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Combined ATLAS and CMS measurements of the Higgs boson production and decay rates, as well as constraints on its couplings to vector bosons and fermions, are presented. The combination is based on the analysis of five production processes, namely gluon fusion, vector boson fusion, and associated production with a $W$ or a $Z$ boson or a pair of top quarks, and of the six decay modes $H \to ZZ, WW$, $\gamma\gamma, \tau\tau, bb$, and $\mu\mu$. All results are reported assuming a value of 125.09 GeV for the Higgs boson mass, the result of the combined measurement by the ATLAS and CMS experiments. The analysis uses the CERN LHC proton--proton collision data recorded by the ATLAS and CMS experiments in 2011 and 2012, corresponding to integrated luminosities per experiment of approximately 5 fb$^{-1}$ at $\sqrt{s}=7$ TeV and 20 fb$^{-1}$ at $\sqrt{s} = 8$ TeV. The Higgs boson production and decay rates measured by the two experiments are combined within the context of three generic parameterisations: two based on cross sections and branching fractions, and one on ratios of coupling modifiers. Several interpretations of the measurements with more model-dependent parameterisations are also given. The combined signal yield relative to the Standard Model prediction is measured to be 1.09 $\pm$ 0.11. The combined measurements lead to observed significances for the vector boson fusion production process and for the $H \to \tau\tau$ decay of $5.4$ and $5.5$ standard deviations, respectively. The data are consistent with the Standard Model predictions for all parameterisations considered.
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-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-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-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.
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 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 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 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 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 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 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 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 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 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 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.
Expected 95% CL exclusion contours for the gluino one-step x = 1/2 model. space.
Observed 95% CL exclusion contours for the gluino one-step variable-x
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.
Observed 95% CL exclusion contours for the squark one-step x = 1/2 model.
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 squark one-step variable-x
Expected 95% CL exclusion contours for the squark one-step variable-x
Expected 95% CL exclusion contours for the squark one-flavour schemes in 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 gluino one-step variable-x
Upper limits on the signal cross section for simplified model squark one-step x = 1/2
Upper limits on the signal cross section for simplified model squark one-step variable-x
Upper limits on the signal cross section for simplified model squark one-step x=1/2 in one-flavour schemes
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 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 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 TR4J 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 WR4J 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 2J b-tag 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 2J 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 4J b-tag 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 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 6J b-tag validation region. Uncertainties include statistical and systematic uncertainties.
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.
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.
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.
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.
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.
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 SR2J b-Tag bin2 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 SR2J b-Veto bin1 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 SR2J b-Veto bin3 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 SR2J discovery low 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 SR4Jhx b-Tag bin1 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 SR4Jhx b-Tag bin3 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 SR4Jhx b-Veto bin2 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 SR4Jlx 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 SR4Jlx 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 SR4Jlx 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 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 SR4Jlx 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 SR4Jlx 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 SR4Jlx 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 SR6J b-Tag bin1 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 b-Tag bin3 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 SR6J 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 SR6J 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 discovery high 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 SR2J b-Tag bin1 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 SR2J b-Tag bin3 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 SR2J b-Veto bin2 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 SR2J discovery high 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 SR4Jhx discovery 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 SR4Jhx b-Tag bin2 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 SR4Jhx b-Veto bin1 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 SR4Jhx b-Veto bin3 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 SR4Jlx 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 SR4Jlx 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 SR4Jlx 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 SR6J b-Tag bin1 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 b-Tag bin3 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 SR6J 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 SR6J 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 discovery high 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 SR2J b-Tag bin1 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 SR2J b-Tag bin3 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 SR2J b-Veto bin2 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 SR2J discovery high 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 SR4Jhx discovery 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 SR4Jhx b-Tag bin2 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 SR4Jhx b-Veto bin1 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 SR4Jhx b-Veto bin3 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 SR4Jlx 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 SR4Jlx 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 SR4Jlx 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 SR6J b-Tag bin1 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 b-Tag bin3 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 SR6J 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 SR6J 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 discovery high 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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-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 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 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 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-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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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-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 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 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 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-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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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-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 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 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 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-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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 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-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 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 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 pair production of scalar leptoquarks, each decaying into either an electron or a muon and a top quark, is presented. This is the first leptoquark search using ATLAS data to investigate top-philic cross-generational couplings that could provide explanations for recently observed anomalies in $B$ meson decays. This analysis targets high leptoquark masses which cause the decay products of each resultant top quark to be contained within a single high-$p_{\mathrm{T}}$ large-radius jet. The full Run 2 dataset is exploited, consisting of 139 fb$^{-1}$ of data collected from proton-proton collisions at $\sqrt{s}=13$ TeV from 2015 to 2018 with the ATLAS detector at the CERN Large Hadron Collider. In the absence of any significant deviation from the background expectation, lower limits on the leptoquark masses are set at 1480 GeV and 1470 GeV for the electron and muon channel, respectively.
