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Dijet angular distributions from the first LHC pp collisions at center-of-mass energy sqrt(s) = 7 TeV have been measured with the ATLAS detector. The dataset used for this analysis represents an integrated luminosity of 3.1 pb-1. Dijet $\chi$ distributions and centrality ratios have been measured up to dijet masses of 2.8 TeV, and found to be in good agreement with Standard Model predictions. Analysis of the $\chi$ distributions excludes quark contact interactions with a compositeness scale $\Lambda$ below 3.4 TeV, at 95% confidence level, significantly exceeding previous limits.
CHI distribution for mass bin 340 to 520 GeV.
CHI distribution for mass bin 520 to 800 GeV.
CHI distribution for mass bin 800 to 1200 GeV.
CHI distribution for mass bin > 1200 GeV.
Centrality Ratio.
A search for new heavy particles manifested as resonances in two-jet final states is presented. The data were produced in 7 TeV proton-proton collisions by the Large Hadron Collider (LHC) and correspond to an integrated luminosity of 315 nb^-1 collected by the ATLAS detector. No resonances were observed. Upper limits were set on the product of cross section and signal acceptance for excited-quark (q*) production as a function of q* mass. These exclude at the 95% CL the q* mass interval 0.30 < mq* < 1.26 TeV, extending the reach of previous experiments.
The dijet mass distribution (NUMBER OF EVENTS).
95 PCT CL upper limit of the cross section x acceptance.
The results of a search for gluino and squark pair production with the pairs decaying via the lightest charginos into a final state consisting of two $W$ bosons, the lightest neutralinos ($\tilde\chi^0_1$), and quarks, are presented. The signal is characterised by the presence of a single charged lepton ($e^{\pm}$ or $\mu^{\pm}$) from a $W$ boson decay, jets, and missing transverse momentum. The analysis is performed using 139 fb$^{-1}$ of proton-proton collision data taken at a centre-of-mass energy $\sqrt{s}=13$ TeV delivered by the Large Hadron Collider and recorded by the ATLAS experiment. No statistically significant excess of events above the Standard Model expectation is found. Limits are set on the direct production of squarks and gluinos in simplified models. Masses of gluino (squark) up to 2.2 TeV (1.4 TeV) are excluded at 95% confidence level for a light $\tilde\chi^0_1$.
Post-fit $m_{T}$ distribution in the SR 2J b-veto N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{T}$ distribution in the SR 2J b-veto N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{T}$ distribution in the SR 2J b-tag N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{T}$ distribution in the SR 2J b-tag N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{T}$ distribution in the SR 4J b-veto N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{T}$ distribution in the SR 4J b-veto N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{T}$ distribution in the SR 4J b-tag N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{T}$ distribution in the SR 4J b-tag N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{T}$ distribution in the SR 6J b-veto N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{T}$ distribution in the SR 6J b-veto N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{T}$ distribution in the SR 6J b-tag N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{T}$ distribution in the SR 6J b-tag N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Pre-fit $m_{eff}$ distribution in the TR6J control region. Uncertainties include statistical and systematic uncertainties (added in quadrature). The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 2J b-tag signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Pre-fit $m_{eff}$ distribution in the WR6J control region. Uncertainties include statistical and systematic uncertainties (added in quadrature). The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 2J b-veto signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the TR6J control region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 4J low-x b-tag signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the WR6J control region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 4J low-x b-veto signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 2J b-tag signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 4J high-x b-tag signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 2J b-veto signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 4J high-x b-veto signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 4J low-x b-tag signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 6J b-tag signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 4J low-x b-veto signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 6J b-veto signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 4J high-x b-tag signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Observed 95% CL exclusion contours for the gluino one-step x = 1/2 model.
Post-fit $m_{eff}$ distribution in the 4J high-x b-veto signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Expected 95% CL exclusion contours for the gluino one-step x = 1/2 model. space.
Post-fit $m_{eff}$ distribution in the 6J b-tag signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Observed 95% CL exclusion contours for the gluino one-step variable-x
Post-fit $m_{eff}$ distribution in the 6J b-veto signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.
Expected 95% CL exclusion contours for the gluino one-step variable-x
Observed 95% CL exclusion contours for the gluino one-step x = 1/2 model.
Observed 95% CL exclusion contours for the squark one-step x = 1/2 model.
Expected 95% CL exclusion contours for the gluino one-step x = 1/2 model. space.
Observed 95% CL exclusion contours for the squark one-step x = 1/2 model.
Observed 95% CL exclusion contours for the gluino one-step variable-x
Observed 95% CL exclusion contours for one-flavour schemes in one-step x = 1/2 model.
Expected 95% CL exclusion contours for the gluino one-step variable-x
Observed 95% CL exclusion contours for one-flavour schemes in one-step x = 1/2 model.
Observed 95% CL exclusion contours for the squark one-step x = 1/2 model.
Expected 95% CL exclusion contours for the squark one-step variable-x
Observed 95% CL exclusion contours for the squark one-step x = 1/2 model.
Expected 95% CL exclusion contours for the squark one-step variable-x
Observed 95% CL exclusion contours for one-flavour schemes in one-step x = 1/2 model.
Expected 95% CL exclusion contours for the squark one-flavour schemes in variable-x
Observed 95% CL exclusion contours for one-flavour schemes in one-step x = 1/2 model.
Expected 95% CL exclusion contours for the squark one-flavour schemes in variable-x
Expected 95% CL exclusion contours for the squark one-step variable-x
Upper limits on the signal cross section for simplified model gluino one-step x = 1/2
Expected 95% CL exclusion contours for the squark one-step variable-x
Upper limits on the signal cross section for simplified model gluino one-step variable-x
Expected 95% CL exclusion contours for the squark one-flavour schemes in variable-x
Upper limits on the signal cross section for simplified model squark one-step x = 1/2
Expected 95% CL exclusion contours for the squark one-flavour schemes in variable-x
Upper limits on the signal cross section for simplified model squark one-step variable-x
Upper limits on the signal cross section for simplified model gluino one-step x = 1/2
Upper limits on the signal cross section for simplified model squark one-step x=1/2 in one-flavour schemes
Upper limits on the signal cross section for simplified model gluino one-step variable-x
Upper limits on the signal cross section for simplified model squark one-step variable-x in one-flavour schemes
Upper limits on the signal cross section for simplified model squark one-step x = 1/2
Post-fit $m_{eff}$ distribution in the 2J b-tag validation region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Upper limits on the signal cross section for simplified model squark one-step variable-x
Post-fit $m_{eff}$ distribution in the 2J b-veto validation region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Upper limits on the signal cross section for simplified model squark one-step x=1/2 in one-flavour schemes
Post-fit $m_{eff}$ distribution in the 4J b-tag validation region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Upper limits on the signal cross section for simplified model squark one-step variable-x in one-flavour schemes
Post-fit $m_{eff}$ distribution in the 4J b-veto validation region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the TR2J control region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 6J b-tag validation region. Uncertainties include statistical and systematic uncertainties.
Post-fit $m_{eff}$ distribution in the WR2J control region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Post-fit $m_{eff}$ distribution in the 6J b-veto validation region. Uncertainties include statistical and systematic uncertainties.
Post-fit $m_{eff}$ distribution in the TR4J control region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Event selection cutflow for two representative signal samples for the SR2JBT. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.
Post-fit $m_{eff}$ distribution in the WR4J control region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Event selection cutflow for two representative signal samples for the SR2JBV. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.
Post-fit $m_{eff}$ distribution in the 2J b-tag validation region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Event selection cutflow for two representative signal samples for the SR4JBT. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.
Post-fit $m_{eff}$ distribution in the 2J b-veto validation region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Event selection cutflow for two representative signal samples for the SR4JBV. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.
Post-fit $m_{eff}$ distribution in the 4J b-tag validation region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Event selection cutflow for two representative signal samples for the SR6JBT. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.
Post-fit $m_{eff}$ distribution in the 4J b-veto validation region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.
Event selection cutflow for two representative signal samples for the SR6JBV. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.
Post-fit $m_{eff}$ distribution in the 6J b-tag validation region. Uncertainties include statistical and systematic uncertainties.
Signal acceptance in SR2J b-Tag bin1 region for gluino production one-step x = 1/2 simplified models
Post-fit $m_{eff}$ distribution in the 6J b-veto validation region. Uncertainties include statistical and systematic uncertainties.
Signal acceptance in SR2J b-Tag bin2 region for gluino production one-step x = 1/2 simplified models
Event selection cutflow for two representative signal samples for the SR2JBT. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.
Signal acceptance in SR2J b-Tag bin3 region for gluino production one-step x = 1/2 simplified models
Event selection cutflow for two representative signal samples for the SR2JBV. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.
Signal acceptance in SR2J b-Veto bin1 region for gluino production one-step x = 1/2 simplified models
Event selection cutflow for two representative signal samples for the SR4JBT. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.
Signal acceptance in SR2J b-Veto bin2 region for gluino production one-step x = 1/2 simplified models
Event selection cutflow for two representative signal samples for the SR4JBV. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.
Signal acceptance in SR2J b-Veto bin3 region for gluino production one-step x = 1/2 simplified models
Event selection cutflow for two representative signal samples for the SR6JBT. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.
Signal acceptance in SR2J discovery high region for gluino production one-step x = 1/2 simplified models
Event selection cutflow for two representative signal samples for the SR6JBV. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.
Signal acceptance in SR2J discovery low region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx discovery region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Tag bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Tag bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Tag bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Veto bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Veto bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J discovery high region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Veto bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J discovery low region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx discovery region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx discovery region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Tag bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Tag bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Tag bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Tag bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Tag bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Tag bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Veto bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Veto bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Veto bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Veto bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Veto bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Veto bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx discovery region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Tag bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Tag bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin4 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Tag bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Veto bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Veto bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Veto bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin4 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J discovery high region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J discovery low region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin4 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin2 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin4 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J discovery high region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J discovery high region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J discovery low region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J discovery low region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Tag bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx discovery region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Tag bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Tag bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Veto bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Veto bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Veto bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J discovery high region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J discovery low region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx discovery region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx discovery region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx discovery region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin4 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin4 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J discovery high region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J discovery low region for gluino production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Tag bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin4 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Tag bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Tag bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin2 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Veto bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin3 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Veto bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin4 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Veto bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J discovery high region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J discovery high region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J discovery low region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J discovery low region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx discovery region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Tag bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Tag bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Tag bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Veto bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Veto bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J discovery high region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Veto bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J discovery low region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx discovery region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx discovery region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Tag bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Tag bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Tag bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Tag bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Tag bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Tag bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Veto bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Veto bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Veto bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Veto bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Veto bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jhx b-Veto bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx discovery region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Tag bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Tag bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin4 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Tag bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Veto bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Veto bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR4Jlx b-Veto bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin4 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J discovery high region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J discovery low region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin4 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin1 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin2 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin3 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin4 region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Veto bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J discovery high region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J discovery high region for squark production one-step variable-x simplified models
Signal acceptance in SR6J discovery low region for squark production one-step x = 1/2 simplified models
Signal acceptance in SR2J discovery low region for squark production one-step variable-x simplified models
Signal acceptance in SR2J b-Tag bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx discovery region for squark production one-step variable-x simplified models
Signal acceptance in SR2J b-Tag bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR2J b-Tag bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR2J b-Veto bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR2J b-Veto bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR2J b-Veto bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR2J discovery high region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR2J discovery low region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx discovery region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx discovery region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Tag bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jhx b-Veto bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx discovery region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin4 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Tag bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR4Jlx b-Veto bin3 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Veto bin4 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin1 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J discovery high region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin2 region for squark production one-step variable-x simplified models
Signal acceptance in SR6J discovery low region for squark production one-step variable-x simplified models
Signal acceptance in SR6J b-Tag bin3 region for squark production one-step variable-x simplified models
Signal efficiency in SR2J b-Tag bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal acceptance in SR6J b-Tag bin4 region for squark production one-step variable-x simplified models
Signal efficiency in SR2J b-Tag bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal acceptance in SR6J b-Veto bin1 region for squark production one-step variable-x simplified models
Signal efficiency in SR2J b-Tag bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal acceptance in SR6J b-Veto bin2 region for squark production one-step variable-x simplified models
Signal efficiency in SR2J b-Veto bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal acceptance in SR6J b-Veto bin3 region for squark production one-step variable-x simplified models
Signal efficiency in SR2J b-Veto bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal acceptance in SR6J b-Veto bin4 region for squark production one-step variable-x simplified models
Signal efficiency in SR2J b-Veto bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal acceptance in SR6J discovery high region for squark production one-step variable-x simplified models
Signal efficiency in SR2J discovery high region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal acceptance in SR6J discovery low region for squark production one-step variable-x simplified models
Signal efficiency in SR2J discovery low region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx discovery region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery high region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery low region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx discovery region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx discovery region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx discovery region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin4 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin4 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery high region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery low region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin4 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin4 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery high region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery high region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery low region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery low region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx discovery region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery high region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery low region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx discovery region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx discovery region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx discovery region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin4 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin4 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery high region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery low region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin4 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin4 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery high region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery high region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery low region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery low region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx discovery region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery high region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery low region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx discovery region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx discovery region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx discovery region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin4 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin4 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery high region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery low region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin4 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin4 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery high region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery high region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery low region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery low region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx discovery region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Tag bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J b-Veto bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery high region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR2J discovery low region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx discovery region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx discovery region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Tag bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jhx b-Veto bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx discovery region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin4 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Tag bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR4Jlx b-Veto bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin4 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery high region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery low region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Tag bin4 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J b-Veto bin4 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery high region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
Signal efficiency in SR6J discovery low region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0
This paper presents a statistical combination of searches targeting final states with two top quarks and invisible particles, characterised by the presence of zero, one or two leptons, at least one jet originating from a $b$-quark and missing transverse momentum. The analyses are searches for phenomena beyond the Standard Model consistent with the direct production of dark matter in $pp$ collisions at the LHC, using 139 fb$^{-\text{1}}$ of data collected with the ATLAS detector at a centre-of-mass energy of 13 TeV. The results are interpreted in terms of simplified dark matter models with a spin-0 scalar or pseudoscalar mediator particle. In addition, the results are interpreted in terms of upper limits on the Higgs boson invisible branching ratio, where the Higgs boson is produced according to the Standard Model in association with a pair of top quarks. For scalar (pseudoscalar) dark matter models, with all couplings set to unity, the statistical combination extends the mass range excluded by the best of the individual channels by 50 (25) GeV, excluding mediator masses up to 370 GeV. In addition, the statistical combination improves the expected coupling exclusion reach by 14% (24%), assuming a scalar (pseudoscalar) mediator mass of 10 GeV. An upper limit on the Higgs boson invisible branching ratio of 0.38 (0.30$^{+\text{0.13}}_{-\text{0.09}}$) is observed (expected) at 95% confidence level.
Post-fit signal region yields for the tt0L-high and the tt0L-low analyses. The bottom panel shows the statistical significance of the difference between the SM prediction and the observed data in each region. '$t\bar{t}$ (other)' represents $t\bar{t}$ events without extra jets or events with extra light-flavour jets. 'Other' includes contributions from $t\bar{t}W$, $tZ$ and $tWZ$ processes. The total uncertainty in the SM expectation is represented with hatched bands and the expected distributions for selected signal models are shown as dashed lines.
Representative fit distribution in the signal region for the tt1L analysis: each bin of such distribution corresponds to a single SR included in the fit. 'Other' includes contributions from $t\bar{t}W$, $tZ$, $tWZ$ and $t\bar{t}$ (semileptonic) processes. The total uncertainty in the SM expectation is represented with hatched bands and the expected distributions for selected signal models are shown as dashed lines.
Representative fit distribution in the same flavour leptons signal region for the tt2L analysis: each bin of such distribution, starting from the red arrow, corresponds to a single SR included in the fit. 'FNP' includes the contribution from fake/non-prompt lepton background arising from jets (mainly $\pi/K$, heavy-flavour hadron decays and photon conversion) misidentified as leptons, estimated in a purely data-driven way. 'Other' includes contributions from $t\bar{t}W$, $tZ$ and $tWZ$ processes. The total uncertainty in the SM expectation is represented with hatched bands and the expected distributions for selected signal models are shown as dashed lines.
Summary of the total uncertainty in the background prediction for each SR of the tt0L-low, tt0L-high, tt1L and tt2L analysis channels in the statistical combination. Their dominant contributions are indicated by individual lines. Individual uncertainties can be correlated, and do not necessarily add up in quadrature to the total background uncertainty.
Exclusion limits for colour-neutral scalar mediator dark matter models as a function of the mediator mass $m(\phi)$ for a DM mass $m_{\chi} = 1$ GeV. Associated production of DM with both single top quarks ($tW$ and $tj$ channels) and top quark pairs is considered. The limits are calculated at 95% CL and are expressed in terms of the ratio of the excluded cross section to the cross section for a coupling assumption of $g = g_q = g_{\chi} = 1$. The solid (dashed) lines show the observed (expected) exclusion limits for each individual channel and their statistical combination.
Exclusion limits for colour-neutral pseudoscalar mediator dark matter models as a function of the mediator mass $m(a)$ for a DM mass $m_{\chi} = 1$ GeV. Associated production of DM with both single top quarks ($tW$ and $tj$ channels) and top quark pairs is considered. The limits are calculated at 95% CL and are expressed in terms of the ratio of the excluded cross section to the cross section for a coupling assumption of $g = g_q = g_{\chi} = 1$. The solid (dashed) lines show the observed (expected) exclusion limits for each individual channel and their statistical combination.
$E_{\text{T}}^{\text{miss}}$ distribution in SR0X for the tt0L-low analysis. The contributions from all SM backgrounds are shown after the profile likelihood simultaneous fit to all tt0L-low CRs, with the hatched bands representing the total uncertainty. The category '$t\bar{t}$ (other)' represents $t\bar{t}$ events without extra jets or events with extra light-flavour jets. 'Other' includes contributions from $t\bar{t}W$, $tZ$ and $tWZ$ processes. The expected distributions for selected signal models are shown as dashed lines. The overflow events are included in the last bin. The bottom panels show the ratio of the observed data to the total SM background prediction, with the hatched area representing the total uncertainty in the background prediction and the red arrows marking data outside the vertical-axis range.
$E_{\text{T}}^{\text{miss}}$ distribution in SRWX for the tt0L-low analysis. The contributions from all SM backgrounds are shown after the profile likelihood simultaneous fit to all tt0L-low CRs, with the hatched bands representing the total uncertainty. The category '$t\bar{t}$ (other)' represents $t\bar{t}$ events without extra jets or events with extra light-flavour jets. 'Other' includes contributions from $t\bar{t}W$, $tZ$ and $tWZ$ processes. The expected distributions for selected signal models are shown as dashed lines. The overflow events are included in the last bin. The bottom panels show the ratio of the observed data to the total SM background prediction, with the hatched area representing the total uncertainty in the background prediction and the red arrows marking data outside the vertical-axis range.
