Showing 50 of 63 results
A search is made for a vector-like $T$ quark decaying into a Higgs boson and a top quark in 13 TeV proton-proton collisions using the ATLAS detector at the Large Hadron Collider with a data sample corresponding to an integrated luminosity of 139 fb$^{-1}$. The Higgs-boson and top-quark candidates are identified in the all-hadronic decay mode, where $H\to b\bar{b}$ and $t\to b W \to b q \bar{q}^\prime$ are reconstructed as large-radius jets. The candidate Higgs boson, top quark, and associated B-hadrons are identified using tagging algorithms. No significant excess is observed above the background, so limits are set on the production cross-section of a singlet $T$ quark at 95% confidence level, depending on the mass, $m_T$, and coupling, $\kappa_T$, of the vector-like $T$ quark to Standard Model particles. In the considered mass range between 1.0 and 2.3 TeV, the upper limit on the allowed coupling values increases with $m_T$ from a minimum value of 0.35 for 1.07 < $m_T$ < 1.4 TeV to 1.6 for $m_T$ = 2.3 TeV.
Dijet invariant mass distribution for the $SR$ showing the results of the model when fitted to the data. A $T$-quark hypothesis with $m_{T} = 1.6$ TeV and $\kappa_{T} = 0.5$ is used in the fit.
Dijet invariant mass distribution for the $ttNR$ showing the results of the model when fitted to the data. A $T$-quark hypothesis with $m_{T} = 1.6$ TeV and $\kappa_{T} = 0.5$ is used in the fit.
Observed and expected 95% CL upper limits on the single $T$-quark coupling $\kappa_{T}$ as a function of $m_{T}$ are shown.
Observed and expected 95% CL lower limits on the $T$-quark mass as a function of the $T$-quark width-to-mass ratio and the branching fraction of the $T \rightarrow Ht$ decay ($\Gamma_{T}$ is the $T$-quark width).
Cutflow table listing the number of events passing each criterion for a $T$-quark hypothesis with a mass of 1.6 TeV and $\kappa_{T} = 0.5$. The initial signal event yield is the predicted number of $T$-quark events inclusive in the Higgs-boson and top-quark decays for 139 fb$^{-1}$.
Observed 95% CL upper limits on the single $T$-quark production cross-section as a function of the $T$-quark coupling $\kappa_{T}$ and $m_{T}$.
Expected 95% CL upper limits on the single $T$-quark production cross-section as a function of the $T$-quark coupling $\kappa_{T}$ and $m_{T}$.
Observed and expected 95% CL lower limits on the $T$-quark mass as a function of the $T$-quark width-to-mass ratio and the branching fraction of the $T \rightarrow Wb$ decay ($\Gamma_{T}$ is the $T$-quark width).
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.
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-tag 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 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.
Observed 95% CL exclusion contours for the gluino one-step variable-x
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.
Expected 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.
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.
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 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
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-step 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
Expected 95% CL exclusion contours for the squark one-flavour schemes in 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.
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 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 SR2JBV. 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 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-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 SR4JBV. 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 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-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 SR6JBV. 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.
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-tag 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
Post-fit $m_{eff}$ distribution in the 6J b-veto validation region. Uncertainties include statistical and systematic uncertainties.
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 SR2JBT. 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 SR2JBV. 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 SR4JBT. 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 SR4JBV. 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 SR6JBT. 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
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 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
A search for new phenomena in final states with hadronically decaying tau leptons, $b$-jets, and missing transverse momentum is presented. The analyzed dataset comprises $pp$~collision data at a center-of-mass energy of $\sqrt s = 13$ TeV with an integrated luminosity of 139/fb, delivered by the Large Hadron Collider and recorded with the ATLAS detector from 2015 to 2018. The observed data are compatible with the expected Standard Model background. The results are interpreted in simplified models for two different scenarios. The first model is based on supersymmetry and considers pair production of top squarks, each of which decays into a $b$-quark, a neutrino and a tau slepton. Each tau slepton in turn decays into a tau lepton and a nearly massless gravitino. Within this model, top-squark masses up to 1.4 TeV can be excluded at the 95% confidence level over a wide range of tau-slepton masses. The second model considers pair production of leptoquarks with decays into third-generation leptons and quarks. Depending on the branching fraction into charged leptons, leptoquarks with masses up to around 1.25 TeV can be excluded at the 95% confidence level for the case of scalar leptoquarks and up to 1.8 TeV (1.5 TeV) for vector leptoquarks in a Yang--Mills (minimal-coupling) scenario. In addition, model-independent upper limits are set on the cross section of processes beyond the Standard Model.
Relative systematic uncertainties in the estimated number of background events in the signal regions. In the lower part of the table, a breakdown of the total uncertainty into different categories is given. For the multi-bin SR, the breakdown refers to the integral over all three $p_{\text{T}}(\tau)$ bins. As the individual uncertainties are correlated, they do not add in quadrature to equal the total background uncertainty.
Distributions of $m_{\text{T}2}(\tau_{1},\tau_{2})$ in the di-tau SR. The stacked histograms show the various SM background contributions. The hatched band indicates the total statistical and systematic uncertainty of the SM background. The $t\bar{t}$ (2 real $\tau$) and $t\bar{t}$ (1 real $\tau$) as well as the single-top background contributions are scaled with the normalization factors obtained from the background-only fit. Minor backgrounds are grouped together and denoted as 'Other'. This includes $t\bar{t}$-fake, single top, and other top (di-tau channel) or $t\bar{t}$-fake, $t\bar{t}+H$, multiboson, and other top (single-tau channel). The overlaid dotted lines show the additional contributions for signal scenarios close to the expected exclusion contour with the particle type and the mass and $\beta$ parameters for the simplified models indicated in the legend. For the leptoquark signal model the shapes of the distributions for $\text{LQ}_{3}^{\text{d}}$ and $\text{LQ}_{3}^{\text{v}}$ (not shown) are similar to that of $\text{LQ}_{3}^{\text{u}}$. The rightmost bin includes the overflow.
Distributions of $E_{\text{T}}^{\text{miss}}$ in the di-tau SR. The stacked histograms show the various SM background contributions. The hatched band indicates the total statistical and systematic uncertainty of the SM background. The $t\bar{t}$ (2 real $\tau$) and $t\bar{t}$ (1 real $\tau$) as well as the single-top background contributions are scaled with the normalization factors obtained from the background-only fit. Minor backgrounds are grouped together and denoted as 'Other'. This includes $t\bar{t}$-fake, single top, and other top (di-tau channel) or $t\bar{t}$-fake, $t\bar{t}+H$, multiboson, and other top (single-tau channel). The overlaid dotted lines show the additional contributions for signal scenarios close to the expected exclusion contour with the particle type and the mass and $\beta$ parameters for the simplified models indicated in the legend. For the leptoquark signal model the shapes of the distributions for $\text{LQ}_{3}^{\text{d}}$ and $\text{LQ}_{3}^{\text{v}}$ (not shown) are similar to that of $\text{LQ}_{3}^{\text{u}}$. The rightmost bin includes the overflow.
Distributions of $s_{\text{T}}$ in the single-tau one-bin SR. The stacked histograms show the various SM background contributions. The hatched band indicates the total statistical and systematic uncertainty of the SM background. The $t\bar{t}$ (2 real $\tau$) and $t\bar{t}$ (1 real $\tau$) as well as the single-top background contributions are scaled with the normalization factors obtained from the background-only fit. Minor backgrounds are grouped together and denoted as 'Other'. This includes $t\bar{t}$-fake, single top, and other top (di-tau channel) or $t\bar{t}$-fake, $t\bar{t}+H$, multiboson, and other top (single-tau channel). The overlaid dotted lines show the additional contributions for signal scenarios close to the expected exclusion contour with the particle type and the mass and $\beta$ parameters for the simplified models indicated in the legend. For the leptoquark signal model the shapes of the distributions for $\text{LQ}_{3}^{\text{d}}$ and $\text{LQ}_{3}^{\text{v}}$ (not shown) are similar to that of $\text{LQ}_{3}^{\text{u}}$. The rightmost bin includes the overflow.
Distributions of $m_{\text{T}}(\tau)$ in the single-tau one-bin SR. The stacked histograms show the various SM background contributions. The hatched band indicates the total statistical and systematic uncertainty of the SM background. The $t\bar{t}$ (2 real $\tau$) and $t\bar{t}$ (1 real $\tau$) as well as the single-top background contributions are scaled with the normalization factors obtained from the background-only fit. Minor backgrounds are grouped together and denoted as 'Other'. This includes $t\bar{t}$-fake, single top, and other top (di-tau channel) or $t\bar{t}$-fake, $t\bar{t}+H$, multiboson, and other top (single-tau channel). The overlaid dotted lines show the additional contributions for signal scenarios close to the expected exclusion contour with the particle type and the mass and $\beta$ parameters for the simplified models indicated in the legend. For the leptoquark signal model the shapes of the distributions for $\text{LQ}_{3}^{\text{d}}$ and $\text{LQ}_{3}^{\text{v}}$ (not shown) are similar to that of $\text{LQ}_{3}^{\text{u}}$. The rightmost bin includes the overflow.
Distributions of $\Sigma m_{\text{T}}(b_{1,2})$ in the single-tau $p_{\text{T}}(\tau)$-binned SR. The stacked histograms show the various SM background contributions. The hatched band indicates the total statistical and systematic uncertainty of the SM background. The $t\bar{t}$ (2 real $\tau$) and $t\bar{t}$ (1 real $\tau$) as well as the single-top background contributions are scaled with the normalization factors obtained from the background-only fit. Minor backgrounds are grouped together and denoted as 'Other'. This includes $t\bar{t}$-fake, single top, and other top (di-tau channel) or $t\bar{t}$-fake, $t\bar{t}+H$, multiboson, and other top (single-tau channel). The overlaid dotted lines show the additional contributions for signal scenarios close to the expected exclusion contour with the particle type and the mass and $\beta$ parameters for the simplified models indicated in the legend. For the leptoquark signal model the shapes of the distributions for $\text{LQ}_{3}^{\text{d}}$ and $\text{LQ}_{3}^{\text{v}}$ (not shown) are similar to that of $\text{LQ}_{3}^{\text{u}}$. The rightmost bin includes the overflow.
Distributions of $p_{\text{T}}(\tau)$ in the single-tau $p_{\text{T}}(\tau)$-binned SR. The stacked histograms show the various SM background contributions. The hatched band indicates the total statistical and systematic uncertainty of the SM background. The $t\bar{t}$ (2 real $\tau$) and $t\bar{t}$ (1 real $\tau$) as well as the single-top background contributions are scaled with the normalization factors obtained from the background-only fit. Minor backgrounds are grouped together and denoted as 'Other'. This includes $t\bar{t}$-fake, single top, and other top (di-tau channel) or $t\bar{t}$-fake, $t\bar{t}+H$, multiboson, and other top (single-tau channel). The overlaid dotted lines show the additional contributions for signal scenarios close to the expected exclusion contour with the particle type and the mass and $\beta$ parameters for the simplified models indicated in the legend. For the leptoquark signal model the shapes of the distributions for $\text{LQ}_{3}^{\text{d}}$ and $\text{LQ}_{3}^{\text{v}}$ (not shown) are similar to that of $\text{LQ}_{3}^{\text{u}}$. The rightmost bin includes the overflow.
Observed event yields in data ('Observed') and expected event yields for SM background processes obtained from the background-only fit ('Total bkg.' and rows below) in the signal regions of the di-tau and single-tau channels. The quoted uncertainties include both the statistical and systematic uncertainties and are truncated at zero yield. By construction, no $t\bar{t}$ (2 real $\tau$) events can pass the selections in the single-tau channel. As the individual uncertainties are correlated, they do not add in quadrature to equal the total background uncertainty.
From left to right: upper limits at the 95% confidence level (CL) on the visible cross section ($\sigma_\text{vis}$) and on the number of signal events ($S_{\text{obs}}^{95}$). The third column ($S_{\text{exp}}^{95}$) shows the upper limit at the 95% CL on the number of signal events, given the expected number (and $\pm 1\,\sigma$ excursions on the expectation) of background events. The last two columns indicate the confidence level observed for the background-only hypothesis ($\text{CL}_{b}$), the discovery $p$-value ($p(s=0)$) and the significance ($Z$). In the di-tau SR, where fewer events are observed than predicted by the fitted background estimate, the $p$-value is capped at 0.5.
Expected and observed exclusion contours at the 95% confidence level for the vector third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{v}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ into a quark and a charged lepton. The plot shows the exclusion contour for the minimal-coupling scenario. The limits are derived from the binned single-tau signal region.
Expected and observed exclusion contours at the 95% confidence level for the vector third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{v}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ into a quark and a charged lepton. The plot shows the exclusion contour for the minimal-coupling scenario. The limits are derived from the binned single-tau signal region.
Expected and observed exclusion contours at the 95% confidence level for the vector third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{v}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ into a quark and a charged lepton. The plot shows the exclusion contour for vector leptoquarks with additional gauge couplings. The limits are derived from the binned single-tau signal region.
Expected and observed exclusion contours at the 95% confidence level for the vector third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{v}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ into a quark and a charged lepton. The plot shows the exclusion contour for vector leptoquarks with additional gauge couplings. The limits are derived from the binned single-tau signal region.
Exclusion contours at the 95% confidence level for the stop-stau signal model as a function of the masses of the top squark $m(\tilde{t}_{1})$ and of the tau slepton $m(\tilde{\tau}_{1})$. Expected and observed limits are shown for the present search in comparison to observed limits from previous ATLAS analyses based on data from Run-1 of the LHC at $\sqrt{s} = 8$ TeV [Eur. Phys. J. C 76 (2016)] and on a partial dataset from Run 2 at $\sqrt{s} = 13$ TeV [Phys. Rev. D 98 (2018) 032008]. The green band indicates the limit on the mass of the tau slepton (for a massless LSP) from the LEP experiments.
Exclusion contours at the 95% confidence level for the stop-stau signal model as a function of the masses of the top squark $m(\tilde{t}_{1})$ and of the tau slepton $m(\tilde{\tau}_{1})$. Expected and observed limits are shown for the present search in comparison to observed limits from previous ATLAS analyses based on data from Run-1 of the LHC at $\sqrt{s} = 8$ TeV [Eur. Phys. J. C 76 (2016)] and on a partial dataset from Run 2 at $\sqrt{s} = 13$ TeV [Phys. Rev. D 98 (2018) 032008]. The green band indicates the limit on the mass of the tau slepton (for a massless LSP) from the LEP experiments.
Expected and observed exclusion contours at the 95% confidence level for the scalar third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{u}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow q\ell)$ into a quark and a charged lepton. The plot shows the exclusion contour for up-type leptoquarks $\text{LQ}_{3}^{\text{u}})$ with charge $+2/3e$. The limits are derived from the binned single-tau signal region. Shown in gray for comparison are the observed exclusion-limit contours from the previous ATLAS publication that targets the same leptoquark models but is based on a subset of the Run-2 data [JHEP 06 (2019) 144]. In this previous publication five different analyses are considered that target not only the final state studied here but also the final states that correspond to a branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow q\ell)$ of 0 or 1, leading to the concave shapes of the gray exclusion contours.
Expected and observed exclusion contours at the 95% confidence level for the scalar third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{u}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow q\ell)$ into a quark and a charged lepton. The plot shows the exclusion contour for up-type leptoquarks $\text{LQ}_{3}^{\text{u}})$ with charge $+2/3e$. The limits are derived from the binned single-tau signal region. Shown in gray for comparison are the observed exclusion-limit contours from the previous ATLAS publication that targets the same leptoquark models but is based on a subset of the Run-2 data [JHEP 06 (2019) 144]. In this previous publication five different analyses are considered that target not only the final state studied here but also the final states that correspond to a branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow q\ell)$ of 0 or 1, leading to the concave shapes of the gray exclusion contours.
Expected and observed exclusion contours at the 95% confidence level for the scalar third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{d}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow q\ell)$ into a quark and a charged lepton. The plot shows the exclusion contour for down-type leptoquarks $\text{LQ}_{3}^{\text{d}})$ with charge $-1/3e$. The limits are derived from the binned single-tau signal region. Shown in gray for comparison are the observed exclusion-limit contours from the previous ATLAS publication that targets the same leptoquark models but is based on a subset of the Run-2 data [JHEP 06 (2019) 144]. In this previous publication five different analyses are considered that target not only the final state studied here but also the final states that correspond to a branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow q\ell)$ of 0 or 1, leading to the concave shapes of the gray exclusion contours.
Expected and observed exclusion contours at the 95% confidence level for the scalar third-generation leptoquark signal model, as a function of the mass $m(\text{LQ}_{3}^{\text{d}})$ and the branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow q\ell)$ into a quark and a charged lepton. The plot shows the exclusion contour for down-type leptoquarks $\text{LQ}_{3}^{\text{d}})$ with charge $-1/3e$. The limits are derived from the binned single-tau signal region. Shown in gray for comparison are the observed exclusion-limit contours from the previous ATLAS publication that targets the same leptoquark models but is based on a subset of the Run-2 data [JHEP 06 (2019) 144]. In this previous publication five different analyses are considered that target not only the final state studied here but also the final states that correspond to a branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow q\ell)$ of 0 or 1, leading to the concave shapes of the gray exclusion contours.
Upper limits on the signal cross section at the 95 % confidence level for the stop-stau signal model.
Upper limits on the signal cross section at the 95 % confidence level for the scalar third-generation leptoquark signal model with up-type leptoquarks.
Upper limits on the signal cross section at the 95 % confidence level for the scalar third-generation leptoquark signal model with down-type leptoquarks.
Upper limits on the signal cross section at the 95 % confidence level for the vector third-generation leptoquark signal model with minimal coupling (MC).
Upper limits on the signal cross section at the 95 % confidence level for the vector third-generation leptoquark signal model with additional gauge couplings (YM).
Acceptance of the one-bin signal region of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$.
Efficiency of the one-bin signal region of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$.
Efficiency of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$.
Efficiency of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$.
Efficiency of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the signal region of the di-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$.
Efficiency of the signal region of the di-tau channel for pair production of up-type leptoquarks $\text{LQ}_{3}^{\text{u}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{u}} \rightarrow b\tau)$ of 0 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the one-bin signal region of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$.
Efficiency of the one-bin signal region of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow t\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$.
Efficiency of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow t\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$.
Efficiency of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow t\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$.
Efficiency of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow t\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the signal region of the di-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$.
Efficiency of the signal region of the di-tau channel for pair production of down-type leptoquarks $\text{LQ}_{3}^{\text{d}}$. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{d}} \rightarrow t\tau)$ of 0 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the one-bin signal region of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario.
Efficiency of the one-bin signal region of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario.
Efficiency of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario.
Efficiency of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario.
Efficiency of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the signal region of the di-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario.
Efficiency of the signal region of the di-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ in the minimal-coupling scenario. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the one-bin signal region of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings.
Efficiency of the one-bin signal region of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings.
Efficiency of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings.
Efficiency of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings.
Efficiency of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 or 1 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the signal region of the di-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings.
Efficiency of the signal region of the di-tau channel for pair production of vector leptoquarks $\text{LQ}_{3}^{\text{v}}$ with additional gauge couplings. The plot does not show efficiencies for a branching fraction $B(\text{LQ}_{3}^{\text{v}} \rightarrow b\tau)$ of 0 because here the acceptance at generator level becomes zero and the efficiency is thus undefined.
Acceptance of the one-bin signal region of the single-tau channel for pair production of top squarks with decays via tau sleptons.
Efficiency of the one-bin signal region of the single-tau channel for pair production of top squarks with decays via tau sleptons.
Acceptance of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of top squarks with decays via tau sleptons.
Efficiency of the first bin of the multi-bin signal region (50 GeV $< p_{\text{T}}(\tau) <$ 100 GeV) of the single-tau channel for pair production of top squarks with decays via tau sleptons.
Acceptance of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of top squarks with decays via tau sleptons.
Efficiency of the middle bin of the multi-bin signal region (100 GeV $< p_{\text{T}}(\tau) <$ 200 GeV) of the single-tau channel for pair production of top squarks with decays via tau sleptons.
Acceptance of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of top squarks with decays via tau sleptons.
Efficiency of the last bin of the multi-bin signal region (200 GeV $< p_{\text{T}}(\tau)$) of the single-tau channel for pair production of top squarks with decays via tau sleptons.
Acceptance of the signal region of the di-tau channel for pair production of top squarks with decays via tau sleptons.
Efficiency of the signal region of the di-tau channel for pair production of top squarks with decays via tau sleptons.
Cutflow for the benchmark signal model $m(\tilde{t}_{1}) = 1350$ GeV, $m(\tilde{\tau}_{1}) = 1090$ GeV for the di-tau SR. The simulated sample contains 30,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the di-tau channel.
Cutflow for the benchmark signal model $m(\tilde{t}_{1}) = 1350$ GeV, $m(\tilde{\tau}_{1}) = 1090$ GeV for the single-tau one-bin SR. The simulated sample contains 30,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.
Cutflow for the benchmark signal model $m(\tilde{t}_{1}) = 1350$ GeV, $m(\tilde{\tau}_{1}) = 1090$ GeV for the single-tau multi-bin SR. The simulated sample contains 30,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.
Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{u}}) = 1.2$ TeV, $\beta = 0.5$ for the di-tau SR. The simulated sample contains 210,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the di-tau channel.
Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{u}}) = 1.2$ TeV, $\beta = 0.5$ for the single-tau one-bin SR. The simulated sample contains 210,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.
Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{u}}) = 1.2$ TeV, $\beta = 0.5$ for the single-tau multi-bin SR. The simulated sample contains 210,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.
Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{d}}) = 1.2$ TeV, $\beta = 0.5$ for the di-tau SR. The simulated sample contains 210,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the di-tau channel.
Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{d}}) = 1.2$ TeV, $\beta = 0.5$ for the single-tau one-bin SR. The simulated sample contains 210,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.
Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{d}}) = 1.2$ TeV, $\beta = 0.5$ for the single-tau multi-bin SR. The simulated sample contains 210,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.
Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{v}}) = 1.4$ TeV, $\beta = 0.5$ in the minimal-coupling scenario for the di-tau SR. The simulated sample contains 50,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the di-tau channel.
Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{v}}) = 1.4$ TeV, $\beta = 0.5$ in the minimal-coupling scenario for the single-tau one-bin SR. The simulated sample contains 50,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.
Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{v}}) = 1.4$ TeV, $\beta = 0.5$ in the minimal-coupling scenario for the single-tau multi-bin SR. The simulated sample contains 50,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.
Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{v}}) = 1.4$ TeV, $\beta = 0.5$ in the Yang--Mills scenario for the di-tau SR. The simulated sample contains 50,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the di-tau channel.
Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{v}}) = 1.4$ TeV, $\beta = 0.5$ in the Yang--Mills scenario for the single-tau one-bin SR. The simulated sample contains 50,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.
Cutflow for the benchmark signal model $m(\text{LQ}_{3}^{\text{v}}) = 1.4$ TeV, $\beta = 0.5$ in the Yang--Mills scenario for the single-tau multi-bin SR. The simulated sample contains 50,000 raw MC events. Weighted event yields are reported, normalized to an integrated luminosity of 139 fb$^{-1}$. 'Preselection' refers to the preselection for the single-tau channel.
A search for the decay of the Higgs boson to a $Z$ boson and a light, pseudoscalar particle, $a$, decaying respectively to two leptons and to two photons is reported. The search uses the full LHC Run 2 proton-proton collision data at $\sqrt{s}=13$ TeV, corresponding to 139 fb$^{-1}$ collected by the ATLAS detector. This is one of the first searches for this specific decay mode of the Higgs boson, and it probes unexplored parameter space in models with axion-like particles (ALPs) and extended scalar sectors. The mass of the $a$ particle is assumed to be in the range 0.1-33 GeV. The data are analysed in two categories: a merged category where the photons from the $a$ decay are reconstructed in the ATLAS calorimeter as a single cluster, and a resolved category in which two separate photons are detected. The main background processes are from Standard Model $Z$ boson production in association with photons or jets. The data are in agreement with the background predictions, and upper limits on the branching ratio of the Higgs boson decay to $Za$ times the branching ratio $a\to\gamma\gamma$ are derived at the 95% confidence level and they range from 0.08% to 2% depending on the mass of the $a$ particle. The results are also interpreted in the context of ALP models.
Post-fit distribution for $m_{\gamma\gamma}$ for the resolved category in number of events per 0.2 GeV for data. The figure uses $pp$ collision data at $\sqrt{s}=13$ TeV corresponding to 139 fb$^{-1}$.
Post-fit distribution for $m_{\gamma\gamma}$ for the resolved category in number of events per 0.2 GeV for a signal distribution for $m_a = 9$ GeV, and the signal plus background fit with its background component. The branching ratio of the Higgs boson decay to $Za$ times the branching ratio $a $->$ \gamma \gamma$ is assumed to be 50%. The figure uses $pp$ collision data at $\sqrt{s}=13$ TeV corresponding to 139 fb$^{-1}$.
Post-fit final discriminating variable $\Delta R_{Z\gamma}$ in the signal region of the merged category. Signal distributions for $m_a$ values used in this category are overlayed for comparison, assuming a branching ratio of the Higgs boson decay to $Za$ times the branching ratio $a $->$ \gamma \gamma$ of 100%. The signal yields have been multiplied by 10 for better visibility. The figure uses $pp$ collision data at $\sqrt{s}=13$ TeV corresponding to 139 fb$^{-1}$.
Expected and observed 95% CL upper limits on the branching ratio of the Higgs boson decay to $Za$ times the branching ratio $a $->$ \gamma \gamma$ as a function of the $a$ particle mass in the merged ($m_a \le 2$ GeV) and the resolved ($m_a > 2$ GeV) categories. The figure uses $pp$ collision data at $\sqrt{s}=13$ TeV corresponding to 139 fb$^{-1}$.
ATLAS observed 95% CL exclusion contours limits in terms of the ALP mass and its effective coupling to photons, $|C_{\gamma\gamma}|/\Lambda$, for different values of the Higgs coupling to $Za$, $|C_{Zh}|/\Lambda$. The figure uses $pp$ collision data at $\sqrt{s}=13$ TeV corresponding to 139 fb$^{-1}$. The value 100 in the tables is presentational, denoting the upper edge of the plot.
Inclusive charged particle and event shape distributions are measured using 321 hadronic events collected with the DELPHI experiment at LEP at effective centre of mass energies of 130 to 136 GeV. These distributions are presented and compared to data at lower energies, in particular to the precise Z data. Fragmentation models describe the observed changes of the distributions well. The energy dependence of the means of the event shape variables can also be described using second order QCD plus power terms. A method independent of fragmentation model corrections is used to determine αs from the energy dependence of the mean thrust and heavy jet mass. It is measured to be: $$←pha _s(133 {⤪ GeV})={0.116}pm {0.007}_{exp-0.004theo}^{+0.005}$$ from the high energy data.
mean values for event shape variables.
Integral of event shape distribution over the specified interval.
Integral of event shape distribution over the specified interval.
Integral of event shape distribution over the specified interval.
Integral of event shape distribution over the specified interval.
Integral of event shape distribution over the specified interval.
Inclusive charged particle distributions, corrected to final state charged particles.
Rapidity, YS, w.r.t. Sphericity axis distribution. Axis definition is from corrected charged plus neutral particles.
Transverse momentum PTIN w.r.t. the Thrust axis. Axis definition is from corrected charged plus neutral particles.
Transverse momentum PTOUT w.r.t. the Thrust axis. Axis definition is from corrected charged plus neutral particles.
1-Thrust distribution. Axis definition is from corrected charged plus neutral particles.
Thrust Major distribution. Axis definition is from corrected charged plus neutral particles.
Thrust Minor distribution. Axis definition is from corrected charged plus neutral particles.
Oblateness distribution. Axis definition is from corrected charged plus neutral particles.
Wide Hemisphere Broadening, DBMAX. Axis definition is from charged corrected plus neutral particles.
Narrow Hemisphere Broadening, DBMIN. Axis definition is from charged corrected plus neutral particles.
Total Hemisphere Broadening, DBSUM. Axis definition is from charged corrected plus neutral particles.
Difference of the Hemisphere Broadening, DBDIFF. Axis definition is from charged corrected plus neutral particles.
2-jet rate for the Durham Algorithm.
3-jet rate for the Durham Algorithm.
4-jet rate for the Durham Algorithm.
5-jet rate for the Durham Algorithm.
2-jet rate for the Jade Algorithm.
3-jet rate for the Jade Algorithm.
4-jet rate for the Jade Algorithm.
5-jet rate for the Jade Algorithm.
The splitting processes in identified quark and gluon jets are investigated using longitudinal and transverse observables. The jets are selected from symmetric three-jet events measured in Z decays with the Delphi detector in 1991-1994. Gluon jets are identified using heavy quark anti-tagging. Scaling violations in identified gluon jets are observed for the first time. The scale energy dependence of the gluon fragmentation function is found to be about two times larger than for the corresponding quark jets, consistent with the QCD expectation CA/CF. The primary splitting of gluons and quarks into subjets agrees with fragmentation models and, for specific regions of the jet resolution y, with NLLA calculations. The maximum of the ratio of the primary subjet splittings in quark and gluon jets is 2.77±0.11±0.10. Due to non-perturbative effects, the data are below the expectation at small y. The transition from the perturbative to the non-perturbative domain appears at smaller y for quark jets than for gluon jets. Combined with the observed behaviour of the higher rank splittings, this explains the relatively small multiplicity ratio between gluon and quark jets.
Scaled energy distribution of charged hadrons produced in Quark jets in 'Y'topology 3-JET events.
Scaled energy distribution of charged hadrons produced in Gluon jets in 'Y'topology 3-JET events.
Scaled energy distribution of charged hadrons produced in Quark jets in 'Mercedes' topology 3-JET events.
Scaled energy distribution of charged hadrons produced in Gluon jets in 'Mercedes' topology 3-JET events.
Subjet multiplicity-1 as a function of the jet resolution parameter ycut for Quark jets in 'Y' topology events.
Subjet multiplicity-1 as a function of the jet resolution parameter ycut for Gluon jets in 'Y' topology events.
Ratio of the sub-jet multiplicity-1 for gluon jets to the sub-jet multiplicity-1 for quark jets as a function of the jet resolution parameter ycut in 'Y' topology events.
Total 1-jet rate for Quark jets as a function of the jet resolution parameter ycut in 'Y' topology events.
Total 1-jet rate for Gluon jets as a function of the jet resolution parameter ycut in 'Y' topology events.
Differential 1-jet rate for Quark jets as a function of the jet resolution parameter ycut in 'Y' topology events.
Differential 1-jet rate for Gluon jets as a function of the jet resolution parameter ycut in 'Y' topology events.
Splitting Function for Quark jets as a function of the jet resolution parameter ycut in 'Y' topology events.
Splitting Function for Gluon jets as a function of the jet resolution parameter ycut in 'Y' topology events.
Ratio of Splitting Functions for Gluon jets and Quark jets as a function ofthe jet resolution parameter ycut in 'Y' topology events.
A search is presented for flavour-changing neutral-current interactions involving the top quark, the Higgs boson and an up-type quark ($q=u,c$) with the ATLAS detector at the Large Hadron Collider. The analysis considers leptonic decays of the top quark along with Higgs boson decays into two $W$ bosons, two $Z$ bosons or a $\tau^{+}\tau^{-}$ pair. It focuses on final states containing either two leptons (electrons or muons) of the same charge or three leptons. The considered processes are $t\bar{t}$ and $Ht$ production. For the $t\bar{t}$ production, one top quark decays via $t\to Hq$. The proton-proton collision data set analysed amounts to 140 fb$^{-1}$ at $\sqrt{s}=13$ TeV. No significant excess beyond Standard Model expectations is observed and upper limits are set on the $t\to Hq$ branching ratios at 95% confidence level, amounting to observed (expected) limits of $\mathcal{B}(t\to Hu)<2.8\,(3.0) \times 10^{-4}$ and $\mathcal{B}(t\to Hc)<3.3\,(3.8) \times 10^{-4}$. Combining this search with other searches for $tHq$ flavour-changing neutral-current interactions previously conducted by ATLAS, considering $H\to b\bar{b}$ and $H\to\gamma\gamma$ decays, as well as $H\to\tau^{+}\tau^{-}$ decays with one or two hadronically decaying $\tau$-leptons, yields observed (expected) upper limits on the branching ratios of $\mathcal{B}(t\to Hu)<2.6\,(1.8) \times 10^{-4}$ and $\mathcal{B}(t\to Hc)<3.4\,(2.3) \times 10^{-4}$.
Pre-fit background composition of the SR$2\ell$ Dec. The table shows the event yields as opposed to just the percentages of the relevant background processes.
Pre-fit background composition of the SR$2\ell$ Prod. The table shows the event yields as opposed to just the percentages of the relevant background processes.
Pre-fit background composition of the SR$3\ell$ Dec. The table shows the event yields as opposed to just the percentages of the relevant background processes.
Pre-fit background composition of the SR$3\ell$ Prod. The table shows the event yields as opposed to just the percentages of the relevant background processes.
Post-fit plot of $H_\text{T}(\text{jets})$ in the SR$2\ell$ Dec from a signal-blinded background-only fit.
Post-fit plot of $m(t_\text{SM}, b\text{-jet}_0)$ in the SR$2\ell$ Prod from a signal-blinded background-only fit.
Post-fit plot of $m(\ell_\text{OS},\ell_\text{SS,1})$ in the SR$3\ell$ Dec from a signal-blinded background-only fit.
Post-fit plot of $m(\ell_\text{OS},\ell_\text{SS,1})$ in the SR$3\ell$ Prod from a signal-blinded background-only fit.
Post-fit plot of $D_\text{NN}(tHc)$ in the SR$2\ell$ Dec from the full fit to data.
Post-fit plot of $D_\text{NN}(tHc)$ in the SR$2\ell$ Prod from the full fit to data.
Post-fit plot of $D_\text{NN}(tHc)$ in the SR$3\ell$ Dec from the full fit to data.
Post-fit plot of $D_\text{NN}(tHc)$ in the SR$3\ell$ Prod from the full fit to data.
Post-fit plot of $p_\text{T}(\ell_1)$ in the CR$2\ell$ HF$e$ from the full fit to data.
Post-fit plot of $p_\text{T}(\ell_1)$ in the CR$2\ell$ HF$\mu$ from the full fit to data.
Post-fit plot of $p_\text{T}(\ell_1)$ in the CR$2\ell$ $t\bar{t}V$ from the full fit to data.
Post-fit plot of $p_\text{T}(\ell_2)$ in the CR$3\ell$ HF$e$ from the full fit to data.
Post-fit plot of $p_\text{T}(\ell_2)$ in the CR$3\ell$ HF$\mu$ from the full fit to data.
Post-fit plot of $p_\text{T}(b\text{-jet}_0)$ in the CR$3\ell$ $t\bar{t}W$ from the full fit to data.
Post-fit plot of $p_\text{T}(b\text{-jet}_0)$ in the CR$3\ell$ $t\bar{t}Z$ from the full fit to data.
Observed and expected upper exclusion limits on the branching ratio $\mathcal{B}(t\to Hu)$ for different analyses and their statistical combination.
Observed and expected upper exclusion limits on the branching ratio $\mathcal{B}(t\to Hc)$ for different analyses and their statistical combination.
Post-fit normalisation factors of free-floating background processes and the signal normalisation.
Post-fit predicted and observed yields in all $2\ell$SS signal and control regions. Pre-fit signal contributions for a signal cross section equivalent to $\mathcal{B}(t\to Hq)=0.1\,\%$ are given as well.
Post-fit predicted and observed yields in all $3\ell$ signal and control regions. Pre-fit signal contributions for a signal cross section equivalent to $\mathcal{B}(t\to Hq)=0.1\,\%$ are given as well.
Expected upper limits on $\mathcal{B}(t\to Hq)$ for the nominal fit and alternative fit configurations. One contains the full phase space but only considers statistical uncertainties. Two other configurations consider the full set of systematic uncertainties, but only encompass one final state.
Expected and observed upper limits on $\mathcal{B}(t\to Hq)$ and $|C_{u\phi}^{qt,tq}|$ for the full fit containing all systematic uncertainties.
Pre-fit plot of $H_\text{T}(\text{jets})$ in the SR$2\ell$ Dec from a signal-blinded background-only fit.
Pre-fit plot of $m(t_\text{SM}, b\text{-jet}_0)$ in the SR$2\ell$ Prod from a signal-blinded background-only fit.
Pre-fit plot of $m(\ell_\text{OS},\ell_\text{SS,1})$ in the SR$3\ell$ Dec from a signal-blinded background-only fit.
Pre-fit plot of $m(\ell_\text{OS},\ell_\text{SS,1})$ in the SR$3\ell$ Prod from a signal-blinded background-only fit.
Post-fit plot of $D_\text{NN}(tHu)$ in the SR$2\ell$ Dec from the full fit to data.
Post-fit plot of $D_\text{NN}(tHu)$ in the SR$2\ell$ Prod from the full fit to data.
Post-fit plot of $D_\text{NN}(tHu)$ in the SR$3\ell$ Dec from the full fit to data.
Post-fit plot of $D_\text{NN}(tHu)$ in the SR$3\ell$ Prod from the full fit to data.
Pre-fit plot of $D_\text{NN}(tHc)$ in the SR$2\ell$ Dec from the full fit to data.
Pre-fit plot of $D_\text{NN}(tHc)$ in the SR$2\ell$ Prod from the full fit to data.
Pre-fit plot of $D_\text{NN}(tHc)$ in the SR$3\ell$ Dec from the full fit to data.
Pre-fit plot of $D_\text{NN}(tHc)$ in the SR$3\ell$ Prod from the full fit to data.
Pre-fit plot of $D_\text{NN}(tHu)$ in the SR$2\ell$ Dec from the full fit to data.
Pre-fit plot of $D_\text{NN}(tHu)$ in the SR$2\ell$ Prod from the full fit to data.
Pre-fit plot of $D_\text{NN}(tHu)$ in the SR$3\ell$ Dec from the full fit to data.
Pre-fit plot of $D_\text{NN}(tHu)$ in the SR$3\ell$ Prod from the full fit to data.
Pre-fit plot of $p_\text{T}(\ell_1)$ in the CR$2\ell$ HF$e$ from the full fit to data.
Pre-fit plot of $p_\text{T}(\ell_1)$ in the CR$2\ell$ HF$\mu$ from the full fit to data.
Pre-fit plot of $p_\text{T}(\ell_1)$ in the CR$2\ell$ $t\bar{t}V$ from the full fit to data.
Pre-fit plot of $p_\text{T}(\ell_2)$ in the CR$3\ell$ HF$e$ from the full fit to data.
Pre-fit plot of $p_\text{T}(\ell_2)$ in the CR$3\ell$ HF$\mu$ from the full fit to data.
Pre-fit plot of $p_\text{T}(b\text{-jet}_0)$ in the CR$3\ell$ $t\bar{t}W$ from the full fit to data.
Pre-fit plot of $p_\text{T}(b\text{-jet}_0)$ in the CR$3\ell$ $t\bar{t}Z$ from the full fit to data.
Ranking of fit nuisance parameters according to their impact on the post-fit $tHu$ signal normalisation when fixed to $\pm1\sigma$
Ranking of fit nuisance parameters according to their impact on the post-fit $tHc$ signal normalisation when fixed to $\pm1\sigma$
Expected upper exclusion limits on the branching ratio $\mathcal{B}(t\to Hu)$ for each individual final state and the full analysis.
Expected upper exclusion limits on the branching ratio $\mathcal{B}(t\to Hc)$ for each individual final state and the full analysis.
A search for supersymmetry in events with four or more charged leptons (electrons, muons and $\tau$-leptons) is presented. The analysis uses a data sample corresponding to $139\,\mbox{fb\(^{-1}\)}$ of proton-proton collisions delivered by the Large Hadron Collider at $\sqrt{s}=13$ TeV and recorded by the ATLAS detector. Four-lepton signal regions with up to two hadronically decaying $\tau$-leptons are designed to target several supersymmetric models, while a general five-lepton signal region targets any new physics phenomena leading to a final state with five charged leptons. Data yields are consistent with Standard Model expectations and results are used to set upper limits on contributions from processes beyond the Standard Model. Exclusion limits are set at the 95% confidence level in simplified models of general gauge-mediated supersymmetry, excluding higgsino masses up to $540$ GeV. In $R$-parity-violating simplified models with decays of the lightest supersymmetric particle to charged leptons, lower limits of $1.6$ TeV, $1.2$ TeV, and $2.5$ TeV are placed on wino, slepton and gluino masses, respectively.
The $E_{\mathrm{T}}^{\mathrm{miss}}$ distribution in SR0-ZZ$^{\mathrm{loose}}$ and SR0-ZZ$^{\mathrm{tight}}$ for events passing the signal region requirements except the $E_{\mathrm{T}}^{\mathrm{miss}}$ requirement. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band. The red arrows indicate the $E_{\mathrm{T}}^{\mathrm{miss}}$ selections in the signal regions.
The $E_{\mathrm{T}}^{\mathrm{miss}}$ distribution in SR0-ZZ$_{\mathrm{bveto}}^{\mathrm{loose}}$ and SR0-ZZ$_{\mathrm{bveto}}^{\mathrm{tight}}$ for events passing the signal region requirements except the $E_{\mathrm{T}}^{\mathrm{miss}}$ requirement. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band. The red arrows indicate the $E_{\mathrm{T}}^{\mathrm{miss}}$ selections in the signal regions.
The $E_{\mathrm{T}}^{\mathrm{miss}}$ distribution in SR5L. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.
The $m_{\mathrm{eff}}$ distribution in SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$ and SR0$_{\mathrm{bveto}}^{\mathrm{tight}}$ for events passing the signal region requirements except the $m_{\mathrm{eff}}$ requirement. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band. The red arrows indicate the $m_{\mathrm{eff}}$ selections in the signal regions.
The $m_{\mathrm{eff}}$ distribution in SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$ and SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$ for events passing the signal region requirements except the $m_{\mathrm{eff}}$ requirement. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band. The red arrows indicate the $m_{\mathrm{eff}}$ selections in the signal regions.
The $m_{\mathrm{eff}}$ distribution in SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$ and SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$ for events passing the signal region requirements except the $m_{\mathrm{eff}}$ requirement. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band. The red arrows indicate the $m_{\mathrm{eff}}$ selections in the signal regions.
The $m_{\mathrm{eff}}$ distribution in SR0$_{\mathrm{breq}}$ for events passing the signal region requirements except the $m_{\mathrm{eff}}$ requirement. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band. The red arrows indicate the $m_{\mathrm{eff}}$ selections in the signal regions.
The $m_{\mathrm{eff}}$ distribution in SR1$_{\mathrm{breq}}$ for events passing the signal region requirements except the $m_{\mathrm{eff}}$ requirement. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band. The red arrows indicate the $m_{\mathrm{eff}}$ selections in the signal regions.
The $m_{\mathrm{eff}}$ distribution in SR2$_{\mathrm{breq}}$ for events passing the signal region requirements except the $m_{\mathrm{eff}}$ requirement. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band. The red arrows indicate the $m_{\mathrm{eff}}$ selections in the signal regions.
Expected 95% CL exclusion limits on the higgsino GGM models. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$+1\sigma$ expected 95% CL exclusion limits on the higgsino GGM models. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$-1\sigma$ expected 95% CL exclusion limits on the higgsino GGM models. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
Observed 95% CL exclusion limits on the higgsino GGM models. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$+1\sigma$ observed 95% CL exclusion limits on the higgsino GGM models. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$-1\sigma$ observed 95% CL exclusion limits on the higgsino GGM models. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
Expected 95% CL exclusion limits on wino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$+1\sigma$ expected 95% CL exclusion limits on wino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$-1\sigma$ expected 95% CL exclusion limits on wino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
Observed 95% CL exclusion limits on wino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$+1\sigma$ bserved 95% CL exclusion limits on wino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$-1\sigma$ observed 95% CL exclusion limits on wino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
Expected 95% CL exclusion limits on wino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$+1\sigma$ expected 95% CL exclusion limits on wino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$-1\sigma$ expected 95% CL exclusion limits on wino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
Observed 95% CL exclusion limits on wino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$+1\sigma$ observed 95% CL exclusion limits on wino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$-1\sigma$ observed 95% CL exclusion limits on wino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
Expected 95% CL exclusion limits on slepton/sneutrino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$+1\sigma$ expected 95% CL exclusion limits on slepton/sneutrino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$-1\sigma$ expected 95% CL exclusion limits on slepton/sneutrino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
Observed 95% CL exclusion limits on slepton/sneutrino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$+1\sigma$ observed 95% CL exclusion limits on slepton/sneutrino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$-1\sigma$ observed 95% CL exclusion limits on slepton/sneutrino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
Expected 95% CL exclusion limits on slepton/sneutrino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$+1\sigma$ expected 95% CL exclusion limits on slepton/sneutrino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$-1\sigma$ expected 95% CL exclusion limits on slepton/sneutrino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
Observed 95% CL exclusion limits on slepton/sneutrino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$+1\sigma$ observed 95% CL exclusion limits on slepton/sneutrino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$-1\sigma$ observed 95% CL exclusion limits on slepton/sneutrino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
Expected 95% CL exclusion limits on gluino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$+1\sigma$ expected 95% CL exclusion limits on gluino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$-1\sigma$ expected 95% CL exclusion limits on gluino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
Observed 95% CL exclusion limits on gluino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$+1\sigma$ observed 95% CL exclusion limits on gluino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$-1\sigma$ observed 95% CL exclusion limits on gluino NLSP pair production with RPV LSP decays via $\lambda_{12k}$, where $k \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
Expected 95% CL exclusion limits on gluino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$+1\sigma$ expected 95% CL exclusion limits on gluino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$-1\sigma$ expected 95% CL exclusion limits on gluino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
Observed 95% CL exclusion limits on gluino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$+1\sigma$ observed 95% CL exclusion limits on gluino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
$-1\sigma$ observed 95% CL exclusion limits on gluino NLSP pair production with RPV LSP decays via $\lambda_{i33}$, where $i \in{1,2}$. The limits are set using the statistical combination of disjoint signal regions. Where two (or more) signal regions overlap, the signal region contributing its observed $\mathrm{CL}_{\mathrm{s}}$ value to the combination is the one with the better (best) expected $\mathrm{CL}_{\mathrm{s}}$ value.
Observed upper limit on the signal cross section in fb for the wino NLSP models with RPV LSP decays via $\lambda_{12k}$ where $k \in{1,2}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Observed upper limit on the signal cross section in fb for the wino NLSP models with RPV LSP decays via $\lambda_{i33}$ where $i \in{1,2}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Observed upper limit on the signal cross section in fb for the slepton/sneutrino NLSP models with RPV LSP decays via $\lambda_{12k}$ where $k \in{1,2}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Observed upper limit on the signal cross section in fb for the slepton/sneutrino NLSP models with RPV LSP decays via $\lambda_{i33}$ where $i \in{1,2}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Observed upper limit on the signal cross section in fb for the gluino NLSP models with RPV LSP decays via $\lambda_{12k}$ where $k \in{1,2}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Observed upper limit on the signal cross section in fb for the gluino NLSP models with RPV LSP decays via $\lambda_{i33}$ where $i \in{1,2}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Observed upper limit on the signal cross section in fb for the higgsino GGM models. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Best expected SR for the wino NLSP models with RPV LSP decays via $\lambda_{12k}$ where $k \in{1,2}$. A value of 1 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$, 2 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$, 3 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$, 4 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$, and 5 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{tight}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$.
Best expected SR for the wino NLSP models with RPV LSP decays via $\lambda_{i33}$ where $i \in{1,2}$. A value of 1 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$, 2 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$, 3 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$, 4 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$, and 5 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{tight}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$.
Best expected SR for the slepton/sneutrino NLSP models with RPV LSP decays via $\lambda_{12k}$ where $k \in{1,2}$. A value of 1 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$, 2 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$, 3 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$, 4 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$, and 5 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{tight}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$.
Best expected SR for the slepton/sneutrino NLSP models with RPV LSP decays via $\lambda_{i33}$ where $i \in{1,2}$. A value of 1 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$, 2 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$, 3 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$, 4 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$, and 5 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{tight}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$.
Best expected SR for the gluino NLSP models with RPV LSP decays via $\lambda_{12k}$ where $k \in{1,2}$. A value of 1 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$, 2 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$, 3 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$, 4 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$, and 5 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{tight}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$.
Best expected SR for the gluino NLSP models with RPV LSP decays via $\lambda_{i33}$ where $i \in{1,2}$. A value of 1 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$, 2 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$, 3 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$, 4 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$, and 5 corresponds to SR0$_{\mathrm{bveto}}^{\mathrm{tight}}$SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$.
Best expected SR for the higgsino GGM models. A value of 6 corresponds to SR0-ZZ$^{\mathrm{loose}}$, 7 corresponds to SR0-ZZ$^{\mathrm{tight}}$, 8 corresponds to SR0-ZZ$^{\mathrm{loose}}_{\mathrm{bveto}}$, and 9 corresponds to SR0-ZZ$^{\mathrm{tight}}_{\mathrm{bveto}}$.
Acceptance across the wino NLSP $\lambda_{12k}\neq 0$ models for SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Efficiency across the wino NLSP $\lambda_{12k}\neq 0$ models for SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Acceptance across the wino NLSP $\lambda_{12k}\neq 0$ models for SR0$_{\mathrm{bveto}}^{\mathrm{tight}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Efficiency across the wino NLSP $\lambda_{12k}\neq 0$ models for SR0$_{\mathrm{bveto}}^{\mathrm{tight}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Acceptance across the wino NLSP $\lambda_{12k}\neq 0$ models for SR0$_{\mathrm{breq}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Efficiency across the wino NLSP $\lambda_{12k}\neq 0$ models for SR0$_{\mathrm{breq}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Acceptance across the wino NLSP $\lambda_{i33}\neq 0$ models for SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Efficiency across the wino NLSP $\lambda_{i33}\neq 0$ models for SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Acceptance across the wino NLSP $\lambda_{i33}\neq 0$ models for SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Efficiency across the wino NLSP $\lambda_{i33}\neq 0$ models for SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Acceptance across the wino NLSP $\lambda_{i33}\neq 0$ models for SR1$_{\mathrm{breq}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Efficiency across the wino NLSP $\lambda_{i33}\neq 0$ models for SR1$_{\mathrm{breq}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Acceptance across the wino NLSP $\lambda_{i33}\neq 0$ models for SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Efficiency across the wino NLSP $\lambda_{i33}\neq 0$ models for SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Acceptance across the wino NLSP $\lambda_{i33}\neq 0$ models for SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Efficiency across the wino NLSP $\lambda_{i33}\neq 0$ models for SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Acceptance across the wino NLSP $\lambda_{i33}\neq 0$ models for SR2$_{\mathrm{breq}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Efficiency across the wino NLSP $\lambda_{i33}\neq 0$ models for SR2$_{\mathrm{breq}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Acceptance across the GGM Higgsino grid for SR0-ZZ$^{\mathrm{loose}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Efficiency across the GGM Higgsino grid for SR0-ZZ$^{\mathrm{loose}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Acceptance across the GGM Higgsino grid for SR0-ZZ$^{\mathrm{tight}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Efficiency across the GGM Higgsino grid for SR0-ZZ$^{\mathrm{tight}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Acceptance across the GGM Higgsino grid for SR0-ZZ$_{\mathrm{bveto}}^{\mathrm{loose}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Efficiency across the GGM Higgsino grid for SR0-ZZ$_{\mathrm{bveto}}^{\mathrm{loose}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Acceptance across the GGM Higgsino grid for SR0-ZZ$_{\mathrm{bveto}}^{\mathrm{tight}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
Efficiency across the GGM Higgsino grid for SR0-ZZ$_{\mathrm{bveto}}^{\mathrm{tight}}$. The interpolation between signal scenarios studied is included for illustration purposes only and may be subject to interpolation effects in sparsely populated areas.
The $p_{\mathrm{T}}$ of the light leptons in distribution in SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.
The $p_{\mathrm{T}}$ of the light leptons in distribution in SR0-ZZ$^{\mathrm{loose}}$. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.
The $p_{\mathrm{T}}$ of the light leptons in distribution in SR0-ZZ$^{\mathrm{tight}}$. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.
The $p_{\mathrm{T}}$ of the light leptons in distribution in SR0-ZZ$_{\mathrm{bveto}}^{\mathrm{loose}}$. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.
The $p_{\mathrm{T}}$ of the light leptons in distribution in SR5L. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.
The $p_{\mathrm{T}}$ of the light leptons in distribution in SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.
The $p_{\mathrm{T}}$ of the taus leptons in distribution in SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.
The $p_{\mathrm{T}}$ of the light taus in distribution in SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.
The lepton flavour and multiplicities in events with four light leptons and a Z veto. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.
The lepton flavour and multiplicities in events with four light leptons and one Z candidate. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.
The lepton flavour and multiplicities in events with four light leptons and two Z candidates. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.
The lepton flavour and multiplicities in events with exactly five light leptons. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.
The lepton flavour and multiplicities in events with three light leptons and one tau and a Z veto. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.
The lepton flavour and multiplicities in events with three light leptons and one tau and one Z candidate. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.
The lepton flavour and multiplicities in events with two light leptons and two taus and a Z veto. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.
The lepton flavour and multiplicities in events with two light leptons and two taus and one Z candidate. Distributions for data, the estimated SM backgrounds after the background-only fit, and an example SUSY scenario are shown. "Other" is the sum of the $tWZ$, $t\bar{t}WW$, $t\bar{t} ZZ$, $t\bar{t} WH$, $t\bar{t} HH$, $t\bar{t} tW$, and $t\bar{t}t\bar{t}$ backgrounds. The last bin captures the overflow events. The lower panel shows the ratio of the observed data to the expected SM background yield in each bin. Both the statistical and systematic uncertainties in the SM background are included in the shaded band.
Cutflow event yields in regions SR0$_{\mathrm{bveto}}^{\mathrm{loose}}$, SR0$_{\mathrm{bveto}}^{\mathrm{tight}}$, SR0$_{\mathrm{breq}}$, and SR5L for RPV models with the $\lambda_{12k}\neq 0$ coupling. All yields correspond to weighted events, so that effects from lepton reconstruction efficiencies, trigger corrections, pileup reweighting, etc., are included. They are normalized to the integrated luminosity of the data sample, $\int L dt = 139\,\mbox{fb\(^{-1}\)}$. The preliminary event reduction is a centralized stage where at least two electrons/muons with uncalibrated $p_{\mathrm{T}} >$ 9 GeV are required.
Cutflow event yields in regions SR1$_{\mathrm{bveto}}^{\mathrm{loose}}$, SR1$_{\mathrm{bveto}}^{\mathrm{tight}}$, and SR1$_{\mathrm{breq}}$ for RPV models with the $\lambda_{i33}\neq 0$ coupling. All yields correspond to weighted events, so that effects from lepton reconstruction efficiencies, trigger corrections, pileup reweighting, etc., are included. They are normalized to the integrated luminosity of the data sample, $\int L dt = 139\,\mbox{fb\(^{-1}\)}$. The preliminary event reduction is a centralized stage where at least two electrons/muons with uncalibrated $p_{\mathrm{T}} >$ 9 GeV are required.
Cutflow event yields in regions SR2$_{\mathrm{bveto}}^{\mathrm{loose}}$, SR2$_{\mathrm{bveto}}^{\mathrm{tight}}$, and SR2$_{\mathrm{breq}}$ for RPV models with the $\lambda_{i33}\neq 0$ coupling. All yields correspond to weighted events, so that effects from lepton reconstruction efficiencies, trigger corrections, pileup reweighting, etc., are included. They are normalized to the integrated luminosity of the data sample, $\int L dt = 139\,\mbox{fb\(^{-1}\)}$. The preliminary event reduction is a centralized stage where at least two electrons/muons with uncalibrated $p_{\mathrm{T}} >$ 9 GeV are required.
Cutflow event yields in regions SR0-ZZ$^{\mathrm{loose}}$, SR0-ZZ$^{\mathrm{tight}}$, SR0-ZZ$_{\mathrm{bveto}}^{\mathrm{loose}}$, SR0-ZZ$_{\mathrm{bveto}}^{\mathrm{tight}}$, and SR5L the higgsino GGM RPC model with BR($\tilde{\chi}^{0}_1 \rightarrow Z \tilde{G}$) = 50% and higgsino masses of 200 GeV, or BR($\tilde{\chi}^{0}_1 \rightarrow Z \tilde{G}$) = 100% and higgsino masses of 300 GeV. All yields correspond to weighted events, so that effects from lepton reconstruction efficiencies, trigger corrections, pileup reweighting, etc., are included. They are normalized to the integrated luminosity of the data sample, $\int L dt = 139\,\mbox{fb\(^{-1}\)}$. The generator filter is a selection of $\geq$4e/$\mu$/$\tau_{\mathrm{had-vis}}$ leptons with $p_{\mathrm{T}}(e,\mu)>4$GeV, $p_{\mathrm{T}}(\tau_{\mathrm{had-vis}})>15$GeV and $|\eta|<2.8$ and is applied during the MC generation of the simulated events. The preliminary event reduction is a centralized stage where at least two electrons/muons with uncalibrated $p_{\mathrm{T}} > 9$ GeV are required.
A search is reported for excited $\tau$-leptons and leptoquarks in events with two hadronically decaying $\tau$-leptons and two or more jets. The search uses proton-proton (pp) collision data at $\sqrt{s} = 13$ TeV recorded by the ATLAS experiment during the Run 2 of the Large Hadron Collider in 2015-2018. The total integrated luminosity is 139 fb$^{-1}$. The excited $\tau$-lepton is assumed to be produced and to decay via a four-fermion contact interaction into an ordinary $\tau$-lepton and a quark-antiquark pair. The leptoquarks are assumed to be produced in pairs via the strong interaction, and each leptoquark is assumed to couple to a charm or lighter quark and a $\tau$-lepton. No excess over the background prediction is observed. Excited $\tau$-leptons with masses below 2.8 TeV are excluded at 95% CL in scenarios with the contact interaction scale $\Lambda$ set to 10 TeV. At the extreme limit of model validity where $\Lambda$ is set equal to the excited $\tau$-lepton mass, excited $\tau$-leptons with masses below 4.6 TeV are excluded. Leptoquarks with masses below 1.3 TeV are excluded at 95% CL if their branching ratio to a charm quark and a $\tau$-lepton equals 1. The analysis does not exploit flavour-tagging in the signal region.
Observed and expected upper 95% CL limit on the $\tau^\ast$ production cross-section as a function of $m_{\tau^\ast}$ for a fixed value of the contact interaction scale, $\Lambda = 10$ TeV.
Observed and expected lower 95% CL limit on the contact interaction scale $\Lambda$ as a function of $m_{\tau^\ast}$.
Observed and expected upper 95% CL limit on the LQ production cross-section as a function of $m_\mathrm{LQ}$. The LQ couples to a tau lepton and a c-quark. The limits are also valid for scenarios in which the LQ couples to lighter quarks.
Cutflow for two representative signal samples used in this analysis. The excited tau mass $m_{\tau^\ast} = 2.75$ TeV and the contact interaction scale $\Lambda=10$ TeV. The LQ mass $m_\mathrm{LQ} = 1.3$ TeV. The event yields include all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$.
Acceptance x efficiency of the $\tau^\ast$ signal SR selection
Acceptance x efficiency of the LQ signal SR selection
This search, a type not previously performed at ATLAS, uses a comparison of the production cross sections for $e^+ \mu^-$ and $e^- \mu^+$ pairs to constrain physics processes beyond the Standard Model. It uses $139 \text{fb}^{-1}$ of proton$-$proton collision data recorded at $\sqrt{s} = 13$ TeV at the LHC. Targeting sources of new physics which prefer final states containing $e^{+}\mu^{-}$ to $e^{-}\mu^{+}$, the search contains two broad signal regions which are used to provide model-independent constraints on the ratio of cross sections at the 2% level. The search also has two special selections targeting supersymmetric models and leptoquark signatures. Observations using one of these selections are able to exclude, at 95% confidence level, singly produced smuons with masses up to 640 GeV in a model in which the only other light sparticle is a neutralino when the $R$-parity-violating coupling $\lambda'_{231}$ is close to unity. Observations using the other selection exclude scalar leptoquarks with masses below 1880 GeV when $g_{\text{1R}}^{eu}=g_{\text{1R}}^{\mu c}=1$, at 95% confidence level. The limit on the coupling reduces to $g_{\text{1R}}^{eu}=g_{\text{1R}}^{\mu c}=0.46$ for a mass of 1420 GeV.
Observed yields, and (post-fit) expected yields for the data-driven SM estimates. Yields are shown for the benchmark RPV-supersymmetry signal points in SR-RPV and the leptoquark signal points in SR-LQ after a fit excluding the $e^{+}\mu^{-}$ signal region and setting $\mu_{\text{sig}}=1$. Small weights correcting for muon charge biases affect all rows except that containing the fake-lepton estimate. These weights, $w_i$, cause non-integer yields. The uncertainties, $\sqrt{\sum_i w_i^2}$, are given for data to support the choice made to model the yields with a Poisson distribution.
The observed exclusion contour at 95% CL as a function of the smuon and neutralino masses, for $\lambda_{231}^{'}=1.0$.
The expected exclusion contour at 95% CL as a function of the smuon and neutralino masses, for $\lambda_{231}^{'}=1.0$.
The $1\sigma_{\text{exp}}$ variation of the expected exclusion contour at 95% CL as a function of the smuon and neutralino masses, for $\lambda_{231}^{'}=1.0$.
The observed exclusion contour at 95% CL as a function of the smuon and neutralino masses, for $\lambda_{231}^{'}=0.1$.
The expected exclusion contour at 95% CL as a function of the smuon and neutralino masses, for $\lambda_{231}^{'}=0.1$.
The observed exclusion contour at 95% CL as a function of the smuon and neutralino masses, for $\lambda_{231}^{'}=0.15$.
The expected exclusion contour at 95% CL as a function of the smuon and neutralino masses, for $\lambda_{231}^{'}=0.15$.
The observed exclusion contour at 95% CL as a function of the smuon and neutralino masses, for $\lambda_{231}^{'}=0.2$.
The expected exclusion contour at 95% CL as a function of the smuon and neutralino masses, for $\lambda_{231}^{'}=0.2$.
The observed exclusion contour at 95% CL as a function of the smuon and neutralino masses, for $\lambda_{231}^{'}=0.4$.
The expected exclusion contour at 95% CL as a function of the smuon and neutralino masses, for $\lambda_{231}^{'}=0.4$.
The observed exclusion contour at 95% CL as a function of the smuon and neutralino masses, for $\lambda_{231}^{'}=0.6$.
The expected exclusion contour at 95% CL as a function of the smuon and neutralino masses, for $\lambda_{231}^{'}=0p6$.
The observed exclusion contour at 95% CL as a function of the smuon and neutralino masses, for $\lambda_{231}^{'}=1.5$.
The expected exclusion contour at 95% CL as a function of the smuon and neutralino masses, for $\lambda_{231}^{'}=1.5$.
The observed exclusion contour at 95% CL as a function of the leptoquark mass and coupling strength.
The expected exclusion contour at 95% CL as a function of the leptoquark mass and coupling strength.
The minus $1\sigma_{\text{theory}}$ variation of the observed exclusion contour at 95% CL as a function of the leptoquark mass and coupling strength.
The plus $1\sigma_{\text{theory}}$ variation of the observed exclusion contour at 95% CL as a function of the leptoquark mass and coupling strength.
The $1\sigma_{\text{exp}}$ variation of the expected exclusion contour at 95% CL as a function of the leptoquark mass and coupling strength.
Observed yields, and fake lepton background yields in the $e^{+}\mu^{-}$ and $e^{-}\mu^{+}$ channels of SR-MET, along with the results of the $e^{+}\mu^{-}/e^{-}\mu^{+}$ ratio measurement and 1-sided p-value in SR-MET, binned in $M_{T2}$.
Observed yields, and fake lepton background yields in the $e^{+}\mu^{-}$ and $e^{-}\mu^{+}$ channels of SR-JET, along with the results of the $e^{+}\mu^{-}/e^{-}\mu^{+}$ ratio measurement and 1-sided p-value in SR-JET, binned in $H_{\text{P}}$.
Observed and expected 95% CL upper limits on the total number of signal events entering the $e^{+}\mu^{-}$ and $e^{-}\mu^{+}$ channels of each bin of SR-MET. The regions are binned in the same way as the ratio $\rho$ measurement. The limits are shown for a selection of 'z' values, where 'z' is the fraction of the total signal events entering the $e^{+}\mu^{-}$ channel.
Observed and expected 95% CL upper limits on the total number of signal events entering the $e^{+}\mu^{-}$ and $e^{-}\mu^{+}$ channels of each bin of SR-JET. The regions are binned in the same way as the ratio $\rho$ measurement. The limits are shown for a selection of 'z' values, where 'z' is the fraction of the total signal events entering the $e^{+}\mu^{-}$ channel.
Signal yields following each cut in the analysis, for representative $R$-parity-violating supersymmetry and leptoquark signals. All yields are MC generator-weighted and normalised to $139~\text{fb}^{-1}$. The cut labelled `Preselection' includes trigger requirements, and requires exactly one Baseline electron and one Baseline muon. At this point, the muon charge-bias correction weights are also applied. The $R$-parity-violating supersymmetry models were generated by specifying a top-quark in the final state and applying a two-lepton filter, hence the first row also includes events where the top quark decays to an electron.