Expected and observed upper limits at the 95% CL on the leptoquark pair production cross section as a function of leptoquark mass under the assumption of $\mathcal{B}$(LQ->$te$)=1.
Expected and observed upper limits at the 95% CL on the leptoquark pair production cross section as a function of leptoquark mass under the assumption of $\mathcal{B}$(LQ->$t\mu$)=1.
Expected and observed 95% CL lower limits on the leptoquark mass as a function of the branching ratio $\mathcal{B}$(LQ->$te$).
Expected and observed 95% CL lower limits on the leptoquark mass as a function of the branching ratio $\mathcal{B}$(LQ->$t\mu$).
The ATLAS experiment at the Large Hadron Collider reports a search for charged-lepton-flavour violation in decays of $Z$ bosons into a τ lepton and an electron or muon of opposite charge.
The best-fit expected and observed distributions of the combined NN output in the CRZ$\tau\tau$ for the $\mu\tau$ channel for events with 1-prong $\tau_\text{had-vis}$ candidates. The last bin in each plot includes overflow events.
The best-fit expected and observed distributions of the combined NN output in the CRZ$\tau\tau$ for the $\mu\tau$ channel for events with 3-prong $\tau_\text{had-vis}$ candidates. The last bin in each plot includes overflow events.
The best-fit expected and observed distributions of the combined NN output in the VRSS for the $e\tau$ channel for events with 1-prong $\tau_\text{had-vis}$ candidates. The last bin in each plot includes overflow events.
The best-fit expected and observed distributions of the combined NN output in the VRSS for the $e\tau$ channel for events with 3-prong $\tau_\text{had-vis}$ candidates. The last bin in each plot includes overflow events.
The best-fit expected and observed distributions of the combined NN output in the SR for the $e\tau$ channel for events with 1-prong $\tau_\text{had-vis}$ candidates. The last bin in each plot includes overflow events.
The best-fit expected and observed distributions of the combined NN output in the SR for the $e\tau$ channel for events with 3-prong $\tau_\text{had-vis}$ candidates. The last bin in each plot includes overflow events.
The best-fit expected and observed distributions of the combined NN output in the SR for the $\mu\tau$ channel for events with 1-prong $\tau_\text{had-vis}$ candidates. The last bin in each plot includes overflow events.
The best-fit expected and observed distributions of the combined NN output in the SR for the $\mu\tau$ channel for events with 3-prong $\tau_\text{had-vis}$ candidates. The last bin in each plot includes overflow events.
Observed and expected upper limits on $\mathcal{B}(Z\rightarrow\ell\tau)$ at 95% confidence level.
This paper presents a search for dark matter in the context of a two-Higgs-doublet model together with an additional pseudoscalar mediator, $a$, which decays into the dark-matter particles. Processes where the pseudoscalar mediator is produced in association with a single top quark in the 2HDM+$a$ model are explored for the first time at the LHC. Several final states which include either one or two charged leptons (electrons or muons) and a significant amount of missing transverse momentum are considered. The analysis is based on proton-proton collision data collected with the ATLAS experiment at $\sqrt{s} = 13$ TeV during LHC Run2 (2015-2018), corresponding to an integrated luminosity of 139 fb$^{-1}$. No significant excess above the Standard Model predictions is found. The results are expressed as 95% confidence-level limits on the parameters of the signal models considered.