$E_{\text{T}}^{\text{miss}}$ distribution in SRTX for the tt0L-low analysis. The contributions from all SM backgrounds are shown after the profile likelihood simultaneous fit to all tt0L-low CRs, with the hatched bands representing the total uncertainty. The category '$t\bar{t}$ (other)' represents $t\bar{t}$ events without extra jets or events with extra light-flavour jets. 'Other' includes contributions from $t\bar{t}W$, $tZ$ and $tWZ$ processes. The expected distributions for selected signal models are shown as dashed lines. The overflow events are included in the last bin. The bottom panels show the ratio of the observed data to the total SM background prediction, with the hatched area representing the total uncertainty in the background prediction and the red arrows marking data outside the vertical-axis range.
Exclusion limits for colour-neutral scalar mediator dark matter models as a function of the mediator mass $m(\phi)$ for a DM mass $m_{\chi} = 1$ GeV. Associated production of DM with both single top quarks ($tW$ and $tj$ channels) and top quark pairs is considered. The limits are calculated at 95% CL and are expressed in terms of the ratio of the excluded cross section to the nominal cross section for a coupling assumption of $g = g_q = g_{\chi} = 1$. The solid (dashed) lines show the observed (expected) exclusion limits for the tt0L-high and tt0L-low analyses and their statistical combination.
Exclusion limits for colour-neutral pseudoscalar mediator dark matter models as a function of the mediator mass $m(a)$ for a DM mass $m_{\chi} = 1$ GeV. Associated production of DM with both single top quarks ($tW$ and $tj$ channels) and top quark pairs is considered. The limits are calculated at 95% CL and are expressed in terms of the ratio of the excluded cross section to the nominal cross section for a coupling assumption of $g = g_q = g_{\chi} = 1$. The solid (dashed) lines show the observed (expected) exclusion limits for the tt0L-high and tt0L-low analyses and their statistical combination.
Exclusion limits for colour-neutral scalar mediator dark matter models as a function of the mediator mass $m(\phi)$ for a DM mass $m_{\chi} = 1$ GeV. Only associated production of DM with top quark pairs is considered for this interpretation. The limits are calculated at 95% CL and are expressed in terms of the ratio of the excluded cross section to the cross section for a coupling assumption of $g = g_q = g_{\chi} = 1$. The solid (dashed) lines show the observed (expected) exclusion limits for each individual channel and their statistical combination.
Exclusion limits for colour-neutral pseudoscalar mediator dark matter models as a function of the mediator mass $m(a)$ for a DM mass $m_{\chi} = 1$ GeV. Only associated production of DM with top quark pairs is considered for this interpretation. The limits are calculated at 95% CL and are expressed in terms of the ratio of the excluded cross section to the cross section for a coupling assumption of $g = g_q = g_{\chi} = 1$. The solid (dashed) lines show the observed (expected) exclusion limits for each individual channel and their statistical combination.
Exclusion limits for colour-neutral scalar mediator dark matter models as a function of the mediator mass $m(\phi)$ for a DM mass $m_{\chi} = 1$ GeV. Only associated production of DM with top quark pairs is considered for this interpretation. The limits are calculated at 95% CL and are expressed in terms of the ratio of the excluded cross section to the nominal cross section for a coupling assumption of $g = g_q = g_{\chi} = 1$. The solid (dashed) lines show the observed (expected) exclusion limits for the tt0L-high and tt0L-low analyses and their statistical combination.
Exclusion limits for colour-neutral pseudoscalar mediator dark matter models as a function of the mediator mass $m(a)$ for a DM mass $m_{\chi} = 1$ GeV. Only associated production of DM with top quark pairs is considered for this interpretation. The limits are calculated at 95% CL and are expressed in terms of the ratio of the excluded cross section to the nominal cross section for a coupling assumption of $g = g_q = g_{\chi} = 1$. The solid (dashed) lines show the observed (expected) exclusion limits for the tt0L-high and tt0L-low analyses and their statistical combination.
Representative fit distribution in the different flavour leptons signal region for the tt2L analysis: each bin of such distribution, starting from the red arrow, corresponds to a single SR included in the fit. 'FNP' includes the contribution from fake/non-prompt lepton background arising from jets (mainly $\pi/K$, heavy-flavour hadron decays and photon conversion) misidentified as leptons, estimated in a purely data-driven way. 'Other' includes contributions from $t\bar{t}W$, $tZ$ and $tWZ$ processes. The total uncertainty in the SM expectation is represented with hatched bands and the expected distributions for selected signal models are shown as dashed lines.
Signal acceptance in SR0X, SRWX and SRTX for simplified DM+$t\bar{t}$ model, defined as the number of accepted events at generator level in signal Monte Carlo simulation divided by the total number of events in the sample.
Signal acceptance in SR0X, SRWX and SRTX for simplified DM+$tW$ model, defined as the number of accepted events at generator level in signal Monte Carlo simulation divided by the total number of events in the sample.
Signal acceptance in SR0X, SRWX and SRTX for simplified DM+$tj$ model, defined as the number of accepted events at generator level in signal Monte Carlo simulation divided by the total number of events in the sample.
Signal efficiency in SR0X, SRWX and SRTX for simplified DM+$t\bar{t}$ model, defined as the number of selected reconstructed events divided by the acceptance.
Signal efficiency in SR0X, SRWX and SRTX for simplified DM+$tW$ model, defined as the number of selected reconstructed events divided by the acceptance.
Signal efficiency in SR0X, SRWX and SRTX for simplified DM+$tj$ model, defined as the number of selected reconstructed events divided by the acceptance.
Cutflow for the reference point DM+$t\bar{t}$ $m(\phi, \chi) = (10, 1)$ GeV in signal region SR0X. The column labelled 'weighted' shows the event yield including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns the 'weighted' numbers in the first and the second row, labelled 'Total' and 'Filtered', which correspond to $\mathcal{L}\cdot\sigma$ and $\mathcal{L}\cdot\sigma\cdot\epsilon$ expected, respectively. The 'Skim' selection requires the $p_{\text{T}}$ of the leading four jets to be above (80, 60, 40, 40) GeV, the missing transverse momentum $E_{\text{T}}^{\text{miss}} > 140$ GeV, the missing momentum significance $\mathcal{S} > 8$, $\Delta\phi_{\min}(\vec{p}_{\text{T,1-4}},\vec{p}_{\text{T}}^{\text{miss}}) > 0.4$ and a lepton veto. The 'Orthogonalisation' selection is defined in the main body. In total 2045000 raw MC events were generated prior to the specified cuts, with the column 'Unweighted yield' collecting the numbers after each cut.
Cutflow for the reference point DM+$t\bar{t}$ $m(\phi, \chi) = (10, 1)$ GeV in signal region SRWX. The column labelled 'weighted' shows the event yield including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns the 'weighted' numbers in the first and the second row, labelled 'Total' and 'Filtered', which correspond to $\mathcal{L}\cdot\sigma$ and $\mathcal{L}\cdot\sigma\cdot\epsilon$ expected, respectively. The 'Skim' selection requires the $p_{\text{T}}$ of the leading four jets to be above (80, 60, 40, 40) GeV, the missing transverse momentum $E_{\text{T}}^{\text{miss}} > 140$ GeV, the missing momentum significance $\mathcal{S} > 8$, $\Delta\phi_{\min}(\vec{p}_{\text{T,1-4}},\vec{p}_{\text{T}}^{\text{miss}}) > 0.4$ and a lepton veto. The 'Orthogonalisation' selection is defined in the main body. In total 2045000 raw MC events were generated prior to the specified cuts, with the column 'Unweighted yield' collecting the numbers after each cut.
Cutflow for the reference point DM+$t\bar{t}$ $m(\phi, \chi) = (10, 1)$ GeV in signal region SRTX. The column labelled 'weighted' shows the event yield including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns the 'weighted' numbers in the first and the second row, labelled 'Total' and 'Filtered', which correspond to $\mathcal{L}\cdot\sigma$ and $\mathcal{L}\cdot\sigma\cdot\epsilon$ expected, respectively. The 'Skim' selection requires the $p_{\text{T}}$ of the leading four jets to be above (80, 60, 40, 40) GeV, the missing transverse momentum $E_{\text{T}}^{\text{miss}} > 140$ GeV, the missing momentum significance $\mathcal{S} > 8$, $\Delta\phi_{\min}(\vec{p}_{\text{T,1-4}},\vec{p}_{\text{T}}^{\text{miss}}) > 0.4$ and a lepton veto. The 'Orthogonalisation' selection is defined in the main body. In total 2045000 raw MC events were generated prior to the specified cuts, with the column 'Unweighted yield' collecting the numbers after each cut.
Cutflow for the reference point DM+$t\bar{t}$ $m(a, \chi) = (10, 1)$ GeV in signal region SR0X. The column labelled 'weighted' shows the event yield including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns the 'weighted' numbers in the first and the second row, labelled 'Total' and 'Filtered', which correspond to $\mathcal{L}\cdot\sigma$ and $\mathcal{L}\cdot\sigma\cdot\epsilon$ expected, respectively. The 'Skim' selection requires the $p_{\text{T}}$ of the leading four jets to be above (80, 60, 40, 40) GeV, the missing transverse momentum $E_{\text{T}}^{\text{miss}} > 140$ GeV, the missing momentum significance $\mathcal{S} > 8$, $\Delta\phi_{\min}(\vec{p}_{\text{T,1-4}},\vec{p}_{\text{T}}^{\text{miss}}) > 0.4$ and a lepton veto. The 'Orthogonalisation' selection is defined in the main body. In total 400000 raw MC events were generated prior to the specified cuts, with the column 'Unweighted yield' collecting the numbers after each cut.
Cutflow for the reference point DM+$t\bar{t}$ $m(a, \chi) = (10, 1)$ GeV in signal region SRWX. The column labelled 'weighted' shows the event yield including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns the 'weighted' numbers in the first and the second row, labelled 'Total' and 'Filtered', which correspond to $\mathcal{L}\cdot\sigma$ and $\mathcal{L}\cdot\sigma\cdot\epsilon$ expected, respectively. The 'Skim' selection requires the $p_{\text{T}}$ of the leading four jets to be above (80, 60, 40, 40) GeV, the missing transverse momentum $E_{\text{T}}^{\text{miss}} > 140$ GeV, the missing momentum significance $\mathcal{S} > 8$, $\Delta\phi_{\min}(\vec{p}_{\text{T,1-4}},\vec{p}_{\text{T}}^{\text{miss}}) > 0.4$ and a lepton veto. The 'Orthogonalisation' selection is defined in the main body. In total 400000 raw MC events were generated prior to the specified cuts, with the column 'Unweighted yield' collecting the numbers after each cut.
Cutflow for the reference point DM+$t\bar{t}$ $m(a, \chi) = (10, 1)$ GeV in signal region SRTX. The column labelled 'weighted' shows the event yield including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns the 'weighted' numbers in the first and the second row, labelled 'Total' and 'Filtered', which correspond to $\mathcal{L}\cdot\sigma$ and $\mathcal{L}\cdot\sigma\cdot\epsilon$ expected, respectively. The 'Skim' selection requires the $p_{\text{T}}$ of the leading four jets to be above (80, 60, 40, 40) GeV, the missing transverse momentum $E_{\text{T}}^{\text{miss}} > 140$ GeV, the missing momentum significance $\mathcal{S} > 8$, $\Delta\phi_{\min}(\vec{p}_{\text{T,1-4}},\vec{p}_{\text{T}}^{\text{miss}}) > 0.4$ and a lepton veto. The 'Orthogonalisation' selection is defined in the main body. In total 400000 raw MC events were generated prior to the specified cuts, with the column 'Unweighted yield' collecting the numbers after each cut.
Cutflow for the reference point DM+$tW$ $m(\phi, \chi) = (10, 1)$ GeV in signal region SR0X. The column labelled 'weighted' shows the event yield including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns the 'weighted' numbers in the first and the second row, labelled 'Total' and 'Filtered', which correspond to $\mathcal{L}\cdot\sigma$ and $\mathcal{L}\cdot\sigma\cdot\epsilon$ expected, respectively. The 'Skim' selection requires the $p_{\text{T}}$ of the leading four jets to be above (80, 60, 40, 40) GeV, the missing transverse momentum $E_{\text{T}}^{\text{miss}} > 140$ GeV, the missing momentum significance $\mathcal{S} > 8$, $\Delta\phi_{\min}(\vec{p}_{\text{T,1-4}},\vec{p}_{\text{T}}^{\text{miss}}) > 0.4$ and a lepton veto. The 'Orthogonalisation' selection is defined in the main body. In total 120000 raw MC events were generated prior to the specified cuts, with the column 'Unweighted yield' collecting the numbers after each cut.
Cutflow for the reference point DM+$tW$ $m(\phi, \chi) = (10, 1)$ GeV in signal region SRWX. The column labelled 'weighted' shows the event yield including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns the 'weighted' numbers in the first and the second row, labelled 'Total' and 'Filtered', which correspond to $\mathcal{L}\cdot\sigma$ and $\mathcal{L}\cdot\sigma\cdot\epsilon$ expected, respectively. The 'Skim' selection requires the $p_{\text{T}}$ of the leading four jets to be above (80, 60, 40, 40) GeV, the missing transverse momentum $E_{\text{T}}^{\text{miss}} > 140$ GeV, the missing momentum significance $\mathcal{S} > 8$, $\Delta\phi_{\min}(\vec{p}_{\text{T,1-4}},\vec{p}_{\text{T}}^{\text{miss}}) > 0.4$ and a lepton veto. The 'Orthogonalisation' selection is defined in the main body. In total 120000 raw MC events were generated prior to the specified cuts, with the column 'Unweighted yield' collecting the numbers after each cut.
Cutflow for the reference point DM+$tW$ $m(\phi, \chi) = (10, 1)$ GeV in signal region SRTX. The column labelled 'weighted' shows the event yield including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns the 'weighted' numbers in the first and the second row, labelled 'Total' and 'Filtered', which correspond to $\mathcal{L}\cdot\sigma$ and $\mathcal{L}\cdot\sigma\cdot\epsilon$ expected, respectively. The 'Skim' selection requires the $p_{\text{T}}$ of the leading four jets to be above (80, 60, 40, 40) GeV, the missing transverse momentum $E_{\text{T}}^{\text{miss}} > 140$ GeV, the missing momentum significance $\mathcal{S} > 8$, $\Delta\phi_{\min}(\vec{p}_{\text{T,1-4}},\vec{p}_{\text{T}}^{\text{miss}}) > 0.4$ and a lepton veto. The 'Orthogonalisation' selection is defined in the main body. In total 120000 raw MC events were generated prior to the specified cuts, with the column 'Unweighted yield' collecting the numbers after each cut.
Cutflow for the reference point DM+$tW$ $m(a, \chi) = (10, 1)$ GeV in signal region SR0X. The column labelled 'weighted' shows the event yield including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns the 'weighted' numbers in the first and the second row, labelled 'Total' and 'Filtered', which correspond to $\mathcal{L}\cdot\sigma$ and $\mathcal{L}\cdot\sigma\cdot\epsilon$ expected, respectively. The 'Skim' selection requires the $p_{\text{T}}$ of the leading four jets to be above (80, 60, 40, 40) GeV, the missing transverse momentum $E_{\text{T}}^{\text{miss}} > 140$ GeV, the missing momentum significance $\mathcal{S} > 8$, $\Delta\phi_{\min}(\vec{p}_{\text{T,1-4}},\vec{p}_{\text{T}}^{\text{miss}}) > 0.4$ and a lepton veto. The 'Orthogonalisation' selection is defined in the main body. In total 100000 raw MC events were generated prior to the specified cuts, with the column 'Unweighted yield' collecting the numbers after each cut.
Cutflow for the reference point DM+$tW$ $m(a, \chi) = (10, 1)$ GeV in signal region SRWX. The column labelled 'weighted' shows the event yield including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns the 'weighted' numbers in the first and the second row, labelled 'Total' and 'Filtered', which correspond to $\mathcal{L}\cdot\sigma$ and $\mathcal{L}\cdot\sigma\cdot\epsilon$ expected, respectively. The 'Skim' selection requires the $p_{\text{T}}$ of the leading four jets to be above (80, 60, 40, 40) GeV, the missing transverse momentum $E_{\text{T}}^{\text{miss}} > 140$ GeV, the missing momentum significance $\mathcal{S} > 8$, $\Delta\phi_{\min}(\vec{p}_{\text{T,1-4}},\vec{p}_{\text{T}}^{\text{miss}}) > 0.4$ and a lepton veto. The 'Orthogonalisation' selection is defined in the main body. In total 100000 raw MC events were generated prior to the specified cuts, with the column 'Unweighted yield' collecting the numbers after each cut.
Cutflow for the reference point DM+$tW$ $m(a, \chi) = (10, 1)$ GeV in signal region SRTX. The column labelled 'weighted' shows the event yield including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns the 'weighted' numbers in the first and the second row, labelled 'Total' and 'Filtered', which correspond to $\mathcal{L}\cdot\sigma$ and $\mathcal{L}\cdot\sigma\cdot\epsilon$ expected, respectively. The 'Skim' selection requires the $p_{\text{T}}$ of the leading four jets to be above (80, 60, 40, 40) GeV, the missing transverse momentum $E_{\text{T}}^{\text{miss}} > 140$ GeV, the missing momentum significance $\mathcal{S} > 8$, $\Delta\phi_{\min}(\vec{p}_{\text{T,1-4}},\vec{p}_{\text{T}}^{\text{miss}}) > 0.4$ and a lepton veto. The 'Orthogonalisation' selection is defined in the main body. In total 100000 raw MC events were generated prior to the specified cuts, with the column 'Unweighted yield' collecting the numbers after each cut.
Cutflow for the reference point DM+$tj$ $m(\phi, \chi) = (10, 1)$ GeV in signal region SR0X. The column labelled 'weighted' shows the event yield including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns the 'weighted' numbers in the first and the second row, labelled 'Total' and 'Filtered', which correspond to $\mathcal{L}\cdot\sigma$ and $\mathcal{L}\cdot\sigma\cdot\epsilon$ expected, respectively. The 'Skim' selection requires the $p_{\text{T}}$ of the leading four jets to be above (80, 60, 40, 40) GeV, the missing transverse momentum $E_{\text{T}}^{\text{miss}} > 140$ GeV, the missing momentum significance $\mathcal{S} > 8$, $\Delta\phi_{\min}(\vec{p}_{\text{T,1-4}},\vec{p}_{\text{T}}^{\text{miss}}) > 0.4$ and a lepton veto. The 'Orthogonalisation' selection is defined in the main body. In total 169000 raw MC events were generated prior to the specified cuts, with the column 'Unweighted yield' collecting the numbers after each cut.
