
Distribution of the mass of selected candidates, derived from the specific ionisation loss, for one example of chargino signal, for searches for stable particles. The signal distributions are stacked on the expected background, and a narrower binning is used for them to allow the signal shape to be seen more clearly. The number of signal events is that expected according to the theoretical cross sections.
Distribution of the mass of selected candidates, derived from the specific ionisation loss, for background and data, for searches for stable particles. The expected background is shown with its total uncertainty (sum in quadrature of statistical, normalisation and systematic errors).
Distribution of the mass of selected candidates, derived from the specific ionisation loss, for an example of gluino R-hadron signal, for searches for metastable particles. The signal distributions are stacked on the expected background, and a narrower binning is used for them to allow the signal shape to be seen more clearly. The number of signal events is that expected according to the theoretical cross sections.
Distribution of the mass of selected candidates, derived from the specific ionisation loss, for an example of chargino signal, for searches for metastable particles. The signal distributions are stacked on the expected background, and a narrower binning is used for them to allow the signal shape to be seen more clearly. The number of signal events is that expected according to the theoretical cross sections.
Distribution of the mass of selected candidates, derived from the specific ionisation loss, for background and data. The expected background is shown with its total uncertainty (sum in quadrature of statistical, normalisation and systematic errors).
Theoretical values for the cross section of gluino pairs production with their uncertainty.
Expected upper limits on the production cross section as a function of mass for metastable gluino R-hadrons, with lifetime tau =10 ns, decaying into g/qq plus a light neutralino of mass 100 GeV, in the background-only case, with its 1 sigma band.
Observed 95 PCT upper limits on the production cross section as a function of mass for metastable gluino R-hadrons, with lifetime tau =10 ns, decaying into g/qq plus a light neutralino of mass 100 GeV.
Expected upper limits on the production cross section as a function of mass for metastable gluino R-hadrons, with lifetime tau =10 ns, decaying into g/qq plus a heavy neutralino of mass(gluino) - 100 GeV, in the background-only case, with its 1 sigma band.
Observed 95 PCT upper limits on the production cross section as a function of mass for metastable gluino R-hadrons, with lifetime tau =10 ns, decaying into g/qq plus a heavy neutralino of mass(gluino) - 100 GeV.
The expected excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into g/qq plus a light neutralino of mass 100 GeV, with respect to the nominal theoretical cross section.
The expected excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into g/qq plus a light neutralino of mass 100 GeV, with respect to the nominal theoretical cross section, plus 1 experimental sigma.
The expected excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into g/qq plus a light neutralino of mass 100 GeV, with respect to the nominal theoretical cross section, minus 1 experimental sigma.
The observed excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into g/qq plus a light neutralino of mass 100 GeV, with respect to the nominal theoretical cross section.
The observed excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into g/qq plus a light neutralino of mass 100 GeV, with respect to the nominal theoretical cross section minus its uncertainty.
The observed excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into g/qq plus a light neutralino of mass 100 GeV, with respect to the nominal theoretical cross section plus its uncertainty.
The expected excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into g/qq plus a heavy neutralino of mass = m(gluino) - 100 GeV, with respect to the nominal theoretical cross section.
The expected excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into g/qq plus a heavy neutralino of mass = m(gluino) - 100 GeV, with respect to the nominal theoretical cross section, plus 1 experimental sigma.
The expected excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into g/qq plus a heavy neutralino of mass = m(gluino) - 100 GeV, with respect to the nominal theoretical cross section, minus 1 experimental sigma.
The observed excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into g/qq plus a heavy neutralino of mass = m(gluino) - 100 GeV, with respect to the nominal theoretical cross section.
The observed excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into g/qq plus a heavy neutralino of mass = m(gluino) - 100 GeV, with respect to the nominal theoretical cross section minus its uncertainty.
The observed excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into g/qq plus a heavy neutralino of mass = m(gluino) - 100 GeV, with respect to the nominal theoretical cross section plus its uncertainty.
Expected upper limits on the production cross section as a function of mass for metastable gluino R-hadrons, with lifetime tau =10 ns, decaying into tt plus a light neutralino of mass 100 GeV, in the background-only case, with its 1 sigma band.
Observed 95 PCT upper limits on the production cross section as a function of mass for metastable gluino R-hadrons, with lifetime tau =10 ns, decaying into tt plus a light neutralino of mass 100 GeV.
Expected upper limits on the production cross section as a function of mass for metastable gluino R-hadrons, with lifetime tau =10 ns, decaying into tt plus a heavy neutralino of mass(gluino) - 100 GeV, in the background-only case, with its 1 sigma band.
Observed 95 PCT upper limits on the production cross section as a function of mass for metastable gluino R-hadrons, with lifetime tau =10 ns, decaying into tt plus a heavy neutralino of mass(gluino) - 100 GeV.