Searches are performed for nonresonant and resonant di-Higgs boson production in the $b\bar{b}\gamma\gamma$ final state. The data set used corresponds to an integrated luminosity of 139 fb$^{-1}$ of proton-proton collisions at a center-of-mass energy of 13 TeV recorded by the ATLAS detector at the CERN Large Hadron Collider. No excess above the expected background is found and upper limits on the di-Higgs boson production cross sections are set. A 95% confidence-level upper limit of 4.2 times the cross section predicted by the Standard Model is set on $pp \rightarrow HH$ nonresonant production, where the expected limit is 5.7 times the Standard Model predicted value. The expected constraints are obtained for a background hypothesis excluding $pp \rightarrow HH$ production. The observed (expected) constraints on the Higgs boson trilinear coupling modifier $\kappa_{\lambda}$ are determined to be $[-1.5, 6.7]$ $([-2.4, 7.7])$ at 95% confidence level, where the expected constraints on $\kappa_{\lambda}$ are obtained excluding $pp \rightarrow HH$ production from the background hypothesis. For resonant production of a new hypothetical scalar particle $X$ ($X \rightarrow HH \rightarrow b\bar{b}\gamma\gamma$), limits on the cross section for $pp \to X \to HH$ are presented in the narrow-width approximation as a function of $m_{X}$ in the range $251 \leq m_{X} \leq 1000$ GeV. The observed (expected) limits on the cross section for $pp \to X \to HH$ range from 640 fb to 44 fb (391 fb to 46 fb) over the considered mass range.
The BDT distribution of the di-Higgs ggF signal for two different values of $\kappa_{\lambda}$ and the main backgrounds in the low mass region ($m^{*}_{b\bar{b}\gamma\gamma} < 350$ GeV). Distributions are normalized to unit area. The dotted lines denote the category boundaries. Events with a BDT score below 0.881 in the low mass region are discarded.
The BDT distribution of the di-Higgs ggF signal for two different values of $\kappa_{\lambda}$ and the main backgrounds in the low mass region ($m^{*}_{b\bar{b}\gamma\gamma} < 350$ GeV). Distributions are normalized to unit area. The dotted lines denote the category boundaries. Events with a BDT score below 0.881 in the low mass region are discarded.
The BDT distribution of the di-Higgs ggF signal for two different values of $\kappa_{\lambda}$ and the main backgrounds in the low mass region ($m^{*}_{b\bar{b}\gamma\gamma} < 350$ GeV). Distributions are normalized to unit area. The dotted lines denote the category boundaries. Events with a BDT score below 0.881 in the low mass region are discarded.
The BDT distribution of the di-Higgs ggF signal for two different values of $\kappa_{\lambda}$ and the main backgrounds in the low mass region ($m^{*}_{b\bar{b}\gamma\gamma} < 350$ GeV). Distributions are normalized to unit area. The dotted lines denote the category boundaries. Events with a BDT score below 0.881 in the low mass region are discarded.
The BDT distribution (with x-axis zoomed in) of the di-Higgs ggF signal for two different values of $\kappa_{\lambda}$ and the main backgrounds in the low mass region ($m^{*}_{b\bar{b}\gamma\gamma} < 350$ GeV). Distributions are normalized to unit area. The dotted lines denote the category boundaries. Events with a BDT score below 0.881 in the low mass region are discarded. The range of BDT scores is from 0.8 to 1.
The BDT distribution (with x-axis zoomed in) of the di-Higgs ggF signal for two different values of $\kappa_{\lambda}$ and the main backgrounds in the low mass region ($m^{*}_{b\bar{b}\gamma\gamma} < 350$ GeV). Distributions are normalized to unit area. The dotted lines denote the category boundaries. Events with a BDT score below 0.881 in the low mass region are discarded. The range of BDT scores is from 0.8 to 1.
The BDT distribution (with x-axis zoomed in) of the di-Higgs ggF signal for two different values of $\kappa_{\lambda}$ and the main backgrounds in the low mass region ($m^{*}_{b\bar{b}\gamma\gamma} < 350$ GeV). Distributions are normalized to unit area. The dotted lines denote the category boundaries. Events with a BDT score below 0.881 in the low mass region are discarded. The range of BDT scores is from 0.8 to 1.
The BDT distribution (with x-axis zoomed in) of the di-Higgs ggF signal for two different values of $\kappa_{\lambda}$ and the main backgrounds in the low mass region ($m^{*}_{b\bar{b}\gamma\gamma} < 350$ GeV). Distributions are normalized to unit area. The dotted lines denote the category boundaries. Events with a BDT score below 0.881 in the low mass region are discarded. The range of BDT scores is from 0.8 to 1.
The BDT distribution of the di-Higgs ggF signal for two different values of $\kappa_{\lambda}$ and the main backgrounds in the high mass region ($m^{*}_{b\bar{b}\gamma\gamma} > 350$ GeV). Distributions are normalized to unit area. The dotted lines denote the category boundaries. Events with a BDT score below 0.857 in the high mass region are discarded.
The BDT distribution of the di-Higgs ggF signal for two different values of $\kappa_{\lambda}$ and the main backgrounds in the high mass region ($m^{*}_{b\bar{b}\gamma\gamma} > 350$ GeV). Distributions are normalized to unit area. The dotted lines denote the category boundaries. Events with a BDT score below 0.857 in the high mass region are discarded.
The BDT distribution of the di-Higgs ggF signal for two different values of $\kappa_{\lambda}$ and the main backgrounds in the high mass region ($m^{*}_{b\bar{b}\gamma\gamma} > 350$ GeV). Distributions are normalized to unit area. The dotted lines denote the category boundaries. Events with a BDT score below 0.857 in the high mass region are discarded.
The BDT distribution of the di-Higgs ggF signal for two different values of $\kappa_{\lambda}$ and the main backgrounds in the high mass region ($m^{*}_{b\bar{b}\gamma\gamma} > 350$ GeV). Distributions are normalized to unit area. The dotted lines denote the category boundaries. Events with a BDT score below 0.857 in the high mass region are discarded.
The BDT distribution (with x-axis zoomed in) of the di-Higgs ggF signal for two different values of $\kappa_{\lambda}$ and the main backgrounds in the high mass region ($m^{*}_{b\bar{b}\gamma\gamma} > 350$ GeV). Distributions are normalized to unit area. The dotted lines denote the category boundaries. Events with a BDT score below 0.857 in the high mass region are discarded. The range of BDT scores is from 0.8 to 1.
The BDT distribution (with x-axis zoomed in) of the di-Higgs ggF signal for two different values of $\kappa_{\lambda}$ and the main backgrounds in the high mass region ($m^{*}_{b\bar{b}\gamma\gamma} > 350$ GeV). Distributions are normalized to unit area. The dotted lines denote the category boundaries. Events with a BDT score below 0.857 in the high mass region are discarded. The range of BDT scores is from 0.8 to 1.
The BDT distribution (with x-axis zoomed in) of the di-Higgs ggF signal for two different values of $\kappa_{\lambda}$ and the main backgrounds in the high mass region ($m^{*}_{b\bar{b}\gamma\gamma} > 350$ GeV). Distributions are normalized to unit area. The dotted lines denote the category boundaries. Events with a BDT score below 0.857 in the high mass region are discarded. The range of BDT scores is from 0.8 to 1.
The BDT distribution (with x-axis zoomed in) of the di-Higgs ggF signal for two different values of $\kappa_{\lambda}$ and the main backgrounds in the high mass region ($m^{*}_{b\bar{b}\gamma\gamma} > 350$ GeV). Distributions are normalized to unit area. The dotted lines denote the category boundaries. Events with a BDT score below 0.857 in the high mass region are discarded. The range of BDT scores is from 0.8 to 1.
The $BDT_{tot}$ score for the benchmark signal $m_{X}$ = 300 GeV and for the main backgrounds. Distributions are normalized to unit area. The dotted line denotes the event selection threshold. Events with a $BDT_{tot}$ score below 0.85 for $m_{X}$ = 300 GeV are discarded.
The $BDT_{tot}$ score for the benchmark signal $m_{X}$ = 300 GeV and for the main backgrounds. Distributions are normalized to unit area. The dotted line denotes the event selection threshold. Events with a $BDT_{tot}$ score below 0.85 for $m_{X}$ = 300 GeV are discarded.
The $BDT_{tot}$ score for the benchmark signal $m_{X}$ = 300 GeV and for the main backgrounds. Distributions are normalized to unit area. The dotted line denotes the event selection threshold. Events with a $BDT_{tot}$ score below 0.85 for $m_{X}$ = 300 GeV are discarded.
The $BDT_{tot}$ score for the benchmark signal $m_{X}$ = 300 GeV and for the main backgrounds. Distributions are normalized to unit area. The dotted line denotes the event selection threshold. Events with a $BDT_{tot}$ score below 0.85 for $m_{X}$ = 300 GeV are discarded.
The $BDT_{tot}$ score for the benchmark signal $m_{X}$ = 500 GeV and for the main backgrounds. Distributions are normalized to unit area. The dotted line denotes the event selection threshold. Events with a $BDT_{tot}$ score below 0.75 for $m_{X}$ = 500 GeV are discarded.
The $BDT_{tot}$ score for the benchmark signal $m_{X}$ = 500 GeV and for the main backgrounds. Distributions are normalized to unit area. The dotted line denotes the event selection threshold. Events with a $BDT_{tot}$ score below 0.75 for $m_{X}$ = 500 GeV are discarded.
The $BDT_{tot}$ score for the benchmark signal $m_{X}$ = 500 GeV and for the main backgrounds. Distributions are normalized to unit area. The dotted line denotes the event selection threshold. Events with a $BDT_{tot}$ score below 0.75 for $m_{X}$ = 500 GeV are discarded.
The $BDT_{tot}$ score for the benchmark signal $m_{X}$ = 500 GeV and for the main backgrounds. Distributions are normalized to unit area. The dotted line denotes the event selection threshold. Events with a $BDT_{tot}$ score below 0.75 for $m_{X}$ = 500 GeV are discarded.
Distributions of $m_{\gamma\gamma}$ in high mass BDT tight category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.
Distributions of $m_{\gamma\gamma}$ in high mass BDT tight category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.
Distributions of $m_{\gamma\gamma}$ in high mass BDT tight category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.
Distributions of $m_{\gamma\gamma}$ in high mass BDT tight category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.
Distributions of $m_{\gamma\gamma}$ in high mass BDT loose category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.
Distributions of $m_{\gamma\gamma}$ in high mass BDT loose category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.
Distributions of $m_{\gamma\gamma}$ in high mass BDT loose category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.
Distributions of $m_{\gamma\gamma}$ in high mass BDT loose category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.
Distributions of $m_{\gamma\gamma}$ in low mass BDT tight category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.
Distributions of $m_{\gamma\gamma}$ in low mass BDT tight category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.
Distributions of $m_{\gamma\gamma}$ in low mass BDT tight category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.
Distributions of $m_{\gamma\gamma}$ in low mass BDT tight category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.
Distributions of $m_{\gamma\gamma}$ in low mass BDT loose category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.
Distributions of $m_{\gamma\gamma}$ in low mass BDT loose category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.
Distributions of $m_{\gamma\gamma}$ in low mass BDT loose category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.
Distributions of $m_{\gamma\gamma}$ in low mass BDT loose category for the nonresonant $HH$ search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband.
Distributions of $m_{\gamma\gamma}$ for the selections used for the resonance mass point $m_{X}$ = 300 GeV for the resonant search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband. The scalar resonance signal is scaled to a total production cross section $\sigma(pp \rightarrow X \rightarrow HH)$ = 370 fb.
Distributions of $m_{\gamma\gamma}$ for the selections used for the resonance mass point $m_{X}$ = 300 GeV for the resonant search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband. The scalar resonance signal is scaled to a total production cross section $\sigma(pp \rightarrow X \rightarrow HH)$ = 370 fb.
Distributions of $m_{\gamma\gamma}$ for the selections used for the resonance mass point $m_{X}$ = 300 GeV for the resonant search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband. The scalar resonance signal is scaled to a total production cross section $\sigma(pp \rightarrow X \rightarrow HH)$ = 370 fb.
Distributions of $m_{\gamma\gamma}$ for the selections used for the resonance mass point $m_{X}$ = 300 GeV for the resonant search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband. The scalar resonance signal is scaled to a total production cross section $\sigma(pp \rightarrow X \rightarrow HH)$ = 370 fb.
Distributions of $m_{\gamma\gamma}$ for the selections used for the resonance mass point $m_{X}$ = 500 GeV for the resonant search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband. The scalar resonance signal is scaled to a total production cross section $\sigma(pp \rightarrow X \rightarrow HH)$ = 67 fb.
Distributions of $m_{\gamma\gamma}$ for the selections used for the resonance mass point $m_{X}$ = 500 GeV for the resonant search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband. The scalar resonance signal is scaled to a total production cross section $\sigma(pp \rightarrow X \rightarrow HH)$ = 67 fb.
Distributions of $m_{\gamma\gamma}$ for the selections used for the resonance mass point $m_{X}$ = 500 GeV for the resonant search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband. The scalar resonance signal is scaled to a total production cross section $\sigma(pp \rightarrow X \rightarrow HH)$ = 67 fb.
Distributions of $m_{\gamma\gamma}$ for the selections used for the resonance mass point $m_{X}$ = 500 GeV for the resonant search. The data-derived fractions of nonresonant $\gamma\gamma$, $\gamma$-jet or jet-$\gamma$, and dijet background are applied and the total background is normalized to the data sideband. The scalar resonance signal is scaled to a total production cross section $\sigma(pp \rightarrow X \rightarrow HH)$ = 67 fb.
The number of data events observed in the 120 GeV < $m_{\gamma\gamma}$ < 130 GeV window, the number of $HH$ signal events expected for $\kappa_{\lambda}$ = 1 and for $\kappa_{\lambda}$ = 10, and events expected for single Higgs boson production (estimated using MC simulation), as well as for continuum background. For the single Higgs boson, Rest includes VBF, $WH$, $tHqb$, and $tHW$. The values are obtained from a fit of the Asimov data set generated under the SM signal-plus-background hypothesis, $\kappa_{\lambda}$ = 1. The continuum background component of the Asimov data set is obtained from the fit of the data sideband. The uncertainties in $HH$ signals and single Higgs boson background include the systematic uncertainties discussed in Section 6. The uncertainty in the continuum background is given by the sum in quadrature of the statistical uncertainty from the fit to the data and the spurious-signal uncertainty.
The number of data events observed in the 120 GeV < $m_{\gamma\gamma}$ < 130 GeV window, the number of $HH$ signal events expected for $\kappa_{\lambda}$ = 1 and for $\kappa_{\lambda}$ = 10, and events expected for single Higgs boson production (estimated using MC simulation), as well as for continuum background. For the single Higgs boson, Rest includes VBF, $WH$, $tHqb$, and $tHW$. The values are obtained from a fit of the Asimov data set generated under the SM signal-plus-background hypothesis, $\kappa_{\lambda}$ = 1. The continuum background component of the Asimov data set is obtained from the fit of the data sideband. The uncertainties in $HH$ signals and single Higgs boson background include the systematic uncertainties discussed in Section 6. The uncertainty in the continuum background is given by the sum in quadrature of the statistical uncertainty from the fit to the data and the spurious-signal uncertainty.
The number of data events observed in the 120 GeV < $m_{\gamma\gamma}$ < 130 GeV window, the number of $HH$ signal events expected for $\kappa_{\lambda}$ = 1 and for $\kappa_{\lambda}$ = 10, and events expected for single Higgs boson production (estimated using MC simulation), as well as for continuum background. For the single Higgs boson, Rest includes VBF, $WH$, $tHqb$, and $tHW$. The values are obtained from a fit of the Asimov data set generated under the SM signal-plus-background hypothesis, $\kappa_{\lambda}$ = 1. The continuum background component of the Asimov data set is obtained from the fit of the data sideband. The uncertainties in $HH$ signals and single Higgs boson background include the systematic uncertainties discussed in Section 6. The uncertainty in the continuum background is given by the sum in quadrature of the statistical uncertainty from the fit to the data and the spurious-signal uncertainty.
The number of data events observed in the 120 GeV < $m_{\gamma\gamma}$ < 130 GeV window, the number of $HH$ signal events expected for $\kappa_{\lambda}$ = 1 and for $\kappa_{\lambda}$ = 10, and events expected for single Higgs boson production (estimated using MC simulation), as well as for continuum background. For the single Higgs boson, Rest includes VBF, $WH$, $tHqb$, and $tHW$. The values are obtained from a fit of the Asimov data set generated under the SM signal-plus-background hypothesis, $\kappa_{\lambda}$ = 1. The continuum background component of the Asimov data set is obtained from the fit of the data sideband. The uncertainties in $HH$ signals and single Higgs boson background include the systematic uncertainties discussed in Section 6. The uncertainty in the continuum background is given by the sum in quadrature of the statistical uncertainty from the fit to the data and the spurious-signal uncertainty.
Observed and expected limits at 95% CL on the cross section of nonresonant Higgs boson pair production as a function of the Higgs boson self-coupling modifier $\kappa_{\lambda}= \lambda_{HHH}/\lambda^{\textrm{SM}}_{HHH}$. The expected constraints on $\kappa_{\lambda}$ are obtained with a background hypothesis excluding $pp \rightarrow HH$ production. The $\pm 1\sigma$ and $\pm 2\sigma$ variations about the expected limit due to statistical and systematic uncertainties are also shown. The theory prediction curve represents the scenario where all parameters and couplings are set to their SM values except for $\kappa_{\lambda}$. The uncertainty band of the theory prediction curve shows the cross-section uncertainty.
Observed and expected limits at 95% CL on the cross section of nonresonant Higgs boson pair production as a function of the Higgs boson self-coupling modifier $\kappa_{\lambda}= \lambda_{HHH}/\lambda^{\textrm{SM}}_{HHH}$. The expected constraints on $\kappa_{\lambda}$ are obtained with a background hypothesis excluding $pp \rightarrow HH$ production. The $\pm 1\sigma$ and $\pm 2\sigma$ variations about the expected limit due to statistical and systematic uncertainties are also shown. The theory prediction curve represents the scenario where all parameters and couplings are set to their SM values except for $\kappa_{\lambda}$. The uncertainty band of the theory prediction curve shows the cross-section uncertainty.
Observed and expected limits at 95% CL on the cross section of nonresonant Higgs boson pair production as a function of the Higgs boson self-coupling modifier $\kappa_{\lambda}= \lambda_{HHH}/\lambda^{\textrm{SM}}_{HHH}$. The expected constraints on $\kappa_{\lambda}$ are obtained with a background hypothesis excluding $pp \rightarrow HH$ production. The $\pm 1\sigma$ and $\pm 2\sigma$ variations about the expected limit due to statistical and systematic uncertainties are also shown. The theory prediction curve represents the scenario where all parameters and couplings are set to their SM values except for $\kappa_{\lambda}$. The uncertainty band of the theory prediction curve shows the cross-section uncertainty.
Observed and expected limits at 95% CL on the cross section of nonresonant Higgs boson pair production as a function of the Higgs boson self-coupling modifier $\kappa_{\lambda}= \lambda_{HHH}/\lambda^{\textrm{SM}}_{HHH}$. The expected constraints on $\kappa_{\lambda}$ are obtained with a background hypothesis excluding $pp \rightarrow HH$ production. The $\pm 1\sigma$ and $\pm 2\sigma$ variations about the expected limit due to statistical and systematic uncertainties are also shown. The theory prediction curve represents the scenario where all parameters and couplings are set to their SM values except for $\kappa_{\lambda}$. The uncertainty band of the theory prediction curve shows the cross-section uncertainty.
Values of the negative log-profile-likelihood ratio ($-2ln\Lambda$) as a function of $\kappa_{\lambda}$ evaluated for the combination of all the categories of the nonresonant search. The coupling of the Higgs boson to fermions and gauge bosons is set to SM values in the profile likelihood calculation. The Asimov data set is generated under the SM signal-plus-background hypothesis, $\kappa_{\lambda}$= 1. All systematic uncertainties, including the theoretical uncertainties in the di-Higgs boson production cross section, are included. The intersections of the solid curves and the horizontal dashed lines indicate the 1$\sigma$ and 2$\sigma$ confidence-level intervals.
Values of the negative log-profile-likelihood ratio ($-2ln\Lambda$) as a function of $\kappa_{\lambda}$ evaluated for the combination of all the categories of the nonresonant search. The coupling of the Higgs boson to fermions and gauge bosons is set to SM values in the profile likelihood calculation. The Asimov data set is generated under the SM signal-plus-background hypothesis, $\kappa_{\lambda}$= 1. All systematic uncertainties, including the theoretical uncertainties in the di-Higgs boson production cross section, are included. The intersections of the solid curves and the horizontal dashed lines indicate the 1$\sigma$ and 2$\sigma$ confidence-level intervals.
Values of the negative log-profile-likelihood ratio ($-2ln\Lambda$) as a function of $\kappa_{\lambda}$ evaluated for the combination of all the categories of the nonresonant search. The coupling of the Higgs boson to fermions and gauge bosons is set to SM values in the profile likelihood calculation. The Asimov data set is generated under the SM signal-plus-background hypothesis, $\kappa_{\lambda}$= 1. All systematic uncertainties, including the theoretical uncertainties in the di-Higgs boson production cross section, are included. The intersections of the solid curves and the horizontal dashed lines indicate the 1$\sigma$ and 2$\sigma$ confidence-level intervals.
Values of the negative log-profile-likelihood ratio ($-2ln\Lambda$) as a function of $\kappa_{\lambda}$ evaluated for the combination of all the categories of the nonresonant search. The coupling of the Higgs boson to fermions and gauge bosons is set to SM values in the profile likelihood calculation. The Asimov data set is generated under the SM signal-plus-background hypothesis, $\kappa_{\lambda}$= 1. All systematic uncertainties, including the theoretical uncertainties in the di-Higgs boson production cross section, are included. The intersections of the solid curves and the horizontal dashed lines indicate the 1$\sigma$ and 2$\sigma$ confidence-level intervals.
The number of events observed in the 120 < $m_{\gamma\gamma}$ < 130 GeV window in data, the number of events expected for scalar resonance signals of masses $m_{X}$ = 300 GeV and $m_{X}$ = 500 GeV assuming a total production cross section $\sigma(pp \rightarrow X \rightarrow HH)$ equal to the observed exclusion limits of Figure 15, and events expected for SM $HH$ and single Higgs boson production (estimated using MC simulation), as well as for continuum background. The values are obtained from a fit of the Asimov data set generated under the signal-plus-background hypothesis. The continuum background component of the Asimov data set is obtained from the fit of the data sideband. The uncertainties in the resonant signals and the SM $HH$ and single-Higgs-boson backgrounds include the systematic uncertainties discussed in Section 6. The uncertainty in the continuum background is given by the sum in quadrature of the statistical uncertainty from the fit to the data and the spurious-signal uncertainty.
The number of events observed in the 120 < $m_{\gamma\gamma}$ < 130 GeV window in data, the number of events expected for scalar resonance signals of masses $m_{X}$ = 300 GeV and $m_{X}$ = 500 GeV assuming a total production cross section $\sigma(pp \rightarrow X \rightarrow HH)$ equal to the observed exclusion limits of Figure 15, and events expected for SM $HH$ and single Higgs boson production (estimated using MC simulation), as well as for continuum background. The values are obtained from a fit of the Asimov data set generated under the signal-plus-background hypothesis. The continuum background component of the Asimov data set is obtained from the fit of the data sideband. The uncertainties in the resonant signals and the SM $HH$ and single-Higgs-boson backgrounds include the systematic uncertainties discussed in Section 6. The uncertainty in the continuum background is given by the sum in quadrature of the statistical uncertainty from the fit to the data and the spurious-signal uncertainty.
The number of events observed in the 120 < $m_{\gamma\gamma}$ < 130 GeV window in data, the number of events expected for scalar resonance signals of masses $m_{X}$ = 300 GeV and $m_{X}$ = 500 GeV assuming a total production cross section $\sigma(pp \rightarrow X \rightarrow HH)$ equal to the observed exclusion limits of Figure 15, and events expected for SM $HH$ and single Higgs boson production (estimated using MC simulation), as well as for continuum background. The values are obtained from a fit of the Asimov data set generated under the signal-plus-background hypothesis. The continuum background component of the Asimov data set is obtained from the fit of the data sideband. The uncertainties in the resonant signals and the SM $HH$ and single-Higgs-boson backgrounds include the systematic uncertainties discussed in Section 6. The uncertainty in the continuum background is given by the sum in quadrature of the statistical uncertainty from the fit to the data and the spurious-signal uncertainty.
The number of events observed in the 120 < $m_{\gamma\gamma}$ < 130 GeV window in data, the number of events expected for scalar resonance signals of masses $m_{X}$ = 300 GeV and $m_{X}$ = 500 GeV assuming a total production cross section $\sigma(pp \rightarrow X \rightarrow HH)$ equal to the observed exclusion limits of Figure 15, and events expected for SM $HH$ and single Higgs boson production (estimated using MC simulation), as well as for continuum background. The values are obtained from a fit of the Asimov data set generated under the signal-plus-background hypothesis. The continuum background component of the Asimov data set is obtained from the fit of the data sideband. The uncertainties in the resonant signals and the SM $HH$ and single-Higgs-boson backgrounds include the systematic uncertainties discussed in Section 6. The uncertainty in the continuum background is given by the sum in quadrature of the statistical uncertainty from the fit to the data and the spurious-signal uncertainty.
Observed and expected limits at 95% CL on the production cross section of a narrow-width scalar resonance $X$ as a function of the mass $m_{X}$ of the hypothetical scalar particle. The black solid line represents the observed upper limits. The dashed line represents the expected upper limits. The $\pm 1\sigma$ and $\pm 2\sigma$ variations about the expected limit due to statistical and systematic uncertainties are also shown.
Observed and expected limits at 95% CL on the production cross section of a narrow-width scalar resonance $X$ as a function of the mass $m_{X}$ of the hypothetical scalar particle. The black solid line represents the observed upper limits. The dashed line represents the expected upper limits. The $\pm 1\sigma$ and $\pm 2\sigma$ variations about the expected limit due to statistical and systematic uncertainties are also shown.
Observed and expected limits at 95% CL on the production cross section of a narrow-width scalar resonance $X$ as a function of the mass $m_{X}$ of the hypothetical scalar particle. The black solid line represents the observed upper limits. The dashed line represents the expected upper limits. The $\pm 1\sigma$ and $\pm 2\sigma$ variations about the expected limit due to statistical and systematic uncertainties are also shown.
Observed and expected limits at 95% CL on the production cross section of a narrow-width scalar resonance $X$ as a function of the mass $m_{X}$ of the hypothetical scalar particle. The black solid line represents the observed upper limits. The dashed line represents the expected upper limits. The $\pm 1\sigma$ and $\pm 2\sigma$ variations about the expected limit due to statistical and systematic uncertainties are also shown.
Breakdown of the dominant systematic uncertainties. The impact of the uncertainties is defined according to the statistical analysis described in Section 7. It corresponds to the relative variation of the expected upper limit on the cross section when re-evaluating the profile likelihood ratio after fixing the nuisance parameter in question to its best-fit value, while all remaining nuisance parameters remain free to float. The impact is shown in %. Only systematic uncertainties with an impact of at least 0.2% are shown. Uncertainties of the "Norm. + Shape" type affect both the normalization and the parameters of the functional form. The rest of the uncertainties affect only the yields.
Breakdown of the dominant systematic uncertainties. The impact of the uncertainties is defined according to the statistical analysis described in Section 7. It corresponds to the relative variation of the expected upper limit on the cross section when re-evaluating the profile likelihood ratio after fixing the nuisance parameter in question to its best-fit value, while all remaining nuisance parameters remain free to float. The impact is shown in %. Only systematic uncertainties with an impact of at least 0.2% are shown. Uncertainties of the "Norm. + Shape" type affect both the normalization and the parameters of the functional form. The rest of the uncertainties affect only the yields.
Breakdown of the dominant systematic uncertainties. The impact of the uncertainties is defined according to the statistical analysis described in Section 7. It corresponds to the relative variation of the expected upper limit on the cross section when re-evaluating the profile likelihood ratio after fixing the nuisance parameter in question to its best-fit value, while all remaining nuisance parameters remain free to float. The impact is shown in %. Only systematic uncertainties with an impact of at least 0.2% are shown. Uncertainties of the "Norm. + Shape" type affect both the normalization and the parameters of the functional form. The rest of the uncertainties affect only the yields.
Breakdown of the dominant systematic uncertainties. The impact of the uncertainties is defined according to the statistical analysis described in Section 7. It corresponds to the relative variation of the expected upper limit on the cross section when re-evaluating the profile likelihood ratio after fixing the nuisance parameter in question to its best-fit value, while all remaining nuisance parameters remain free to float. The impact is shown in %. Only systematic uncertainties with an impact of at least 0.2% are shown. Uncertainties of the "Norm. + Shape" type affect both the normalization and the parameters of the functional form. The rest of the uncertainties affect only the yields.
Cutflow for nonresonant di-Higgs ggF signal sample, yields are normalized to 139 $fb^{-1}$.
Cutflow for nonresonant di-Higgs ggF signal sample, yields are normalized to 139 $fb^{-1}$.
Cutflow for nonresonant di-Higgs ggF signal sample, yields are normalized to 139 $fb^{-1}$.
Cutflow for nonresonant di-Higgs ggF signal sample, yields are normalized to 139 $fb^{-1}$.
Cutflow for resonant signal sample, with $m_{X}$ = 300 GeV, yields are normalized to 139 $fb^{-1}$.
Cutflow for resonant signal sample, with $m_{X}$ = 300 GeV, yields are normalized to 139 $fb^{-1}$.
Cutflow for resonant signal sample, with $m_{X}$ = 300 GeV, yields are normalized to 139 $fb^{-1}$.
Cutflow for resonant signal sample, with $m_{X}$ = 300 GeV, yields are normalized to 139 $fb^{-1}$.
Cutflow for resonant signal sample, with $m_{X}$ = 500 GeV, yields are normalized to 139 $fb^{-1}$.
Cutflow for resonant signal sample, with $m_{X}$ = 500 GeV, yields are normalized to 139 $fb^{-1}$.
Cutflow for resonant signal sample, with $m_{X}$ = 500 GeV, yields are normalized to 139 $fb^{-1}$.
Cutflow for resonant signal sample, with $m_{X}$ = 500 GeV, yields are normalized to 139 $fb^{-1}$.
Comparison of $m_{b\bar{b}}$ distributions when applying the specific b-jet energy calibration and the nominal jet energy calibration. The distributions are fitted using a Bukin function, and the values of the peak position, resolution and the relative improvement are reported in the legend.
Comparison of $m_{b\bar{b}}$ distributions when applying the specific b-jet energy calibration and the nominal jet energy calibration. The distributions are fitted using a Bukin function, and the values of the peak position, resolution and the relative improvement are reported in the legend.
Comparison of $m_{b\bar{b}}$ distributions when applying the specific b-jet energy calibration and the nominal jet energy calibration. The distributions are fitted using a Bukin function, and the values of the peak position, resolution and the relative improvement are reported in the legend.
Comparison of $m_{b\bar{b}}$ distributions when applying the specific b-jet energy calibration and the nominal jet energy calibration. The distributions are fitted using a Bukin function, and the values of the peak position, resolution and the relative improvement are reported in the legend.
Fit results of $m_{b\bar{b}}$ distributions when applying the specific b-jet energy calibration and the nominal jet energy calibration. The distributions are fitted using a Bukin function, and the values of the peak position, resolution and the relative improvement are reported in the legend.
Fit results of $m_{b\bar{b}}$ distributions when applying the specific b-jet energy calibration and the nominal jet energy calibration. The distributions are fitted using a Bukin function, and the values of the peak position, resolution and the relative improvement are reported in the legend.
Fit results of $m_{b\bar{b}}$ distributions when applying the specific b-jet energy calibration and the nominal jet energy calibration. The distributions are fitted using a Bukin function, and the values of the peak position, resolution and the relative improvement are reported in the legend.
Fit results of $m_{b\bar{b}}$ distributions when applying the specific b-jet energy calibration and the nominal jet energy calibration. The distributions are fitted using a Bukin function, and the values of the peak position, resolution and the relative improvement are reported in the legend.
The relative amount (purity) of expected events from SM $HH$ and single Higgs boson production processes for each of the four categories of the nonresonant search. The Higgs boson pair production with $k_{\lambda} = 1$ is considered as signal in (a), while the case with $k_{\lambda} = 10$ is considered as signal in (b).
The relative amount (purity) of expected events from SM $HH$ and single Higgs boson production processes for each of the four categories of the nonresonant search. The Higgs boson pair production with $k_{\lambda} = 1$ is considered as signal in (a), while the case with $k_{\lambda} = 10$ is considered as signal in (b).
The relative amount (purity) of expected events from SM $HH$ and single Higgs boson production processes for each of the four categories of the nonresonant search. The Higgs boson pair production with $k_{\lambda} = 1$ is considered as signal in (a), while the case with $k_{\lambda} = 10$ is considered as signal in (b).
The relative amount (purity) of expected events from SM $HH$ and single Higgs boson production processes for each of the four categories of the nonresonant search. The Higgs boson pair production with $k_{\lambda} = 1$ is considered as signal in (a), while the case with $k_{\lambda} = 10$ is considered as signal in (b).
The expected significance in each of the four categories of the nonresonant search. The Higgs boson pair production with $k_{\lambda} = 1$ is considered as signal in (a), while the case with $k_{\lambda} = 10$ is considered as signal in (b). The single Higgs boson processes and the di-photon continuum spectrum are considered as background.
The expected significance in each of the four categories of the nonresonant search. The Higgs boson pair production with $k_{\lambda} = 1$ is considered as signal in (a), while the case with $k_{\lambda} = 10$ is considered as signal in (b). The single Higgs boson processes and the di-photon continuum spectrum are considered as background.
The expected significance in each of the four categories of the nonresonant search. The Higgs boson pair production with $k_{\lambda} = 1$ is considered as signal in (a), while the case with $k_{\lambda} = 10$ is considered as signal in (b). The single Higgs boson processes and the di-photon continuum spectrum are considered as background.
The expected significance in each of the four categories of the nonresonant search. The Higgs boson pair production with $k_{\lambda} = 1$ is considered as signal in (a), while the case with $k_{\lambda} = 10$ is considered as signal in (b). The single Higgs boson processes and the di-photon continuum spectrum are considered as background.
Spurious signal result for the exponential pdf for the various ggF nonresonant di-Higgs categories. In each category, the spurious signal value ($n_{sp}$) and its ratio to the expected statistical error ($Z_{spur}$) from data are shown.
Spurious signal result for the exponential pdf for the various ggF nonresonant di-Higgs categories. In each category, the spurious signal value ($n_{sp}$) and its ratio to the expected statistical error ($Z_{spur}$) from data are shown.
Spurious signal result for the exponential pdf for the various ggF nonresonant di-Higgs categories. In each category, the spurious signal value ($n_{sp}$) and its ratio to the expected statistical error ($Z_{spur}$) from data are shown.
Spurious signal result for the exponential pdf for the various ggF nonresonant di-Higgs categories. In each category, the spurious signal value ($n_{sp}$) and its ratio to the expected statistical error ($Z_{spur}$) from data are shown.
Spurious signal result for the exponential pdf as function of the resonant di-Higgs signal mass. The spurious signal value and its ratio to the expected statistical error from data are shown.
Spurious signal result for the exponential pdf as function of the resonant di-Higgs signal mass. The spurious signal value and its ratio to the expected statistical error from data are shown.
Spurious signal result for the exponential pdf as function of the resonant di-Higgs signal mass. The spurious signal value and its ratio to the expected statistical error from data are shown.
Spurious signal result for the exponential pdf as function of the resonant di-Higgs signal mass. The spurious signal value and its ratio to the expected statistical error from data are shown.
Distributions of the signal efficiency as a function of $\kappa_{\lambda}$, for the di-Higgs boson ggF nonresonant production mode. The range of $\kappa_{\lambda}$ in the table is from -10 to 10.
Distributions of the signal efficiency as a function of $\kappa_{\lambda}$, for the di-Higgs boson ggF nonresonant production mode. The range of $\kappa_{\lambda}$ in the table is from -10 to 10.
Distributions of the signal efficiency as a function of $\kappa_{\lambda}$, for the di-Higgs boson ggF nonresonant production mode. The range of $\kappa_{\lambda}$ in the table is from -10 to 10.
Distributions of the signal efficiency as a function of $\kappa_{\lambda}$, for the di-Higgs boson ggF nonresonant production mode. The range of $\kappa_{\lambda}$ in the table is from -10 to 10.
Distributions of the signal efficiency as a function of $\kappa_{\lambda}$, for the di-Higgs boson VBF nonresonant production mode. The range of $\kappa_{\lambda}$ in the table is from -10 to 10.
Distributions of the signal efficiency as a function of $\kappa_{\lambda}$, for the di-Higgs boson VBF nonresonant production mode. The range of $\kappa_{\lambda}$ in the table is from -10 to 10.
Distributions of the signal efficiency as a function of $\kappa_{\lambda}$, for the di-Higgs boson VBF nonresonant production mode. The range of $\kappa_{\lambda}$ in the table is from -10 to 10.
Distributions of the signal efficiency as a function of $\kappa_{\lambda}$, for the di-Higgs boson VBF nonresonant production mode. The range of $\kappa_{\lambda}$ in the table is from -10 to 10.
Values of the negative log-profile-likelihood ($-2ln\Lambda$) as a function of $\kappa_{\lambda}$ evaluated for the combination of all the categories of the nonresonant search. The coupling of the Higgs boson to fermions and gauge bosons is set to SM values in the profile likelihood calculation. The Asimov data set is generated under the SM signal-plus-background hypothesis, $\kappa_{\lambda}$= 1. All systematic uncertainties, including the theoretical uncertainties on the di-Higgs boson production cross section, are included. The intersections of the solid curves and the horizontal dashed lines indicate the 1$\sigma$ and 2$\sigma$ confidence level intervals. The best fit value corresponds to $\kappa_{\lambda}$ = $2.8^{+2.0}_{-2.2}(^{+3.8}_{-4.3})$ for the 1$\sigma$(2$\sigma$) confidence interval. The expected value corresponds to $\kappa_{\lambda}$ = $1.0^{+5.5}_{-2.4}(^{+7.3}_{-4.2})$ for the 1$\sigma$(2$\sigma$) confidence interval. The dashed curves represent values of the negative log-profile-likelihood where the Higgs boson branching fractions and the cross section of the production modes are varied as a function of $\kappa_{\lambda}$. In this case,the best fit value corresponds to $\kappa_{\lambda}$ = $2.7^{+2.0}_{-2.2}(^{+3.8}_{-4.3})$ and the expected value corresponds to $\kappa_{\lambda}$ = $1.0^{+5.4}_{-2.5}(^{+7.3}_{-4.3})$ for the 1$\sigma$(2$\sigma$) confidence interval.
Values of the negative log-profile-likelihood ($-2ln\Lambda$) as a function of $\kappa_{\lambda}$ evaluated for the combination of all the categories of the nonresonant search. The coupling of the Higgs boson to fermions and gauge bosons is set to SM values in the profile likelihood calculation. The Asimov data set is generated under the SM signal-plus-background hypothesis, $\kappa_{\lambda}$= 1. All systematic uncertainties, including the theoretical uncertainties on the di-Higgs boson production cross section, are included. The intersections of the solid curves and the horizontal dashed lines indicate the 1$\sigma$ and 2$\sigma$ confidence level intervals. The best fit value corresponds to $\kappa_{\lambda}$ = $2.8^{+2.0}_{-2.2}(^{+3.8}_{-4.3})$ for the 1$\sigma$(2$\sigma$) confidence interval. The expected value corresponds to $\kappa_{\lambda}$ = $1.0^{+5.5}_{-2.4}(^{+7.3}_{-4.2})$ for the 1$\sigma$(2$\sigma$) confidence interval. The dashed curves represent values of the negative log-profile-likelihood where the Higgs boson branching fractions and the cross section of the production modes are varied as a function of $\kappa_{\lambda}$. In this case,the best fit value corresponds to $\kappa_{\lambda}$ = $2.7^{+2.0}_{-2.2}(^{+3.8}_{-4.3})$ and the expected value corresponds to $\kappa_{\lambda}$ = $1.0^{+5.4}_{-2.5}(^{+7.3}_{-4.3})$ for the 1$\sigma$(2$\sigma$) confidence interval.
Values of the negative log-profile-likelihood ($-2ln\Lambda$) as a function of $\kappa_{\lambda}$ evaluated for the combination of all the categories of the nonresonant search. The coupling of the Higgs boson to fermions and gauge bosons is set to SM values in the profile likelihood calculation. The Asimov data set is generated under the SM signal-plus-background hypothesis, $\kappa_{\lambda}$= 1. All systematic uncertainties, including the theoretical uncertainties on the di-Higgs boson production cross section, are included. The intersections of the solid curves and the horizontal dashed lines indicate the 1$\sigma$ and 2$\sigma$ confidence level intervals. The best fit value corresponds to $\kappa_{\lambda}$ = $2.8^{+2.0}_{-2.2}(^{+3.8}_{-4.3})$ for the 1$\sigma$(2$\sigma$) confidence interval. The expected value corresponds to $\kappa_{\lambda}$ = $1.0^{+5.5}_{-2.4}(^{+7.3}_{-4.2})$ for the 1$\sigma$(2$\sigma$) confidence interval. The dashed curves represent values of the negative log-profile-likelihood where the Higgs boson branching fractions and the cross section of the production modes are varied as a function of $\kappa_{\lambda}$. In this case,the best fit value corresponds to $\kappa_{\lambda}$ = $2.7^{+2.0}_{-2.2}(^{+3.8}_{-4.3})$ and the expected value corresponds to $\kappa_{\lambda}$ = $1.0^{+5.4}_{-2.5}(^{+7.3}_{-4.3})$ for the 1$\sigma$(2$\sigma$) confidence interval.
Values of the negative log-profile-likelihood ($-2ln\Lambda$) as a function of $\kappa_{\lambda}$ evaluated for the combination of all the categories of the nonresonant search. The coupling of the Higgs boson to fermions and gauge bosons is set to SM values in the profile likelihood calculation. The Asimov data set is generated under the SM signal-plus-background hypothesis, $\kappa_{\lambda}$= 1. All systematic uncertainties, including the theoretical uncertainties on the di-Higgs boson production cross section, are included. The intersections of the solid curves and the horizontal dashed lines indicate the 1$\sigma$ and 2$\sigma$ confidence level intervals. The best fit value corresponds to $\kappa_{\lambda}$ = $2.8^{+2.0}_{-2.2}(^{+3.8}_{-4.3})$ for the 1$\sigma$(2$\sigma$) confidence interval. The expected value corresponds to $\kappa_{\lambda}$ = $1.0^{+5.5}_{-2.4}(^{+7.3}_{-4.2})$ for the 1$\sigma$(2$\sigma$) confidence interval. The dashed curves represent values of the negative log-profile-likelihood where the Higgs boson branching fractions and the cross section of the production modes are varied as a function of $\kappa_{\lambda}$. In this case,the best fit value corresponds to $\kappa_{\lambda}$ = $2.7^{+2.0}_{-2.2}(^{+3.8}_{-4.3})$ and the expected value corresponds to $\kappa_{\lambda}$ = $1.0^{+5.4}_{-2.5}(^{+7.3}_{-4.3})$ for the 1$\sigma$(2$\sigma$) confidence interval.
Minimum BDT value of the events passing the selection criteria of the resonant search. The combined BDT score is formed using as coefficients $C_{1}$ = 0.65 and $C_{2}$ = 1 − $C_{1}$. The selection efficiency for the resonant $X \rightarrow HH$ signal is also shown.
Minimum BDT value of the events passing the selection criteria of the resonant search. The combined BDT score is formed using as coefficients $C_{1}$ = 0.65 and $C_{2}$ = 1 − $C_{1}$. The selection efficiency for the resonant $X \rightarrow HH$ signal is also shown.
Minimum BDT value of the events passing the selection criteria of the resonant search. The combined BDT score is formed using as coefficients $C_{1}$ = 0.65 and $C_{2}$ = 1 − $C_{1}$. The selection efficiency for the resonant $X \rightarrow HH$ signal is also shown.
Minimum BDT value of the events passing the selection criteria of the resonant search. The combined BDT score is formed using as coefficients $C_{1}$ = 0.65 and $C_{2}$ = 1 − $C_{1}$. The selection efficiency for the resonant $X \rightarrow HH$ signal is also shown.
A search for chargino$-$neutralino pair production in three-lepton final states with missing transverse momentum is presented. The study is based on a dataset of $\sqrt{s} = 13$ TeV $pp$ collisions recorded with the ATLAS detector at the LHC, corresponding to an integrated luminosity of 139 fb$^{-1}$. No significant excess relative to the Standard Model predictions is found in data. The results are interpreted in simplified models of supersymmetry, and statistically combined with results from a previous ATLAS search for compressed spectra in two-lepton final states. Various scenarios for the production and decay of charginos ($\tilde\chi^\pm_1$) and neutralinos ($\tilde\chi^0_2$) are considered. For pure higgsino $\tilde\chi^\pm_1\tilde\chi^0_2$ pair-production scenarios, exclusion limits at 95% confidence level are set on $\tilde\chi^0_2$ masses up to 210 GeV. Limits are also set for pure wino $\tilde\chi^\pm_1\tilde\chi^0_2$ pair production, on $\tilde\chi^0_2$ masses up to 640 GeV for decays via on-shell $W$ and $Z$ bosons, up to 300 GeV for decays via off-shell $W$ and $Z$ bosons, and up to 190 GeV for decays via $W$ and Standard Model Higgs bosons.
Comparison of the observed data and expected SM background yields in the CRs (pre-fit) and VRs (post-fit) of the onshell $W\!Z$ and $W\!h$ selections. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. The hatched band indicates the combined theoretical, experimental, and MC statistical uncertainties. The bottom panel shows the relative difference between the observed data and expected yields for the CRs and the significance of the difference for the VRs, calculated with the profile likelihood method from [169], adding a minus sign if the yield is below the prediction.
Comparison of the observed data and expected SM background yields in the CRs (pre-fit) and VRs (post-fit) of the onshell $W\!Z$ and $W\!h$ selections. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. The hatched band indicates the combined theoretical, experimental, and MC statistical uncertainties. The bottom panel shows the relative difference between the observed data and expected yields for the CRs and the significance of the difference for the VRs, calculated with the profile likelihood method from [169], adding a minus sign if the yield is below the prediction.
Comparison of the observed data and expected SM background yields in the CRs and VRs of the offshell $W\!Z$ selection. The SM prediction is taken from the background-only fit. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. The hatched band indicates the combined theoretical, experimental, and MC statistical uncertainties. The bottom panel shows the significance of the difference between the observed and expected yields, calculated with the profile likelihood method from [169], adding a minus sign if the yield is below the prediction.
Comparison of the observed data and expected SM background yields in the CRs and VRs of the offshell $W\!Z$ selection. The SM prediction is taken from the background-only fit. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. The hatched band indicates the combined theoretical, experimental, and MC statistical uncertainties. The bottom panel shows the significance of the difference between the observed and expected yields, calculated with the profile likelihood method from [169], adding a minus sign if the yield is below the prediction.
Observed and expected yields after the background-only fit in the SRs for the onshell $W\!Z$ selection. The normalization factors of the $W\!Z$ sample are extracted separately for the 0j, low-H<sub>T</sub> and high-H<sub>T</sub> regions, and are treated separately in the combined fit. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. Combined statistical and systematic uncertainties are presented.
Observed and expected yields after the background-only fit in the SRs for the onshell $W\!Z$ selection. The normalization factors of the $W\!Z$ sample are extracted separately for the 0j, low-H<sub>T</sub> and high-H<sub>T</sub> regions, and are treated separately in the combined fit. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. Combined statistical and systematic uncertainties are presented.
Observed and expected yields after the background-only fit in the SRs for the $W\!h$ selection. The normalization factors of the $W\!Z$ sample are extracted separately for the 0j, low-H<sub>T</sub> and high-H<sub>T</sub> regions, and are treated separately in the combined fit. The "Others" category contains the single-top, WW, tt̄+X and rare top processes. Combined statistical and systematic uncertainties are presented.
Observed and expected yields after the background-only fit in the SRs for the $W\!h$ selection. The normalization factors of the $W\!Z$ sample are extracted separately for the 0j, low-H<sub>T</sub> and high-H<sub>T</sub> regions, and are treated separately in the combined fit. The "Others" category contains the single-top, WW, tt̄+X and rare top processes. Combined statistical and systematic uncertainties are presented.
Comparison of the observed data and expected SM background yields in the SRs of the onshell $W\!Z$ selection. The SM prediction is taken from the background-only fit. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. The hatched band indicates the combined theoretical, experimental, and MC statistical uncertainties. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the significance of the difference between the observed and expected yields, calculated with the profile likelihood method from [169], adding a minus sign if the yield is below the prediction.
Comparison of the observed data and expected SM background yields in the SRs of the onshell $W\!Z$ selection. The SM prediction is taken from the background-only fit. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. The hatched band indicates the combined theoretical, experimental, and MC statistical uncertainties. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the significance of the difference between the observed and expected yields, calculated with the profile likelihood method from [169], adding a minus sign if the yield is below the prediction.
Comparison of the observed data and expected SM background yields in the SRs of the $W\!h$ selection. The SM prediction is taken from the background-only fit. The "Others" category contains the single-top, WW, tt̄+X and rare top processes. The hatched band indicates the combined theoretical, experimental, and MC statistical uncertainties. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!h$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the significance of the difference between the observed and expected yields, calculated with the profile likelihood method from [169], adding a minus sign if the yield is below the prediction.
Comparison of the observed data and expected SM background yields in the SRs of the $W\!h$ selection. The SM prediction is taken from the background-only fit. The "Others" category contains the single-top, WW, tt̄+X and rare top processes. The hatched band indicates the combined theoretical, experimental, and MC statistical uncertainties. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!h$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the significance of the difference between the observed and expected yields, calculated with the profile likelihood method from [169], adding a minus sign if the yield is below the prediction.
Observed and expected yields after the background-only fit in SR<sup>offWZ</sup><sub>lowETmiss</sub>. The normalization factors of the $W\!Z$ sample extracted separately for 0j and nj, and are treated separately in the combined fit. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. Combined statistical and systematic uncertainties are presented.
Observed and expected yields after the background-only fit in SR<sup>offWZ</sup><sub>lowETmiss</sub>. The normalization factors of the $W\!Z$ sample extracted separately for 0j and nj, and are treated separately in the combined fit. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. Combined statistical and systematic uncertainties are presented.
Observed and expected yields after the background-only fit in SR<sup>offWZ</sup><sub>highETmiss</sub>. The normalization factors of the $W\!Z$ sample extracted separately for 0j and nj, and are treated separately in the combined fit. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. Combined statistical and systematic uncertainties are presented.
Observed and expected yields after the background-only fit in SR<sup>offWZ</sup><sub>highETmiss</sub>. The normalization factors of the $W\!Z$ sample extracted separately for 0j and nj, and are treated separately in the combined fit. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. Combined statistical and systematic uncertainties are presented.
Comparison of the observed data and expected SM background yields in the SRs of the offshell $W\!Z$ selection. The SM prediction is taken from the background-only fit. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. The hatched band indicates the combined theoretical, experimental, and MC statistical uncertainties. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W^{*}\!Z^{*}$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the significance of the difference between the observed and expected yields, calculated with the profile likelihood method from [169], adding a minus sign if the yield is below the prediction.
Comparison of the observed data and expected SM background yields in the SRs of the offshell $W\!Z$ selection. The SM prediction is taken from the background-only fit. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. The hatched band indicates the combined theoretical, experimental, and MC statistical uncertainties. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W^{*}\!Z^{*}$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the significance of the difference between the observed and expected yields, calculated with the profile likelihood method from [169], adding a minus sign if the yield is below the prediction.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the onshell $W\!Z$ and $W\!h$ selections. The figure shows (a) the ΔR<sub>OS,near</sub> distribution in SR<sup>Wh</sup><sub>DF</sub>-1, (b) the 3rd leading lepton p<sub>T</sub> in SR<sup>Wh</sup><sub>DF</sub>-2, and the (c) E<sub>T</sub><sup>miss</sup> and (d) m<sub>T</sub> distributions in SR<sup>WZ</sup><sub>0j</sub> (with all SR-i bins of SR<sup>WZ</sup><sub>0j</sub> summed up). The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes, except in the top panels, where triboson and Higgs production contributions are shown separately, and tt̄+X is merged into Others. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$/$W\!h$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the onshell $W\!Z$ and $W\!h$ selections. The figure shows (a) the ΔR<sub>OS,near</sub> distribution in SR<sup>Wh</sup><sub>DF</sub>-1, (b) the 3rd leading lepton p<sub>T</sub> in SR<sup>Wh</sup><sub>DF</sub>-2, and the (c) E<sub>T</sub><sup>miss</sup> and (d) m<sub>T</sub> distributions in SR<sup>WZ</sup><sub>0j</sub> (with all SR-i bins of SR<sup>WZ</sup><sub>0j</sub> summed up). The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes, except in the top panels, where triboson and Higgs production contributions are shown separately, and tt̄+X is merged into Others. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$/$W\!h$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the onshell $W\!Z$ and $W\!h$ selections. The figure shows (a) the ΔR<sub>OS,near</sub> distribution in SR<sup>Wh</sup><sub>DF</sub>-1, (b) the 3rd leading lepton p<sub>T</sub> in SR<sup>Wh</sup><sub>DF</sub>-2, and the (c) E<sub>T</sub><sup>miss</sup> and (d) m<sub>T</sub> distributions in SR<sup>WZ</sup><sub>0j</sub> (with all SR-i bins of SR<sup>WZ</sup><sub>0j</sub> summed up). The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes, except in the top panels, where triboson and Higgs production contributions are shown separately, and tt̄+X is merged into Others. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$/$W\!h$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the onshell $W\!Z$ and $W\!h$ selections. The figure shows (a) the ΔR<sub>OS,near</sub> distribution in SR<sup>Wh</sup><sub>DF</sub>-1, (b) the 3rd leading lepton p<sub>T</sub> in SR<sup>Wh</sup><sub>DF</sub>-2, and the (c) E<sub>T</sub><sup>miss</sup> and (d) m<sub>T</sub> distributions in SR<sup>WZ</sup><sub>0j</sub> (with all SR-i bins of SR<sup>WZ</sup><sub>0j</sub> summed up). The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes, except in the top panels, where triboson and Higgs production contributions are shown separately, and tt̄+X is merged into Others. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$/$W\!h$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the onshell $W\!Z$ and $W\!h$ selections. The figure shows (a) the ΔR<sub>OS,near</sub> distribution in SR<sup>Wh</sup><sub>DF</sub>-1, (b) the 3rd leading lepton p<sub>T</sub> in SR<sup>Wh</sup><sub>DF</sub>-2, and the (c) E<sub>T</sub><sup>miss</sup> and (d) m<sub>T</sub> distributions in SR<sup>WZ</sup><sub>0j</sub> (with all SR-i bins of SR<sup>WZ</sup><sub>0j</sub> summed up). The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes, except in the top panels, where triboson and Higgs production contributions are shown separately, and tt̄+X is merged into Others. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$/$W\!h$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the onshell $W\!Z$ and $W\!h$ selections. The figure shows (a) the ΔR<sub>OS,near</sub> distribution in SR<sup>Wh</sup><sub>DF</sub>-1, (b) the 3rd leading lepton p<sub>T</sub> in SR<sup>Wh</sup><sub>DF</sub>-2, and the (c) E<sub>T</sub><sup>miss</sup> and (d) m<sub>T</sub> distributions in SR<sup>WZ</sup><sub>0j</sub> (with all SR-i bins of SR<sup>WZ</sup><sub>0j</sub> summed up). The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes, except in the top panels, where triboson and Higgs production contributions are shown separately, and tt̄+X is merged into Others. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$/$W\!h$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the onshell $W\!Z$ and $W\!h$ selections. The figure shows (a) the ΔR<sub>OS,near</sub> distribution in SR<sup>Wh</sup><sub>DF</sub>-1, (b) the 3rd leading lepton p<sub>T</sub> in SR<sup>Wh</sup><sub>DF</sub>-2, and the (c) E<sub>T</sub><sup>miss</sup> and (d) m<sub>T</sub> distributions in SR<sup>WZ</sup><sub>0j</sub> (with all SR-i bins of SR<sup>WZ</sup><sub>0j</sub> summed up). The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes, except in the top panels, where triboson and Higgs production contributions are shown separately, and tt̄+X is merged into Others. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$/$W\!h$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the onshell $W\!Z$ and $W\!h$ selections. The figure shows (a) the ΔR<sub>OS,near</sub> distribution in SR<sup>Wh</sup><sub>DF</sub>-1, (b) the 3rd leading lepton p<sub>T</sub> in SR<sup>Wh</sup><sub>DF</sub>-2, and the (c) E<sub>T</sub><sup>miss</sup> and (d) m<sub>T</sub> distributions in SR<sup>WZ</sup><sub>0j</sub> (with all SR-i bins of SR<sup>WZ</sup><sub>0j</sub> summed up). The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes, except in the top panels, where triboson and Higgs production contributions are shown separately, and tt̄+X is merged into Others. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$/$W\!h$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the offshell $W\!Z$ selection. The figure shows the m<sub>T</sub><sup>m<sub>ll</sub>min</sup> distribution in (a) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj and (c) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and the |p<sub>T</sub><sup>lep</sup>|/E<sub>T</sub><sup>miss</sup> distribution in (d) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj. The contributing m<sub>ll</sub><sup>min</sup> mass bins within each SR<sup>offWZ</sup> category are summed together. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the offshell $W\!Z$ selection. The figure shows the m<sub>T</sub><sup>m<sub>ll</sub>min</sup> distribution in (a) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj and (c) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and the |p<sub>T</sub><sup>lep</sup>|/E<sub>T</sub><sup>miss</sup> distribution in (d) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj. The contributing m<sub>ll</sub><sup>min</sup> mass bins within each SR<sup>offWZ</sup> category are summed together. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the offshell $W\!Z$ selection. The figure shows the m<sub>T</sub><sup>m<sub>ll</sub>min</sup> distribution in (a) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj and (c) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and the |p<sub>T</sub><sup>lep</sup>|/E<sub>T</sub><sup>miss</sup> distribution in (d) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj. The contributing m<sub>ll</sub><sup>min</sup> mass bins within each SR<sup>offWZ</sup> category are summed together. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the offshell $W\!Z$ selection. The figure shows the m<sub>T</sub><sup>m<sub>ll</sub>min</sup> distribution in (a) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj and (c) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and the |p<sub>T</sub><sup>lep</sup>|/E<sub>T</sub><sup>miss</sup> distribution in (d) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj. The contributing m<sub>ll</sub><sup>min</sup> mass bins within each SR<sup>offWZ</sup> category are summed together. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the offshell $W\!Z$ selection. The figure shows the m<sub>T</sub><sup>m<sub>ll</sub>min</sup> distribution in (a) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj and (c) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and the |p<sub>T</sub><sup>lep</sup>|/E<sub>T</sub><sup>miss</sup> distribution in (d) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj. The contributing m<sub>ll</sub><sup>min</sup> mass bins within each SR<sup>offWZ</sup> category are summed together. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the offshell $W\!Z$ selection. The figure shows the m<sub>T</sub><sup>m<sub>ll</sub>min</sup> distribution in (a) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj and (c) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and the |p<sub>T</sub><sup>lep</sup>|/E<sub>T</sub><sup>miss</sup> distribution in (d) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj. The contributing m<sub>ll</sub><sup>min</sup> mass bins within each SR<sup>offWZ</sup> category are summed together. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the offshell $W\!Z$ selection. The figure shows the m<sub>T</sub><sup>m<sub>ll</sub>min</sup> distribution in (a) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj and (c) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and the |p<sub>T</sub><sup>lep</sup>|/E<sub>T</sub><sup>miss</sup> distribution in (d) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj. The contributing m<sub>ll</sub><sup>min</sup> mass bins within each SR<sup>offWZ</sup> category are summed together. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the offshell $W\!Z$ selection. The figure shows the m<sub>T</sub><sup>m<sub>ll</sub>min</sup> distribution in (a) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj and (c) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and the |p<sub>T</sub><sup>lep</sup>|/E<sub>T</sub><sup>miss</sup> distribution in (d) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj. The contributing m<sub>ll</sub><sup>min</sup> mass bins within each SR<sup>offWZ</sup> category are summed together. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Observed (N<sub>obs</sub>) yields after the discovery-fit and expected (N<sub>exp</sub>) after the background-only fit, for the inclusive SRs of the onshell $W\!Z$ and $W\!h$ selections. The third and fourth column list the 95 CL upper limits on the visible cross-section (σ<sub>vis</sub><sup>95</sup>) and on the number of signal events (S<sub>obs</sub><sup>95</sup>). The fifth column (S<sub>exp</sub><sup>95</sup>) shows the 95 CL upper limit on the number of signal events, given the expected number (and ± 1σ excursions on the expectation) of background events. The last two columns indicate the CLb value, i.e. the confidence level observed for the background-only hypothesis, and the discovery p-value (p(s = 0)). If the observed yield is below the expected yield, the p-value is capped at 0.5.
Observed (N<sub>obs</sub>) yields after the discovery-fit and expected (N<sub>exp</sub>) after the background-only fit, for the inclusive SRs of the onshell $W\!Z$ and $W\!h$ selections. The third and fourth column list the 95 CL upper limits on the visible cross-section (σ<sub>vis</sub><sup>95</sup>) and on the number of signal events (S<sub>obs</sub><sup>95</sup>). The fifth column (S<sub>exp</sub><sup>95</sup>) shows the 95 CL upper limit on the number of signal events, given the expected number (and ± 1σ excursions on the expectation) of background events. The last two columns indicate the CLb value, i.e. the confidence level observed for the background-only hypothesis, and the discovery p-value (p(s = 0)). If the observed yield is below the expected yield, the p-value is capped at 0.5.
Observed (N<sub>obs</sub>) yields after the discovery-fit and expected (N<sub>exp</sub>) after the background-only fit, for the inclusive SRs of the offshell $W\!Z$ selection. The third and fourth column list the 95 CL upper limits on the visible cross section (σ<sub>vis</sub><sup>95</sup>) and on the number of signal events (S<sub>obs</sub><sup>95</sup>). The fifth column (S<sub>exp</sub><sup>95</sup>) shows the 95 CL upper limit on the number of signal events, given the expected number (and ± 1σ excursions on the expectation) of background events. The last two columns indicate the CLb value, i.e. the confidence level observed for the background-only hypothesis, and the discovery p-value (p(s = 0)). If the observed yield is below the expected yield, the p-value is capped at 0.5.
Observed (N<sub>obs</sub>) yields after the discovery-fit and expected (N<sub>exp</sub>) after the background-only fit, for the inclusive SRs of the offshell $W\!Z$ selection. The third and fourth column list the 95 CL upper limits on the visible cross section (σ<sub>vis</sub><sup>95</sup>) and on the number of signal events (S<sub>obs</sub><sup>95</sup>). The fifth column (S<sub>exp</sub><sup>95</sup>) shows the 95 CL upper limit on the number of signal events, given the expected number (and ± 1σ excursions on the expectation) of background events. The last two columns indicate the CLb value, i.e. the confidence level observed for the background-only hypothesis, and the discovery p-value (p(s = 0)). If the observed yield is below the expected yield, the p-value is capped at 0.5.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!h$med in the wino/bino (+) scenario, calculated using the $W\!h$ SRs and projected onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>{exp}</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties.
Exclusion limits obtained for the $W\!h$med in the wino/bino (+) scenario, calculated using the $W\!h$ SRs and projected onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>{exp}</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties.
Exclusion limits obtained for the $W\!h$med in the wino/bino (+) scenario, calculated using the $W\!h$ SRs and projected onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>{exp}</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties.
Exclusion limits obtained for the $W\!h$med in the wino/bino (+) scenario, calculated using the $W\!h$ SRs and projected onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>{exp}</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties.
Exclusion limits obtained for the $W\!h$med in the wino/bino (+) scenario, calculated using the $W\!h$ SRs and projected onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>{exp}</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties.
Exclusion limits obtained for the $W\!h$med in the wino/bino (+) scenario, calculated using the $W\!h$ SRs and projected onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>{exp}</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties.
Exclusion limits obtained for the $W\!h$med in the wino/bino (+) scenario, calculated using the $W\!h$ SRs and projected onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>{exp}</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties.
Exclusion limits obtained for the $W\!h$med in the wino/bino (+) scenario, calculated using the $W\!h$ SRs and projected onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>{exp}</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties.
Exclusion limits obtained for the $W\!h$med in the wino/bino (+) scenario, calculated using the $W\!h$ SRs and projected onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>{exp}</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties.
Exclusion limits obtained for the $W\!h$med in the wino/bino (+) scenario, calculated using the $W\!h$ SRs and projected onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>{exp}</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties.
Exclusion limits obtained for the $W\!h$med in the wino/bino (+) scenario, calculated using the $W\!h$ SRs and projected onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>{exp}</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties.
Exclusion limits obtained for the $W\!h$med in the wino/bino (+) scenario, calculated using the $W\!h$ SRs and projected onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>{exp}</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties.
Comparison of the observed data and expected SM background yields in the CRs and VRs of the RJR selection. The SM prediction is taken from the background-only fit. The "FNP leptons" category contains backgrounds from tt̄, tW, WW and Z+jets processes. The "Others" category contains backgrounds from Higgs and rare top processes. The hatched band indicates the combined theoretical, experimental, and MC statistical uncertainties. The bottom panel shows the significance of the difference between the observed and expected yields, calculated with the profile likelihood method from [169], adding a minus sign if the yield is below the prediction.
Comparison of the observed data and expected SM background yields in the CRs and VRs of the RJR selection. The SM prediction is taken from the background-only fit. The "FNP leptons" category contains backgrounds from tt̄, tW, WW and Z+jets processes. The "Others" category contains backgrounds from Higgs and rare top processes. The hatched band indicates the combined theoretical, experimental, and MC statistical uncertainties. The bottom panel shows the significance of the difference between the observed and expected yields, calculated with the profile likelihood method from [169], adding a minus sign if the yield is below the prediction.
Observed and expected yields after the background-only fit in the SRs for the RJR selection. The "FNP leptons" category contains backgrounds from tt̄, tW, WW and Z+jets processes. The "Others" category contains backgrounds from Higgs and rare top processes. Combined statistical and systematic uncertainties are presented.
Observed and expected yields after the background-only fit in the SRs for the RJR selection. The "FNP leptons" category contains backgrounds from tt̄, tW, WW and Z+jets processes. The "Others" category contains backgrounds from Higgs and rare top processes. Combined statistical and systematic uncertainties are presented.