Cutflow for the reference point DM+$tj$ $m(\phi, \chi) = (10, 1)$ GeV in signal region SRWX. The column labelled 'weighted' shows the event yield including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns the 'weighted' numbers in the first and the second row, labelled 'Total' and 'Filtered', which correspond to $\mathcal{L}\cdot\sigma$ and $\mathcal{L}\cdot\sigma\cdot\epsilon$ expected, respectively. The 'Skim' selection requires the $p_{\text{T}}$ of the leading four jets to be above (80, 60, 40, 40) GeV, the missing transverse momentum $E_{\text{T}}^{\text{miss}} > 140$ GeV, the missing momentum significance $\mathcal{S} > 8$, $\Delta\phi_{\min}(\vec{p}_{\text{T,1-4}},\vec{p}_{\text{T}}^{\text{miss}}) > 0.4$ and a lepton veto. The 'Orthogonalisation' selection is defined in the main body. In total 169000 raw MC events were generated prior to the specified cuts, with the column 'Unweighted yield' collecting the numbers after each cut.
Cutflow for the reference point DM+$tj$ $m(\phi, \chi) = (10, 1)$ GeV in signal region SRTX. The column labelled 'weighted' shows the event yield including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns the 'weighted' numbers in the first and the second row, labelled 'Total' and 'Filtered', which correspond to $\mathcal{L}\cdot\sigma$ and $\mathcal{L}\cdot\sigma\cdot\epsilon$ expected, respectively. The 'Skim' selection requires the $p_{\text{T}}$ of the leading four jets to be above (80, 60, 40, 40) GeV, the missing transverse momentum $E_{\text{T}}^{\text{miss}} > 140$ GeV, the missing momentum significance $\mathcal{S} > 8$, $\Delta\phi_{\min}(\vec{p}_{\text{T,1-4}},\vec{p}_{\text{T}}^{\text{miss}}) > 0.4$ and a lepton veto. The 'Orthogonalisation' selection is defined in the main body. In total 169000 raw MC events were generated prior to the specified cuts, with the column 'Unweighted yield' collecting the numbers after each cut.
Cutflow for the reference point DM+$tj$ $m(a, \chi) = (10, 1)$ GeV in signal region SR0X. The column labelled 'weighted' shows the event yield including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns the 'weighted' numbers in the first and the second row, labelled 'Total' and 'Filtered', which correspond to $\mathcal{L}\cdot\sigma$ and $\mathcal{L}\cdot\sigma\cdot\epsilon$ expected, respectively. The 'Skim' selection requires the $p_{\text{T}}$ of the leading four jets to be above (80, 60, 40, 40) GeV, the missing transverse momentum $E_{\text{T}}^{\text{miss}} > 140$ GeV, the missing momentum significance $\mathcal{S} > 8$, $\Delta\phi_{\min}(\vec{p}_{\text{T,1-4}},\vec{p}_{\text{T}}^{\text{miss}}) > 0.4$ and a lepton veto. The 'Orthogonalisation' selection is defined in the main body. In total 140000 raw MC events were generated prior to the specified cuts, with the column 'Unweighted yield' collecting the numbers after each cut.
Cutflow for the reference point DM+$tj$ $m(a, \chi) = (10, 1)$ GeV in signal region SRWX. The column labelled 'weighted' shows the event yield including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns the 'weighted' numbers in the first and the second row, labelled 'Total' and 'Filtered', which correspond to $\mathcal{L}\cdot\sigma$ and $\mathcal{L}\cdot\sigma\cdot\epsilon$ expected, respectively. The 'Skim' selection requires the $p_{\text{T}}$ of the leading four jets to be above (80, 60, 40, 40) GeV, the missing transverse momentum $E_{\text{T}}^{\text{miss}} > 140$ GeV, the missing momentum significance $\mathcal{S} > 8$, $\Delta\phi_{\min}(\vec{p}_{\text{T,1-4}},\vec{p}_{\text{T}}^{\text{miss}}) > 0.4$ and a lepton veto. The 'Orthogonalisation' selection is defined in the main body. In total 140000 raw MC events were generated prior to the specified cuts, with the column 'Unweighted yield' collecting the numbers after each cut.
Cutflow for the reference point DM+$tj$ $m(a, \chi) = (10, 1)$ GeV in signal region SRTX. The column labelled 'weighted' shows the event yield including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns the 'weighted' numbers in the first and the second row, labelled 'Total' and 'Filtered', which correspond to $\mathcal{L}\cdot\sigma$ and $\mathcal{L}\cdot\sigma\cdot\epsilon$ expected, respectively. The 'Skim' selection requires the $p_{\text{T}}$ of the leading four jets to be above (80, 60, 40, 40) GeV, the missing transverse momentum $E_{\text{T}}^{\text{miss}} > 140$ GeV, the missing momentum significance $\mathcal{S} > 8$, $\Delta\phi_{\min}(\vec{p}_{\text{T,1-4}},\vec{p}_{\text{T}}^{\text{miss}}) > 0.4$ and a lepton veto. The 'Orthogonalisation' selection is defined in the main body. In total 140000 raw MC events were generated prior to the specified cuts, with the column 'Unweighted yield' collecting the numbers after each cut.
A search for Higgs boson pair production in events with two $b$-jets and two $\tau$-leptons is presented, using a proton-proton collision dataset with an integrated luminosity of 139 fb$^{-1}$ collected at $\sqrt{s}=13$ TeV by the ATLAS experiment at the LHC. Higgs boson pairs produced non-resonantly or in the decay of a narrow scalar resonance in the mass range from 251 to 1600 GeV are targeted. Events in which at least one $\tau$-lepton decays hadronically are considered, and multivariate discriminants are used to reject the backgrounds. No significant excess of events above the expected background is observed in the non-resonant search. The largest excess in the resonant search is observed at a resonance mass of 1 TeV, with a local (global) significance of $3.1\sigma$ ($2.0\sigma$). Observed (expected) 95% confidence-level upper limits are set on the non-resonant Higgs boson pair-production cross-section at 4.7 (3.9) times the Standard Model prediction, assuming Standard Model kinematics, and on the resonant Higgs boson pair-production cross-section at between 21 and 900 fb (12 and 840 fb), depending on the mass of the narrow scalar resonance.
Breakdown of the relative contributions to the uncertainty in the extracted signal cross-sections, as determined in the likelihood fit (described in Section 8) to data. These are obtained by fixing the relevant nuisance parameters in the likelihood fit, and subtracting the obtained uncertainty on the fitted signal cross-sections in quadrature from the total uncertainty, and then dividing the result by the total uncertainty. The sum in quadrature of the individual components differs from the total uncertainty due to correlations between uncertainties in the different groups.
Post-fit expected number of signal and background events and observed number of data events in the last two bins of the non-resonant BDT score distribution of the SM signal after applying the selection criteria and requiring exactly 2 b-tagged jets and assuming a background-only hypothesis
Observed and expected upper limits at 95% CL on the cross-section of non-resonant HH production according to SM-like kinematics, and on the cross-section of non-resonant HH production divided by the SM prediction. The 1 sigma and 2 sigma variations around the expected limit are also shown.
Cumulative efficiency for simulated signal events to pass each stage of the event selection in the hadhad category. The efficiencies are calculated with respect to HH to bbtautau decays in which both tau-leptons decay hadronically. The ‘Pre-selection’ consists of basic requirements, including that at least two tau-had-vis pass loose kinematic requirements, at least one of the tau-had-vis candidate passes identification requirement, and that events do not contain an electron or muon. The ‘Object selections’ require exactly two tau-had-vis candidates, and at least two jets with pT > 25 GeV and abs(eta) < 2.5. The ‘Loose tau ID’ requires that both tau-had-vis candidates pass identification requirements. The ‘DTT offline jet cuts’ are cuts placed on the pT of the reconstructed jet or tau-had-vis that are geometrically matched to the HLT objects, to ensure the efficiencies of the HLT objects reach the plateau region.
Cumulative efficiency for simulated signal events to pass each stage of the event selection in the lephad SLT category. The efficiencies are calculated with respect to HH to bbtautau decays in which one tau-lepton decays hadronically and one decays leptonically. The ‘Pre-selection’ consists of basic requirements, including that at least one tau-had-vis candidate and one lepton pass loose kinematic requirements. The ‘Object selections’ require exactly one tau-had-vis candidate, and at least two jets with pT > 25 GeV and abs(eta) < 2.5. The ‘Trigger specific offline pT cuts’ are cuts placed on the pT of the reconstructed jet or tau-had-vis that are geometrically matched to the HLT objects, to ensure the efficiencies of the HLT objects reach the plateau region.
Cumulative efficiency for simulated signal events to pass each stage of the event selection in the lephad LTT category. The efficiencies are calculated with respect to HH to bbtautau decays in which one tau-lepton decays hadronically and one decays leptonically. The ‘Pre-selection’ consists of basic requirements, including that at least one tau-had-vis candidate and one lepton pass loose kinematic requirements. The ‘Object selections’ require exactly one tau-had-vis candidate, and at least two jets with pT > 25 GeV and abs(eta) < 2.5. The ‘Trigger specific offline pT cuts’ are cuts placed on the pT of the reconstructed jet or tau-had-vis that are geometrically matched to the HLT objects, to ensure the efficiencies of the HLT objects reach the plateau region.
Post-fit expected number of signal and background events and observed number of data events after applying the selection criteria and requiring exactly 2 b-tagged jets and assuming a background-only hypothesis.
Observed and expected limits at 95% CL on the cross-section of HH production, for the non-resonant ggF+VBF HH search, and the resonant HH search for four values of the resonance mass mX.
Acceptance times efficiency for the full analysis selections as a function of the resonance mass mX in the hadhad, lephad SLT and lephad LTT trigger categories, and the combined lephad. The acceptance times efficiency is evaluated for HH to bbtautau decays, with respect to the targeted tau-lepton decay modes (lephad or hadhad).
Post-fit distribution of mHH in the hadhad channel.
Post-fit distribution of mHH in the lephad SLT channel.
Post-fit distribution of mHH in the lephad LTT channel.
Post-fit distribution of mtautau MMC in the hadhad channel.
Post-fit distribution of mtautau MMC in the hadhad channel.
Post-fit distribution of mtautau MMC in the hadhad channel.
Post-fit distribution of of di-b-jet mass in the hadhad channel.
Post-fit distribution of di-b-jet mass in the LTT lephad channel.
Post-fit distribution of di-b-jet mass in the LTT lephad channel.
BDT for SM HH in the hadhad channel
NN for SM HH in the lephad SLT channel
NN for SM HH in the lephad LTT channel
PNN for mX = 500 GeV resonant HH in the hadhad channel
PNN for mX = 500 GeV resonant HH in the lephad SLT channel
PNN for mX = 500 GeV resonant HH in the lephad LTT channel
PNN for mX = 1000 GeV resonant HH in the hadhad channel
PNN for mX = 1000 GeV resonant HH in the lephad SLT channel
PNN for mX = 1000 GeV resonant HH in the lephad LTT channel
Event yields as a function of log10(S/B) for data, background and non-resonant HH signal. Final discriminant bins from the hadhad, lephad SLT and lephad LTT categories are combined into bins of log10(S/B). The B is the fitted background yield assuming background-only hypothesis, and the signal S is scaled to the SM expected cross-section.
Observed and expected limits at 95% CL on the cross-section of the resonant HH production as a function of the scalar resonance mass mX.
Post-fit distribution of delta-R between the taus in the hadhad channel.
Post-fit distribution of delta-R between the b-tagged jets in the hadhad channel.
Post-fit distribution of delta-R between the taus in the lephad SLT channel.
Post-fit distribution of delta-R between the b-tagged jets in the lephad SLT channel.
Post-fit distribution of delta-pT between the tau and lepton in the lephad SLT channel.
Post-fit distribution of pT of the subleading b-tagged jet in the lephad SLT channel.
Post-fit distribution of MTW in the lephad SLT channel.
Post-fit distribution of missing transverse momentum in the lephad SLT channel.
Post-fit distribution of missing transverse momentum centrality in the lephad SLT channel.
Post-fit distribution of delta-phi between the Higgs boson candidates in the lephad SLT channel.
Post-fit distribution of delta-pT between the tau and lepton in the lephad LTT channel.
Post-fit distribution of delta-R between the taus in the lephad LTT channel.
Post-fit distribution of delta-phi between the lepton and the missing transverse momentum in the lephad LTT channel.
Post-fit distribution of delta-phi between the Higgs boson candidates in the lephad LTT channel.
Post-fit distribution of the total transverse momentum s in the lephad LTT channel.
PNN for mX = 300 GeV resonant HH in the hadhad channel
PNN for mX = 300 GeV resonant HH in the lephad SLT channel
PNN for mX = 300 GeV resonant HH in the lephad LTT channel
PNN for mX = 1600 GeV resonant HH in the hadhad channel
PNN for mX = 1600 GeV resonant HH in the lephad SLT channel
PNN for mX = 1600 GeV resonant HH in the lephad LTT channel
Local p-value of the background-only hypothesis as a function of the resonance mass.
A measurement of single top-quark production in the s-channel is performed in proton$-$proton collisions at a centre-of-mass energy of 13 TeV with the ATLAS detector at the CERN Large Hadron Collider. The dataset corresponds to an integrated luminosity of 139 fb$^{-1}$. The analysis is performed on events with an electron or muon, missing transverse momentum and exactly two $b$-tagged jets in the final state. A discriminant based on matrix element calculations is used to separate single-top-quark s-channel events from the main background contributions, which are top-quark pair production and $W$-boson production in association with jets. The observed (expected) signal significance over the background-only hypothesis is 3.3 (3.9) standard deviations, and the measured cross-section is $\sigma=8.2^{+3.5}_{-2.9}$ pb, consistent with the Standard Model prediction of $\sigma^{\mathrm{SM}}=10.32^{+0.40}_{-0.36}$ pb.
Result of the s-channel single-top cross-section measurement, in pb. The statistical and systematic uncertainties are given, as well as the total uncertainty. The normalisation factors for the $t\bar{t}$ and $W$+jets backgrounds are also shown, with their total uncertainties.
Distribution of ${E}_{T}^{miss}$ after the fit of the multijet backgrounds, in the electron channel, in the signal region, without applying the cut on ${E}_{T}^{miss}$. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit. The last bin includes the overflow. The uncertainty band indicates the simulation's statistical uncertainty, the normalisation uncertainties for different processes ($40$ % for $W$+jets production, $30$ % for multijet background and $6$ % for top-quark processes) and the multijet background shape uncertainty in each bin, summed in quadrature. The lower panel of the figure shows the ratio of the data to the prediction.
Distribution of ${E}_{T}^{miss}$ after the fit of the multijet backgrounds, in the electron channel, in the $W$+jets VR, without applying the cut on ${E}_{T}^{miss}$. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit. The last bin includes the overflow. The uncertainty band indicates the simulation's statistical uncertainty, the normalisation uncertainties for different processes ($40$ % for $W$+jets production, $30$ % for multijet background and $6$ % for top-quark processes) and the multijet background shape uncertainty in each bin, summed in quadrature. The lower panel of the figure shows the ratio of the data to the prediction.
Distribution of ${E}_{T}^{miss}$ after the fit of the multijet backgrounds, in the electron channel, in the $t\bar{t}$ 3-jets VR, without applying the cut on ${E}_{T}^{miss}$. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit. The last bin includes the overflow. The uncertainty band indicates the simulation's statistical uncertainty, the normalisation uncertainties for different processes ($40$ % for $W$+jets production, $30$ % for multijet background and $6$ % for top-quark processes) and the multijet background shape uncertainty in each bin, summed in quadrature. The lower panel of the figure shows the ratio of the data to the prediction.
Distribution of ${E}_{T}^{miss}$ after the fit of the multijet backgrounds, in the electron channel, in the $t\bar{t}$ 4-jets VR, without applying the cut on ${E}_{T}^{miss}$. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit. The last bin includes the overflow. The uncertainty band indicates the simulation's statistical uncertainty, the normalisation uncertainties for different processes ($40$ % for $W$+jets production, $30$ % for multijet background and $6$ % for top-quark processes) and the multijet background shape uncertainty in each bin, summed in quadrature. The lower panel of the figure shows the ratio of the data to the prediction.
Distribution of $m_{T}^{W}$ after the fit of the multijet backgrounds, in the muon channel, in the signal region, without applying the cut on $m_{T}^{W}$. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit. The last bin includes the overflow. The uncertainty band indicates the simulation's statistical uncertainty, the normalisation uncertainties for different processes ($40$ % for $W$+jets production, $30$ % for multijet background and $6$ % for top-quark processes) and the multijet background shape uncertainty in each bin, summed in quadrature. The lower panel of the figure shows the ratio of the data to the prediction.
Distribution of $m_{T}^{W}$ after the fit of the multijet backgrounds, in the muon channel, in the $W$+jets VR, without applying the cut on $m_{T}^{W}$. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit. The last bin includes the overflow. The uncertainty band indicates the simulation's statistical uncertainty, the normalisation uncertainties for different processes ($40$ % for $W$+jets production, $30$ % for multijet background and $6$ % for top-quark processes) and the multijet background shape uncertainty in each bin, summed in quadrature. The lower panel of the figure shows the ratio of the data to the prediction.
Distribution of $m_{T}^{W}$ after the fit of the multijet backgrounds, in the muon channel, in the $t\bar{t}$ 3-jets VR, without applying the cut on $m_{T}^{W}$. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit. The last bin includes the overflow. The uncertainty band indicates the simulation's statistical uncertainty, the normalisation uncertainties for different processes ($40$ % for $W$+jets production, $30$ % for multijet background and $6$ % for top-quark processes) and the multijet background shape uncertainty in each bin, summed in quadrature. The lower panel of the figure shows the ratio of the data to the prediction.
Distribution of $m_{T}^{W}$ after the fit of the multijet backgrounds, in the muon channel, in the $t\bar{t}$ 4-jets VR, without applying the cut on $m_{T}^{W}$. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit. The last bin includes the overflow. The uncertainty band indicates the simulation's statistical uncertainty, the normalisation uncertainties for different processes ($40$ % for $W$+jets production, $30$ % for multijet background and $6$ % for top-quark processes) and the multijet background shape uncertainty in each bin, summed in quadrature. The lower panel of the figure shows the ratio of the data to the prediction.
Expected distributions of the MEM discriminant $P(S|X)$ in the SR, for the s-channel single-top signal, and for the $t\bar{t}$ and $W$+jets backgrounds, for MEM discriminant values larger than $2.0\times10^{-4}$. Each distribution is normalised to unity. The binning is the same as the optimised binning used in the signal extraction fit, resulting in a non-linear horizontal scale.