The expected excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into tt plus a light neutralino of mass 100 GeV, with respect to the nominal theoretical cross section.
The expected excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into tt plus a light neutralino of mass 100 GeV, with respect to the nominal theoretical cross section, plus 1 experimental sigma.
The expected excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into tt plus a light neutralino of mass 100 GeV, with respect to the nominal theoretical cross section, minus 1 experimental sigma.
The observed excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into tt plus a light neutralino of mass 100 GeV, with respect to the nominal theoretical cross section.
The observed excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into tt plus a light neutralino of mass 100 GeV, with respect to the nominal theoretical cross section minus its uncertainty.
The observed excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into tt plus a light neutralino of mass 100 GeV, with respect to the nominal theoretical cross section plus its uncertainty.
The expected excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into tt plus a heavy neutralino of mass = m(gluino) - 100 GeV, with respect to the nominal theoretical cross section.
The expected excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into tt plus a heavy neutralino of mass = m(gluino) - 100 GeV, with respect to the nominal theoretical cross section, plus 1 experimental sigma.
The expected excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into tt plus a heavy neutralino of mass = m(gluino) - 100 GeV, with respect to the nominal theoretical cross section, minus 1 experimental sigma.
The observed excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into tt plus a heavy neutralino of mass = m(gluino) - 100 GeV, with respect to the nominal theoretical cross section.
The observed excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into tt plus a heavy neutralino of mass = m(gluino) - 100 GeV, with respect to the nominal theoretical cross section minus its uncertainty.
The observed excluded range of lifetimes as a function of gluino mass for gluino R-hadrons decaying into tt plus a heavy neutralino of mass = m(gluino) - 100 GeV, with respect to the nominal theoretical cross section plus its uncertainty.
Theoretical values for the production cross section of charginos or chargino/neutralino pairs, with their uncertainty.
Expected upper limits on the production cross section as a function of mass for metastable charginos, with lifetime tau =1.0 ns, decaying into neutralino + pion, in the background-only case, with its 1 sigma band.
Observed 95 PCT upper limits on the production cross section as a function of mass for metastable charginos, with lifetime tau =1.0 ns, decaying into neutralino + pion.
The expected excluded range of lifetimes as a function of chargino mass for charginos decaying into neutralino plus pion, with respect to the nominal theoretical cross section.
The expected excluded range of lifetimes as a function of chargino mass for charginos decaying into neutralino plus pion, with respect to the nominal theoretical cross section, plus 1 experimental sigma.
The expected excluded range of lifetimes as a function of chargino mass for charginos decaying into neutralino plus pion, with respect to the nominal theoretical cross section, minus 1 experimental sigma.
The observed excluded range of lifetimes as a function of chargino mass for charginos decaying into neutralino plus pion, with respect to the nominal theoretical cross section.
The observed excluded range of lifetimes as a function of chargino mass for charginos decaying into neutralino plus pion, with respect to the nominal theoretical cross section minus its uncertainty.
The observed excluded range of lifetimes as a function of gluino mass for chargino mass for charginos decaying into neutralino plus pion, with respect to the nominal theoretical cross section plus its uncertainty.
dEdx ionization for data, 1 TeV gluino R-hadrons stable and decaying in 100 GeV neutralinos with a 10 ns lifetime and for charginos of 350 GeV. Tracks that fulfil all the requirements up to including the High-m_T (see Tab.1 in the paper) are considered at this stage and normalised to an integrated luminosity of 18.4 fb^-1.
Expected upper limits on the production cross section as a function of mass for stable gluino R-hadrons, in case of background only, with its 1 sigma band.
Observed 95 PCT upper limits on the production cross section as a function of mass for stable gluino R-hadrons.
Theoretical values for the cross section of squark pairs production with their uncertainty.
Expected upper limits on the production cross section as a function of mass for stable sbottom R-hadrons, in case of background only, with its 1 sigma band.
Observed 95 PCT upper limits on the production cross section as a function of mass for stable sbottom $R$-hadrons. Cross section IN PB.
Expected upper limits on the production cross section as a function of mass for stop R-hadrons, in case of background only, with its 1 sigma band.
Observed 95 PCT upper limits on the production cross section as a function of mass for stop R-hadrons.
Expected upper limits on the production cross section as a function of mass for stable charginos, in case of background only, with its 1 sigma band.
Observed 95 PCT upper limits on the production cross section as a function of mass for stable charginos.
Expected upper limits on the production cross section as a function of mass for metastable gluino R-hadrons, with lifetime tau=1.0 ns, decaying to g/qq plus a light neutralino of mass 100 GeV.
Observed 95 PCT upper limits on the production cross section as a function of mass for metastable gluino R-hadrons, with lifetime tau=1.0 ns, decaying to g/qq plus a light neutralino of mass 100 GeV.