Example of kinematic distributions after the background-only fit, showing the data and the post-fit expected background, in regions of the RJR selection. The figure shows the (a) p<sub>T</sub><sup>ℓ<sub>1</sub></sup> and (b) H<sup>PP</sup><sub>3,1</sub> distributions in SR3ℓ-Low, and the (c) p<sup>CM</sup><sub>T ISR</sub> and (d) R<sub>ISR</sub> distributions in SR3ℓ-ISR. The last bin includes overflow. The "FNP leptons" category contains backgrounds from tt̄, tW, WW and Z+jets processes. The "Others" category contains backgrounds from Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Example of kinematic distributions after the background-only fit, showing the data and the post-fit expected background, in regions of the RJR selection. The figure shows the (a) p<sub>T</sub><sup>ℓ<sub>1</sub></sup> and (b) H<sup>PP</sup><sub>3,1</sub> distributions in SR3ℓ-Low, and the (c) p<sup>CM</sup><sub>T ISR</sub> and (d) R<sub>ISR</sub> distributions in SR3ℓ-ISR. The last bin includes overflow. The "FNP leptons" category contains backgrounds from tt̄, tW, WW and Z+jets processes. The "Others" category contains backgrounds from Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Example of kinematic distributions after the background-only fit, showing the data and the post-fit expected background, in regions of the RJR selection. The figure shows the (a) p<sub>T</sub><sup>ℓ<sub>1</sub></sup> and (b) H<sup>PP</sup><sub>3,1</sub> distributions in SR3ℓ-Low, and the (c) p<sup>CM</sup><sub>T ISR</sub> and (d) R<sub>ISR</sub> distributions in SR3ℓ-ISR. The last bin includes overflow. The "FNP leptons" category contains backgrounds from tt̄, tW, WW and Z+jets processes. The "Others" category contains backgrounds from Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Example of kinematic distributions after the background-only fit, showing the data and the post-fit expected background, in regions of the RJR selection. The figure shows the (a) p<sub>T</sub><sup>ℓ<sub>1</sub></sup> and (b) H<sup>PP</sup><sub>3,1</sub> distributions in SR3ℓ-Low, and the (c) p<sup>CM</sup><sub>T ISR</sub> and (d) R<sub>ISR</sub> distributions in SR3ℓ-ISR. The last bin includes overflow. The "FNP leptons" category contains backgrounds from tt̄, tW, WW and Z+jets processes. The "Others" category contains backgrounds from Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Example of kinematic distributions after the background-only fit, showing the data and the post-fit expected background, in regions of the RJR selection. The figure shows the (a) p<sub>T</sub><sup>ℓ<sub>1</sub></sup> and (b) H<sup>PP</sup><sub>3,1</sub> distributions in SR3ℓ-Low, and the (c) p<sup>CM</sup><sub>T ISR</sub> and (d) R<sub>ISR</sub> distributions in SR3ℓ-ISR. The last bin includes overflow. The "FNP leptons" category contains backgrounds from tt̄, tW, WW and Z+jets processes. The "Others" category contains backgrounds from Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Example of kinematic distributions after the background-only fit, showing the data and the post-fit expected background, in regions of the RJR selection. The figure shows the (a) p<sub>T</sub><sup>ℓ<sub>1</sub></sup> and (b) H<sup>PP</sup><sub>3,1</sub> distributions in SR3ℓ-Low, and the (c) p<sup>CM</sup><sub>T ISR</sub> and (d) R<sub>ISR</sub> distributions in SR3ℓ-ISR. The last bin includes overflow. The "FNP leptons" category contains backgrounds from tt̄, tW, WW and Z+jets processes. The "Others" category contains backgrounds from Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Example of kinematic distributions after the background-only fit, showing the data and the post-fit expected background, in regions of the RJR selection. The figure shows the (a) p<sub>T</sub><sup>ℓ<sub>1</sub></sup> and (b) H<sup>PP</sup><sub>3,1</sub> distributions in SR3ℓ-Low, and the (c) p<sup>CM</sup><sub>T ISR</sub> and (d) R<sub>ISR</sub> distributions in SR3ℓ-ISR. The last bin includes overflow. The "FNP leptons" category contains backgrounds from tt̄, tW, WW and Z+jets processes. The "Others" category contains backgrounds from Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Example of kinematic distributions after the background-only fit, showing the data and the post-fit expected background, in regions of the RJR selection. The figure shows the (a) p<sub>T</sub><sup>ℓ<sub>1</sub></sup> and (b) H<sup>PP</sup><sub>3,1</sub> distributions in SR3ℓ-Low, and the (c) p<sup>CM</sup><sub>T ISR</sub> and (d) R<sub>ISR</sub> distributions in SR3ℓ-ISR. The last bin includes overflow. The "FNP leptons" category contains backgrounds from tt̄, tW, WW and Z+jets processes. The "Others" category contains backgrounds from Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
{Results of the discovery-fit for the SRs of the RJR selection, calculated using pseudo-experiments.} The first and second column list the 95 CL upper limits on the visible cross section (σ<sub>vis</sub><sup>95</sup>) and on the number of signal events (S<sub>obs</sub><sup>95</sup>). The third column (S<sub>exp</sub><sup>95</sup>) shows the 95 CL upper limit on the number of signal events, given the expected number (and ± 1σ excursions on the expectation) of background events. The last two columns indicate the CLb value, i.e. the confidence level observed for the background-only hypothesis, and the discovery p-value (p(s = 0)). If the observed yield is below the expected yield, the p-value is capped at 0.5. vspace{0.5em}
{Results of the discovery-fit for the SRs of the RJR selection, calculated using pseudo-experiments.} The first and second column list the 95 CL upper limits on the visible cross section (σ<sub>vis</sub><sup>95</sup>) and on the number of signal events (S<sub>obs</sub><sup>95</sup>). The third column (S<sub>exp</sub><sup>95</sup>) shows the 95 CL upper limit on the number of signal events, given the expected number (and ± 1σ excursions on the expectation) of background events. The last two columns indicate the CLb value, i.e. the confidence level observed for the background-only hypothesis, and the discovery p-value (p(s = 0)). If the observed yield is below the expected yield, the p-value is capped at 0.5. vspace{0.5em}
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!h$-mediated model, for the wino/bino (+) scenario, as in Figure 17. The black numbers represent the observed (a,c,e,g) and expected (b,d,f,h) upper cross-section limits.
Exclusion limits obtained for the $W\!h$-mediated model, for the wino/bino (+) scenario, as in Figure 17. The black numbers represent the observed (a,c,e,g) and expected (b,d,f,h) upper cross-section limits.
Exclusion limits obtained for the $W\!h$-mediated model, for the wino/bino (+) scenario, as in Figure 17. The black numbers represent the observed (a,c,e,g) and expected (b,d,f,h) upper cross-section limits.
Exclusion limits obtained for the $W\!h$-mediated model, for the wino/bino (+) scenario, as in Figure 17. The black numbers represent the observed (a,c,e,g) and expected (b,d,f,h) upper cross-section limits.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c) truth-level acceptances and (b,d) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>WZ</sup><sub>0j</sub>, (c,d) SR<sup>WZ</sup><sub>nj</sub> regions of the onshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c) truth-level acceptances and (b,d) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>WZ</sup><sub>0j</sub>, (c,d) SR<sup>WZ</sup><sub>nj</sub> regions of the onshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c) truth-level acceptances and (b,d) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>WZ</sup><sub>0j</sub>, (c,d) SR<sup>WZ</sup><sub>nj</sub> regions of the onshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c) truth-level acceptances and (b,d) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>WZ</sup><sub>0j</sub>, (c,d) SR<sup>WZ</sup><sub>nj</sub> regions of the onshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c) truth-level acceptances and (b,d) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>WZ</sup><sub>0j</sub>, (c,d) SR<sup>WZ</sup><sub>nj</sub> regions of the onshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c) truth-level acceptances and (b,d) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>WZ</sup><sub>0j</sub>, (c,d) SR<sup>WZ</sup><sub>nj</sub> regions of the onshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c) truth-level acceptances and (b,d) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>WZ</sup><sub>0j</sub>, (c,d) SR<sup>WZ</sup><sub>nj</sub> regions of the onshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c) truth-level acceptances and (b,d) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>WZ</sup><sub>0j</sub>, (c,d) SR<sup>WZ</sup><sub>nj</sub> regions of the onshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e) truth-level acceptances and (b,d,f) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-0j</sub>, (c,d) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-nj</sub>, and (e,f) SR<sup>Wh</sup><sub>DF</sub> regions of the $W\!h$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e) truth-level acceptances and (b,d,f) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-0j</sub>, (c,d) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-nj</sub>, and (e,f) SR<sup>Wh</sup><sub>DF</sub> regions of the $W\!h$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e) truth-level acceptances and (b,d,f) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-0j</sub>, (c,d) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-nj</sub>, and (e,f) SR<sup>Wh</sup><sub>DF</sub> regions of the $W\!h$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e) truth-level acceptances and (b,d,f) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-0j</sub>, (c,d) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-nj</sub>, and (e,f) SR<sup>Wh</sup><sub>DF</sub> regions of the $W\!h$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e) truth-level acceptances and (b,d,f) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-0j</sub>, (c,d) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-nj</sub>, and (e,f) SR<sup>Wh</sup><sub>DF</sub> regions of the $W\!h$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e) truth-level acceptances and (b,d,f) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-0j</sub>, (c,d) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-nj</sub>, and (e,f) SR<sup>Wh</sup><sub>DF</sub> regions of the $W\!h$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e) truth-level acceptances and (b,d,f) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-0j</sub>, (c,d) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-nj</sub>, and (e,f) SR<sup>Wh</sup><sub>DF</sub> regions of the $W\!h$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e) truth-level acceptances and (b,d,f) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-0j</sub>, (c,d) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-nj</sub>, and (e,f) SR<sup>Wh</sup><sub>DF</sub> regions of the $W\!h$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e) truth-level acceptances and (b,d,f) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-0j</sub>, (c,d) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-nj</sub>, and (e,f) SR<sup>Wh</sup><sub>DF</sub> regions of the $W\!h$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e) truth-level acceptances and (b,d,f) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-0j</sub>, (c,d) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-nj</sub>, and (e,f) SR<sup>Wh</sup><sub>DF</sub> regions of the $W\!h$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e) truth-level acceptances and (b,d,f) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-0j</sub>, (c,d) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-nj</sub>, and (e,f) SR<sup>Wh</sup><sub>DF</sub> regions of the $W\!h$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e) truth-level acceptances and (b,d,f) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-0j</sub>, (c,d) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-nj</sub>, and (e,f) SR<sup>Wh</sup><sub>DF</sub> regions of the $W\!h$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
Summary of onshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (300,200) GeV and m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (600,100) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal points, for the wino/bino (+) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks per inclusive regions, and then further for each SR. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5.
Summary of onshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (300,200) GeV and m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (600,100) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal points, for the wino/bino (+) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks per inclusive regions, and then further for each SR. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5.
Summary of $W\!h$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (190,60) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (+) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks per inclusive regions, and then further for each SR. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5.
Summary of $W\!h$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (190,60) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (+) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks per inclusive regions, and then further for each SR. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (250,235) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (+) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (250,235) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (+) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (125,85) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (+) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (125,85) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (+) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (250,170) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (+) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (250,170) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (+) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (250,235) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (-) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (250,235) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (-) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (125,85) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (-) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (125,85) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (-) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (250,170) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (-) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (250,170) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (-) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (120,100) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the higgsino interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (120,100) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the higgsino interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (100,40) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the higgsino interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (100,40) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the higgsino interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (185,125) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the higgsino interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (185,125) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the higgsino interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
A search for diphoton resonances in the mass range between 10 and 70 GeV with the ATLAS experiment at the Large Hadron Collider (LHC) is presented. The analysis is based on $pp$ collision data corresponding to an integrated luminosity of 138 fb$^{-1}$ at a centre-of-mass energy of 13 TeV recorded from 2015 to 2018. Previous searches for diphoton resonances at the LHC have explored masses down to 65 GeV, finding no evidence of new particles. This search exploits the particular kinematics of events with pairs of closely spaced photons reconstructed in the detector, allowing examination of invariant masses down to 10 GeV. The presented strategy covers a region previously unexplored at hadron colliders because of the experimental challenges of recording low-energy photons and estimating the backgrounds. No significant excess is observed and the reported limits provide the strongest bound on promptly decaying axion-like particles coupling to gluons and photons for masses between 10 and 70 GeV.
The expected and observed upper limits at 95\% CL on the fiducial cross-section times branching ratio to two photons of a narrow-width ($\Gamma_{X}$ = 4 MeV) scalar resonance as a function of its mass $m_{X}$.
Diphoton invariant mass in the signal region using a 0.1 GeV binning.
Parametrization of the $C_{X}$ factor, defined as the ratio between the number of reconstructed signal events passing the analysis cuts and the number of signal events at the particle level generated within the fiducial volume, as function of $m_{X}$ obtained from the narrow width simulated signal samples produced in gluon fusion.
Parametrization of the $A_{X}$ factor, defined as the fraction of diphoton resonances satisfying the fiducial acceptance at the particle level, as function of $m_{X}$ obtained from the narrow width simulated signal samples produced in gluon fusion.
The correction factor, $C_{X}$, defined as the ratio between the number of reconstructed signal events passing the analysis cuts and the number of signal events at the particle level generated within the fiducial volume, and acceptance correction factor, $A_{X}$, defined as the fraction of diphoton resonances satisfying the fiducial acceptance at the particle level. Both are computed for NWA spin-0 models as a function of $m_{X}$.
Effect of event selections on a scalar MC signal sample generated for $m_{X}$ = 15 GeV and on the data. For the MC sample, the efficiencies are shown after applying event weights and a truth level filter that requires two photons with $p^{\gamma\gamma}_{T}>40$ GeV; for the data, the absolute yields are shown. The initial yields for data include a trigger preselection that is the OR of a list of single photon and diphoton triggers. The "2 $loose$ photons" step includes the kinematic acceptance cuts.
Parameterization of the Double Sided Crystal Ball function parameters describing the scalar mass resolution model as a function of $m_{X}$ [GeV].
Differential cross-sections are measured for the production of four charged leptons in association with two jets. These measurements are sensitive to final states in which the jets are produced via the strong interaction as well as to the purely-electroweak vector boson scattering process. The analysis is performed using proton-proton collision data collected by ATLAS at $\sqrt{s}=13$ TeV and with an integrated luminosity of 140 fb$^{-1}$. The data are corrected for the effects of detector inefficiency and resolution and are compared to state-of-the-art Monte Carlo event generator predictions. The differential cross-sections are used to search for anomalous weak-boson self-interactions that are induced by dimension-six and dimension-eight operators in Standard Model effective field theory.
Predicted and observed yields as a function of $m_{jj}$ in the VBS-Enhanced region. Overflow events are included in the last bin of the distribution.
Predicted and observed yields as a function of $m_{jj}$ in the VBS-Suppressed region. Overflow events are included in the last bin of the distribution.
Predicted and observed yields as a function of $m_{4\ell}$ in the VBS-Enhanced region. Overflow events are included in the last bin of the distribution.
Predicted and observed yields as a function of $m_{4\ell}$ in the VBS-Suppressed region. Overflow events are included in the last bin of the distribution.
Relative systematic uncertainties in the unfolded differential cross section for 4ljj production in the VBS-Enhanced region as a function of m_{jj}
Relative systematic uncertainties in the unfolded differential cross section for 4ljj production in the VBS-Enhanced region as a function of m_{4\ell}
Differential cross-sections for inclusive 4ljj production in the VBS-Enhanced region as a function of $m_{jj}$. Overflow events are included in the last bin of the distribution.
Differential cross-sections for inclusive 4ljj production in the VBS-Suppressed region as a function of $m_{jj}$. Overflow events are included in the last bin of the distribution.
Differential cross-sections for inclusive 4ljj production in the VBS-Enhanced region as a function of $m_{4\ell}$. Overflow events are included in the last bin of the distribution.
Differential cross-sections for inclusive 4ljj production in the VBS-Suppressed region as a function of $m_{4\ell}$. Overflow events are included in the last bin of the distribution.
Differential cross-sections for inclusive 4ljj production in the VBS-Enhanced region as a function of $ p_{T,4l}$. Overflow events are included in the last bin of the distribution.
Differential cross-sections for inclusive 4ljj production in the VBS-Suppressed region as a function of $ p_{T,4l}$. Overflow events are included in the last bin of the distribution.
Differential cross-sections for inclusive 4ljj production in the VBS-Enhanced region as a function of $\Delta\phi_{jj}$. Overflow events are included in the last bin of the distribution.
Differential cross-sections for inclusive 4ljj production in the VBS-Suppressed region as a function of $\Delta\phi_{jj}$. Overflow events are included in the last bin of the distribution.
Differential cross-sections for inclusive 4ljj production in the VBS-Enhanced region as a function of $|\Delta y_{jj}|$. Overflow events are included in the last bin of the distribution.
Differential cross-sections for inclusive 4ljj production in the VBS-Suppressed region as a function of $|\Delta y_{jj}|$. Overflow events are included in the last bin of the distribution.
Differential cross-sections for inclusive 4ljj production in the VBS-Enhanced region as a function of $cos(\theta^{*}_{12})$. Overflow events are included in the last bin of the distribution.
Differential cross-sections for inclusive 4ljj production in the VBS-Suppressed region as a function of $cos(\theta^{*}_{12})$. Overflow events are included in the last bin of the distribution.
Differential cross-sections for inclusive 4ljj production in the VBS-Enhanced region as a function of $cos(\theta^{*}_{34})$. Overflow events are included in the last bin of the distribution.
Differential cross-sections for inclusive 4ljj production in the VBS-Suppressed region as a function of $cos(\theta^{*}_{34})$. Overflow events are included in the last bin of the distribution.
Differential cross-sections for inclusive 4ljj production in the VBS-Enhanced region as a function of $p_{T,jj}$. Overflow events are included in the last bin of the distribution.
Differential cross-sections for inclusive 4ljj production in the VBS-Suppressed region as a function of $p_{T,jj}$. Overflow events are included in the last bin of the distribution.
Differential cross-sections for inclusive 4ljj production in the VBS-Enhanced region as a function of $p_{T,4ljj}$. Overflow events are included in the last bin of the distribution.
Differential cross-sections for inclusive 4ljj production in the VBS-Suppressed region as a function of $p_{T,4ljj}$. Overflow events are included in the last bin of the distribution.
Differential cross-sections for inclusive 4ljj production in the VBS-Enhanced region as a function of $S_{T,4ljj}$. Overflow events are included in the last bin of the distribution.
Differential cross-sections for inclusive 4ljj production in the VBS-Suppressed region as a function of $S_{T,4ljj}$. Overflow events are included in the last bin of the distribution.
Statistical correlation between different bins of the unfolded cross-section for all the measured observables in the VBS-Enhanced region.
Statistical correlation between different bins of the unfolded cross-section for all the measured observables in the VBS-Suppressed region.
A search for pair production of bottom squarks in events with hadronically decaying $\tau$-leptons, $b$-tagged jets and large missing transverse momentum is presented. The analyzed dataset is based on proton-proton collisions at $\sqrt{s}$ = 13 TeV delivered by the Large Hadron Collider and recorded by the ATLAS detector from 2015 to 2018, and corresponds to an integrated luminosity of 139 fb$^{-1}$. The observed data are compatible with the expected Standard Model background. Results are interpreted in a simplified model where each bottom squark is assumed to decay into the second-lightest neutralino $\tilde \chi_2^0$ and a bottom quark, with $\tilde \chi_2^0$ decaying into a Higgs boson and the lightest neutralino $\tilde \chi_1^0$. The search focuses on final states where at least one Higgs boson decays into a pair of hadronically decaying $\tau$-leptons. This allows the acceptance and thus the sensitivity to be significantly improved relative to the previous results at low masses of the $\tilde \chi_2^0$, where bottom-squark masses up to 850 GeV are excluded at the 95% confidence level, assuming a mass difference of 130 GeV between $\tilde \chi_2^0$ and $\tilde \chi_1^0$. Model-independent upper limits are also set on the cross section of processes beyond the Standard Model.
The expected exclusion contour at $95\%$ CL as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV. Masses within the contour are excluded.
The observed exclusion contour at $95\%$ CL as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV. Masses within the contour are excluded.
Acceptance in the Single-bin SR as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV. Keep in mind that the acceptance is given in units of $10^{-4}$.
Efficiency in the Single-bin SR as a function of the M(Sbottom) vs. M(N2) with the $\Delta$ M(N2,N1) $= 130$ GeV. Keep in mind that the efficiency is given in units of $10^{-2}$.
Acceptance in the Multi-bin SR, $\min_{\Theta} < 0.5$ bin as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV. Keep in mind that the acceptance is given in units of $10^{-4}$.
Efficiency in the Multi-bin SR, $\min_{\Theta} < 0.5$ bin as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV. Keep in mind that the efficiency is given in units of $10^{-2}$.
Acceptance in the Multi-bin SR, $0.5 < \min_{\Theta} < 1.0$ bin as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV. Keep in mind that the acceptance is given in units of $10^{-4}$.
Efficiency in the Multi-bin SR, $0.5 < \min_{\Theta} < 1.0$ bin as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV. Keep in mind that the efficiency is given in units of $10^{-2}$.
Acceptance in the Multi-bin SR, $\min_{\Theta} > 1.0$ bin as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV. Keep in mind that the acceptance is given in units of $10^{-4}$.
Efficiency in the Multi-bin SR, $\min_{\Theta} > 1.0$ bin as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV. Keep in mind that the efficiency is given in units of $10^{-2}$.
Observed upper limits on the signal cross section as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV.
Expected upper limits on the signal cross section as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV.
Cutflows for the bechmarl signal point M(Sbottom) = 800 GeV, M(N2) = 180 GeV. Weighted event yields are reported starting with the "Preselection" line, normalized to an integrated luminosity of $139$ fb$^{−1}$.
Comparison of the expected and observed event yields in the signal regions. The top-quark and Z(mumu) background contributions are scaled with the normalization factors obtained from the background-only fit. The other contribution includes all the backgrounds not explicitly listed in the legend (V+jets except Z(mumu)+jets, di-/triboson, multijet). The hatched band indicates the total statistical and systematic uncertainties in the SM background. The contributions from three signal models to the signal regions are also displayed, where the masses M(Sbottom) and M(N2) are given in GeV in the legend. The lower panel shows the significance of the deviation of the observed yield from the expected background yield.
Dominant systematic uncertainties in the background prediction for the signal regions after the fit to the control regions. “Other” includes the uncertainties arising from muons, jet-vertex tagging, modeling of pile-up, the $E_{T}^{miss}$ computation, multijet background, and luminosity. The individual uncertainties can be correlated and do not necessarily add up quadratically to the total uncertainty.
This Letter reports the observation of single top quarks produced together with a photon, which directly probes the electroweak coupling of the top quark. The analysis uses 139 fb$^{-1}$ of 13 TeV proton-proton collision data collected with the ATLAS detector at the Large Hadron Collider. Requiring a photon with transverse momentum larger than 20 GeV and within the detector acceptance, the fiducial cross section is measured to be 688 $\pm$ 23 (stat.) $^{+75}_{-71}$ (syst.) fb, to be compared with the standard model prediction of 515 $^{+36}_{-42}$ fb at next-to-leading order in QCD.
This table shows the values for $\sigma_{tq\gamma}\times\mathcal{B}(t\rightarrow l\nu b)$ and $\sigma_{tq\gamma}\times\mathcal{B}(t\rightarrow l\nu b)+\sigma_{t(\rightarrow l\nu b\gamma)q}$ obtained by a profile-likelihood fit in the fiducial parton-level phase space (defined in Table 1) and particle-level phase space (defined in Table 2), respectively.
Distribution of the reconstructed top-quark mass in the $W\gamma\,$CR before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions. The first and last bins include the underflow and overflow, respectively.
Distribution of the NN output in the 0fj$\,$SR in data and the expected contribution of the signal and background processes after the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions considering the correlations of the uncertainties as obtained by the fit.
Distribution of the NN output in the $\geq$1fj$\,$SR in data and the expected contribution of the signal and background processes after the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions considering the correlations of the uncertainties as obtained by the fit.
Distribution of the NN output in the $t\bar{t}\gamma\,$CR in data and the expected contribution of the signal and background processes after the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions considering the correlations of the uncertainties as obtained by the fit.
Total event yield in the $W\gamma\,$CR in data and the expected contribution of the signal and background processes after the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions considering the correlations of the uncertainties as obtained by the fit.
Distribution of the scalar sum of the jet transverse momenta in the 0fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions. The first and last bins include the underflow and overflow, respectively.
Distribution of the $\eta$ of the $b$-tagged jet in the 0fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions.
Distribution of the reconstructed top-quark mass in the 0fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions. The first and last bins include the underflow and overflow, respectively.
Distribution of the $p_{\mathrm{T}}$ of the top-quark+photon system in the 0fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions and the last bin includes the overflow.
Distribution of the photon $p_{\mathrm{T}}$ in the 0fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions and the last bin includes the overflow.
Distribution of the photon $\eta$ in the 0fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions.
Distribution of the scalar sum of the jet transverse momenta in the $\geq$1fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions and the last bin includes the overflow.
Distribution of the invariant mass of the $b$-tagged jet and the highest-$p_{\mathrm{T}}$ forward jet in the $\geq$1fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions and the last bin includes the overflow.
Distribution of $p_{\mathrm{T}}$ of the highest-$p_{\mathrm{T}}$ forward jet in the $\geq$1fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions and the last bin includes the overflow.
Distribution of the difference in $\eta$ between the highest-$p_{\mathrm{T}}$ forward jet and the photon in the $\geq$1fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions and the last bin includes the overflow.
Distribution of the energy of the system formed by the highest-$p_{\mathrm{T}}$ forward jet and the photon in the $\geq$1fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions. The first and last bins include the underflow and overflow, respectively.
Distribution of the $\eta$ of the $b$-tagged jet in the $\geq$1fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions.
Distribution of the reconstructed top-quark mass in the $\geq$1fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions. The first and last bins include the underflow and overflow, respectively.
Distribution of the $p_{\mathrm{T}}$ of the top-quark and photon system in the $\geq$1fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions and the last bin includes the overflow.
Distribution of the photon $p_{\mathrm{T}}$ in the $\geq$1fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions and the last bin includes the overflow.
Distribution of the photon $\eta$ in the $\geq$1fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions.
Ordered list of the 30 systematic uncertainties with the largest impact on the measured signal normalisation in the fit to data in the parton-level measurement considered as nuisance parameters (NPs) in the profile-likelihood fit. The column "NP value, error" corresponds to the nominal best-fit values and the corresponding uncertainties. The impact of each NP, $\Delta\sigma$/$\sigma_{\mathrm{pred}}$, is computed by comparing the nominal best-fit value of the POI ($\sigma$/$\sigma_{\mathrm{pred}}$) with the result of the fits when fixing the considered NP to its best-fit value shifted by its pre-fit and post-fit uncertainties. The corresponding impacts are listed in the "POI impact prefit high/low" and "POI impact high/low" columns, respectively. The "MC stat." NPs represent the MC statistical uncertainty and they enter the likelihood with a Poisson term, while all the other NPs enter the likelihood via a Gaussian term.
Ordered list of the 30 systematic uncertainties with the largest impact on the measured signal normalisation in the fit to data in the particle-level measurement considered as nuisance parameters (NPs) in the profile-likelihood fit. The column "NP value, error" corresponds to the nominal best-fit values and the corresponding uncertainties. The impact of each NP, $\Delta\sigma$/$\sigma_{\mathrm{pred}}$, is computed by comparing the nominal best-fit value of the POI ($\sigma$/$\sigma_{\mathrm{pred}}$) with the result of the fits when fixing the considered NP to its best-fit value shifted by its pre-fit and post-fit uncertainties. The corresponding impacts are listed in the "POI impact prefit high/low" and "POI impact high/low" columns, respectively. The "MC stat." NPs represent the MC statistical uncertainty and they enter the likelihood with a Poisson term, while all the other NPs enter the likelihood via a Gaussian term.
This table lists the kinematic requirements on parton-level objects used to define of the fiducial phase space for the parton-level measurement. Frixione isolation ($\href{https://arxiv.org/abs/hep-ph/9801442}{\text{hep-ph/9801442}}$) with a chosen radius of $\Delta R = 0.2$ is applied to photons ($\gamma$). The measured fiducial parton-level cross section is $\sigma_{tq\gamma}\times\mathcal{B}(t\rightarrow l\nu b) = 688\pm 23(\text{stat.})^{+75}_{-71}(\text{syst.})\,$fb.
This table lists the kinematic requirements on particle-level objects used to define of the fiducial phase space for the particle-level measurement. The particle level objects are photons ($\gamma$) not from a hadron decay, neutrinos not from a hadron decay ($\nu$), prompt electrons and muons ($\ell$) "dressed" by adding close-by ($\Delta R < 0.1$) photons, and anti-$k_t$ $R = 0.4$ jets built from stable particles ($\tau > 30\,$ps) and tau leptons excluding neutrinos and prompt dressed muons. Jets are $b$-tagged ($b$-jet) using ghost-matched $b$-hadrons with $p_{\text{T}} > 5\,$GeV. Apart from the kinematic requirements, isolation and overlap removal criteria are applied. Jets within $\Delta R = 0.4$ of a photon are removed if the $p_{\text{T}}$ of charged particles within $\Delta R = 0.3$ of the photon is smaller than $10\,\%$ of its $p_{\text{T}}$. Jets within $\Delta R = 0.4$ of a lepton are removed. Events are removed where a photon is close ($\Delta R < 0.4$) to a lepton or a surviving jet. The measured fiducial particle-level cross section is $\sigma_{tq\gamma}\times\mathcal{B}(t\rightarrow l\nu b)+\sigma_{t(\rightarrow l\nu b\gamma)q} = 303\pm 9(\text{stat.})^{+33}_{-32}(\text{syst.})\,$fb.
The factor of four increase in the LHC luminosity, from $0.5\times 10^{34}\,\textrm{cm}^{-2}\textrm{s}^{-1}$ to $2.0\times 10^{34}\textrm{cm}^{-2}\textrm{s}^{-1}$, and the corresponding increase in pile-up collisions during the 2015-2018 data-taking period, presented a challenge for ATLAS to trigger on missing transverse momentum. The output data rate at fixed threshold typically increases exponentially with the number of pile-up collisions, so the legacy algorithms from previous LHC data-taking periods had to be tuned and new approaches developed to maintain the high trigger efficiency achieved in earlier operations. A study of the trigger performance and comparisons with simulations show that these changes resulted in event selection efficiencies of >98% for this period, meeting and in some cases exceeding the performance of similar triggers in earlier run periods, while at the same time keeping the necessary bandwidth within acceptable limits.
A comparison of the measured cell $E_T^{miss}$ distribution with that predicted by the two-component model for two pile-up scenarios. The magenta points extend the measured distribution using L1 $E_T^{miss} > 30\,$GeV and L1 $E_T^{miss} > 50\,$GeV data. The red curve is the prediction from the calorimeter-resolution part of the model. The green curve is the high $E_T^{miss}$ tail's probability distribution for the mean number of $pp$ interactions $\mu$ in each figure. The blue curve is the full model prediction computed by combining the $E_T^{miss}$ from these two individual sources shown in red and green, each calculated for $\mu=\langle\mu\rangle$. The black points show the unbiased $E_T^{miss}$ distribution measured in data. Corresponds to a prediction for $\langle\mu\rangle = 25$.
A comparison of the measured cell $E_T^{miss}$ distribution with that predicted by the two-component model for two pile-up scenarios. The magenta points extend the measured distribution using L1 $E_T^{miss} > 30\,$GeV and L1 $E_T^{miss} > 50\,$GeV data. The red curve is the prediction from the calorimeter-resolution part of the model. The green curve is the high $E_T^{miss}$ tail's probability distribution for the mean number of $pp$ interactions $\mu$ in each figure. The blue curve is the full model prediction computed by combining the $E_T^{miss}$ from these two individual sources shown in red and green, each calculated for $\mu=\langle\mu\rangle$. The black points show the unbiased $E_T^{miss}$ distribution measured in data. Corresponds to a prediction for $\langle\mu\rangle = 25$.
A comparison of the measured cell $E_T^{miss}$ distribution with that predicted by the two-component model for two pile-up scenarios. The magenta points extend the measured distribution using L1 $E_T^{miss} > 30\,$GeV and L1 $E_T^{miss} > 50\,$GeV data. The red curve is the prediction from the calorimeter-resolution part of the model. The green curve is the high $E_T^{miss}$ tail's probability distribution for the mean number of $pp$ interactions $\mu$ in each figure. The blue curve is the full model prediction computed by combining the $E_T^{miss}$ from these two individual sources shown in red and green, each calculated for $\mu=\langle\mu\rangle$. The black points show the unbiased $E_T^{miss}$ distribution measured in data. Corresponds to a prediction for $\langle\mu\rangle = 25$.
A comparison of the measured cell $E_T^{miss}$ distribution with that predicted by the two-component model for two pile-up scenarios. The magenta points extend the measured distribution using L1 $E_T^{miss} > 30\,$GeV and L1 $E_T^{miss} > 50\,$GeV data. The red curve is the prediction from the calorimeter-resolution part of the model. The green curve is the high $E_T^{miss}$ tail's probability distribution for the mean number of $pp$ interactions $\mu$ in each figure. The blue curve is the full model prediction computed by combining the $E_T^{miss}$ from these two individual sources shown in red and green, each calculated for $\mu=\langle\mu\rangle$. The black points show the unbiased $E_T^{miss}$ distribution measured in data. Corresponds to a prediction for $\langle\mu\rangle = 25$.
A comparison of the measured cell $E_T^{miss}$ distribution with that predicted by the two-component model for two pile-up scenarios. The magenta points extend the measured distribution using L1 $E_T^{miss} > 30\,$GeV and L1 $E_T^{miss} > 50\,$GeV data. The red curve is the prediction from the calorimeter-resolution part of the model. The green curve is the high $E_T^{miss}$ tail's probability distribution for the mean number of $pp$ interactions $\mu$ in each figure. The blue curve is the full model prediction computed by combining the $E_T^{miss}$ from these two individual sources shown in red and green, each calculated for $\mu=\langle\mu\rangle$. The black points show the unbiased $E_T^{miss}$ distribution measured in data. Corresponds to a prediction for $\langle\mu\rangle = 25$.
A comparison of the measured cell $E_T^{miss}$ distribution with that predicted by the two-component model for two pile-up scenarios. The magenta points extend the measured distribution using L1 $E_T^{miss} > 30\,$GeV and L1 $E_T^{miss} > 50\,$GeV data. The red curve is the prediction from the calorimeter-resolution part of the model. The green curve is the high $E_T^{miss}$ tail's probability distribution for the mean number of $pp$ interactions $\mu$ in each figure. The blue curve is the full model prediction computed by combining the $E_T^{miss}$ from these two individual sources shown in red and green, each calculated for $\mu=\langle\mu\rangle$. The black points show the unbiased $E_T^{miss}$ distribution measured in data. Corresponds to a prediction for $\langle\mu\rangle = 55$.
A comparison of the measured cell $E_T^{miss}$ distribution with that predicted by the two-component model for two pile-up scenarios. The magenta points extend the measured distribution using L1 $E_T^{miss} > 30\,$GeV and L1 $E_T^{miss} > 50\,$GeV data. The red curve is the prediction from the calorimeter-resolution part of the model. The green curve is the high $E_T^{miss}$ tail's probability distribution for the mean number of $pp$ interactions $\mu$ in each figure. The blue curve is the full model prediction computed by combining the $E_T^{miss}$ from these two individual sources shown in red and green, each calculated for $\mu=\langle\mu\rangle$. The black points show the unbiased $E_T^{miss}$ distribution measured in data. Corresponds to a prediction for $\langle\mu\rangle = 55$.
A comparison of the measured cell $E_T^{miss}$ distribution with that predicted by the two-component model for two pile-up scenarios. The magenta points extend the measured distribution using L1 $E_T^{miss} > 30\,$GeV and L1 $E_T^{miss} > 50\,$GeV data. The red curve is the prediction from the calorimeter-resolution part of the model. The green curve is the high $E_T^{miss}$ tail's probability distribution for the mean number of $pp$ interactions $\mu$ in each figure. The blue curve is the full model prediction computed by combining the $E_T^{miss}$ from these two individual sources shown in red and green, each calculated for $\mu=\langle\mu\rangle$. The black points show the unbiased $E_T^{miss}$ distribution measured in data. Corresponds to a prediction for $\langle\mu\rangle = 55$.
A comparison of the measured cell $E_T^{miss}$ distribution with that predicted by the two-component model for two pile-up scenarios. The magenta points extend the measured distribution using L1 $E_T^{miss} > 30\,$GeV and L1 $E_T^{miss} > 50\,$GeV data. The red curve is the prediction from the calorimeter-resolution part of the model. The green curve is the high $E_T^{miss}$ tail's probability distribution for the mean number of $pp$ interactions $\mu$ in each figure. The blue curve is the full model prediction computed by combining the $E_T^{miss}$ from these two individual sources shown in red and green, each calculated for $\mu=\langle\mu\rangle$. The black points show the unbiased $E_T^{miss}$ distribution measured in data. Corresponds to a prediction for $\langle\mu\rangle = 55$.
A comparison of the measured cell $E_T^{miss}$ distribution with that predicted by the two-component model for two pile-up scenarios. The magenta points extend the measured distribution using L1 $E_T^{miss} > 30\,$GeV and L1 $E_T^{miss} > 50\,$GeV data. The red curve is the prediction from the calorimeter-resolution part of the model. The green curve is the high $E_T^{miss}$ tail's probability distribution for the mean number of $pp$ interactions $\mu$ in each figure. The blue curve is the full model prediction computed by combining the $E_T^{miss}$ from these two individual sources shown in red and green, each calculated for $\mu=\langle\mu\rangle$. The black points show the unbiased $E_T^{miss}$ distribution measured in data. Corresponds to a prediction for $\langle\mu\rangle = 55$.
The L1 $E_T^{miss}$ trigger efficiency, shown as a function of $p_T(\mu\mu)$ in $Z\rightarrow\mu\mu$ events.
The efficiencies in the plot are shown for events satisfying a $Z\rightarrow\mu\mu$ selection and with $p_T(\mu\mu)$ larger than $150\,$GeV vs pile-up for each of the four years of data taking.
Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $0\leq\langle\mu\rangle < 20$.
Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $0\leq\langle\mu\rangle < 20$.
Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $0\leq\langle\mu\rangle < 20$.
Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $0\leq\langle\mu\rangle < 20$.
Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $0\leq\langle\mu\rangle < 20$.
Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $20\leq\langle\mu\rangle < 30$.
Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $20\leq\langle\mu\rangle < 30$.
Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $20\leq\langle\mu\rangle < 30$.
Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $20\leq\langle\mu\rangle < 30$.
Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $20\leq\langle\mu\rangle < 30$.
Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $30\leq\langle\mu\rangle < 40$.
Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $30\leq\langle\mu\rangle < 40$.
Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $30\leq\langle\mu\rangle < 40$.
Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $30\leq\langle\mu\rangle < 40$.
Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $30\leq\langle\mu\rangle < 40$.
Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $40\leq\langle\mu\rangle$.
Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $40\leq\langle\mu\rangle$.
Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $40\leq\langle\mu\rangle$.
Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $40\leq\langle\mu\rangle$.
Background acceptance vs signal efficiency for each of four individual HLT $E_T^{miss}$ algorithms for a $Z\rightarrow\mu\mu$ selection with $p_T(\mu\mu) > 175\,$GeV for data recorded in the year 2017. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger. $40\leq\langle\mu\rangle$.
Relative background acceptance fraction vs. relative efficiency for two different $p_T(\mu\mu)>150\,$GeV threshold for data recorded in the year 2018. Two of the curves show the performance of the stand-alone cell algorithm and the stand-alone pufit algorithm. The other two show combined algorithms each formed by requiring that the event satisfy both a fixed threshold (either 65 GeV or 70 GeV as shown in the legend) for the cell algorithm and a pufit threshold which varies along the curve. In each plot the background acceptance fractions and the efficiencies are relative to those of the pufit $E_T^{miss} > 110\,$GeV trigger and thus can be greater than one. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger while the cross indicates the performance of the combined (pufit $E_T^{miss}>110\,$GeV and cell $E_T^{miss}>50\,$GeV) trigger.
Relative background acceptance fraction vs. relative efficiency for two different $p_T(\mu\mu)>150\,$GeV threshold for data recorded in the year 2018. Two of the curves show the performance of the stand-alone cell algorithm and the stand-alone pufit algorithm. The other two show combined algorithms each formed by requiring that the event satisfy both a fixed threshold (either 65 GeV or 70 GeV as shown in the legend) for the cell algorithm and a pufit threshold which varies along the curve. In each plot the background acceptance fractions and the efficiencies are relative to those of the pufit $E_T^{miss} > 110\,$GeV trigger and thus can be greater than one. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger while the cross indicates the performance of the combined (pufit $E_T^{miss}>110\,$GeV and cell $E_T^{miss}>50\,$GeV) trigger.
Relative background acceptance fraction vs. relative efficiency for two different $p_T(\mu\mu)>150\,$GeV threshold for data recorded in the year 2018. Two of the curves show the performance of the stand-alone cell algorithm and the stand-alone pufit algorithm. The other two show combined algorithms each formed by requiring that the event satisfy both a fixed threshold (either 65 GeV or 70 GeV as shown in the legend) for the cell algorithm and a pufit threshold which varies along the curve. In each plot the background acceptance fractions and the efficiencies are relative to those of the pufit $E_T^{miss} > 110\,$GeV trigger and thus can be greater than one. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger while the cross indicates the performance of the combined (pufit $E_T^{miss}>110\,$GeV and cell $E_T^{miss}>50\,$GeV) trigger.
Relative background acceptance fraction vs. relative efficiency for two different $p_T(\mu\mu)>150\,$GeV threshold for data recorded in the year 2018. Two of the curves show the performance of the stand-alone cell algorithm and the stand-alone pufit algorithm. The other two show combined algorithms each formed by requiring that the event satisfy both a fixed threshold (either 65 GeV or 70 GeV as shown in the legend) for the cell algorithm and a pufit threshold which varies along the curve. In each plot the background acceptance fractions and the efficiencies are relative to those of the pufit $E_T^{miss} > 110\,$GeV trigger and thus can be greater than one. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger while the cross indicates the performance of the combined (pufit $E_T^{miss}>110\,$GeV and cell $E_T^{miss}>50\,$GeV) trigger.
Relative background acceptance fraction vs. relative efficiency for two different $p_T(\mu\mu)>150\,$GeV threshold for data recorded in the year 2018. Two of the curves show the performance of the stand-alone cell algorithm and the stand-alone pufit algorithm. The other two show combined algorithms each formed by requiring that the event satisfy both a fixed threshold (either 65 GeV or 70 GeV as shown in the legend) for the cell algorithm and a pufit threshold which varies along the curve. In each plot the background acceptance fractions and the efficiencies are relative to those of the pufit $E_T^{miss} > 110\,$GeV trigger and thus can be greater than one. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger while the cross indicates the performance of the combined (pufit $E_T^{miss}>110\,$GeV and cell $E_T^{miss}>50\,$GeV) trigger.
Relative background acceptance fraction vs. relative efficiency for two different $p_T(\mu\mu)>150\,$GeV threshold for data recorded in the year 2018. Two of the curves show the performance of the stand-alone cell algorithm and the stand-alone pufit algorithm. The other two show combined algorithms each formed by requiring that the event satisfy both a fixed threshold (either 65 GeV or 70 GeV as shown in the legend) for the cell algorithm and a pufit threshold which varies along the curve. In each plot the background acceptance fractions and the efficiencies are relative to those of the pufit $E_T^{miss} > 110\,$GeV trigger and thus can be greater than one. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger while the cross indicates the performance of the combined (pufit $E_T^{miss}>110\,$GeV and cell $E_T^{miss}>50\,$GeV) trigger.
Relative background acceptance fraction vs. relative efficiency for two different $p_T(\mu\mu)>150\,$GeV threshold for data recorded in the year 2018. Two of the curves show the performance of the stand-alone cell algorithm and the stand-alone pufit algorithm. The other two show combined algorithms each formed by requiring that the event satisfy both a fixed threshold (either 65 GeV or 70 GeV as shown in the legend) for the cell algorithm and a pufit threshold which varies along the curve. In each plot the background acceptance fractions and the efficiencies are relative to those of the pufit $E_T^{miss} > 110\,$GeV trigger and thus can be greater than one. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger while the cross indicates the performance of the combined (pufit $E_T^{miss}>110\,$GeV and cell $E_T^{miss}>50\,$GeV) trigger.
Relative background acceptance fraction vs. relative efficiency for two different $p_T(\mu\mu)>150\,$GeV threshold for data recorded in the year 2018. Two of the curves show the performance of the stand-alone cell algorithm and the stand-alone pufit algorithm. The other two show combined algorithms each formed by requiring that the event satisfy both a fixed threshold (either 65 GeV or 70 GeV as shown in the legend) for the cell algorithm and a pufit threshold which varies along the curve. In each plot the background acceptance fractions and the efficiencies are relative to those of the pufit $E_T^{miss} > 110\,$GeV trigger and thus can be greater than one. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger while the cross indicates the performance of the combined (pufit $E_T^{miss}>110\,$GeV and cell $E_T^{miss}>50\,$GeV) trigger.
Relative background acceptance fraction vs. relative efficiency for two different $p_T(\mu\mu)>150\,$GeV threshold for data recorded in the year 2018. Two of the curves show the performance of the stand-alone cell algorithm and the stand-alone pufit algorithm. The other two show combined algorithms each formed by requiring that the event satisfy both a fixed threshold (either 65 GeV or 70 GeV as shown in the legend) for the cell algorithm and a pufit threshold which varies along the curve. In each plot the background acceptance fractions and the efficiencies are relative to those of the pufit $E_T^{miss} > 110\,$GeV trigger and thus can be greater than one. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger while the cross indicates the performance of the combined (pufit $E_T^{miss}>110\,$GeV and cell $E_T^{miss}>50\,$GeV) trigger.
Relative background acceptance fraction vs. relative efficiency for two different $p_T(\mu\mu)>150\,$GeV threshold for data recorded in the year 2018. Two of the curves show the performance of the stand-alone cell algorithm and the stand-alone pufit algorithm. The other two show combined algorithms each formed by requiring that the event satisfy both a fixed threshold (either 65 GeV or 70 GeV as shown in the legend) for the cell algorithm and a pufit threshold which varies along the curve. In each plot the background acceptance fractions and the efficiencies are relative to those of the pufit $E_T^{miss} > 110\,$GeV trigger and thus can be greater than one. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger while the cross indicates the performance of the combined (pufit $E_T^{miss}>110\,$GeV and cell $E_T^{miss}>50\,$GeV) trigger.
Relative background acceptance fraction vs. relative efficiency for two different $p_T(\mu\mu)>150\,$GeV threshold for data recorded in the year 2018. Two of the curves show the performance of the stand-alone cell algorithm and the stand-alone pufit algorithm. The other two show combined algorithms each formed by requiring that the event satisfy both a fixed threshold (either 65 GeV or 70 GeV as shown in the legend) for the cell algorithm and a pufit threshold which varies along the curve. In each plot the background acceptance fractions and the efficiencies are relative to those of the pufit $E_T^{miss} > 110\,$GeV trigger and thus can be greater than one. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger while the cross indicates the performance of the combined (pufit $E_T^{miss}>110\,$GeV and cell $E_T^{miss}>50\,$GeV) trigger.
Relative background acceptance fraction vs. relative efficiency for two different $p_T(\mu\mu)>150\,$GeV threshold for data recorded in the year 2018. Two of the curves show the performance of the stand-alone cell algorithm and the stand-alone pufit algorithm. The other two show combined algorithms each formed by requiring that the event satisfy both a fixed threshold (either 65 GeV or 70 GeV as shown in the legend) for the cell algorithm and a pufit threshold which varies along the curve. In each plot the background acceptance fractions and the efficiencies are relative to those of the pufit $E_T^{miss} > 110\,$GeV trigger and thus can be greater than one. The diamond indicates the performance of the pufit $E_T^{miss}>110\,$GeV trigger while the cross indicates the performance of the combined (pufit $E_T^{miss}>110\,$GeV and cell $E_T^{miss}>50\,$GeV) trigger.
Turn-on efficiency curves are shown for $Z\rightarrow\mu\mu$ events for three algorithms: the cell algorithm alone, the pufit algorithm alone and the combined cell+pufit algorithm. The thresholds are set such that the algorithms have equal rates, and the data were recorded in the year 2018. Here the trigger efficiency is shown with respect to $p_T(\mu\mu)$.
Turn-on efficiency curves are shown for $Z\rightarrow\mu\mu$ events for three algorithms: the cell algorithm alone, the pufit algorithm alone and the combined cell+pufit algorithm. The thresholds are set such that the algorithms have equal rates, and the data were recorded in the year 2018. Here the trigger efficiency is shown with respect to the offline $E_T^{miss}$ calculation with muons treated as being invisible.
Full-chain trigger efficiencies for each year as a function of $p_T(\mu\mu)$. The efficiency corresponds to that of the lowest unprescaled trigger that is adjusted throughout each year.
Full-chain trigger efficiencies for 2015, 2016, 2017 and 2018 as a function of $\langle\mu\rangle$ for $p_T(\mu\mu)>150$ GeV. The efficiency corresponds to that of the lowest unprescaled trigger that is adjusted throughout the year.
A search is presented for displaced production of Higgs bosons or $Z$ bosons, originating from the decay of a neutral long-lived particle (LLP) and reconstructed in the decay modes $H\rightarrow \gamma\gamma$ and $Z\rightarrow ee$. The analysis uses the full Run 2 data set of proton$-$proton collisions delivered by the LHC at an energy of $\sqrt{s}=13$ TeV between 2015 and 2018 and recorded by the ATLAS detector, corresponding to an integrated luminosity of 139 fb$^{-1}$. Exploiting the capabilities of the ATLAS liquid argon calorimeter to precisely measure the arrival times and trajectories of electromagnetic objects, the analysis searches for the signature of pairs of photons or electrons which arise from a common displaced vertex and which arrive after some delay at the calorimeter. The results are interpreted in a gauge-mediated supersymmetry breaking model with pair-produced higgsinos that decay to LLPs, and each LLP subsequently decays into either a Higgs boson or a $Z$ boson. The final state includes at least two particles that escape direct detection, giving rise to missing transverse momentum. No significant excess is observed above the background expectation. The results are used to set upper limits on the cross section for higgsino pair production, up to a $\tilde\chi^0_1$ mass of 369 (704) GeV for decays with 100% branching ratio of $\tilde\chi^0_1$ to Higgs ($Z$) bosons for a $\tilde\chi^0_1$ lifetime of 2 ns. A model-independent limit is also set on the production of pairs of photons or electrons with a significant delay in arrival at the calorimeter.
Average timing distributions for SR data and the estimated background as determined by the background-only fit, in each of the five exclusive $\rho$ categories. For comparison, the expected timing shapes for a few different signal models are superimposed, with each model labeled by the values of the $\tilde\chi^0_1$ mass and lifetime, as well as decay mode. To provide some indication of the variations in signal yield and shape, three signal models are shown for each of the $\tilde\chi^0_1$ decay modes, namely $\tilde\chi^0_1$ $\rightarrow$ $H \tilde G$ and $\tilde\chi^0_1$ $\rightarrow$ $Z \tilde G$. The models shown include a rather low $\tilde\chi^0_1$ mass value of 135 GeV for lifetimes of either 2 ns or 10 ns, and a higher $\tilde\chi^0_1$ mass value which is near the 95% CL exclusion limit for each decay mode for a lifetime of 2 ns. Each signal model is shown with the signal normalization corresponding to a BR value of unity for the decay mode in question.
Average timing distributions for SR data and the estimated background as determined by the background-only fit, in each of the five exclusive $\rho$ categories. For comparison, the expected timing shapes for a few different signal models are superimposed, with each model labeled by the values of the $\tilde\chi^0_1$ mass and lifetime, as well as decay mode. To provide some indication of the variations in signal yield and shape, three signal models are shown for each of the $\tilde\chi^0_1$ decay modes, namely $\tilde\chi^0_1$ $\rightarrow$ $H \tilde G$ and $\tilde\chi^0_1$ $\rightarrow$ $Z \tilde G$. The models shown include a rather low $\tilde\chi^0_1$ mass value of 135 GeV for lifetimes of either 2 ns or 10 ns, and a higher $\tilde\chi^0_1$ mass value which is near the 95% CL exclusion limit for each decay mode for a lifetime of 2 ns. Each signal model is shown with the signal normalization corresponding to a BR value of unity for the decay mode in question.
Average timing distributions for SR data and the estimated background as determined by the background-only fit, in each of the five exclusive $\rho$ categories. For comparison, the expected timing shapes for a few different signal models are superimposed, with each model labeled by the values of the $\tilde\chi^0_1$ mass and lifetime, as well as decay mode. To provide some indication of the variations in signal yield and shape, three signal models are shown for each of the $\tilde\chi^0_1$ decay modes, namely $\tilde\chi^0_1$ $\rightarrow$ $H \tilde G$ and $\tilde\chi^0_1$ $\rightarrow$ $Z \tilde G$. The models shown include a rather low $\tilde\chi^0_1$ mass value of 135 GeV for lifetimes of either 2 ns or 10 ns, and a higher $\tilde\chi^0_1$ mass value which is near the 95% CL exclusion limit for each decay mode for a lifetime of 2 ns. Each signal model is shown with the signal normalization corresponding to a BR value of unity for the decay mode in question.
Average timing distributions for SR data and the estimated background as determined by the background-only fit, in each of the five exclusive $\rho$ categories. For comparison, the expected timing shapes for a few different signal models are superimposed, with each model labeled by the values of the $\tilde\chi^0_1$ mass and lifetime, as well as decay mode. To provide some indication of the variations in signal yield and shape, three signal models are shown for each of the $\tilde\chi^0_1$ decay modes, namely $\tilde\chi^0_1$ $\rightarrow$ $H \tilde G$ and $\tilde\chi^0_1$ $\rightarrow$ $Z \tilde G$. The models shown include a rather low $\tilde\chi^0_1$ mass value of 135 GeV for lifetimes of either 2 ns or 10 ns, and a higher $\tilde\chi^0_1$ mass value which is near the 95% CL exclusion limit for each decay mode for a lifetime of 2 ns. Each signal model is shown with the signal normalization corresponding to a BR value of unity for the decay mode in question.
Average timing distributions for SR data and the estimated background as determined by the background-only fit, in each of the five exclusive $\rho$ categories. For comparison, the expected timing shapes for a few different signal models are superimposed, with each model labeled by the values of the $\tilde\chi^0_1$ mass and lifetime, as well as decay mode. To provide some indication of the variations in signal yield and shape, three signal models are shown for each of the $\tilde\chi^0_1$ decay modes, namely $\tilde\chi^0_1$ $\rightarrow$ $H \tilde G$ and $\tilde\chi^0_1$ $\rightarrow$ $Z \tilde G$. The models shown include a rather low $\tilde\chi^0_1$ mass value of 135 GeV for lifetimes of either 2 ns or 10 ns, and a higher $\tilde\chi^0_1$ mass value which is near the 95% CL exclusion limit for each decay mode for a lifetime of 2 ns. Each signal model is shown with the signal normalization corresponding to a BR value of unity for the decay mode in question.
The 95% CL limits on $\sigma(pp \rightarrow \tilde\chi^0_1 \tilde\chi^0_1$) in fb as a function of $\tilde\chi^0_1$ mass (left) and $\tilde\chi^0_1$ lifetime (right), for the different decay modes of $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow H + \tilde{G}$) = 1 (top) and $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow Z +\tilde{G}$) = 1 (bottom). For the limits as a function of mass (lifetime), several signal models with varying lifetime (mass) are overlaid for comparison. Included are the theoretical expectations from higgsino production for each mass hypothesis, calculated from a GMSB SUSY model that assumes nearly degenerate $\tilde\chi^0_1$, $\tilde\chi^\pm_1$, and $\tilde\chi^0_2$.
The 95% CL limits on $\sigma(pp \rightarrow \tilde\chi^0_1 \tilde\chi^0_1$) in fb as a function of $\tilde\chi^0_1$ mass (left) and $\tilde\chi^0_1$ lifetime (right), for the different decay modes of $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow H + \tilde{G}$) = 1 (top) and $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow Z +\tilde{G}$) = 1 (bottom). For the limits as a function of mass (lifetime), several signal models with varying lifetime (mass) are overlaid for comparison. Included are the theoretical expectations from higgsino production for each mass hypothesis, calculated from a GMSB SUSY model that assumes nearly degenerate $\tilde\chi^0_1$, $\tilde\chi^\pm_1$, and $\tilde\chi^0_2$.
The 95% CL limits on $\sigma(pp \rightarrow \tilde\chi^0_1 \tilde\chi^0_1$) in fb as a function of $\tilde\chi^0_1$ mass (left) and $\tilde\chi^0_1$ lifetime (right), for the different decay modes of $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow H + \tilde{G}$) = 1 (top) and $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow Z +\tilde{G}$) = 1 (bottom). For the limits as a function of mass (lifetime), several signal models with varying lifetime (mass) are overlaid for comparison. Included are the theoretical expectations from higgsino production for each mass hypothesis, calculated from a GMSB SUSY model that assumes nearly degenerate $\tilde\chi^0_1$, $\tilde\chi^\pm_1$, and $\tilde\chi^0_2$.
The 95% CL limits on $\sigma(pp \rightarrow \tilde\chi^0_1 \tilde\chi^0_1$) in fb as a function of $\tilde\chi^0_1$ mass (left) and $\tilde\chi^0_1$ lifetime (right), for the different decay modes of $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow H + \tilde{G}$) = 1 (top) and $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow Z +\tilde{G}$) = 1 (bottom). For the limits as a function of mass (lifetime), several signal models with varying lifetime (mass) are overlaid for comparison. Included are the theoretical expectations from higgsino production for each mass hypothesis, calculated from a GMSB SUSY model that assumes nearly degenerate $\tilde\chi^0_1$, $\tilde\chi^\pm_1$, and $\tilde\chi^0_2$.
The 95% CL limits on $\sigma(pp \rightarrow \tilde\chi^0_1 \tilde\chi^0_1$) in fb as a function of $\tilde\chi^0_1$ mass (left) and $\tilde\chi^0_1$ lifetime (right), for the different decay modes of $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow H + \tilde{G}$) = 1 (top) and $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow Z +\tilde{G}$) = 1 (bottom). For the limits as a function of mass (lifetime), several signal models with varying lifetime (mass) are overlaid for comparison. Included are the theoretical expectations from higgsino production for each mass hypothesis, calculated from a GMSB SUSY model that assumes nearly degenerate $\tilde\chi^0_1$, $\tilde\chi^\pm_1$, and $\tilde\chi^0_2$.
The 95% CL limits on $\sigma(pp \rightarrow \tilde\chi^0_1 \tilde\chi^0_1$) in fb as a function of $\tilde\chi^0_1$ mass (left) and $\tilde\chi^0_1$ lifetime (right), for the different decay modes of $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow H + \tilde{G}$) = 1 (top) and $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow Z +\tilde{G}$) = 1 (bottom). For the limits as a function of mass (lifetime), several signal models with varying lifetime (mass) are overlaid for comparison. Included are the theoretical expectations from higgsino production for each mass hypothesis, calculated from a GMSB SUSY model that assumes nearly degenerate $\tilde\chi^0_1$, $\tilde\chi^\pm_1$, and $\tilde\chi^0_2$.
The 95% CL limits on $\sigma(pp \rightarrow \tilde\chi^0_1 \tilde\chi^0_1$) in fb as a function of $\tilde\chi^0_1$ mass (left) and $\tilde\chi^0_1$ lifetime (right), for the different decay modes of $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow H + \tilde{G}$) = 1 (top) and $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow Z +\tilde{G}$) = 1 (bottom). For the limits as a function of mass (lifetime), several signal models with varying lifetime (mass) are overlaid for comparison. Included are the theoretical expectations from higgsino production for each mass hypothesis, calculated from a GMSB SUSY model that assumes nearly degenerate $\tilde\chi^0_1$, $\tilde\chi^\pm_1$, and $\tilde\chi^0_2$.
The 95% CL limits on $\sigma(pp \rightarrow \tilde\chi^0_1 \tilde\chi^0_1$) in fb as a function of $\tilde\chi^0_1$ mass (left) and $\tilde\chi^0_1$ lifetime (right), for the different decay modes of $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow H + \tilde{G}$) = 1 (top) and $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow Z +\tilde{G}$) = 1 (bottom). For the limits as a function of mass (lifetime), several signal models with varying lifetime (mass) are overlaid for comparison. Included are the theoretical expectations from higgsino production for each mass hypothesis, calculated from a GMSB SUSY model that assumes nearly degenerate $\tilde\chi^0_1$, $\tilde\chi^\pm_1$, and $\tilde\chi^0_2$.
The 95% CL limits on $\sigma(pp \rightarrow \tilde\chi^0_1 \tilde\chi^0_1$) in fb as a function of $\tilde\chi^0_1$ mass (left) and $\tilde\chi^0_1$ lifetime (right), for the different decay modes of $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow H + \tilde{G}$) = 1 (top) and $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow Z +\tilde{G}$) = 1 (bottom). For the limits as a function of mass (lifetime), several signal models with varying lifetime (mass) are overlaid for comparison. Included are the theoretical expectations from higgsino production for each mass hypothesis, calculated from a GMSB SUSY model that assumes nearly degenerate $\tilde\chi^0_1$, $\tilde\chi^\pm_1$, and $\tilde\chi^0_2$.
The 95% CL limits on $\sigma(pp \rightarrow \tilde\chi^0_1 \tilde\chi^0_1$) in fb as a function of $\tilde\chi^0_1$ mass (left) and $\tilde\chi^0_1$ lifetime (right), for the different decay modes of $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow H + \tilde{G}$) = 1 (top) and $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow Z +\tilde{G}$) = 1 (bottom). For the limits as a function of mass (lifetime), several signal models with varying lifetime (mass) are overlaid for comparison. Included are the theoretical expectations from higgsino production for each mass hypothesis, calculated from a GMSB SUSY model that assumes nearly degenerate $\tilde\chi^0_1$, $\tilde\chi^\pm_1$, and $\tilde\chi^0_2$.
The 95% CL limits on $\sigma(pp \rightarrow \tilde\chi^0_1 \tilde\chi^0_1$) in fb as a function of $\tilde\chi^0_1$ mass (left) and $\tilde\chi^0_1$ lifetime (right), for the different decay modes of $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow H + \tilde{G}$) = 1 (top) and $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow Z +\tilde{G}$) = 1 (bottom). For the limits as a function of mass (lifetime), several signal models with varying lifetime (mass) are overlaid for comparison. Included are the theoretical expectations from higgsino production for each mass hypothesis, calculated from a GMSB SUSY model that assumes nearly degenerate $\tilde\chi^0_1$, $\tilde\chi^\pm_1$, and $\tilde\chi^0_2$.
The 95% CL limits on $\sigma(pp \rightarrow \tilde\chi^0_1 \tilde\chi^0_1$) in fb as a function of $\tilde\chi^0_1$ mass (left) and $\tilde\chi^0_1$ lifetime (right), for the different decay modes of $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow H + \tilde{G}$) = 1 (top) and $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow Z +\tilde{G}$) = 1 (bottom). For the limits as a function of mass (lifetime), several signal models with varying lifetime (mass) are overlaid for comparison. Included are the theoretical expectations from higgsino production for each mass hypothesis, calculated from a GMSB SUSY model that assumes nearly degenerate $\tilde\chi^0_1$, $\tilde\chi^\pm_1$, and $\tilde\chi^0_2$.
The 95% CL limits on $\sigma(pp \rightarrow \tilde\chi^0_1 \tilde\chi^0_1$) in fb as a function of $\tilde\chi^0_1$ mass (left) and $\tilde\chi^0_1$ lifetime (right), for the different decay modes of $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow H + \tilde{G}$) = 1 (top) and $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow Z +\tilde{G}$) = 1 (bottom). For the limits as a function of mass (lifetime), several signal models with varying lifetime (mass) are overlaid for comparison. Included are the theoretical expectations from higgsino production for each mass hypothesis, calculated from a GMSB SUSY model that assumes nearly degenerate $\tilde\chi^0_1$, $\tilde\chi^\pm_1$, and $\tilde\chi^0_2$.
The 95% CL limits on $\sigma(pp \rightarrow \tilde\chi^0_1 \tilde\chi^0_1$) in fb as a function of $\tilde\chi^0_1$ mass (left) and $\tilde\chi^0_1$ lifetime (right), for the different decay modes of $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow H + \tilde{G}$) = 1 (top) and $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow Z +\tilde{G}$) = 1 (bottom). For the limits as a function of mass (lifetime), several signal models with varying lifetime (mass) are overlaid for comparison. Included are the theoretical expectations from higgsino production for each mass hypothesis, calculated from a GMSB SUSY model that assumes nearly degenerate $\tilde\chi^0_1$, $\tilde\chi^\pm_1$, and $\tilde\chi^0_2$.
The 95% CL limits on $\sigma(pp \rightarrow \tilde\chi^0_1 \tilde\chi^0_1$) in fb as a function of $\tilde\chi^0_1$ mass (left) and $\tilde\chi^0_1$ lifetime (right), for the different decay modes of $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow H + \tilde{G}$) = 1 (top) and $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow Z +\tilde{G}$) = 1 (bottom). For the limits as a function of mass (lifetime), several signal models with varying lifetime (mass) are overlaid for comparison. Included are the theoretical expectations from higgsino production for each mass hypothesis, calculated from a GMSB SUSY model that assumes nearly degenerate $\tilde\chi^0_1$, $\tilde\chi^\pm_1$, and $\tilde\chi^0_2$.