Distribution of the MEM discriminant $P(S|X)$ in the $W$+jets VR. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit presented in Section 5 in the paper. The uncertainty band indicates the simulation's statistical uncertainty and the normalisation uncertainties for the various processes in each bin, summed in quadrature. The ratio of the observed number to the predicted number of events in each bin is shown in the lower panel of the figure, with different vertical axis ranges. The binning is the same as the optimised binning used in the signal extraction fit described in Section 8 in the paper, resulting in a non-linear horizontal scale.
Distribution of the MEM discriminant $P(S|X)$ in the $t\bar{t}$ 3-jets VR. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit presented in Section 5 in the paper. The uncertainty band indicates the simulation's statistical uncertainty and the normalisation uncertainties for the various processes in each bin, summed in quadrature. The ratio of the observed number to the predicted number of events in each bin is shown in the lower panel of the figure, with different vertical axis ranges. The binning is the same as the optimised binning used in the signal extraction fit described in Section 8 in the paper, resulting in a non-linear horizontal scale.
Distribution of the MEM discriminant $P(S|X)$ in the $t\bar{t}$ 4-jets VR. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit presented in Section 5 in the paper. The uncertainty bands indicate the simulation's statistical uncertainty and the normalisation uncertainties for the various processes in each bin, summed in quadrature. The ratio of the observed number to the predicted number of events in each bin is shown in the lower panel of the figure, with different vertical axis ranges. The binning is the same as the optimised binning used in the signal extraction fit described in Section 8 in the paper, resulting in a non-linear horizontal scale.
Distribution of the MEM discriminant $P(S|X)$ in the SR before the fit to data, for MEM discriminant values larger than $2.0\times10^{-4}$. The lower panel of the figure shows the ratio of the data to the prediction, with different vertical axis ranges. The uncertainty band indicates the total uncertainties and their correlations in each bin. The uncertainties in the $t\bar{t}$ and $W$+jets normalisation factors, as well as in the s-channel signal cross-section, are not defined pre-fit and therefore not included. The binning is the same as the optimised binning used in the fit, resulting in a non-linear horizontal scale.
Distribution of the MEM discriminant $P(S|X)$ in the SR after the fit to data, for MEM discriminant values larger than $2.0\times10^{-4}$. The lower panel of the figure shows the ratio of the data to the prediction, with different vertical axis ranges. The uncertainty band indicates the total uncertainties and their correlations in each bin. The binning is the same as the optimised binning used in the fit, resulting in a non-linear horizontal scale.
Distribution of the MEM discriminant $P(S|X)$ in the SR after the fit to data, for MEM discriminant values larger than $2.0\times10^{-4}$, after subtraction of all backgrounds. The fitted distribution for the simulation of the signal is shown together with the post-fit uncertainty in the backgrounds. The binning is the same as the optimised binning used in the fit, resulting in a non-linear horizontal scale.
Pre-fit and post-fit event yields in the SR, for MEM discriminant values larger than $2.0\times10^{-4}$. The central value of the event yield for each process is calculated by summing the values of the discriminant bin contents, using the nominal expected yield for the pre-fit value, and the best-fit estimate for the post-fit value. The error includes statistical and systematic uncertainties summed in quadrature. All sources of systematic uncertainties are included, taking into account correlations and anti-correlations in the post-fit case. The uncertainties in the $t\bar{t}$ and $W$+jets normalisation factors, as well as in the s-channel signal cross-section, are not defined pre-fit and therefore only included in the post-fit uncertainties.
Observed impact of the different sources of uncertainty on the measured s-channel signal cross-section, grouped by categories. The impact of each category is obtained by repeating the fit after having fixed the set of nuisance parameters corresponding to that category, subtracting the square of the resulting uncertainty from the square of the uncertainty found in the full fit, and calculating the square root. The 'Systematic uncertainties' category combines all sources of systematic uncertainties. The statistical uncertainty is obtained by repeating the fit after having fixed all nuisance parameters, including the $t\bar{t}$ and $W$+jets normalisation factors. 'Total' gives the total uncertainty on the measurement.
Observed impact of the different sources of $t\bar{t}$ modelling uncertainty on the measured s-channel signal cross-section. The impact of each category is obtained by repeating the fit after having fixed the set of nuisance parameters corresponding to that category, subtracting the square of the resulting uncertainty from the square of the uncertainty found in the full fit, and calculating the square root. 'PS & had.' refers to the parton shower and hadronisation model, and 'ME/PS matching' to the matching of the ME to the parton shower.
Observed impact of the different sources of s-channel modelling uncertainty on the measured s-channel signal cross-section. The impact of each category is obtained by repeating the fit after having fixed the set of nuisance parameters corresponding to that category, subtracting the square of the resulting uncertainty from the square of the uncertainty found in the full fit, and calculating the square root. 'PS & had.' refers to the parton shower and hadronisation model, as described in Section 7 in the paper.
Observed impact of the different sources of t-channel modelling uncertainty on the measured s-channel signal cross-section. The impact of each category is obtained by repeating the fit after having fixed the set of nuisance parameters corresponding to that category, subtracting the square of the resulting uncertainty from the square of the uncertainty found in the full fit, and calculating the square root. 'PS & had.' refers to the parton shower and hadronisation model, as described in Section 7 in the paper.
Observed impact of the different sources of $tW$ modelling uncertainty on the measured s-channel signal cross-section, grouped by categories. The impact of each category is obtained by repeating the fit after having fixed the set of nuisance parameters corresponding to that category, subtracting the square of the resulting uncertainty from the square of the uncertainty found in the full fit, and calculating the square root. 'PS & had.' refers to the parton shower and hadronisation model, and '$t\bar{t}$ overlap' to the algorithm removing the overlap between $tW$ and $t\bar{t}$ production at NLO, as described in Section 7 in the paper.
Observed impact of the different sources of PDF uncertainties on the measured s-channel signal cross-section, grouped by categories. The impact of each category is obtained by repeating the fit after having fixed the set of nuisance parameters corresponding to that category, subtracting the square of the resulting uncertainty from the square of the uncertainty found in the full fit, and calculating the square root.
Comparison between data and prediction after the fit to data in the signal region for the leading-jet $p_{T}$. The last bin includes the overflow. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.
Comparison between data and prediction after the fit to data in the signal region for the leading-jet $\eta$. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.
Comparison between data and prediction after the fit to data in the signal region for the subleading-jet $p_{T}$. The last bin includes the overflow. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.
Comparison between data and prediction after the fit to data in the signal region for the subleading-jet $\eta$. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.
Comparison between data and prediction after the fit to data in the signal region for the lepton $p_{T}$. The last bin includes the overflow. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.
Comparison between data and prediction after the fit to data in the signal region for the lepton $\eta$. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.
Comparison between data and prediction after the fit to data in the signal region for the ${E}_{T}^{miss}$. The last bin includes the overflow. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.
Comparison between data and prediction after the fit to data in the signal region for the $m_{T}^{W}$. The last bin includes the overflow. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.
Nuisance parameters ranked according to their post-fit impacts on the best-fit value of the ratio $\mu$ of the measured cross-section to the predicted cross-section. In the figure, only the 20 nuisance parameters with the largest post-fit impacts are shown. The empty (solid) blue rectangles illustrate the pre-fit (post-fit) impact on $\mu$, corresponding to the upper axis. The pre-fit (post-fit) impact of each nuisance parameter, $\Delta\mu$, is calculated as the difference in the fitted value of $\mu$ between the nominal fit and the fit when fixing the corresponding nuisance parameter to $\hat{\theta}\pm\Delta\theta$ ($\hat{\theta}\pm\Delta\hat{\theta}$), where $\hat{\theta}$ is the best-fit value of the nuisance parameter and $\Delta\theta$ ($\Delta\hat{\theta}$) is its pre-fit (post-fit) uncertainty. Several systematic uncertainties are split into different nuisance parameters, which are indicated by NP. JES (JER) indicates jet energy scale (resolution), and $\gamma$ indicates a nuisance parameter associated to the MC statistics in one of the 18 bins numbered from 0 to 17. The black points show the best-fit values of the nuisance parameters, with the error bars representing the post-fit uncertainties. Each nuisance parameter is shown wrt. its nominal value, $\theta_0$, and in units of its pre-fit uncertainty, except the free-floating normalisation factors of the $t\bar{t}$ and $W$+jets backgrounds, and the parameters associated to the MC statistics in each bin, for which the post-fit values and uncertainties are shown.
Correlation matrix of the nuisance parameters and of the ratio $\mu$ of the measured cross-section to the predicted cross-section. The correlations are given after the fit to data. In the figure, only the parameters which have a correlation of at least 0.2 with any other parameter are shown.
Distribution of the MEM discriminant $P(S|X)$ in the SR for MEM discriminant values larger than $2.0\times10^{-4}$, for the collision data used for the measurement, and for 1000 pseudo-data replicas, generated using a bootstrapping technique, in order to assess the statistical correlations between this measurement and others, for the purpose of combinations. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the <a href="https://zenodo.org/record/5361038">BootstrapGenerator</a> software package , which implements a technique described in <a href="https://cds.cern.ch/record/2759945/">ATL-PHYS-PUB-2021-011</a>. The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. Each pseudo-data replica is assigned an index, ranging from 0 to 999, corresponding to the random number index used consistently for each observed data event.
Measured values of the signal cross-section and of the $t\bar{t}$ and $W$+jets normalisation factors, obtained by statistical-only fits to the collision data used for the measurement, and to 1000 pseudo-data replicas, generated using a bootstrapping technique, in order to assess the statistical correlations between this measurement and others, for the purpose of combinations. The central values and their statistical uncertainties are obtained by repeating the fit after having fixed all nuisance parameters, except the $t\bar{t}$ and $W$+jets normalisation factors, which are let free-floating (unlike for the statistical uncertainty on the cross-section quoted in the paper). The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the <a href="https://zenodo.org/record/5361038">BootstrapGenerator</a> software package , which implements a technique described in <a href="https://cds.cern.ch/record/2759945/">ATL-PHYS-PUB-2021-011</a>. The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. Each pseudo-data replica is assigned an index, ranging from 0 to 999, corresponding to the random number index used consistently for each observed data event.
A search for new phenomena has been performed in final states with at least one isolated high-momentum photon, jets and missing transverse momentum in proton--proton collisions at a centre-of-mass energy of $\sqrt{s} = 13$ TeV. The data, collected by the ATLAS experiment at the CERN LHC, correspond to an integrated luminosity of 139 $fb^{-1}$. The experimental results are interpreted in a supersymmetric model in which pair-produced gluinos decay into neutralinos, which in turn decay into a gravitino, at least one photon, and jets. No significant deviations from the predictions of the Standard Model are observed. Upper limits are set on the visible cross section due to physics beyond the Standard Model, and lower limits are set on the masses of the gluinos and neutralinos, all at 95% confidence level. Visible cross sections greater than 0.022 fb are excluded and pair-produced gluinos with masses up to 2200 GeV are excluded for most of the NLSP masses investigated.
The observed and expected (post-fit) yields in the control and validation regions. The lower panel shows the difference in standard deviations between the observed and expected yields, considering both the systematic and statistical uncertainties on the background expectation.
Observed (points with error bars) and expected background (solid histograms) distributions for $E_{T}^{miss}$ in the signal region (a) SRL, (b) SRM and (c) SRH after the background-only fit applied to the CRs. The predicted signal distributions for the two models with a gluino mass of 2000 GeV and neutralino mass of 250 GeV (SRL), 1050 GeV (SRM) or 1950 GeV (SRH) are also shown for comparison. The uncertainties in the SM background are only statistical.
Observed (points with error bars) and expected background (solid histograms) distributions for $E_{T}^{miss}$ in the signal region (a) SRL, (b) SRM and (c) SRH after the background-only fit applied to the CRs. The predicted signal distributions for the two models with a gluino mass of 2000 GeV and neutralino mass of 250 GeV (SRL), 1050 GeV (SRM) or 1950 GeV (SRH) are also shown for comparison. The uncertainties in the SM background are only statistical.
Observed (points with error bars) and expected background (solid histograms) distributions for $E_{T}^{miss}$ in the signal region (a) SRL, (b) SRM and (c) SRH after the background-only fit applied to the CRs. The predicted signal distributions for the two models with a gluino mass of 2000 GeV and neutralino mass of 250 GeV (SRL), 1050 GeV (SRM) or 1950 GeV (SRH) are also shown for comparison. The uncertainties in the SM background are only statistical.
Observed and expected exclusion limit in the gluino-neutralino mass plane at 95% CL combined using the signal region with the best expected sensitivity at each point, for the full Run-2 dataset corresponding to an integrated luminosity of $139~\mathrm{fb}^{-1}$, for $\gamma/Z$ (a) and $\gamma/h$ (b) signal models. The black solid line corresponds to the expected limits at 95% CL, with the light (yellow) bands indicating the 1$\sigma$ exclusions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves, the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties. For each point in the higgsino-bino parameter space, the labels indicate the best-expected signal region, where L, M and H mean SRL, SRM and SRH, respectively.
Observed and expected exclusion limit in the gluino-neutralino mass plane at 95% CL combined using the signal region with the best expected sensitivity at each point, for the full Run-2 dataset corresponding to an integrated luminosity of $139~\mathrm{fb}^{-1}$, for $\gamma/Z$ (a) and $\gamma/h$ (b) signal models. The black solid line corresponds to the expected limits at 95% CL, with the light (yellow) bands indicating the 1$\sigma$ exclusions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves, the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties. For each point in the higgsino-bino parameter space, the labels indicate the best-expected signal region, where L, M and H mean SRL, SRM and SRH, respectively.
Acceptance (left) and efficiency (right) for the $\gamma/Z$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).
Acceptance (left) and efficiency (right) for the $\gamma/Z$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).
Acceptance (left) and efficiency (right) for the $\gamma/Z$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).
Acceptance (left) and efficiency (right) for the $\gamma/Z$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).
Acceptance (left) and efficiency (right) for the $\gamma/Z$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).
Acceptance (left) and efficiency (right) for the $\gamma/Z$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).
Acceptance (left) and efficiency (right) for the $\gamma/h$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).
Acceptance (left) and efficiency (right) for the $\gamma/h$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).
Acceptance (left) and efficiency (right) for the $\gamma/h$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).
Acceptance (left) and efficiency (right) for the $\gamma/h$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).
Acceptance (left) and efficiency (right) for the $\gamma/h$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).
Acceptance (left) and efficiency (right) for the $\gamma/h$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).
Cutflow for the SRL selection, for two relevant signal points for both $\gamma/Z$ and $\gamma/h$ models, where the gluinos have mass of 2000 GeV and the neutralinos have a mass of 250 GeV (10000 generated events). The numbers are normalized to a luminosity of 139 $fb^{-1}$.
Cutflow for the SRM selection, for two relevant signal points for both $\gamma/Z$ and $\gamma/h$ models, where the gluinos have mass of 2000 GeV and the neutralinos have a mass of 1050 GeV (10000 generated events). The numbers are normalized to a luminosity of 139 $fb^{-1}$.
Cutflow for the SRH selection, for two relevant signal points for both $\gamma/Z$ and $\gamma/h$ models, where the gluinos have mass of 2000 GeV and the neutralinos have a mass of 1950 GeV (10000 generated events). The numbers are normalized to a luminosity of 139 $fb^{-1}$.
Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.
Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.
Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.
Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.
Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.
Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.
Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.
Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.
Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.
Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.
Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.
Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.
Searches for new phenomena inspired by supersymmetry in final states containing an $e^+e^-$ or $\mu^+\mu^-$ pair, jets, and missing transverse momentum are presented. These searches make use of proton-proton collision data with an integrated luminosity of 139 $\text{fb}^{-1}$, collected during 2015-2018 at a centre-of-mass energy $\sqrt{s}=13 $TeV by the ATLAS detector at the Large Hadron Collider. Two searches target the pair production of charginos and neutralinos. One uses the recursive-jigsaw reconstruction technique to follow up on excesses observed in 36.1 $\text{fb}^{-1}$ of data, and the other uses conventional event variables. The third search targets pair production of coloured supersymmetric particles (squarks or gluinos) decaying through the next-to-lightest neutralino $(\tilde\chi_2^0)$ via a slepton $(\tilde\ell)$ or $Z$ boson into $\ell^+\ell^-\tilde\chi_1^0$, resulting in a kinematic endpoint or peak in the dilepton invariant mass spectrum. The data are found to be consistent with the Standard Model expectations. Results are interpreted using simplified models and exclude masses up to 900 GeV for electroweakinos, 1550 GeV for squarks, and 2250 GeV for gluinos.