Expected upper limits on the production cross section as a function of mass for metastable gluino R-hadrons, with lifetime tau=1.0 ns, decaying to g/qq plus a heavy neutralino of mass = m(gluino) - 100 GeV.
Observed 95 PCT upper limits on the production cross section as a function of mass for metastable gluino R-hadrons, with lifetime tau=1.0 ns, decaying to g/qq plus a heavy neutralino of mass = m(gluino) - 100 GeV.
Expected upper limits on the production cross section as a function of mass for metastable gluino R-hadrons, with lifetime tau=1.0 ns, decaying to tt plus a light neutralino of mass 100 GeV.
Observed 95 PCT upper limits on the production cross section as a function of mass for metastable gluino R-hadrons, with lifetime tau=1.0 ns, decaying to tt plus a light neutralino of mass 100 GeV.
Expected upper limits on the production cross section as a function of mass for metastable gluino R-hadrons, with lifetime tau=1.0 ns, decaying to tt plus a heavy neutralino of mass = m(gluino) - 100 GeV.
Observed 95 PCT upper limits on the production cross section as a function of mass for metastable gluino R-hadrons, with lifetime tau=1.0 ns, decaying to tt plus a heavy neutralino of mass = m(gluino) - 100 GeV.
Expected upper limits on the production cross section as a function of mass for metastable charginos, with lifetime tau =15 ns, decaying to neutralino and pion, in case of background only, with its 1 sigma band.
Observed 95 PCT upper limits on the production cross section as a function of mass for metastable charginos, with lifetime tau =15 ns, decaying to neutralino and pion, in case of background only, with its 1 sigma band.
A search for new phenomena in final states characterized by high jet multiplicity, an isolated lepton (electron or muon) and either zero or at least three $b$-tagged jets is presented. The search uses 36.1 fb$^{-1}$ of $\sqrt{s}$ = 13 TeV proton-proton collision data collected by the ATLAS experiment at the Large Hadron Collider in 2015 and 2016. The dominant sources of background are estimated using parameterized extrapolations, based on observables at medium jet multiplicity, to predict the $b$-tagged jet multiplicity distribution at the higher jet multiplicities used in the search. No significant excess over the Standard Model expectation is observed and 95% confidence-level limits are extracted constraining four simplified models of $R$-parity-violating supersymmetry that feature either gluino or top-squark pair production. The exclusion limits reach as high as 2.1 TeV in gluino mass and 1.2 TeV in top-squark mass in the models considered. In addition, an upper limit is set on the cross-section for Standard Model $t\bar{t}t\bar{t}$ production of 60 fb (6.5 $\times$ the Standard Model prediction) at 95% confidence level. Finally, model-independent limits are set on the contribution from new phenomena to the signal-region yields.
The expected background and observed data with five jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with five jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with six jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with six jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with seven jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with seven jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with eight jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with eight jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with nine jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with nine jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with ten jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with ten jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with eleven jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with eleven jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with twelve-or-more jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with twelve-or-more jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with five jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with five jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with six jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with six jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with seven jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with seven jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with eight jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with eight jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with nine jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with nine jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with ten-or-more jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with ten-or-more jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with five jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with five jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with six jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with six jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with seven jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with seven jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with eight jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with eight jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with nine jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with nine jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with ten-or-more jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
The expected background and observed data with ten-or-more jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.
Observed exclusion contours on the gluino and neutralino masses in a model where the gluino decays via a virtual top squark to two top quarks and the lightest neutralino, with the neutralino decaying to three light quarks (neutralino --> uds) via the RPV coupling lambda''_112.
Observed exclusion contours on the gluino and neutralino masses in a model where the gluino decays via a virtual top squark to two top quarks and the lightest neutralino, with the neutralino decaying to three light quarks (neutralino --> uds) via the RPV coupling lambda''_112.
Expected exclusion contours on the gluino and neutralino masses in a model where the gluino decays via a virtual top squark to two top quarks and the lightest neutralino, with the neutralino decaying to three light quarks (neutralino --> uds) via the RPV coupling lambda''_112.
Expected exclusion contours on the gluino and neutralino masses in a model where the gluino decays via a virtual top squark to two top quarks and the lightest neutralino, with the neutralino decaying to three light quarks (neutralino --> uds) via the RPV coupling lambda''_112.
Observed exclusion contours on the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.
Observed exclusion contours on the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.
Expected exclusion contours on the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.
Expected exclusion contours on the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.
Observed exclusion contours on the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.
Observed exclusion contours on the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.
Expected exclusion contours on the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.
Expected exclusion contours on the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.
Observed exclusion contours on the stop and neutralino masses in a model where the stop decays to a third-generation quark and a higgsino, which decays via the RPV coupling lambda''_323.