The 95% CL limits on $\sigma(pp \rightarrow \tilde\chi^0_1 \tilde\chi^0_1$) in fb as a function of $\tilde\chi^0_1$ mass (left) and $\tilde\chi^0_1$ lifetime (right), for the different decay modes of $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow H + \tilde{G}$) = 1 (top) and $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow Z +\tilde{G}$) = 1 (bottom). For the limits as a function of mass (lifetime), several signal models with varying lifetime (mass) are overlaid for comparison. Included are the theoretical expectations from higgsino production for each mass hypothesis, calculated from a GMSB SUSY model that assumes nearly degenerate $\tilde\chi^0_1$, $\tilde\chi^\pm_1$, and $\tilde\chi^0_2$.
The 95% CL limits on $\sigma(pp \rightarrow \tilde\chi^0_1 \tilde\chi^0_1$) in fb as a function of $\tilde\chi^0_1$ branching ratio to the SM Higgs boson, where the assumed cross-section is for higgsino production, and $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow Z +\tilde{G}$) = 1 - $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow H + \tilde{G}$). Several signal hypotheses are overlaid that are labelled by the $\tilde\chi^0_1$ mass, all with a fixed $\tilde\chi^0_1$ lifetime of 2 ns.
The 95% CL limits on $\sigma(pp \rightarrow \tilde\chi^0_1 \tilde\chi^0_1$) in fb as a function of $\tilde\chi^0_1$ branching ratio to the SM Higgs boson, where the assumed cross-section is for higgsino production, and $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow Z +\tilde{G}$) = 1 - $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow H + \tilde{G}$). Several signal hypotheses are overlaid that are labelled by the $\tilde\chi^0_1$ mass, all with a fixed $\tilde\chi^0_1$ lifetime of 2 ns.
The 95% CL limits on $\sigma(pp \rightarrow \tilde\chi^0_1 \tilde\chi^0_1$) in fb as a function of $\tilde\chi^0_1$ branching ratio to the SM Higgs boson, where the assumed cross-section is for higgsino production, and $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow Z +\tilde{G}$) = 1 - $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow H + \tilde{G}$). Several signal hypotheses are overlaid that are labelled by the $\tilde\chi^0_1$ mass, all with a fixed $\tilde\chi^0_1$ lifetime of 2 ns.
The 95% CL limits on $\sigma(pp \rightarrow \tilde\chi^0_1 \tilde\chi^0_1$) in fb as a function of $\tilde\chi^0_1$ branching ratio to the SM Higgs boson, where the assumed cross-section is for higgsino production, and $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow Z +\tilde{G}$) = 1 - $\mathcal{B}$($\tilde\chi^0_1$ $\rightarrow H + \tilde{G}$). Several signal hypotheses are overlaid that are labelled by the $\tilde\chi^0_1$ mass, all with a fixed $\tilde\chi^0_1$ lifetime of 2 ns.
The 95% CL exclusion limits on the target signal hypothesis, for $\tilde\chi^0_1$ lifetime in ns as a function of $\tilde\chi^0_1$ mass in GeV. The overlaid curves correspond to different decay hypotheses, where the assumed cross-section is for higgsino production, and the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ or $Z + \tilde{G}$ such that $\mathcal{B}(H + \tilde{G}) + \mathcal{B}(Z + \tilde{G})$ = 100%. The curve shown in red represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $Z + \tilde{G}$ with 100% branching ratio. The curve shown in blue represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ with 100% branching ratio.
The 95% CL exclusion limits on the target signal hypothesis, for $\tilde\chi^0_1$ lifetime in ns as a function of $\tilde\chi^0_1$ mass in GeV. The overlaid curves correspond to different decay hypotheses, where the assumed cross-section is for higgsino production, and the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ or $Z + \tilde{G}$ such that $\mathcal{B}(H + \tilde{G}) + \mathcal{B}(Z + \tilde{G})$ = 100%. The curve shown in red represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $Z + \tilde{G}$ with 100% branching ratio. The curve shown in blue represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ with 100% branching ratio.
The 95% CL exclusion limits on the target signal hypothesis, for $\tilde\chi^0_1$ lifetime in ns as a function of $\tilde\chi^0_1$ mass in GeV. The overlaid curves correspond to different decay hypotheses, where the assumed cross-section is for higgsino production, and the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ or $Z + \tilde{G}$ such that $\mathcal{B}(H + \tilde{G}) + \mathcal{B}(Z + \tilde{G})$ = 100%. The curve shown in red represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $Z + \tilde{G}$ with 100% branching ratio. The curve shown in blue represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ with 100% branching ratio.
The 95% CL exclusion limits on the target signal hypothesis, for $\tilde\chi^0_1$ lifetime in ns as a function of $\tilde\chi^0_1$ mass in GeV. The overlaid curves correspond to different decay hypotheses, where the assumed cross-section is for higgsino production, and the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ or $Z + \tilde{G}$ such that $\mathcal{B}(H + \tilde{G}) + \mathcal{B}(Z + \tilde{G})$ = 100%. The curve shown in red represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $Z + \tilde{G}$ with 100% branching ratio. The curve shown in blue represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ with 100% branching ratio.
The 95% CL exclusion limits on the target signal hypothesis, for $\tilde\chi^0_1$ lifetime in ns as a function of $\tilde\chi^0_1$ mass in GeV. The overlaid curves correspond to different decay hypotheses, where the assumed cross-section is for higgsino production, and the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ or $Z + \tilde{G}$ such that $\mathcal{B}(H + \tilde{G}) + \mathcal{B}(Z + \tilde{G})$ = 100%. The curve shown in red represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $Z + \tilde{G}$ with 100% branching ratio. The curve shown in blue represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ with 100% branching ratio.
The 95% CL exclusion limits on the target signal hypothesis, for $\tilde\chi^0_1$ lifetime in ns as a function of $\tilde\chi^0_1$ mass in GeV. The overlaid curves correspond to different decay hypotheses, where the assumed cross-section is for higgsino production, and the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ or $Z + \tilde{G}$ such that $\mathcal{B}(H + \tilde{G}) + \mathcal{B}(Z + \tilde{G})$ = 100%. The curve shown in red represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $Z + \tilde{G}$ with 100% branching ratio. The curve shown in blue represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ with 100% branching ratio.
The 95% CL exclusion limits on the target signal hypothesis, for $\tilde\chi^0_1$ lifetime in ns as a function of $\tilde\chi^0_1$ mass in GeV. The overlaid curves correspond to different decay hypotheses, where the assumed cross-section is for higgsino production, and the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ or $Z + \tilde{G}$ such that $\mathcal{B}(H + \tilde{G}) + \mathcal{B}(Z + \tilde{G})$ = 100%. The curve shown in red represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $Z + \tilde{G}$ with 100% branching ratio. The curve shown in blue represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ with 100% branching ratio.
The 95% CL exclusion limits on the target signal hypothesis, for $\tilde\chi^0_1$ lifetime in ns as a function of $\tilde\chi^0_1$ mass in GeV. The overlaid curves correspond to different decay hypotheses, where the assumed cross-section is for higgsino production, and the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ or $Z + \tilde{G}$ such that $\mathcal{B}(H + \tilde{G}) + \mathcal{B}(Z + \tilde{G})$ = 100%. The curve shown in red represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $Z + \tilde{G}$ with 100% branching ratio. The curve shown in blue represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ with 100% branching ratio.
The 95% CL exclusion limits on the target signal hypothesis, for $\tilde\chi^0_1$ lifetime in ns as a function of $\tilde\chi^0_1$ mass in GeV. The overlaid curves correspond to different decay hypotheses, where the assumed cross-section is for higgsino production, and the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ or $Z + \tilde{G}$ such that $\mathcal{B}(H + \tilde{G}) + \mathcal{B}(Z + \tilde{G})$ = 100%. The curve shown in red represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $Z + \tilde{G}$ with 100% branching ratio. The curve shown in blue represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ with 100% branching ratio.
The 95% CL exclusion limits on the target signal hypothesis, for $\tilde\chi^0_1$ lifetime in ns as a function of $\tilde\chi^0_1$ mass in GeV. The overlaid curves correspond to different decay hypotheses, where the assumed cross-section is for higgsino production, and the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ or $Z + \tilde{G}$ such that $\mathcal{B}(H + \tilde{G}) + \mathcal{B}(Z + \tilde{G})$ = 100%. The curve shown in red represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $Z + \tilde{G}$ with 100% branching ratio. The curve shown in blue represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ with 100% branching ratio.
The 95% CL exclusion limits on the target signal hypothesis, for $\tilde\chi^0_1$ lifetime in ns as a function of $\tilde\chi^0_1$ mass in GeV. The overlaid curves correspond to different decay hypotheses, where the assumed cross-section is for higgsino production, and the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ or $Z + \tilde{G}$ such that $\mathcal{B}(H + \tilde{G}) + \mathcal{B}(Z + \tilde{G})$ = 100%. The curve shown in red represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $Z + \tilde{G}$ with 100% branching ratio. The curve shown in blue represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ with 100% branching ratio.
The 95% CL exclusion limits on the target signal hypothesis, for $\tilde\chi^0_1$ lifetime in ns as a function of $\tilde\chi^0_1$ mass in GeV. The overlaid curves correspond to different decay hypotheses, where the assumed cross-section is for higgsino production, and the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ or $Z + \tilde{G}$ such that $\mathcal{B}(H + \tilde{G}) + \mathcal{B}(Z + \tilde{G})$ = 100%. The curve shown in red represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $Z + \tilde{G}$ with 100% branching ratio. The curve shown in blue represents the decay hypothesis where the $\tilde\chi^0_1$ decays to $H + \tilde{G}$ with 100% branching ratio.
Cutflow for an example higgsino signal with mass 225 GeV and lifetime 10 ns, in the H decay mode. Acceptance is defined at truth level, and efficiency compares the events passing at reconstruction level with respect to truth.
Cutflow for an example higgsino signal with mass 225 GeV and lifetime 10 ns, in the Z decay mode. Acceptance is defined at truth level, and efficiency compares the events passing at reconstruction level with respect to truth.
Cutflow for an example higgsino signal with mass 225 GeV and lifetime 2 ns, in the H decay mode. Acceptance is defined at truth level, and efficiency compares the events passing at reconstruction level with respect to truth.
Cutflow for an example higgsino signal with mass 225 GeV and lifetime 2 ns, in the Z decay mode. Acceptance is defined at truth level, and efficiency compares the events passing at reconstruction level with respect to truth.
Acceptance across the H decay mode signal grid, calculated using truth information. The selection applied corresponds to the model-independent signal region (i.e. the standard SR with $t_{\text{avg}$ > 0.9 ns).
Acceptance across the Z decay mode signal grid, calculated using truth information. The selection applied corresponds to the model-independent signal region (i.e. the standard SR with $t_{\text{avg}$ > 0.9 ns).
Efficiency across the H decay mode signal grid, calculated using reco information. The selection applied corresponds to the model-independent signal region (i.e. the standard SR with $t_{\text{avg}$ > 0.9 ns). Here, the numerator is the signal yield passing the reco selection and the denominator is the signal yield passing the truth selection.
Efficiency across the Z decay mode signal grid, calculated using reco information. The selection applied corresponds to the model-independent signal region (i.e. the standard SR with $t_{\text{avg}$ > 0.9 ns). Here, the numerator is the signal yield passing the reco selection and the denominator is the signal yield passing the truth selection.
The production of single top quarks and top antiquarks via the $t$-channel exchange of a virtual $W$ boson is measured in proton-proton collisions at a centre-of-mass energy of 13 TeV at the LHC using $140\,\mathrm{fb^{-1}}$ of ATLAS data. The total cross-sections are determined to be $\sigma(tq)=137^{+8}_{-8}\,\mathrm{pb}$ and $\sigma(\bar{t}q)=84^{+6}_{-5}\,\mathrm{pb}$ for top-quark and top-antiquark production, respectively. The combined cross-section is found to be $\sigma(tq+\bar{t}q)=221^{+13}_{-13}\,\mathrm{pb}$ and the cross-section ratio is $R_{t}=\sigma(tq)/\sigma(\bar{t}q)=1.636^{+0.036}_{-0.034}$. The predictions at next-to-next-to-leading-order in quantum chromodynamics are in good agreement with these measurements. The predicted value of $R_{t}$ using different sets of parton distribution functions is compared with the measured value, demonstrating the potential to further constrain the functions when using this result in global fits. The measured cross-sections are interpreted in an effective field theory approach, setting limits at the 95% confidence level on the strength of a four-quark operator and an operator coupling the third quark generation to the Higgs boson doublet: $-0.37 < C_{Qq}^{3,1}/\Lambda^2 < 0.06$ and $-0.87 < C_{\phi Q}^{3}/\Lambda^2 < 1.42$. The constraint $|V_{tb}|>0.95$ at the 95% confidence level is derived from the measured value of $\sigma(tq+\bar{t}q)$. In a more general approach, pairs of CKM matrix elements involving top quarks are simultaneously constrained, leading to confidence contours in the corresponding two-dimensional parameter spaces.
The 17 variables used for the training of the NN ordered by their discriminating power. The jet that is not \(b\)-tagged is referred to as the untagged jet. The charged lepton is denoted \(\ell\). The sphericity tensor \(S^{\alpha\beta}\) used to define the sphericity \(S\) is formed with the three-momenta \(\vec{p}_i\) of the reconstructed objects, namely the jets, the charged lepton and the reconstructed neutrino. The tensor is given by \(S^{\alpha\beta}=\frac{\sum_i p_i^\alpha p_i^\beta}{\sum_i |\vec{p}_i|^2}\) where \(\alpha\) and \(\beta\) correspond to the spatial components $x$, $y$ and $z$.
The impact of different groups of systematic uncertainties on the \(\sigma(tq)\) , \(\sigma(\bar t q)\), \(\sigma(tq + \bar t q)\) and \(R_t\), given in %.
The impact of the eight most important systematic uncertainties on the \(\sigma(tq)\) , \(\sigma(\bar t q)\) and \(\sigma(tq + \bar t q)\), given in %. The sequence of the uncertainties is given by the impact on \(\sigma(tq + \bar t q)\)
The impact of the eight most important systematic uncertainties on \(R_t\), in %.
The post-fit yields in the two SRs. All uncertainties applied in the analysis are included.
Limits on EFT parameters and Vtb extracted from the analysis. The upper and lower limits correspond to 95% CL.
Results of the main analysis.
Pre-fit distribution of the NN discriminant \(D_{\text{nn}}\) in SR plus.
Post-fit distribution of the NN discriminant \(D_{\text{nn}}\) in SR plus.
Post-fit distribution of the \(\Delta\phi(\vec{p}_{T}^{miss},\mu)\) variable in the muon-plus CR.
Pre-fit distribution of the NN discriminant \(D_{\text{nn}}\) in SR minus.
Post-fit distribution of the NN discriminant \(D_{\text{nn}}\) in SR minus.
Post-fit distribution of the \(\Delta\phi(\vec{p}_{T}^{miss},\mu)\) variable in the muon-minus CR.
Pre-fit distribution of the invariant mass of the untagged jet and the b-tagged jet, \(m(jb)\), in SR plus.
Pre-fit distribution of the absolute value of the pseudorapidity of the untagged jet, \(|\eta(j)|\), in SR plus.
Pre-fit distribution of the absolute value of the difference in \(p_{\text{T}}\) between the reconstructed W boson and the jet pair, \(|\Delta p_{\text{T}}(W, jb)|\), in SR plus.
Pre-fit distribution of the difference in azimuth angle between the reconstructed W boson and the jet pair, \(|\Delta\phi(W, jb)|\), in SR plus.
Pre-fit distribution of the invariant mass of the reconstructed top quark, \(m(t)\), in SR plus.
Pre-fit distribution of the absolute value of the difference in pseudorapidity between the charged lepton and the untagged jet, \(|\Delta\eta(\ell ,j)|\), SR plus.
Pre-fit distribution of the angular distance of the charged lepton and the untagged jet, \(\Delta R(\ell ,j)\), in SR plus.
Pre-fit distribution of the absolute value of the difference in pseudorapidity between the b-tagged jet and the charged lepton, \(|\Delta\eta(b,\ell )|\), in SR plus.
A search for long-lived particles decaying into an oppositely charged lepton pair, $\mu\mu$, $ee$, or $e\mu$, is presented using 32.8 fb$^{-1}$ of $pp$ collision data collected at $\sqrt{s}=13$ TeV by the ATLAS detector at the LHC. Candidate leptons are required to form a vertex, within the inner tracking volume of ATLAS, displaced from the primary $pp$ interaction region. No lepton pairs with an invariant mass greater than 12 GeV are observed, consistent with the background expectations derived from data. The detection efficiencies for generic resonances with lifetimes ($c\tau$) of 100-1000 mm decaying into a dilepton pair with masses between 0.1-1.0 TeV are presented as a function of $p_T$ and decay radius of the resonances to allow the extraction of upper limits on the cross sections for theoretical models. The result is also interpreted in a supersymmetric model in which the lightest neutralino, produced via squark-antisquark production, decays into $\ell^{+}\ell^{'-}\nu$ ($\ell, \ell^{'} = e$, $\mu$) with a finite lifetime due to the presence of R-parity violating couplings. Cross-section limits are presented for specific squark and neutralino masses. For a 700 GeV squark, neutralinos with masses of 50-500 GeV and mean proper lifetimes corresponding to $c\tau$ values between 1 mm to 6 m are excluded. For a 1.6 TeV squark, $c\tau$ values between 3 mm to 1 m are excluded for 1.3 TeV neutralinos.
<h1>Overview of reinterpretation material</h1><p><b>Important note:</b> A detailed explanation of the reinterpretation material can be found <a href="https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/SUSY-2017-04/hepdata_info.pdf">here</a>.<br/>Please read this stand-alone document before reinterpreting the search.</p><h2>Parameterized detection efficiencies</h2><p>RPV SUSY model: Tables <a href="90606?version=1&table=Table27">27</a> to <a href="90606?version=1&table=Table44">44</a><br/>Z' toy model: Tables <a href="90606?version=1&table=Table45">45</a> to <a href="90606?version=1&table=Table59">59</a></p><h2>Further material for the RPV SUSY model</h2><p>Acceptances: Tables <a href="90606?version=1&table=Table18">18</a> (ee), <a href="90606?version=1&table=Table19">19</a> (emu) and <a href="90606?version=1&table=Table20">20</a> (mumu)<br/>Detection efficiencies: Tables <a href="90606?version=1&table=Table21">21</a> (ee), <a href="90606?version=1&table=Table22">22</a> (emu) and <a href="90606?version=1&table=Table23">23</a> (mumu)<br/>Overall signal efficiencies: Tables <a href="90606?version=1&table=Table24">24</a> (ee), <a href="90606?version=1&table=Table25">25</a> (emu) and <a href="90606?version=1&table=Table26">26</a> (mumu)</p><h2>Further material for the Z' toy model</h2><p>Acceptances, detection efficiencies and overall signal efficiencies: Tables <a href="90606?version=1&table=Table60">60</a> (mZ' = 100 GeV) to <a href="90606?version=1&table=Table64">64</a> (mZ' = 1000 GeV)</p>
dRcos distribution of dimuon pairs (scaled) and dimuon vertices in the cosmic rays control region. The distribution of all dimuon pairs is scaled to the DV distribution.
Dependence of the overall signal efficiency on the transverse decay radius Rxy of the long-lived Z' for Z' -> ee. The error bars indicate the total uncertainties.
Dependence of the overall signal efficiency on the pT of the long-lived Z' for Z' -> ee. The error bars indicate the total uncertainties.
Dependence of the overall signal efficiency on the transverse decay radius Rxy of the long-lived Z' for Z' -> emu. The error bars indicate the total uncertainties.
Dependence of the overall signal efficiency on the pT of the long-lived Z' for Z' -> emu. The error bars indicate the total uncertainties.
Dependence of the overall signal efficiency on the transverse decay radius Rxy of the long-lived Z' for Z' -> mumu. The error bars indicate the total uncertainties.
Dependence of the overall signal efficiency on the pT of the long-lived Z' for Z' -> mumu. The error bars indicate the total uncertainties.
Overall signal efficiency as a function of the mean proper lifetime (ctau) of the neutralino for the lambda121 scenario of the RPV SUSY model. The error bars indicate the total uncertainties.
Overall signal efficiency as a function of the mean proper lifetime (ctau) of the neutralino for the lambda122 scenario of the RPV SUSY model. The error bars indicate the total uncertainties.
95% CL upper limits on the squark-antisquark production cross-section as a function of the mean proper lifetime (ctau) of the neutralino for the lambda121 scenario of the RPV SUSY model and a 700 GeV squark. The uncertainties of the expected limit indicate the +-1sigma variations.
95% CL upper limits on the squark-antisquark production cross-section as a function of the mean proper lifetime (ctau) of the neutralino for the lambda122 scenario of the RPV SUSY model and a 700 GeV squark. The uncertainties of the expected limit indicate the +-1sigma variations.
95% CL upper limits on the squark-antisquark production cross-section as a function of the mean proper lifetime (ctau) of the neutralino for the lambda121 scenario of the RPV SUSY model and a 1600 GeV squark. The uncertainties of the expected limit indicate the +-1sigma variations.
95% CL upper limits on the squark-antisquark production cross-section as a function of the mean proper lifetime (ctau) of the neutralino for the lambda122 scenario of the RPV SUSY model and a 1600 GeV squark. The uncertainties of the expected limit indicate the +-1sigma variations.
Fraction of detector volume covered by the material veto as a function of z and Rxy of the displaced dilepton vertex.
Fraction of detector volume covered by the disabled pixel modules veto veto as a function of z and Rxy of the displaced dilepton vertex.
Observed Rxy distribution of vertices composed of two non-leptonic tracks in a control sample in the data and the predicted distribution obtained from the event mixing. The error bars indicate the statistical uncertainties.
Rxy distributions of Kshort vertices from the large radius tracking in the data and background MC samples. Data has been normalised such that the total number of Kshort from the standard tracking in the data agrees with the total number of Kshort from the standard tracking in the MC. The error bars indicate the statistical uncertainties.
Acceptance per decay as a function of the mean proper lifetime (ctau) of the neutralino for neutralino -> eenu. The error bars indicate the statistical uncertainties.
Acceptance per decay as a function of the mean proper lifetime (ctau) of the neutralino for neutralino -> emunu. The error bars indicate the statistical uncertainties.
Acceptance per decay as a function of the mean proper lifetime (ctau) of the neutralino for neutralino -> mumunu. The error bars indicate the statistical uncertainties.
Detection efficiency per decay as a function of the mean proper lifetime (ctau) of the neutralino for neutralino -> eenu. The error bars indicate the total uncertainties.
Detection efficiency per decay as a function of the mean proper lifetime (ctau) of the neutralino for neutralino -> emunu. The error bars indicate the total uncertainties.
Detection efficiency per decay as a function of the mean proper lifetime (ctau) of the neutralino for neutralino -> mumunu. The error bars indicate the total uncertainties.
Overall signal efficiency (acceptance times efficiency) per decay as a function of the mean proper lifetime (ctau) of the neutralino for neutralino -> eenu. The error bars indicate the total uncertainties.
Overall signal efficiency (acceptance times efficiency) per decay as a function of the mean proper lifetime (ctau) of the neutralino for neutralino -> emunu. The error bars indicate the total uncertainties.
Overall signal efficiency (acceptance times efficiency) per decay as a function of the mean proper lifetime (ctau) of the neutralino for neutralino -> mumunu. The error bars indicate the total uncertainties.
Detection efficiency per decay for Rxy < 22 mm as a function of the invariant mass and pT of the electron pair in LLP -> eeX.
Detection efficiency per decay for 22 <= Rxy < 38 mm as a function of the invariant mass and pT of the electron pair in LLP -> eeX.
Detection efficiency per decay for 38 <= Rxy < 73 mm as a function of the invariant mass and pT of the electron pair in LLP -> eeX.
Detection efficiency per decay for 73 <= Rxy < 111 mm as a function of the invariant mass and pT of the electron pair in LLP -> eeX.
Detection efficiency per decay for 111 <= Rxy < 145 mm as a function of the invariant mass and pT of the electron pair in LLP -> eeX.
Detection efficiency per decay for 145 <= Rxy < 300 mm as a function of the invariant mass and pT of the electron pair in LLP -> eeX.
Detection efficiency per decay for Rxy < 22 mm as a function of the invariant mass and pT of the electron and muon pair in LLP -> emuX.
Detection efficiency per decay for 22 <= Rxy < 38 mm as a function of the invariant mass and pT of the electron and muon pair in LLP -> emuX.
Detection efficiency per decay for 38 <= Rxy < 73 mm as a function of the invariant mass and pT of the electron and muon pair in LLP -> emuX.
Detection efficiency per decay for 73 <= Rxy < 111 mm as a function of the invariant mass and pT of the electron and muon pair in LLP -> emuX.
Detection efficiency per decay for 111 <= Rxy < 145 mm as a function of the invariant mass and pT of the electron and muon pair in LLP -> emuX.
Detection efficiency per decay for 145 <= Rxy < 300 mm as a function of the invariant mass and pT of the electron and muon pair in LLP -> emuX.
Detection efficiency per decay for Rxy < 22 mm as a function of the invariant mass and pT of the muon pair in LLP -> mumuX.
Detection efficiency per decay for 22 <= Rxy < 38 mm as a function of the invariant mass and pT of the muon pair in LLP -> mumuX.
Detection efficiency per decay for 38 <= Rxy < 73 mm as a function of the invariant mass and pT of the muon pair in LLP -> mumuX.
Detection efficiency per decay for 73 <= Rxy < 111 mm as a function of the invariant mass and pT of the muon pair in LLP -> mumuX.
Detection efficiency per decay for 111 <= Rxy < 145 mm as a function of the invariant mass and pT of the muon pair in LLP -> mumuX.
Detection efficiency per decay for 145 <= Rxy < 300 mm as a function of the invariant mass and pT of the muon pair in LLP -> mumuX.
Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 100 GeV and LLP -> ee.
Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 100 GeV and LLP -> emu.
Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 100 GeV and LLP -> mumu.
Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 250 GeV and LLP -> ee.
Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 250 GeV and LLP -> emu.
Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 250 GeV and LLP -> mumu.
Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 500 GeV and LLP -> ee.
Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 500 GeV and LLP -> emu.
Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 500 GeV and LLP -> mumu.
Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 750 GeV and LLP -> ee.
Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 750 GeV and LLP -> emu.
Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 750 GeV and LLP -> mumu.
Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 1000 GeV and LLP -> ee.
Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 1000 GeV and LLP -> emu.
Detection efficiency per decay as a function of the transverse decay radius Rxy and the dilepton pT for a LLP mass of 1000 GeV and LLP -> mumu.
Acceptance, detection efficiency, and overall signal efficiency in the Z' toy model for mZ' = 100 GeV, three mean proper lifetimes (ctau) and the three decay modes of the Z'.
Acceptance, detection efficiency, and overall signal efficiency in the Z' toy model for mZ' = 250 GeV, three mean proper lifetimes (ctau) and the three decay modes of the Z'.
Acceptance, detection efficiency, and overall signal efficiency in the Z' toy model for mZ' = 500 GeV, three mean proper lifetimes (ctau) and the three decay modes of the Z'.
Acceptance, detection efficiency, and overall signal efficiency in the Z' toy model for mZ' = 750 GeV, three mean proper lifetimes (ctau) and the three decay modes of the Z'.
Acceptance, detection efficiency, and overall signal efficiency in the Z' toy model for mZ' = 1000 GeV, three mean proper lifetimes (ctau) and the three decay modes of the Z'.
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 forward proton scattering in association with light-by-light scattering mediated by an axion-like particle is presented, using the ATLAS Forward Proton spectrometer to detect scattered protons and the central ATLAS detector to detect pairs of outgoing photons. Proton-proton collision data recorded in 2017 at a centre-of-mass energy of $\sqrt{s} = 13$ TeV were analysed, corresponding to an integrated luminosity of 14.6 fb$^{-1}$. A total of 441 candidate signal events were selected. A search was made for a narrow resonance in the diphoton mass distribution, corresponding to an axion-like particle (ALP) with mass in the range 150-1600 GeV. No excess is observed above a smooth background. Upper limits on the production cross section of a narrow resonance are set as a function of the mass, and are interpreted as upper limits on the ALP production coupling constant, assuming 100% decay branching ratio into a photon pair. The inferred upper limit on the coupling constant is in the range 0.04-0.09 TeV$^{-1}$ at 95%confidence level.
Signal selection efficiency as a function of ALP mass $m_{\textrm{X}}$ for the exclusive (EL), single-dissociative (SD), and double-dissociative (DD) processes. The ratio of the number of selected events to the number of generated MC events is given (black points) and is parameterised by an analytic function (red solid line). The linear (black dashed line) and cubic (blue chain line) interpolations of the black points are used to derive the envelopes (cyan filled region) which are regarded as systematic uncertainties.
The diphoton mass distribution of the mixed-data sample (black points).
The $(\xi_{\gamma\gamma}^{+},\xi_{\gamma\gamma}^{-})$ distribution of the selected data candidates after the full event selection in $m_{\gamma\gamma}$ in [150,1600] GeV with $m_{\gamma\gamma}$ contours (blue) and $y_{\gamma\gamma}$ contours (black). The range of $\xi_{\gamma\gamma}$ in which forward-proton matching is possible, $[0.035-\xi_{\textrm{th}}, 0.08+\xi_{\textrm{th}} ]$, for events that pass the matching requirement to the A or C side as indicated. No event passed the matching requirement for both the A-side and C-side.
Background-only fit to the observed numbers of events (black points) as a function of the diphoton invariant mass $m_{\gamma\gamma}$.
Expected and observed 95% CL upper limits on the signal fiducial cross section $\sigma_{\textrm{fid}}$, assuming 100% branching ratio for ALP decay into two photons, as a function of the hypothetical ALP mass $m_{\textrm{X}}$. The 1$\sigma$ and 2$\sigma$ confidence intervals are shown by the coloured bands.
Expected and observed 95% CL upper limits on the the ALP coupling constant, assuming 100% branching ratio for ALP decay into two photons, as a function of the hypothetical ALP mass $m_{\textrm{X}}$. The 1$\sigma$ and 2$\sigma$ confidence intervals are shown by the coloured bands. Contours of the ALP natural width $\Gamma$ are illustrated by the smooth blue solid lines.
Fiducial region acceptance of signal events for coupling constant f$^{-1}=0.05$ TeV$^{-1}$. EL, SD, and DD stand for the exclusive, single-dissociative, and double-dissociative processes. The acceptances are parameterised as $p_0 + p^{i}_{1} e^{p_{2}^{i} m_{\textrm{X}}} + p_{3}^{i} e^{p_{4}^{i} m_{\textrm{X}}} $ , where $i$ specifies the process type, exclusive, single-dissociative, or double-dissociative.
Correction factors $A_{\textrm{X}}/A_{0}$ and $C_{\textrm{X}}$ for the exclusive signal events with ALP coupling constant f$^{-1}$=0.05 TeV$^{-1}$, where acceptance $A_{\textrm{X}}$ and efficiency $C_{\textrm{X}}$ are defined in arXiv:2102.13405. $A_{\textrm{X}}$/$A_{0}$ and $C_{\textrm{X}}$ are parameterised as $p_0 + p^{i}_{1} e^{p_{2}^{i} m_{\textrm{X}}} + p_{3}^{i} e^{p_{4}^{i} m_{\textrm{X}}}$, where $i$ specifies the process type.
Simulated ALP signal cutflow for $m_{\rm{X}}$=300 GeV and $m_{\rm{X}}$=1200 GeV. The yields are normalized to a luminosity of 14.6 fb$^{-1}$. Selections are applied for each side after the selection on acoplanarity. The union of the sets of selected events is taken finally.
This paper presents a search for dark matter, $\chi$, using events with a single top quark and an energetic $W$ boson. The analysis is based on proton-proton collision data collected with the ATLAS experiment at $\sqrt{s}=$ 13 TeV during LHC Run 2 (2015-2018), corresponding to an integrated luminosity of 139 fb$^{-1}$. The search considers final states with zero or one charged lepton (electron or muon), at least one $b$-jet and large missing transverse momentum. In addition, a result from a previous search considering two-charged-lepton final states is included in the interpretation of the results. The data are found to be in good agreement with the Standard Model predictions and the results are interpreted in terms of 95% confidence-level exclusion limits in the context of a class of dark matter models involving an extended two-Higgs-doublet sector together with a pseudoscalar mediator particle. The search is particularly sensitive to on-shell production of the charged Higgs boson state, $H^{\pm}$, arising from the two-Higgs-doublet mixing, and its semi-invisible decays via the mediator particle, $a$: $H^{\pm} \rightarrow W^\pm a (\rightarrow \chi\chi)$. Signal models with $H^{\pm}$ masses up to 1.5 TeV and $a$ masses up to 350 GeV are excluded assuming a tan$\beta$ value of 1. For masses of $a$ of 150 (250) GeV, tan$\beta$ values up to 2 are excluded for $H^{\pm}$ masses between 200 (400) GeV and 1.5 TeV. Signals with tan$\beta$ values between 20 and 30 are excluded for $H^{\pm}$ masses between 500 and 800 GeV.
The observed exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour.
The expected exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour.
The observed exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour.
The expected exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour.
The observed exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour.
The expected exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour.
The observed exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour.
The expected exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour.
The observed exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The expected exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The observed exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The expected exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The observed exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The expected exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The observed exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The expected exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 0L channel only.
The observed exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The expected exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The observed exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The expected exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The observed exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The expected exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The observed exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The expected exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 1L channel only.
The observed exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 2L channel only.
The expected exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 2L channel only.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 2L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 2L channel only.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 2L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 2L channel only.
The observed exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 2L channel only.
The expected exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 2L channel only.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 2L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 2L channel only.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 2L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 2L channel only.
The expected exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 2L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 2L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Only signals simulating the tW+DM final states are considered in this contour. These exclusion contours are derived using the 2L channel only.
The expected exclusion contour at 95% CL as a function of the $m_a$ vs. $m_{H^{\pm}}$ and assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 2L channel only.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 2L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 150 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 2L channel only.
The observed exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 2L channel only.
The expected exclusion contour at 95% CL as a function of the $m_{H^{\pm}}$ vs. tan$\beta$ and assuming $m_a$ = 250 $\mathrm{GeV}$, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Masses that are within the contours are excluded. Signals simulating the tW+DM + tt+DM final states are considered in this contour. These exclusion contours are derived using the 2L channel only.
Model dependent upper limit on the cross section for the $m_a$ vs. $ m_{H^{\pm}}$ signal grid assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Only signals simulating the tW+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 150 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Only signals simulating the tW+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 250 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Only signals simulating the tW+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_a$ vs. $ m_{H^{\pm}}$ signal grid assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Signals simulating the tW+DM + tt+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 150 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Signals simulating the tW+DM + tt+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 250 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Signals simulating the tW+DM + tt+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_a$ vs. $ m_{H^{\pm}}$ signal grid assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Only signals simulating the tW+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 150 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Only signals simulating the tW+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 250 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Only signals simulating the tW+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_a$ vs. $ m_{H^{\pm}}$ signal grid assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Signals simulating the tW+DM + tt+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 150 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Signals simulating the tW+DM + tt+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 250 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Signals simulating the tW+DM + tt+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_a$ vs. $ m_{H^{\pm}}$ signal grid assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Only signals simulating the tW+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 150 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Only signals simulating the tW+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 250 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Only signals simulating the tW+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_a$ vs. $ m_{H^{\pm}}$ signal grid assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Signals simulating the tW+DM + tt+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 150 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Signals simulating the tW+DM + tt+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 250 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Signals simulating the tW+DM + tt+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_a$ vs. $ m_{H^{\pm}}$ signal grid assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Only signals simulating the tW+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 150 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Only signals simulating the tW+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 250 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Only signals simulating the tW+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_a$ vs. $ m_{H^{\pm}}$ signal grid assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Signals simulating the tW+DM + tt+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 150 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Signals simulating the tW+DM + tt+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 250 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Signals simulating the tW+DM + tt+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_a$ vs. $ m_{H^{\pm}}$ signal grid assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Only signals simulating the tW+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 150 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Only signals simulating the tW+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 250 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Only signals simulating the tW+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_a$ vs. $ m_{H^{\pm}}$ signal grid assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Signals simulating the tW+DM + tt+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 150 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Signals simulating the tW+DM + tt+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 250 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.7$. Signals simulating the tW+DM + tt+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_a$ vs. $ m_{H^{\pm}}$ signal grid assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Only signals simulating the tW+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 150 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Only signals simulating the tW+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 250 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Only signals simulating the tW+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_a$ vs. $ m_{H^{\pm}}$ signal grid assuming tan$\beta$ = 1, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Signals simulating the tW+DM + tt+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 150 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Signals simulating the tW+DM + tt+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
Model dependent upper limit on the cross section for the $m_{H^{\pm}}$ vs. tan$\beta$ signal grid assuming $m_a$ = 250 GeV, $m_{\mathrm{DM}} = 10 \mathrm{GeV}$, $g_{\chi} = 1$ and sin$\theta = 0.35$. Signals simulating the tW+DM + tt+DM final states are considered. Upper limits with large $\mu_{\mathrm{sig}}$ for the observed limit are capped at 500.
The distributions of $m_{\mathrm{b1},\mathrm{W-tagged}}$ in the 0L inclusive signal region. For each bin yields for the data and total SM prediction are provided. The SM prediction is provided with the total uncertainty, including the MC statistical uncertainty, detector-related systematic uncertainties and theoretical uncertainties. The rightmost bin includes overflow events.
The distributions of $m_{\mathrm{T}}^{\mathrm{b,E_{\mathrm{T}^{\mathrm{miss}}}}}$ in the 0L inclusive signal region. For each bin yields for the data and total SM prediction are provided. The SM prediction is provided with the total uncertainty, including the MC statistical uncertainty, detector-related systematic uncertainties and theoretical uncertainties. The rightmost bin includes overflow events.
The distributions of $N_{\mathrm{W-tagged}}$ in the 0L inclusive signal region. For each bin yields for the data and total SM prediction are provided. The SM prediction is provided with the total uncertainty, including the MC statistical uncertainty, detector-related systematic uncertainties and theoretical uncertainties. The rightmost bin includes overflow events.
The distributions of $m_{\mathrm{b1},\mathrm{\cancel{b1}}}$ in the hadronic top inclusive signal region. For each bin yields for the data and total SM prediction are provided. The SM prediction is provided with the total uncertainty, including the MC statistical uncertainty, detector-related systematic uncertainties and theoretical uncertainties. The rightmost bin includes overflow events.
The distributions of $m_{\mathrm{b1},\mathrm{\cancel{b1}}}$ in the leptonic top inclusive signal region. For each bin yields for the data and total SM prediction are provided. The SM prediction is provided with the total uncertainty, including the MC statistical uncertainty, detector-related systematic uncertainties and theoretical uncertainties. The rightmost bin includes overflow events.
The distributions of $m_{\mathrm{b1},\mathrm{\cancel{b1}}}$ in the leptonic top inclusive signal region. For each bin yields for the data and total SM prediction are provided. The SM prediction is provided with the total uncertainty, including the MC statistical uncertainty, detector-related systematic uncertainties and theoretical uncertainties. The rightmost bin includes overflow events.
Cutflow for the reference point $(\it{m}_{\mathrm{H^{\pm}}}, \it{m}_{a}, tan\beta, sin\theta )=$ (500,100,1,0.7) , (800,150,20,0.7), (600,250,30,0.7), (1000,400,1,0.7) in 0L regions. Results are shown including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$.
Cutflow for the reference point $(\it{m}_{\mathrm{H^{\pm}}}, \it{m}_{a}, tan\beta, sin\theta )=$ (500,100,1,0.7) , (800,150,20,0.7), (600,250,30,0.7), (1000,400,1,0.7) in 1L leptonic top regions. Results are shown including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$.
Cutflow for the reference point $(\it{m}_{\mathrm{H^{\pm}}}, \it{m}_{a}, tan\beta, sin\theta )=$ (500,100,1,0.7) , (800,150,20,0.7), (600,250,30,0.7), (1000,400,1,0.7) in 1L hadronic top regions. Results are shown including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$.
Signal acceptance in the 0L region for 2HDM+a model DM signals on the plane defined by m$_a$--m$_{H^{\pm}}$ assuming tan$\beta$ = 1, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.7. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal efficiency in the 0L region for 2HDM+a model DM signals on the plane defined by m$_a$--m$_{H^{\pm}}$ assuming tan$\beta$ = 1, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.7. Please mind that the efficiency given in the table is multiplied by factor of $10^{2}$
Signal acceptance in the 0L region for 2HDM+a model DM signals on the plane defined by m$_{H^{\pm}}$--tan$\beta$ assuming m$_a$ = 150 GeV, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.7. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal efficiency in the 0L region for 2HDM+a model DM signals on the plane defined by m$_{H^{\pm}}$--tan$\beta$ assuming m$_a$ = 150 GeV, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.7. Please mind that the efficiency given in the table is multiplied by factor of $10^{2}$
Signal acceptance in the 0L region for 2HDM+a model DM signals on the plane defined by m$_{H^{\pm}}$--tan$\beta$ assuming m$_a$ = 250 GeV, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.7. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal efficiency in the 0L region for 2HDM+a model DM signals on the plane defined by m$_{H^{\pm}}$--tan$\beta$ assuming m$_a$ = 250 GeV, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.7. Please mind that the efficiency given in the table is multiplied by factor of $10^{2}$
Signal acceptance in the 1L region for 2HDM+a model DM signals on the plane defined by m$_a$--m$_{H^{\pm}}$ assuming tan$\beta$ = 1, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.7. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal efficiency in the 1L region for 2HDM+a model DM signals on the plane defined by m$_a$--m$_{H^{\pm}}$ assuming tan$\beta$ = 1, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.7. Please mind that the efficiency given in the table is multiplied by factor of $10^{2}$
Signal acceptance in the 1L region for 2HDM+a model DM signals on the plane defined by m$_{H^{\pm}}$--tan$\beta$ assuming m$_a$ = 150 GeV, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.7. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal efficiency in the 1L region for 2HDM+a model DM signals on the plane defined by m$_{H^{\pm}}$--tan$\beta$ assuming m$_a$ = 150 GeV, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.7. Please mind that the efficiency given in the table is multiplied by factor of $10^{2}$
Signal acceptance in the 1L region for 2HDM+a model DM signals on the plane defined by m$_{H^{\pm}}$--tan$\beta$ assuming m$_a$ = 250 GeV, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.7. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal efficiency in the 1L region for 2HDM+a model DM signals on the plane defined by m$_{H^{\pm}}$--tan$\beta$ assuming m$_a$ = 250 GeV, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.7. Please mind that the efficiency given in the table is multiplied by factor of $10^{2}$
Signal acceptance in the 0L region for 2HDM+a model DM signals on the plane defined by m$_a$--m$_{H^{\pm}}$ assuming tan$\beta$ = 1, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.35. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal efficiency in the 0L region for 2HDM+a model DM signals on the plane defined by m$_a$--m$_{H^{\pm}}$ assuming tan$\beta$ = 1, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.35. Please mind that the efficiency given in the table is multiplied by factor of $10^{2}$
Signal acceptance in the 0L region for 2HDM+a model DM signals on the plane defined by m$_{H^{\pm}}$--tan$\beta$ assuming m$_a$ = 150 GeV, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.35. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal efficiency in the 0L region for 2HDM+a model DM signals on the plane defined by m$_{H^{\pm}}$--tan$\beta$ assuming m$_a$ = 150 GeV, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.35. Please mind that the efficiency given in the table is multiplied by factor of $10^{2}$
Signal acceptance in the 0L region for 2HDM+a model DM signals on the plane defined by m$_{H^{\pm}}$--tan$\beta$ assuming m$_a$ = 250 GeV, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.35. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal efficiency in the 0L region for 2HDM+a model DM signals on the plane defined by m$_{H^{\pm}}$--tan$\beta$ assuming m$_a$ = 250 GeV, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.35. Please mind that the efficiency given in the table is multiplied by factor of $10^{2}$
Signal acceptance in the 1L region for 2HDM+a model DM signals on the plane defined by m$_a$--m$_{H^{\pm}}$ assuming tan$\beta$ = 1, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.35. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal efficiency in the 1L region for 2HDM+a model DM signals on the plane defined by m$_a$--m$_{H^{\pm}}$ assuming tan$\beta$ = 1, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.35. Please mind that the efficiency given in the table is multiplied by factor of $10^{2}$
Signal acceptance in the 1L region for 2HDM+a model DM signals on the plane defined by m$_{H^{\pm}}$--tan$\beta$ assuming m$_a$ = 150 GeV, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.35. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal efficiency in the 1L region for 2HDM+a model DM signals on the plane defined by m$_{H^{\pm}}$--tan$\beta$ assuming m$_a$ = 150 GeV, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.35. Please mind that the efficiency given in the table is multiplied by factor of $10^{2}$
Signal acceptance in the 1L region for 2HDM+a model DM signals on the plane defined by m$_{H^{\pm}}$--tan$\beta$ assuming m$_a$ = 250 GeV, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.35. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$
Signal efficiency in the 1L region for 2HDM+a model DM signals on the plane defined by m$_{H^{\pm}}$--tan$\beta$ assuming m$_a$ = 250 GeV, m$_{\chi}$= 10 GeV and sin$\theta$ = 0.35. Please mind that the efficiency given in the table is multiplied by factor of $10^{2}$
A search for resonant Higgs boson pair production in the $b\bar{b}b\bar{b}$ final state is presented. The analysis uses 126-139 fb$^{-1}$ of $pp$ collision data at $\sqrt{s}$ = 13 TeV collected with the ATLAS detector at the Large Hadron Collider. The analysis is divided into two channels, targeting Higgs boson decays which are reconstructed as pairs of small-radius jets or as individual large-radius jets. Spin-0 and spin-2 benchmark signal models are considered, both of which correspond to resonant $HH$ production via gluon$-$gluon fusion. The data are consistent with Standard Model predictions. Upper limits are set on the production cross-section times branching ratio to Higgs boson pairs of a new resonance in the mass range from 251 GeV to 5 TeV.
Cumulative acceptance times efficiency as a function of resonance mass for each event selection step in the resolved channel for the spin-0 signal models. The local maximum at 251 GeV is a consequence of the near-threshold kinematics.
Cumulative acceptance times efficiency as a function of resonance mass for each event selection step in the resolved channel for the spin-2 signal models. The local maximum at 251 GeV is a consequence of the near-threshold kinematics.
Corrected $m(HH)$ distribution in the resolved $4b$ validation region (dots), compared with the reweighted distribution in $2b$ validation region (teal histogram). The error bars on the $4b$ points represent the Poisson uncertainties corresponding to their event yields. The final bin includes overflow. The background uncertainty (gray band) is computed by adding all individual components in quadrature. The bottom panel shows the difference between the $4b$ and reweighted $2b$ distributions, relative to the $2b$ distribution.
Corrected $m(HH)$ distribution in the resolved $4b$ signal region (dots), after the fit under the background-only hypothesis. The error bars on the $4b$ points represent the Poisson uncertainties corresponding to their event yields. The background model (teal histogram) is shown with its total post-fit uncertainty (gray band). The final bin includes overflow. Representative spin-0 signal hypotheses (dashed, dotted, and dashed-dotted lines) are overlaid, normalized to the overall expected limits on their cross-sections. The bottom panel shows the difference between the $4b$ distribution and the background model, relative to the background model. No significant excess of data relative to the SM background is observed.
Corrected $m(HH)$ distribution in the resolved $4b$ signal region (dots), after the fit under the background-only hypothesis. The error bars on the $4b$ points represent the Poisson uncertainties corresponding to their event yields. The background model (teal histogram) is shown with its total post-fit uncertainty (gray band). The final bin includes overflow. Representative spin-2 signal hypotheses (dashed, dotted, and dashed-dotted lines) are overlaid, normalized to the overall expected limits on their cross-sections. The bottom panel shows the difference between the $4b$ distribution and the background model, relative to the background model. No significant excess of data relative to the SM background is observed.
Cumulative signal acceptance times efficiency as a function of the resonance mass for various selection steps in the boosted channel. The steps up to the $b$-tag categorization are shown for the spin-0.
Cumulative signal acceptance times efficiency as a function of the resonance mass for various selection steps in the boosted channel. The steps up to the $b$-tag categorization are shown for the spin-2.
Cumulative signal acceptance times efficiency as a function of the resonance mass for various selection steps in the boosted channel. The efficiencies of the three b-tag categories are shown for the spin-0 scenario; this efficiency is obtained after the other selection steps including the SR definition. The signal efficiency in the 4b region has a maximum around 1.5 TeV. Above that value the track-jets start to merge together, and for the highest resonance masses the 2b category becomes the most efficient.
Cumulative signal acceptance times efficiency as a function of the resonance mass for various selection steps in the boosted channel. The efficiencies of the three b-tag categories are shown for the spin-2 scenario; this efficiency is obtained after the other selection steps including the SR definition. The signal efficiency in the 4b region has a maximum around 1.5 TeV. Above that value the track-jets start to merge together, and for the highest resonance masses the 2b category becomes the most efficient.
Comparison of the background model (stacked histograms) with data (dots) in the $2b$ validation region. The error bars on the data points represent the Poisson uncertainties corresponding to their event yields. The background uncertainty (gray band) is computed by adding all individual components in quadrature and is not allowed to extend below zero.
Comparison of the background model (stacked histograms) with data (dots) in the $3b$ validation region. The error bars on the data points represent the Poisson uncertainties corresponding to their event yields. The background uncertainty (gray band) is computed by adding all individual components in quadrature and is not allowed to extend below zero.
Comparison of the background model (stacked histograms) with data (dots) in the $4b$ validation region. The error bars on the data points represent the Poisson uncertainties corresponding to their event yields. The background uncertainty (gray band) is computed by adding all individual components in quadrature and is not allowed to extend below zero.
The $m(HH)$ distributions in the boosted $2b$ signal regions (dots), after the fit under the background-only hypothesis. The error bars on the data points represent the Poisson uncertainties corresponding to their event yields. The background model (stacked histogram) is shown with its total post-fit uncertainty (gray band). The uncertainty bands are defined using an ensemble of curves constructed by sampling a multivariate Gaussian probability density function built from the covariance matrix of the fit. Representative spin-0 signal hypotheses (dashed and dashed-dotted lines) are overlaid, normalized to the overall expected limits on their cross-sections. No significant excess of data relative to the SM background is observed.
The $m(HH)$ distributions in the boosted $2b$ signal regions (dots), after the fit under the background-only hypothesis. The error bars on the data points represent the Poisson uncertainties corresponding to their event yields. The background model (stacked histogram) is shown with its total post-fit uncertainty (gray band). The uncertainty bands are defined using an ensemble of curves constructed by sampling a multivariate Gaussian probability density function built from the covariance matrix of the fit. Representative spin-2 signal hypotheses (dashed and dashed-dotted lines) are overlaid, normalized to the overall expected limits on their cross-sections. No significant excess of data relative to the SM background is observed.
The $m(HH)$ distributions in the boosted $3b$ signal regions (dots), after the fit under the background-only hypothesis. The error bars on the data points represent the Poisson uncertainties corresponding to their event yields. The background model (stacked histogram) is shown with its total post-fit uncertainty (gray band). The uncertainty bands are defined using an ensemble of curves constructed by sampling a multivariate Gaussian probability density function built from the covariance matrix of the fit. Representative spin-0 signal hypotheses (dashed and dashed-dotted lines) are overlaid, normalized to the overall expected limits on their cross-sections. No significant excess of data relative to the SM background is observed.
The $m(HH)$ distributions in the boosted $3b$ signal regions (dots), after the fit under the background-only hypothesis. The error bars on the data points represent the Poisson uncertainties corresponding to their event yields. The background model (stacked histogram) is shown with its total post-fit uncertainty (gray band). The uncertainty bands are defined using an ensemble of curves constructed by sampling a multivariate Gaussian probability density function built from the covariance matrix of the fit. Representative spin-2 signal hypotheses (dashed and dashed-dotted lines) are overlaid, normalized to the overall expected limits on their cross-sections. No significant excess of data relative to the SM background is observed.
The $m(HH)$ distributions in the boosted $4b$ signal regions (dots), after the fit under the background-only hypothesis. The error bars on the data points represent the Poisson uncertainties corresponding to their event yields. The background model (stacked histogram) is shown with its total post-fit uncertainty (gray band). The uncertainty bands are defined using an ensemble of curves constructed by sampling a multivariate Gaussian probability density function built from the covariance matrix of the fit. Representative spin-0 signal hypotheses (dashed and dashed-dotted lines) are overlaid, normalized to the overall expected limits on their cross-sections. No significant excess of data relative to the SM background is observed.
The $m(HH)$ distributions in the boosted $4b$ signal regions (dots), after the fit under the background-only hypothesis. The error bars on the data points represent the Poisson uncertainties corresponding to their event yields. The background model (stacked histogram) is shown with its total post-fit uncertainty (gray band). The uncertainty bands are defined using an ensemble of curves constructed by sampling a multivariate Gaussian probability density function built from the covariance matrix of the fit. Representative spin-2 signal hypotheses (dashed and dashed-dotted lines) are overlaid, normalized to the overall expected limits on their cross-sections. No significant excess of data relative to the SM background is observed.
Expected (dashed black lines) and observed (solid black lines) 95% CL upper limits on the cross-section of resonant $HH$ production in the spin-0 signal models. The $\pm 1 \sigma$ and $\pm 2 \sigma$ uncertainty ranges for the expected limits (colored bands) are shown. Expected limits using each of the resolved and boosted channels individually (dashed colored lines) are shown. The nominal $H\rightarrow b\bar{b}$ branching ratio is taken as 0.582.
Expected (dashed black lines) and observed (solid black lines) 95% CL upper limits on the cross-section of resonant $HH$ production in the spin-2 signal models. The $\pm 1 \sigma$ and $\pm 2 \sigma$ uncertainty ranges for the expected limits (colored bands) are shown. Expected limits using each of the resolved and boosted channels individually (dashed colored lines) are shown. The theoretical prediction for the bulk RS model with $k/\bar{M}_{\text{Pl}} = 1$ (solid red line) is shown; the decrease below 350 GeV is due to a sharp reduction in the $G^{*}_{\text{KK}} \rightarrow HH$ branching ratio. The nominal $H\rightarrow b\bar{b}$ branching ratio is taken as 0.582.
The results of a search for direct pair production of top squarks and for dark matter in events with two opposite-charge leptons (electrons or muons), jets and missing transverse momentum are reported, using 139 fb$^{-1}$ of integrated luminosity from proton-proton collisions at $\sqrt{s} = 13$ TeV, collected by the ATLAS detector at the Large Hadron Collider during Run 2 (2015-2018). This search considers the pair production of top squarks and is sensitive across a wide range of mass differences between the top squark and the lightest neutralino. Additionally, spin-0 mediator dark-matter models are considered, in which the mediator is produced in association with a pair of top quarks. The mediator subsequently decays to a pair of dark-matter particles. No significant excess of events is observed above the Standard Model background, and limits are set at 95% confidence level. The results exclude top squark masses up to about 1 TeV, and masses of the lightest neutralino up to about 500 GeV. Limits on dark-matter production are set for scalar (pseudoscalar) mediator masses up to about 250 (300) GeV.
Two-body selection. Distributions of $m_{T2}$ in $SR^{2-body}_{110,\infty}$ for (a) different-flavour and (b) same-flavour events satisfying the selection criteria of the given SR, except the one for the presented variable, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack. ''Others'' includes contributions from $VVV$, $t\bar{t} t$, $t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$ processes. The hatched bands represent the total statistical and systematic uncertainty. The rightmost bin of each plot includes overflow events. Reference dark-matter signal models are overlayed for comparison. Red arrows in the upper panels indicate the signal region selection criteria. The bottom panels show the ratio of the observed data to the total SM background prediction, with hatched bands representing the total uncertainty in the background prediction.
Two-body selection. Distributions of $m_{T2}$ in $SR^{2-body}_{110,\infty}$ for (a) different-flavour and (b) same-flavour events satisfying the selection criteria of the given SR, except the one for the presented variable, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack. ''Others'' includes contributions from $VVV$, $t\bar{t} t$, $t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$ processes. The hatched bands represent the total statistical and systematic uncertainty. The rightmost bin of each plot includes overflow events. Reference dark-matter signal models are overlayed for comparison. Red arrows in the upper panels indicate the signal region selection criteria. The bottom panels show the ratio of the observed data to the total SM background prediction, with hatched bands representing the total uncertainty in the background prediction.
Three-body selection. Distributions of $M_{\Delta}^R$ in (a,b) $SR_{W}^{3-body}$ and (c,d) $SR_{T}^{3-body}$ for (left) same-flavour and (right) different-flavour events satisfying the selection criteria of the given SR, except the one for the presented variable, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack. ''Others'' includes contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$ processes. The hatched bands represent the total statistical and systematic uncertainty. The rightmost bin of each plot includes overflow events. Reference top squark pair production signal models are overlayed for comparison. Red arrows in the upper panels indicate the signal region selection criteria. The bottom panels show the ratio of the observed data to the total SM background prediction, with hatched bands representing the total uncertainty in the background prediction; red arrows show data outside the vertical-axis range.
Three-body selection. Distributions of $M_{\Delta}^R$ in (a,b) $SR_{W}^{3-body}$ and (c,d) $SR_{T}^{3-body}$ for (left) same-flavour and (right) different-flavour events satisfying the selection criteria of the given SR, except the one for the presented variable, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack. ''Others'' includes contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$ processes. The hatched bands represent the total statistical and systematic uncertainty. The rightmost bin of each plot includes overflow events. Reference top squark pair production signal models are overlayed for comparison. Red arrows in the upper panels indicate the signal region selection criteria. The bottom panels show the ratio of the observed data to the total SM background prediction, with hatched bands representing the total uncertainty in the background prediction; red arrows show data outside the vertical-axis range.
Three-body selection. Distributions of $M_{\Delta}^R$ in (a,b) $SR_{W}^{3-body}$ and (c,d) $SR_{T}^{3-body}$ for (left) same-flavour and (right) different-flavour events satisfying the selection criteria of the given SR, except the one for the presented variable, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack. ''Others'' includes contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$ processes. The hatched bands represent the total statistical and systematic uncertainty. The rightmost bin of each plot includes overflow events. Reference top squark pair production signal models are overlayed for comparison. Red arrows in the upper panels indicate the signal region selection criteria. The bottom panels show the ratio of the observed data to the total SM background prediction, with hatched bands representing the total uncertainty in the background prediction; red arrows show data outside the vertical-axis range.
Three-body selection. Distributions of $M_{\Delta}^R$ in (a,b) $SR_{W}^{3-body}$ and (c,d) $SR_{T}^{3-body}$ for (left) same-flavour and (right) different-flavour events satisfying the selection criteria of the given SR, except the one for the presented variable, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack. ''Others'' includes contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$ processes. The hatched bands represent the total statistical and systematic uncertainty. The rightmost bin of each plot includes overflow events. Reference top squark pair production signal models are overlayed for comparison. Red arrows in the upper panels indicate the signal region selection criteria. The bottom panels show the ratio of the observed data to the total SM background prediction, with hatched bands representing the total uncertainty in the background prediction; red arrows show data outside the vertical-axis range.
Four-body selection. (a) distributions of $E_{T}^{miss}$ in $SR^{4-body}_{Small\,\Delta m}$ and (b) distribution of $R_{2\ell 4j}$ in $SR^{4-body}_{Large\,\Delta m}$ for events satisfying the selection criteria of the given SR, except the one for the presented variable, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack. ''Others'' includes contributions from $VVV$, $t\bar{t} t$, $t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$ processes. The hatched bands represent the total statistical and systematic uncertainty. The rightmost bin of each plot includes overflow events. Reference top squark pair production signal models are overlayed for comparison. Red arrows in the upper panel indicate the signal region selection criteria. The bottom panels show the ratio of the observed data to the total SM background prediction, with hatched bands representing the total uncertainty in the background prediction; red arrows show data outside the vertical-axis range.
Four-body selection. (a) distributions of $E_{T}^{miss}$ in $SR^{4-body}_{Small\,\Delta m}$ and (b) distribution of $R_{2\ell 4j}$ in $SR^{4-body}_{Large\,\Delta m}$ for events satisfying the selection criteria of the given SR, except the one for the presented variable, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack. ''Others'' includes contributions from $VVV$, $t\bar{t} t$, $t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$ processes. The hatched bands represent the total statistical and systematic uncertainty. The rightmost bin of each plot includes overflow events. Reference top squark pair production signal models are overlayed for comparison. Red arrows in the upper panel indicate the signal region selection criteria. The bottom panels show the ratio of the observed data to the total SM background prediction, with hatched bands representing the total uncertainty in the background prediction; red arrows show data outside the vertical-axis range.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}_1^0$ with 100% branching ratio, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the expected limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}_1^0$ with 100% branching ratio, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the expected limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}_1^0$ with 100% branching ratio, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the expected limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}_1^0$ with 100% branching ratio, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the Observed limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}_1^0$ with 100% branching ratio, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the expected limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}_1^0$ with 100% branching ratio, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the expected limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}_1^0$ with 100\% branching ratio, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the expected limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}_1^0$ with 100\% branching ratio, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the expected limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}_1^0$ with 100\% branching ratio, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the expected limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}_1^0$ with 100\% branching ratio, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the expected limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}_1^0$ with 100\% branching ratio, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the expected limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}_1^0$ with 100\% branching ratio, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the expected limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.
Exclusion limits for (a) $t\bar{t} + \phi $ scalar and (b) $t\bar{t} + a $ pseudoscalar models as a function of the mediator mass for a DM particle mass of $m(\chi)=1$ GeV. 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 shows the observed (expected) exclusion limits.
Exclusion limits for (a) $t\bar{t} + \phi $ scalar and (b) $t\bar{t} + a $ pseudoscalar models as a function of the mediator mass for a DM particle mass of $m(\chi)=1$ GeV. 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 shows the observed (expected) exclusion limits.
Exclusion limits for (a) $t\bar{t} + \phi $ scalar and (b) $t\bar{t} + a $ pseudoscalar models as a function of the mediator mass for a DM particle mass of $m(\chi)=1$ GeV. 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 shows the observed (expected) exclusion limits.
Exclusion limits for (a) $t\bar{t} + \phi $ scalar and (b) $t\bar{t} + a $ pseudoscalar models as a function of the mediator mass for a DM particle mass of $m(\chi)=1$ GeV. 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 shows the observed (expected) exclusion limits.
Two-body selection. Background fit results for $\mathrm{CR}^{\mathrm{2-body}}_{t\bar{t}}$, $\mathrm{CR}^{\mathrm{2-body}}_{t\bar{t}Z}$, $\mathrm{VR}^{\mathrm{2-body}}_{t\bar{t}, DF}$, $\mathrm{VR}^{\mathrm{2-body}}_{t\bar{t}, SF}$ and $\mathrm{VR}^{\mathrm{2-body}}_{t\bar{t} Z}$. ''Others'' includes contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$ processes. Combined statistical and systematic uncertainties are given. Entries marked `--' indicate a negligible background contribution (less than 0.001 events). The individual uncertainties can be correlated, and do not necessarily add up in quadrature to the total background uncertainty.
Three-body selection. Background fit results for $\mathrm{CR}^{\mathrm{3-body}}_{t\bar{t}}$, $\mathrm{CR}^{\mathrm{3-body}}_{VV}$, $\mathrm{CR}^{\mathrm{2-body}}_{t\bar{t}Z}$, $\mathrm{VR}^{\mathrm{3-body}}_{VV}$, $\mathrm{VR(1)}^{\mathrm{3-body}}_{t\bar{t}}$ and $\mathrm{VR(2)}^{\mathrm{3-body}}_{t\bar{t}}$. ''Others'' includes contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$ processes. Combined statistical and systematic uncertainties are given. Entries marked `--' indicate a negligible background contribution (less than 0.001 events). The individual uncertainties can be correlated, and do not necessarily add up in quadrature to the total background uncertainty.
Four-body selection. Background fit results for $\mathrm{CR}^{\mathrm{4-body}}_{t\bar{t}}$,$\mathrm{CR}^{\mathrm{4-body}}_{VV}$, $\mathrm{VR}^{\mathrm{4-body}}_{t\bar{t}}$, $VR^{4-body}_{VV}$ and $\mathrm{VR}^{\mathrm{4-body}}_{VV,lll}$. The ''Others'' category contains the contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$. Combined statistical and systematic uncertainties are given. Entries marked `--' indicate a negligible background contribution (less than 0.001 events). The individual uncertainties can be correlated, and do not necessarily add up in quadrature to the total background uncertainty.
Two-body selection. Background fit results for the different-flavour leptons binned SRs. The ''Others'' category contains the contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$. Combined statistical and systematic uncertainties are given. Entries marked `--' indicate a negligible background contribution (less than 0.001 events). The individual uncertainties can be correlated, and do not necessarily add up in quadrature to the total background uncertainty.
Two-body selection. Background fit results for the same-flavour leptons binned SRs. The ''Others'' category contains the contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$. Combined statistical and systematic uncertainties are given. The individual uncertainties can be correlated, and do not necessarily add up in quadrature to the total background uncertainty.
Three-body selection. Observed event yields and background fit results for the three-body selection SRs. The ''Others'' category contains contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$. Combined statistical and systematic uncertainties are given. Entries marked `--' indicate a negligible background contribution (less than 0.001 events). The individual uncertainties can be correlated, and do not necessarily add up in quadrature to the total background uncertainty.
Four-body selection. Observed event yields and background fit results for SR$^{\mathrm{4-body}}_{\mathrm{Small}\,\Delta m}$ and SR$^{\mathrm{4-body}}_{\mathrm{Large}\,\Delta m}$. The ''Others'' category contains the contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$. Combined statistical and systematic uncertainties are given. The individual uncertainties can be correlated, and do not necessarily add up in quadrature to the total background uncertainty.
Exclusion limits contours (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}^0_1$ with 100% branching ratio in $\tilde{t}_1--\tilde{\chi}^0_1$ masses planes. The dashed lines and the shaded bands are the expected limit and its $\pm 1\sigma$ uncertainty. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The exclusion limits contours for the two-body, three-body and four-body selections are respectively shown in blue, green and red.