- - - - - - - - Overview of HEPData Record - - - - - - - - <br/><br/> <b>EWK SR distributions:</b> <a href="116034?version=1&table=Figure 11a">SR-High_8-EWK</a>; <a href="116034?version=1&table=Figure 11b">SR-ℓℓ𝑏𝑏-EWK</a>; <a href="116034?version=1&table=Figure 11c">SR-Int-EWK</a>; <a href="116034?version=1&table=Figure 11d">SR-Low-EWK</a>; <a href="116034?version=1&table=Figure 11e">SR-OffShell-EWK</a><br/><br/> <b>Strong SR distributions:</b> <a href="116034?version=1&table=Figure 13a">SRC-STR</a>; <a href="116034?version=1&table=Figure 13b">SRLow-STR</a>; <a href="116034?version=1&table=Figure 13c">SRMed-STR</a>; <a href="116034?version=1&table=Figure 13d">SRHigh-STR</a><br/><br/> <b>RJR SR Yields:</b> <a href="116034?version=1&table=Table 16">SR2l-Low-RJR, SR2l-ISR-RJR</a><br/><br/> <b>EWK SR Yields:</b> <a href="116034?version=1&table=Table 18">SR-High_16a-EWK, SR-High_8a-EWK, SR-1J-High-EWK, SR-ℓℓ𝑏𝑏-EWK, SR-High_16b-EWK, SR-High_8b-EWK</a>; <a href="116034?version=1&table=Table 19">SR-Int_a-EWK, SR-Low_a-EWK, SR-Low-2-EWK, SR-OffShell_a-EWK, SR-Int_b-EWK, SR-Low_b-EWK, SR-OffShell_b-EWK </a><br/><br/> <b>Strong SR Yields:</b> <a href="116034?version=1&table=Table 21">SRC-STR, SRLow-STR, SRMed-STR, SRHigh-STR</a>; <a href="116034?version=1&table=Table 22">SRZLow-STR, SRZMed-STR, SRZHigh-STR</a><br/><br/> <b>C1N2 Model Limits:</b> <a href="116034?version=1&table=Table 15a C1N2 Observed Limit">Obs</a>; <a href="116034?version=1&table=Table 15a C1N2 Expected Limit">Exp</a>; <a href="116034?version=1&table=Auxiliary Figure 34a C1N2 Expected XS Upper Limit">Upper Limits</a><br/><br/> <b>GMSB Model Limits:</b> <a href="116034?version=1&table=Table 15b GMSB Observed Limit">Obs</a>; <a href="116034?version=1&table=Table 15b GMSB Expected Limit">Exp</a>; <a href="116034?version=1&table=Auxiliary Figure 34b GMSB Expected XS Upper Limit">Upper Limits</a><br/><br/> <b>Gluon-Slepton Model Limits:</b> <a href="116034?version=1&table=Figure 16a Observed Limit">Obs</a>; <a href="116034?version=1&table=Figure 16a Expected Limit">Exp</a>; <a href="116034?version=1&table=Auxiliary Figure 23a XS Upper Limit">Upper Limits</a><br/><br/> <b>Gluon-Z* Model Limits:</b> <a href="116034?version=1&table=Figure 16b Observed Limit">Obs</a>; <a href="116034?version=1&table=Figure 16b Expected Limit">Exp</a>; <a href="116034?version=1&table=Auxiliary Figure 23b XS Upper Limit">Upper Limits</a><br/><br/> <b>Squark-Z* Model Limits:</b> <a href="116034?version=1&table=Figure 16c Observed Limit">Obs</a>; <a href="116034?version=1&table=Figure 16c Expected Limit">Exp</a>; <a href="116034?version=1&table=Auxiliary Figure 23c XS Upper Limit">Upper Limits</a><br/><br/> <b>EWK VR distributions:</b> <a href="116034?version=1&table=Figure 4a S_ETmiss in VR-High-Sideband-EWK">VR-High-Sideband-EWK</a>; <a href="116034?version=1&table=Figure 4b S_Etmiss in VR-High-R-EWK">VR-High-R-EWK</a>; <a href="116034?version=1&table=Figure 4c S_Etmiss in VR-1J-High-EWK">VR-1J-High-EWK</a>; <a href="116034?version=1&table=Figure 4d S_Etmiss in VR-llbb-EWK">VR-ℓℓ𝑏𝑏-EWK</a>; <a href="116034?version=1&table=Figure 5a S_Etmiss in VR-Int-EWK">VR-Int-EWK</a>; <a href="116034?version=1&table=Figure 5b S_Etmiss in VR-Low-EWK">VR-Low-EWK</a>; <a href="116034?version=1&table=Figure 5c S_Etmiss in VR-Low-2-EWK">VR-Low-2-EWK</a>; <a href="116034?version=1&table=Figure 5d S_Etmiss in VR-OffShell-EWK">VR-OffShell-EWK</a><br/><br/> <b>Strong VR distributions:</b> <a href="116034?version=1&table=Figure 6a">VRC-STR</a>; <a href="116034?version=1&table=Figure 6b">VRLow-STR</a>; <a href="116034?version=1&table=Figure 6c">VRMed-STR</a>; <a href="116034?version=1&table=Figure 6d">VRHigh-STR</a>; <a href="116034?version=1&table=Figure 8">VR3L-STR</a><br/><br/> <b>Other Strong distributions:</b> <a href="116034?version=1&table=Auxiliary Figure 17a">SRLow-STR + VRLow-STR</a><br/><br/> <b>Other EWK distributions:</b> <a href="116034?version=1&table=Auxiliary Figure 33a Mjj in CR-Z-EWK and SR-Low-EWK">CR-Z-EWK + SR-Low-EWK</a>; <a href="116034?version=1&table=Auxiliary Figure 33b S_ETmiss in CR-Z-met-EWK">CR-Z-met-EWK</a><br/><br/> <b>Strong Signal Cutflows:</b> <a href="116034?version=1&table=Auxiliary Table 30-31 SRC-STR Cutflow">SRC-STR GG_N2_ZN1</a>; <a href="116034?version=1&table=Auxiliary Table 30-31 SRMed-STR Cutflow">SRC-STR SS_N2_ZN1</a>; <a href="116034?version=1&table=Auxiliary Table 30-31 SRLow-STR Cutflow">SRLow-STR GG_N2_SLN1</a>; <a href="116034?version=1&table=Auxiliary Table 30-31 SRHigh-STR Cutflow">SRC-STR GG_N2_SLN1</a>; <a href="116034?version=1&table=Auxiliary Table 30-31 SRZLow-STR Cutflow">SRZLow-STR SS_N2_ZN1</a>; <a href="116034?version=1&table=Auxiliary Table 30-31 SRZMed-STR Cutflow">SRZMed-STR SS_N2_ZN1</a>; <a href="116034?version=1&table=Auxiliary Table 30-31 SRZHigh-STR Cutflow">SRZHigh-STR SS_N2_ZN1</a><br/><br/> <b>EWK Signal Cutflows:</b> <a href="116034?version=1&table=Auxiliary Table 36 SR-OffShell_a-EWK Cutflow"> SR-OffShell_a-EWK</a>; <a href="116034?version=1&table=Auxiliary Table 37 SR-OffShell_b-EWK Cutflow"> SR-OffShell_b-EWK</a>; <a href="116034?version=1&table=Auxiliary Table 38 SR-Low_a-EWK Cutflow"> SR-Low_a-EWK</a>; <a href="116034?version=1&table=Auxiliary Table 39 SR-Low_b-EWK Cutflow"> SR-Low_b-EWK</a>; <a href="116034?version=1&table=Auxiliary Table 40 SR-Low-2-EWK Cutflow"> SR-Low-2-E</a>; <a href="116034?version=1&table=Auxiliary Table 41 SR-Int_a-EWK Cutflow"> SR-Int_a-EWK</a>; <a href="116034?version=1&table=Auxiliary Table 42 SR-Int_b-EWK Cutflow"> SR-Int_b-EWK</a>; <a href="116034?version=1&table=Auxiliary Table 43 SR-High_16a-EWK Cutflow"> SR-High_16a-EWK</a>; <a href="116034?version=1&table=Auxiliary Table 44 SR-High_16b-EWK Cutflow"> SR-High_16b-EWK</a>; <a href="116034?version=1&table=Auxiliary Table 45 SR-High_8a-EWK Cutflow"> SR-High_8a-EWK</a>; <a href="116034?version=1&table=Auxiliary Table 46 SR-High_8b-EWK Cutflow"> SR-High_8b-EWK</a>; <a href="116034?version=1&table=Auxiliary Table 47 SR-1J-High-EWK Cutflow"> SR-1J-Hig</a>; <a href="116034?version=1&table=Auxiliary Table 48 SR-llbb-EWK Cutflow"> SR-llbb-EWK</a><br/><br/> <b>EWK Signal Number of MC Events:</b> <a href="116034?version=1&table=Auxiliary Table 36 SR-OffShell_a-EWK Generated"> SR-OffShell_a-EWK</a>; <a href="116034?version=1&table=Auxiliary Table 37 SR-OffShell_b-EWK Generated"> SR-OffShell_b-EWK</a>; <a href="116034?version=1&table=Auxiliary Table 38 SR-Low_a-EWK Generated"> SR-Low_a-EWK</a>; <a href="116034?version=1&table=Auxiliary Table 39 SR-Low_b-EWK Generated"> SR-Low_b-EWK</a>; <a href="116034?version=1&table=Auxiliary Table 40 SR-Low-2-EWK Generated"> SR-Low-2-E</a>; <a href="116034?version=1&table=Auxiliary Table 41 SR-Int_a-EWK Generated"> SR-Int_a-EWK</a>; <a href="116034?version=1&table=Auxiliary Table 42 SR-Int_b-EWK Generated"> SR-Int_b-EWK</a>; <a href="116034?version=1&table=Auxiliary Table 43 SR-High_16a-EWK Generated"> SR-High_16a-EWK</a>; <a href="116034?version=1&table=Auxiliary Table 44 SR-High_16b-EWK Generated"> SR-High_16b-EWK</a>; <a href="116034?version=1&table=Auxiliary Table 45 SR-High_8a-EWK Generated"> SR-High_8a-EWK</a>; <a href="116034?version=1&table=Auxiliary Table 46 SR-High_8b-EWK Generated"> SR-High_8b-EWK</a>; <a href="116034?version=1&table=Auxiliary Table 47 SR-1J-High-EWK Generated"> SR-1J-Hig</a>; <a href="116034?version=1&table=Auxiliary Table 48 SR-llbb-EWK Generated"> SR-llbb-EWK</a><br/><br/> <b>SRC-STR Signal Acceptance:</b> <a href="116034?version=1&table=GG_N2_SLN1 acc in SRC">GG_N2_SLN1</a>; <a href="116034?version=1&table=GG_N2_ZN1 acc in SRC">GG_N2_ZN1</a>; <a href="116034?version=1&table=SS_N2_ZN1 acc in SRC">SS_N2_ZN1</a><br/><br/> <b>SRLow-STR Signal Acceptance:</b> <a href="116034?version=1&table=GG_N2_SLN1 acc in SRLow">GG_N2_SLN1</a>; <a href="116034?version=1&table=GG_N2_ZN1 acc in SRLow">GG_N2_ZN1</a>; <a href="116034?version=1&table=SS_N2_ZN1 acc in SRLow">SS_N2_ZN1</a><br/><br/> <b>SRMed-STR Signal Acceptance:</b> <a href="116034?version=1&table=GG_N2_SLN1 acc in SRMed">GG_N2_SLN1</a>; <a href="116034?version=1&table=GG_N2_ZN1 acc in SRMed">GG_N2_ZN1</a>; <a href="116034?version=1&table=SS_N2_ZN1 acc in SRMed">SS_N2_ZN1</a><br/><br/> <b>SRHigh-STR Signal Acceptance:</b> <a href="116034?version=1&table=GG_N2_SLN1 acc in SRHigh">GG_N2_SLN1</a>; <a href="116034?version=1&table=GG_N2_ZN1 acc in SRHigh">GG_N2_ZN1</a>; <a href="116034?version=1&table=SS_N2_ZN1 acc in SRHigh">SS_N2_ZN1</a><br/><br/> <b>SRZLow-STR Signal Acceptance:</b> <a href="116034?version=1&table=GG_N2_ZN1 acc in SRZLow">GG_N2_ZN1</a>; <a href="116034?version=1&table=SS_N2_ZN1 acc in SRZLow">SS_N2_ZN1</a><br/><br/> <b>SRZMed-STR Signal Acceptance:</b> <a href="116034?version=1&table=GG_N2_ZN1 acc in SRZMed">GG_N2_ZN1</a>; <a href="116034?version=1&table=SS_N2_ZN1 acc in SRZMed">SS_N2_ZN1</a><br/><br/> <b>SRZHigh-STR Signal Acceptance:</b> <a href="116034?version=1&table=GG_N2_ZN1 acc in SRZHigh">GG_N2_ZN1</a>; <a href="116034?version=1&table=SS_N2_ZN1 acc in SRZHigh">SS_N2_ZN1</a><br/><br/> <b>SRC-STR Signal Efficiency:</b> <a href="116034?version=1&table=GG_N2_SLN1 eff in SRC">GG_N2_SLN1</a>; <a href="116034?version=1&table=GG_N2_ZN1 eff in SRC">GG_N2_ZN1</a>; <a href="116034?version=1&table=SS_N2_ZN1 eff in SRC">SS_N2_ZN1</a><br/><br/> <b>SRLow-STR Signal Efficiency:</b> <a href="116034?version=1&table=GG_N2_SLN1 eff in SRLow">GG_N2_SLN1</a>; <a href="116034?version=1&table=GG_N2_ZN1 eff in SRLow">GG_N2_ZN1</a>; <a href="116034?version=1&table=SS_N2_ZN1 eff in SRLow">SS_N2_ZN1</a><br/><br/> <b>SRMed-STR Signal Efficiency:</b> <a href="116034?version=1&table=GG_N2_SLN1 eff in SRMed">GG_N2_SLN1</a>; <a href="116034?version=1&table=GG_N2_ZN1 eff in SRMed">GG_N2_ZN1</a>; <a href="116034?version=1&table=SS_N2_ZN1 eff in SRMed">SS_N2_ZN1</a><br/><br/> <b>SRHigh-STR Signal Efficiency:</b> <a href="116034?version=1&table=GG_N2_SLN1 eff in SRHigh">GG_N2_SLN1</a>; <a href="116034?version=1&table=GG_N2_ZN1 eff in SRHigh">GG_N2_ZN1</a>; <a href="116034?version=1&table=SS_N2_ZN1 eff in SRHigh">SS_N2_ZN1</a><br/><br/> <b>SRZLow-STR Signal Efficiency:</b> <a href="116034?version=1&table=GG_N2_ZN1 eff in SRZLow">GG_N2_ZN1</a>; <a href="116034?version=1&table=SS_N2_ZN1 eff in SRZLow">SS_N2_ZN1</a><br/><br/> <b>SRZMed-STR Signal Efficiency:</b> <a href="116034?version=1&table=GG_N2_ZN1 eff in SRZMed">GG_N2_ZN1</a>; <a href="116034?version=1&table=SS_N2_ZN1 eff in SRZMed">SS_N2_ZN1</a><br/><br/> <b>SRZHigh-STR Signal Efficiency:</b> <a href="116034?version=1&table=GG_N2_ZN1 eff in SRZHigh">GG_N2_ZN1</a>; <a href="116034?version=1&table=SS_N2_ZN1 eff in SRZHigh">SS_N2_ZN1</a><br/><br/> <b>SR-OffShell_a-EWK Signal Acceptance:</b><a href="116034?version=1&table=GMSB acc in SR-OffShell_a-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 acc in SR-OffShell_a-EWK">C1N2</a>; <br/><br/> <b>SR-OffShell_b-EWK Signal Acceptance:</b><a href="116034?version=1&table=GMSB acc in SR-OffShell_b-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 acc in SR-OffShell_b-EWK">C1N2</a>; <br/><br/> <b>SR-Low_a-EWK Signal Acceptance:</b><a href="116034?version=1&table=GMSB acc in C1N2 acc in SR-Low_a-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 acc in C1N2 acc in SR-Low_a-EWK">C1N2</a>; <br/><br/> <b>SR-Low_b-EWK Signal Acceptance:</b><a href="116034?version=1&table=GMSB acc in SR-Low_b-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 acc in SR-Low_b-EWK">C1N2</a>; <br/><br/> <b>SR-Int_a-EWK Signal Acceptance:</b><a href="116034?version=1&table=GMSB acc in SR-Int_a-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 acc in SR-Int_a-EWK">C1N2</a>; <br/><br/> <b>SR-Int_b-EWK Signal Acceptance:</b><a href="116034?version=1&table=GMSB acc in SR-Int_b-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 acc in SR-Int_b-EWK">C1N2</a>; <br/><br/> <b>SR-High_16a-EWK Signal Acceptance:</b><a href="116034?version=1&table=GMSB acc in SR-High_16a-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 acc in SR-High_16a-EWK">C1N2</a>; <br/><br/> <b>SR-High_16b-EWK Signal Acceptance:</b><a href="116034?version=1&table=GMSB acc in SR-High_16b-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 acc in SR-High_16b-EWK">C1N2</a>; <br/><br/> <b>SR-High_8a-EWK Signal Acceptance:</b><a href="116034?version=1&table=GMSB acc in SR-High_8a-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 acc in SR-High_8a-EWK">C1N2</a>; <br/><br/> <b>SR-High_8b-EWK Signal Acceptance:</b><a href="116034?version=1&table=GMSB acc in SR-High_8b-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 acc in SR-High_8b-EWK">C1N2</a>; <br/><br/> <b>SR-1J-High-EWK Signal Acceptance:</b><a href="116034?version=1&table=GMSB acc in SR-1J-High-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 acc in SR-1J-High-EWK">C1N2</a>; <br/><br/> <b>SR-llbb-EWK Signal Acceptance:</b><a href="116034?version=1&table=GMSB acc in SR-llbb-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 acc in SR-llbb-EWK">C1N2</a>; <br/><br/> <b>SR-OffShell_a-EWK Signal Efficiency:</b><a href="116034?version=1&table=GMSB eff in SR-OffShell_a-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 eff in SR-OffShell_a-EWK">C1N2</a>; <br/><br/> <b>SR-OffShell_b-EWK Signal Efficiency:</b><a href="116034?version=1&table=GMSB eff in SR-OffShell_b-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 eff in SR-OffShell_b-EWK">C1N2</a>; <br/><br/> <b>SR-Low_a-EWK Signal Efficiency:</b><a href="116034?version=1&table=GMSB eff in C1N2 eff in SR-Low_a-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 eff in C1N2 eff in SR-Low_a-EWK">C1N2</a>; <br/><br/> <b>SR-Low_b-EWK Signal Efficiency:</b><a href="116034?version=1&table=GMSB eff in SR-Low_b-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 eff in SR-Low_b-EWK">C1N2</a>; <br/><br/> <b>SR-Int_a-EWK Signal Efficiency:</b><a href="116034?version=1&table=GMSB eff in SR-Int_a-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 eff in SR-Int_a-EWK">C1N2</a>; <br/><br/> <b>SR-Int_b-EWK Signal Efficiency:</b><a href="116034?version=1&table=GMSB eff in SR-Int_b-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 eff in SR-Int_b-EWK">C1N2</a>; <br/><br/> <b>SR-High_16a-EWK Signal Efficiency:</b><a href="116034?version=1&table=GMSB eff in SR-High_16a-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 eff in SR-High_16a-EWK">C1N2</a>; <br/><br/> <b>SR-High_16b-EWK Signal Efficiency:</b><a href="116034?version=1&table=GMSB eff in SR-High_16b-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 eff in SR-High_16b-EWK">C1N2</a>; <br/><br/> <b>SR-High_8a-EWK Signal Efficiency:</b><a href="116034?version=1&table=GMSB eff in SR-High_8a-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 eff in SR-High_8a-EWK">C1N2</a>; <br/><br/> <b>SR-High_8b-EWK Signal Efficiency:</b><a href="116034?version=1&table=GMSB eff in SR-High_8b-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 eff in SR-High_8b-EWK">C1N2</a>; <br/><br/> <b>SR-1J-High-EWK Signal Efficiency:</b><a href="116034?version=1&table=GMSB eff in SR-1J-High-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 eff in SR-1J-High-EWK">C1N2</a>; <br/><br/> <b>SR-llbb-EWK Signal Efficiency:</b><a href="116034?version=1&table=GMSB eff in SR-llbb-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 eff in SR-llbb-EWK">C1N2</a>; <br/><br/> <b>Truth Code snippets</b>, <b>SLHA files</b>, and <b>PYHF json likelihoods</b> are available under "Resources" (purple button on the left) ---- Record created with hepdata_lib 0.7.0: https://zenodo.org/record/4946277 and PYHF: https://doi.org/10.5281/zenodo.1169739
Breakdown of expected and observed yields in the two recursive-jigsaw reconstruction signal regions after a simultaneous fit of the the CRs. The two sets of regions are fit separately. The uncertainties include both statistical and systematic sources.