Observed exclusion contours on the stop and neutralino masses in a model where the stop decays to a third-generation quark and a higgsino, which decays via the RPV coupling lambda''_323.
Expected exclusion contours on the stop and neutralino masses in a model where the stop decays to a third-generation quark and a higgsino, which decays via the RPV coupling lambda''_323.
Expected exclusion contours on the stop and neutralino masses in a model where the stop decays to a third-generation quark and a higgsino, which decays via the RPV coupling lambda''_323.
Observed exclusion contours on the stop and neutralino masses in a model where the stop decays to a top and a bino-like neutralino, which decays via the RPV coupling lambda''_323.
Observed exclusion contours on the stop and neutralino masses in a model where the stop decays to a top and a bino-like neutralino, which decays via the RPV coupling lambda''_323.
Expected exclusion contours on the stop and neutralino masses in a model where the stop decays to a top and a bino-like neutralino, which decays via the RPV coupling lambda''_323.
Expected exclusion contours on the stop and neutralino masses in a model where the stop decays to a top and a bino-like neutralino, which decays via the RPV coupling lambda''_323.
Observed upper limits on the model cross-section in units of pb as a function of the gluino and neutralino masses in a model where the gluino decays via a virtual top squark to two top quarks and the lightest neutralino, with the neutralino decaying to three light quarks (neutralino --> uds) via the RPV coupling lambda''_112.
Observed upper limits on the model cross-section in units of pb as a function of the gluino and neutralino masses in a model where the gluino decays via a virtual top squark to two top quarks and the lightest neutralino, with the neutralino decaying to three light quarks (neutralino --> uds) via the RPV coupling lambda''_112.
Observed upper limits on the model cross-section in units of pb as a function of the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.
Observed upper limits on the model cross-section in units of pb as a function of the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.
Observed upper limits on the model cross-section in units of pb as a function of the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.
Observed upper limits on the model cross-section in units of pb as a function of the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.
Observed upper limits on the model cross-section in units of pb as a function of the stop and neutralino masses in a model where the stop decays to a third-generation quark and a higgsino, which decays via the RPV coupling lambda''_323.
Observed upper limits on the model cross-section in units of pb as a function of the stop and neutralino masses in a model where the stop decays to a third-generation quark and a higgsino, which decays via the RPV coupling lambda''_323.
Observed upper limits on the model cross-section in units of pb as a function of the stop and neutralino masses in a model where the stop decays to a top and a bino-like neutralino, which decays via the RPV coupling lambda''_323.
Observed upper limits on the model cross-section in units of pb as a function of the stop and neutralino masses in a model where the stop decays to a top and a bino-like neutralino, which decays via the RPV coupling lambda''_323.
Acceptance as a function of the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.
Acceptance as a function of the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.
Efficiency as a function of the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.
Efficiency as a function of the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.
Acceptance as a function of the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.
Acceptance as a function of the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.
Efficiency as a function of the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.
Efficiency as a function of the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.
Cut flow for a model of gluino pair production where the gluino decays to two (u, d, s, c) quarks and the neutralino, which then decays to two (u, d, s, c) quarks and a lepton via a lambda' RPV coupling, where each RPV decay can produce any of the four first and second generation leptons (e, mu, nu_e, nu_mu) with equal probability (m_gluino = 1800 GeV, m_neutralino = 900 GeV). The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies pT > 25 GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed.
Cut flow for a model of gluino pair production where the gluino decays to two (u, d, s, c) quarks and the neutralino, which then decays to two (u, d, s, c) quarks and a lepton via a lambda' RPV coupling, where each RPV decay can produce any of the four first and second generation leptons (e, mu, nu_e, nu_mu) with equal probability (m_gluino = 1800 GeV, m_neutralino = 900 GeV). The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies pT > 25 GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed.
Cut flow for a model of gluino pair production where each gluino decays to a top quark and a top squark, with the top squark decaying to an s- and a b- quark via a non-zero lambda''_323 RPV coupling (m_gluino = 1600 GeV, m_stop = 1000 GeV). The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies pT > 25 GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed.
Cut flow for a model of gluino pair production where each gluino decays to a top quark and a top squark, with the top squark decaying to an s- and a b- quark via a non-zero lambda''_323 RPV coupling (m_gluino = 1600 GeV, m_stop = 1000 GeV). The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies pT > 25 GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed.
Cut flow for a model of gluino pair production where each gluino decays via an off-shell top squark to two top quarks and the lightest neutralino, with the neutralino decaying to three light quarks (neutralino -> uds) via the RPV coupling lambda''_112 (m_gluino = 2000 GeV, m_neutralino = 941 GeV). The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies pT > 25 GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed.