Exclusion limits contours (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}^0_1$ with 100% branching ratio in $\tilde{t}_1--\tilde{\chi}^0_1$ masses planes. The dashed lines and the shaded bands are the expected limit and its $\pm 1\sigma$ uncertainty. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The exclusion limits contours for the two-body, three-body and four-body selections are respectively shown in blue, green and red.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t \tilde{\chi}_1^0$ with 100% branching ratio, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t \tilde{\chi}_1^0$ with 100% branching ratio, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t \tilde{\chi}_1^0$ with 100% branching ratio, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t \tilde{\chi}_1^0$ with 100% branching ratio, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b W \tilde{\chi}_1^0$ with 100% branching ratio, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b W \tilde{\chi}_1^0$ with 100% branching ratio, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b W \tilde{\chi}_1^0$ with 100% branching ratio, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm 1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b W \tilde{\chi}_1^0$ with 100% branching ratio, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b l \nu \tilde{\chi}_1^0$ with 100% branching ratio, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b l \nu \tilde{\chi}_1^0$ with 100% branching ratio, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty. The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b l \nu \tilde{\chi}_1^0$ with 100% branching ratio, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty.The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.
Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b l \nu \tilde{\chi}_1^0$ with 100% branching ratio, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty.The thick solid lines are the observed limits for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.
Exclusion limits for (a) $t\bar{t} + \phi $ scalar and (b) $t\bar{t} + a $ pseudoscalar models as a function of the DM particle mass for a mediator mass of 10 GeV. 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 shows the observed (expected) exclusion limits.
Exclusion limits for (a) $t\bar{t} + \phi $ scalar and (b) $t\bar{t} + a $ pseudoscalar models as a function of the DM particle mass for a mediator mass of 10 GeV. 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 shows the observed (expected) exclusion limits.
Exclusion limits for (a) $t\bar{t} + \phi $ scalar and (b) $t\bar{t} + a $ pseudoscalar models as a function of the DM particle mass for a mediator mass of 10 GeV. 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 shows the observed (expected) exclusion limits.
Exclusion limits for (a) $t\bar{t} + \phi $ scalar and (b) $t\bar{t} + a $ pseudoscalar models as a function of the DM particle mass for a mediator mass of 10 GeV. 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 shows the observed (expected) exclusion limits.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Three-body selection efficiency (a) SR-DF$^{3-body}_{t}$, (b) SR-SF$^{3-body}_{t}$, (c) SR-DF$^{3-body}_{W}$, (d) SR-SF$^{3-body}_{W}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Three-body selection efficiency (a) SR-DF$^{3-body}_{t}$, (b) SR-SF$^{3-body}_{t}$, (c) SR-DF$^{3-body}_{W}$, (d) SR-SF$^{3-body}_{W}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Three-body selection efficiency (a) SR-DF$^{3-body}_{t}$, (b) SR-SF$^{3-body}_{t}$, (c) SR-DF$^{3-body}_{W}$, (d) SR-SF$^{3-body}_{W}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Three-body selection efficiency (a) SR-DF$^{3-body}_{t}$, (b) SR-SF$^{3-body}_{t}$, (c) SR-DF$^{3-body}_{W}$, (d) SR-SF$^{3-body}_{W}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Four-body selection Efficiency (a) SR$^{4-body}_{Small \Delta m}$ , (b) $SR^{4-body}_{Large \Delta m}$ for a simplified model assuming $\tilde{t}_1$ pair production.
Four-body selection Efficiency (a) SR$^{4-body}_{Small \Delta m}$ , (b) $SR^{4-body}_{Large \Delta\ m}$ for a simplified model assuming $\tilde{t}_1$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} +\phi$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ t \tilde{t} +\phi$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ t \tilde{t} +\phi$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ t \tilde{t} +\phi$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ t \tilde{t} +\phi$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ t \tilde{t} +\phi$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming t \tilde{t} + a$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Three-body selection acceptance (a) SR-DF$^{3-body}_{t}$, (b) SR-SF$^{3-body}_{t}$, (c) SR-DF$^{3-body}_{W}$, (d) SR-SF$^{3-body}_{W}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Three-body selection acceptance (a) SR-DF$^{3-body}_{t}$, (b) SR-SF$^{3-body}_{t}$, (c) SR-DF$^{3-body}_{W}$, (d) SR-SF$^{3-body}_{W}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Three-body selection acceptance (a) SR-DF$^{3-body}_{t}$, (b) SR-SF$^{3-body}_{t}$, (c) SR-DF$^{3-body}_{W}$, (d) SR-SF$^{3-body}_{W}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Three-body selection acceptance (a) SR-DF$^{3-body}_{t}$, (b) SR-SF$^{3-body}_{t}$, (c) SR-DF$^{3-body}_{W}$, (d) SR-SF$^{3-body}_{W}$ for a simplified model assuming $ \tilde{t}_1$ pair production.
Four-body selection acceptance (a) SR$^{4-body}_{Small \Delta m}$ , (b) $SR^{4-body}_{Large \Delta m}$ for a simplified model assuming $\tilde{t}_1$ pair production.
Four-body selection acceptance (a) SR$^{4-body}_{Small \Delta m}$ , (b) $SR^{4-body}_{Large \Delta m}$ for a simplified model assuming $\tilde{t}_1$ pair production.
Two-body selection The numbers indicate the observed upper limits on the signal strenght for (a) a simplified model assuming $\tilde{t}_1$ pair production, (b) for $t\tilde{t} + a $ pseudoscalar models, (c) for $t\tilde{t} + \phi $ scalar models. In Figure (a), the red line corresponds to the observed limit.
Two-body selection The numbers indicate the observed upper limits on the signal strenght for (a) a simplified model assuming $\tilde{t}_1$ pair production, (b) for $t\tilde{t} + a $ pseudoscalar models, (c) for $t\tilde{t} + \phi $ scalar models. In Figure (a), the red line corresponds to the observed limit.
Two-body selection The numbers indicate the observed upper limits on the signal strenght for (a) a simplified model assuming $\tilde{t}_1$ pair production, (b) for $t\tilde{t} + a $ pseudoscalar models, (c) for $t\tilde{t} + \phi $ scalar models. In Figure (a), the red line corresponds to the observed limit.
Three-body selection The numbers indicate the upper limits on the signal strenght for a simplified model assuming $\tilde{t}_1$ pair production. For comparison, the red line corresponds to the observed limit.
Four-body selection The numbers indicate the upper limits on the signal strenght for a simplified model assuming $\tilde{t}_1$ pair production. For comparison, the red line corresponds to the observed limit.
Two-body selection The numbers indicate the upper limits on the signal cross-section for (a) a simplified model assuming $\tilde{t}_1$ pair production, (b) for $t\tilde{t} + a $ pseudoscalar models, (c) for $t\tilde{t} + \phi $ scalar models. In Figure (a), the red line corresponds to the observed limit.
Two-body selection The numbers indicate the upper limits on the signal cross-section for (a) a simplified model assuming $\tilde{t}_1$ pair production, (b) for $t\tilde{t} + a $ pseudoscalar models, (c) for $t\tilde{t} + \phi $ scalar models. In Figure (a), the red line corresponds to the observed limit.
Two-body selection The numbers indicate the upper limits on the signal cross-section for (a) a simplified model assuming $\tilde{t}_1$ pair production, (b) for $t\tilde{t} + a $ pseudoscalar models, (c) for $t\tilde{t} + \phi $ scalar models. In Figure (a), the red line corresponds to the observed limit.
Three-body selection The numbers indicate the upper limits on the signal cross-section for a simplified model assuming $\tilde{t}_1$ pair production. For comparison, the red line corresponds to the observed limit.
Four-body selection The numbers indicate the upper limits on the signal cross-section for a simplified model assuming $\tilde{t}_1$ pair production. For comparison, the red line corresponds to the observed limit.
Two-body selection. Background fit results for the $inclusive$ SRs. The Others category contains the contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$. Combined statistical and systematic uncertainties are given. Note that the individual uncertainties can be correlated, and do not necessarily add up quadratically to the total background uncertainty.
Cut flow for the simplified signal model $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}^0_1$ with $m(\tilde{t}_1)=600~ GeV$ and $m(\tilde{\chi}^0_1)=400~ GeV$ in the SRs for the two-body selection. The number of events is normalized to the cross-section and to an integrated luminosity of $139~fb^{-1}$.
Cut flow for the scalar signal model $t\bar{t} + \phi $ with $m(\phi)=150~ GeV$ and $m(\chi)=1~ GeV$ in the SRs for the two-body selection. The number of events is normalized to the cross-section and to an integrated luminosity of $139~fb^{-1}$.
Cut flow for the pseudoscalar signal model $t\bar{t} + a $ with $m(a)=150~ GeV$ and $m(\chi)=1~ GeV$ in the SRs for the two-body selection. The number of events is normalized to the cross-section and to an integrated luminosity of $139~fb^{-1}$.
Cut flow for the simplified signal model $\tilde{t}_1 \rightarrow bW\tilde{\chi}^0_1$ with $m(\tilde{t}_1)=550~ GeV$ and $m(\tilde{\chi}^0_1)=385~ GeV$ in the SRs for the three-body selection. The number of events is normalized to the cross-section and to an integrated luminosity of $139~fb^{-1}$.
Cut flow for the simplified signal model $\tilde{t}_1 \rightarrow bW\tilde{\chi}^0_1$ with $m(\tilde{t}_1)=550~ GeV$ and $m(\tilde{\chi}^0_1)=400~ GeV$ in the SRs for the three-body selection. The number of events is normalized to the cross-section and to an integrated luminosity of $139~fb^{-1}$.
Cut flow for the simplified signal model $\tilde{t}_1 \rightarrow bW\tilde{\chi}^0_1$ with $m(\tilde{t}_1)=550~ GeV$ and $m(\tilde{\chi}^0_1)=430~ GeV$ in the SRs for the three-body selection. The number of events is normalized to the cross-section and to an integrated luminosity of $139~fb^{-1}$.
Cut flow for the simplified signal model $\tilde{t}_1 \rightarrow bW\tilde{\chi}^0_1$ with $m(\tilde{t}_1)=550~ GeV$ and $m(\tilde{\chi}^0_1)=460~ GeV$ in the SRs for the three-body selection. The number of events is normalized to the cross-section and to an integrated luminosity of $139~fb^{-1}$.
Cut flow for the simplified signal model $\tilde{t}_1 \rightarrow b l \nu \tilde{\chi}^0_1$ with $m(\tilde{t}_1)=400~ GeV$ and $m(\tilde{\chi}^0_1)=380~ GeV$ in the SRs for the four-body selection. The number of events is normalized to the cross-section and to an integrated luminosity of $139~fb^{-1}$.
Cut flow for the simplified signal model $\tilde{t}_1 \rightarrow b l \nu \tilde{\chi}^0_1$ with $m(\tilde{t}_1)=460~ GeV$ and $m(\tilde{\chi}^0_1)=415~ GeV$ in the SRs for the four-body selection. The number of events is normalized to the cross-section and to an integrated luminosity of $139~fb^{-1}$.
Cut flow for the simplified signal model $\tilde{t}_1 \rightarrow b l \nu \tilde{\chi}^0_1$ with $m(\tilde{t}_1)=400~ GeV$ and $m(\tilde{\chi}^0_1)=320~ GeV$ in the SRs for the four-body selection. The number of events is normalized to the cross-section and to an integrated luminosity of $139~fb^{-1}$.
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.
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.
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-High-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-High-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-High-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-High-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-High-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-High-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-High-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-High-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-1J-High-EWK and SR-$\ell\ell bb$-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-1J-High-EWK and SR-$\ell\ell bb$-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-1J-High-EWK and SR-$\ell\ell bb$-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-1J-High-EWK and SR-$\ell\ell bb$-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 C1N2 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 C1N2 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 C1N2 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 C1N2 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 C1N2 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 C1N2 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 C1N2 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 C1N2 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 C1N2 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 C1N2 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 C1N2 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 C1N2 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 C1N2 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 C1N2 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 C1N2 model in the regions SR-High-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 C1N2 model in the regions SR-High-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 C1N2 model in the regions SR-High-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 C1N2 model in the regions SR-High-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 C1N2 model in the regions SR-High-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 C1N2 model in the regions SR-High-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 C1N2 model in the regions SR-High-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 C1N2 model in the regions SR-High-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 C1N2 model in the regions SR-1J-High-EWK and SR-$\ell\ell bb$-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 C1N2 model in the regions SR-1J-High-EWK and SR-$\ell\ell bb$-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 C1N2 model in the regions SR-1J-High-EWK and SR-$\ell\ell bb$-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 C1N2 model in the regions SR-1J-High-EWK and SR-$\ell\ell bb$-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) over the full \mll\ range for the GG_N2_SLN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_SLN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_SLN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_SLN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_SLN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_SLN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_SLN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_SLN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
A search for long-lived particles decaying into hadrons is presented. The analysis uses 139 fb$^{-1}$ of $pp$ collision data collected at $\sqrt{s} = 13$ TeV by the ATLAS detector at the LHC using events that contain multiple energetic jets and a displaced vertex. The search employs dedicated reconstruction techniques that significantly increase the sensitivity to long-lived particles decaying in the ATLAS inner detector. Background estimates for Standard Model processes and instrumental effects are extracted from data. The observed event yields are compatible with those expected from background processes. The results are used to set limits at 95% confidence level on model-independent cross sections for processes beyond the Standard Model, and on scenarios with pair-production of supersymmetric particles with long-lived electroweakinos that decay via a small $R$-parity-violating coupling. The pair-production of electroweakinos with masses below 1.5 TeV is excluded for mean proper lifetimes in the range from 0.03 ns to 1 ns. When produced in the decay of $m(\tilde{g})=2.4$ TeV gluinos, electroweakinos with $m(\tilde\chi^0_1)=1.5$ TeV are excluded with lifetimes in the range of 0.02 ns to 4 ns.
<b>Tables of Yields:</b> <a href="?table=validation_regions_yields_highpt_SR">Validation Regions Summary Yields, High-pT jet selections</a> <a href="?table=validation_regions_yields_trackless_SR">Validiation Regions Summary Yields, Trackless jet selections</a> <a href="?table=yields_highpt_SR_observed">Signal region (and sidebands) observed yields, High-pT jet selections</a> <a href="?table=yields_highpt_SR_expected">Signal region (and sidebands) expected yields, High-pT jet selections</a> <a href="?table=yields_trackless_SR_observed">Signal region (and sidebands) observed yields, Trackless jet selections</a> <a href="?table=yields_trackless_SR_expected">Signal region (and sidebands) expected yields, Trackless jet selections</a> <b>Exclusion Contours:</b> <a href="?table=excl_ewk_exp_nominal">EWK RPV signal; expected, nominal</a> <a href="?table=excl_ewk_exp_up">EWK RPV signal; expected, $+1\sigma$</a> <a href="?table=excl_ewk_exp_down">EWK RPV signal; expected, $-1\sigma$</a> <a href="?table=excl_ewk_obs_nominal">EWK RPV signal; observed, nominal</a> <a href="?table=excl_ewk_obs_up">EWK RPV signal; observed, $+1\sigma$</a> <a href="?table=excl_ewk_obs_down">EWK RPV signal; observed, $-1\sigma$</a> <a href="?table=excl_strong_mgluino_2400_GeV_exp_nominal">Strong RPV signal, m($\tilde{g}$)=2.4 TeV; expected, nominal</a> <a href="?table=excl_strong_mgluino_2400_GeV_exp_up">Strong RPV signal, m($\tilde{g}$)=2.4 TeV; expected, $+1\sigma$</a> <a href="?table=excl_strong_mgluino_2400_GeV_exp_down">Strong RPV signal, m($\tilde{g}$)=2.4 TeV; expected, $-1\sigma$</a> <a href="?table=excl_strong_mgluino_2400_GeV_obs_nominal">Strong RPV signal, m($\tilde{g}$)=2.4 TeV; observed, nominal</a> <a href="?table=excl_strong_mgluino_2400_GeV_obs_up">Strong RPV signal, m($\tilde{g}$)=2.4 TeV; observed, $+1\sigma$</a> <a href="?table=excl_strong_mgluino_2400_GeV_obs_down">Strong RPV signal, m($\tilde{g}$)=2.4 TeV; observed, $-1\sigma$</a> <a href="?table=excl_xsec_ewk">EWK RPV signal; cross-section limits for fixed lifetime values.</a> <a href="?table=excl_xsec_strong_mgluino_2400">Strong RPV signal, m($\tilde{g}$)=2.4 TeV; cross-section limits for fixed lifetime values.</a> <a href="?table=excl_strong_mgluino_2000_GeV_exp_nominal">Strong RPV signal, m($\tilde{g}$)=2.0 TeV; expected, nominal</a> <a href="?table=excl_strong_mgluino_2000_GeV_exp_up">Strong RPV signal, m($\tilde{g}$)=2.0 TeV; expected, $+1\sigma$</a> <a href="?table=excl_strong_mgluino_2000_GeV_exp_down">Strong RPV signal, m($\tilde{g}$)=2.0 TeV; expected, $-1\sigma$</a> <a href="?table=excl_strong_mgluino_2000_GeV_obs_nominal">Strong RPV signal, m($\tilde{g}$)=2.0 TeV; observed, nominal</a> <a href="?table=excl_strong_mgluino_2000_GeV_obs_up">Strong RPV signal, m($\tilde{g}$)=2.0 TeV; observed, $+1\sigma$</a> <a href="?table=excl_strong_mgluino_2000_GeV_obs_down">Strong RPV signal, m($\tilde{g}$)=2.0 TeV; observed, $-1\sigma$</a> <a href="?table=excl_strong_mgluino_2200_GeV_exp_nominal">Strong RPV signal, m($\tilde{g}$)=2.2 TeV; expected, nominal</a> <a href="?table=excl_strong_mgluino_2200_GeV_exp_up">Strong RPV signal, m($\tilde{g}$)=2.2 TeV; expected, $+1\sigma$</a> <a href="?table=excl_strong_mgluino_2200_GeV_exp_down">Strong RPV signal, m($\tilde{g}$)=2.2 TeV; expected, $-1\sigma$</a> <a href="?table=excl_strong_mgluino_2200_GeV_obs_nominal">Strong RPV signal, m($\tilde{g}$)=2.2 TeV; observed, nominal</a> <a href="?table=excl_strong_mgluino_2200_GeV_obs_up">Strong RPV signal, m($\tilde{g}$)=2.2 TeV; observed, $+1\sigma$</a> <a href="?table=excl_strong_mgluino_2200_GeV_obs_down">Strong RPV signal, m($\tilde{g}$)=2.2 TeV; observed, $-1\sigma$</a> <a href="?table=excl_strong_mchi0_50_GeV_exp_nominal">Strong RPV signal, m($\tilde{\chi}^{0}$)=0.1 TeV; expected, nominal</a> <a href="?table=excl_strong_mchi0_50_GeV_exp_up">Strong RPV signal, m($\tilde{\chi}^{0}$)=0.1 TeV; expected, $+1\sigma$</a> <a href="?table=excl_strong_mchi0_50_GeV_exp_down">Strong RPV signal, m($\tilde{\chi}^{0}$)=0.1 TeV; expected, $-1\sigma$</a> <a href="?table=excl_strong_mchi0_50_GeV_obs_nominal">Strong RPV signal, m($\tilde{\chi}^{0}$)=0.1 TeV; observed, nominal</a> <a href="?table=excl_strong_mchi0_50_GeV_obs_up">Strong RPV signal, m($\tilde{\chi}^{0}$)=0.1 TeV; observed, $+1\sigma$</a> <a href="?table=excl_strong_mchi0_50_GeV_obs_down">Strong RPV signal, m($\tilde{\chi}^{0}$)=0.1 TeV; observed, $-1\sigma$</a> <a href="?table=excl_strong_mchi0_450_GeV_exp_nominal">Strong RPV signal, m($\tilde{\chi}^{0}$)=0.5 TeV; expected, nominal</a> <a href="?table=excl_strong_mchi0_450_GeV_exp_up">Strong RPV signal, m($\tilde{\chi}^{0}$)=0.5 TeV; expected, $+1\sigma$</a> <a href="?table=excl_strong_mchi0_450_GeV_exp_down">Strong RPV signal, m($\tilde{\chi}^{0}$)=0.5 TeV; expected, $-1\sigma$</a> <a href="?table=excl_strong_mchi0_450_GeV_obs_nominal">Strong RPV signal, m($\tilde{\chi}^{0}$)=0.5 TeV; observed, nominal</a> <a href="?table=excl_strong_mchi0_450_GeV_obs_up">Strong RPV signal, m($\tilde{\chi}^{0}$)=0.5 TeV; observed, $+1\sigma$</a> <a href="?table=excl_strong_mchi0_450_GeV_obs_down">Strong RPV signal, m($\tilde{\chi}^{0}$)=0.5 TeV; observed, $-1\sigma$</a> <a href="?table=excl_strong_tau_0p01_ns_exp_nominal">Strong RPV signal, $\tau$=0.01 ns; expected, nominal</a> <a href="?table=excl_strong_tau_0p01_ns_exp_up">Strong RPV signal, $\tau$=0.01 ns; expected, $+1\sigma$</a> <a href="?table=excl_strong_tau_0p01_ns_exp_down">Strong RPV signal, $\tau$=0.01 ns; expected, $-1\sigma$</a> <a href="?table=excl_strong_tau_0p01_ns_obs_nominal">Strong RPV signal, $\tau$=0.01 ns; observed, nominal</a> <a href="?table=excl_strong_tau_0p01_ns_obs_up">Strong RPV signal, $\tau$=0.01 ns; observed, $+1\sigma$</a> <a href="?table=excl_strong_tau_0p01_ns_obs_down">Strong RPV signal, $\tau$=0.01 ns; observed, $-1\sigma$</a> <a href="?table=excl_strong_tau_0p1_ns_exp_nominal">Strong RPV signal, $\tau$=0.10 ns; expected, nominal</a> <a href="?table=excl_strong_tau_0p1_ns_exp_up">Strong RPV signal, $\tau$=0.10 ns; expected, $+1\sigma$</a> <a href="?table=excl_strong_tau_0p1_ns_exp_down">Strong RPV signal, $\tau$=0.10 ns; expected, $-1\sigma$</a> <a href="?table=excl_strong_tau_0p1_ns_obs_nominal">Strong RPV signal, $\tau$=0.10 ns; observed, nominal</a> <a href="?table=excl_strong_tau_0p1_ns_obs_up">Strong RPV signal, $\tau$=0.10 ns; observed, $+1\sigma$</a> <a href="?table=excl_strong_tau_0p1_ns_obs_down">Strong RPV signal, $\tau$=0.10 ns; observed, $-1\sigma$</a> <a href="?table=excl_strong_tau_1_ns_exp_nominal">Strong RPV signal, $\tau$=1.00 ns; expected, nominal</a> <a href="?table=excl_strong_tau_1_ns_exp_up">Strong RPV signal, $\tau$=1.00 ns; expected, $+1\sigma$</a> <a href="?table=excl_strong_tau_1_ns_exp_down">Strong RPV signal, $\tau$=1.00 ns; expected, $-1\sigma$</a> <a href="?table=excl_strong_tau_1_ns_obs_nominal">Strong RPV signal, $\tau$=1.00 ns; observed, nominal</a> <a href="?table=excl_strong_tau_1_ns_obs_up">Strong RPV signal, $\tau$=1.00 ns; observed, $+1\sigma$</a> <a href="?table=excl_strong_tau_1_ns_obs_down">Strong RPV signal, $\tau$=1.00 ns; observed, $-1\sigma$</a> <a href="?table=excl_strong_tau_10_ns_exp_nominal">Strong RPV signal, $\tau$=10.00 ns; expected, nominal</a> <a href="?table=excl_strong_tau_10_ns_exp_up">Strong RPV signal, $\tau$=10.00 ns; expected, $+1\sigma$</a> <a href="?table=excl_strong_tau_10_ns_exp_down">Strong RPV signal, $\tau$=10.00 ns; expected, $-1\sigma$</a> <a href="?table=excl_strong_tau_10_ns_obs_nominal">Strong RPV signal, $\tau$=10.00 ns; observed, nominal</a> <a href="?table=excl_strong_tau_10_ns_obs_up">Strong RPV signal, $\tau$=10.00 ns; observed, $+1\sigma$</a> <a href="?table=excl_strong_tau_10_ns_obs_down">Strong RPV signal, $\tau$=10.00 ns; observed, $-1\sigma$</a> <a href="?table=excl_xsec_strong_chi0_1250">Strong RPV signal, m($\tilde{\chi}^0_1$)=1.25 TeV; cross-section limits for fixed lifetime values.</a> <br/><b>Reinterpretation Material:</b> See the attached resource (purple button on the left) or directly <a href="https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/SUSY-2016-08/hepdata_info.pdf">this link</a> for information about acceptance definition and about how to use the efficiency histograms below. SLHA files are also available in the reource page of this HEPData record. <a href="?table=acceptance_highpt_strong"> Acceptance cutflow, High-pT SR, Strong production.</a> <a href="?table=acceptance_trackless_ewk"> Acceptance cutflow, Trackless SR, EWK production.</a> <a href="?table=acceptance_trackless_ewk_hf"> Acceptance cutflow, Trackless SR, EWK production with heavy-flavor.</a> <a href="?table=acceptance_highpt_ewk_hf"> Acceptance cutflow, Trackless SR, EWK production with heavy-flavor.</a> <a href="?table=event_efficiency_HighPt_R_1150_mm">Reinterpretation Material: Event-level Efficiency for HighPt SR selections, R < 1150 mm</a> <a href="?table=event_efficiency_HighPt_R_1150_3870_mm">Reinterpretation Material: Event-level Efficiency for HighPt SR selections, R [1150, 3870] mm</a> <a href="?table=event_efficiency_HighPt_R_3870_mm">Reinterpretation Material: Event-level Efficiency for HighPt SR selections, R > 3870 mm</a> <a href="?table=event_efficiency_Trackless_R_1150_mm">Reinterpretation Material: Event-level Efficiency for Trackless SR selections, R < 1150 mm</a> <a href="?table=event_efficiency_Trackless_R_1150_3870_mm">Reinterpretation Material: Event-level Efficiency for Trackless SR selections, R [1150, 3870] mm</a> <a href="?table=event_efficiency_Trackless_R_3870_mm">Reinterpretation Material: Event-level Efficiency for Trackless SR selections, R > 3870 mm</a> <a href="?table=vertex_efficiency_R_22_mm">Reinterpretation Material: Vertex-level Efficiency for R < 22 mm</a> <a href="?table=vertex_efficiency_R_22_25_mm">Reinterpretation Material: Vertex-level Efficiency for R [22, 25] mm</a> <a href="?table=vertex_efficiency_R_25_29_mm">Reinterpretation Material: Vertex-level Efficiency for R [25, 29] mm</a> <a href="?table=vertex_efficiency_R_29_38_mm">Reinterpretation Material: Vertex-level Efficiency for R [29, 38] mm</a> <a href="?table=vertex_efficiency_R_38_46_mm">Reinterpretation Material: Vertex-level Efficiency for R [38, 46] mm</a> <a href="?table=vertex_efficiency_R_46_73_mm">Reinterpretation Material: Vertex-level Efficiency for R [46, 73] mm</a> <a href="?table=vertex_efficiency_R_73_84_mm">Reinterpretation Material: Vertex-level Efficiency for R [73, 84] mm</a> <a href="?table=vertex_efficiency_R_84_111_mm">Reinterpretation Material: Vertex-level Efficiency for R [84, 111] mm</a> <a href="?table=vertex_efficiency_R_111_120_mm">Reinterpretation Material: Vertex-level Efficiency for R [111, 120] mm</a> <a href="?table=vertex_efficiency_R_120_145_mm">Reinterpretation Material: Vertex-level Efficiency for R [120, 145] mm</a> <a href="?table=vertex_efficiency_R_145_180_mm">Reinterpretation Material: Vertex-level Efficiency for R [145, 180] mm</a> <a href="?table=vertex_efficiency_R_180_300_mm">Reinterpretation Material: Vertex-level Efficiency for R [180, 300] mm</a> <br/><b>Cutflow Tables:</b> <a href="?table=cutflow_highpt_strong"> Cutflow (Acceptance x Efficiency), High-pT SR, Strong production.</a> <a href="?table=cutflow_trackless_ewk"> Cutflow (Acceptance x Efficiency), Trackless SR, EWK production.</a> <a href="?table=cutflow_trackless_ewk_hf"> Cutflow (Acceptance x Efficiency), Trackless SR, EWK production with heavy-flavor quarks.</a> <a href="?table=cutflow_highpt_ewk_hf"> Cutflow (Acceptance x Efficiency), High-pT SR, EWK production with heavy-flavor quarks.</a>
Validation of background estimate in validation regions for the High-pT jet selections
Validation of background estimate in validation regions for the Trackless jet selections
Two-dimensional distribution of the invariant mass $m_{DV}$ and the track multiplicity in the High-pT jet SR for observed data events
Two-dimensional distribution of the invariant mass $m_{DV}$ and the track multiplicity in the High-pT jet SR for expected signal events in the strong gluino pair pair production model with m(gluino)=1.8 TeV, m(chi0)=0.2 TeV, tau(chi0)=0.1 ns
Two-dimensional distribution of the invariant mass $m_{DV}$ and the track multiplicity in the Trackless jet SR for observed data events
Two-dimensional distribution of the invariant mass $m_{DV}$ and the track multiplicity in the Trackless jet SR for expected signal events in the electroweak pair production model
Expected exclusion limits at 95% CL on the lifetime and mass of the neutralino in electroweakino pair production models
Expected (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in electroweakino pair production models
Expected (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in electroweakino pair production models
Observed exclusion limits at 95% CL on the lifetime and mass of the neutralino in electroweakino pair production models
Observed (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in electroweakino pair production models
Observed (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in electroweakino pair production models
Expected exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.4 TeV
Expected (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.4 TeV
Expected (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.4 TeV
Observed exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.4 TeV
Observed (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.4 TeV
Observed (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.4 TeV
Exclusion limits at 95% CL on the production cross section in the electroweak pair production model.
Exclusion limits at 95% CL on the production cross section in the strong gluino pair production models and m(gluino)=2.4 TeV
Expected exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.0 TeV
Expected (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.0 TeV
Expected (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.0 TeV
Observed exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.0 TeV
Observed (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.0 TeV
Observed (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.0 TeV
Expected exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.2 TeV
Expected (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.2 TeV
Expected (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.2 TeV
Observed exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.2 TeV
Observed (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.2 TeV
Observed (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.2 TeV
Expected exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=50 GeV
Expected (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=50 GeV
Expected (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=50 GeV
Observed exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=50 GeV
Observed (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=50 GeV
Observed (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=50 GeV
Expected exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=450 GeV
Expected (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=450 GeV
Expected (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=450 GeV
Observed exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=450 GeV
Observed (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=450 GeV
Observed (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=450 GeV
Expected exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.01 ns
Expected (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.01 ns
Expected (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.01 ns
Observed exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.01 ns
Observed (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.01 ns
Observed (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.01 ns
Expected exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.1 ns
Expected (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.1 ns
Expected (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.1 ns
Observed exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.1 ns
Observed (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.1 ns
Observed (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.1 ns
Expected exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=1 ns
Expected (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=1 ns
Expected (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=1 ns
Observed exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=1 ns
Observed (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=1 ns
Observed (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=1 ns
Expected exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=10 ns
Expected (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=10 ns
Expected (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=10 ns
Observed exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=10 ns
Observed (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=10 ns
Observed (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=10 ns
Exclusion limits at 95% CL on the production cross section in the strong gluino pair production models and m($ ilde{\chi}^0_1$)=1.25 TeV
Acceptance cutflow for the High-pT SR for representative points in the strong gluino pair production model. See additional resources for more information.
Acceptance cutflow for the Trackless SR for representative points in the electroweak pair production model. See additional resources for more information.
Acceptance cutflow for the Trackless SR for representative points in the electroweak pair production model with heavy-flavor quarks final state. See additional resources for more information.
Acceptance cutflow for the High-pT SR for representative points in the electroweak pair production model with heavy-flavor quarks final state. See additional resources for more information.
Reinterpretation Material: Event-level Efficiency for HighPt SR selections, R < 1150 mm
Reinterpretation Material: Event-level Efficiency for HighPt SR selections, R [1150, 3870] mm
Reinterpretation Material: Event-level Efficiency for HighPt SR selections, R > 3870 mm
Reinterpretation Material: Event-level Efficiency for Trackless SR selections, R < 1150 mm
Reinterpretation Material: Event-level Efficiency for Trackless SR selections, R [1150, 3870] mm
Reinterpretation Material: Event-level Efficiency for Trackless SR selections, R > 3870 mm
Reinterpretation Material: Vertex-level Efficiency for R < 22 mm
Reinterpretation Material: Vertex-level Efficiency for R [22, 25] mm
Reinterpretation Material: Vertex-level Efficiency for R [25, 29] mm
Reinterpretation Material: Vertex-level Efficiency for R [29, 38] mm
Reinterpretation Material: Vertex-level Efficiency for R [38, 46] mm
Reinterpretation Material: Vertex-level Efficiency for R [46, 73] mm
Reinterpretation Material: Vertex-level Efficiency for R [73, 84] mm
Reinterpretation Material: Vertex-level Efficiency for R [84, 111] mm
Reinterpretation Material: Vertex-level Efficiency for R [111, 120] mm
Reinterpretation Material: Vertex-level Efficiency for R [120, 145] mm
Reinterpretation Material: Vertex-level Efficiency for R [145, 180] mm
Reinterpretation Material: Vertex-level Efficiency for R [180, 300] mm
Cutflow (acceptance x efficiency) for the High-pT SR for representative points in the strong gluino pair production model. See additional resources for more information.
Cutflow (acceptance x efficiency) for the Trackless SR for representative points in the electroweak pair production model. See additional resources for more information.
Cutflow (acceptance x efficiency) for the Trackless SR for representative points in the electroweak pair production model with heavy-flavor quarks. See additional resources for more information.
Cutflow (acceptance x efficiency) for the High-pT SR for representative points in the electroweak pair production model with heavy-flavor quarks. See additional resources for more information.
A search is presented for a heavy resonance $Y$ decaying into a Standard Model Higgs boson $H$ and a new particle $X$ in a fully hadronic final state. The full Large Hadron Collider Run 2 dataset of proton-proton collisions at $\sqrt{s}= 13$ TeV collected by the ATLAS detector from 2015 to 2018 is used, and corresponds to an integrated luminosity of 139 fb$^{-1}$. The search targets the high $Y$-mass region, where the $H$ and $X$ have a significant Lorentz boost in the laboratory frame. A novel signal region is implemented using anomaly detection, where events are selected solely because of their incompatibility with a learned background-only model. It is defined using a jet-level tagger for signal-model-independent selection of the boosted $X$ particle, representing the first application of fully unsupervised machine learning to an ATLAS analysis. Two additional signal regions are implemented to target a benchmark $X$ decay into two quarks, covering topologies where the $X$ is reconstructed as either a single large-radius jet or two small-radius jets. The analysis selects Higgs boson decays into $b\bar{b}$, and a dedicated neural-network-based tagger provides sensitivity to the boosted heavy-flavor topology. No significant excess of data over the expected background is observed, and the results are presented as upper limits on the production cross section $\sigma(pp \rightarrow Y \rightarrow XH \rightarrow q\bar{q}b\bar{b}$) for signals with $m_Y$ between 1.5 and 6 TeV and $m_X$ between 65 and 3000 GeV.
Acceptance times efficiency for signal grid in anomaly signal region.
Acceptance times efficiency for signal grid in anomaly signal region.
Acceptance times efficiency for signal grid in merged two-prong signal region.
Acceptance times efficiency for signal grid in merged two-prong signal region.
Acceptance times efficiency for signal grid in resolved two-prong signal region.
Acceptance times efficiency for signal grid in resolved two-prong signal region.
The obtained p-value from comparing data to background estimation across all bins, defined by windows in the X and Y particle masses, in the anomaly signal region.
The obtained p-value from comparing data to background estimation across all bins, defined by windows in the X and Y particle masses, in the anomaly signal region.
The expected 95% CL limits on the cross-section $\sigma(pp \rightarrow Y \rightarrow XH \rightarrow q\bar{q}b\bar{b}$) in pb in the two-dimensional space of $m_Y$ versus $m_X$, obtained from a simultaneous fit of both merged and resolved two-prong signal regions with all statistical and systematic uncertainties.
The expected 95% CL limits on the cross-section $\sigma(pp \rightarrow Y \rightarrow XH \rightarrow q\bar{q}b\bar{b}$) in pb in the two-dimensional space of $m_Y$ versus $m_X$, obtained from a simultaneous fit of both merged and resolved two-prong signal regions with all statistical and systematic uncertainties.
The observed 95% CL limits on the cross-section $\sigma(pp \rightarrow Y \rightarrow XH \rightarrow q\bar{q}b\bar{b}$) in pb in the two-dimensional space of $m_Y$ versus $m_X$, obtained from a simultaneous fit of both merged and resolved two-prong signal regions with all statistical and systematic uncertainties.
The observed 95% CL limits on the cross-section $\sigma(pp \rightarrow Y \rightarrow XH \rightarrow q\bar{q}b\bar{b}$) in pb in the two-dimensional space of $m_Y$ versus $m_X$, obtained from a simultaneous fit of both merged and resolved two-prong signal regions with all statistical and systematic uncertainties.
A direct search for Higgs bosons produced via vector-boson fusion and subsequently decaying into invisible particles is reported. The analysis uses 139 $\text{fb}^{-1}$ of $pp$ collision data at a centre-of-mass energy of $\sqrt{s}$=13 $\text{TeV}$ recorded by the ATLAS detector at the LHC. The observed numbers of events are found to be in agreement with the background expectation from Standard Model processes. For a scalar Higgs boson with a mass of 125 $\text{GeV}$ and a Standard Model production cross section, an observed upper limit of $0.145$ is placed on the branching fraction of its decay into invisible particles at 95% confidence level, with an expected limit of $0.103$. These results are interpreted in the context of models where the Higgs boson acts as a portal to dark matter, and limits are set on the scattering cross section of weakly interacting massive particles and nucleons. Invisible decays of additional scalar bosons with masses from 50 $\text{GeV}$ to 2 $\text{TeV}$ are also studied, and the derived upper limits on the cross section times branching fraction decrease with increasing mass from 1.0 $\text{pb}$ for a scalar boson mass of 50 $\text{GeV}$ to 0.1 $\text{pb}$ at a mass of 2 $\text{TeV}$.
Yields after each selection criterion for a signal sample of an invisibly decaying Higgs boson produced in VBF and ggF for 139 $fb^{-1}$ of data. The lines 'Timing of j1/j2' are referring to requirements that are part of the jet cleaning, and which ensure that the timing of the two leading jets is compatible with the bunch crossing. The last sixteen rows show the yield in each SR bin and the efficiency with respect to the inclusive signal region.
Statistical combinations of searches for charginos and neutralinos using various decay channels are performed using $139\,$fb$^{-1}$ of $pp$ collision data at $\sqrt{s}=13\,$TeV with the ATLAS detector at the Large Hadron Collider. Searches targeting pure-wino chargino pair production, pure-wino chargino-neutralino production, or higgsino production decaying via Standard Model $W$, $Z$, or $h$ bosons are combined to extend the mass reach to the produced SUSY particles by 30-100 GeV. The depth of the sensitivity of the original searches is also improved by the combinations, lowering the 95% CL cross-section upper limits by 15%-40%.
Expected 95% CL exclusion limits on the simplified models of chargino-pair production decaying via W bosons.
$+1\sigma$ expected 95% CL exclusion limits on the simplified models of chargino-pair production decaying via W bosons.
$-1\sigma$ expected 95% CL exclusion limits on the simplified models of chargino-pair production decaying via W bosons.
Observed 95% CL exclusion limits on the simplified models of chargino-pair production decaying via W bosons.
$+1\sigma$ observed 95% CL exclusion limits on the simplified models of chargino-pair production decaying via W bosons.
$-1\sigma$ observed 95% CL exclusion limits on the simplified models of chargino-pair production decaying via W bosons.
Expected 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.
$+1\sigma$ expected 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.
$-1\sigma$ expected 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.
Observed 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.
$+1\sigma$ observed 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.
$-1\sigma$ observed 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.
Expected 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and h bosons.
$+1\sigma$ expected 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and h bosons.
$-1\sigma$ expected 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and h bosons.
Observed 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and h bosons.
$+1\sigma$ observed 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and h bosons.
$-1\sigma$ observed 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and h bosons.
Expected 95% CL exclusion limits on the simplified models of higgsino GGM scenarios.
$+1\sigma$ expected 95% CL exclusion limits on the simplified models of higgsino GGM scenarios.
$-1\sigma$ expected 95% CL exclusion limits on the simplified models of higgsino GGM scenarios.
Observed 95% CL exclusion limits on the simplified models of higgsino GGM scenarios.
$+1\sigma$ observed 95% CL exclusion limits on the simplified models of higgsino GGM scenarios.
$-1\sigma$ observed 95% CL exclusion limits on the simplified models of higgsino GGM scenarios.
Observed upper limit on the signal cross section in fb for the production of $\tilde{\chi}_1^{+}\tilde{\chi}_{1}^{-}$.
The analyses used in combination for each scenario to set limits in models of the production of $\tilde{\chi}_1^{+}\tilde{\chi}_{1}^{-}$.
Observed upper limit on the signal cross section in fb for chargino--neutralino production decaying via W and Z bosons.
The analyses used in combination for each scenario to set limits in models of chargino--neutralino production decaying via W and Z bosons.
Expected 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.
$+1\sigma$ expected 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.
$-1\sigma$ expected 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.
Observed 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.
$+1\sigma$ observed 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.
$-1\sigma$ observed 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.
Observed upper limit on the signal cross section in fb for chargino--neutralino production decaying via W and h bosons.
The analyses used in combination for each scenario to set limits in models of chargino--neutralino production decaying via W and h bosons.
Observed upper limit on the signal cross section in fb for higgsino GGM scenarios.
The analyses used in combination for each scenario to set limits in higgsino GGM scenarios.
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.
The associated production of a Higgs boson and a top-quark pair is measured in events characterised by the presence of one or two electrons or muons. The Higgs boson decay into a $b$-quark pair is used. The analysed data, corresponding to an integrated luminosity of 139 fb$^{-1}$, were collected in proton-proton collisions at the Large Hadron Collider between 2015 and 2018 at a centre-of-mass energy of $\sqrt{s}=13$ TeV. The measured signal strength, defined as the ratio of the measured signal yield to that predicted by the Standard Model, is $0.35^{+0.36}_{-0.34}$. This result is compatible with the Standard Model prediction and corresponds to an observed (expected) significance of 1.0 (2.7) standard deviations. The signal strength is also measured differentially in bins of the Higgs boson transverse momentum in the simplified template cross-section framework, including a bin for specially selected boosted Higgs bosons with transverse momentum above 300 GeV.
Comparison between data and prediction for the DNN $P(H)$ output for the Higgs boson candidate prior to any fit to the data in the single-lepton boosted channel for $300\le p_T^H<450$ GeV. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Comparison between data and prediction for the DNN $P(H)$ output for the Higgs boson candidate prior to any fit to the data in the single-lepton boosted channel for $p_{{T}}^{H}\ge 450$ GeV. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Performance of the Higgs boson reconstruction algorithms. For each row of `truth' ${\hat{p}_{{T}}^{H}}$, the matrix shows (in percentages) the fraction of all Higgs boson candidates with reconstructed $p_T^H$ in the various bins of the dilepton (left), single-lepton resolved (middle) and boosted (right) channels.
Pre-fit distribution of the reconstructed Higgs boson candidate $p_T^H$ for the dilepton $SR^{\geq 4j}_{\geq 4b}$ signal region. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations, except for the uncertainty in the $k({t\bar {t}+{\geq }1b})$ normalisation factor which is not defined pre-fit. The last bin includes the overflow.
Pre-fit distribution of the reconstructed Higgs boson candidate $p_T^H$ for the single-lepton resolved $SR^{\geq 6j}_{\geq 4b}$ signal region. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations, except for the uncertainty in the $k({t\bar {t}+{\geq }1b})$ normalisation factor which is not defined pre-fit. The last bin includes the overflow.
Pre-fit distribution of the reconstructed Higgs boson candidate $p_T^H$ for the single-lepton boosted ${{SR}_{{boosted}}}$ signal region. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations, except for the uncertainty in the $k({t\bar {t}+{\geq }1b})$ normalisation factor which is not defined pre-fit. The last bin includes the overflow.
Comparison of predicted and observed event yields in each of the control and signal regions in the dilepton channel after the fit to the data. The uncertainty band includes all uncertainties and their correlations.
Comparison of predicted and observed event yields in each of the control and signal regions in the single-lepton channels after the fit to the data. The uncertainty band includes all uncertainties and their correlations.
Comparison between data and prediction for the BDT discriminant in the dilepton SRs after the inclusive fit to the data for $0\le p_T^H<120$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Comparison between data and prediction for the BDT discriminant in the dilepton SRs after the inclusive fit to the data for $120\le p_T^H<200$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Comparison between data and prediction for the BDT discriminant in the dilepton SRs after the inclusive fit to the data for $200\le p_T^H<300$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Comparison between data and prediction for the BDT discriminant in the dilepton SRs after the inclusive fit to the data for $p_{{T}}^{H}\ge 300$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Comparison between data and prediction for the BDT discriminant in the single-lepton resolved SRs after the inclusive fit to the data for $0\le p_T^H<120$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Comparison between data and prediction for the BDT discriminant in the single-lepton resolved SRs after the inclusive fit to the data for $120\le p_T^H<200$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Comparison between data and prediction for the BDT discriminant in the single-lepton resolved SRs after the inclusive fit to the data for $200\le p_T^H<300$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Comparison between data and prediction for the BDT discriminant in the single-lepton resolved SRs after the inclusive fit to the data for $300\le p_T^H<450$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Comparison between data and prediction for the BDT discriminant in the single-lepton resolved SRs after the inclusive fit to the data for $p_{{T}}^{H}\ge 450$ GeV (yield only). The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Comparison between data and prediction for the BDT discriminant in the single-lepton boosted SRs after the inclusive fit to the data for $300\le p_T^H<450$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Comparison between data and prediction for the BDT discriminant in the single-lepton boosted SRs after the inclusive fit to the data for $p_{{T}}^{H}\ge 450$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Comparison between data and prediction for ${\Delta R^{{avg}}_{bb}}$ after the inclusive fit to the data in the single-lepton $CR^{5j}_{{\geq}4b\ lo}$ control region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The first (last) bin includes the underflow (overflow).
Comparison between data and prediction for ${\Delta R^{{avg}}_{bb}}$ after the inclusive fit to the data in the single-lepton $CR^{5j}_{{\geq}4b\ hi}$ control region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The first (last) bin includes the underflow (overflow).
Post-fit yields of signal ($S$) and total background ($B$) as a function of $\log (S/B)$, compared with data. Final-discriminant bins in all dilepton and single-lepton analysis regions are combined into bins of $\log (S/B)$, with the signal normalised to the SM prediction used for the computation of $\log (S/B)$. The signal is then shown normalised to the best-fit value and the SM prediction. The lower frame reports the ratio of data to background, and this is compared with the expected ${t\bar {t}H}$-signal-plus-background yield divided by the background-only yield for the best-fit signal strength (solid red line) and the SM prediction (dashed orange line).
Comparison between data and prediction for the reconstruction BDT score for the Higgs boson candidate identified using Higgs boson information, after the inclusive fit to the data in the dilepton resolved channel for $0\le p_T^H<120$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Comparison between data and prediction for the average $\Delta \eta $ between $b$-tagged jets, after the inclusive fit to the data in the dilepton resolved channel for $0\le p_T^H<120$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Comparison between data and prediction for the likelihood discriminant, after the inclusive fit to the data in the single-lepton resolved channel for $0\le p_T^H<120$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Comparison between data and prediction for the average $\Delta R$ for all possible combinations of $b$-tagged jet pairs, after the inclusive fit to the data in the single-lepton resolved channel for $0\le p_T^H<120$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Comparison between data and prediction for the DNN $P(H)$ output for the Higgs boson candidate after the inclusive fit to the data in the single-lepton boosted channel for $300\le p_T^H<450$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Comparison between data and prediction for the DNN $P(H)$ output for the Higgs boson candidate after the inclusive fit to the data in the single-lepton boosted channel for $p_{{T}}^{H}\ge 450$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Post-fit distribution of the reconstructed Higgs boson candidate mass for the dilepton $SR^{\geq 4j}_{\geq 4b}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The first (last) bin includes the underflow (overflow).
Post-fit distribution of the reconstructed Higgs boson candidate mass for the single-lepton resolved $SR^{\geq 6j}_{\geq 4b}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The first (last) bin includes the underflow (overflow).
Post-fit distribution of the reconstructed Higgs boson candidate mass for the single-lepton boosted ${{SR}_{{boosted}}}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The first (last) bin includes the underflow (overflow).
Fitted values of the ${t\bar {t}H}$ signal strength parameter in the individual channels and in the inclusive signal-strength measurement.
Ranking of the 20 nuisance parameters with the largest post-fit impact on $\mu $ in the fit. Nuisance parameters corresponding to statistical uncertainties in the simulated event samples are not included. The empty blue rectangles correspond to the pre-fit impact on $\mu $ and the filled blue ones to the post-fit impact on $\mu $, both referring to the upper scale. The impact of each nuisance parameter, $\Delta \mu $, is computed by comparing the nominal best-fit value of $\mu $ with the result of the fit when fixing the considered nuisance parameter to its best-fit value, $\hat{\theta }$, shifted by its pre-fit (post-fit) uncertainties $\pm \Delta \theta $ ($\pm \Delta \hat{\theta }$). The black points show the pulls of the nuisance parameters relative to their nominal values, $\theta _0$. These pulls and their relative post-fit errors, $\Delta \hat{\theta }/\Delta \theta $, refer to the lower scale. The `ljets' (`dilep') label refers to the single-lepton (dilepton) channel.
Pre-fit distribution of the number of jets in the dilepton $SR^{\geq 4j}_{\geq 4b}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the Standard Model expectation. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations, except the uncertainty in the $k({t\bar {t}+{\geq }1b})$ normalisation factor that is not defined pre-fit.
Pre-fit distribution of the number of jets in the single-lepton resolved $SR^{\geq 6j}_{\geq 4b}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the Standard Model expectation. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations, except the uncertainty in the $k({t\bar {t}+{\geq }1b})$ normalisation factor that is not defined pre-fit.
Pre-fit distribution of the number of jets in the single-lepton boosted ${{SR}_{{boosted}}}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the Standard Model expectation. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations, except the uncertainty in the $k({t\bar {t}+{\geq }1b})$ normalisation factor that is not defined pre-fit.
Post-fit distribution of the number of jets in the dilepton $SR^{\geq 4j}_{\geq 4b}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Post-fit distribution of the number of jets in the single-lepton resolved $SR^{\geq 6j}_{\geq 4b}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Post-fit distribution of the number of jets in the single-lepton boosted ${{SR}_{{boosted}}}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Post-fit distribution of the reconstructed Higgs boson candidate $p_T^H$ for the dilepton $SR^{\geq 4j}_{\geq 4b}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The last bin includes the overflow.
Post-fit distribution of the reconstructed Higgs boson candidate $p_T^H$ for the single-lepton resolved $SR^{\geq 6j}_{\geq 4b}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The last bin includes the overflow.
Post-fit distribution of the reconstructed Higgs boson candidate $p_T^H$ for the single-lepton boosted ${{SR}_{{boosted}}}$ signal region. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The last bin includes the overflow.
Signal-strength measurements in the individual STXS ${\hat{p}_{{T}}^{H}}$ bins, as well as the inclusive signal strength.
95% CL simplified template cross-section upper limits in the individual STXS ${\hat{p}_{{T}}^{H}}$ bins, as well as the inclusive limit. The observed limits are shown (solid black lines), together with the expected limits both in the background-only hypothesis (dotted black lines) and in the SM hypothesis (dotted red lines). In the case of the expected limits in the background-only hypothesis, one- and two-standard-deviation uncertainty bands are also shown. The hatched uncertainty bands correspond to the theory uncertainty in the fiducial cross-section prediction in each bin.
The ratios $S/B$ (black solid line, referring to the vertical axis on the left) and $S/\sqrt{B}$ (red dashed line, referring to the vertical axis on the right) for each category in the inclusive analysis in the dilepton channel (left) and in the single-lepton channels (right), where $S$ ($B$) is the number of selected signal (background) events predicted by the simulation and normalised to a luminosity of 139 fb$^{-1}$ .
Comparison between data and prediction for the $\Delta R$ between the Higgs candidate and the ${t\bar {t}}$ candidate system, after the inclusive fit to the data in the dilepton resolved channel for $0\le p_T^H<120$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Comparison between data and prediction for the number of $b$-tagged jet pairs with an invariant mass within 30 GeV of 125 GeV, after the inclusive fit to the data in the dilepton resolved channel for $0\le p_T^H<120$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Comparison between data and prediction for the reconstruction BDT score for the Higgs boson candidate identified using Higgs boson information, after the inclusive fit to the data in the single-lepton resolved channel for $0\le p_T^H<120$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Comparison between data and prediction for the $\Delta R$ between the two highest ${p_{{T}}}$ $b$-tagged jets, after the inclusive fit to the data in the single-lepton resolved channel for $0\le p_T^H<120$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations.
Comparison between data and prediction for the sum of $b$-tagging discriminants of jets from Higgs, hadronic top and leptonic top candidates, after the inclusive fit to the data in the single-lepton boosted channel for $300\le p_T^H<450$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The first (last) bin includes the underflow (overflow).
Comparison between data and prediction for the sum of $b$-tagging discriminants of jets from Higgs, hadronic top and leptonic top candidates, after the inclusive fit to the data in the single-lepton boosted channel for $p_{{T}}^{H}\ge 450$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The first (last) bin includes the underflow (overflow).
Comparison between data and prediction for the hadronic top candidate invariant mass, after the inclusive fit to the data in the single-lepton boosted channel for $300\le p_T^H<450$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The first (last) bin includes the underflow (overflow).
Comparison between data and prediction for the hadronic top candidate invariant mass, after the inclusive fit to the data in the single-lepton boosted channel for $p_{{T}}^{H}\ge 450$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The first (last) bin includes the underflow (overflow).
Comparison between data and prediction for the fraction of the sum of $b$-tagging discriminants of all jets not associated to the Higgs or hadronic top candidates, after the inclusive fit to the data in the single-lepton boosted channel for $300\le p_T^H<450$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The first (last) bin includes the underflow (overflow).
Comparison between data and prediction for the fraction of the sum of $b$-tagging discriminants of all jets not associated to the Higgs or hadronic top candidates, after the inclusive fit to the data in the single-lepton boosted channel for $p_{{T}}^{H}\ge 450$ GeV. The ${t\bar {t}H}$ signal yield (solid red) is normalised to the fitted $\mu $ value from the inclusive fit. The dashed line shows the ${t\bar {t}H}$ signal distribution normalised to the total background prediction. The uncertainty band includes all uncertainties and their correlations. The first (last) bin includes the underflow (overflow).
Ranking of the 20 nuisance parameters with the largest post-fit impact on $\mu $ in the STXS fit for $0\le {\hat{p}_{{T}}^{H}}<120$ GeV. Nuisance parameters corresponding to statistical uncertainties in the simulated event samples are not included. The empty blue rectangles correspond to the pre-fit impact on $\mu $ and the filled blue ones to the post-fit impact on $\mu $, both referring to the upper scale. The impact of each nuisance parameter, $\Delta \mu $, is computed by comparing the nominal best-fit value of $\mu $ with the result of the fit when fixing the considered nuisance parameter to its best-fit value, $\hat{\theta }$, shifted by its pre-fit (post-fit) uncertainties $\pm \Delta \theta $ ($\pm \Delta \hat{\theta }$). The black points show the pulls of the nuisance parameters relative to their nominal values, $\theta _0$. These pulls and their relative post-fit errors, $\Delta \hat{\theta }/\Delta \theta $, refer to the lower scale. For experimental uncertainties that are decomposed into several independent sources, NP X corresponds to the X$^{th}$ nuisance parameter, ordered by their impact on $\mu $. The `ljets' (`dilep') label refers to the single-lepton (dilepton) channel.
Ranking of the 20 nuisance parameters with the largest post-fit impact on $\mu $ in the STXS fit for $120\le {\hat{p}_{{T}}^{H}}<200$ GeV. Nuisance parameters corresponding to statistical uncertainties in the simulated event samples are not included. The empty blue rectangles correspond to the pre-fit impact on $\mu $ and the filled blue ones to the post-fit impact on $\mu $, both referring to the upper scale. The impact of each nuisance parameter, $\Delta \mu $, is computed by comparing the nominal best-fit value of $\mu $ with the result of the fit when fixing the considered nuisance parameter to its best-fit value, $\hat{\theta }$, shifted by its pre-fit (post-fit) uncertainties $\pm \Delta \theta $ ($\pm \Delta \hat{\theta }$). The black points show the pulls of the nuisance parameters relative to their nominal values, $\theta _0$. These pulls and their relative post-fit errors, $\Delta \hat{\theta }/\Delta \theta $, refer to the lower scale. For experimental uncertainties that are decomposed into several independent sources, NP X corresponds to the X$^{th}$ nuisance parameter, ordered by their impact on $\mu $. The `ljets' (`dilep') label refers to the single-lepton (dilepton) channel.
Ranking of the 20 nuisance parameters with the largest post-fit impact on $\mu $ in the STXS fit for $200\le {\hat{p}_{{T}}^{H}}<300$ GeV. Nuisance parameters corresponding to statistical uncertainties in the simulated event samples are not included. The empty blue rectangles correspond to the pre-fit impact on $\mu $ and the filled blue ones to the post-fit impact on $\mu $, both referring to the upper scale. The impact of each nuisance parameter, $\Delta \mu $, is computed by comparing the nominal best-fit value of $\mu $ with the result of the fit when fixing the considered nuisance parameter to its best-fit value, $\hat{\theta }$, shifted by its pre-fit (post-fit) uncertainties $\pm \Delta \theta $ ($\pm \Delta \hat{\theta }$). The black points show the pulls of the nuisance parameters relative to their nominal values, $\theta _0$. These pulls and their relative post-fit errors, $\Delta \hat{\theta }/\Delta \theta $, refer to the lower scale. For experimental uncertainties that are decomposed into several independent sources, NP X corresponds to the X$^{th}$ nuisance parameter, ordered by their impact on $\mu $. The `ljets' (`dilep') label refers to the single-lepton (dilepton) channel.
Ranking of the 20 nuisance parameters with the largest post-fit impact on $\mu $ in the STXS fit for $300\le {\hat{p}_{{T}}^{H}}<450$ GeV. Nuisance parameters corresponding to statistical uncertainties in the simulated event samples are not included. The empty blue rectangles correspond to the pre-fit impact on $\mu $ and the filled blue ones to the post-fit impact on $\mu $, both referring to the upper scale. The impact of each nuisance parameter, $\Delta \mu $, is computed by comparing the nominal best-fit value of $\mu $ with the result of the fit when fixing the considered nuisance parameter to its best-fit value, $\hat{\theta }$, shifted by its pre-fit (post-fit) uncertainties $\pm \Delta \theta $ ($\pm \Delta \hat{\theta }$). The black points show the pulls of the nuisance parameters relative to their nominal values, $\theta _0$. These pulls and their relative post-fit errors, $\Delta \hat{\theta }/\Delta \theta $, refer to the lower scale. For experimental uncertainties that are decomposed into several independent sources, NP X corresponds to the X$^{th}$ nuisance parameter, ordered by their impact on $\mu $. The `ljets' (`dilep') label refers to the single-lepton (dilepton) channel.
Ranking of the 20 nuisance parameters with the largest post-fit impact on $\mu $ in the STXS fit for ${\hat{p}_{{T}}^{H}}\ge 450$ GeV. Nuisance parameters corresponding to statistical uncertainties in the simulated event samples are not included. The empty blue rectangles correspond to the pre-fit impact on $\mu $ and the filled blue ones to the post-fit impact on $\mu $, both referring to the upper scale. The impact of each nuisance parameter, $\Delta \mu $, is computed by comparing the nominal best-fit value of $\mu $ with the result of the fit when fixing the considered nuisance parameter to its best-fit value, $\hat{\theta }$, shifted by its pre-fit (post-fit) uncertainties $\pm \Delta \theta $ ($\pm \Delta \hat{\theta }$). The black points show the pulls of the nuisance parameters relative to their nominal values, $\theta _0$. These pulls and their relative post-fit errors, $\Delta \hat{\theta }/\Delta \theta $, refer to the lower scale. For experimental uncertainties that are decomposed into several independent sources, NP X corresponds to the X$^{th}$ nuisance parameter, ordered by their impact on $\mu $. The `ljets' (`dilep') label refers to the single-lepton (dilepton) channel.
95% confidence level upper limits on signal-strength measurements in the individual STXS ${\hat{p}_{{T}}^{H}}$ bins, as well as the inclusive signal-strength limit, after the fit used to extract multiple signal-strength parameters. The observed limits are shown (solid black lines), together with the expected limits both in the background-only hypothesis (dotted black lines) and in the SM hypothesis (dotted red lines). In the case of the expected limits in the background-only hypothesis, one- and two-standard-deviation uncertainty bands are also shown.
Post-fit correlation matrix (in percentages) between the $\mu $ values obtained in the STXS bins.
Performance of the Higgs boson reconstruction algorithms. For each row of `truth' ${\hat{p}_{{T}}^{H}}$, the matrix shows (in percentages) the fraction of Higgs boson candidates which are truth-matched to ${b\bar {b}}$ decays, with reconstructed $p_T^H$ in the various bins of the dilepton (left), single lepton resolved (middle) and boosted (right) channels.
Pre-fit event yields in the dilepton signal regions and control regions. All uncertainties are included except the $k({t\bar {t}+{\geq }1b})$ uncertainty that is not defined pre-fit. For the ${t\bar {t}H}$ signal, the pre-fit yield values correspond to the theoretical prediction and corresponding uncertainties. `Other sources' refers to s-channel, t-channel, $tW$, $tWZ$, $tZq$, $Z+$ jets and diboson events.
Post-fit event yields in the dilepton signal regions and control regions, after the inclusive fit in all channels. All uncertainties are included, taking into account correlations. For the ${t\bar {t}H}$ signal, the post-fit yield and uncertainties correspond to those in the inclusive signal-strength measurement. `Other sources' refers to s-channel, t-channel, $tW$, $tWZ$, $tZq$, $Z+$ jets and diboson events.
Pre-fit event yields in the single-lepton resolved and boosted signal regions and control regions. All uncertainties are included except the $k({t\bar {t}+{\geq }1b})$ uncertainty that is not defined pre-fit. For the ${t\bar {t}H}$ signal, the pre-fit yield values correspond to the theoretical prediction and corresponding uncertainties. `Other top sources' refers to s-channel, t-channel, $tWZ$ and $tZq$ events.
Post-fit event yields in the single-lepton resolved and boosted signal regions and control regions, after the inclusive fit in all channels. All uncertainties are included, taking into account correlations. For the ${t\bar {t}H}$ signal, the post-fit yield and uncertainties correspond to those in the inclusive signal-strength measurement. `Other top sources' refers to s-channel, t-channel, $tWZ$ and $tZq$ events.
Breakdown of the contributions to the uncertainties in $\mu$. The contributions from the different sources of uncertainty are evaluated after the fit. The $\Delta \mu $ values are obtained by repeating the fit after having fixed a certain set of nuisance parameters corresponding to a group of systematic uncertainties, and then evaluating $(\Delta \mu)^2$ by subtracting the resulting squared uncertainty of $\mu $ from its squared uncertainty found in the full fit. The same procedure is followed when quoting the effect of the ${t\bar {t}+{\geq }1b}$ normalisation. The total uncertainty is different from the sum in quadrature of the different components due to correlations between nuisance parameters existing in the fit.
Fraction (in percentages) of signal events, after SR and CR selections, originating from $b\bar {b}$, $WW$ and other remaining Higgs boson decay modes in the dilepton channel.
Fraction (in percentages) of signal events, after SR and CR selections, originating from $b\bar {b}$, $WW$ and other remaining Higgs boson decay modes in the single-lepton channels.
Predicted SM ${t\bar {t}H}$ cross-section in each of the five STXS ${\hat{p}_{{T}}^{H}}$ bins and signal acceptance times efficiency (including all event selection criteria) in each STXS bin as well as for the inclusive ${\hat{p}_{{T}}^{H}}$ range.
Number of expected signal events before the fit, after each selection requirement applied to enter the dilepton channel $SR^{\geq 4j}_{\geq 4b}$ region. All ${t\bar {t}H}$ signal events are included, regardless of the $H$ or ${t\bar {t}H}$ decay mode. All object corrections are applied, except for the initial number of events which is calculated using the NLO QCD+EW theoretical prediction. All quoted numbers are rounded to unity. More details on the selection criteria can be found in the text.
Number of expected signal events before the fit, after each selection requirement applied to enter the single-lepton channel resolved $SR^{\geq 6j}_{\geq 4b}$ region. All ${t\bar {t}H}$ signal events are included, regardless of the $H$ or ${t\bar {t}H}$ decay mode. All object corrections are applied, except for the initial number of events which is calculated using the NLO QCD+EW theoretical prediction. All quoted numbers are rounded to unity. More details on the selection criteria can be found in the text.
Number of expected signal events before the fit, after each selection requirement applied to enter the single-lepton channel boosted $SR_{boosted}$ region. All ${t\bar {t}H}$ signal events are included, regardless of the $H$ or ${t\bar {t}H}$ decay mode. All object corrections are applied, except for the initial number of events which is calculated using the NLO QCD+EW theoretical prediction. All quoted numbers are rounded to unity. More details on the selection criteria can be found in the text.