Breakdown of expected and observed yields in the electroweak search High and $\ell\ell bb$ signal regions after a simultaneous fit to the signal regions and control regions. All statistical and systematic uncertainties are included.
Breakdown of expected and observed yields in the electroweak search Int, Low, and OffShell signal regions after a simultaneous fit to the signal regions and control regions. All statistical and systematic uncertainties are included.
Breakdown of expected and observed yields in the four edge signal regions, integrated over the $m_{\ell\ell}$ distribution after a separate simultaneous fit to each signal region and control region pair. The uncertainties include both the statistical and systematic sources.
Breakdown of expected and observed yields in the three on-$Z$ signal regions after a separate simultaneous fit to each signal region and control region pair. The uncertainties include both the statistical and systematic sources.
Distributions of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in VR-High-Sideband-EWK (top-left), VR-High-R-EWK (top-right), VR-1J-High-EWK (bottom-left), and VR-$\ell\ell bb$-EWK (bottom-right) from the EWK search after a simultaneous fit of the control regions. The hatched band includes both the systematic and statistical uncertainties. The last bin includes the overflow.
Distributions of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in VR-High-Sideband-EWK (top-left), VR-High-R-EWK (top-right), VR-1J-High-EWK (bottom-left), and VR-$\ell\ell bb$-EWK (bottom-right) from the EWK search after a simultaneous fit of the control regions. The hatched band includes both the systematic and statistical uncertainties. The last bin includes the overflow.
Distributions of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in VR-High-Sideband-EWK (top-left), VR-High-R-EWK (top-right), VR-1J-High-EWK (bottom-left), and VR-$\ell\ell bb$-EWK (bottom-right) from the EWK search after a simultaneous fit of the control regions. The hatched band includes both the systematic and statistical uncertainties. The last bin includes the overflow.
Distributions of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in VR-High-Sideband-EWK (top-left), VR-High-R-EWK (top-right), VR-1J-High-EWK (bottom-left), and VR-$\ell\ell bb$-EWK (bottom-right) from the EWK search after a simultaneous fit of the control regions. The hatched band includes both the systematic and statistical uncertainties. The last bin includes the overflow.
Distributions of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in VR-Int-EWK (top-left), VR-Low-EWK (top-right), VR-Low-2-EWK (bottom-left), and VR-OffShell-EWK (bottom-right) from the EWK search after a simultaneous fit of the control regions. The hatched band includes both the systematic and statistical uncertainties. The last bin includes the overflow.
Distributions of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in VR-Int-EWK (top-left), VR-Low-EWK (top-right), VR-Low-2-EWK (bottom-left), and VR-OffShell-EWK (bottom-right) from the EWK search after a simultaneous fit of the control regions. The hatched band includes both the systematic and statistical uncertainties. The last bin includes the overflow.
Distributions of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in VR-Int-EWK (top-left), VR-Low-EWK (top-right), VR-Low-2-EWK (bottom-left), and VR-OffShell-EWK (bottom-right) from the EWK search after a simultaneous fit of the control regions. The hatched band includes both the systematic and statistical uncertainties. The last bin includes the overflow.
Distributions of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in VR-Int-EWK (top-left), VR-Low-EWK (top-right), VR-Low-2-EWK (bottom-left), and VR-OffShell-EWK (bottom-right) from the EWK search after a simultaneous fit of the control regions. The hatched band includes both the systematic and statistical uncertainties. The last bin includes the overflow.
Observed and expected dilepton mass distributions in VRC-STR (top-left), VRLow-STR (top-right), VRMed-STR (bottom-left), and VRHigh-STR (bottom-right). Each validation region is fit separately with the corresponding control region. All statistical and systematic uncertainties are included in the hatched band. The entries are normalized to the bin width, and the last bin is the overflow.
Observed and expected dilepton mass distributions in VRC-STR (top-left), VRLow-STR (top-right), VRMed-STR (bottom-left), and VRHigh-STR (bottom-right). Each validation region is fit separately with the corresponding control region. All statistical and systematic uncertainties are included in the hatched band. The entries are normalized to the bin width, and the last bin is the overflow.
Observed and expected dilepton mass distributions in VRC-STR (top-left), VRLow-STR (top-right), VRMed-STR (bottom-left), and VRHigh-STR (bottom-right). Each validation region is fit separately with the corresponding control region. All statistical and systematic uncertainties are included in the hatched band. The entries are normalized to the bin width, and the last bin is the overflow.
Observed and expected dilepton mass distributions in VRC-STR (top-left), VRLow-STR (top-right), VRMed-STR (bottom-left), and VRHigh-STR (bottom-right). Each validation region is fit separately with the corresponding control region. All statistical and systematic uncertainties are included in the hatched band. The entries are normalized to the bin width, and the last bin is the overflow.
Observed and expected jet multiplicity in VRLow-STR (top-left), VRMed-STR (top-right), and VRHigh-STR (bottom) after a fit performed on the $m_{\ell\ell}$ distribution and corresponding control region. All statistical and systematic uncertainties are included in the hatched band. The last bin contains the overflow.
Observed and expected jet multiplicity in VRLow-STR (top-left), VRMed-STR (top-right), and VRHigh-STR (bottom) after a fit performed on the $m_{\ell\ell}$ distribution and corresponding control region. All statistical and systematic uncertainties are included in the hatched band. The last bin contains the overflow.
Observed and expected jet multiplicity in VRLow-STR (top-left), VRMed-STR (top-right), and VRHigh-STR (bottom) after a fit performed on the $m_{\ell\ell}$ distribution and corresponding control region. All statistical and systematic uncertainties are included in the hatched band. The last bin contains the overflow.
Observed and expected dilepton mass distributions in VR3L-STR without a fit to the data. The 'Other' category includes the negligible contributions from $t\bar{t}$ and $Z/\gamma^*$+jets processes. The hatched band contains the statistical uncertainty and the theoretical systematic uncertainties of the $WZ$/$ZZ$ prediction, which are the dominant sources of uncertainty. No fit is performed. The last bin contains the overflow.
Observed and expected distributions in five EWK search regions after a simultaneous fit to the SR and CR. In the top row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-High_8-EWK and $m_{bb}$ in SR-$\ell\ell bb$-EWK. In the middle row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Int-EWK and $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Low-EWK. In the bottom row is $m_{\ell\ell}$ in SR-OffShell-EWK. Overlaid are example C1N2 and GMSB signal models, where the numbers in the brackets indicate the masses, in $\mathrm{GeV}$, of the $\tilde{\chi}_1^\pm$ and $\tilde{\chi}_2^0$ or the mass of the $\tilde{\chi}_1^0$ and branching ratio to the Higgs boson respectively. All statistical and systematic uncertainties are included in the hatched bands. The last bin includes the overflow.
Observed and expected distributions in five EWK search regions after a simultaneous fit to the SR and CR. In the top row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-High_8-EWK and $m_{bb}$ in SR-$\ell\ell bb$-EWK. In the middle row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Int-EWK and $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Low-EWK. In the bottom row is $m_{\ell\ell}$ in SR-OffShell-EWK. Overlaid are example C1N2 and GMSB signal models, where the numbers in the brackets indicate the masses, in $\mathrm{GeV}$, of the $\tilde{\chi}_1^\pm$ and $\tilde{\chi}_2^0$ or the mass of the $\tilde{\chi}_1^0$ and branching ratio to the Higgs boson respectively. All statistical and systematic uncertainties are included in the hatched bands. The last bin includes the overflow.
Observed and expected distributions in five EWK search regions after a simultaneous fit to the SR and CR. In the top row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-High_8-EWK and $m_{bb}$ in SR-$\ell\ell bb$-EWK. In the middle row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Int-EWK and $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Low-EWK. In the bottom row is $m_{\ell\ell}$ in SR-OffShell-EWK. Overlaid are example C1N2 and GMSB signal models, where the numbers in the brackets indicate the masses, in $\mathrm{GeV}$, of the $\tilde{\chi}_1^\pm$ and $\tilde{\chi}_2^0$ or the mass of the $\tilde{\chi}_1^0$ and branching ratio to the Higgs boson respectively. All statistical and systematic uncertainties are included in the hatched bands. The last bin includes the overflow.
Observed and expected distributions in five EWK search regions after a simultaneous fit to the SR and CR. In the top row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-High_8-EWK and $m_{bb}$ in SR-$\ell\ell bb$-EWK. In the middle row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Int-EWK and $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Low-EWK. In the bottom row is $m_{\ell\ell}$ in SR-OffShell-EWK. Overlaid are example C1N2 and GMSB signal models, where the numbers in the brackets indicate the masses, in $\mathrm{GeV}$, of the $\tilde{\chi}_1^\pm$ and $\tilde{\chi}_2^0$ or the mass of the $\tilde{\chi}_1^0$ and branching ratio to the Higgs boson respectively. All statistical and systematic uncertainties are included in the hatched bands. The last bin includes the overflow.
Observed and expected distributions in five EWK search regions after a simultaneous fit to the SR and CR. In the top row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-High_8-EWK and $m_{bb}$ in SR-$\ell\ell bb$-EWK. In the middle row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Int-EWK and $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Low-EWK. In the bottom row is $m_{\ell\ell}$ in SR-OffShell-EWK. Overlaid are example C1N2 and GMSB signal models, where the numbers in the brackets indicate the masses, in $\mathrm{GeV}$, of the $\tilde{\chi}_1^\pm$ and $\tilde{\chi}_2^0$ or the mass of the $\tilde{\chi}_1^0$ and branching ratio to the Higgs boson respectively. All statistical and systematic uncertainties are included in the hatched bands. The last bin includes the overflow.
Observed and expected dilepton mass distributions in SRC-STR (top-left), SRLow-STR (top-right), SRMed-STR (bottom-left), and SRHigh-STR (bottom-right), with the binning used for interpretations after a separate simultaneous fit to each signal region and control region pair. The red dashed lines are example signal models overlaid on the figure. All statistical and systematic uncertainties are included in the hatched bands. The last bins are the overflow.
Observed and expected dilepton mass distributions in SRC-STR (top-left), SRLow-STR (top-right), SRMed-STR (bottom-left), and SRHigh-STR (bottom-right), with the binning used for interpretations after a separate simultaneous fit to each signal region and control region pair. The red dashed lines are example signal models overlaid on the figure. All statistical and systematic uncertainties are included in the hatched bands. The last bins are the overflow.
Observed and expected dilepton mass distributions in SRC-STR (top-left), SRLow-STR (top-right), SRMed-STR (bottom-left), and SRHigh-STR (bottom-right), with the binning used for interpretations after a separate simultaneous fit to each signal region and control region pair. The red dashed lines are example signal models overlaid on the figure. All statistical and systematic uncertainties are included in the hatched bands. The last bins are the overflow.
Observed and expected dilepton mass distributions in SRC-STR (top-left), SRLow-STR (top-right), SRMed-STR (bottom-left), and SRHigh-STR (bottom-right), with the binning used for interpretations after a separate simultaneous fit to each signal region and control region pair. The red dashed lines are example signal models overlaid on the figure. All statistical and systematic uncertainties are included in the hatched bands. The last bins are the overflow.
Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].
Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].
Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].
Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].
Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].
Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].
Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].
Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].
Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].
Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].
Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].
Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].
Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294]. The grey numbers indicate the observed 95\% CLs upper limit on the cross section.
Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294]. The grey numbers indicate the observed 95$\%$ CLs upper limit on the cross section.
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$ ilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$ ilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$ ilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$ ilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].The grey numbers indicated the observed 95\% CL upper limit on the cross section.
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].The grey numbers indicated the observed 95\% CL upper limit on the cross section.
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].The grey numbers indicated the observed 95\% CL upper limit on the cross section.
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
The combined $E_{\mathrm{T}}^{\mathrm{miss}}$ distribution of VRLow-STR and SRLow-STR (left), and the same region with the $\Delta\phi(\boldsymbol{j}_{1,2},\boldsymbol{\mathit{p}}_{ ext{T}}^{ ext{miss}})<0.4$ requirement, used as a control region to normalize the $Z/\gamma^*+\mathrm{jets}$ process (right). Separate fits for the SR and VR are performed, as for the results in the paper, and the resulting distributions are merged. All statistical and systematic uncertainties are included in the hatched bands. The last bins contain the overflow.
Cutflow of expected events in the four Strong search edge signal regions. `Leptons' refers to electrons and muons only. The gluino-$Z^{(*)}$ model with $m_{ ilde{g}}=800~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for SRC-STR with 60000 Monte Carlo (MC) events generated. The slepton-$Z^{(*)}$ model with $m_{ ilde{\ell}}=1200~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for SRMed-STR with 30000 (MC) events generated. The gluino-slepton model with $m_{ ilde{g}}=2~TeV$ and $m_{ ilde{\ell}}=1.3~TeV$ is used for SRLow-STR and SRHigh-STR with 30000 MC events generated. The Generator Filter requires two 5~GeV leptons and 100~GeV of \met. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~GeV$ or at least one lepton with $p_{\mathrm{T}}>25~GeV$ and a photon with $p_{\mathrm{T}}>40~GeV$, with all objects within $|\eta|=2.6$.
Cutflow of expected events in the four Strong search edge signal regions. `Leptons' refers to electrons and muons only. The gluino-$Z^{(*)}$ model with $m_{ ilde{g}}=800~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for SRC-STR with 60000 Monte Carlo (MC) events generated. The slepton-$Z^{(*)}$ model with $m_{ ilde{\ell}}=1200~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for SRMed-STR with 30000 (MC) events generated. The gluino-slepton model with $m_{ ilde{g}}=2~TeV$ and $m_{ ilde{\ell}}=1.3~TeV$ is used for SRLow-STR and SRHigh-STR with 30000 MC events generated. The Generator Filter requires two 5~GeV leptons and 100~GeV of \met. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~GeV$ or at least one lepton with $p_{\mathrm{T}}>25~GeV$ and a photon with $p_{\mathrm{T}}>40~GeV$, with all objects within $|\eta|=2.6$.
Cutflow of expected events in the four Strong search edge signal regions. `Leptons' refers to electrons and muons only. The gluino-$Z^{(*)}$ model with $m_{ ilde{g}}=800~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for SRC-STR with 60000 Monte Carlo (MC) events generated. The slepton-$Z^{(*)}$ model with $m_{ ilde{\ell}}=1200~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for SRMed-STR with 30000 (MC) events generated. The gluino-slepton model with $m_{ ilde{g}}=2~TeV$ and $m_{ ilde{\ell}}=1.3~TeV$ is used for SRLow-STR and SRHigh-STR with 30000 MC events generated. The Generator Filter requires two 5~GeV leptons and 100~GeV of \met. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~GeV$ or at least one lepton with $p_{\mathrm{T}}>25~GeV$ and a photon with $p_{\mathrm{T}}>40~GeV$, with all objects within $|\eta|=2.6$.
Cutflow of expected events in the four Strong search edge signal regions. `Leptons' refers to electrons and muons only. The gluino-$Z^{(*)}$ model with $m_{ ilde{g}}=800~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for SRC-STR with 60000 Monte Carlo (MC) events generated. The slepton-$Z^{(*)}$ model with $m_{ ilde{\ell}}=1200~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for SRMed-STR with 30000 (MC) events generated. The gluino-slepton model with $m_{ ilde{g}}=2~TeV$ and $m_{ ilde{\ell}}=1.3~TeV$ is used for SRLow-STR and SRHigh-STR with 30000 MC events generated. The Generator Filter requires two 5~GeV leptons and 100~GeV of \met. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~GeV$ or at least one lepton with $p_{\mathrm{T}}>25~GeV$ and a photon with $p_{\mathrm{T}}>40~GeV$, with all objects within $|\eta|=2.6$.
Cutflow of expected events in the three Strong search on-$Z$ signal regions. The cutflow up to the signal region specific requirements is the same as in the Strong search edge cutflow. The slepton-$Z^{(*)}$ model with $m_{ ilde{\ell}}=1200~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for all of the on-$Z$ signal regions with 30000 (MC) events generated.
Cutflow of expected events in the three Strong search on-$Z$ signal regions. The cutflow up to the signal region specific requirements is the same as in the Strong search edge cutflow. The slepton-$Z^{(*)}$ model with $m_{ ilde{\ell}}=1200~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for all of the on-$Z$ signal regions with 30000 (MC) events generated.
Cutflow of expected events in the three Strong search on-$Z$ signal regions. The cutflow up to the signal region specific requirements is the same as in the Strong search edge cutflow. The slepton-$Z^{(*)}$ model with $m_{ ilde{\ell}}=1200~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for all of the on-$Z$ signal regions with 30000 (MC) events generated.
Table 36: Cutflow of expected events in the region SR-OffShell_a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 36: Cutflow of expected events in the region SR-OffShell_a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 37: Cutflow of expected events in the region SR-OffShell_b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 37: Cutflow of expected events in the region SR-OffShell_b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 38: Cutflow of expected events in the region SR-Low_a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 38: Cutflow of expected events in the region SR-Low_a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 39: Cutflow of expected events in the region SR-Low_b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 39: Cutflow of expected events in the region SR-Low_b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 40: Cutflow of expected events in the region SR-Low-2-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 40: Cutflow of expected events in the region SR-Low-2-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 41: Cutflow of expected events in the region SR-Int_a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 41: Cutflow of expected events in the region SR-Int_a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 42: Cutflow of expected events in the region SR-Int_b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 42: Cutflow of expected events in the region SR-Int_b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 43: Cutflow of expected events in the region SR-High_16a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 43: Cutflow of expected events in the region SR-High_16a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 44: Cutflow of expected events in the region SR-High_16b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 44: Cutflow of expected events in the region SR-High_16b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 45: Cutflow of expected events in the region SR-High_8a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 45: Cutflow of expected events in the region SR-High_8a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 46: Cutflow of expected events in the region SR-High_8b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 46: Cutflow of expected events in the region SR-High_8b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 47: Cutflow of expected events in the region SR-1J-High-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 47: Cutflow of expected events in the region SR-1J-High-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 48: Cutflow of expected events in the region SR-llbb-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 48: Cutflow of expected events in the region SR-llbb-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
The combined $m_{jj}$ distribution of CR-Z-EWK and SR-Low-EWK (left), and the $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ distribution in CR-Z-met-EWK (right), which removes the upper limit of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}}) < 9$ from the definition of CR-Z-EWK. This $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ tail overlaps other control and validation regions, but not signal regions. The arrows indicate the signal region SR-Low-EWK (left), and the $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ phase space which is not included in CR-Z-EWK (right). All EWK search control and signal regions are included in the fit. All statistical and systematic uncertainties are included in the hatched bands. The theoretical uncertainties from CR-Z-EWK are applied to CR-Z-met-EWK. The last bins contain the overflow.