Cut flow for a model of gluino pair production where each gluino decays via an off-shell top squark to two top quarks and the lightest neutralino, with the neutralino decaying to three light quarks (neutralino -> uds) via the RPV coupling lambda''_112 (m_gluino = 2000 GeV, m_neutralino = 941 GeV). The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies pT > 25 GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed.
Cut flow for a model of right-handed top squark pair production with the top squark decaying to the lightest supersymmetric particle (LSP) which is considered to be purely higgsino. The higgsino-like LSP decays through the non-zero RPV coupling lambda''_323 (m_stop = 975 GeV, m_neutralino = 600 GeV). The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies pT > 25 GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed.
Cut flow for a model of right-handed top squark pair production with the top squark decaying to the lightest supersymmetric particle (LSP) which is considered to be purely higgsino. The higgsino-like LSP decays through the non-zero RPV coupling lambda''_323 (m_stop = 975 GeV, m_neutralino = 600 GeV). The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies pT > 25 GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed.
Results are reported of a search for new phenomena, such as supersymmetric particle production, that could be observed in high-energy proton--proton collisions. Events with large numbers of jets, together with missing transverse momentum from unobserved particles, are selected. The data analysed were recorded by the ATLAS experiment during 2015 using the 13 TeV centre-of-mass proton--proton collisions at the Large Hadron Collider, and correspond to an integrated luminosity of 3.2 fb$^{-1}$. The search selected events with various jet multiplicities from $\ge 7$ to $\ge 10$ jets, and with various $b$-jet multiplicity requirements to enhance sensitivity. No excess above Standard Model expectations is observed. The results are interpreted within two supersymmetry models, where gluino masses up to 1400 GeV are excluded at 95% confidence level, significantly extending previous limits.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in validation region 7ej50 0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in validation region 6ej80 0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 10j50 0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 10j50 2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 8j80 0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 8j80 2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
Observed 95% CL limit for the pMSSM grid.
Observed 95% CL limit for the pMSSM grid when the signal cross section is increased by one standard deviation.
Observed 95% CL limit for the pMSSM grid when the signal cross section is decreased by one standard deviation.
Expected 95% CL limit for the pMSSM grid.
+1 sigma excursion of the expected 95% CL limit for the pMSSM grid.
-1 sigma excursion of the expected 95% CL limit for the pMSSM grid.
Observed 95% CL limit for the 2Step grid.
Observed 95% CL limit for the 2Step grid when the signal cross section is increased by one standard deviation.
Observed 95% CL limit for the 2Step grid when the signal cross section is decreased by one standard deviation.
Expected 95% CL limit for the 2Step grid.
+1 sigma excursion of the expected 95% CL limit for the 2Step grid.
-1 sigma excursion of the expected 95% CL limit for the 2Step grid.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 8j50 0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 8j50 1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 8j50 2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 9j50 0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 9j50 1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 9j50 2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 10j50 0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 10j50 1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 10j50 2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 7j80 0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 7j80 1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 7j80 2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 8j80 0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 8j80 1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region 8j80 2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
Degree of multijet closure for signal and vaidation regions with at no b-jet requirement. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The bins labelled in bold are signal regions, while the others are validation regions. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).
Degree of multijet closure for signal and vaidation regions with at least 1 b-jet. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The bins labelled in bold are signal regions, while the others are validation regions. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).
Degree of multijet closure for signal and vaidation regions with at least 2 b-jets. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The bins labelled in bold are signal regions, while the others are validation regions. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).
Summary of all 15 signal regions (post-fit).
Signal region yielding the best-expected CLs value, the best expected CLs value, and the corresponding observed CLs value for the 2Step grid.
Signal region yielding the best-expected CLs value, the best expected CLs value, and the corresponding observed CLs value for the pMSSM grid.
95% CLs observed upper limit on model cross-section for 2-step signal points for the best-expected signal region.
Performance of the 8j50-0b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 8j50-1b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 8j50-2b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 9j50-0b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 9j50-1b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 9j50-2b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 10j50-0b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 10j50-1b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 10j50-2b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 7j80-0b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 7j80-1b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 7j80-2b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 8j80-0b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 8j80-1b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 8j80-2b selection for the pMSSM grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 8j50-0b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 8j50-1b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 8j50-2b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 9j50-0b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 9j50-1b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 9j50-2b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 10j50-0b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 10j50-1b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 10j50-2b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 7j80-0b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 7j80-1b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 7j80-2b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 8j80-0b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 8j80-1b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
Performance of the 8j80-2b selection for the 2Step grid: number of generated signal events; total signal cross-section; acceptance; efficiency (fractional); observed CL using this region alone; expected CL using this region alone.