A search for pair production of squarks or gluinos decaying via sleptons or weak bosons is reported. The search targets a final state with exactly two leptons with same-sign electric charge or at least three leptons without any charge requirement. The analysed data set corresponds to an integrated luminosity of 139 fb$^{-1}$ of proton$-$proton collisions collected at a centre-of-mass energy of 13 TeV with the ATLAS detector at the LHC. Multiple signal regions are defined, targeting several SUSY simplified models yielding the desired final states. A single control region is used to constrain the normalisation of the $WZ$+jets background. No significant excess of events over the Standard Model expectation is observed. The results are interpreted in the context of several supersymmetric models featuring R-parity conservation or R-parity violation, yielding exclusion limits surpassing those from previous searches. In models considering gluino (squark) pair production, gluino (squark) masses up to 2.2 (1.7) TeV are excluded at 95% confidence level.
Observed exclusion limits at 95% CL from Fig 7(a) for $\tilde{g}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$
Positive one $\sigma$ observed exclusion limits at 95% CL from Fig 7(a) for $\tilde{g}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$
Negative one $\sigma$ observed exclusion limits at 95% CL from Fig 7(a) for $\tilde{g}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$
Expected exclusion limits at 95% CL from Fig 7(a) for $\tilde{g}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$
One $\sigma$ band of expected exclusion limits at 95% CL from Fig 7(a) for $\tilde{g}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$
Observed exclusion limits at 95% CL from Fig 7(c) for $\tilde{g}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$
Positive one $\sigma$ observed exclusion limits at 95% CL from Fig 7(c) for $\tilde{g}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$
Negative one $\sigma$ observed exclusion limits at 95% CL from Fig 7(c) for $\tilde{g}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$
Expected exclusion limits at 95% CL from Fig 7(c) for $\tilde{g}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$
One $\sigma$ band of expected exclusion limits at 95% CL from Fig 7(c) for $\tilde{g}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$
Observed exclusion limits at 95% CL from Fig 7(f) for $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$
Positive one $\sigma$ observed exclusion limits at 95% CL from Fig 7(f) for $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$
Negative one $\sigma$ observed exclusion limits at 95% CL from Fig 7(f) for $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$
Expected exclusion limits at 95% CL from Fig 7(f) for $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$
One $\sigma$ band of expected exclusion limits at 95% CL from Fig 7(f) for $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$
Observed exclusion limits at 95% CL from Fig 7(e) for direct $\tilde{\chi_{1}^{0}}$ decay into SM leptons and quarks via a non-zero RPV coupling $\lambda'$
Positive one $\sigma$ observed exclusion limits at 95% CL from Fig 7(e) for direct $\tilde{\chi_{1}^{0}}$ decay into SM leptons and quarks via a non-zero RPV coupling $\lambda'$
Negative one $\sigma$ observed exclusion limits at 95% CL from Fig 7(e) for direct $\tilde{\chi_{1}^{0}}$ decay into SM leptons and quarks via a non-zero RPV coupling $\lambda'$
Expected exclusion limits at 95% CL from Fig 7(e) for direct $\tilde{\chi_{1}^{0}}$ decay into SM leptons and quarks via a non-zero RPV coupling $\lambda'$
One $\sigma$ band of expected exclusion limits at 95% CL from Fig 7(e) for direct $\tilde{\chi_{1}^{0}}$ decay into SM leptons and quarks via a non-zero RPV coupling $\lambda'$
Observed exclusion limits at 95% CL from Fig 7(b) for $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$
Positive one $\sigma$ observed exclusion limits at 95% CL from Fig 7(b) for $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$
Negative one $\sigma$ observed exclusion limits at 95% CL from Fig 7(b) for $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$
Expected exclusion limits at 95% CL from Fig 7(b) for $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$
One $\sigma$ band of expected exclusion limits at 95% CL from Fig 7(b) for $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$
Observed exclusion limits at 95% CL from Fig 7(d) for $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$
Positive one $\sigma$ observed exclusion limits at 95% CL from Fig 7(d) for $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$
Negative one $\sigma$ observed exclusion limits at 95% CL from Fig 7(d) for $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$
Expected exclusion limits at 95% CL from Fig 7(d) for $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$
One $\sigma$ band of expected exclusion limits at 95% CL from Fig 7(d) for $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$
N-1 distribution for $m_{\mathrm{eff}}$of observed data and expected background in SRGGWZ-H.
N-1 distribution for $E_{\mathrm{T}}^{\mathrm{miss}}$of observed data and expected background in SRGGSlep-M.
N-1 distribution for $\sum{p_{\mathrm{T}}^\mathrm{jet}}$of observed data and expected background in SRUDD-ge2b.
N-1 distribution for $m_{\mathrm{eff}}$of observed data and expected background in SRLQD.
N-1 distribution for $m_{\mathrm{eff}}$of observed data and expected background in SRSSWZ-H.
N-1 distribution for $m_{\mathrm{eff}}$of observed data and expected background in SRSSSlep-H(loose).
Signal acceptance for SRGGWZ-H signal region from Fig 10(c) in a SUSY scenario where $\tilde{g}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$
Signal efficiency for SRGGWZ-H signal region from Fig 15(c) in a SUSY scenario where $\tilde{g}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$
Signal acceptance for SRGGWZ-M signal region from Fig 10(b) in a SUSY scenario where $\tilde{g}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$
Signal efficiency for SRGGWZ-M signal region from Fig 15(b) in a SUSY scenario where $\tilde{g}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$
Signal acceptance for SRGGWZ-L signal region from Fig 10(a) in a SUSY scenario where $\tilde{g}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$
Signal efficiency for SRGGWZ-L signal region from Fig 15(a) in a SUSY scenario where $\tilde{g}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$
Signal acceptance for SRGGSlep-L signal region from Fig 12(a) in a SUSY scenario where $\tilde{g}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$
Signal efficiency for SRGGSlep-L signal region from Fig 17(a) in a SUSY scenario where $\tilde{g}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$
Signal acceptance for SRGGSlep-M signal region from Fig 12(b) in a SUSY scenario where $\tilde{g}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$
Signal efficiency for SRGGSlep-M signal region from Fig 17(b) in a SUSY scenario where $\tilde{g}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$
Signal acceptance for SRGGSlep-H signal region from Fig 12(c) in a SUSY scenario where $\tilde{g}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$
Signal efficiency for SRGGSlep-H signal region from Fig 17(c) in a SUSY scenario where $\tilde{g}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$
Signal acceptance for SRUDD-1b signal region from Fig 14(b) in a SUSY scenario where $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$
Signal efficiency for SRUDD-1b signal region from Fig 19(b) in a SUSY scenario where $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$
Signal acceptance for SRUDD-2b signal region from Fig 14(c) in a SUSY scenario where $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$
Signal efficiency for SRUDD-2b signal region from Fig 19(c) in a SUSY scenario where $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$
Signal acceptance for SRUDD-ge2b signal region from Fig 14(d) in a SUSY scenario where $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$
Signal efficiency for SRUDD-ge2b signal region from Fig 19(d) in a SUSY scenario where $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$
Signal acceptance for SRUDD-ge3b signal region from Fig 14(e) in a SUSY scenario where $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$
Signal efficiency for SRUDD-ge3b signal region from Fig 19(e) in a SUSY scenario where $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$
Signal acceptance for SRLQD signal region from Fig 14(a) in a SUSY scenario where direct $\tilde{\chi_{1}^{0}}$ decay into SM leptons and quarks via a non-zero RPV coupling $\lambda'$
Signal efficiency for SRLQD signal region from Fig 19(a) in a SUSY scenario where direct $\tilde{\chi_{1}^{0}}$ decay into SM leptons and quarks via a non-zero RPV coupling $\lambda'$
Signal acceptance for SRSSWZ-L signal region from Fig 11(a) in a SUSY scenario where $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$
Signal efficiency for SRSSWZ-L signal region from Fig 16(a) in a SUSY scenario where $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$
Signal acceptance for SRSSWZ-ML signal region from Fig 11(b) in a SUSY scenario where $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$
Signal efficiency for SRSSWZ-ML signal region from Fig 16(b) in a SUSY scenario where $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$
Signal acceptance for SRSSWZ-MH signal region from Fig 11(c) in a SUSY scenario where $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$
Signal efficiency for SRSSWZ-MH signal region from Fig 16(c) in a SUSY scenario where $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$
Signal acceptance for SRSSWZ-H signal region from Fig 11(d) in a SUSY scenario where $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$
Signal efficiency for SRSSWZ-H signal region from Fig 16(d) in a SUSY scenario where $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$
Signal acceptance for SRSSSlep-H signal region from Fig 13(d) in a SUSY scenario where $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$
Signal efficiency for SRSSSlep-H signal region from Fig 18(d) in a SUSY scenario where $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$
Signal acceptance for SRSSSlep-MH signal region from Fig 13(c) in a SUSY scenario where $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$
Signal efficiency for SRSSSlep-MH signal region from Fig 18(c) in a SUSY scenario where $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$
Signal acceptance for SRSSSlep-L signal region from Fig 13(a) in a SUSY scenario where $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$
Signal efficiency for SRSSSlep-L signal region from Fig 18(a) in a SUSY scenario where $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$
Signal acceptance for SRSSSlep-ML signal region from Fig 13(b) in a SUSY scenario where $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$
Signal efficiency for SRSSSlep-ML signal region from Fig 18(b) in a SUSY scenario where $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$
Signal acceptance for SRSSSlep-H(loose) signal region from Fig 13(e) in a SUSY scenario where $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$
Signal efficiency for SRSSSlep-H(loose) signal region from Fig 18(e) in a SUSY scenario where $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRGGWZ-H in a susy scenario where $\tilde{g}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$. The masses of the superpartners involved in the process are set to $m(\tilde{g})$ = 1400 GeV, $m(\tilde{\chi_{1}^{0}})$ = 1000 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRGGWZ-M in a susy scenario where $\tilde{g}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$. The masses of the superpartners involved in the process are set to $m(\tilde{g})$ = 1400 GeV, $m(\tilde{\chi_{1}^{0}})$ = 1000 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRGGWZ-L in a susy scenario where $\tilde{g}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$. The masses of the superpartners involved in the process are set to $m(\tilde{g})$ = 1400 GeV, $m(\tilde{\chi_{1}^{0}})$ = 1000 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRGGSlep-L in a susy scenario where $\tilde{g}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$. The masses of the superpartners involved in the process are set to $m(\tilde{g})$ = 2000 GeV, $m(\tilde{\chi_{1}^{0}})$ = 500 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRGGSlep-M in a susy scenario where $\tilde{g}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$. The masses of the superpartners involved in the process are set to $m(\tilde{g})$ = 2000 GeV, $m(\tilde{\chi_{1}^{0}})$ = 500 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRGGSlep-H in a susy scenario where $\tilde{g}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$. The masses of the superpartners involved in the process are set to $m(\tilde{g})$ = 2000 GeV, $m(\tilde{\chi_{1}^{0}})$ = 500 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRUDD-1b in a susy scenario where $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$. The masses of the superpartners involved in the process are set to $m(\tilde{g})$ = 1600 GeV, $m(\tilde{t})$ = 600 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRUDD-2b in a susy scenario where $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$. The masses of the superpartners involved in the process are set to $m(\tilde{g})$ = 1600 GeV, $m(\tilde{t})$ = 600 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRUDD-ge2b in a susy scenario where $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$. The masses of the superpartners involved in the process are set to $m(\tilde{g})$ = 1600 GeV, $m(\tilde{t})$ = 600 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRUDD-ge3b in a susy scenario where $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$. The masses of the superpartners involved in the process are set to $m(\tilde{g})$ = 1600 GeV, $m(\tilde{t})$ = 600 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRLQD in a susy scenario where direct $\tilde{\chi_{1}^{0}}$ decay into SM leptons and quarks via a non-zero RPV coupling $\lambda'$. The masses of the superpartners involved in the process are set to $m(\tilde{g})$ = 2200 GeV, $m(\tilde{\chi_{1}^{0}})$ = 1870 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRSSWZ-L in a susy scenario where $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$. The masses of the superpartners involved in the process are set to $m(\tilde{q})$ = 800 GeV, $m(\tilde{\chi_{1}^{0}})$ = 600 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRSSWZ-ML in a susy scenario where $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$. The masses of the superpartners involved in the process are set to $m(\tilde{q})$ = 800 GeV, $m(\tilde{\chi_{1}^{0}})$ = 600 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRSSWZ-MH in a susy scenario where $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$. The masses of the superpartners involved in the process are set to $m(\tilde{q})$ = 800 GeV, $m(\tilde{\chi_{1}^{0}})$ = 600 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRSSWZ-H in a susy scenario where $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$. The masses of the superpartners involved in the process are set to $m(\tilde{q})$ = 800 GeV, $m(\tilde{\chi_{1}^{0}})$ = 600 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRSSSlep-H in a susy scenario where $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$. The masses of the superpartners involved in the process are set to $m(\tilde{q})$ = 1000 GeV, $m(\tilde{\chi_{1}^{0}})$ = 800 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRSSSlep-MH in a susy scenario where $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$. The masses of the superpartners involved in the process are set to $m(\tilde{q})$ = 1000 GeV, $m(\tilde{\chi_{1}^{0}})$ = 800 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRSSSlep-L in a susy scenario where $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$. The masses of the superpartners involved in the process are set to $m(\tilde{q})$ = 1000 GeV, $m(\tilde{\chi_{1}^{0}})$ = 800 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRSSSlep-ML in a susy scenario where $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$. The masses of the superpartners involved in the process are set to $m(\tilde{q})$ = 1000 GeV, $m(\tilde{\chi_{1}^{0}})$ = 800 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRSSSlep-H(loose) in a susy scenario where $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$. The masses of the superpartners involved in the process are set to $m(\tilde{q})$ = 1000 GeV, $m(\tilde{\chi_{1}^{0}})$ = 800 GeV. Only statistical uncertainties are shown.
Cross-section upper limits at 95% CL from Fig1(a) for $\tilde{g}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$
Cross-section upper limits at 95% CL from Fig1(c) for $\tilde{g}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$
Cross-section upper limits at 95% CL from Fig1(f) for $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$
Cross-section upper limits at 95% CL from Fig1(e) for direct $\tilde{\chi_{1}^{0}}$ decay into SM leptons and quarks via a non-zero RPV coupling $\lambda'$
Cross-section upper limits at 95% CL from Fig1(b) for $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$
Cross-section upper limits at 95% CL from Fig1(d) for $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$
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.
<b>- - - - - - - - Overview of HEPData Record - - - - - - - -</b> <b>Title: </b><em>Search for direct pair production of sleptons and charginos decaying to two leptons and neutralinos with mass splittings near the $W$ boson mass in $\sqrt{s}=13$ TeV $pp$ collisions with the ATLAS detector</em> <b>Paper website:</b> <a href="https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/SUSY-2019-02/">SUSY-2019-02</a> <b>Exclusion contours</b> <ul><li><b>Sleptons:</b> <a href=?table=excl_comb_obs_nominal>Combined Observed Nominal</a> <a href=?table=excl_comb_obs_up>Combined Observed Up</a> <a href=?table=excl_comb_obs_down>Combined Observed Down</a> <a href=?table=excl_comb_exp_nominal>Combined Expected Nominal</a> <a href=?table=excl_comb_exp_up>Combined Expected Up</a> <a href=?table=excl_comb_exp_down>Combined Expected Down</a> <a href=?table=excl_comb_obs_nominal_dM>Combined Observed Nominal $(\Delta m)$</a> <a href=?table=excl_comb_obs_up_dM>Combined Observed Up $(\Delta m)$</a> <a href=?table=excl_comb_obs_down_dM>Combined Observed Down $(\Delta m)$</a> <a href=?table=excl_comb_exp_nominal_dM>Combined Expected Nominal $(\Delta m)$</a> <a href=?table=excl_comb_exp_up_dM>Combined Expected Up $(\Delta m)$</a> <a href=?table=excl_comb_exp_down_dM>Combined Expected Down $(\Delta m)$</a> <a href=?table=excl_ee_obs_nominal>$\tilde{e}_\mathrm{L,R}$ Observed Nominal</a> <a href=?table=excl_ee_exp_nominal>$\tilde{e}_\mathrm{L,R}$ Expected Nominal</a> <a href=?table=excl_eLeL_obs_nominal>$\tilde{e}_\mathrm{L}$ Observed Nominal</a> <a href=?table=excl_eLeL_exp_nominal>$\tilde{e}_\mathrm{L}$ Expected Nominal</a> <a href=?table=excl_eReR_obs_nominal>$\tilde{e}_\mathrm{R}$ Observed Nominal</a> <a href=?table=excl_eReR_exp_nominal>$\tilde{e}_\mathrm{R}$ Expected Nominal</a> <a href=?table=excl_ee_obs_nominal_dM>$\tilde{e}_\mathrm{L,R}$ Observed Nominal $(\Delta m)$</a> <a href=?table=excl_ee_exp_nominal_dM>$\tilde{e}_\mathrm{L,R}$ Expected Nominal $(\Delta m)$</a> <a href=?table=excl_eLeL_obs_nominal_dM>$\tilde{e}_\mathrm{L}$ Observed Nominal $(\Delta m)$</a> <a href=?table=excl_eLeL_exp_nominal_dM>$\tilde{e}_\mathrm{L}$ Expected Nominal $(\Delta m)$</a> <a href=?table=excl_eReR_obs_nominal_dM>$\tilde{e}_\mathrm{R}$ Observed Nominal $(\Delta m)$</a> <a href=?table=excl_eReR_exp_nominal_dM>$\tilde{e}_\mathrm{R}$ Expected Nominal $(\Delta m)$</a> <a href=?table=excl_mm_obs_nominal>$\tilde{\mu}_\mathrm{L,R}$ Observed Nominal</a> <a href=?table=excl_mm_exp_nominal>$\tilde{\mu}_\mathrm{L,R}$ Expected Nominal</a> <a href=?table=excl_mLmL_obs_nominal>$\tilde{\mu}_\mathrm{L}$ Observed Nominal</a> <a href=?table=excl_mLmL_exp_nominal>$\tilde{\mu}_\mathrm{L}$ Expected Nominal</a> <a href=?table=excl_mRmR_obs_nominal>$\tilde{\mu}_\mathrm{R}$ Observed Nominal</a> <a href=?table=excl_mRmR_exp_nominal>$\tilde{\mu}_\mathrm{R}$ Expected Nominal</a> <a href=?table=excl_mm_obs_nominal_dM>$\tilde{\mu}_\mathrm{L,R}$ Observed Nominal $(\Delta m)$</a> <a href=?table=excl_mm_exp_nominal_dM>$\tilde{\mu}_\mathrm{L,R}$ Expected Nominal $(\Delta m)$</a> <a href=?table=excl_mLmL_obs_nominal_dM>$\tilde{\mu}_\mathrm{L}$ Observed Nominal $(\Delta m)$</a> <a href=?table=excl_mLmL_exp_nominal_dM>$\tilde{\mu}_\mathrm{L}$ Expected Nominal $(\Delta m)$</a> <a href=?table=excl_mRmR_obs_nominal_dM>$\tilde{\mu}_\mathrm{R}$ Observed Nominal $(\Delta m)$</a> <a href=?table=excl_mRmR_exp_nominal_dM>$\tilde{\mu}_\mathrm{R}$ Expected Nominal $(\Delta m)$</a> <a href=?table=excl_comb_obs_nominal_SR0j>Combined Observed Nominal SR-0j</a> <a href=?table=excl_comb_exp_nominal_SR0j>Combined Expected Nominal SR-0j</a> <a href=?table=excl_comb_obs_nominal_SR1j>Combined Observed Nominal SR-1j</a> <a href=?table=excl_comb_exp_nominal_SR1j>Combined Expected Nominal SR-1j</a> <li><b>Charginos:</b> <a href=?table=excl_c1c1_obs_nominal>Observed Nominal</a> <a href=?table=excl_c1c1_obs_up>Observed Up</a> <a href=?table=excl_c1c1_obs_down>Observed Down</a> <a href=?table=excl_c1c1_exp_nominal>Expected Nominal</a> <a href=?table=excl_c1c1_exp_nominal>Expected Up</a> <a href=?table=excl_c1c1_exp_nominal>Expected Down</a> <a href=?table=excl_c1c1_obs_nominal_dM>Observed Nominal $(\Delta m)$</a> <a href=?table=excl_c1c1_obs_up_dM>Observed Up $(\Delta m)$</a> <a href=?table=excl_c1c1_obs_down_dM>Observed Down $(\Delta m)$</a> <a href=?table=excl_c1c1_exp_nominal_dM>Expected Nominal $(\Delta m)$</a> <a href=?table=excl_c1c1_exp_nominal_dM>Expected Up $(\Delta m)$</a> <a href=?table=excl_c1c1_exp_nominal_dM>Expected Down $(\Delta m)$</a> </ul> <b>Upper Limits</b> <ul><li><b>Sleptons:</b> <a href=?table=UL_slep>ULs</a> <li><b>Charginos:</b> <a href=?table=UL_c1c1>ULs</a> </ul> <b>Pull Plots</b> <ul><li><b>Sleptons:</b> <a href=?table=pullplot_slep>SRs summary plot</a> <li><b>Charginos:</b> <a href=?table=pullplot_c1c1>SRs summary plot</a> </ul> <b>Cutflows</b> <ul><li><b>Sleptons:</b> <a href=?table=Cutflow_slep_SR0j>Towards SR-0J</a> <a href=?table=Cutflow_slep_SR1j>Towards SR-1J</a> <li><b>Charginos:</b> <a href=?table=Cutflow_SRs>Towards SRs</a> </ul> <b>Acceptance and Efficiencies</b> <ul><li><b>Sleptons:</b> <a href=?table=Acceptance_SR0j_MT2_100_infty>SR-0J $m_{\mathrm{T2}}^{100} \in[100,\infty)$ Acceptance</a> <a href=?table=Efficiency_SR0j_MT2_100_infty>SR-0J $m_{\mathrm{T2}}^{100} \in[100,\infty)$ Efficiency</a> <a href=?table=Acceptance_SR0j_MT2_110_infty>SR-0J $m_{\mathrm{T2}}^{100} \in[110,\infty)$ Acceptance</a> <a href=?table=Efficiency_SR0j_MT2_110_infty>SR-0J $m_{\mathrm{T2}}^{100} \in[110,\infty)$ Efficiency</a> <a href=?table=Acceptance_SR0j_MT2_120_infty>SR-0J $m_{\mathrm{T2}}^{100} \in[120,\infty)$ Acceptance</a> <a href=?table=Efficiency_SR0j_MT2_120_infty>SR-0J $m_{\mathrm{T2}}^{100} \in[120,\infty)$ Efficiency</a> <a href=?table=Acceptance_SR0j_MT2_130_infty>SR-0J $m_{\mathrm{T2}}^{100} \in[130,\infty)$ Acceptance</a> <a href=?table=Efficiency_SR0j_MT2_130_infty>SR-0J $m_{\mathrm{T2}}^{100} \in[130,\infty)$ Efficiency</a> <a href=?table=Acceptance_SR0j_MT2_100_105>SR-0J $m_{\mathrm{T2}}^{100} \in[100,105)$ Acceptance</a> <a href=?table=Efficiency_SR0j_MT2_100_105>SR-0J $m_{\mathrm{T2}}^{100} \in[100,105)$ Efficiency</a> <a href=?table=Acceptance_SR0j_MT2_105_110>SR-0J $m_{\mathrm{T2}}^{100} \in[105,110)$ Acceptance</a> <a href=?table=Efficiency_SR0j_MT2_105_110>SR-0J $m_{\mathrm{T2}}^{100} \in[105,110)$ Efficiency</a> <a href=?table=Acceptance_SR0j_MT2_110_115>SR-0J $m_{\mathrm{T2}}^{100} \in[110,115)$ Acceptance</a> <a href=?table=Efficiency_SR0j_MT2_110_115>SR-0J $m_{\mathrm{T2}}^{100} \in[110,115)$ Efficiency</a> <a href=?table=Acceptance_SR0j_MT2_115_120>SR-0J $m_{\mathrm{T2}}^{100} \in[115,120)$ Acceptance</a> <a href=?table=Efficiency_SR0j_MT2_115_120>SR-0J $m_{\mathrm{T2}}^{100} \in[115,120)$ Efficiency</a> <a href=?table=Acceptance_SR0j_MT2_120_125>SR-0J $m_{\mathrm{T2}}^{100} \in[120,125)$ Acceptance</a> <a href=?table=Efficiency_SR0j_MT2_125_130>SR-0J $m_{\mathrm{T2}}^{100} \in[125,130)$ Efficiency</a> <a href=?table=Acceptance_SR0j_MT2_130_140>SR-0J $m_{\mathrm{T2}}^{100} \in[130,140)$ Acceptance</a> <a href=?table=Efficiency_SR0j_MT2_130_140>SR-0J $m_{\mathrm{T2}}^{100} \in[130,140)$ Efficiency</a> <a href=?table=Acceptance_SR0j_MT2_140_infty>SR-0J $m_{\mathrm{T2}}^{100} \in[140,\infty)$ Acceptance</a> <a href=?table=Efficiency_SR0j_MT2_140_infty>SR-0J $m_{\mathrm{T2}}^{100} \in[140,\infty)$ Efficiency</a> <a href=?table=Acceptance_SR1j_MT2_100_infty>SR-1j $m_{\mathrm{T2}}^{100} \in[100,\infty)$ Acceptance</a> <a href=?table=Efficiency_SR1j_MT2_100_infty>SR-1j $m_{\mathrm{T2}}^{100} \in[100,\infty)$ Efficiency</a> <a href=?table=Acceptance_SR1j_MT2_110_infty>SR-1j $m_{\mathrm{T2}}^{100} \in[110,\infty)$ Acceptance</a> <a href=?table=Efficiency_SR1j_MT2_110_infty>SR-1j $m_{\mathrm{T2}}^{100} \in[110,\infty)$ Efficiency</a> <a href=?table=Acceptance_SR1j_MT2_120_infty>SR-1j $m_{\mathrm{T2}}^{100} \in[120,\infty)$ Acceptance</a> <a href=?table=Efficiency_SR1j_MT2_120_infty>SR-1j $m_{\mathrm{T2}}^{100} \in[120,\infty)$ Efficiency</a> <a href=?table=Acceptance_SR1j_MT2_130_infty>SR-1j $m_{\mathrm{T2}}^{100} \in[130,\infty)$ Acceptance</a> <a href=?table=Efficiency_SR1j_MT2_130_infty>SR-1j $m_{\mathrm{T2}}^{100} \in[130,\infty)$ Efficiency</a> <a href=?table=Acceptance_SR1j_MT2_100_105>SR-1j $m_{\mathrm{T2}}^{100} \in[100,105)$ Acceptance</a> <a href=?table=Efficiency_SR1j_MT2_100_105>SR-1j $m_{\mathrm{T2}}^{100} \in[100,105)$ Efficiency</a> <a href=?table=Acceptance_SR1j_MT2_105_110>SR-1j $m_{\mathrm{T2}}^{100} \in[105,110)$ Acceptance</a> <a href=?table=Efficiency_SR1j_MT2_105_110>SR-1j $m_{\mathrm{T2}}^{100} \in[105,110)$ Efficiency</a> <a href=?table=Acceptance_SR1j_MT2_110_115>SR-1j $m_{\mathrm{T2}}^{100} \in[110,115)$ Acceptance</a> <a href=?table=Efficiency_SR1j_MT2_110_115>SR-1j $m_{\mathrm{T2}}^{100} \in[110,115)$ Efficiency</a> <a href=?table=Acceptance_SR1j_MT2_115_120>SR-1j $m_{\mathrm{T2}}^{100} \in[115,120)$ Acceptance</a> <a href=?table=Efficiency_SR1j_MT2_115_120>SR-1j $m_{\mathrm{T2}}^{100} \in[115,120)$ Efficiency</a> <a href=?table=Acceptance_SR1j_MT2_120_125>SR-1j $m_{\mathrm{T2}}^{100} \in[120,125)$ Acceptance</a> <a href=?table=Efficiency_SR1j_MT2_125_130>SR-1j $m_{\mathrm{T2}}^{100} \in[125,130)$ Efficiency</a> <a href=?table=Acceptance_SR1j_MT2_130_140>SR-1j $m_{\mathrm{T2}}^{100} \in[130,140)$ Acceptance</a> <a href=?table=Efficiency_SR1j_MT2_130_140>SR-1j $m_{\mathrm{T2}}^{100} \in[130,140)$ Efficiency</a> <a href=?table=Acceptance_SR1j_MT2_140_infty>SR-1j $m_{\mathrm{T2}}^{100} \in[140,\infty)$ Acceptance</a> <a href=?table=Efficiency_SR1j_MT2_140_infty>SR-1j $m_{\mathrm{T2}}^{100} \in[140,\infty)$ Efficiency</a> <li><b>Charginos:</b> <a href=?table=Acceptance_SR_DF_81_1_SF_77_1>SR$^{\text{-DF BDT-signal}\in(0.81,1]}_{\text{-SF BDT-signal}\in(0.77,1]}$ Acceptance</a> <a href=?table=Efficiency_SR_DF_81_1_SF_77_1>SR$^{\text{-DF BDT-signal}\in(0.81,1]}_{\text{-SF BDT-signal}\in(0.77,1]}$ Efficiency</a> <a href=?table=Acceptance_SR_DF_81_1>SR-DF BDT-signal$\in(0.81,1]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_81_1>SR-DF BDT-signal$\in(0.81,1]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_82_1>SR-DF BDT-signal$\in(0.82,1]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_82_1>SR-DF BDT-signal$\in(0.82,1]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_83_1>SR-DF BDT-signal$\in(0.83,1]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_83_1>SR-DF BDT-signal$\in(0.83,1]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_84_1>SR-DF BDT-signal$\in(0.84,1]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_84_1>SR-DF BDT-signal$\in(0.84,1]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_85_1>SR-DF BDT-signal$\in(0.85,1]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_85_1>SR-DF BDT-signal$\in(0.85,1]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_81_8125>SR-DF BDT-signal$\in(0.81,8125]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_81_8125>SR-DF BDT-signal$\in(0.81,8125]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_8125_815>SR-DF BDT-signal$\in(0.8125,815]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_8125_815>SR-DF BDT-signal$\in(0.8125,815]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_815_8175>SR-DF BDT-signal$\in(0.815,8175]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_815_8175>SR-DF BDT-signal$\in(0.815,8175]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_8175_82>SR-DF BDT-signal$\in(0.8175,82]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_8175_82>SR-DF BDT-signal$\in(0.8175,82]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_82_8225>SR-DF BDT-signal$\in(0.82,8225]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_82_8225>SR-DF BDT-signal$\in(0.82,8225]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_8225_825>SR-DF BDT-signal$\in(0.8225,825]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_8225_825>SR-DF BDT-signal$\in(0.8225,825]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_825_8275>SR-DF BDT-signal$\in(0.825,8275]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_825_8275>SR-DF BDT-signal$\in(0.825,8275]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_8275_83>SR-DF BDT-signal$\in(0.8275,83]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_8275_83>SR-DF BDT-signal$\in(0.8275,83]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_83_8325>SR-DF BDT-signal$\in(0.83,8325]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_83_8325>SR-DF BDT-signal$\in(0.83,8325]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_8325_835>SR-DF BDT-signal$\in(0.8325,835]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_8325_835>SR-DF BDT-signal$\in(0.8325,835]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_835_8375>SR-DF BDT-signal$\in(0.835,8375]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_835_8375>SR-DF BDT-signal$\in(0.835,8375]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_8375_84>SR-DF BDT-signal$\in(0.8375,84]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_8375_84>SR-DF BDT-signal$\in(0.8375,84]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_84_845>SR-DF BDT-signal$\in(0.85,845]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_84_845>SR-DF BDT-signal$\in(0.85,845]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_845_85>SR-DF BDT-signal$\in(0.845,85]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_845_85>SR-DF BDT-signal$\in(0.845,85]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_85_86>SR-DF BDT-signal$\in(0.85,86]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_85_86>SR-DF BDT-signal$\in(0.85,86]$ Efficiency</a> <a href=?table=Acceptance_SR_DF_86_1>SR-DF BDT-signal$\in(0.86,1]$ Acceptance</a> <a href=?table=Efficiency_SR_DF_86_1>SR-DF BDT-signal$\in(0.86,1]$ Efficiency</a> <a href=?table=Acceptance_SR_SF_77_1>SR-SF BDT-signal$\in(0.77,1]$ Acceptance</a> <a href=?table=Efficiency_SR_SF_77_1>SR-SF BDT-signal$\in(0.77,1]$ Efficiency</a> <a href=?table=Acceptance_SR_SF_78_1>SR-SF BDT-signal$\in(0.78,1]$ Acceptance</a> <a href=?table=Efficiency_SR_SF_78_1>SR-SF BDT-signal$\in(0.78,1]$ Efficiency</a> <a href=?table=Acceptance_SR_SF_79_1>SR-SF BDT-signal$\in(0.79,1]$ Acceptance</a> <a href=?table=Efficiency_SR_SF_79_1>SR-SF BDT-signal$\in(0.79,1]$ Efficiency</a> <a href=?table=Acceptance_SR_SF_80_1>SR-SF BDT-signal$\in(0.80,1]$ Acceptance</a> <a href=?table=Efficiency_SR_SF_80_1>SR-SF BDT-signal$\in(0.80,1]$ Efficiency</a> <a href=?table=Acceptance_SR_SF_77_775>SR-SF BDT-signal$\in(0.77,0.775]$ Acceptance</a> <a href=?table=Efficiency_SR_SF_77_775>SR-SF BDT-signal$\in(0.77,0.775]$ Efficiency</a> <a href=?table=Acceptance_SR_SF_775_78>SR-SF BDT-signal$\in(0.775,0.78]$ Acceptance</a> <a href=?table=Efficiency_SR_SF_775_78>SR-SF BDT-signal$\in(0.775,0.78]$ Efficiency</a> <a href=?table=Acceptance_SR_SF_78_785>SR-SF BDT-signal$\in(0.78,0.785]$ Acceptance</a> <a href=?table=Efficiency_SR_SF_78_785>SR-SF BDT-signal$\in(0.78,0.785]$ Efficiency</a> <a href=?table=Acceptance_SR_SF_785_79>SR-SF BDT-signal$\in(0.785,0.79]$ Acceptance</a> <a href=?table=Efficiency_SR_SF_785_79>SR-SF BDT-signal$\in(0.785,0.79]$ Efficiency</a> <a href=?table=Acceptance_SR_SF_79_795>SR-SF BDT-signal$\in(0.79,0.795]$ Acceptance</a> <a href=?table=Efficiency_SR_SF_79_795>SR-SF BDT-signal$\in(0.79,0.795]$ Efficiency</a> <a href=?table=Acceptance_SR_SF_795_80>SR-SF BDT-signal$\in(0.795,0.80]$ Acceptance</a> <a href=?table=Efficiency_SR_SF_795_80>SR-SF BDT-signal$\in(0.795,0.80]$ Efficiency</a> <a href=?table=Acceptance_SR_SF_80_81>SR-SF BDT-signal$\in(0.80,0.81]$ Acceptance</a> <a href=?table=Efficiency_SR_SF_80_81>SR-SF BDT-signal$\in(0.80,0.81]$ Efficiency</a> <a href=?table=Acceptance_SR_SF_81_1>SR-SF BDT-signal$\in(0.81,1]$ Acceptance</a> <a href=?table=Efficiency_SR_SF_81_1>SR-SF BDT-signal$\in(0.81,1]$ Efficiency</a></ul> <b>Truth Code snippets</b>, <b>SLHA</b> and <b>machine learning</b> files are available under "Resources" (purple button on the left)
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[100,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[100,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[110,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[110,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[120,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[120,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[130,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[130,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[100,105)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[100,105)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[105,110)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[105,110)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[110,115)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[110,115)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[115,120)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[115,120)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[120,125)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[120,125)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[125,130)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[125,130)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[130,140)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[130,140)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[140,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[140,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[100,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[100,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[110,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[110,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[120,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[120,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[130,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[130,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[100,105)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[100,105)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[105,110)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[105,110)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[110,115)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[110,115)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[115,120)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[115,120)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[120,125)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[120,125)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[125,130)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[125,130)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[130,140)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[130,140)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[140,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[140,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
Cutflow table for the slepton signal sample with $m(\tilde{\ell},\tilde{\chi}_1^0) = (100,70)$ GeV, in the SR-0J $m_{\mathrm{T2}}^{100} \in [100,\infty)$ region. The yields include the process cross section and are weighted to the 139 fb$^{-1}$ luminosity. 246000 events were generated for the sample.
Cutflow table for the slepton signal sample with $m(\tilde{\ell},\tilde{\chi}_1^0) = (100,70)$ GeV, in the SR-1J $m_{\mathrm{T2}}^{100} \in [100,\infty)$ region. The yields include the process cross section and are weighted to the 139 fb$^{-1}$ luminosity. 246000 events were generated for the sample.
Observed and expected exclusion limits on SUSY simplified models, with observed upper limits on signal cross-section (fb) overlaid, for slepton-pair production in the $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ plane. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ plane. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The red contour shows the exclusion limits obtained using both the SR-0J and SR-1J region, as presented in Figure 6. The blue and green contours correspond to the result obtained considering only SR-0J and SR-1J region respectively. All limits are computed at 95% CL. The observed limits obtained by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ plane. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The red contour shows the exclusion limits obtained using both the SR-0J and SR-1J region, as presented in Figure 6. The blue and green contours correspond to the result obtained considering only SR-0J and SR-1J region respectively. All limits are computed at 95% CL. The observed limits obtained by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ plane. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The red contour shows the exclusion limits obtained using both the SR-0J and SR-1J region, as presented in Figure 6. The blue and green contours correspond to the result obtained considering only SR-0J and SR-1J region respectively. All limits are computed at 95% CL. The observed limits obtained by the ATLAS experiment in previous searches are also shown.
Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ plane. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The red contour shows the exclusion limits obtained using both the SR-0J and SR-1J region, as presented in Figure 6. The blue and green contours correspond to the result obtained considering only SR-0J and SR-1J region respectively. All limits are computed at 95% CL. The observed limits obtained by the ATLAS experiment in previous searches are also shown.
The upper panel shows the observed number of events in each of the binned SRs defined in Table 3, together with the expected SM backgrounds obtained after applying the efficiency correction method to compute the number of expected FSB events. `Others' include the non-dominant background sources, e.g. $t \bar{t}$+$V$, Higgs boson and Drell--Yan events. The uncertainty band includes systematic and statistical errors from all sources. The distributions of two signal points with mass splittings $\Delta m(\tilde{\ell},\tilde{\chi}_1^0) = m(\tilde{\ell})-m(\tilde{\chi}_1^0) = 30$ GeV and $\Delta m(\tilde{\ell},\tilde{\chi}_1^0) = m(\tilde{\ell})-m(\tilde{\chi}_1^0) = 50$ GeV are overlaid. The lower panel shows the significance as defined in Ref. [115].
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR$^{\text{-DF BDT-signal}\in(0.81,1]}_{\text{-SF BDT-signal}\in(0.77,1]}$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR$^{\text{-DF BDT-signal}\in(0.81,1]}_{\text{-SF BDT-signal}\in(0.77,1]}$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.81,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.81,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.82,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.82,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.83,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.83,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.84,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.84,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.85,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.85,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.81,0.8125]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.81,0.8125]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8125,0.815]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8125,0.815]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.815,0.8175]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.815,0.8175]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8175,0.82]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8175,0.82]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.82,0.8225]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.82,0.8225]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8225,0.825]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8225,0.825]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.825,0.8275]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.825,0.8275]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8275,0.83]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8275,0.83]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.83,0.8325]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.83,0.8325]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8325,0.835]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8325,0.835]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.835,0.8375]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.835,0.8375]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8375,0.84]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8375,0.84]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.84,0.845]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.84,0.845]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.845,0.85]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.845,0.85]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.85,0.86]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.85,0.86]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.86,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.86,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.77,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.77,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.78,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.78,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.79,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.79,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.80,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.80,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.77,0.775]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.77,0.775]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.775,0.78]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.775,0.78]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.78,0.785]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.78,0.785]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.785,0.79]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.785,0.79]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.79,0.795]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.79,0.795]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.795,0.80]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.795,0.80]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.80,0.81]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.80,0.81]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.81,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.81,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.
Cutflow table for the chargino signal sample with $m\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0=(125,25)$ GeV, in the SR-SF BDT-signal$\in (0.77,1]$ and SR-DF BDT-signal$\in (0.81,1]$ regions. The yields include the process cross-section and are weighted to the 139 fb$^{-1}$ luminosity. 170000 events were generated for the sample.
Observed and expected exclusion limits on SUSY simplified models, with observed upper limits on signal cross-section (fb) overlaid, for chargino-pair production with $W$-boson-mediated decays in the $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ plane. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.
Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.
Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.
Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.
Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.
Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.
Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.
Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.
Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.
Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.
Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.
Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.
Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.
The upper panel shows the observed number of events in the SRs defined in Table 3, together with the expected SM backgrounds obtained after the background fit in the CRs. `Others' include the non-dominant background sources, e.g.$t \bar{t}$+$V$, Higgs boson and Drell--Yan events. The uncertainty band includes systematic and statistical errors from all sources. Distributions for three benchmark signal points are overlaid for comparison. The lower panel shows the significance as defined in Ref. [115].
The production of dark matter in association with Higgs bosons is predicted in several extensions of the Standard Model. An exploration of such scenarios is presented, considering final states with missing transverse momentum and $b$-tagged jets consistent with a Higgs boson. The analysis uses proton-proton collision data at a centre-of-mass energy of 13 TeV recorded by the ATLAS experiment at the LHC during Run 2, amounting to an integrated luminosity of 139 fb$^{-1}$. The analysis, when compared with previous searches, benefits from a larger dataset, but also has further improvements providing sensitivity to a wider spectrum of signal scenarios. These improvements include both an optimised event selection and advances in the object identification, such as the use of the likelihood-based significance of the missing transverse momentum and variable-radius track-jets. No significant deviation from Standard Model expectations is observed. Limits are set, at 95% confidence level, in two benchmark models with two Higgs doublets extended by either a heavy vector boson $Z'$ or a pseudoscalar singlet $a$ and which both provide a dark matter candidate $\chi$. In the case of the two-Higgs-doublet model with an additional vector boson $Z'$, the observed limits extend up to a $Z'$ mass of 3 TeV for a mass of 100 GeV for the dark matter candidate. The two-Higgs-doublet model with a dark matter particle mass of 10 GeV and an additional pseudoscalar $a$ is excluded for masses of the $a$ up to 520 GeV and 240 GeV for $\tan \beta = 1$ and $\tan \beta = 10$ respectively. Limits on the visible cross-sections are set and range from 0.05 fb to 3.26 fb, depending on the missing transverse momentum and $b$-quark jet multiplicity requirements.
<b>- - - - - - - - Overview of HEPData Record - - - - - - - -</b> <br><br> <b>Exclusion contours:</b> <ul> <li><a href="?table=LimitContour_ZP2HDM_obs">Observed 95% CL exclusion limit for the Z'-2HDM model</a> <li><a href="?table=LimitContour_ZP2HDM_exp">Expected 95% CL exclusion limit for the Z'-2HDM model</a> <li><a href="?table=LimitContour_ZP2HDM_exp_1s">Expected +- 1sigma 95% CL exclusion limit for the Z'-2HDM model</a> <li><a href="?table=LimitContour_ZP2HDM_exp_2s">Expected +- 2sigma 95% CL exclusion limit for the Z'-2HDM model</a> <li><a href="?table=LimitContour_2HDMa_tb1_sp0p35_obs">Observed 95% CL exclusion limit for ggF production in the 2HDM+a model</a> <li><a href="?table=LimitContour_2HDMa_tb1_sp0p35_exp">Expected 95% CL exclusion limit for ggF production in the 2HDM+a model</a> <li><a href="?table=LimitContour_2HDMa_tb1_sp0p35_exp_1s">Expected +- 1 sigma 95% CL exclusion limit for ggF production in the 2HDM+a model</a> <li><a href="?table=LimitContour_2HDMa_tb1_sp0p35_exp_2s">Expected +- 2 sigma 95% CL exclusion limit for ggF production in the 2HDM+a model</a> <li><a href="?table=LimitContour_2HDMa_tb10_sp0p35_obs">Observed 95% CL exclusion limit for bbA production in the 2HDM+a model</a> <li><a href="?table=LimitContour_2HDMa_tb10_sp0p35_exp">Expected 95% CL exclusion limit for bbA production in the 2HDM+a model</a> <li><a href="?table=LimitContour_2HDMa_tb10_sp0p35_exp_1s">Expected +- 1 sigma 95% CL exclusion limit for bbA production in the 2HDM+a model</a> <li><a href="?table=LimitContour_2HDMa_tb10_sp0p35_exp_2s">Expected +- 2 sigma 95% CL exclusion limit for bbA production in the 2HDM+a model</a> <li><a href="?table=LimitContour_ZP2HDM_2018CONF_obs">Observed 95% CL exclusion limit for the Z'-2HDM model with the benchmark used in arXiv:1707.01302.</a> <li><a href="?table=LimitContour_ZP2HDM_2018CONF_exp">Expected 95% CL exclusion limit for the Z'-2HDM model with the benchmark used in arXiv:1707.01302.</a> <li><a href="?table=LimitContour_ZP2HDM_2018CONF_exp_1s">Expected +- 1 sigma 95% CL exclusion limit for the Z'-2HDM model with the benchmark used in arXiv:1707.01302.</a> <li><a href="?table=LimitContour_ZP2HDM_2018CONF_exp_2s">Expected +- 2 sigma 95% CL exclusion limit for the Z'-2HDM model with the benchmark used in arXiv:1707.01302.</a> </ul> <b>Upper limits on cross-sections:</b> <ul> <li><a href="?table=Limits_ZP2HDM">95% CL upper limit on the cross-section for the Z'-2HDM model</a> <li><a href="?table=Limits_2HDMa_tb1_sp0p35">95% CL upper limit on the ggF cross-section in the 2HDM+a model</a> <li><a href="?table=Limits_2HDMa_tb10_sp0p35">95% CL upper limit on the bbA cross-section in the 2HDM+a model</a> <li><a href="?table=MIL">95% CL upper limit on the visible cross-section</a> </ul> <b>Theoretical cross-sections:</b> <ul> <li><a href="?table=CrossSections_ZP2HDM">Cross-section for the Z'-2HDM model</a> <li><a href="?table=CrossSections_2HDMa_tb1_sp0p35">Cross-section for ggF production in the 2HDM+a model</a> <li><a href="?table=CrossSections_2HDMa_tb10_sp0p35">Cross-section for bbA production in the 2HDM+a model</a> </ul> <b>Kinematic distributions:</b> <ul> <li><a href="?table=SR_post_plot_2b_150_200">Higgs candidate invariant mass in the region with 2 b-jets and missing energy between 150-200 GeV</a> <li><a href="?table=SR_post_plot_2b_200_350">Higgs candidate invariant mass in the region with 2 b-jets and missing energy between 200-350 GeV</a> <li><a href="?table=SR_post_plot_2b_350_500">Higgs candidate invariant mass in the region with 2 b-jets and missing energy between 350-500 GeV</a> <li><a href="?table=SR_post_plot_2b_500_750">Higgs candidate invariant mass in the region with 2 b-jets and missing energy between 500-750 GeV</a> <li><a href="?table=SR_post_plot_2b_750">Higgs candidate invariant mass in the region with 2 b-jets and missing energy higher than 750 GeV</a> <li><a href="?table=SR_post_plot_3b_150_200">Higgs candidate invariant mass in the region with at least 3 b-jets and missing energy between 150-200 GeV</a> <li><a href="?table=SR_post_plot_3b_200_350">Higgs candidate invariant mass in the region with at least 3 b-jets and missing energy between 200-350 GeV</a> <li><a href="?table=SR_post_plot_3b_350_500">Higgs candidate invariant mass in the region with at least 3 b-jets and missing energy between 350-500 GeV</a> <li><a href="?table=SR_post_plot_3b_500">Higgs candidate invariant mass in the region with at least 3 b-jets and missing energy higher than 500 GeV</a> <li><a href="?table=MET_post_plot_0L2b">Missing energy in events with 0 leptons and 2 b-jets</a> <li><a href="?table=MET_post_plot_0L3b">Missing energy in events with 0 leptons and at least 3 b-jets</a> <li><a href="?table=CR_post_plot_CR1">Yields in the different missing energy bins and muon-charge of the 1-lepton control region</a> <li><a href="?table=CR_post_plot_CR2">Yields in the different METlepInv bins of the 2-lepton control region</a> </ul> <b>Cut flows:</b> The tables contain three columns, corresponding to the Z'-2HDM and 2HDM+a model assuming 100% ggF or bbA production respectively. <ul> <li><a href="?table=Resolved_150_200_2b">Signal region with 2 b-jets and missing energy between 150-200 GeV</a> <li><a href="?table=Resolved_200_350_2b">Signal region with 2 b-jets and missing energy between 200-350 GeV</a> <li><a href="?table=Resolved_350_500_2b">Signal region with 2 b-jets and missing energy between 350-500 GeV</a> <li><a href="?table=Merged_500_750_2w0b">Signal region with 2 b-jets and missing energy between 500-750 GeV</a> <li><a href="?table=Merged_750_2w0b">Signal region with 2 b-jets and missing energy higher than 750 GeV</a> <li><a href="?table=Resolved_150_200_3pb">Signal region with at least 3 b-jets and missing energy between 150-200 GeV</a> <li><a href="?table=Resolved_200_350_3pb">Signal region with at least 3 b-jets and missing energy between 200-350 GeV</a> <li><a href="?table=Resolved_350_500_3pb">Signal region with at least 3 b-jets and missing energy between 350-500 GeV</a> <li><a href="?table=Merged_2w1pb">Signal region with at least 3 b-jets and missing energy higher than 500 GeV</a> </ul> <b>Acceptance and efficiencies:</b> <ul> <li><a href="?table=AcceptanceTimesEfficiency_a2HDM_bb_2_150_noHiggsWindowCut">2HDM+a model, bbA production, 2 b-jets, MET=150-200 GeV</a> <li><a href="?table=AcceptanceTimesEfficiency_a2HDM_bb_2_200_noHiggsWindowCut">2HDM+a model, bbA production, 2 b-jets, MET=200-350 GeV</a> <li><a href="?table=AcceptanceTimesEfficiency_a2HDM_bb_2_350_noHiggsWindowCut">2HDM+a model, bbA production, 2 b-jets, MET=350-500 GeV</a> <li><a href="?table=AcceptanceTimesEfficiency_a2HDM_bb_2_500_noHiggsWindowCut">2HDM+a model, bbA production, 2 b-jets, MET=500-750 GeV</a> <li><a href="?table=AcceptanceTimesEfficiency_a2HDM_bb_2_750ptv_noHiggsWindowCut">2HDM+a model, bbA production, 2 b-jets, MET higher than 750 GeV</a> <li><a href="?table=AcceptanceTimesEfficiency_a2HDM_bb_3_150_noHiggsWindowCut">2HDM+a model, bbA production, at least 3 b-jets, MET=150-200 GeV</a> <li><a href="?table=AcceptanceTimesEfficiency_a2HDM_bb_3_200_noHiggsWindowCut">2HDM+a model, bbA production, at least 3 b-jets, MET=200-350 GeV</a> <li><a href="?table=AcceptanceTimesEfficiency_a2HDM_bb_3_350_noHiggsWindowCut">2HDM+a model, bbA production, at least 3 b-jets, MET=350-500 GeV</a> <li><a href="?table=AcceptanceTimesEfficiency_a2HDM_bb_3_500ptv_noHiggsWindowCut">2HDM+a model, bbA production, at least 3 b-jets, MET higher than GeV</a> <li><a href="?table=AcceptanceTimesEfficiency_a2HDM_ggF_2_150_noHiggsWindowCut">2HDM+a model, ggF production, 2 b-jets, MET=150-200 GeV</a> <li><a href="?table=AcceptanceTimesEfficiency_a2HDM_ggF_2_200_noHiggsWindowCut">2HDM+a model, ggF production, 2 b-jets, MET=200-350 GeV</a> <li><a href="?table=AcceptanceTimesEfficiency_a2HDM_ggF_2_350_noHiggsWindowCut">2HDM+a model, ggF production, 2 b-jets, MET=350-500 GeV</a> <li><a href="?table=AcceptanceTimesEfficiency_a2HDM_ggF_2_500_noHiggsWindowCut">2HDM+a model, ggF production, 2 b-jets, MET=500-750 GeV</a> <li><a href="?table=AcceptanceTimesEfficiency_a2HDM_ggF_2_750ptv_noHiggsWindowCut">2HDM+a model, ggF production, 2 b-jets, MET higher than 750 GeV</a> <li><a href="?table=AcceptanceTimesEfficiency_a2HDM_ggF_3_150_noHiggsWindowCut">2HDM+a model, ggF production, at least 3 b-jets, MET=150-200 GeV</a> <li><a href="?table=AcceptanceTimesEfficiency_a2HDM_ggF_3_200_noHiggsWindowCut">2HDM+a model, ggF production, at least 3 b-jets, MET=200-350 GeV</a> <li><a href="?table=AcceptanceTimesEfficiency_a2HDM_ggF_3_350_noHiggsWindowCut">2HDM+a model, ggF production, at least 3 b-jets, MET=350-500 GeV</a> <li><a href="?table=AcceptanceTimesEfficiency_a2HDM_ggF_3_500ptv_noHiggsWindowCut">2HDM+a model, ggF production, at least 3 b-jets, MET higher than 500 GeV</a> <li><a href="?table=AcceptanceTimesEfficiency_zp2hdm_CMS_2_150_noHiggsWindowCut">Z'-2HDM model, 2 b-jets, MET=150-200 GeV</a> <li><a href="?table=AcceptanceTimesEfficiency_zp2hdm_CMS_2_200_noHiggsWindowCut">Z'-2HDM model, 2 b-jets, MET=200-350 GeV</a> <li><a href="?table=AcceptanceTimesEfficiency_zp2hdm_CMS_2_350_noHiggsWindowCut">Z'-2HDM model, 2 b-jets, MET=350-500 GeV</a> <li><a href="?table=AcceptanceTimesEfficiency_zp2hdm_CMS_2_500_noHiggsWindowCut">Z'-2HDM model, 2 b-jets, MET=500-750 GeV</a> <li><a href="?table=AcceptanceTimesEfficiency_zp2hdm_CMS_2_750ptv_noHiggsWindowCut">Z'-2HDM model, 2 b-jets, MET higher than 750 GeV</a> <li><a href="?table=AcceptanceTimesEfficiency_zp2hdm_CMS_3_150_noHiggsWindowCut">Z'-2HDM model, at least 3 b-jets, MET=150-200 GeV</a> <li><a href="?table=AcceptanceTimesEfficiency_zp2hdm_CMS_3_200_noHiggsWindowCut">Z'-2HDM model, at least 3 b-jets, MET=200-350 GeV</a> <li><a href="?table=AcceptanceTimesEfficiency_zp2hdm_CMS_3_350_noHiggsWindowCut">Z'-2HDM model, at least 3 b-jets, MET=350-500 GeV</a> <li><a href="?table=AcceptanceTimesEfficiency_zp2hdm_CMS_3_500ptv_noHiggsWindowCut">Z'-2HDM model, at least 3 b-jets, MET higher than 500 GeV</a> </ul>
Observed 95% CL exclusion limit for the Zprime-2HDM model.
Expected 95% CL exclusion limit for the Zprime-2HDM model.
Expected +- 1 sigma 95% CL exclusion limit for the Zprime-2HDM model.
Expected +- 2 sigma 95% CL exclusion limit for the Zprime-2HDM model.
Observed 95% CL exclusion limit for the 2HDM+a model ggF production.
Expected 95% CL exclusion limit for the 2HDM+a model ggF production.
Expected +- 1 sigma 95% CL exclusion limit for the 2HDM+a model ggF production.
Expected +- 2 sigma 95% CL exclusion limit for the 2HDM+a model ggF production.
Observed 95% CL exclusion limit for the 2HDM+a model bbA production.
Expected 95% CL exclusion limit for the 2HDM+a model bbA production.
Expected +- 1 sigma 95% CL exclusion limit for the 2HDM+a model bbA production.
Expected +- 2 sigma 95% CL exclusion limit for the 2HDM+a model bbA production.
Observed 95% CL exclusion limit for the Zprime-2HDM model with the benchmark used in arXiv:1707.01302.
Expected 95% CL exclusion limit for the Zprime-2HDM model with the benchmark used in arXiv:1707.01302.
Expected +- 1 sigma 95% CL exclusion limit for the Zprime-2HDM model with the benchmark used in arXiv:1707.01302.
Expected +- 2 sigma 95% CL exclusion limit for the Zprime-2HDM model with the benchmark used in arXiv:1707.01302.
Expected and observed upper limits at 95% CL on cross-section for Zprime-2HDM model.
Expected and observed upper limits at 95% CL on cross-section for ggF producton in the 2HDM+a model.
Expected and observed upper limits at 95% CL on cross-section for bbA producton in the 2HDM+a model.
Model-independent upper limits on the visible cross-section $σ_{vis, $h(\bar{b})+DM} ≡ σ_{h+DM} \times B(h \to b\bar{b}) \times \mathcal{A} \times \epsilon$ in the different signal regions.
Theory cross-section for Zprime-2HDM model.
Theory cross-section for bbA production in the 2HDM+a model.
Theory cross-section for ggF production in the 2HDM+a model.
Distribution of Higgs boson candidate mass in 2b region with MET=150-200 GeV.
Distribution of Higgs boson candidate mass in 2b region with MET=200-350 GeV.
Distribution of Higgs boson candidate mass in 2b region with MET=350-500 GeV.
Distribution of Higgs boson candidate mass in 2b region with MET=500-750 GeV.
Distribution of Higgs boson candidate mass in 2b region with MET > 750 GeV.
Distribution of Higgs boson candidate mass in 3b region with MET=150-200 GeV.
Distribution of Higgs boson candidate mass in 3b region with MET=200-350 GeV.
Distribution of Higgs boson candidate mass in 3b region with MET=350-500 GeV.
Distribution of Higgs boson candidate mass in 3b region with MET > 500 GeV.
Yields in 1-lepton control region.
Yields in 2-lepton control region.
MET distribution in 2b region of the 0-lepton channel.
MET distribution in 3b region of the 0-lepton channel.
Expected signal yields after certain selection cuts in 2b region with MET=150-200 GeV.
Expected signal yields after certain selection cuts in 2b region with MET=200-350 GeV.
Expected signal yields after certain selection cuts in 2b region with MET=350-500 GeV.
Expected signal yields after certain selection cuts in 2b region with MET=500-750 GeV.
Expected signal yields after certain selection cuts in 2b region with MET > 750 GeV.
Expected signal yields after certain selection cuts in 3b region with MET=150-200 GeV.
Expected signal yields after certain selection cuts in 3b region with MET=200-350 GeV.
Expected signal yields after certain selection cuts in 3b region with MET=350-500 GeV.
Expected signal yields after certain selection cuts in 3b region with MET > 500 GeV.
Acceptance times efficiency for bbA production in the 2HDM+a model - 2b region with MET=150-200 GeV.
Acceptance times efficiency for bbA production in the 2HDM+a model - 2b region with MET=200-350 GeV.
Acceptance times efficiency for bbA production in the 2HDM+a model - 2b region with MET=350-500 GeV.
Acceptance times efficiency for bbA production in the 2HDM+a model - 2b region with MET=500-750 GeV.
Acceptance times efficiency for bbA production in the 2HDM+a model - 2b region with MET > 750 GeV.
Acceptance times efficiency for bbA production in the 2HDM+a model - 3b region with MET=150-200 GeV.
Acceptance times efficiency for bbA production in the 2HDM+a model - 3b region with MET=200-350 GeV.
Acceptance times efficiency for bbA production in the 2HDM+a model - 3b region with MET=350-500 GeV.
Acceptance times efficiency for bbA production in the 2HDM+a model - 3b region with MET>500 GeV.
Acceptance times efficiency for ggF production in the 2HDM+a model - 2b region with MET=150-200 GeV.
Acceptance times efficiency for ggF production in the 2HDM+a model - 2b region with MET=200-350 GeV.
Acceptance times efficiency for ggF production in the 2HDM+a model - 2b region with MET=350-500 GeV.
Acceptance times efficiency for ggF production in the 2HDM+a model - 2b region with MET=500-750 GeV.
Acceptance times efficiency for ggF production in the 2HDM+a model - 2b region with MET > 750 GeV.
Acceptance times efficiency for ggF production in the 2HDM+a model - 3b region with MET=150-200 GeV.
Acceptance times efficiency for ggF production in the 2HDM+a model - 3b region with MET=200-350 GeV.
Acceptance times efficiency for ggF production in the 2HDM+a model - 3b region with MET=350-500 GeV.
Acceptance times efficiency for ggF production in the 2HDM+a model - 3b region with MET > 500 GeV.
Acceptance times efficiency for ggF production in the Zprime-2HDM model - 2b region with MET=150-200 GeV.
Acceptance times efficiency for ggF production in the Zprime-2HDM model - 2b region with MET=200-350 GeV.
Acceptance times efficiency for ggF production in the Zprime-2HDM model - 2b region with MET=350-500 GeV.
Acceptance times efficiency for ggF production in the Zprime-2HDM model - 2b region with MET=500-750 GeV.
Acceptance times efficiency for ggF production in the Zprime-2HDM model - 2b region with MET > 750 GeV.
Acceptance times efficiency for ggF production in the Zprime-2HDM model - 3b region with MET=150-200 GeV.
Acceptance times efficiency for ggF production in the Zprime-2HDM model - 3b region with MET=200-350 GeV.
Acceptance times efficiency for ggF production in the Zprime-2HDM model - 3b region with MET=350-500 GeV.
Acceptance times efficiency for ggF production in the Zprime-2HDM model - 3b region with MET > 500 GeV.
A search is presented for the pair production of higgsinos $\tilde{\chi}$ in gauge-mediated supersymmetry models, where the lightest neutralinos $\tilde{\chi}_1^0$ decay into a light gravitino $\tilde{G}$ either via a Higgs $h$ or $Z$ boson. The search is performed with the ATLAS detector at the Large Hadron Collider using 139 fb$^{-1}$ of proton-proton collisions at a centre-of-mass energy of $\sqrt{s}$ = 13 TeV. It targets final states in which a Higgs boson decays into a photon pair, while the other Higgs or $Z$ boson decays into a $b\bar{b}$ pair, with missing transverse momentum associated with the two gravitinos. Search regions dependent on the amount of missing transverse momentum are defined by the requirements that the diphoton mass should be consistent with the mass of the Higgs boson, and the $b\bar{b}$ mass with the mass of the Higgs or $Z$ boson. The main backgrounds are estimated with data-driven methods using the sidebands of the diphoton mass distribution. No excesses beyond Standard Model expectations are observed and higgsinos with masses up to 320 GeV are excluded, assuming a branching fraction of 100% for $\tilde{\chi}_1^0\rightarrow h\tilde{G}$. This analysis excludes higgsinos with masses of 130 GeV for branching fractions to $h\tilde{G}$ as low as 36%, thus providing complementarity to previous ATLAS searches in final states with multiple leptons or multiple $b$-jets, targeting different decays of the electroweak bosons.
<b>- - - - - - - - Overview of HEPData Record - - - - - - - -</b> <b>Histograms:</b><ul> <li><a href=?table=Distribution1>Figure 3a: $m_{\gamma\gamma}$ Distribution in VR1</a> <li><a href=?table=Distribution2>Figure 3b: $E_{\mathrm{T}}^{\mathrm{miss}}$ Distribution in VR1</a> <li><a href=?table=Distribution3>Figure 3c: $m_{\gamma\gamma}$ Distribution in VR2</a> <li><a href=?table=Distribution4>Figure 3d: $E_{\mathrm{T}}^{\mathrm{miss}}$ Distribution in VR2</a> <li><a href=?table=Distribution5>Figure 4a: N-1 $m_{\gamma\gamma}$ Distribution for SR1h</a> <li><a href=?table=Distribution6>Figure 4b: N-1 $m_{\gamma\gamma}$ Distribution for SR1Z</a> <li><a href=?table=Distribution7>Figure 4c: N-1 $m_{\gamma\gamma}$ Distribution for SR2</a> <li><a href=?table=Distribution8>Auxiliary Figure 1: Signal and Validation Region Yields</a> </ul> <b>Tables:</b><ul> <li><a href=?table=YieldsTable1>Table 3: Signal Region Yields & Model-independent Limits</a> <li><a href=?table=Cutflow1>Auxiliary Table 1: Benchmark Signal Cutflows</a> </ul> <b>Cross section limits:</b><ul> <li><a href=?table=X-sectionU.L.1>Figure 5: 1D Cross-section Limits</a> <li><a href=?table=X-sectionU.L.2>Auxiliary Figure 3: 2D Cross-section Limits</a> </ul> <b>2D CL limits:</b><ul> <li><a href=?table=Exclusioncontour1>Figure 6: Expected Limit on $\mathrm{BF}(\tilde{\chi}_1^0\rightarrow h\tilde{G})$</a> <li><a href=?table=Exclusioncontour2>Figure 6: $+1\sigma$ Variation for Expected Limit on $\mathrm{BF}(\tilde{\chi}_1^0\rightarrow h\tilde{G})$</a> <li><a href=?table=Exclusioncontour3>Figure 6: $-1\sigma$ Variation for Expected Limit on $\mathrm{BF}(\tilde{\chi}_1^0\rightarrow h\tilde{G})$</a> <li><a href=?table=Exclusioncontour4>Figure 6: Observed Limit on $\mathrm{BF}(\tilde{\chi}_1^0\rightarrow h\tilde{G})$</a> <li><a href=?table=Exclusioncontour5>Figure 6: $+1\sigma$ Variation for Observed Limit on $\mathrm{BF}(\tilde{\chi}_1^0\rightarrow h\tilde{G})$</a> <li><a href=?table=Exclusioncontour6>Figure 6: $-1\sigma$ Variation for Observed Limit on $\mathrm{BF}(\tilde{\chi}_1^0\rightarrow h\tilde{G})$</a> </ul> <b>2D Acceptance and Efficiency maps:</b><ul> <li><a href=?table=Acceptance1>Auxiliary Figure 4a: Acceptances SR1h</a> <li><a href=?table=Acceptance2>Auxiliary Figure 4b: Acceptances SR1Z</a> <li><a href=?table=Acceptance3>Auxiliary Figure 4c: Acceptances SR2</a> <li><a href=?table=Efficiency1>Auxiliary Figure 5a: Efficiencies SR1h</a> <li><a href=?table=Efficiency2>Auxiliary Figure 5b: Efficiencies SR1Z</a> <li><a href=?table=Efficiency3>Auxiliary Figure 5c: Efficiencies SR2</a> </ul>
Distribution of the diphoton invariant mass in validation region VR1. The solid histograms are stacked to show the SM expectations after the 2×2D background estimation technique is applied. Background and signal predictions are normalised to the luminosity. The background category "h (other)" includes events originating from VBF, Vh, ggF, thq, thW and bb̄h, all subdominant in this signature. Statistical and systematic uncertainties are indicated by the shaded area. The lower panel of each plot shows the ratio of the data to the SM prediction for the respective bin. The first and last bins include the underflows and overflows respectively.