The combined $m_{jj}$ distribution of CR-Z-EWK and SR-Low-EWK (left), and the $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ distribution in CR-Z-met-EWK (right), which removes the upper limit of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}}) < 9$ from the definition of CR-Z-EWK. This $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ tail overlaps other control and validation regions, but not signal regions. The arrows indicate the signal region SR-Low-EWK (left), and the $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ phase space which is not included in CR-Z-EWK (right). All EWK search control and signal regions are included in the fit. All statistical and systematic uncertainties are included in the hatched bands. The theoretical uncertainties from CR-Z-EWK are applied to CR-Z-met-EWK. The last bins contain the overflow.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
This paper presents a search for hypothetical massive, charged, long-lived particles with the ATLAS detector at the LHC using an integrated luminosity of 139 fb$^{-1}$ of proton-proton collisions at $\sqrt{s}=13$ TeV. These particles are expected to move significantly slower than the speed of light and should be identifiable by their high transverse momenta and anomalously large specific ionisation losses, ${\mathrm{d}}E/\mathrm{d}x$. Trajectories reconstructed solely by the inner tracking system and a ${\mathrm{d}}E/\mathrm{d}x$ measurement in the pixel detector layers provide sensitivity to particles with lifetimes down to ${\cal O}(1)$$\text{ns}$ with a mass, measured using the Bethe--Bloch relation, ranging from 100 GeV to 3 TeV. Interpretations for pair-production of $R$-hadrons, charginos and staus in scenarios of supersymmetry compatible with these particles being long-lived are presented, with mass limits extending considerably beyond those from previous searches in broad ranges of lifetime.
This material aims to give people outside the ATLAS Collaboration the possibility to reinterpret the results from the search for heavy charged long-lived particles (CLLPs), using only particles from Monte Carlo event generators. The reinterpretation material is provided for signal regions SR-Inclusive_Low and SR-Inclusive_High. <ul display="inline-block"> <li>The "long" lifetime regime of mass windows is used.</li> <li>Users are guided to read Guide.pdf (available from "Resources" or "Download All" buttons) for how to use the provided materials for reinterpretation.</li> <li>The pseudo-code snippet snippet.cxx also illustrates a sketch of possible implementation.</li> </ul> <b>Signal Region (Discovery) mass distribution</b> <ul> <li><a href="?table=SR-Inclusive_Low%20mass%20distribution">SR-Inclusive_Low mass distribution</a></li> <li><a href="?table=SR-Inclusive_High%20mass%20distribution">SR-Inclusive_High mass distribution</a></li> </ul> <b>Signal Region (Discovery) $p_\text{T}, \eta, dE/dx$ distribution</b> <ul> <li><a href="?table=SR-Inclusive_Low%20pT%20distribution">SR-Inclusive_Low pT distribution</a></li> <li><a href="?table=SR-Inclusive_High%20pT%20distribution">SR-Inclusive_High pT distribution</a></li> <li><a href="?table=SR-Inclusive_Low%20$eta$%20distribution">SR-Inclusive_Low $\eta$ distribution</a></li> <li><a href="?table=SR-Inclusive_High%20$eta$%20distribution">SR-Inclusive_High $\eta$ distribution</a></li> <li><a href="?table=SR-Inclusive_Low%20dE/dx%20distribution">SR-Inclusive_Low dE/dx distribution</a></li> <li><a href="?table=SR-Inclusive_High%20dE/dx%20distribution">SR-Inclusive_High dE/dx distribution</a></li> </ul> <b>Signal Region (Limit Setting) mass distribution</b> <ul> <li><a href="?table=SR-Trk-IBL0_Low%20mass%20distribution">SR-Trk-IBL0_Low mass distribution</a></li> <li><a href="?table=SR-Mu-IBL0_Low%20mass%20distribution">SR-Mu-IBL0_Low mass distribution</a></li> <li><a href="?table=SR-Trk-IBL0_High%20mass%20distribution">SR-Trk-IBL0_High mass distribution</a></li> <li><a href="?table=SR-Mu-IBL0_High%20mass%20distribution">SR-Mu-IBL0_High mass distribution</a></li> <li><a href="?table=SR-Trk-IBL1%20mass%20distribution">SR-Trk-IBL1 mass distribution</a></li> <li><a href="?table=SR-Mu-IBL1%20mass%20distribution">SR-Mu-IBL1 mass distribution</a></li> </ul> <b>Signal Region (Limit Setting) $p_\text{T}$ distribution</b> <ul> <li><a href="?table=SR-Trk-IBL0_Low%20pT%20distribution">SR-Trk-IBL0_Low pT distribution</a></li> <li><a href="?table=SR-Mu-IBL0_Low%20pT%20distribution">SR-Mu-IBL0_Low pT distribution</a></li> <li><a href="?table=SR-Trk-IBL0_High%20pT%20distribution">SR-Trk-IBL0_High pT distribution</a></li> <li><a href="?table=SR-Mu-IBL0_High%20pT%20distribution">SR-Mu-IBL0_High pT distribution</a></li> <li><a href="?table=SR-Trk-IBL1%20pT%20distribution">SR-Trk-IBL1 pT distribution</a></li> <li><a href="?table=SR-Mu-IBL1%20pT%20distribution">SR-Mu-IBL1 pT distribution</a></li> </ul> <b>Signal Region (Limit Setting) $dE/dx$ distribution</b> <ul> <li><a href="?table=SR-Trk-IBL0_Low%20dE/dx%20distribution">SR-Trk-IBL0_Low dE/dx distribution</a></li> <li><a href="?table=SR-Mu-IBL0_Low%20dE/dx%20distribution">SR-Mu-IBL0_Low dE/dx distribution</a></li> <li><a href="?table=SR-Trk-IBL0_High%20dE/dx%20distribution">SR-Trk-IBL0_High dE/dx distribution</a></li> <li><a href="?table=SR-Mu-IBL0_High%20dE/dx%20distribution">SR-Mu-IBL0_High dE/dx distribution</a></li> <li><a href="?table=SR-Trk-IBL1%20dE/dx%20distribution">SR-Trk-IBL1 dE/dx distribution</a></li> <li><a href="?table=SR-Mu-IBL1%20dE/dx%20distribution">SR-Mu-IBL1 dE/dx distribution</a></li> </ul> <b>Discovery Signal Regions $p_{0}$ values</b> <ul> <li><a href="?table=p0-values%20and%20model-independent%20limits,%20short%20regime">p0-values and model-independent limits, short regime</a></li> <li><a href="?table=p0-values%20and%20model-independent%20limits,%20long%20regime">p0-values and model-independent limits, long regime</a></li> </ul> <b>Validation Region plots</b> <ul> <li><a href="?table=VR-LowPt-Inclusive_High%20mass%20distribution">VR-LowPt-Inclusive_High mass distribution</a></li> <li><a href="?table=VR-HiEta-Inclusive%20mass%20distribution">VR-HiEta-Inclusive mass distribution</a></li> </ul> <ul> <li><a href="?table=VR-LowPt-Trk-IBL0_Low%20mass%20distribution">VR-LowPt-Trk-IBL0_Low mass distribution</a></li> <li><a href="?table=VR-LowPt-Mu-IBL0_Low%20mass%20distribution">VR-LowPt-Mu-IBL0_Low mass distribution</a></li> <li><a href="?table=VR-LowPt-Trk-IBL0_High%20mass%20distribution">VR-LowPt-Trk-IBL0_High mass distribution</a></li> <li><a href="?table=VR-LowPt-Mu-IBL0_High%20mass%20distribution">VR-LowPt-Mu-IBL0_High mass distribution</a></li> <li><a href="?table=VR-LowPt-Trk-IBL1%20mass%20distribution">VR-LowPt-Trk-IBL1 mass distribution</a></li> <li><a href="?table=VR-LowPt-Mu-IBL1%20mass%20distribution">VR-LowPt-Mu-IBL1 mass distribution</a></li> </ul> <ul> <li><a href="?table=VR-HiEta-Trk-IBL0_Low%20mass%20distribution">VR-HiEta-Trk-IBL0_Low mass distribution</a></li> <li><a href="?table=VR-HiEta-Mu-IBL0_Low%20mass%20distribution">VR-HiEta-Mu-IBL0_Low mass distribution</a></li> <li><a href="?table=VR-HiEta-Trk-IBL0_High%20mass%20distribution">VR-HiEta-Trk-IBL0_High mass distribution</a></li> <li><a href="?table=VR-HiEta-Mu-IBL0_High%20mass%20distribution">VR-HiEta-Mu-IBL0_High mass distribution</a></li> <li><a href="?table=VR-HiEta-Trk-IBL1%20mass%20distribution">VR-HiEta-Trk-IBL1 mass distribution</a></li> <li><a href="?table=VR-HiEta-Mu-IBL1%20mass%20distribution">VR-HiEta-Mu-IBL1 mass distribution</a></li> </ul> <b>Mass vs. Lifetime limit plots</b> <ul> <li><a href="?table=Mass%20Limit%20vs.%20Lifetime,%20R-hadron,%20Expected">Mass Limit vs. Lifetime, R-hadron, Expected</a></li> <li><a href="?table=Mass%20Limit%20vs.%20Lifetime,%20R-hadron,%20Observed">Mass Limit vs. Lifetime, R-hadron, Observed</a></li> <li><a href="?table=Mass%20Limit%20vs.%20Lifetime,%20R-hadron,%20compressed,%20Expected">Mass Limit vs. Lifetime, R-hadron, compressed, Expected</a></li> <li><a href="?table=Mass%20Limit%20vs.%20Lifetime,%20R-hadron,%20compressed,%20Observed">Mass Limit vs. Lifetime, R-hadron, compressed, Observed</a></li> <li><a href="?table=Mass%20Limit%20vs.%20Lifetime,%20Chargino,%20Expected">Mass Limit vs. Lifetime, Chargino, Expected</a></li> <li><a href="?table=Mass%20Limit%20vs.%20Lifetime,%20Chargino,%20Observed">Mass Limit vs. Lifetime, Chargino, Observed</a></li> <li><a href="?table=Mass%20Limit%20vs.%20Lifetime,%20Stau,%20Expected">Mass Limit vs. Lifetime, Stau, Expected</a></li> <li><a href="?table=Mass%20Limit%20vs.%20Lifetime,%20Stau,%20Observed">Mass Limit vs. Lifetime, Stau, Observed</a></li> </ul> <b>Cross-section limit plots</b> <ul> <li><a href="?table=Cross%20Section%20Limit,%20R-hadron%201ns">Cross Section Limit, R-hadron 1ns</a></li> <li><a href="?table=Cross%20Section%20Limit,%20R-hadron%203ns">Cross Section Limit, R-hadron 3ns</a></li> <li><a href="?table=Cross%20Section%20Limit,%20R-hadron%2010ns">Cross Section Limit, R-hadron 10ns</a></li> <li><a href="?table=Cross%20Section%20Limit,%20R-hadron%2030ns">Cross Section Limit, R-hadron 30ns</a></li> <li><a href="?table=Cross%20Section%20Limit,%20R-hadron%20Stable">Cross Section Limit, R-hadron Stable</a></li> <li><a href="?table=Cross%20Section%20Limit,%20R-hadron%20Compressed%201ns">Cross Section Limit, R-hadron Compressed 1ns</a></li> <li><a href="?table=Cross%20Section%20Limit,%20R-hadron%20Compressed%203ns">Cross Section Limit, R-hadron Compressed 3ns</a></li> <li><a href="?table=Cross%20Section%20Limit,%20R-hadron%20Compressed%2010ns">Cross Section Limit, R-hadron Compressed 10ns</a></li> <li><a href="?table=Cross%20Section%20Limit,%20R-hadron%20Compressed%2030ns">Cross Section Limit, R-hadron Compressed 30ns</a></li> <li><a href="?table=Cross%20Section%20Limit,%20Chargino%201ns">Cross Section Limit, Chargino 1ns</a></li> <li><a href="?table=Cross%20Section%20Limit,%20Chargino%204ns">Cross Section Limit, Chargino 4ns</a></li> <li><a href="?table=Cross%20Section%20Limit,%20Chargino%2010ns">Cross Section Limit, Chargino 10ns</a></li> <li><a href="?table=Cross%20Section%20Limit,%20Chargino%2030ns">Cross Section Limit, Chargino 30ns</a></li> <li><a href="?table=Cross%20Section%20Limit,%20Chargino%20Stable">Cross Section Limit, Chargino Stable</a></li> <li><a href="?table=Cross%20Section%20Limit,%20Stau%201ns">Cross Section Limit, Stau 1ns</a></li> <li><a href="?table=Cross%20Section%20Limit,%20Stau%203ns">Cross Section Limit, Stau 3ns</a></li> <li><a href="?table=Cross%20Section%20Limit,%20Stau%2010ns">Cross Section Limit, Stau 10ns</a></li> <li><a href="?table=Cross%20Section%20Limit,%20Stau%2030ns">Cross Section Limit, Stau 30ns</a></li> <li><a href="?table=Cross%20Section%20Limit,%20Stau%20Stable">Cross Section Limit, Stau Stable</a></li> </ul> <b>Signal Region events projected to other kinematic variables</b> <ul> <li><a href="?table=SR-Inclusive_Low%20MET">SR-Inclusive_Low MET</a></li> <li><a href="?table=SR-Inclusive_High%20MET">SR-Inclusive_High MET</a></li> <li><a href="?table=SR-Inclusive_Low%20deltaPhi(MET,%20Track)">SR-Inclusive_Low deltaPhi(MET, Track)</a></li> <li><a href="?table=SR-Inclusive_High%20deltaPhi(MET,%20Track)">SR-Inclusive_High deltaPhi(MET, Track)</a></li> <li><a href="?table=SR-Inclusive_Low%20mT(MET,%20Track)">SR-Inclusive_Low mT(MET, Track)</a></li> <li><a href="?table=SR-Inclusive_High%20mT(MET,%20Track)">SR-Inclusive_High mT(MET, Track)</a></li> <li><a href="?table=SR-Inclusive_Low%20Leading%20jet%20pT">SR-Inclusive_Low Leading jet pT</a></li> <li><a href="?table=SR-Inclusive_High%20Leading%20jet%20pT">SR-Inclusive_High Leading jet pT</a></li> <li><a href="?table=SR-Inclusive_Low%20deltaPhi(Leading%20jet,%20Track)">SR-Inclusive_Low deltaPhi(Leading jet, Track)</a></li> <li><a href="?table=SR-Inclusive_High%20deltaPhi(Leading%20jet,%20Track)">SR-Inclusive_High deltaPhi(Leading jet, Track)</a></li> <li><a href="?table=SR-Inclusive_Low%20deltaPhi(MET,%20Leading%20jet)">SR-Inclusive_Low deltaPhi(MET, Leading jet)</a></li> <li><a href="?table=SR-Inclusive_High%20deltaPhi(MET,%20Leading%20jet)">SR-Inclusive_High deltaPhi(MET, Leading jet)</a></li> <li><a href="?table=SR-Inclusive_Low%20mT(MET,%20Leading%20jet)">SR-Inclusive_Low mT(MET, Leading jet)</a></li> <li><a href="?table=SR-Inclusive_High%20mT(MET,%20Leading%20jet)">SR-Inclusive_High mT(MET, Leading jet)</a></li> <li><a href="?table=SR-Inclusive_Low%20Effective%20mass">SR-Inclusive_Low Effective mass</a></li> <li><a href="?table=SR-Inclusive_High%20Effective%20mass">SR-Inclusive_High Effective mass</a></li> </ul> <b>Acceptance and efficiency values for reinterpretation</b> <ul> <li><a href="?table=Muon%20Reconstruction%20Efficiency%20distribution">Muon Reconstruction Efficiency distribution</a></li> <li><a href="?table=Muon%20Reconstruction%20Efficiency,%20R-hadron%20distribution">Muon Reconstruction Efficiency, R-hadron distribution</a></li> <li><a href="?table=Trigger%20Efficiency%20distribution">Trigger Efficiency distribution</a></li> <li><a href="?table=Event%20Selection%20Efficiency%20distribution">Event Selection Efficiency distribution</a></li> <li><a href="?table=Track%20Selection%20Efficiency%20distribution">Track Selection Efficiency distribution</a></li> <li><a href="?table=Mass%20Window%20Efficiency">Mass Window Efficiency</a></li> </ul> <b>Acceptance and efficiency tables for signal samples</b> <ul> <li><a href="?table=Acceptance,%20R-hadron">Acceptance, R-hadron</a></li> <li><a href="?table=Acceptance,%20R-hadron,%20compressed">Acceptance, R-hadron, compressed</a></li> <li><a href="?table=Acceptance,%20Chargino">Acceptance, Chargino</a></li> <li><a href="?table=Acceptance,%20Stau">Acceptance, Stau</a></li> </ul> <ul> <li><a href="?table=Event-level%20efficiency,%20R-hadron">Event-level efficiency, R-hadron</a></li> <li><a href="?table=Event-level%20efficiency,%20R-hadron,%20compressed">Event-level efficiency, R-hadron, compressed</a></li> <li><a href="?table=Event-level%20efficiency,%20Chargino">Event-level efficiency, Chargino</a></li> <li><a href="?table=Event-level%20efficiency,%20Stau">Event-level efficiency, Stau</a></li> </ul> <ul> <li><a href="?table=Efficiency,%20SR-Inclusve_High,%20R-hadron">Efficiency, SR-Inclusve_High, R-hadron</a></li> <li><a href="?table=Efficiency,%20SR-Inclusve_High,%20R-hadron,%20compressed">Efficiency, SR-Inclusve_High, R-hadron, compressed</a></li> <li><a href="?table=Efficiency,%20SR-Inclusve_High,%20Chargino">Efficiency, SR-Inclusve_High, Chargino</a></li> <li><a href="?table=Efficiency,%20SR-Inclusve_High,%20Stau">Efficiency, SR-Inclusve_High, Stau</a></li> </ul> <ul> <li><a href="?table=Efficiency,%20SR-Inclusive_Low,%20R-hadron">Efficiency, SR-Inclusive_Low, R-hadron</a></li> <li><a href="?table=Efficiency,%20SR-Inclusive_Low,%20R-hadron,%20compressed">Efficiency, SR-Inclusive_Low, R-hadron, compressed</a></li> <li><a href="?table=Efficiency,%20SR-Inclusive_Low,%20Chargino">Efficiency, SR-Inclusive_Low, Chargino</a></li> <li><a href="?table=Efficiency,%20SR-Inclusive_Low,%20Stau">Efficiency, SR-Inclusive_Low, Stau</a></li> </ul> <b>Cut flow for signal samples</b> <ul> <li><a href="?table=Cut%20Flow,%20R-hadron">Cut Flow, R-hadron</a></li> <li><a href="?table=Cut%20Flow,%20R-hadron,%20compressed">Cut Flow, R-hadron, compressed</a></li> <li><a href="?table=Cut%20Flow,%20Chargino">Cut Flow, Chargino</a></li> <li><a href="?table=Cut%20Flow,%20Stau">Cut Flow, Stau</a></li> </ul>
Comparison of the observed and expected VAR distributionsin VR-LowPt-Inclusive_High. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.