A search for new phenomena in final states containing an $e^+e^-$ or $\mu^+\mu^-$ pair, jets, and large missing transverse momentum is presented. This analysis makes use of proton--proton collision data with an integrated luminosity of $36.1 \; \mathrm{fb}^{-1}$, collected during 2015 and 2016 at a centre-of-mass energy $\sqrt{s}$ = 13 TeV with the ATLAS detector at the Large Hadron Collider. The search targets the pair production of supersymmetric coloured particles (squarks or gluinos) and their decays into final states containing an $e^+e^-$ or $\mu^+\mu^-$ pair and the lightest neutralino ($\tilde{\chi}_1^0$) via one of two next-to-lightest neutralino ($\tilde{\chi}_2^0$) decay mechanisms: $\tilde{\chi}_2^0 \rightarrow Z \tilde{\chi}_1^0$, where the $Z$ boson decays leptonically leading to a peak in the dilepton invariant mass distribution around the $Z$ boson mass; and $\tilde{\chi}_2^0 \rightarrow \ell^+\ell^- \tilde{\chi}_1^0$ with no intermediate $\ell^+\ell^-$ resonance, yielding a kinematic endpoint in the dilepton invariant mass spectrum. The data are found to be consistent with the Standard Model expectation. Results are interpreted using simplified models, and exclude gluinos and squarks with masses as large as 1.85 TeV and 1.3 TeV at 95% confidence level, respectively.
Observed and expected dilepton mass distributions, with the bin boundaries considered for the interpretation, in SR-low. All statistical and systematic uncertainties of the expected background are included in the hatched band. An example signal from the slepton model with m(gluino) = 1200 GeV and m(neutralino1) = 900 GeV is overlaid.
Observed and expected dilepton mass distributions, with the bin boundaries considered for the interpretation, in SR-med. All statistical and systematic uncertainties of the expected background are included in the hatched band. An example signal from the slepton model with m(gluino) = 1600 GeV and m(neutralino1) = 900 GeV, and from an on-$Z$ model with m(gluino) = 1640 GeV and m(neutralino1) = 1160 GeV, is overlaid.
Observed and expected dilepton mass distributions, with the bin boundaries considered for the interpretation, in SR-high. All statistical and systematic uncertainties of the expected background are included in the hatched band. An example signal from the slepton model with m(gluino) = 1800 GeV and m(neutralino1) = 500 GeV, and from an on-$Z$ model with m(gluino) = 1650 GeV and m(neutralino1) = 550 GeV, is overlaid.
Observed and expected dilepton mass distributions, with the bin boundaries considered for the interpretation, in SRC of the low-pT edge search. All statistical and systematic uncertainties of the expected background are included in the hatched band. An example signal from the $Z^{*}$ model with m(gluino) = 1000 GeV and m(neutralino1) = 900 GeV is overlaid.
Observed and expected dilepton mass distributions, with the bin boundaries considered for the interpretation, in SRC-MET of the low-pT edge search. All statistical and systematic uncertainties of the expected background are included in the hatched band. An example signal from the $Z^{*}$ model with m(gluino) = 1000 GeV and m(neutralino1) = 900 GeV is overlaid.
Observed 95% CL exclusion contours on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.
Expected 95% CL exclusion contours on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.
Observed 95% CL exclusion contours from the low-p$_{T}$ signal regions on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.
Expected 95% CL exclusion contours from the low-p$_{T}$ signal regions on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.
Observed 95% CL exclusion contours on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay to an on- or off-shell $Z$ boson and the lightest neutralino.
Expected 95% CL exclusion contours on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay to an on- or off-shell $Z$ boson and the lightest neutralino.
Observed 95% CL exclusion contours from the low-p$_{T}$ signal regions on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay to an on- or off-shell $Z$ boson and the lightest neutralino.
Expected 95% CL exclusion contours from the low-p$_{T}$ signal regions on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay to an on- or off-shell $Z$ boson and the lightest neutralino.
Observed 95% CL exclusion contours from the on-Z signal regions on the gluino and next-to-lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino.
Expected 95% CL exclusion contours from the on-Z signal regions on the gluino and next-to-lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino.
Observed 95% CL exclusion contours from the on-Z signal regions on the squark and next-to-lightest neutralino masses in a SUSY scenario where squarks are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino.
Expected 95% CL exclusion contours from the on-Z signal regions on the squark and next-to-lightest neutralino masses in a SUSY scenario where squarks are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino.
Observed 95% CL exclusion contours from the on-Z signal regions on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson the lightest neutralino.
Expected 95% CL exclusion contours from the on-Z signal regions on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson and the lightest neutralino.
Acceptance and efficiency in the on-Z bin for SR-medium for the SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino.
Acceptance and efficiency in the on-Z bin for SR-high for the SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino.
Acceptance and efficiency over the full $m_{ll}$ range for SR-low for a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.
Acceptance and efficiency over the full $m_{ll}$ range for SR-medium for a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.
Acceptance and efficiency over the full $m_{ll}$ range for SR-high for a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.