Distribution of the missing transverse momentum in validation region VR1. The solid histograms are stacked to show the SM expectations after the 2×2D background estimation technique is applied. Background and signal predictions are normalised to the luminosity. The background category "h (other)" includes events originating from VBF, Vh, ggF, thq, thW and bb̄h, all subdominant in this signature. Statistical and systematic uncertainties are indicated by the shaded area. The lower panel of each plot shows the ratio of the data to the SM prediction for the respective bin. The first and last bins include the underflows and overflows respectively.
Distribution of the diphoton invariant mass in validation region VR2. The solid histograms are stacked to show the SM expectations after the 2×2D background estimation technique is applied. Background and signal predictions are normalised to the luminosity. The background category "h (other)" includes events originating from VBF, Vh, ggF, thq, thW and bb̄h, all subdominant in this signature. Statistical and systematic uncertainties are indicated by the shaded area. The lower panel of each plot shows the ratio of the data to the SM prediction for the respective bin. The first and last bins include the underflows and overflows respectively.
Distribution of the missing transverse momentum in validation region VR2. The solid histograms are stacked to show the SM expectations after the 2×2D background estimation technique is applied. Background and signal predictions are normalised to the luminosity. The background category "h (other)" includes events originating from VBF, Vh, ggF, thq, thW and bb̄h, all subdominant in this signature. Statistical and systematic uncertainties are indicated by the shaded area. The lower panel of each plot shows the ratio of the data to the SM prediction for the respective bin. The first and last bins include the underflows and overflows respectively.
Distribution of the diphoton invariant mass with all selections of the signal regions applied, except on m<sub>γγ</sub> itself, for signal region SR1h. The background estimation techniques described in the text are applied. The different backgrounds are stacked to add up to the total SM prediction in each bin. The predicted yields for signal benchmark models of varying χ̃<sup>0</sup><sub>1</sub> mass are also overlaid (not stacked) assuming B(χ̃<sup>0</sup><sub>1</sub> → hG̃ ) to equal 100%. Background and signal predictions are normalised to the luminosity. The background category "h (other)" includes events originating from VBF, Vh, ggF, thq, thW and bb̄h, all subdominant in this signature. The sizes of the statistical and systematic uncertainties are indicated by the shaded areas. The lower panels show the ratio of the data to the SM prediction. Arrows indicate the borders of the signal region (|m<sub>γγ</sub>-125 GeV|<5 GeV). The first and last bins include the underflows and overflows respectively.
Distribution of the diphoton invariant mass with all selections of the signal regions applied, except on m<sub>γγ</sub> itself, for signal region SR1Z. The background estimation techniques described in the text are applied. The different backgrounds are stacked to add up to the total SM prediction in each bin. The predicted yields for signal benchmark models of varying χ̃<sup>0</sup><sub>1</sub> mass are also overlaid (not stacked) assuming B(χ̃<sup>0</sup><sub>1</sub> → hG̃ ) to equal 50%. Background and signal predictions are normalised to the luminosity. The background category "h (other)" includes events originating from VBF, Vh, ggF, thq, thW and bb̄h, all subdominant in this signature. The sizes of the statistical and systematic uncertainties are indicated by the shaded areas. The lower panels show the ratio of the data to the SM prediction. Arrows indicate the borders of the signal region (|m<sub>γγ</sub>-125 GeV|<5 GeV). The first and last bins include the underflows and overflows respectively.
Distribution of the diphoton invariant mass with all selections of the signal regions applied, except on m<sub>γγ</sub> itself, for signal region SR2. The background estimation techniques described in the text are applied. The different backgrounds are stacked to add up to the total SM prediction in each bin. The predicted yields for signal benchmark models of varying χ̃<sup>0</sup><sub>1</sub> mass are also overlaid (not stacked) assuming B(χ̃<sup>0</sup><sub>1</sub> → hG̃ ) to equal 100%. Background and signal predictions are normalised to the luminosity. The background category "h (other)" includes events originating from VBF, Vh, ggF, thq, thW and bb̄h, all subdominant in this signature. The sizes of the statistical and systematic uncertainties are indicated by the shaded areas. The lower panels show the ratio of the data to the SM prediction. Arrows indicate the borders of the signal region (|m<sub>γγ</sub>-125 GeV|<5 GeV). The first and last bins include the underflows and overflows respectively.
Observed and expected limits on the pure higgsino cross-section at 95% CL assuming B(χ̃<sup>0</sup><sub>1</sub> → hG̃ )=100% for different χ̃<sup>0</sup><sub>1</sub> masses, obtained by a statistical combination of the three signal regions SR1h, SR1Z and SR2. The inner and outer bands indicate the 1σ and 2σ variation on the expected limit respectively.
Observed and expected 95% CL limits on the pure-higgsino branching fraction to B(χ̃<sup>0</sup><sub>1</sub> → hG̃ ) as a function of the higgsino mass m(χ̃<sup>0</sup><sub>1</sub>) assuming it decays via either χ̃<sup>0</sup><sub>1</sub>→ hG̃ or χ̃<sup>0</sup><sub>1</sub>→ ZG̃. Limits are obtained by performing a statistical combination of the three signal regions SR1h, SR1Z and SR2. The ± 1σ variation on the expected limit is shown. The dotted lines indicate the observed limit obtained by a variation of theoretical prediction for the neutralino production cross-section by ±1 σ. Values of B(χ̃<sup>0</sup><sub>1</sub> → hG̃ ) larger than the observed 95% CL limit are excluded, as indicated by the hatched area.
Observed and expected 95% CL limits on the pure-higgsino branching fraction to B(χ̃<sup>0</sup><sub>1</sub> → hG̃ ) as a function of the higgsino mass m(χ̃<sup>0</sup><sub>1</sub>) assuming it decays via either χ̃<sup>0</sup><sub>1</sub>→ hG̃ or χ̃<sup>0</sup><sub>1</sub>→ ZG̃. Limits are obtained by performing a statistical combination of the three signal regions SR1h, SR1Z and SR2. The ± 1σ variation on the expected limit is shown. The dotted lines indicate the observed limit obtained by a variation of theoretical prediction for the neutralino production cross-section by ±1 σ. Values of B(χ̃<sup>0</sup><sub>1</sub> → hG̃ ) larger than the observed 95% CL limit are excluded, as indicated by the hatched area.
Observed and expected 95% CL limits on the pure-higgsino branching fraction to B(χ̃<sup>0</sup><sub>1</sub> → hG̃ ) as a function of the higgsino mass m(χ̃<sup>0</sup><sub>1</sub>) assuming it decays via either χ̃<sup>0</sup><sub>1</sub>→ hG̃ or χ̃<sup>0</sup><sub>1</sub>→ ZG̃. Limits are obtained by performing a statistical combination of the three signal regions SR1h, SR1Z and SR2. The ± 1σ variation on the expected limit is shown. The dotted lines indicate the observed limit obtained by a variation of theoretical prediction for the neutralino production cross-section by ±1 σ. Values of B(χ̃<sup>0</sup><sub>1</sub> → hG̃ ) larger than the observed 95% CL limit are excluded, as indicated by the hatched area.
Observed and expected 95% CL limits on the pure-higgsino branching fraction to B(χ̃<sup>0</sup><sub>1</sub> → hG̃ ) as a function of the higgsino mass m(χ̃<sup>0</sup><sub>1</sub>) assuming it decays via either χ̃<sup>0</sup><sub>1</sub>→ hG̃ or χ̃<sup>0</sup><sub>1</sub>→ ZG̃. Limits are obtained by performing a statistical combination of the three signal regions SR1h, SR1Z and SR2. The ± 1σ variation on the expected limit is shown. The dotted lines indicate the observed limit obtained by a variation of theoretical prediction for the neutralino production cross-section by ±1 σ. Values of B(χ̃<sup>0</sup><sub>1</sub> → hG̃ ) larger than the observed 95% CL limit are excluded, as indicated by the hatched area.
Observed and expected 95% CL limits on the pure-higgsino branching fraction to B(χ̃<sup>0</sup><sub>1</sub> → hG̃ ) as a function of the higgsino mass m(χ̃<sup>0</sup><sub>1</sub>) assuming it decays via either χ̃<sup>0</sup><sub>1</sub>→ hG̃ or χ̃<sup>0</sup><sub>1</sub>→ ZG̃. Limits are obtained by performing a statistical combination of the three signal regions SR1h, SR1Z and SR2. The ± 1σ variation on the expected limit is shown. The dotted lines indicate the observed limit obtained by a variation of theoretical prediction for the neutralino production cross-section by ±1 σ. Values of B(χ̃<sup>0</sup><sub>1</sub> → hG̃ ) larger than the observed 95% CL limit are excluded, as indicated by the hatched area.
Observed and expected 95% CL limits on the pure-higgsino branching fraction to B(χ̃<sup>0</sup><sub>1</sub> → hG̃ ) as a function of the higgsino mass m(χ̃<sup>0</sup><sub>1</sub>) assuming it decays via either χ̃<sup>0</sup><sub>1</sub>→ hG̃ or χ̃<sup>0</sup><sub>1</sub>→ ZG̃. Limits are obtained by performing a statistical combination of the three signal regions SR1h, SR1Z and SR2. The ± 1σ variation on the expected limit is shown. The dotted lines indicate the observed limit obtained by a variation of theoretical prediction for the neutralino production cross-section by ±1 σ. Values of B(χ̃<sup>0</sup><sub>1</sub> → hG̃ ) larger than the observed 95% CL limit are excluded, as indicated by the hatched area.
Numbers of signal and background events in the signal regions. The respective background estimation techniques are applied. The background category "h (other)" includes events originating from VBF, Vh, ggF, thq, thW and bb̄h, all subdominant in this signature. The different backgrounds are stacked to add up to the total Standard Model prediction in each bin. The predicted yields for signal benchmark models of varying χ̃<sup>0</sup><sub>1</sub> mass are also plotted (not stacked), assuming B(χ̃<sup>0</sup><sub>1</sub> → hG̃ )=100% and a χ̃<sup>0</sup><sub>1</sub> mass of 130 or 200 GeV. The statistical and systematic uncertainties are indicated by the shaded areas in the top plot. The bottom panel shows the statistical significance <a href="https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2020-025/">[Ref]</a> of the difference between the SM prediction and the observed data in each region.
Observed 95% CL limits in pb on the pure higgsino cross-section, shown in the m(χ̃<sup>0</sup><sub>1</sub>)-B(χ̃<sup>0</sup><sub>1</sub> → hG̃ ) plane. Limits are obtained by a statistical combination of the three signal regions SR1h, SR1Z and SR2, assuming the neutralino to decay via either χ̃<sup>0</sup><sub>1</sub>→ hG̃ or χ̃<sup>0</sup><sub>1</sub>→ ZG̃.
Acceptances for all signal model points considered in the analysis, shown in the m(χ̃<sup>0</sup><sub>1</sub>)-B(χ̃<sup>0</sup><sub>1</sub> → hG̃ ) plane. Acceptances are provided separately for signal region SR1h, assuming the neutralino to decay via either χ̃<sup>0</sup><sub>1</sub>→ hG̃ or χ̃<sup>0</sup><sub>1</sub>→ ZG̃.
Acceptances for all signal model points considered in the analysis, shown in the m(χ̃<sup>0</sup><sub>1</sub>)-B(χ̃<sup>0</sup><sub>1</sub> → hG̃ ) plane. Acceptances are provided separately for signal region SR1Z, assuming the neutralino to decay via either χ̃<sup>0</sup><sub>1</sub>→ hG̃ or χ̃<sup>0</sup><sub>1</sub>→ ZG̃.
Acceptances for all signal model points considered in the analysis, shown in the m(χ̃<sup>0</sup><sub>1</sub>)-B(χ̃<sup>0</sup><sub>1</sub> → hG̃ ) plane. Acceptances are provided separately for signal region SR2, assuming the neutralino to decay via either χ̃<sup>0</sup><sub>1</sub>→ hG̃ or χ̃<sup>0</sup><sub>1</sub>→ ZG̃.
Efficiencies for all signal model points considered in the analysis, shown in the m(χ̃<sup>0</sup><sub>1</sub>)-B(χ̃<sup>0</sup><sub>1</sub> → hG̃ ) plane. Efficiencies are provided separately for signal region SR1h, assuming the neutralino to decay via either χ̃<sup>0</sup><sub>1</sub>→ hG̃ or χ̃<sup>0</sup><sub>1</sub>→ ZG̃.
Efficiencies for all signal model points considered in the analysis, shown in the m(χ̃<sup>0</sup><sub>1</sub>)-B(χ̃<sup>0</sup><sub>1</sub> → hG̃ ) plane. Efficiencies are provided separately for signal region SR1Z, assuming the neutralino to decay via either χ̃<sup>0</sup><sub>1</sub>→ hG̃ or χ̃<sup>0</sup><sub>1</sub>→ ZG̃.
Efficiencies for all signal model points considered in the analysis, shown in the m(χ̃<sup>0</sup><sub>1</sub>)-B(χ̃<sup>0</sup><sub>1</sub> → hG̃ ) plane. Efficiencies are provided separately for signal region SR2, assuming the neutralino to decay via either χ̃<sup>0</sup><sub>1</sub>→ hG̃ or χ̃<sup>0</sup><sub>1</sub>→ ZG̃.
Observed and expected numbers of events in the three signal regions. The background category "h (other)" includes events originating from VBF, Vh, ggF, thq, thW and bb̄h, all subdominant in this signature. The table also includes model-independent 95% CL upper limits on the visible number of BSM events (S<sup>95</sup><sub>obs</sub>), the number of BSM events given the expected number of background events (S<sup>95</sup><sub>exp</sub>) and the visible BSM cross-section (⟨ε σ⟩<sub>obs</sub><sup>95</sup>), all calculated from pseudo-experiments. The discovery p-value (p<sub>0</sub>) is also shown and its value is capped at 0.5 if the observed number of events is below the expected number of events.
Cutflows of two benchmark signal points assuming B(χ̃<sup>0</sup><sub>1</sub> → hG̃ )=100% for all three discovery signal regions. The initial selection includes the leptons veto. Only statistical uncertainties are included. Expected yields are normalised to a luminosity of 139 fb<sup>-1</sup>.
This paper presents a search for pair production of higgsinos, the supersymmetric partners of the Higgs bosons, in scenarios with gauge-mediated supersymmetry breaking. Each higgsino is assumed to decay into a Higgs boson and a nearly massless gravitino. The search targets events where each Higgs boson decays into $b\bar{b}$, leading to a reconstructed final state with at least three energetic $b$-jets and missing transverse momentum. Two complementary analysis channels are used, with each channel specifically targeting either low or high values of the higgsino mass. The low-mass (high-mass) channel exploits 126 (139) fb$^{-1}$ of $\sqrt{s}=13$ TeV data collected by the ATLAS detector during Run 2 of the Large Hadron Collider. No significant excess above the Standard Model prediction is found. At 95% confidence level, masses between 130 GeV and 940 GeV are excluded for higgsinos decaying exclusively into Higgs bosons and gravitinos. Exclusion limits as a function of the higgsino decay branching ratio to a Higgs boson are also reported.
Post-fit SR yields of the high-mass channel. The upper panel shows the observed number of events, as well the post-fit background predictions in each region. The bottom panel shows the ratio of the observed data and the total background prediction. The shaded areas correspond to the total statistical and systematic uncertainties obtained after the fit and described in Section 6.
Post-fit SR yields of the high-mass channel. The upper panel shows the observed number of events, as well the post-fit background predictions in each region. The bottom panel shows the ratio of the observed data and the total background prediction. The shaded areas correspond to the total statistical and systematic uncertainties obtained after the fit and described in Section 6.
Post-fit SR yields of the high-mass channel. The upper panel shows the observed number of events, as well the post-fit background predictions in each region. The bottom panel shows the ratio of the observed data and the total background prediction. The shaded areas correspond to the total statistical and systematic uncertainties obtained after the fit and described in Section 6.
Post-fit SR yields of the high-mass channel. The upper panel shows the observed number of events, as well the post-fit background predictions in each region. The bottom panel shows the ratio of the observed data and the total background prediction. The shaded areas correspond to the total statistical and systematic uncertainties obtained after the fit and described in Section 6.
Post-fit SR yields of the high-mass channel. The upper panel shows the observed number of events, as well the post-fit background predictions in each region. The bottom panel shows the ratio of the observed data and the total background prediction. The shaded areas correspond to the total statistical and systematic uncertainties obtained after the fit and described in Section 6.
Post-fit SR yields of the high-mass channel. The upper panel shows the observed number of events, as well the post-fit background predictions in each region. The bottom panel shows the ratio of the observed data and the total background prediction. The shaded areas correspond to the total statistical and systematic uncertainties obtained after the fit and described in Section 6.
Post-fit SR yields of the high-mass channel. The upper panel shows the observed number of events, as well the post-fit background predictions in each region. The bottom panel shows the ratio of the observed data and the total background prediction. The shaded areas correspond to the total statistical and systematic uncertainties obtained after the fit and described in Section 6.
Post-fit SR yields of the high-mass channel. The upper panel shows the observed number of events, as well the post-fit background predictions in each region. The bottom panel shows the ratio of the observed data and the total background prediction. The shaded areas correspond to the total statistical and systematic uncertainties obtained after the fit and described in Section 6.
Post-fit SR yields of the high-mass channel. The upper panel shows the observed number of events, as well the post-fit background predictions in each region. The bottom panel shows the ratio of the observed data and the total background prediction. The shaded areas correspond to the total statistical and systematic uncertainties obtained after the fit and described in Section 6.
Post-fit SR yields of the high-mass channel. The upper panel shows the observed number of events, as well the post-fit background predictions in each region. The bottom panel shows the ratio of the observed data and the total background prediction. The shaded areas correspond to the total statistical and systematic uncertainties obtained after the fit and described in Section 6.
Pre-fit data and background (reweighted $2b$) predictions for each $4b$ SR $E_\text{T}^\text{miss}$ and $m_\text{eff}$ bin of the low-mass channel for the 2016 data-taking period. The bottom panel shows the significance of any differences between the observed $4b$ data and the background prediction. The $1\sigma$ and $2\sigma$ bands are shown in green and yellow, respectively. All systematics are included except the background normalization, which is 2.3%.
Pre-fit data and background (reweighted $2b$) predictions for each $4b$ SR $E_\text{T}^\text{miss}$ and $m_\text{eff}$ bin of the low-mass channel for the 2017 data-taking period. The bottom panel shows the significance of any differences between the observed $4b$ data and the background prediction. The $1\sigma$ and $2\sigma$ bands are shown in green and yellow, respectively. All systematics are included except the background normalization, which is 3.7%.
Pre-fit data and background (reweighted $2b$) predictions for each $4b$ SR $E_\text{T}^\text{miss}$ and $m_\text{eff}$ bin of the low-mass channel for the 2018 data-taking period. The bottom panel shows the significance of any differences between the observed $4b$ data and the background prediction. The $1\sigma$ and $2\sigma$ bands are shown in green and yellow, respectively. All systematics are included except the background normalization, which is 1.8%.
Exclusion limits of the low-mass and high-mass channels. The low-mass channel is used for $m_{\tilde{H}}<250$ GeV while the high-mass channel is used for $m_{\tilde{H}}\ge250$ GeV. The plot shows the observed (solid) and expected (dashed) 95% CL upper limits on the cross section of higgsino pair production, assuming a higgsino decay branching ratio of $\mathcal{B}(\tilde{H}\rightarrow h + \tilde{G})=100\%$. The theory cross section and its uncertainty are shown by the solid red line and red shading. Results from a previous ATLAS search using 24.3-36.1 fb$^{-1}$ [13] are shown by the solid (observed) and dashed (expected) blue lines. The bottom panel shows the ratio of the limits to the theory cross section. The phase space above the lines is excluded.
Exclusion limits of the low-mass and high-mass channels. The low-mass channel is used for $m_{\tilde{H}}<250$ GeV while the high-mass channel is used for $m_{\tilde{H}}\ge250$ GeV. The plot shows the observed (solid) and expected (dashed) 95% CL upper limits on the cross section of higgsino pair production, assuming a higgsino decay branching ratio of $\mathcal{B}(\tilde{H}\rightarrow h + \tilde{G})=100\%$. The theory cross section and its uncertainty are shown by the solid red line and red shading. Results from a previous ATLAS search using 24.3-36.1 fb$^{-1}$ [13] are shown by the solid (observed) and dashed (expected) blue lines. The bottom panel shows the ratio of the limits to the theory cross section. The phase space above the lines is excluded.
Exclusion limits of the low-mass and high-mass channels. The low-mass channel is used for $m_{\tilde{H}}<250$ GeV while the high-mass channel is used for $m_{\tilde{H}}\ge250$ GeV. The plot shows the observed (solid) and expected (dashed) 95% CL upper limits on the cross section of higgsino pair production, assuming a higgsino decay branching ratio of $\mathcal{B}(\tilde{H}\rightarrow h + \tilde{G})=100\%$. The theory cross section and its uncertainty are shown by the solid red line and red shading. Results from a previous ATLAS search using 24.3-36.1 fb$^{-1}$ [13] are shown by the solid (observed) and dashed (expected) blue lines. The bottom panel shows the ratio of the limits to the theory cross section. The phase space above the lines is excluded.
Exclusion limits of the low-mass and high-mass channels. The low-mass channel is used for $m_{\tilde{H}}<250$ GeV while the high-mass channel is used for $m_{\tilde{H}}\ge250$ GeV. The plot shows the observed (solid) and expected (dashed) 95% CL upper limits on the cross section of higgsino pair production, assuming a higgsino decay branching ratio of $\mathcal{B}(\tilde{H}\rightarrow h + \tilde{G})=100\%$. The theory cross section and its uncertainty are shown by the solid red line and red shading. Results from a previous ATLAS search using 24.3-36.1 fb$^{-1}$ [13] are shown by the solid (observed) and dashed (expected) blue lines. The bottom panel shows the ratio of the limits to the theory cross section. The phase space above the lines is excluded.
Exclusion limits of the low-mass and high-mass channels. The low-mass channel is used for $m_{\tilde{H}}<250$ GeV while the high-mass channel is used for $m_{\tilde{H}}\ge250$ GeV. The plot shows the observed (solid) and expected (dashed) 95% CL upper limits on the cross section of higgsino pair production, assuming a higgsino decay branching ratio of $\mathcal{B}(\tilde{H}\rightarrow h + \tilde{G})=100\%$. The theory cross section and its uncertainty are shown by the solid red line and red shading. Results from a previous ATLAS search using 24.3-36.1 fb$^{-1}$ [13] are shown by the solid (observed) and dashed (expected) blue lines. The bottom panel shows the ratio of the limits to the theory cross section. The phase space above the lines is excluded.
Exclusion limits of the low-mass and high-mass channels. The low-mass channel is used for $m_{\tilde{H}}<250$ GeV while the high-mass channel is used for $m_{\tilde{H}}\ge250$ GeV. The plot shows the observed (solid) and expected (dashed) 95% CL upper limits on the cross section of higgsino pair production, assuming a higgsino decay branching ratio of $\mathcal{B}(\tilde{H}\rightarrow h + \tilde{G})=100\%$. The theory cross section and its uncertainty are shown by the solid red line and red shading. Results from a previous ATLAS search using 24.3-36.1 fb$^{-1}$ [13] are shown by the solid (observed) and dashed (expected) blue lines. The bottom panel shows the ratio of the limits to the theory cross section. The phase space above the lines is excluded.
Exclusion limits of the low-mass and high-mass channels. The low-mass channel is used for $m_{\tilde{H}}<250$ GeV while the high-mass channel is used for $m_{\tilde{H}}\ge250$ GeV. The plot shows the observed (solid) and expected (dashed) 95% CL upper limits on the cross section of higgsino pair production, assuming a higgsino decay branching ratio of $\mathcal{B}(\tilde{H}\rightarrow h + \tilde{G})=100\%$. The theory cross section and its uncertainty are shown by the solid red line and red shading. Results from a previous ATLAS search using 24.3-36.1 fb$^{-1}$ [13] are shown by the solid (observed) and dashed (expected) blue lines. The bottom panel shows the ratio of the limits to the theory cross section. The phase space above the lines is excluded.
Exclusion limits of the low-mass and high-mass channels. The low-mass channel is used for $m_{\tilde{H}}<250$ GeV while the high-mass channel is used for $m_{\tilde{H}}\ge250$ GeV. The plot shows the observed (solid) and expected (dashed) 95% CL upper limits on the cross section of higgsino pair production, assuming a higgsino decay branching ratio of $\mathcal{B}(\tilde{H}\rightarrow h + \tilde{G})=100\%$. The theory cross section and its uncertainty are shown by the solid red line and red shading. Results from a previous ATLAS search using 24.3-36.1 fb$^{-1}$ [13] are shown by the solid (observed) and dashed (expected) blue lines. The bottom panel shows the ratio of the limits to the theory cross section. The phase space above the lines is excluded.
Exclusion limits of the low-mass and high-mass channels. The low-mass channel is used for $m_{\tilde{H}}<250$ GeV while the high-mass channel is used for $m_{\tilde{H}}\ge250$ GeV. The plot shows the observed (solid) and expected (dashed) 95% CL upper limits on the cross section of higgsino pair production, assuming a higgsino decay branching ratio of $\mathcal{B}(\tilde{H}\rightarrow h + \tilde{G})=100\%$. The theory cross section and its uncertainty are shown by the solid red line and red shading. Results from a previous ATLAS search using 24.3-36.1 fb$^{-1}$ [13] are shown by the solid (observed) and dashed (expected) blue lines. The bottom panel shows the ratio of the limits to the theory cross section. The phase space above the lines is excluded.
Exclusion limits of the low-mass and high-mass channels. The low-mass channel is used for $m_{\tilde{H}}<250$ GeV while the high-mass channel is used for $m_{\tilde{H}}\ge250$ GeV. The plot shows the observed (solid) and expected (dashed) 95% CL upper limits on the cross section of higgsino pair production, assuming a higgsino decay branching ratio of $\mathcal{B}(\tilde{H}\rightarrow h + \tilde{G})=100\%$. The theory cross section and its uncertainty are shown by the solid red line and red shading. Results from a previous ATLAS search using 24.3-36.1 fb$^{-1}$ [13] are shown by the solid (observed) and dashed (expected) blue lines. The bottom panel shows the ratio of the limits to the theory cross section. The phase space above the lines is excluded.
Exclusion limits of the low-mass and high-mass channels. The low-mass channel is used for $m_{\tilde{H}}<250$ GeV while the high-mass channel is used for $m_{\tilde{H}}\ge250$ GeV. The plot shows the 95% CL observed (solid) and expected (dashed) upper limits on $\mathcal{B}(\tilde{H}\rightarrow h + \tilde{G})$, assuming the theory cross section for higgsino pair production. The higgsinos are assumed to decay as $\tilde{H}\rightarrow h + \tilde{G}$ or $\tilde{H}\rightarrow Z + \tilde{G}$. The phase space above the lines is excluded.
Exclusion limits of the low-mass and high-mass channels. The low-mass channel is used for $m_{\tilde{H}}<250$ GeV while the high-mass channel is used for $m_{\tilde{H}}\ge250$ GeV. The plot shows the 95% CL observed (solid) and expected (dashed) upper limits on $\mathcal{B}(\tilde{H}\rightarrow h + \tilde{G})$, assuming the theory cross section for higgsino pair production. The higgsinos are assumed to decay as $\tilde{H}\rightarrow h + \tilde{G}$ or $\tilde{H}\rightarrow Z + \tilde{G}$. The phase space above the lines is excluded.
Exclusion limits of the low-mass and high-mass channels. The low-mass channel is used for $m_{\tilde{H}}<250$ GeV while the high-mass channel is used for $m_{\tilde{H}}\ge250$ GeV. The plot shows the 95% CL observed (solid) and expected (dashed) upper limits on $\mathcal{B}(\tilde{H}\rightarrow h + \tilde{G})$, assuming the theory cross section for higgsino pair production. The higgsinos are assumed to decay as $\tilde{H}\rightarrow h + \tilde{G}$ or $\tilde{H}\rightarrow Z + \tilde{G}$. The phase space above the lines is excluded.
Exclusion limits of the low-mass and high-mass channels. The low-mass channel is used for $m_{\tilde{H}}<250$ GeV while the high-mass channel is used for $m_{\tilde{H}}\ge250$ GeV. The plot shows the 95% CL observed (solid) and expected (dashed) upper limits on $\mathcal{B}(\tilde{H}\rightarrow h + \tilde{G})$, assuming the theory cross section for higgsino pair production. The higgsinos are assumed to decay as $\tilde{H}\rightarrow h + \tilde{G}$ or $\tilde{H}\rightarrow Z + \tilde{G}$. The phase space above the lines is excluded.
Exclusion limits of the low-mass and high-mass channels. The low-mass channel is used for $m_{\tilde{H}}<250$ GeV while the high-mass channel is used for $m_{\tilde{H}}\ge250$ GeV. The plot shows the 95% CL observed (solid) and expected (dashed) upper limits on $\mathcal{B}(\tilde{H}\rightarrow h + \tilde{G})$, assuming the theory cross section for higgsino pair production. The higgsinos are assumed to decay as $\tilde{H}\rightarrow h + \tilde{G}$ or $\tilde{H}\rightarrow Z + \tilde{G}$. The phase space above the lines is excluded.
Exclusion limits of the low-mass channel. The plot shows the observed (solid) and expected (dashed) 95% CL upper limits on the cross section of higgsino pair production, assuming a higgsino decay branching ratio of $\mathcal{B}(\tilde{H}\rightarrow h + \tilde{G})=100\%$. The theory cross section and its uncertainty are shown by the solid red line and red shading. The bottom panel shows the ratio of the limits to the theory cross section. The phase space above the lines is excluded.
Exclusion limits of the low-mass channel. The plot shows the observed (solid) and expected (dashed) 95% CL upper limits on the cross section of higgsino pair production, assuming a higgsino decay branching ratio of $\mathcal{B}(\tilde{H}\rightarrow h + \tilde{G})=100\%$. The theory cross section and its uncertainty are shown by the solid red line and red shading. The bottom panel shows the ratio of the limits to the theory cross section. The phase space above the lines is excluded.
Exclusion limits of the high-mass channel. The plot shows the observed (solid) and expected (dashed) 95% CL upper limits on the cross section of higgsino pair production, assuming a higgsino decay branching ratio of $\mathcal{B}(\tilde{H}\rightarrow h + \tilde{G})=100\%$. The theory cross section and its uncertainty are shown by the solid red line and red shading. The bottom panel shows the ratio of the limits to the theory cross section. The phase space above the lines is excluded.
Exclusion limits of the high-mass channel. The plot shows the observed (solid) and expected (dashed) 95% CL upper limits on the cross section of higgsino pair production, assuming a higgsino decay branching ratio of $\mathcal{B}(\tilde{H}\rightarrow h + \tilde{G})=100\%$. The theory cross section and its uncertainty are shown by the solid red line and red shading. The bottom panel shows the ratio of the limits to the theory cross section. The phase space above the lines is excluded.
Results of the background-only fit in the low-mass channel discovery region SR_LM_150. Both pre-fit and post-fit values are shown.
Results of the background-only fit in the low-mass channel discovery region SR_LM_300. Both pre-fit and post-fit values are shown.
The experimental efficiency of the low-mass channel for the exclusion and discovery signal regions as a function of higgsino mass. The experimental efficiency is defined as the number of events passing the detector-level event selections divided by the number of events passing the event selections for a perfect detector. The denominator is obtained by implementing particle-level event selections that emulate the detector-level selections. This treats the lack of availability of $b$-jet triggers as an inefficiency.
The particle-level acceptance for the low-mass exclusion and discovery signal regions, shown as a function of higgsino mass. The acceptance is defined as the fraction of signal events passing the particle-level event selection that emulates the detector-level selection. The acceptance calculation considers only those signal events where both higgsinos decay to Higgs bosons.
The experimental efficiency of the high-mass channel discovery regions as a function of higgsino mass. For each higgsino mass, the efficiency is shown for the SR-1 region corresponding to the mass. For masses above 1100 GeV, SR-1-1100 is used. The experimental efficiency is defined as the number of events passing the detector-level event selections divided by the number of events passing the event selections for a perfect detector. The denominator is obtained by implementing particle-level event selections that emulate the detector-level selections. The efficiency calculation considers only those signal events where both higgsinos decay to Higgs bosons.
The particle-level acceptance for the high-mass signal regions, shown as a function of higgsino mass. For each higgsino mass, the acceptance is shown for the SR-1 region corresponding to the mass. For masses above 1100 GeV, SR-1-1100 is used. The acceptance is defined as the fraction of signal events passing the particle-level event selection that emulates the detector-level selection. The acceptance calculation considers only those signal events where both higgsinos decay to Higgs bosons.
Cutflow for the low-mass channel for a representative 130 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. The $b$-jet cut requires 4 or more $b$-jets with $p_\text{T}>40$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$, with the availability of $b$-jet triggers lowering the luminosity to 126 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the low-mass channel for a representative 150 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. The $b$-jet cut requires 4 or more $b$-jets with $p_\text{T}>40$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$, with the availability of $b$-jet triggers lowering the luminosity to 126 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the low-mass channel for a representative 200 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. The $b$-jet cut requires 4 or more $b$-jets with $p_\text{T}>40$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$, with the availability of $b$-jet triggers lowering the luminosity to 126 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the low-mass channel for a representative 250 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. The $b$-jet cut requires 4 or more $b$-jets with $p_\text{T}>40$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$, with the availability of $b$-jet triggers lowering the luminosity to 126 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the low-mass channel for a representative 300 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. The $b$-jet cut requires 4 or more $b$-jets with $p_\text{T}>40$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$, with the availability of $b$-jet triggers lowering the luminosity to 126 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the low-mass channel for a representative 400 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. The $b$-jet cut requires 4 or more $b$-jets with $p_\text{T}>40$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$, with the availability of $b$-jet triggers lowering the luminosity to 126 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the low-mass channel for a representative 500 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. The $b$-jet cut requires 4 or more $b$-jets with $p_\text{T}>40$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$, with the availability of $b$-jet triggers lowering the luminosity to 126 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the low-mass channel for a representative 600 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. The $b$-jet cut requires 4 or more $b$-jets with $p_\text{T}>40$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$, with the availability of $b$-jet triggers lowering the luminosity to 126 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the low-mass channel for a representative 700 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. The $b$-jet cut requires 4 or more $b$-jets with $p_\text{T}>40$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$, with the availability of $b$-jet triggers lowering the luminosity to 126 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the low-mass channel for a representative 800 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. The $b$-jet cut requires 4 or more $b$-jets with $p_\text{T}>40$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$, with the availability of $b$-jet triggers lowering the luminosity to 126 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the low-mass channel for a representative 900 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. The $b$-jet cut requires 4 or more $b$-jets with $p_\text{T}>40$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$, with the availability of $b$-jet triggers lowering the luminosity to 126 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the low-mass channel for a representative 1000 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. The $b$-jet cut requires 4 or more $b$-jets with $p_\text{T}>40$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$, with the availability of $b$-jet triggers lowering the luminosity to 126 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the low-mass channel for a representative 1100 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. The $b$-jet cut requires 4 or more $b$-jets with $p_\text{T}>40$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$, with the availability of $b$-jet triggers lowering the luminosity to 126 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the high-mass channel for a representative 200 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the high-mass channel for a representative 250 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the high-mass channel for a representative 300 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the high-mass channel for a representative 400 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the high-mass channel for a representative 500 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the high-mass channel for a representative 600 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the high-mass channel for a representative 700 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the high-mass channel for a representative 800 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the high-mass channel for a representative 900 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the high-mass channel for a representative 1000 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the high-mass channel for a representative 1100 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the high-mass channel for a representative 1200 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the high-mass channel for a representative 1300 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the high-mass channel for a representative 1400 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
Cutflow for the high-mass channel for a representative 1500 GeV signal. The preselection requires 4 or more jets with $p_\text{T}>25$ GeV and 2 or more $b$-jets with $p_\text{T}>25$ GeV. As the samples are generated with $\mathcal{B}(\tilde{H}\rightarrow h\tilde{G})$=50%, $\mathcal{B}(\tilde{H}\rightarrow Z\tilde{G})$=50% to allow for both decays to be studied, the $hh$ events selection is used to select the events where each of the higgsinos decays to a Higgs boson. Expected yields are normalized to a luminosity of 139 fb$^{-1}$. All selections are cumulative, with the exception of the SR cuts, which are each applied separately.
A search for a new massive charged gauge boson, $W'$, is performed with the ATLAS detector at the LHC. The dataset used in this analysis was collected from proton-proton collisions at a centre-of-mass energy of $\sqrt{s} =13$ TeV, and corresponds to an integrated luminosity of 139 fb$^{-1}$. The reconstructed $tb$ invariant mass is used to search for a $W'$ boson decaying into a top quark and a bottom quark. The result is interpreted in terms of a $W'$ boson with purely right-handed or left-handed chirality in a mass range of 0.5-6 TeV. Different values for the coupling of the $W'$ boson to the top and bottom quarks are considered, taking into account interference with single-top-quark production in the $s$-channel. No significant deviation from the background prediction is observed. The results are expressed as upper limits on the $W' \rightarrow tb$ production cross-section times branching ratio as a function of the $W'$-boson mass and in the plane of the coupling vs the $W'$-boson mass.
Distribution (events/100 GeV) of the reconstructed $m_{tb}$ for data and backgrounds in the 0-lepton channel's signal region 1 after the background-only fit to data. The systematics uncertainty is shown for the post-fit background sum, including the background statistical uncertainty. The individual background components are obtained after the fit, too. There are also the pre-fit background sum and the expected signal distribution. The distribution of the $W^{\prime}$ boson signal for a mass of 3 TeV is normalised to the predicted cross-section. The last bin in each distribution includes overflow.
Distribution (events/100 GeV) of the reconstructed $m_{tb}$ for data and backgrounds in the 0-lepton channel's signal region 2 after the background-only fit to data. The systematics uncertainty is shown for the post-fit background sum, including the background statistical uncertainty. The individual background components are obtained after the fit, too. There are also the pre-fit background sum and the expected signal distribution. The distribution of the $W^{\prime}$ boson signal for a mass of 3 TeV is normalised to the predicted cross-section. The last bin in each distribution includes overflow.
Distribution (events/100 GeV) of the reconstructed $m_{tb}$ for data and backgrounds in the 0-lepton channel's the signal region 3 after the background-only fit to data. The systematics uncertainty is shown for the post-fit background sum, including the background statistical uncertainty. The individual background components are obtained after the fit, too. There are also the pre-fit background sum and the expected signal distribution. The distribution of the $W^{\prime}$ boson signal for a mass of 3 TeV is normalised to the predicted cross-section. The last bin in each distribution includes overflow.
Distribution (events/100 GeV) of the reconstructed $m_{tb}$ for data and backgrounds in the 0-lepton channel's validation region before the fit to data. The systematics uncertainty is shown for the pre-fit background sum, including the background statistical uncertainty. The individual background components are obtained before the fit, too. There is also the expected signal distribution. The distribution of the $W^{\prime}$ boson signal for a mass of 3 TeV is normalised to the predicted cross-section. The last bin in each distribution includes overflow.
Reconstructed $m_{tb}$ distributions (events/50 GeV) for data and backgrounds in the 1-lepton channel's 2j1b signal region after the background-only fit to data. The systematics uncertainty is shown for the post-fit background sum, including the background statistical uncertainty. The individual background components are obtained after the fit, too. There are also the pre-fit background sum and the expected signal distribution. The distribution of the $W^{\prime}$ boson signal for a mass of 3 TeV is normalised to the predicted cross-section. The last bin in each distribution includes overflow.
Reconstructed $m_{tb}$ distributions (events/50 GeV) for data and backgrounds in the 1-lepton channel's 3j1b signal region after the background-only fit to data. The systematics uncertainty is shown for the post-fit background sum, including the background statistical uncertainty. The individual background components are obtained after the fit, too. There are also the pre-fit background sum and the expected signal distribution. The distribution of the $W^{\prime}$ boson signal for a mass of 3 TeV is normalised to the predicted cross-section. The last bin in each distribution includes overflow.
Reconstructed $m_{tb}$ distributions (events/50 GeV) for data and backgrounds in the 1-lepton channel's 2j2b signal region after the background-only fit to data. The systematics uncertainty is shown for the post-fit background sum, including the background statistical uncertainty. The individual background components are obtained after the fit, too. There are also the pre-fit background sum and the expected signal distribution. The distribution of the $W^{\prime}$ boson signal for a mass of 3 TeV is normalised to the predicted cross-section. The last bin in each distribution includes overflow.
Reconstructed $m_{tb}$ distributions (events/50 GeV) for data and backgrounds in the 1-lepton channel's 3j2b signal region after the background-only fit to data. The systematics uncertainty is shown for the post-fit background sum, including the background statistical uncertainty. The individual background components are obtained after the fit, too. There are also the pre-fit background sum and the expected signal distribution. The distribution of the $W^{\prime}$ boson signal for a mass of 3 TeV is normalised to the predicted cross-section. The last bin in each distribution includes overflow.
Reconstructed $m_{tb}$ distributions (events/50 GeV) for data and backgrounds in the 1-lepton channel's 2j1b control region after the background-only fit to data. The systematics uncertainty is shown for the post-fit background sum, including the background statistical uncertainty. The individual background components are obtained after the fit, too. There are also the pre-fit background sum and the expected signal distribution. The distribution of the $W^{\prime}$ boson signal for a mass of 3 TeV is normalised to the predicted cross-section. The last bin in each distribution includes overflow.
Reconstructed $m_{tb}$ distributions (events/50 GeV) for data and backgrounds in the 1-lepton channel's 3j1b control region after the background-only fit to data. The systematics uncertainty is shown for the post-fit background sum, including the background statistical uncertainty. The individual background components are obtained after the fit, too. There are also the pre-fit background sum and the expected signal distribution. The distribution of the $W^{\prime}$ boson signal for a mass of 3 TeV is normalised to the predicted cross-section. The last bin in each distribution includes overflow.
Reconstructed $m_{tb}$ distributions (events/50 GeV) for data and backgrounds in the 1-lepton channel's 2j1b validation region after the background-only fit to data. The systematics uncertainty is shown for the post-fit background sum, including the background statistical uncertainty. The individual background components are obtained after the fit, too. There are also the pre-fit background sum and the expected signal distribution. The distribution of the $W^{\prime}$ boson signal for a mass of 3 TeV is normalised to the predicted cross-section. The last bin in each distribution includes overflow.
Reconstructed $m_{tb}$ distributions (events/50 GeV) for data and backgrounds in the 1-lepton channel's 3j1b validation region after the background-only fit to data. The systematics uncertainty is shown for the post-fit background sum, including the background statistical uncertainty. The individual background components are obtained after the fit, too. There are also the pre-fit background sum and the expected signal distribution. The distribution of the $W^{\prime}$ boson signal for a mass of 3 TeV is normalised to the predicted cross-section. The last bin in each distribution includes overflow.
Observed and expected 95% CL limits on the cross-section times branching ratio for the production of a $W^{\prime}$ boson with decay to tb and left-handed couplings as a function of the mass of the $W^{\prime}$ boson and a coupling value of $g^{\prime}/g$=0.5. The observed and expected limits are derived using a linear interpolation between simulated signal mass hypotheses. The uncertainty on the theory prediction includes components from factorisation and renormalisation scales, PDFs, the strong coupling constant, and the top-quark mass.
Observed and expected 95% CL limits on the cross-section times branching ratio for the production of a $W^{\prime}$ boson with decay to tb and left-handed couplings as a function of the mass of the $W^{\prime}$ boson and a coupling value of $g^{\prime}/g$=1.0. The observed and expected limits are derived using a linear interpolation between simulated signal mass hypotheses. The uncertainty on the theory prediction includes components from factorisation and renormalisation scales, PDFs, the strong coupling constant, and the top-quark mass.
Observed and expected 95% CL limits on the cross-section times branching ratio for the production of a $W^{\prime}$ boson with decay to tb and left-handed couplings as a function of the mass of the $W^{\prime}$ boson and a coupling value of $g^{\prime}/g$=2.0. The observed and expected limits are derived using a linear interpolation between simulated signal mass hypotheses. The uncertainty on the theory prediction includes components from factorisation and renormalisation scales, PDFs, the strong coupling constant, and the top-quark mass.
Observed and expected 95% CL limits on the cross-section times branching ratio for the production of a $W^{\prime}$ boson with decay to tb and right-handed couplings as a function of the mass of the $W^{\prime}$ boson and a coupling value of $g^{\prime}/g$=0.5. The observed and expected limits are derived using a linear interpolation between simulated signal mass hypotheses. The uncertainty on the theory prediction includes components from factorisation and renormalisation scales, PDFs, the strong coupling constant, and the top-quark mass.
Observed and expected 95% CL limits on the cross-section times branching ratio for the production of a $W^{\prime}$ boson with decay to tb and right-handed couplings as a function of the mass of the $W^{\prime}$ boson and a coupling value of $g^{\prime}/g$=1.0. The observed and expected limits are derived using a linear interpolation between simulated signal mass hypotheses. The uncertainty on the theory prediction includes components from factorisation and renormalisation scales, PDFs, the strong coupling constant, and the top-quark mass.
Observed and expected 95% CL limits on the cross-section times branching ratio for the production of a $W^{\prime}$ boson with decay to tb and right-handed couplings as a function of the mass of the $W^{\prime}$ boson and a coupling value of $g^{\prime}/g$=2.0. The observed and expected limits are derived using a linear interpolation between simulated signal mass hypotheses. The uncertainty on the theory prediction includes components from factorisation and renormalisation scales, PDFs, the strong coupling constant, and the top-quark mass.
95% CL limits on the coupling value ($g^{\prime}/g$) and the $W^{\prime}$-boson mass for left-handed $W^{\prime}$-boson couplings. The area above the line is excluded.
95% CL limits on the coupling value ($g^{\prime}/g$) and the $W^{\prime}$-boson mass for right-handed $W^{\prime}$-boson couplings. The area above the line is excluded.
The product of fiducial acceptance and selection efficiency for the three signal regions of the 0-lepton channel as a function of the mass of the $W^{\prime}$ boson with left-handed chirality. The $W^{\prime}$ boson coupling strength is set to $g^{\prime}/g=1$.
The product of fiducial acceptance and selection efficiency for the three signal regions of the 0-lepton channel as a function of the mass of the $W^{\prime}$ boson with left-handed chirality. The $W^{\prime}$ boson coupling strength is set to $g^{\prime}/g=0.5$.
The product of fiducial acceptance and selection efficiency for the three signal regions of the 0-lepton channel as a function of the mass of the $W^{\prime}$ boson with left-handed chirality. The $W^{\prime}$ boson coupling strength is set to $g^{\prime}/g=2$.
The product of fiducial acceptance and selection efficiency for the four signal regions of the 1-lepton channel as a function of the mass of the $W^{\prime}$ boson with left-handed chirality. The $W^{\prime}$ boson coupling strength is set to $g^{\prime}/g=1$.
The product of fiducial acceptance and selection efficiency for the four signal regions of the 1-lepton channel as a function of the mass of the $W^{\prime}$ boson with left-handed chirality. The $W^{\prime}$ boson coupling strength is set to $g^{\prime}/g=0.5$.
The product of fiducial acceptance and selection efficiency for the four signal regions of the 1-lepton channel as a function of the mass of the $W^{\prime}$ boson with left-handed chirality. The $W^{\prime}$ boson coupling strength is set to $g^{\prime}/g=2$.
The product of fiducial acceptance and selection efficiency for the three signal regions of the 0-lepton channel as a function of the mass of the $W^{\prime}$ boson with right-handed chirality. The $W^{\prime}$ boson coupling strength is set to $g^{\prime}/g=1$.
The product of fiducial acceptance and selection efficiency for the three signal regions of the 0-lepton channel as a function of the mass of the $W^{\prime}$ boson with right-handed chirality. The $W^{\prime}$ boson coupling strength is set to $g^{\prime}/g=0.5$.
The product of fiducial acceptance and selection efficiency for the three signal regions of the 0-lepton channel as a function of the mass of the $W^{\prime}$ boson with right-handed chirality. The $W^{\prime}$ boson coupling strength is set to $g^{\prime}/g=2$.
The product of fiducial acceptance and selection efficiency for the four signal regions of the 1-lepton channel as a function of the mass of the $W^{\prime}$ boson with right-handed chirality. The $W^{\prime}$ boson coupling strength is set to $g^{\prime}/g=1$.
The product of fiducial acceptance and selection efficiency for the four signal regions of the 1-lepton channel as a function of the mass of the $W^{\prime}$ boson with right-handed chirality. The $W^{\prime}$ boson coupling strength is set to $g^{\prime}/g=0.5$.
The product of fiducial acceptance and selection efficiency for the four signal regions of the 1-lepton channel as a function of the mass of the $W^{\prime}$ boson with right-handed chirality. The $W^{\prime}$ boson coupling strength is set to $g^{\prime}/g=2$.
The multi-strange baryon yields in Pb--Pb collisions have been shown to exhibit an enhancement relative to pp reactions. In this work, $\Xi$ and $\Omega$ production rates have been measured with the ALICE experiment as a function of transverse momentum, ${p_{\rm T}}$, in p-Pb collisions at a centre-of-mass energy of ${\sqrt{s_{\rm NN}}}$ = 5.02 TeV. The results cover the kinematic ranges 0.6 GeV/$c<{p_{\rm T}} <$7.2 GeV/$c$ and 0.8 GeV/$c<{p_{\rm T}}<$ 5 GeV/$c$, for $\Xi$ and $\Omega$ respectively, in the common rapidity interval -0.5 $<{y_{\rm CMS}}<$ 0. Multi-strange baryons have been identified by reconstructing their weak decays into charged particles. The ${p_{\rm T}}$ spectra are analysed as a function of event charged-particle multiplicity, which in p-Pb collisions ranges over one order of magnitude and lies between those observed in pp and Pb-Pb collisions. The measured ${p_{\rm T}}$ distributions are compared to the expectations from a Blast-Wave model. The parameters which describe the production of lighter hadron species also describe the hyperon spectra in high multiplicity p-Pb. The yield of hyperons relative to charged pions is studied and compared with results from pp and Pb-Pb collisions. A statistical model is employed, which describes the change in the ratios with volume using a canonical suppression mechanism, in which the small volume causes a species-dependent relative reduction of hadron production. The calculations, in which the magnitude of the effect depends on the strangeness content, show good qualitative agreement with the data.
Xi pt spectrum in 0-5% multiplicity class.
Xi pt spectrum in 5-10% multiplicity class.
Xi pt spectrum in 10-20% multiplicity class.
Xi pt spectrum in 20-40% multiplicity class.
Xi pt spectrum in 40-60% multiplicity class.
Xi pt spectrum in 60-80% multiplicity class.
Xi pt spectrum in 80-100% multiplicity class.
Omega pt spectrum in 0-5% multiplicity class.
Omega pt spectrum in 5-10% multiplicity class.
Omega pt spectrum in 10-20% multiplicity class.
Omega pt spectrum in 20-40% multiplicity class.
Omega pt spectrum in 40-60% multiplicity class.
Omega pt spectrum in 60-80% multiplicity class.
Omega pt spectrum in 80-100% multiplicity class.
Mean pT of XI- in p-Pb collisions with centre-of-mass energy/nucleon=5.02 TeV for each V0A multiplicity event class.
Mean pT of XIBAR+ in p-Pb collisions with centre-of-mass energy/nucleon=5.02 TeV for each V0A multiplicity event class.
Mean pT of OMEGA- in p-Pb collisions with centre-of-mass energy/nucleon=5.02 TeV for each V0A multiplicity event class.
Mean pT of OMEGABAR+ in p-Pb collisions with centre-of-mass energy/nucleon=5.02 TeV for each V0A multiplicity event class.
XiMinus yield as a function of charged particle multiplicity per unit pseudorapidity.
XiPlus yield as a function of charged particle multiplicity per unit pseudorapidity.
OmegaMinus yield as a function of charged particle multiplicity per unit pseudorapidity.
OmegaPlus yield as a function of charged particle multiplicity per unit pseudorapidity.
Xi/pi ratio as a function of charged particle multiplicity per unit pseudorapidity.
Omega/pi ratio as a function of charged particle multiplicity per unit pseudorapidity.
A search for long-lived particles decaying into hadrons and at least one muon is presented. The analysis selects events that pass a muon or missing-transverse-momentum trigger and contain a displaced muon track and a displaced vertex. The analyzed dataset of proton-proton collisions at $\sqrt{s} = 13$ TeV was collected with the ATLAS detector and corresponds to 136 fb$^{-1}$. The search employs dedicated reconstruction techniques that significantly increase the sensitivity to long-lived particle decays that occur in the ATLAS inner detector. Background estimates for Standard Model processes and instrumental effects are extracted from data. The observed event yields are compatible with those expected from background processes. The results are presented as limits at 95% confidence level on model-independent cross sections for processes beyond the Standard Model, and interpreted as exclusion limits in scenarios with pair-production of long-lived top squarks that decay via a small $R$-parity-violating coupling into a quark and a muon. Top squarks with masses up to 1.7 TeV are excluded for a lifetime of 0.1 ns, and masses below 1.3 TeV are excluded for lifetimes between 0.01 ns and 30 ns.
Vertex selection acceptance for the $\tilde{t}$ $R$-hadron benchmark model as a function of the transverse decay distance $r_{DV}$.
Vertex selection acceptance for the $\tilde{t}$ $R$-hadron benchmark model as a function of the transverse decay distance $r_{DV}$.
Vertex selection efficiency for the $\tilde{t}$ $R$-hadron benchmark model as a function of the transverse decay distance $r_{DV}$.
Vertex selection efficiency for the $\tilde{t}$ $R$-hadron benchmark model as a function of the transverse decay distance $r_{DV}$.
Track multiplicity $n_{Tracks}$ for preselected DVs in MET-triggered events with at least one muon passing the full selection. Along with the data shown with black markers, the stacked filled histograms represent the background estimates, and predictions for signal scenarios are overlaid with dashed lines. The errors include statistical and systematic uncertainties and are indicated by hatched bands. The DV full selection requirements, $n_{Tracks} \geq 3$ and $m_{DV} > 20$ GeV are visualized with a black arrow.
Track multiplicity $n_{Tracks}$ for preselected DVs in MET-triggered events with at least one muon passing the full selection. Along with the data shown with black markers, the stacked filled histograms represent the background estimates, and predictions for signal scenarios are overlaid with dashed lines. The errors include statistical and systematic uncertainties and are indicated by hatched bands. The DV full selection requirements, $n_{Tracks} \geq 3$ and $m_{DV} > 20$ GeV are visualized with a black arrow.
Track multiplicity $n_{Tracks}$ for preselected DVs in muon-triggered events with at least one muon passing the full selection. Along with the data shown with black markers, the stacked filled histograms represent the background estimates, and predictions for signal scenarios are overlaid with dashed lines. The errors include statistical and systematic uncertainties and are indicated by hatched bands. The DV full selection requirements, $n_{Tracks} \geq 3$ and $m_{DV} > 20$ GeV are visualized with a black arrow.
Track multiplicity $n_{Tracks}$ for preselected DVs in muon-triggered events with at least one muon passing the full selection. Along with the data shown with black markers, the stacked filled histograms represent the background estimates, and predictions for signal scenarios are overlaid with dashed lines. The errors include statistical and systematic uncertainties and are indicated by hatched bands. The DV full selection requirements, $n_{Tracks} \geq 3$ and $m_{DV} > 20$ GeV are visualized with a black arrow.
Invariant mass $m_{DV}$ for the highest-mass preselected DV with at least three associated tracks in MET-triggered events with at least one muon passing the full selection. Along with the data shown with black markers, the stacked filled histograms represent the background estimates, and predictions for signal scenarios are overlaid with dashed lines. The errors include statistical and systematic uncertainties and are indicated by hatched bands. The DV full selection requirements, $n_{Tracks} \geq 3$ and $m_{DV} > 20$ GeV are visualized with a black arrow.
Invariant mass $m_{DV}$ for the highest-mass preselected DV with at least three associated tracks in MET-triggered events with at least one muon passing the full selection. Along with the data shown with black markers, the stacked filled histograms represent the background estimates, and predictions for signal scenarios are overlaid with dashed lines. The errors include statistical and systematic uncertainties and are indicated by hatched bands. The DV full selection requirements, $n_{Tracks} \geq 3$ and $m_{DV} > 20$ GeV are visualized with a black arrow.
Invariant mass $m_{DV}$ for the highest-mass preselected DV with at least three associated tracks in muon-triggered events with at least one muon passing the full selection. Along with the data shown with black markers, the stacked filled histograms represent the background estimates, and predictions for signal scenarios are overlaid with dashed lines. The errors include statistical and systematic uncertainties and are indicated by hatched bands. The DV full selection requirements, $n_{Tracks} \geq 3$ and $m_{DV} > 20$ GeV are visualized with a black arrow.
Invariant mass $m_{DV}$ for the highest-mass preselected DV with at least three associated tracks in muon-triggered events with at least one muon passing the full selection. Along with the data shown with black markers, the stacked filled histograms represent the background estimates, and predictions for signal scenarios are overlaid with dashed lines. The errors include statistical and systematic uncertainties and are indicated by hatched bands. The DV full selection requirements, $n_{Tracks} \geq 3$ and $m_{DV} > 20$ GeV are visualized with a black arrow.
The observed event yields in the control, validation and signal regions are shown for the MET Trigger selections, along with the predicted background yields. The bottom panel shows the ratio of observed events to the total background yields. The errors represent the total uncertainty of the backgrounds prediction, including the statistical and systematic uncertainties added in quadrature.
The observed event yields in the control, validation and signal regions are shown for the MET Trigger selections, along with the predicted background yields. The bottom panel shows the ratio of observed events to the total background yields. The errors represent the total uncertainty of the backgrounds prediction, including the statistical and systematic uncertainties added in quadrature.
The observed event yields in the control, validation and signal regions are shown for the Muon Trigger selections, along with the predicted background yields. The bottom panel shows the ratio of observed events to the total background yields. The errors represent the total uncertainty of the backgrounds prediction, including the statistical and systematic uncertainties added in quadrature.
The observed event yields in the control, validation and signal regions are shown for the Muon Trigger selections, along with the predicted background yields. The bottom panel shows the ratio of observed events to the total background yields. The errors represent the total uncertainty of the backgrounds prediction, including the statistical and systematic uncertainties added in quadrature.
Expected exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.
Expected exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.
Expected (1 sigma band) exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.
Expected (1 sigma band) exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.
Expected (2 sigma band) exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.
Expected (2 sigma band) exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.
Observed exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.
Observed exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.
Observed (+1 sigma) exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.
Observed (+1 sigma) exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.
Observed (-1 sigma) exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.
Observed (-1 sigma) exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.
Exclusion limits on the production cross section as a function of m($\tilde{t}$) are shown for several values of $\tau(\tilde{t})$ along with the nominal signal production cross section and its theoretical uncertainty.
Exclusion limits on the production cross section as a function of m($\tilde{t}$) are shown for several values of $\tau(\tilde{t})$ along with the nominal signal production cross section and its theoretical uncertainty.
Parameterized event selection efficiencies for the $E_{T}^{miss}$ Trigger SR. The event-level efficiencies for each SR are extracted for all events passing the acceptance of the corresponding SR.
Parameterized event selection efficiencies for the $E_{T}^{miss}$ Trigger SR. The event-level efficiencies for each SR are extracted for all events passing the acceptance of the corresponding SR.
Parameterized event selection efficiencies for the Muon Trigger SR. The event-level efficiencies for each SR are extracted for all events passing the acceptance of the corresponding SR.
Parameterized event selection efficiencies for the Muon Trigger SR. The event-level efficiencies for each SR are extracted for all events passing the acceptance of the corresponding SR.
Parameterized muon-level reconstruction efficiencies as a function of the muon $p_{T}$ and $d_{0}$. The muon-level efficiencies are extracted using muons passing the muon acceptance criteria.
Parameterized muon-level reconstruction efficiencies as a function of the muon $p_{T}$ and $d_{0}$. The muon-level efficiencies are extracted using muons passing the muon acceptance criteria.
Parameterized vertex-level reconstruction efficiencies as a function of the radial position of the truth vertex. The efficiency is calculated independent of the muons originating from this truth vertex.
Parameterized vertex-level reconstruction efficiencies as a function of the radial position of the truth vertex. The efficiency is calculated independent of the muons originating from this truth vertex.
Parameterized vertex-level reconstruction efficiencies as a function of the radial position of the truth vertex. The efficiency is calculated only for truth vertices which have a muon originating from them which is matched to a reconstructed muon.
Parameterized vertex-level reconstruction efficiencies as a function of the radial position of the truth vertex. The efficiency is calculated only for truth vertices which have a muon originating from them which is matched to a reconstructed muon.
The $p_{T}$ distribution of all muons originating from LLP decays in the samples used to calculate and validate the efficiencies.
The $p_{T}$ distribution of all muons originating from LLP decays in the samples used to calculate and validate the efficiencies.
The invariant mass and multiplicity of selected decay products of all truth vertices used in the calculation and validation of the reconstructed efficiencies.
The invariant mass and multiplicity of selected decay products of all truth vertices used in the calculation and validation of the reconstructed efficiencies.
A search for supersymmetry targeting the direct production of winos and higgsinos is conducted in final states with either two leptons ($e$ or $\mu$) with the same electric charge, or three leptons. The analysis uses 139 fb$^{-1}$ of $pp$ collision data at $\sqrt{s}=13$ TeV collected with the ATLAS detector during Run 2 of the Large Hadron Collider. No significant excess over the Standard Model expectation is observed. Simplified and complete models with and without $R$-parity conservation are considered. In topologies with intermediate states including either $Wh$ or $WZ$ pairs, wino masses up to 525 GeV and 250 GeV are excluded, respectively, for a bino of vanishing mass. Higgsino masses smaller than 440 GeV are excluded in a natural $R$-parity-violating model with bilinear terms. Upper limits on the production cross section of generic events beyond the Standard Model as low as 40 ab are obtained in signal regions optimised for these models and also for an $R$-parity-violating scenario with baryon-number-violating higgsino decays into top quarks and jets. The analysis significantly improves sensitivity to supersymmetric models and other processes beyond the Standard Model that may contribute to the considered final states.
Observed exclusion limits at 95% CL for the WZ-mediated simplified model of wino $\tilde{\chi}^{\pm}_{1}/\tilde{\chi}^{0}_{2}$ production from Fig 13(b) and Fig 8(aux).
positive one $\sigma$ observed exclusion limits at 95% CL for the WZ-mediated simplified model of wino $\tilde{\chi}^{\pm}_{1}/\tilde{\chi}^{0}_{2}$ production from Fig 13(b) and Fig 8(aux).
negative $\sigma$ variation of observed exclusion limits at 95% CL for the WZ-mediated simplified model of wino $\tilde{\chi}^{\pm}_{1}/\tilde{\chi}^{0}_{2}$ production from Fig 13(b) and Fig 8(aux).
Observed excluded cross-section at 95% CL for the WZ-mediated simplified model of wino $\tilde{\chi}^{\pm}_{1}/\tilde{\chi}^{0}_{2}$ production from Fig 8(aux).
Expected exclusion limits at 95% CL for the WZ-mediated simplified model of wino $\tilde{\chi}^{\pm}_{1}/\tilde{\chi}^{0}_{2}$ production.
Observed exclusion limits at 95% CL for the Wh-mediated simplified model of wino $\tilde{\chi}^{\pm}_{1}/\tilde{\chi}^{0}_{2}$ production from from Fig 13(a) and from Fig 7 and Fig 10(aux).
Observed excluded cross-section at 95% CL for the Wh-mediated simplified model of wino $\tilde{\chi}^{\pm}_{1}/\tilde{\chi}^{0}_{2}$ production from Fig 7(aux) and Fig 10(aux).
positive one $\sigma$ observed exclusion limits at 95% CL for the Wh-mediated simplified model of wino $\tilde{\chi}^{\pm}_{1}/\tilde{\chi}^{0}_{2}$ production from from Fig 13(a) and from Fig 7 and Fig 10(aux).
negative one $\sigma$ observed exclusion limits at 95% CL for the Wh-mediated simplified model of wino $\tilde{\chi}^{\pm}_{1}/\tilde{\chi}^{0}_{2}$ production from from Fig 13(a) and from Fig 7 and Fig 10(aux).
Expected exclusion limits at 95% CL for the Wh-mediated simplified model of wino $\tilde{\chi}^{\pm}_{1}/\tilde{\chi}^{0}_{2}$ production.
Expected exclusion limits at 95% CL for the Wh-mediated simplified model of wino $\tilde{\chi}^{\pm}_{1}/\tilde{\chi}^{0}_{2}$ production.