Comparison of the observed and expected VAR distributionsin VR-HiEta-Inclusive. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.
The observed mass distribution in the SR-Inclusive_Low signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed mass distribution in the SR-Inclusive_High signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
List of expected and observed events, $p_{0}$-value and the corresponding $Z$ local significance, as well as the 95% CLs upper limit of the expected and observed signal events ($S^{95}_ ext{exp} and $S^{95}_ ext{obs}$ ) in each mass window for SR-Inclusive bins of the short lifetime regime.
List of expected and observed events, $p_{0}$-value and the corresponding $Z$ local significance, as well as the 95% CLs upper limit of the expected and observed signal events ($S^{95}_ ext{exp} and $S^{95}_ ext{obs}$ ) in each mass window for SR-Inclusive bins of the long lifetime regime.
The observed $p_{\rm T$ distribution in the SR-Inclusive_Low signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed $p_{\rm T$ distribution in the SR-Inclusive_High signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed $|\eta|$ distribution in the SR-Inclusive_Low signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed $|\eta|$ distribution in the SR-Inclusive_High signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed dE/dx distribution in the SR-Inclusive_Low signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed dE/dx distribution in the SR-Inclusive_High signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed mass distribution in the SR-Trk-IBL0_Low signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed mass distribution in the SR-Mu-IBL0_Low signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed mass distribution in the SR-Trk-IBL0_High signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed mass distribution in the SR-Mu-IBL0_High signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed mass distribution in the SR-Trk-IBL1 signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed mass distribution in the SR-Mu-IBL1 signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
Lower limits on the gluino mass, from gluino $R$-hadron pair production, as a function of gluino lifetime for two neutralino mass assumptions of (a) $m(\tilde{\chi}_{1}^{0}) = 100 \text{GeV}$ and (b) $\Delta m(\tilde{g}, \tilde{\chi}_{1}^{0}) = 30 \text{GeV}$. The upper $1 \sigma_\text{exp}$ expected bound is very close to the expected limit for some lifetime values due to the expected background getting very close to 0 events.
Lower limits on the gluino mass, from gluino $R$-hadron pair production, as a function of gluino lifetime for two neutralino mass assumptions of (a) $m(\tilde{\chi}_{1}^{0}) = 100 \text{GeV}$ and (b) $\Delta m(\tilde{g}, \tilde{\chi}_{1}^{0}) = 30 \text{GeV}$. The upper $1 \sigma_\text{exp}$ expected bound is very close to the expected limit for some lifetime values due to the expected background getting very close to 0 events.
Lower limits on the gluino mass, from gluino $R$-hadron pair production, as a function of gluino lifetime for two neutralino mass assumptions of (a) $m(\tilde{\chi}_{1}^{0}) = 100 \text{GeV}$ and (b) $\Delta m(\tilde{g}, \tilde{\chi}_{1}^{0}) = 30 \text{GeV}$. The upper $1 \sigma_\text{exp}$ expected bound is very close to the expected limit for some lifetime values due to the expected background getting very close to 0 events.
Lower limits on the gluino mass, from gluino $R$-hadron pair production, as a function of gluino lifetime for two neutralino mass assumptions of (a) $m(\tilde{\chi}_{1}^{0}) = 100 \text{GeV}$ and (b) $\Delta m(\tilde{g}, \tilde{\chi}_{1}^{0}) = 30 \text{GeV}$. The upper $1 \sigma_\text{exp}$ expected bound is very close to the expected limit for some lifetime values due to the expected background getting very close to 0 events.
(a) Lower limits on the chargino mass as a function of lifetime, and (b) the contours around the excluded mass-lifetime region for stau pair production.
(a) Lower limits on the chargino mass as a function of lifetime, and (b) the contours around the excluded mass-lifetime region for stau pair production.
(a) Lower limits on the chargino mass as a function of lifetime, and (b) the contours around the excluded mass-lifetime region for stau pair production.
(a) Lower limits on the chargino mass as a function of lifetime, and (b) the contours around the excluded mass-lifetime region for stau pair production.
Comparison of the observed and expected VAR distributionsin VR-LowPt-Trk-IBL0_Low. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.
Comparison of the observed and expected VAR distributionsin VR-LowPt-Mu-IBL0_Low. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.
Comparison of the observed and expected VAR distributionsin VR-LowPt-Trk-IBL0_High. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.
Comparison of the observed and expected VAR distributionsin VR-LowPt-Mu-IBL0_High. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.
Comparison of the observed and expected VAR distributionsin VR-LowPt-Trk-IBL1. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.
Comparison of the observed and expected VAR distributionsin VR-LowPt-Mu-IBL1. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.
Comparison of the observed and expected VAR distributionsin VR-HiEta-Trk-IBL0_Low. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.
Comparison of the observed and expected VAR distributionsin VR-HiEta-Mu-IBL0_Low. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.
Comparison of the observed and expected VAR distributionsin VR-HiEta-Trk-IBL0_High. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.
Comparison of the observed and expected VAR distributionsin VR-HiEta-Mu-IBL0_High. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.
Comparison of the observed and expected VAR distributionsin VR-HiEta-Trk-IBL1. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.
Comparison of the observed and expected VAR distributionsin VR-HiEta-Mu-IBL1. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.
The observed $p_{\rm T$ distribution in the SR-Trk-IBL0_Low signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed $p_{\rm T$ distribution in the SR-Mu-IBL0_Low signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed $p_{\rm T$ distribution in the SR-Trk-IBL0_High signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed $p_{\rm T$ distribution in the SR-Mu-IBL0_High signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed $p_{\rm T$ distribution in the SR-Trk-IBL1 signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed $p_{\rm T$ distribution in the SR-Mu-IBL1 signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed dE/dx distribution in the SR-Trk-IBL0_Low signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed dE/dx distribution in the SR-Mu-IBL0_Low signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed dE/dx distribution in the SR-Trk-IBL0_High signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed dE/dx distribution in the SR-Mu-IBL0_High signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed dE/dx distribution in the SR-Trk-IBL1 signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
The observed dE/dx distribution in the SR-Mu-IBL1 signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.
Expected and observed distributions in SR-Inclusive_Low of missing transverse momentum. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.
Expected and observed distributions in SR-Inclusive_High of missing transverse momentum. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.
Expected and observed distributions in SR-Inclusive_Low of relative phi-angle between pTmiss and the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.
Expected and observed distributions in SR-Inclusive_High of relative phi-angle between pTmiss and the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.
Expected and observed distributions in SR-Inclusive_Low of the transverse mass of pTmiss and the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.
Expected and observed distributions in SR-Inclusive_High of the transverse mass of pTmiss and the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.
Expected and observed distributions in SR-Inclusive_Low of the leading jet pT, required to be separated by at least deltaR > 0.4 with respect to the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.
Expected and observed distributions in SR-Inclusive_High of the leading jet pT, required to be separated by at least deltaR > 0.4 with respect to the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.
Expected and observed distributions in SR-Inclusive_Low of the relative phi-angle between the leading jet pT, required to be separated by at least deltaR > 0.4 with respect to the signal candidate track, and the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.
Expected and observed distributions in SR-Inclusive_High of the relative phi-angle between the leading jet pT, required to be separated by at least deltaR > 0.4 with respect to the signal candidate track, and the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.
Expected and observed distributions in SR-Inclusive_Low of the relative phi-angle between pTmiss and the leading jet pT, required to be separated by at least deltaR > 0.4 with respect to the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.
Expected and observed distributions in SR-Inclusive_High of the relative phi-angle between pTmiss and the leading jet pT, required to be separated by at least deltaR > 0.4 with respect to the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.
Expected and observed distributions in SR-Inclusive_Low of the transverse mass of pTmiss and the leading jet pT, required to be separated by at least deltaR > 0.4 with respect to the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.
Expected and observed distributions in SR-Inclusive_High of the transverse mass of pTmiss and the leading jet pT, required to be separated by at least deltaR > 0.4 with respect to the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.
Expected and observed distributions in SR-Inclusive_Low of the effective mass, defined as the scalar sum pT of the signal candidate track, jets satisfying pT > 30 GeV, excluding ones within deltaR < 0.4 with respect to the signal candidate track, and pTmiss. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.
Expected and observed distributions in SR-Inclusive_High of the effective mass, defined as the scalar sum pT of the signal candidate track, jets satisfying pT > 30 GeV, excluding ones within deltaR < 0.4 with respect to the signal candidate track, and pTmiss. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.
The expected upper limits on cross-section for gluinos with $m(\tilde{\chi}_{1}^{0}) = 100 \text{GeV}$, with lifetime with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, (d) 30 ns, and (e) stable.
The expected upper limits on cross-section for gluinos with $m(\tilde{\chi}_{1}^{0}) = 100 \text{GeV}$, with lifetime with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, (d) 30 ns, and (e) stable.
The expected upper limits on cross-section for gluinos with $m(\tilde{\chi}_{1}^{0}) = 100 \text{GeV}$, with lifetime with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, (d) 30 ns, and (e) stable.
The expected upper limits on cross-section for gluinos with $m(\tilde{\chi}_{1}^{0}) = 100 \text{GeV}$, with lifetime with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, (d) 30 ns, and (e) stable.
The expected upper limits on cross-section for gluinos with $m(\tilde{\chi}_{1}^{0}) = 100 \text{GeV}$, with lifetime with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, (d) 30 ns, and (e) stable.
The expected upper limits on cross-section for gluinos with $\Delta m(\tilde{g}, \tilde{\chi}_{1}^{0}) = 30 \text{GeV}$, with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, and (d) 30 ns.
The expected upper limits on cross-section for gluinos with $\Delta m(\tilde{g}, \tilde{\chi}_{1}^{0}) = 30 \text{GeV}$, with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, and (d) 30 ns.
The expected upper limits on cross-section for gluinos with $\Delta m(\tilde{g}, \tilde{\chi}_{1}^{0}) = 30 \text{GeV}$, with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, and (d) 30 ns.
The expected upper limits on cross-section for gluinos with $\Delta m(\tilde{g}, \tilde{\chi}_{1}^{0}) = 30 \text{GeV}$, with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, and (d) 30 ns.
The expected upper limits on cross-section for charginos with lifetime (c) 10 ns, (d) 30 ns, and (e) stable.
The expected upper limits on cross-section for charginos with lifetime (c) 10 ns, (d) 30 ns, and (e) stable.
The expected upper limits on cross-section for charginos with lifetime (c) 10 ns, (d) 30 ns, and (e) stable.
The expected upper limits on cross-section for charginos with lifetime (c) 10 ns, (d) 30 ns, and (e) stable.
The expected upper limits on cross-section for charginos with lifetime (c) 10 ns, (d) 30 ns, and (e) stable.
The expected upper limits on cross-section for sleptons with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, (d) 30 ns, and (e) stable.
The expected upper limits on cross-section for sleptons with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, (d) 30 ns, and (e) stable.
The expected upper limits on cross-section for sleptons with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, (d) 30 ns, and (e) stable.
The expected upper limits on cross-section for sleptons with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, (d) 30 ns, and (e) stable.
The expected upper limits on cross-section for sleptons with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, (d) 30 ns, and (e) stable.
Muon reconstruction efficiency as a function of β and |η| for (a) stable charginos and (b) stable charged R-hadrons. For weakly interacting LLPs with calorimeter materials the efficiency for the chargino is recommended to refer to. The muon reconstruction efficiency for R-hadrons is significantly lower due to having QCD interactions with materials.
Muon reconstruction efficiency as a function of β and |η| for (a) stable charginos and (b) stable charged R-hadrons. For weakly interacting LLPs with calorimeter materials the efficiency for the chargino is recommended to refer to. The muon reconstruction efficiency for R-hadrons is significantly lower due to having QCD interactions with materials.
Trigger and event selection efficiencies. The band on the marker indicates a typical size of fluctuation by the LLP mass and lifetime observed by the samples used in efficiency derivation, but it does not indicate the full envelope of model dependence.
Trigger and event selection efficiencies. The band on the marker indicates a typical size of fluctuation by the LLP mass and lifetime observed by the samples used in efficiency derivation, but it does not indicate the full envelope of model dependence.
Signal track selection efficiency as a function of CLLP $\beta\gamma$ for SR-Inclusive_Low and SR-Inclusive_High bins. The band on the marker indicates a typical size of fluctuation by the LLP mass and lifetime observed by the samples used in efficiency derivation, but it does not indicate the full envelope of model dependence.
Signal selection efficiency by the mass window for SR-Inclusive_Low and SR-Inclusive_High bins.
Acceptance for the R-hadron pair-production model with m(N1) = 100 GeV for various masses and lifetimes. The acceptance is defined as the fraction of events having at least one charged LLP satisfying pT > 120 GeV, |\eta| < 1.8 and r_decay > 500 mm.
Acceptance for the R-hadron pair-production model with DeltaM(gluino, N1) = 30 GeV for various masses and lifetimes. The acceptance is defined as the fraction of events having at least one charged LLP satisfying pT > 120 GeV, |eta| < 1.8 and r_decay > 500 mm.
Acceptance for the chargino pair-production model for various masses and lifetimes. The acceptance is defined as the fraction of events having at least one charged LLP satisfying pT > 120 GeV, |\eta| < 1.8 and r_decay > 500 mm.
Acceptance for the stau pair-production model for various masses and lifetimes. The acceptance is defined as the fraction of events having at least one charged LLP satisfying pT > 120 GeV, |\eta| < 1.8 and r_decay > 500 mm.
Event-level efficiency for the R-hadron pair-production model with m(N1) = 100 GeV for various masses and lifetimes. The efficiency is defined as the fraction of events satisfying the selection of trigger, event and jet cleaning, ETmiss and primary vertex requirements per events satisfying the acceptance criteria.
Event-level efficiency for the R-hadron pair-production model with DeltaM(gluino, N1) = 30 GeV for various masses and lifetimes. The efficiency is defined as the fraction of events satisfying the selection of trigger, event and jet cleaning, ETmiss and primary vertex requirements per events satisfying the acceptance criteria.
Event-level efficiency for the chargino pair-production model for various masses and lifetimes. The efficiency is defined as the fraction of events satisfying the selection of trigger, event and jet cleaning, ETmiss and primary vertex requirements per events satisfying the acceptance criteria.
Event-level efficiency for the stau pair-production model for various masses and lifetimes. The efficiency is defined as the fraction of events satisfying the selection of trigger, event and jet cleaning, ETmiss and primary vertex requirements per events satisfying the acceptance criteria.
Efficiency of SR-Inclusive_Highfor the R-hadron pair-production model with m(N1) = 100 GeV for various masses and lifetimes. The efficiency is defined as the ratio of events satisfying the signal region selection to those satisfying the acceptance criteria. The mass window is not applied for the presented numbers.
Efficiency of SR-Inclusive_Highfor the R-hadron pair-production model with DeltaM(gluino, N1) = 30 GeV for various masses and lifetimes. The efficiency is defined as the ratio of events satisfying the signal region selection to those satisfying the acceptance criteria. The mass window is not applied for the presented numbers.
Efficiency of SR-Inclusive_Highfor the chargino pair-production model for various masses and lifetimes. The efficiency is defined as the ratio of events satisfying the signal region selection to those satisfying the acceptance criteria. The mass window is not applied for the presented numbers.
Efficiency of SR-Inclusive_Highfor the stau pair-production model for various masses and lifetimes. The efficiency is defined as the ratio of events satisfying the signal region selection to those satisfying the acceptance criteria. The mass window is not applied for the presented numbers.
Efficiency of SR-Inclusive_Low for the R-hadron pair-production model with m(N1) = 100 GeV for various masses and lifetimes. The efficiency is defined as the ratio of events satisfying the signal region selection to those satisfying the acceptance criteria. The mass window is not applied for the presented numbers.
Efficiency of SR-Inclusive_Low for the R-hadron pair-production model with DeltaM(gluino, N1) = 30 GeV for various masses and lifetimes. The efficiency is defined as the ratio of events satisfying the signal region selection to those satisfying the acceptance criteria. The mass window is not applied for the presented numbers.
Efficiency of SR-Inclusive_Low for the chargino pair-production model for various masses and lifetimes. The efficiency is defined as the ratio of events satisfying the signal region selection to those satisfying the acceptance criteria. The mass window is not applied for the presented numbers.
Efficiency of SR-Inclusive_Low for the stau pair-production model for various masses and lifetimes. The efficiency is defined as the ratio of events satisfying the signal region selection to those satisfying the acceptance criteria. The mass window is not applied for the presented numbers.
Passing events in event selection steps for the R-hadron pair-production model with m(N1) = 100 GeV for various masses and lifetimes.
Passing events in event selection steps for the R-hadron pair-production model with DeltaM(gluino, N1) = 30 GeV for various masses and lifetimes.
Passing events in event selection steps for the chargino pair-production model for various masses and lifetimes.
Passing events in event selection steps for the stau pair-production model for various masses and lifetimes.
A search for the electroweak production of pairs of charged sleptons or charginos decaying into two-lepton final states with missing transverse momentum is presented. Two simplified models of $R$-parity-conserving supersymmetry are considered: direct pair-production of sleptons ($\tilde{\ell}\tilde{\ell}$), with each decaying into a charged lepton and a $\tilde{\chi}_1^0$ neutralino, and direct pair-production of the lightest charginos $(\tilde{\chi}_1^\pm\tilde{\chi}_1^\mp)$, with each decaying into a $W$-boson and a $\tilde{\chi}_1^0$. The lightest neutralino ($\tilde{\chi}_1^0$) is assumed to be the lightest supersymmetric particle (LSP). The analyses target the experimentally challenging mass regions where $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and $m(\tilde{\chi}_1^\pm)-m(\tilde{\chi}_1^0)$ are close to the $W$-boson mass (`moderately compressed' regions). The search uses 139 fb$^{-1}$ of $\sqrt{s}=13$ TeV proton-proton collisions recorded by the ATLAS detector at the Large Hadron Collider. No significant excesses over the expected background are observed. Exclusion limits on the simplified models under study are reported in the ($\tilde{\ell},\tilde{\chi}_1^0$) and ($\tilde{\chi}_1^\pm,\tilde{\chi}_1^0$) mass planes at 95% confidence level (CL). Sleptons with masses up to 150 GeV are excluded at 95% CL for the case of a mass-splitting between sleptons and the LSP of 50 GeV. Chargino masses up to 140 GeV are excluded at 95% CL for the case of a mass-splitting between the chargino and the LSP down to about 100 GeV.
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