Acceptance and efficiency over the full $m_{ll}$ range for SRC for a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.
Acceptance and efficiency over the full $m_{ll}$ range for SRC-MET for a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.
The grey numbers show the 95% CL upper limits on the production cross section at each model point, derived from the best expected combination of results in the on-Z $m_{ll}$ windows of SR-medium and SR-high, SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino.
The grey numbers show the 95% CL upper limits on the production cross section at each model point, derived from the best expected combination of results in the on-Z $m_{ll}$ windows of SR-medium and SR-high, SUSY scenario where squarks are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino.
The grey numbers show the 95% CL upper limits on the production cross section at each model point, derived from the best expected combination of results in the on-Z $m_{ll}$ windows of SR-medium and SR-high, in a SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson the lightest neutralino.
The grey numbers show the 95% CL upper limits on the production cross section at each model point, derived from the best expected combination of results in the signal regions, in a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.
The grey numbers show the 95% CL upper limits on the production cross section at each model point, derived from the best expected combination of results in the low-p$_{T}$ signal regions, in a SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino.
The grey numbers show the 95% CL upper limits on the production cross section at each model point, derived from the best expected combination of results in the signal regions, in a SUSYscenario where gluinos are produced in pairs and decay to an on- or off-shell $Z$ boson.
The grey numbers show the 95% CL upper limits on the production cross section at each model point, derived from the best expected combination of results in the low-p$_{T}$ signal regions, in a SUSY scenario where gluinos are produced in pairs and decay to an on- or off-shell $Z$ boson.
Cutflow table for three benchmark signal points from the SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino, with m(gluino) = 1395 GeV and m(neutralino2) = 505 GeV, m(gluino) = 920 GeV and m(neutralino2) = 230 GeV and m(gluino) = 940 GeV and m(neutralino2) = 660 GeV, in the on-$Z$ $m_{ll}$ bins of SR-medium and SR-high for the electron and muon channels separately. The numbers are normalized to a luminosity of 36.1 fb$^{-1}$.
Cutflow table for a signal point from the SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino, with m(gluino) = 1000 GeV and m(neutralino1) = 800 GeV, m(gluino) = 1200 GeV and m(neutralino1) = 500 GeV and m(gluino) = 1400 GeV and m(neutralino1) = 100 GeV, in all m_{ll}$ bins of SR-low, SR-medium and SR-high for the electron and muon channels separately. The numbers are normalized to a luminosity of 36.1 fb$^{-1}$.
Cutflow table for a signal point from the SUSY scenario where gluinos are produced in pairs and decay to an on- or off-shell $Z$ boson, with m(gluino) = 600 GeV and m(neutralino1) = 560 GeV and m(gluino) = 1000 GeV and m(neutralino1) = 960 GeV, in all $m_{ll}$ bins of SRC and SRC-MET for the electron and muon channels separately. The numbers are normalized to a luminosity of 36.1 fb$^{-1}$.
Signal region used to derive the exclusion limit for the SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino, corresponding to the SR determined to give the best expected limit for a given signal point.
Signal region used to derive the exclusion limit for the SUSY scenario where squarks are produced in pairs and decay to an on-shell Z-boson and a 1 GeV lightest neutralino, corresponding to the SR determined to give the best expected limit for a given signal point.
Signal region used to derive the exclusion limit for the SUSY scenario where gluinos are produced in pairs and decay to an on-shell Z-boson the lightest neutralino, corresponding to the SR determined to give the best expected limit for a given signal point.
Signal region used to derive the exclusion limit for the SUSY scenario where gluinos are produced in pairs and decay to an on- or off-shell $Z$ boson, corresponding to the SR determined to give the best expected limit for a given signal point.
Low-$p_{T}$ signal region used to derive the exclusion limit in the compressed region for the SUSY scenario where gluinos are produced in pairs and decay to an on- or off-shell $Z$ boson, corresponding to the SR determined to give the best expected limit for a given signal point.
Signal region used to derive the exclusion limit for the SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino, corresponding to the SR determined to give the best expected limit for a given signal point.
Low-$p_{T}$ signal region used to derive the exclusion limit for the SUSY scenario where gluinos are produced in pairs and decay via sleptons into the lightest neutralino, corresponding to the SR determined to give the best expected limit for a given signal point.
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 decreased by one standard deviation.
Expected 95% CL limit for the gtt off-shell grid.
Expected 95% CL limit for the gtt off-shell grid with an up variation of the uncertainties.
Expected 95% CL limit for the gtt off-shell grid with a down variation of the uncertainties.
Observed 95% CL limit for the RPV grid.
Observed 95% CL limit for the RPV grid when the signal cross section is increased by one standard deviation.
Observed 95% CL limit for the RPV grid when the signal cross section is decreased by one standard deviation.
Expected 95% CL limit for the RPV grid.