Efficiencies of the DMt samples in the tW1L channel for all bins in the SR. The efficiency is defined as the number of weighted reconstructed events over the number of weighted TRUTH events in the SR. The maps include all samples in the $m_a - m_H$ plane with $tan\beta = 1$.
Acceptances on TRUTH level of the DMt samples in the tW1L channel for all bins in the SR. The acceptance is defined as the number of weighted TRUTH events in the SR over the number of expected events without any selections. The maps include all samples in the $m_a - m_H$ plane with $tan\beta = 1$.
Efficiencies of the DMt samples in the tW1L channel for all bins in the SR. The efficiency is defined as the number of weighted reconstructed events over the number of weighted TRUTH events in the SR. The maps include all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.
Acceptances on TRUTH level of the DMt samples in the tW1L channel for all bins in the SR. The acceptance is defined as the number of weighted TRUTH events in the SR over the number of expected events without any selections. The maps include all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.
Efficiencies of the DMt samples in the tW2L SR. The efficiency is defined as the number of weighted reconstructed events over the number of weighted TRUTH events in the SR. The maps include all samples in the $m_a - m_H$ plane with $tan\beta = 1$.
Acceptances on TRUTH level of the DMt samples in the tW2L SR. The acceptance is defined as the number of weighted TRUTH events in the SR over the number of expected events without any selections. The maps include all samples in the $m_a - m_H$ plane with $tan\beta = 1$.
Efficiencies of the DMt samples in the tW2L SR. The efficiency is defined as the number of weighted reconstructed events over the number of weighted TRUTH events in the SR. The maps include all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.
Acceptances on TRUTH level of the DMt samples in the tW2L SR. The acceptance is defined as the number of weighted TRUTH events in the SR over the number of expected events without any selections. The maps include all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.
Efficiencies of the DMt samples in the tj1L channel for all bins in the SR. The efficiency is defined as the number of weighted reconstructed events over the number of weighted TRUTH events in the SR. The map includes all used samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.
Acceptances on TRUTH level of the DMt samples in the tj1L channel for all bins in the SR. The acceptance is defined as the number of weighted TRUTH events in the SR over the number of expected events without any selections. The map includes all used samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.
Upper limits on signal strength (excluded cross section over theoretical cross section) of the tW1L analysis considering only DMt signal.
Upper limits on excluded cross sections of the tW1L analysis considering only the DMt signal.
The expected exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming only $tW$+DM contributions, for the tW1L analysis channel.
The observed exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming only $tW$+DM contributions, for the tW1L analysis channel.
Upper limits on signal strength (excluded cross section over theoretical cross section) of the tW1L analysis considering only DMt signal.
Upper limits on excluded cross sections of the tW1L analysis considering only the DMt signal.
The expected exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming only $tW$+DM contributions, for the tW1L analysis channel.
The observed exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming only $tW$+DM contributions, for the tW1L analysis channel.
Upper limits on signal strength (excluded cross section over theoretical cross section) of the tW2L analysis considering only DMt signal.
Upper limits on excluded cross sections of the tW2L analysis considering only the DMt signal.
The expected exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming only $tW$+DM contributions, for the tW2L analysis channel.
The observed exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming only $tW$+DM contributions, for the tW2L analysis channel.
Upper limits on signal strength (excluded cross section over theoretical cross section) of the tW2L analysis considering only DMt signal.
Upper limits on excluded cross sections of the tW2L analysis considering only the DMt signal.
The expected exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming only $tW$+DM contributions, for the tW2L analysis channel.
The observed exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming only $tW$+DM contributions, for the tW2L analysis channel.