Expected exclusion limits at 95% CL for the Wh-mediated simplified model of wino $\tilde{\chi}^{\pm}_{1}/\tilde{\chi}^{0}_{2}$ production.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region $SR^{bRPV}_{2l-SS}$. in a susy scenario where $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are produced in pairs and decay to all possible allowed bRPV decays. The masses of the superpartners involved in the process are set to $m(\tilde{\chi}^{0} _{1}/\tilde{\chi}^{0} _{2})$ = 200 GeV, tan$\beta$=5. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region $SR^{bRPV}_{3l}$. in a susy scenario where $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are produced in pairs and decay to all possible allowed bRPV decays. The masses of the superpartners involved in the process are set to $m(\tilde{\chi}^{0} _{1}/\tilde{\chi}^{0} _{2})$ = 200 GeV, tan$\beta$=5. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region $SR^{WZ}_{high-m_{T2}}$. The wino-like doublet pair ($\tilde{\chi}^{\pm} _{1} and \tilde{\chi}^{0} _{2}$) were produced and then decays into $bino-like \tilde{\chi}^{0} _{1}$ which is the lightest SUSY particle (LSP) accompanied by mass on-shell or mass off-shell W and Z bosons. The masses of the superpartners involved in the process are set to $m(\tilde{\chi}^{\pm} _{1}/\tilde{\chi}^{0} _{2})$ = 150 GeV, $m(\tilde{\chi}^{0} _{1})$ = 50 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region $SR^{WZ}_{low-m_{T2}}$. The wino-like doublet pair ($\tilde{\chi}^{\pm} _{1} and \tilde{\chi}^{0} _{2}$) were produced and then decays into $bino-like \tilde{\chi}^{0} _{1}$ which is the lightest SUSY particle (LSP) accompanied by mass on-shell or mass off-shell W and Z bosons. The masses of the superpartners involved in the process are set to $m(\tilde{\chi}^{\pm} _{1}/\tilde{\chi}^{0} _{2})$ = 150 GeV, $m(\tilde{\chi}^{0} _{1})$ = 50 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the low mass $SR^{RPV}_{2l1b}$, where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays. The masses of the superpartners involved in the process are set to $m(\tilde{\chi}^{0} _{1}/\tilde{\chi}^{0} _{2})$ = 200 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the medium mass $SR^{RPV}_{2l1b}$, where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays. The masses of the superpartners involved in the process are set to $m(\tilde{\chi}^{0} _{1}/\tilde{\chi}^{0} _{2})$ = 200 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the low mass $SR^{RPV}_{2l2b}$, where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays. The masses of the superpartners involved in the process are set to $m(\tilde{\chi}^{0} _{1}/\tilde{\chi}^{0} _{2})$ = 200 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the medium mass $SR^{RPV}_{2l2b}$, where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays. The masses of the superpartners involved in the process are set to $m(\tilde{\chi}^{0} _{1}/\tilde{\chi}^{0} _{2})$ = 200 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the high mass $SR^{RPV}_{2l2b}$, where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays. The masses of the superpartners involved in the process are set to $m(\tilde{\chi}^{0} _{1}/\tilde{\chi}^{0} _{2})$ = 200 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the low mass $SR^{RPV}_{2l3b}$, where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays. The masses of the superpartners involved in the process are set to $m(\tilde{\chi}^{0} _{1}/\tilde{\chi}^{0} _{2})$ = 200 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the medium mass $SR^{RPV}_{2l3b}$, where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays. The masses of the superpartners involved in the process are set to $m(\tilde{\chi}^{0} _{1}/\tilde{\chi}^{0} _{2})$ = 200 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the high mass $SR^{RPV}_{2l3b}$, where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays. The masses of the superpartners involved in the process are set to $m(\tilde{\chi}^{0} _{1}/\tilde{\chi}^{0} _{2})$ = 200 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the $SR^{Wh}_{low-m_{T2} }$. The wino-like doublet pair ($\tilde{\chi}^{\pm} _{1} and \tilde{\chi}^{0} _{2}$) were produced and then decays into $bino-like \tilde{\chi}^{0} _{1}$ which is the lightest SUSY particle (LSP) accompanied by mass on-shell or mass off-shell W and Higgs bosons. The masses of the superpartners involved in the process are set to $m(\tilde{\chi}^{\pm} _{1}/\tilde{\chi}^{0} _{2})$ = 300 GeV, $m(\tilde{\chi}^{0} _{1})$ = 100 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the $SR^{Wh}_{high-m_{T2} }$. The wino-like doublet pair ($\tilde{\chi}^{\pm} _{1} and \tilde{\chi}^{0} _{2}$) were produced and then decays into $bino-like \tilde{\chi}^{0} _{1}$ which is the lightest SUSY particle (LSP) accompanied by mass on-shell or mass off-shell W and Higgs bosons. The masses of the superpartners involved in the process are set to $m(\tilde{\chi}^{\pm} _{1}/\tilde{\chi}^{0} _{2})$ = 300 GeV, $m(\tilde{\chi}^{0} _{1})$ = 100 GeV. Only statistical uncertainties are shown.
Signal Hepdataeptance for $SR^{bRPV}_{2l-SS}$ signal region from Fig 13(a)(aux) in a SUSY scenario where $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are produced in pairs and decay to all possible allowed bRPV decays.
Signal Hepdataeptance for $SR^{bRPV}_{3l}$ signal region from Fig 13(b)(aux) in a SUSY scenario where $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are produced in pairs and decay to all possible allowed bRPV decays.
Signal acceptance for $SR^{WZ}_{high-m_{T2}}$ in a SUSY scenario where the wino-like doublet pair ($\tilde{\chi}^{\pm} _{1} and \tilde{\chi}^{0} _{2}$) were produced and then decays into $bino-like \tilde{\chi}^{0} _{1}$ which is the lightest SUSY particle (LSP) accompanied by mass on-shell or mass off-shell W and Z bosons.
Signal acceptance for $SR^{WZ}_{low-m_{T2}}$ in a SUSY scenario where the wino-like doublet pair ($\tilde{\chi}^{\pm} _{1} and \tilde{\chi}^{0} _{2}$) were produced and then decays into $bino-like \tilde{\chi}^{0} _{1}$ which is the lightest SUSY particle (LSP) accompanied by mass on-shell or mass off-shell W and Z bosons.
Signal acceptance for $SR^{RPV}_{2l1b}-L$ signal region in a SUSY scenario where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays.
Signal acceptance for $SR^{RPV}_{2l1b}-M$ signal region in a SUSY scenario where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays.
Signal acceptance for $SR^{RPV}_{2l2b}-L$ signal region in a SUSY scenario where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays.
Signal acceptance for $SR^{RPV}_{2l2b}-M$ signal region in a SUSY scenario where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays.
Signal acceptance for $SR^{RPV}_{2l2b}-H$ signal region in a SUSY scenario where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays.
Signal acceptance for $SR^{RPV}_{2l3b}-L$ signal region in a SUSY scenario where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays.
Signal acceptance for $SR^{RPV}_{2l3b}-M$ signal region in a SUSY scenario where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays.
Signal acceptance for $SR^{RPV}_{2l3b}-H$ signal region in a SUSY scenario where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays.
Signal efficiency for $SR^{bRPV}_{2l-SS}$ signal region in a SUSY scenario where $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are produced in pairs and decay to all possible allowed bRPV decays.
Signal efficiency for $SR^{bRPV}_{3l}$ signal region in a SUSY scenario where $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are produced in pairs and decay to all possible allowed bRPV decays.
Signal efficiency for $SR^{WZ}_{high-m_{T2}}$ in a SUSY scenario where the wino-like doublet pair ($\tilde{\chi}^{\pm} _{1} and \tilde{\chi}^{0} _{2}$) were produced and then decays into $bino-like \tilde{\chi}^{0} _{1}$ which is the lightest SUSY particle (LSP) accompanied by mass on-shell or mass off-shell W and Z bosons.
Signal efficiency for $SR^{WZ}_{low-m_{T2}}$ in a SUSY scenario where the wino-like doublet pair ($\tilde{\chi}^{\pm} _{1} and \tilde{\chi}^{0} _{2}$) were produced and then decays into $bino-like \tilde{\chi}^{0} _{1}$ which is the lightest SUSY particle (LSP) accompanied by mass on-shell or mass off-shell W and Z bosons.
Signal efficiency for $SR^{RPV}_{2l1b}-L$ signal region in a SUSY scenario where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays.
Signal efficiency for $SR^{RPV}_{2l1b}-M$ signal region in a SUSY scenario where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays.
Signal efficiency for $SR^{RPV}_{2l2b}-L$ signal region in a SUSY scenario where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays.
Signal efficiency for $SR^{RPV}_{2l2b}-M$ signal region in a SUSY scenario where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays.
Signal efficiency for $SR^{RPV}_{2l2b}-H$ signal region in a SUSY scenario where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays.
Signal efficiency for $SR^{RPV}_{2l3b}-L$ signal region in a SUSY scenario where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays.
Signal efficiency for $SR^{RPV}_{2l3b}-M$ signal region in a SUSY scenario where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays.
Signal efficiency for $SR^{RPV}_{2l3b}-H$ signal region in a SUSY scenario where the $\tilde{\chi}^{0} _{1} and \tilde{\chi}^{0} _{2}$ are directly produced and undergoes prompt RPV decays.
Signal acceptance for $SR^{Wh}_{high-m_{T2} }$ signal region from Fig 11(a)(aux) in a SUSY scenario where direct production of a lightest $\tilde{\chi}^{\pm} _{1} and \tilde{\chi}^{0} _{2}$ , decay with 100% branching ratio to a final state with a same sign light lepton (e or $\mu$) pair and two lightest neutralino1, via the on-shell emission of SM W and Higgs bosons,
Signal acceptance for $SR^{Wh}_{low-m_{T2} }$ signal region from Fig 11(b)(aux) in a SUSY scenario where direct production of a lightest $\tilde{\chi}^{\pm} _{1} and \tilde{\chi}^{0} _{2}$ , decay with 100% branching ratio to a final state with a same sign light lepton (e or $\mu$) pair and two lightest neutralino1, via the on-shell emission of SM W and Higgs bosons,
Signal efficiency for $SR^{Wh}_{high-m_{T2} }$ signal region from Fig 15(a)(aux) in a SUSY scenario where direct production of a lightest $\tilde{\chi}^{\pm} _{1} and \tilde{\chi}^{0} _{2}$ , decay with 100% branching ratio to a final state with a same sign light lepton (e or $\mu$) pair and two lightest neutralino1, via the on-shell emission of SM W and Higgs bosons,
Signal efficiency for $SR^{Wh}_{low-m_{T2} }$ signal region from Fig 15(b)(aux) in a SUSY scenario where direct production of a lightest $\tilde{\chi}^{\pm} _{1} and \tilde{\chi}^{0} _{2}$ , decay with 100% branching ratio to a final state with a same sign light lepton (e or $\mu$) pair and two lightest neutralino1, via the on-shell emission of SM W and Higgs bosons,
Observed 95% X-section upper limits as a function of higgsino $\tilde{\chi}^{\pm}_{1}/\tilde{\chi}^{0}_{1}/\tilde{\chi}^{0}_{2}$ mass in the bilinear RPV model from Fig 14.
Observed 95% X-section upper limits as a function of higgsino $\tilde{\chi}^{0}_{1}/\tilde{\chi}^{0}_{2}$ mass in the UDD RPV model from Fig 18.
Observed 95% X-section upper limits as a function of wino $\tilde{\chi}^{\pm}_{1}/\tilde{\chi}^{0}_{2}$ mass in the WZ-mediated simplified model of wino $\tilde{\chi}^{\pm}_{1}/\tilde{\chi}^{0}_{2}$ production from Fig 9(aux).
N-1 distributions for $m_{T2}$ of observed data and expected background towards $SR^{WZ}_{high-m_{T2}}$ from publication's Figure 11(a) . The last bin is inclusive.
N-1 distributions for $m_{T2}$ of observed data and expected background towards $SR^{WZ}_{low-m_{T2}}$ from publication's Figure 11(b) . The last bin is inclusive.
N-1 distributions for $m_{T2}$ of observed data and expected background towards $SR^{bRPV}_{2l-SS}$ from publication's Figure 11(c) . The last bin is inclusive.
N-1 distributions for $m_{T2}$ of observed data and expected background towards $SR^{bRPV}_{3l}$ from publication's Figure 11(d) . The last bin is inclusive.
N-1 distributions for $\sum p^{b-jet}_{T}/\sum p^{jet}_{T}$ of observed data and expected background towards $SR^{RPV}_{2l1b}-L$ from publication's Figure 16(a) . The last bin is inclusive.
N-1 distributions for $\sum p^{b-jet}_{T}/\sum p^{jet}_{T}$ of observed data and expected background towards $SR^{RPV}_{2l2b}-M$ from publication's Figure 16(b) . The last bin is inclusive.
N-1 distributions for $\sum p^{b-jet}_{T}/\sum p^{jet}_{T}$ of observed data and expected background towards $SR^{RPV}_{2l3b}-H$ from publication's Figure 16(c) . The last bin is inclusive.
N-1 distribution for $E_{T}^{miss}$ in $SR^{Wh}_{high-m_{T2} }$ in ee channel
N-1 distribution for $E_{T}^{miss}$ in $SR^{Wh}_{high-m_{T2} }$ in e$\mu$ channel
N-1 distribution for $E_{T}^{miss}$ in $SR^{Wh}_{high-m_{T2} }$ in $\mu\mu$ channel
N-1 distribution for $\mathcal{S}(E_{T}^{miss})$ in $SR^{Wh}_{low-m_{T2} }$ in ee channel
N-1 distribution for $\mathcal{S}(E_{T}^{miss})$ in $SR^{Wh}_{low-m_{T2} }$ in e$\mu$ channel
N-1 distribution for $\mathcal{S}(E_{T}^{miss})$ in $SR^{Wh}_{low-m_{T2} }$ in $\mu\mu$ channel
A search for the direct production of the supersymmetric partners of $\tau$-leptons (staus) in final states with two hadronically decaying $\tau$-leptons is presented. The analysis uses a dataset of $pp$ collisions corresponding to an integrated luminosity of $139$ fb$^{-1}$, recorded with the ATLAS detector at the Large Hadron Collider at a center-of-mass energy of 13 TeV. No significant deviation from the expected Standard Model background is observed. Limits are derived in scenarios of direct production of stau pairs with each stau decaying into the stable lightest neutralino and one $\tau$-lepton in simplified models where the two stau mass eigenstates are degenerate. Stau masses from 120 GeV to 390 GeV are excluded at 95% confidence level for a massless lightest neutralino.
The observed upper limits on the model cross-section in units of pb for simplified models with combined ${\tilde{\tau}}^{+}_{R,L} {\tilde{\tau}}^{-}_{R,L}$ production. Three points at ${M({\tilde{\chi}}^{0}_{1})}=200GeV$ were removed from the plot but kept in the table because they overlapped with the plot's legend and are far from the exclusion contour.
The observed upper limits on the model cross-section in units of pb for simplified models with combined ${\tilde{\tau}}^{+}_{R,L} {\tilde{\tau}}^{-}_{R,L}$ production. Three points at ${M({\tilde{\chi}}^{0}_{1})}=200GeV$ were removed from the plot but kept in the table because they overlapped with the plot's legend and are far from the exclusion contour.
The observed upper limits on the model cross-section in units of pb for simplified models with ${\tilde{\tau}}_L {\tilde{\tau}}_L$ only production. Three points at $M({\tilde{\chi}}^{0}_{1})=200GeV$ were removed from the plot but kept in the table because they overlapped with the plot's legend and are far from the exclusion contour.
The observed upper limits on the model cross-section in units of pb for simplified models with ${\tilde{\tau}}_L {\tilde{\tau}}_L$ only production. Three points at $M({\tilde{\chi}}^{0}_{1})=200GeV$ were removed from the plot but kept in the table because they overlapped with the plot's legend and are far from the exclusion contour.
The observed 95\% CL exclusion contours for the combined fit of SR-lowMass and SR-highMass for simplified models with combined ${\tilde{\tau}}^{+}_{R,L} {\tilde{\tau}}^{-}_{R,L}$ production.
The observed 95\% CL exclusion contours for the combined fit of SR-lowMass and SR-highMass for simplified models with combined ${\tilde{\tau}}^{+}_{R,L} {\tilde{\tau}}^{-}_{R,L}$ production.
The expected 95% CL exclusion contours for the combined fit of SR-lowMass and SR-highMass for simplified models with combined ${\tilde{\tau}}^{+}_{R,L} {\tilde{\tau}}^{-}_{R,L}$ production.
The expected 95% CL exclusion contours for the combined fit of SR-lowMass and SR-highMass for simplified models with combined ${\tilde{\tau}}^{+}_{R,L} {\tilde{\tau}}^{-}_{R,L}$ production.
The observed 95% CL exclusion contours for the combined fit of SR-lowMass and SR-highMass for simplified models with ${\tilde{\tau}}_L {\tilde{\tau}}_L$ only production.
The observed 95% CL exclusion contours for the combined fit of SR-lowMass and SR-highMass for simplified models with ${\tilde{\tau}}_L {\tilde{\tau}}_L$ only production.
The expected 95% CL exclusion contours for the combined fit of SR-lowMass and SR-highMass for simplified models with ${\tilde{\tau}}_L {\tilde{\tau}}_L$ only production.
The expected 95% CL exclusion contours for the combined fit of SR-lowMass and SR-highMass for simplified models with ${\tilde{\tau}}_L {\tilde{\tau}}_L$ only production.
Observed 95% CL exclusion limits for simplified models with direct stau pair production in SR-lowMass.
Observed 95% CL exclusion limits for simplified models with direct stau pair production in SR-lowMass.
Expected 95% CL exclusion limits for simplified models with direct stau pair production in SR-lowMass.
Expected 95% CL exclusion limits for simplified models with direct stau pair production in SR-lowMass.
Observed 95% CL exclusion limits for simplified models with direct stau pair production in SR-highMass.
Observed 95% CL exclusion limits for simplified models with direct stau pair production in SR-highMass.
Expected 95% CL exclusion limits for simplified models with direct stau pair production in SR-highMass.
Expected 95% CL exclusion limits for simplified models with direct stau pair production in SR-highMass.
Signal acceptance in SR highMass for combined stau final states
Signal acceptance in SR highMass for combined stau final states
Signal acceptance in SR lowMass for combined stau final states
Signal acceptance in SR lowMass for combined stau final states
Signal efficiency in SR highMass for combined stau final states
Signal efficiency in SR highMass for combined stau final states
Signal efficiency in SR lowMass for combined stau final states
Signal efficiency in SR lowMass for combined stau final states
Signal acceptance*efficiency in SR highMass for combined stau final states
Signal acceptance*efficiency in SR highMass for combined stau final states
Signal acceptance*efficiency in SR lowMass for combined stau final states
Signal acceptance*efficiency in SR lowMass for combined stau final states
Cutflow for two reference points (${\tilde{\tau}}^{+}_{R,L} {\tilde{\tau}}^{-}_{R,L}$ production) in SR. The column labelled $N_{weighted}$ shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$, while $N_{raw}$ in brackets shows the results for the generated number of events. The quoted uncertainties are statistical only. The "Generator filter" includes the requirements that two $\tau$ in the event have ${p}_{T} > 15$ GeV and $|\eta| <$ 2.6. The "Baseline Cut" includes the requirement of two baseline $\tau$ with a minimum value at 0.01 of the boosted decision tree discriminant (JetBDTSigTransMin $>$ 0.01) and ${p}_{T, \tau_{1}} > 50$ GeV and ${p}_{T, \tau_{2}} > 40$ GeV. At the step "Trigger & offline cuts", the following requirements are applied: the event is recorded using the asymmetric di-$\tau$ trigger (di-$\tau$ $E_{T}^{miss}$ trigger) in SR-lowMass (SR-highMass), and the lepton $p_{T}$ and $E_{T}^{miss}$ are required at plateau.
Cutflow for two reference points (${\tilde{\tau}}^{+}_{R,L} {\tilde{\tau}}^{-}_{R,L}$ production) in SR. The column labelled $N_{weighted}$ shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$, while $N_{raw}$ in brackets shows the results for the generated number of events. The quoted uncertainties are statistical only. The "Generator filter" includes the requirements that two $\tau$ in the event have ${p}_{T} > 15$ GeV and $|\eta| <$ 2.6. The "Baseline Cut" includes the requirement of two baseline $\tau$ with a minimum value at 0.01 of the boosted decision tree discriminant (JetBDTSigTransMin $>$ 0.01) and ${p}_{T, \tau_{1}} > 50$ GeV and ${p}_{T, \tau_{2}} > 40$ GeV. At the step "Trigger & offline cuts", the following requirements are applied: the event is recorded using the asymmetric di-$\tau$ trigger (di-$\tau$ $E_{T}^{miss}$ trigger) in SR-lowMass (SR-highMass), and the lepton $p_{T}$ and $E_{T}^{miss}$ are required at plateau.
Observed and expected numbers of events in the control and signal regions where all control and signal region bins are included as constraints in the likelihood. The expected event yields of SM processes are given after the background-only fit. The entries marked as "--" are negligible. The uncertainties correspond to the sum in quadrature of statistical and systematic uncertainties. The correlation of systematic uncertainties among control regions and among background processes is fully taken into account.
Observed and expected numbers of events in the control and signal regions where all control and signal region bins are included as constraints in the likelihood. The expected event yields of SM processes are given after the background-only fit. The entries marked as "--" are negligible. The uncertainties correspond to the sum in quadrature of statistical and systematic uncertainties. The correlation of systematic uncertainties among control regions and among background processes is fully taken into account.
The post-fit $m_{T2}$ distribution for SR-lowMass. The stacked histograms show the expected SM backgrounds. The multi-jet contribution is estimated from data using the ABCD method. The contributions of multi-jet and $W$+jets events are scaled with the corresponding normalization factors derived from the background-only fit. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distributions from the SUSY reference points are also shown as dashed lines. The last bin includes the overflow events.
The post-fit $m_{T2}$ distribution for SR-lowMass. The stacked histograms show the expected SM backgrounds. The multi-jet contribution is estimated from data using the ABCD method. The contributions of multi-jet and $W$+jets events are scaled with the corresponding normalization factors derived from the background-only fit. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distributions from the SUSY reference points are also shown as dashed lines. The last bin includes the overflow events.
The post-fit $m_{T2}$ distribution for SR-highMass. The stacked histograms show the expected SM backgrounds. The multi-jet contribution is estimated from data using the ABCD method. The contributions of multi-jet and $W$+jets events are scaled with the corresponding normalization factors derived from the background-only fit. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distributions from the SUSY reference points are also shown as dashed lines. The last bin includes the overflow events.
The post-fit $m_{T2}$ distribution for SR-highMass. The stacked histograms show the expected SM backgrounds. The multi-jet contribution is estimated from data using the ABCD method. The contributions of multi-jet and $W$+jets events are scaled with the corresponding normalization factors derived from the background-only fit. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distributions from the SUSY reference points are also shown as dashed lines. The last bin includes the overflow events.
The $m_{T2}$ post-fit distributions in the multi-jet background validation region VR-F (lowMass). The stacked histograms show the contribution of each relevant SM process. The multi-jet shape is taken from VR-E in the ABCD method and the normalization is determined by the transfer factor $T$ and rescaled by a correction factor determined by the fit. The hatched bands represent the combined statistical and systematic uncertainties in the sum of the SM backgrounds shown. For illustration, the distributions of the SUSY reference points are also shown as dashed lines.
The $m_{T2}$ post-fit distributions in the multi-jet background validation region VR-F (lowMass). The stacked histograms show the contribution of each relevant SM process. The multi-jet shape is taken from VR-E in the ABCD method and the normalization is determined by the transfer factor $T$ and rescaled by a correction factor determined by the fit. The hatched bands represent the combined statistical and systematic uncertainties in the sum of the SM backgrounds shown. For illustration, the distributions of the SUSY reference points are also shown as dashed lines.
The $m_{T2}$ post-fit distributions in the multi-jet background validation VR-F (highMass). The stacked histograms show the contribution of each relevant SM process. The multi-jet shape is taken from VR-E in the ABCD method and the normalization is determined by the transfer factor $T$ and rescaled by a correction factor determined by the fit. The hatched bands represent the combined statistical and systematic uncertainties in the sum of the SM backgrounds shown. For illustration, the distributions of the SUSY reference points are also shown as dashed lines.
The $m_{T2}$ post-fit distributions in the multi-jet background validation VR-F (highMass). The stacked histograms show the contribution of each relevant SM process. The multi-jet shape is taken from VR-E in the ABCD method and the normalization is determined by the transfer factor $T$ and rescaled by a correction factor determined by the fit. The hatched bands represent the combined statistical and systematic uncertainties in the sum of the SM backgrounds shown. For illustration, the distributions of the SUSY reference points are also shown as dashed lines.
The $E_{T}^{miss}$ post-fit distributions in the multi-jet background validation region VR-F (lowMass). The stacked histograms show the contribution of each relevant SM process. The multi-jet shape is taken from VR-E in the ABCD method and the normalization is determined by the transfer factor $T$ and rescaled by a correction factor determined by the fit. The hatched bands represent the combined statistical and systematic uncertainties in the sum of the SM backgrounds shown. For illustration, the distributions of the SUSY reference points are also shown as dashed lines.
The $E_{T}^{miss}$ post-fit distributions in the multi-jet background validation region VR-F (lowMass). The stacked histograms show the contribution of each relevant SM process. The multi-jet shape is taken from VR-E in the ABCD method and the normalization is determined by the transfer factor $T$ and rescaled by a correction factor determined by the fit. The hatched bands represent the combined statistical and systematic uncertainties in the sum of the SM backgrounds shown. For illustration, the distributions of the SUSY reference points are also shown as dashed lines.
The $E_{T}^{miss}$ post-fit distributions in the multi-jet background validation region VR-F (highMass). The stacked histograms show the contribution of each relevant SM process. The multi-jet shape is taken from VR-E in the ABCD method and the normalization is determined by the transfer factor $T$ and rescaled by a correction factor determined by the fit. The hatched bands represent the combined statistical and systematic uncertainties in the sum of the SM backgrounds shown. For illustration, the distributions of the SUSY reference points are also shown as dashed lines.
The $E_{T}^{miss}$ post-fit distributions in the multi-jet background validation region VR-F (highMass). The stacked histograms show the contribution of each relevant SM process. The multi-jet shape is taken from VR-E in the ABCD method and the normalization is determined by the transfer factor $T$ and rescaled by a correction factor determined by the fit. The hatched bands represent the combined statistical and systematic uncertainties in the sum of the SM backgrounds shown. For illustration, the distributions of the SUSY reference points are also shown as dashed lines.
The pre-fit $m_{T2}$ distribution in the $WCR$. The SM backgrounds other than multi-jet production are estimated from MC simulation. The multi-jet contribution is estimated from data using the OS--SS method. The hatched bands represent the combined statistical and systematic uncertainties of the total SM background. For illustration, the distributions of the SUSY reference points are also shown as dashed lines.
The pre-fit $m_{T2}$ distribution in the $WCR$. The SM backgrounds other than multi-jet production are estimated from MC simulation. The multi-jet contribution is estimated from data using the OS--SS method. The hatched bands represent the combined statistical and systematic uncertainties of the total SM background. For illustration, the distributions of the SUSY reference points are also shown as dashed lines.
The post-fit yields in the $WVR$, $TVRs$, $ZVRs$ and $VVVRs$. The SM backgrounds other than multi-jet production are estimated from MC simulation. The multi-jet contribution is negligible and is estimated from data using the ABCD method, using CRs obtained with the same technique used for the SRs. The hatched bands represent the combined statistical and systematic uncertainties of the total SM background. For illustration, the distributions of the SUSY reference points are also shown as dashed lines. The lower panels show the ratio of data to the SM background estimate.
The post-fit yields in the $WVR$, $TVRs$, $ZVRs$ and $VVVRs$. The SM backgrounds other than multi-jet production are estimated from MC simulation. The multi-jet contribution is negligible and is estimated from data using the ABCD method, using CRs obtained with the same technique used for the SRs. The hatched bands represent the combined statistical and systematic uncertainties of the total SM background. For illustration, the distributions of the SUSY reference points are also shown as dashed lines. The lower panels show the ratio of data to the SM background estimate.
A search for supersymmetric partners of gluons and quarks is presented, involving signatures with jets and either two isolated leptons (electrons or muons) with the same electric charge, or at least three isolated leptons. A data sample of proton-proton collisions at $\sqrt{s}$ = 13 TeV recorded with the ATLAS detector at the Large Hadron Collider between 2015 and 2018, corresponding to a total integrated luminosity of 139 fb$^{-1}$, is used for the search. No significant excess over the Standard Model expectation is observed. The results are interpreted in simplified supersymmetric models featuring both R-parity conservation and R-parity violation, raising the exclusion limits beyond those of previous ATLAS searches to 1600 GeV for gluino masses and 750 GeV for bottom and top squark masses in these scenarios.
Observed 95% CL exclusion contours in signal region Rpc2L0b on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g \to q \bar{q}^{'} \tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm \to W^\pm \tilde{\chi}_2^0$ and $ \tilde{\chi}_2^0 \to Z \tilde{\chi}_1^0$.
Observed 95% CL exclusion contours in signal region Rpc2L0b on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g \to q \bar{q}^{'} \tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm \to W^\pm \tilde{\chi}_2^0$ and $ \tilde{\chi}_2^0 \to Z \tilde{\chi}_1^0$.
Observed 95% CL exclusion contours in signal region Rpc2L0b on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g \to q \bar{q}^{'} \tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm \to W^\pm \tilde{\chi}_2^0$ and $ \tilde{\chi}_2^0 \to Z \tilde{\chi}_1^0$.
Observed 95% CL exclusion contours in signal region Rpc2L0b on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g \to q \bar{q}^{'} \tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm \to W^\pm \tilde{\chi}_2^0$ and $ \tilde{\chi}_2^0 \to Z \tilde{\chi}_1^0$.
Expected 95% CL exclusion contours in signal region Rpc2L0b on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Expected 95% CL exclusion contours in signal region Rpc2L0b on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Expected 95% CL exclusion contours in signal region Rpc2L0b on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Expected 95% CL exclusion contours in signal region Rpc2L0b on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Observed 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Observed 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Observed 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Observed 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Expected 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Expected 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Expected 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Expected 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Observed 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Observed 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Observed 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Observed 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Expected 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Expected 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Expected 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Expected 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L0b, in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde \chi_1^\pm)$ = 1200 GeV, $m(\tilde \chi_2^0)$ = 1000 GeV and $m(\tilde \chi_1^0)$ = 800 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L0b, in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde \chi_1^\pm)$ = 1200 GeV, $m(\tilde \chi_2^0)$ = 1000 GeV and $m(\tilde \chi_1^0)$ = 800 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L0b, in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde \chi_1^\pm)$ = 1200 GeV, $m(\tilde \chi_2^0)$ = 1000 GeV and $m(\tilde \chi_1^0)$ = 800 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L0b, in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde \chi_1^\pm)$ = 1200 GeV, $m(\tilde \chi_2^0)$ = 1000 GeV and $m(\tilde \chi_1^0)$ = 800 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L1b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 850 GeV, $m(\tilde \chi_1^\pm)$ = 500 GeV and $m(\tilde \chi_1^0)$ = 400 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L1b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 850 GeV, $m(\tilde \chi_1^\pm)$ = 500 GeV and $m(\tilde \chi_1^0)$ = 400 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L1b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 850 GeV, $m(\tilde \chi_1^\pm)$ = 500 GeV and $m(\tilde \chi_1^0)$ = 400 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L1b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 850 GeV, $m(\tilde \chi_1^\pm)$ = 500 GeV and $m(\tilde \chi_1^0)$ = 400 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L2b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 850 GeV, $m(\tilde \chi_1^\pm)$ = 500 GeV and $m(\tilde \chi_1^0)$ = 400 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L2b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 900 GeV, $m(\tilde \chi_1^\pm)$ = 150 GeV and $m(\tilde \chi_1^0)$ = 50 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L2b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 900 GeV, $m(\tilde \chi_1^\pm)$ = 150 GeV and $m(\tilde \chi_1^0)$ = 50 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L2b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 900 GeV, $m(\tilde \chi_1^\pm)$ = 150 GeV and $m(\tilde \chi_1^0)$ = 50 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc3LSS1b, in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate. The masses of the superpartners involved in the process are set to $m(\tilde{t}^{}_1)$ = 800 GeV, $m(\tilde \chi_2^0)$ = 625 GeV, $m(\tilde \chi_1^\pm)\approx m(\tilde \chi_1^0)$ = 525 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc3LSS1b, in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate. The masses of the superpartners involved in the process are set to $m(\tilde{t}^{}_1)$ = 800 GeV, $m(\tilde \chi_2^0)$ = 625 GeV, $m(\tilde \chi_1^\pm)\approx m(\tilde \chi_1^0)$ = 525 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc3LSS1b, in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate. The masses of the superpartners involved in the process are set to $m(\tilde{t}^{}_1)$ = 800 GeV, $m(\tilde \chi_2^0)$ = 625 GeV, $m(\tilde \chi_1^\pm)\approx m(\tilde \chi_1^0)$ = 525 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc3LSS1b, in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate. The masses of the superpartners involved in the process are set to $m(\tilde{t}^{}_1)$ = 800 GeV, $m(\tilde \chi_2^0)$ = 625 GeV, $m(\tilde \chi_1^\pm)\approx m(\tilde \chi_1^0)$ = 525 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpv2L, in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde{t}^{}_{1})$ = 800 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpv2L, in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde{t}^{}_{1})$ = 800 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpv2L, in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde{t}^{}_{1})$ = 800 GeV. Only statistical uncertainties are shown.
Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpv2L, in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde{t}^{}_{1})$ = 800 GeV. Only statistical uncertainties are shown.
Signal acceptance for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Signal acceptance for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Signal acceptance for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Signal acceptance for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Signal acceptance for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal acceptance for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal acceptance for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal acceptance for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal acceptance for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal acceptance for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal acceptance for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal acceptance for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal acceptance for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Signal acceptance for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Signal acceptance for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Signal acceptance for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Signal acceptance for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.
Signal acceptance for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.
Signal acceptance for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.
Signal acceptance for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.
Signal efficiency for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Signal efficiency for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Signal efficiency for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Signal efficiency for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Signal efficiency for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal efficiency for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal efficiency for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal efficiency for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal efficiency for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal efficiency for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal efficiency for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal efficiency for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Signal efficiency for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Signal efficiency for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Signal efficiency for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Signal efficiency for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Signal efficiency for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.
Signal efficiency for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.
Signal efficiency for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.
Signal efficiency for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.
Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.
Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.
Observed 95% CL upper limit on $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Observed 95% CL upper limit on $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Observed 95% CL upper limit on $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Observed 95% CL upper limit on $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Observed 95% CL upper limit on $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.
Observed 95% CL upper limit on $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.
Observed 95% CL upper limit on $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.
Observed 95% CL upper limit on $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.
Best observed 95% CL exclusion contours selected from Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Best observed 95% CL exclusion contours selected from Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Best observed 95% CL exclusion contours selected from Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
Best observed 95% CL exclusion contours selected from Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.
N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L0b from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L0b from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L0b from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L0b from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}} / m_{\mathrm{eff}}$ of observed data and expected background towards Rpc2L1b from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}} / m_{\mathrm{eff}}$ of observed data and expected background towards Rpc2L1b from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}} / m_{\mathrm{eff}}$ of observed data and expected background towards Rpc2L1b from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}} / m_{\mathrm{eff}}$ of observed data and expected background towards Rpc2L1b from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L2b from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L2b from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L2b from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L2b from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $m_{\mathrm{eff}}$ of observed data and expected background towards Rpv2L from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $m_{\mathrm{eff}}$ of observed data and expected background towards Rpv2L from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $m_{\mathrm{eff}}$ of observed data and expected background towards Rpv2L from publication's Figure 5 . The last bin is inclusive.
N-1 distributions for $m_{\mathrm{eff}}$ of observed data and expected background towards Rpv2L from publication's Figure 5 . The last bin is inclusive.
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 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.
This paper presents a measurement of the electroweak production of two jets in association with a $Z\gamma$ pair, with the $Z$ boson decaying into two neutrinos. It also presents a search for invisible or partially invisible decays of a Higgs boson with a mass of 125 GeV produced through vector-boson fusion with a photon in the final state. These results use data from LHC proton-proton collisions at $\sqrt{s}$ = 13 TeV collected with the ATLAS detector and corresponding to an integrated luminosity of 139 fb$^{-1}$. The event signature, shared by all benchmark processes considered for the measurements and searches, is characterized by a significant amount of unbalanced transverse momentum and a photon in the final state, in addition to a pair of forward jets. Electroweak $Z\gamma$ production in association with two jets is observed in this final state with a significance of 5.2 (5.1 expected) standard deviations. The measured fiducial cross-section for this process is 1.31$\pm$0.29 fb. An observed (expected) upper limit of 0.37 ($0.34^{+0.15}_{-0.10}$) at 95% confidence level is set on the branching ratio of a 125 GeV Higgs boson to invisible particles, assuming the Standard Model production cross-section. The signature is also interpreted in the context of decays of a Higgs boson into a photon and a dark photon. An observed (expected) 95% CL upper limit on the branching ratio for this decay is set at 0.018 ($0.017^{+0.007}_{-0.005}$), assuming the Standard Model production cross-section for a 125 GeV Higgs boson.
Post-fit results for all $m_\text{jj}$ SR and CR bins in the EW $Z \gamma + \text{jets}$ cross-section measurement with the $\mu_{Z \gamma_\text{EW}}$ signal normalization floating. The post-fit uncertainties include statistical, experimental, and theory contributions.
Post-fit results for all DNN SR and CR bins in the search for $H \to \text{inv.}$ with the $\mathcal{B}_\text{inv}$ signal normalization set to zero. For the $Z_\text{Rev.Cen.}^\gamma$ CR, the third bin contains all events with DNN output score values of 0.6-1.0. The $H \to \text{inv.}$ signal is scaled to a $\mathcal{B}_\text{inv}$ of 37%. The post-fit uncertainties include statistical, experimental, and theoretical contributions.
Post-fit results for the ten [$m_\text{jj}$, $m_\text{T}$] bins constituting the SR and CRs defined for the dark photon search with the $\mathcal{B}(H \to \gamma \gamma_\text{d})$ signal normalization set to zero. A $H \to \gamma \gamma_\text{d}$ signal is shown for two different mass hypotheses (125 GeV, 500 GeV) and scaled to a branching ratio of 2% and 1%, respectively. The post-fit uncertainties include statistical, experimental, and theoretical contributions.
Post-fit $m_\text{T}(\gamma, E_\text{T}^\text{miss})$ distribution in the inclusive signal region for the dark-photon search with the 125 GeV mass $\mathcal{B}(H \to \gamma \gamma_\text{d})$ signal normalization set to zero. A $H \to \gamma \gamma_\text{d}$ decay signal is shown for two different mass hypotheses, 125 GeV and 500 GeV, and scaled to a $\mathcal{B}(H \to \gamma \gamma_\text{d})$ of 2% and 1%, respectively. Events with $m_\text{T}(\gamma, E_\text{T}^\text{miss})$ larger than the rightmost bin boundary are added to that bin.
The 95% CL upper limit on the Higgs boson production cross-section times branching ratio to $\gamma \gamma_\text{d}$ is shown for different VBF-produced scalar-mediator-mass hypotheses in the NWA. The theoretically predicted cross-section of a Higgs boson produced via VBF and with the $\mathcal{B}(H \to \gamma \gamma_\text{d}) =$ 5% is superimposed on the $\pm 1\sigma$ and $\pm 2\sigma$ NNLO QCD + NLO EW uncertainty band of the expected production cross-section limit.
Post-fit $m_\text{jj}$ distribution in the inclusive signal region. The Higgs boson invisible decay signal is scaled to a $\mathcal{B}_\text{inv}$ of 37%. Events with $m_\text{jj}$ larger than the rightmost bin boundary are added to that bin.
Post-fit $m_\text{jj}$ distribution in the one-lepton control region $W_{\ell \nu}^\gamma$ CR. Events with $m_\text{jj}$ larger than the rightmost bin boundary are added to that bin.
Post-fit $m_\text{T}$ distribution in the one lepton control region. Events with $m_\text{T}$ larger than the rightmost bin boundary are added to that bin.
Post-fit photon centrality distribution in the zero lepton signal plus control region with the $\mathcal{B}_\text{inv}$ signal normalization set to zero in the fit.
Post-fit photon $E_\text{T}$ distribution in the zero lepton signal region with the $\mathcal{B}_\text{inv}$ signal normalization set to zero in the fit.
Post-fit photon centrality distribution in the zero lepton signal plus control region resulting from the fit to the $m_\text{jj}$ distribution for EW $Z \gamma + \text{jets}$. The post-fit uncertainties include statistical, experimental, and theory contributions.
Post-fit photon $E_\text{T}$ distribution in the zero lepton signal region resulting from the fit to the $m_\text{jj}$ distribution for EW $Z \gamma + \text{jets}$. The post-fit uncertainties include statistical, experimental, and theory contributions.
Post-fit DNN output score distribution in the one lepton control region.
Yields for the EW $Z \gamma + \text{jets}$ process are shown after each selection along with relative and absolute signal acceptance efficiencies.
Yields for the 125 GeV Higgs boson with $\mathcal{B}_\text{inv.} =$ 1 signal produced by the vector boson fusion process in association with a final state photon are shown after each selection along with relative and absolute signal acceptance efficiencies.
Yields for the 125 GeV Higgs boson with $\mathcal{B}(H \to \gamma \gamma_\text{d}) =$ 1 signal produced by the vector boson fusion process are shown after each selection along with relative and absolute signal acceptance efficiencies.
This paper presents a measurement of fiducial and differential cross-sections for $W^{+}W^{-}$ production in proton-proton collisions at $\sqrt{s}=13$ TeV with the ATLAS experiment at the Large Hadron Collider using a dataset corresponding to an integrated luminosity of 139 fb$^{-1}$. Events with exactly one electron, one muon and no hadronic jets are studied. The fiducial region in which the measurements are performed is inspired by searches for the electroweak production of supersymmetric charginos decaying to two-lepton final states. The selected events have moderate values of missing transverse momentum and the `stransverse mass' variable $m_{\textrm{T2}}$, which is widely used in searches for supersymmetry at the LHC. The ranges of these variables are chosen so that the acceptance is enhanced for direct $W^{+}W^{-}$ production and suppressed for production via top quarks, which is treated as a background. The fiducial cross-section and particle-level differential cross-sections for six variables are measured and compared with two theoretical SM predictions from perturbative QCD calculations.
Signal region detector-level distribution for the observable $|y_{e\mu}|$.
Signal region detector-level distribution for the observable $|\Delta \phi(e \mu)|$.
Signal region detector-level distribution for the observable $ \cos\theta^{\ast}$.
Signal region detector-level distribution for the observable $p_{\mathrm{T}}^{\mathrm{lead}\, \ell}$.
Signal region detector-level distribution for the observable $m_{e\mu}$.
Signal region detector-level distribution for the observable $p_{\mathrm{T}}^{e\mu}$.
Measured fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $|y_{e\mu}|$
Relative systematic uncertainties for the fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $|y_{e\mu}|$
Measured fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $|\Delta \phi(e \mu)|$
Relative systematic uncertainties for the fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $|\Delta \phi(e \mu)|$
Measured fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $ \cos\theta^{\ast}$
Relative systematic uncertainties for the fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $ \cos\theta^{\ast}$
Measured fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $p_{\mathrm{T}}^{\mathrm{lead}\, \ell}$
Relative systematic uncertainties for the fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $p_{\mathrm{T}}^{\mathrm{lead}\, \ell}$
Measured fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $m_{e\mu}$
Relative systematic uncertainties for the fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $m_{e\mu}$
Measured fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $p_{\mathrm{T}}^{e\mu}$
Relative systematic uncertainties for the fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $p_{\mathrm{T}}^{e\mu}$
The statistical correlation coefficients (in percentage) between bins for the measured fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $|y_{e\mu}|$
The total correlation coefficients (in percentage) between bins for the measured fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $|y_{e\mu}|$
The statistical correlation coefficients (in percentage) between bins for the measured fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $|\Delta \phi(e \mu)|$
The total correlation coefficients (in percentage) between bins for the measured fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $|\Delta \phi(e \mu)|$
The statistical correlation coefficients (in percentage) between bins for the measured fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $ \cos\theta^{\ast}$
The total correlation coefficients (in percentage) between bins for the measured fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $ \cos\theta^{\ast}$
The statistical correlation coefficients (in percentage) between bins for the measured fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $p_{\mathrm{T}}^{\mathrm{lead}\, \ell}$
The total correlation coefficients (in percentage) between bins for the measured fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $p_{\mathrm{T}}^{\mathrm{lead}\, \ell}$
The statistical correlation coefficients (in percentage) between bins for the measured fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $m_{e\mu}$
The total correlation coefficients (in percentage) between bins for the measured fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $m_{e\mu}$
The statistical correlation coefficients (in percentage) between bins for the measured fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $p_{\mathrm{T}}^{e\mu}$
The total correlation coefficients (in percentage) between bins for the measured fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $p_{\mathrm{T}}^{e\mu}$
A search for a heavy CP-odd Higgs boson, $A$, decaying into a $Z$ boson and a heavy CP-even Higgs boson, $H$, is presented. It uses the full LHC Run 2 dataset of $pp$ collisions at $\sqrt{s}=13$ TeV collected with the ATLAS detector, corresponding to an integrated luminosity of $140$ fb$^{-1}$. The search for $A\to ZH$ is performed in the $\ell^+\ell^- t\bar{t}$ and $\nu\bar{\nu}b\bar{b}$ final states and surpasses the reach of previous searches in different final states in the region with $m_H>350$ GeV and $m_A>800$ GeV. No significant deviation from the Standard Model expectation is found. Upper limits are placed on the production cross-section times the decay branching ratios. Limits with less model dependence are also presented as functions of the reconstructed $m(t\bar{t})$ and $m(b\bar{b})$ distributions in the $\ell^+\ell^- t\bar{t}$ and $\nu\bar{\nu}b\bar{b}$ channels, respectively. In addition, the results are interpreted in the context of two-Higgs-doublet models.
The distribution of the fit discriminant m(lltt)-m(tt) in the signal region of the lltt channel for the mH=450 GeV hypothesis. <br><br><a href="?table=overview">return to overview</a>
The distribution of the fit discriminant mTVH in the 2 b-tag signal region of the vvbb channel for the mH=300 GeV hypothesis. <br><br><a href="?table=overview">return to overview</a>
The distribution of the fit discriminant mTVH in the 3+ b-tag signal region of the vvbb channel for the mH=300 GeV hypothesis. <br><br><a href="?table=overview">return to overview</a>
The m(tt) distribution in the Lhi3_Zin region of the lltt channel. <br><br><a href="?table=overview">return to overview</a>
The m(bb) distribution in the 2 b-tag 0L region of the vvbb channel. <br><br><a href="?table=overview">return to overview</a>
The m(bb) distribution in the 3+ b-tag 0L region of the vvbb channel. <br><br><a href="?table=overview">return to overview</a>
Expected and observed upper limits at 95% CL on sigma(gg->A)*B(A->ZH)*B(H->tt) in the (mA,mH) plane. The limits are shown for tanbeta=1. The tanbeta value is relevant only for the choice of the A boson width. <br><a href="?table=overview">return to overview</a>
Expected and observed upper limits at 95% CL on sigma(bbA)*B(A->ZH)*B(H->tt)$ in the (mA,mH) plane. The limits are shown for tanbeta=10. The tanbeta value is relevant only for the choice of the A boson width. <br><br><a href="?table=overview">return to overview</a>
Expected and observed upper limits at 95% CL on sigma(gg->A)*B(A->ZH)*B(H->bb) in the (mA,mH) plane. The limits are shown for tanbeta=1. The tanbeta value is relevant only for the choice of the A boson width. <br><br><a href="?table=overview">return to overview</a>
Expected and observed upper limits at 95% CL on sigma(bbA)*B(A->ZH)*B(H->bb) in the (mA,mH) plane. The limits are shown for tanbeta=10. The tanbeta value is relevant only for the choice of the A boson width. <br><br><a href="?table=overview">return to overview</a>
Expected and observed upper limits at 95% CL on sigma(gg->A)*B(A->ZH)*B(H->tt) in he (mA,mH) plane. The limits are shown for tanbeta=0.5. The tanbeta value is relevant only for the choice of the A boson width. <br><a href="?table=overview">return to overview</a>
Expected and observed upper limits at 95% CL on sigma(gg->A)*B(A->ZH)*B(H->tt) in the (mA,mH) plane. The limits are shown for tanbeta=5. The tanbeta value is relevant only for the choice of the A boson width. <br><a href="?table=overview">return to overview</a>
Expected and observed upper limits at 95% CL on sigma(bbA)*B(A->ZH)*B(H->tt) in the (mA,mH) plane. The limits are shown for tanbeta=1. The tanbeta value is relevant only for the choice of the A boson width. <br><br><a href="?table=overview">return to overview</a>
Expected and observed upper limits at 95% CL on sigma(bbA)*B(A->ZH)*B(H->tt)$ in the (mA,mH) plane. The limits are shown for tanbeta=5. The tanbeta value is relevant only for the choice of the A boson width. <br><br><a href="?table=overview">return to overview</a>
Expected and observed upper limits at 95% CL on sigma(gg->A)*B(A->ZH)*B(H->bb) in the (mA,mH) plane. The limits are shown for tanbeta=0.5. The tanbeta value is relevant only for the choice of the A boson width. <br><br><a href="?table=overview">return to overview</a>
Expected and observed upper limits at 95% CL on sigma(gg->A)*B(A->ZH)*B(H->bb) in the (mA,mH) plane. The limits are shown for tanbeta=5. The tanbeta value is relevant only for the choice of the A boson width. <br><br><a href="?table=overview">return to overview</a>
Expected and observed upper limits at 95% CL on sigma(bbA)*B(A->ZH)*B(H->bb) in the (mA,mH) plane. The limits are shown for tanbeta=1. The tanbeta value is relevant only for the choice of the A boson width. <br><br><a href="?table=overview">return to overview</a>
Expected and observed upper limits at 95% CL on sigma(bbA)*B(A->ZH)*B(H->bb) in the (mA,mH) plane. The limits are shown for tanbeta=5. The tanbeta value is relevant only for the choice of the A boson width. <br><br><a href="?table=overview">return to overview</a>
Expected and observed upper limits at 95% CL on sigma(bbA)*B(A->ZH)*B(H->bb) in the (mA,mH) plane. The limits are shown for tanbeta=20. The tanbeta value is relevant only for the choice of the A boson width. <br><br><a href="?table=overview">return to overview</a>
The distribution of the fit discriminant m(lltt)-m(tt) in the signal region of the lltt channel for the mH=450 GeV hypothesis with the bbA signal shown for comparison. <br><br><a href="?table=overview">return to overview</a>
The m(tt) distribution in the L3hi_Zin region of the lltt channel for the mH=450 GeV hypothesis with the bbA signal shown for comparison. <br><br><a href="?table=overview">return to overview</a>
The distribution of the fit discriminant m(lltt)-m(tt) in the signal region of the lltt channel for the mH=350 GeV hypothesis. <br><br><a href="?table=overview">return to overview</a>
The distribution of the fit discriminant m(lltt)-m(tt) in the signal region of the lltt channel for the mH=400 GeV hypothesis. <br><br><a href="?table=overview">return to overview</a>
The distribution of the fit discriminant m(lltt)-m(tt) in the signal region of the lltt channel for the mH=500 GeV hypothesis. <br><br><a href="?table=overview">return to overview</a>
The distribution of the fit discriminant m(lltt)-m(tt) in the signal region of the lltt channel for the mH=550 GeV hypothesis. <br><br><a href="?table=overview">return to overview</a>
The distribution of the fit discriminant m(lltt)-m(tt) in the signal region of the lltt channel for the mH=600 GeV hypothesis. <br><br><a href="?table=overview">return to overview</a>
The distribution of the fit discriminant m(lltt)-m(tt) in the signal region of the lltt channel for the mH=700 GeV hypothesis. <br><br><a href="?table=overview">return to overview</a>
The distribution of the fit discriminant m(lltt)-m(tt) in the signal region of the lltt channel for the mH=800 GeV hypothesis. <br><br><a href="?table=overview">return to overview</a>
The distribution of the fit discriminant mTVH in the 2 b-tag signal region of the vvbb channel for the mH=130 GeV hypothesis. <br><br><a href="?table=overview">return to overview</a>
The distribution of the fit discriminant mTVH in the 2 b-tag signal region of the vvbb channel for the mH=150 GeV hypothesis. <br><br><a href="?table=overview">return to overview</a>
The distribution of the fit discriminant mTVH in the 2 b-tag signal region of the vvbb channel for the mH=200 GeV hypothesis. <br><br><a href="?table=overview">return to overview</a>
The distribution of the fit discriminant mTVH in the 2 b-tag signal region of the vvbb channel for the mH=250 GeV hypothesis. <br><br><a href="?table=overview">return to overview</a>
The distribution of the fit discriminant mTVH in the 2 b-tag signal region of the vvbb channel for the mH=350 GeV hypothesis. <br><br><a href="?table=overview">return to overview</a>
The distribution of the fit discriminant mTVH in the 2 b-tag signal region of the vvbb channel for the mH=400 GeV hypothesis. <br><br><a href="?table=overview">return to overview</a>
The distribution of the fit discriminant mTVH in the 2 b-tag signal region of the vvbb channel for the mH=450 GeV hypothesis. <br><br><a href="?table=overview">return to overview</a>
The distribution of the fit discriminant mTVH in the 2 b-tag signal region of the vvbb channel for the mH=500 GeV hypothesis. <br><br><a href="?table=overview">return to overview</a>
The distribution of the fit discriminant mTVH in the 2 b-tag signal region of the vvbb channel for the mH=600 GeV hypothesis. <br><br><a href="?table=overview">return to overview</a>
The distribution of the fit discriminant mTVH in the 2 b-tag signal region of the vvbb channel for the mH=700 GeV hypothesis. <br><br><a href="?table=overview">return to overview</a>
The distribution of the fit discriminant mTVH in the 2 b-tag signal region of the vvbb channel for the mH=800 GeV hypothesis. <br><br><a href="?table=overview">return to overview</a>
The distribution of the fit discriminant mTVH i+ the 3p b-tag signal region of the vvbb channel for the mH=130 GeV hypothesis. <br><br><a href="?table=overview">return to overview</a>
The distribution of the fit discriminant mTVH in the 3+ b-tag signal region of the vvbb channel for the mH=150 GeV hypothesis. <br><br><a href="?table=overview">return to overview</a>
The distribution of the fit discriminant mTVH in the 3+ b-tag signal region of the vvbb channel for the mH=200 GeV hypothesis. <br><br><a href="?table=overview">return to overview</a>
The distribution of the fit discriminant mTVH in the 3+ b-tag signal region of the vvbb channel for the mH=250 GeV hypothesis. <br><br><a href="?table=overview">return to overview</a>
The distribution of the fit discriminant mTVH in the 3+ b-tag signal region of the vvbb channel for the mH=350 GeV hypothesis. <br><br><a href="?table=overview">return to overview</a>
The distribution of the fit discriminant mTVH in the 3+ b-tag signal region of the vvbb channel for the mH=400 GeV hypothesis. <br><br><a href="?table=overview">return to overview</a>
The distribution of the fit discriminant mTVH in the 3+ b-tag signal region of the vvbb channel for the mH=450 GeV hypothesis. <br><br><a href="?table=overview">return to overview</a>
The distribution of the fit discriminant mTVH in the 3+ b-tag signal region of the vvbb channel for the mH=500 GeV hypothesis. <br><br><a href="?table=overview">return to overview</a>
The distribution of the fit discriminant mTVH in the 3+ b-tag signal region of the vvbb channel for the mH=600 GeV hypothesis. <br><br><a href="?table=overview">return to overview</a>
The distribution of the fit discriminant mTVH in the 3+ b-tag signal region of the vvbb channel for the mH=700 GeV hypothesis. <br><br><a href="?table=overview">return to overview</a>
The distribution of the fit discriminant mTVH in the 3+ b-tag signal region of the vvbb channel for the mH=800 GeV hypothesis. <br><br><a href="?table=overview">return to overview</a>
The distribution of the fit discriminant mTVH in the 2 b-tag 2L region of the vvbb channel. <br><br><a href="?table=overview">return to overview</a>
The distribution of the fit discriminant mTVH in the 2 b-tag em region of the vvbb channel. <br><br><a href="?table=overview">return to overview</a>
The distribution of the fit discriminant mTVH in the 3+ b-tag 2L region of the vvbb channel. <br><br><a href="?table=overview">return to overview</a>
The distribution of the fit discriminant mTVH in the 3+ b-tag em region of the vvbb channel. <br><br><a href="?table=overview">return to overview</a>
Local significance for lltt ggF signals for tanbeta=1. <br><br><a href="?table=overview">return to overview</a>
Local significance for lltt bbA signals for tanbeta=20. <br><br><a href="?table=overview">return to overview</a>
Local significance for vvbb ggF signals for tanbeta=1. <br><br><a href="?table=overview">return to overview</a>
Local significance for vvbb bbA signals for tanbeta=20. <br><br><a href="?table=overview">return to overview</a>
Signal acceptance times efficiency for lltt ggF signals. <br><br><a href="?table=overview">return to overview</a>
Signal acceptance times efficiency for lltt bbA signals. <br><br><a href="?table=overview">return to overview</a>
Signal acceptance times efficiency for vvbb ggF signals. <br><br><a href="?table=overview">return to overview</a>
Signal acceptance times efficiency for vvbb bbA signals. <br><br><a href="?table=overview">return to overview</a>
The pT distribution of the third lepton in the L3hi_Zin region of the lltt channel. <br><br><a href="?table=overview">return to overview</a>
The eta distribution of the H boson candidate in the rest frame of the A boson candidate in the L3hi_Zin region of the lltt channel. <br><br><a href="?table=overview">return to overview</a>
The ETmiss distribution in the 2 b-tag 0L region of the vvbb channel. <br><br><a href="?table=overview">return to overview</a>
The m_top_near distribution in the 2 b-tag 0L region of the vvbb channel. <br><br><a href="?table=overview">return to overview</a>
The ETmiss distribution in the 3+ b-tag 0L region of the vvbb channel. <br><br><a href="?table=overview">return to overview</a>
The m_top_near distribution in the 3+ b-tag 0L region of the vvbb channel. <br><br><a href="?table=overview">return to overview</a>
We report the double helicity asymmetry, $A_{LL}^{J/\psi}$, in inclusive $J/\psi$ production at forward rapidity as a function of transverse momentum $p_T$ and rapidity $|y|$. The data analyzed were taken during $\sqrt{s}=510$ GeV longitudinally polarized $p
$A_{LL}^{J/\psi}$ as a function of $p_T$ or $|y|$. $N_{J/\psi}^{2\sigma}$ is the $J/\psi$ counting within its $2\sigma$ mass window. The column of Type A systematic uncertainties are a statistically weighted quadratic combination of the background fraction and run grouping uncertainties. $\Delta A_{LL}$ (Rel. Lumi.) is the global systematic uncertainty from relative luminosity measurements. $\Delta A_{LL}$ (Polarization) is the systematic uncertainty from the beam polarization measurement: a zero indicates an uncertainty $< 0.001$.
This paper describes a search for beyond the Standard Model decays of the Higgs boson into a pair of new spin-0 particles subsequently decaying into $b$-quark pairs, $H \rightarrow aa \rightarrow (b\bar{b})(b\bar{b})$, using proton-proton collision data collected by the ATLAS detector at the Large Hadron Collider at center-of-mass energy $\sqrt{s}=13$ TeV. This search focuses on the regime where the decay products are collimated and in the range $15 \leq m_a \leq 30$ GeV and is complementary to a previous search in the same final state targeting the regime where the decay products are well separated and in the range $20 \leq m_a \leq 60$ GeV. A novel strategy for the identification of the $a \rightarrow b\bar{b}$ decays is deployed to enhance the efficiency for topologies with small separation angles. The search is performed with 36 fb$^{-1}$ of integrated luminosity collected in 2015 and 2016 and sets upper limits on the production cross-section of $H \rightarrow aa \rightarrow (b\bar{b})(b\bar{b})$, where the Higgs boson is produced in association with a $Z$ boson.
Summary of the 95% CL upper limits on $\sigma_{ZH} BR(H\rightarrow aa \rightarrow (b\bar{b})(b\bar{b}))$. Both observed and expected limits are listed. In the case of the expected limits, one- and two-standard-deviation uncertainty bands are also listed.
Summary of the 95% CL upper limits on $\sigma_{ZH} BR(H\rightarrow aa \rightarrow (b\bar{b})(b\bar{b}))$. Both observed and expected limits are listed. In the case of the expected limits, one- and two-standard-deviation uncertainty bands are also listed.
Summary of the observed 95% CL upper limits on $\sigma_{ZH} BR(H\rightarrow aa \rightarrow (b\bar{b})(b\bar{b}))$ for the resolved analysis.
Summary of the 95% C.L. upper limits on $\sigma_{ZH} BR(H\rightarrow aa \rightarrow (b\bar{b})(b\bar{b}))$ for the dilepton channel in the resolved analysis. The observed limits are shown, together with the expected limits (dotted black lines). In the case of the expected limits, one- and two-standard-deviation uncertainty bands are also displayed. The data was published in JHEP 10 (2018) 031.
Efficiency and acceptance for simulated $ZH(\rightarrow aa\rightarrow (b\bar{b})(b\bar{b}))$ samples in two signal regions (SR) of the analysis, one with two $a\to b\bar{b}$ candidates in the High Purity Category (HPC), and the other with one $a\to b\bar{b}$ candidate in the High Purity Category (HPC) and one in the Low Purity Category (LPC).
Efficiency and acceptance for simulated $ZH(\rightarrow aa\rightarrow (b\bar{b})(b\bar{b}))$ samples in two signal regions (SR) of the analysis, one with two $a\to b\bar{b}$ candidates in the High Purity Category (HPC), and the other with one $a\to b\bar{b}$ candidate in the High Purity Category (HPC) and one in the Low Purity Category (LPC).
Event yields for a simulated $ZH(\rightarrow aa\rightarrow (b\bar{b})(b\bar{b}))$ sample with $m_a = 17.5\,\text{GeV}$. The signal sample is produced with cross section equals to the standard model $pp\to ZH$, i.e. $0.88\,\text{pb}$. Cut 0 corresponds to the initial number of events. Cut 1 requires the single lepton trigger. Cut 2 requires 2 identified leptons. Cut 3 requires the Z-boson mass window. Cut 4 requires 2 reconstructed $a\to b\bar{b}$ candidates. Cut 5a requires 2 identified $a\to b\bar{b}$ candidates in the 1HPC1LPC region. Cut 6a requires the 2 $a\to b\bar{b}$ candidates in the 1HPC1LPC region to be inside the Higgs mass window. Cut 5b requires 2 identified $a\to b\bar{b}$ candidates in the 2HPC region. Cut 6b requires the 2 $a\to b\bar{b}$ candidates in the 2HPC region to be inside the Higgs mass window.
Event yields for a simulated $ZH(\rightarrow aa\rightarrow (b\bar{b})(b\bar{b}))$ sample with $m_a = 17.5\,\text{GeV}$. The signal sample is produced with cross section equals to the standard model $pp\to ZH$, i.e. $0.88\,\text{pb}$. Cut 0 corresponds to the initial number of events. Cut 1 requires the single lepton trigger. Cut 2 requires 2 identified leptons. Cut 3 requires the Z-boson mass window. Cut 4 requires 2 reconstructed $a\to b\bar{b}$ candidates. Cut 5a requires 2 identified $a\to b\bar{b}$ candidates in the 1HPC1LPC region. Cut 6a requires the 2 $a\to b\bar{b}$ candidates in the 1HPC1LPC region to be inside the Higgs mass window. Cut 5b requires 2 identified $a\to b\bar{b}$ candidates in the 2HPC region. Cut 6b requires the 2 $a\to b\bar{b}$ candidates in the 2HPC region to be inside the Higgs mass window.
Background yield table for Z+jets, $t\bar{t}$, and rare sources. Observed data yield. Signal $ZH(\rightarrow aa\rightarrow (b\bar{b})(b\bar{b}))$ yield with $m_a = 20\,\text{GeV}$. The signal sample is produced with cross section equals to the standard model $pp\to ZH$, i.e. $0.88\,\text{pb}$, with a branching ratio set to 1 for the $H \rightarrow aa$ decay, whereas the ATLAS figure attached to this entry instead uses the upper-limit branching ratio (smaller than 1). The table includes the yields in two signal regions with leptons consistent with an on-shell Z-boson decay, one with 2 $a\to b\bar{b}$ candidates in the 2HPC region and one with 2 $a\to b\bar{b}$ candidates in the 1HPC1LPC region. The table also includes the yields in four control regions, one with leptons consistent with an on-shell Z-boson decay and 2 $a\to b\bar{b}$ candidates in the Low Purity Category (LPC), and three others where the leptons are not consistent an on-shell Z-boson decay.
Background yield table for Z+jets, $t\bar{t}$, and rare sources. Observed data yield. Signal $ZH(\rightarrow aa\rightarrow (b\bar{b})(b\bar{b}))$ yield with $m_a = 20\,\text{GeV}$. The signal sample is produced with cross section equals to the standard model $pp\to ZH$, i.e. $0.88\,\text{pb}$. The table includes the yields in two signal regions with leptons consistent with an on-shell Z-boson decay, one with 2 $a\to b\bar{b}$ candidates in the 2HPC region and one with 2 $a\to b\bar{b}$ candidates in the 1HPC1LPC region. The table also includes the yields in four control regions, one with leptons consistent with an on-shell Z-boson decay and 2 $a\to b\bar{b}$ candidates in the Low Purity Category (LPC), and three others where the leptons are not consistent an on-shell Z-boson decay.
When you search on a word, e.g. 'collisions', we will automatically search across everything we store about a record. But, sometimes you may wish to be more specific. Here we show you how.
Guidance and examples on the query string syntax can be found in the Elasticsearch documentation.
About HEPData Submitting to HEPData HEPData File Formats HEPData Coordinators HEPData Terms of Use HEPData Cookie Policy
Status Email Forum Twitter GitHub
Copyright ~1975-Present, HEPData | Powered by Invenio, funded by STFC, hosted and originally developed at CERN, supported and further developed at IPPP Durham.