Expected 95% CL limit for the RPV grid with an up variation of the uncertainties.
Expected 95% CL limit for the RPV grid with a down variation of the uncertainties.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-7j80-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-7j80-1b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-7j80-2b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-8j80-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-8j80-1b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-8j80-2b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-9j80-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-9j80-1b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-9j80-2b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-8j50-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-8j50-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-8j50-1b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-8j50-2b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-9j50-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-9j50-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-9j50-1b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-9j50-2b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-10j50-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-10j50-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-10j50-1b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-10j50-2b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-11j50-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-11j50-1b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-11j50-2b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-8j50-0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-8j50-1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-8j50-2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-9j50-0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-9j50-1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-9j50-2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-10j50-0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-10j50-1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-10j50-2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-11j50-0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-11j50-1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-11j50-2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-7j80-0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-7j80-1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-7j80-2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-8j80-0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-8j80-1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-8j80-2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-9j80-0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-9j80-1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-9j80-2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-8j50-0b-MJ340. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-8j50-0b-MJ500. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-9j50-0b-MJ340. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-9j50-0b-MJ500. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-10j50-0b-MJ340. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-10j50-0b-MJ500. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.
Degree of multijet closure for signal and vaidation regions (prior to the leptonic background fit) for the flavour stream with no b-jet requirement and a minimum transverse momentum of 50 GeV. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).
Degree of multijet closure for signal and vaidation regions (prior to the leptonic background fit) for the flavour stream with one inclusive b-jet required and a minimum transverse momentum of 50 GeV. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).
Degree of multijet closure for signal and vaidation regions (prior to the leptonic background fit) for the flavour stream with two inclusive b-jets required and a minimum transverse momentum of 50 GeV. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).
Degree of multijet closure for signal and vaidation regions (prior to the leptonic background fit) for the flavour stream with no b-jet requirement and a minimum transverse momentum of 80 GeV. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).
Degree of multijet closure for signal and vaidation regions (prior to the leptonic background fit) for the flavour stream with one inclusive b-jet required and a minimum transverse momentum of 80 GeV. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).
Degree of multijet closure for signal and vaidation regions (prior to the leptonic background fit) for the flavour stream with two inclusive b-jets required and a minimum transverse momentum of 80 GeV. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).
Degree of multijet closure for signal and vaidation regions (prior to the leptonic background fit) for the fat-jet stream with MJSigma above 340 GeV. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).
Degree of multijet closure for signal and vaidation regions (prior to the leptonic background fit) for the fat-jet stream with MJSigma above 500 GeV. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).
The best-expected signal region and the corresponding best-observed and best-expected CLs values for the 2Step grid.
The best-expected signal region and the corresponding best-observed and best-expected CLs values for the 2Step grid.
The best-expected signal region and the corresponding best-observed and best-expected CLs values for the 2Step grid.
The best-expected signal region and the corresponding best-observed and best-expected CLs values for the pMSSM grid.
The best-expected signal region and the corresponding best-observed and best-expected CLs values for the pMSSM grid.
The best-expected signal region and the corresponding best-observed and best-expected CLs values for the pMSSM grid.
The best-expected signal region and the corresponding best-observed and best-expected CLs values for the RPV grid.
The best-expected signal region and the corresponding best-observed and best-expected CLs values for the RPV grid.
The best-expected signal region and the corresponding best-observed and best-expected CLs values for the RPV grid.
The best-expected signal region and the corresponding best-observed and best-expected CLs values for the gtt off-shell grid.
The best-expected signal region and the corresponding best-observed and best-expected CLs values for the gtt off-shell grid.
The best-expected signal region and the corresponding best-observed and best-expected CLs values for the gtt off-shell grid.
95% CLs observed upper limit on model cross-section (in fb) for 2Step signal points for the best-expected signal region.
95% CLs observed upper limit on model cross-section (in fb) for RPV signal points for the best-expected signal region.
95% CLs observed upper limit on model cross-section (in fb) for gtt off-shell signal points for the best-expected signal region.
Performance of the SR-8j50-0b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-8j50-0b-MJ340 for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-8j50-0b-MJ500 for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-8j50-1b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-8j50-2b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-9j50-0b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-9j50-0b-MJ340 for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-9j50-0b-MJ500 for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-9j50-1b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-9j50-2b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-10j50-0b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-10j50-0b-MJ340 for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-10j50-0b-MJ500 for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-10j50-1b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-10j50-2b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-11j50-0b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-11j50-1b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-11j50-2b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-7j80-0b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-7j80-1b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-7j80-2b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-8j80-0b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-8j80-1b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-8j80-2b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-9j80-0b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-9j80-1b for the 2Step grid: fractional acceptance; fractional efficiency.
Performance of the SR-9j80-2b for the 2Step grid: fractional acceptance; fractional efficiency.
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.
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