Upper limits on signal strength (excluded cross section over theoretical cross section) of the combined tW1L and tW2L analyses considering only the DMt signal.
Upper limits on excluded cross sections of the combined tW1L and tW2L analyses considering only the DMt signal.
The expected exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming only $tW$+DM contributions, for the statistical combination of the tW1L and tW2L analysis channel.
The observed exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming only $tW$+DM contributions, for the statistical combination of the tW1L and tW2L analysis channel.
Upper limits on signal strength (excluded cross section over theoretical cross section) of the combined tW1L and tW2L analyses considering only the DMt signal.
Upper limits on excluded cross sections of the combined tW1L and tW2L analyses considering only the DMt signal.
The expected exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming only $tW$+DM contributions, for the statistical combination of the tW1L and tW2L analysis channel.
The observed exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming only $tW$+DM contributions, for the statistical combination of the tW1L and tW2L analysis channel.
Upper limits on signal strength (excluded cross section over theoretical cross section) of the tW1L analysis considering the DMt$\bar{t}$+DMt signal.
The expected exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the tW1L analysis channel.
The observed exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the tW1L analysis channel.
Upper limits on signal strength (excluded cross section over theoretical cross section) of the tW1L analysis considering the DMt$\bar{t}$+DMt signal.
The expected exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the tW1L analysis channel.
The observed exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the tW1L analysis channel.
Upper limits on signal strength (excluded cross section over theoretical cross section) of the tW2L analysis considering the DMt$\bar{t}$+DMt signal.
The expected exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the tW2L analysis channel.
The observed exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the tW2L analysis channel.
Upper limits on signal strength (excluded cross section over theoretical cross section) of the tW2L analysis considering the DMt$\bar{t}$+DMt signal.
The expected exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the tW2L analysis channel.
The observed exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the tW2L analysis channel.
Upper limits on signal strength (excluded cross section over theoretical cross section) of the combined tW1L and tW2L analyses considering the DMt$\bar{t}$+DMt signal.
The expected exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the statistical combination of the tW1L and tW2L analysis channel.
The observed exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the statistical combination of the tW1L and tW2L analysis channel.
Upper limits on signal strength (excluded cross section over theoretical cross section) of the combined tW1L and tW2L analyses considering the DMt$\bar{t}$+DMt signal.
The expected exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the statistical combination of the tW1L and tW2L analysis channel.
The observed exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the statistical combination of the tW1L and tW2L analysis channel.
Upper limits on signal strength (excluded cross section over theoretical cross section) of the tj1L analysis considering only the DMt signal.
Upper limits on upper limits on excluded cross sections of the tj1L analysis considering only the DMt signal.
The expected and observed cross section exclusion limits as a function of $m_{H^{\pm}}$ in the tj1L analysis channel for signal models with $m_a = 250~GeV$, and $\tan\beta=0.3$. The $\sigma^{}_\mathrm{BSM}$ is the cross section of the $t$-channel DM production process.
The expected and observed cross section exclusion limits as a function of $m_{H^{\pm}}$ in the tj1L analysis channel for signal models with $m_a = 250~GeV$, and $\tan\beta=0.5$. The $\sigma^{}_\mathrm{BSM}$ is the cross section of the $t$-channel DM production process.
Cross sections of the DMt samples in the tW1L channel. The maps include all samples in the $m_a - m_H$ plane with $tan\beta = 1$.
Cross sections of the DMt samples in the tW1L channel. The maps include all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.
Cross sections times branching ratio of the DMt samples in the tW2L channel. The maps include all samples in the $m_a - m_H$ plane with $tan\beta = 1$.
Cross sections times branching ratio of the DMt samples in the tW2L channel. The maps include all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.
Cross sections of the DMt samples in the tj1L channel. The map includes all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.
MC generator filter efficiencies of the DMt samples in the tW1L channel. The maps include all samples in the $m_a - m_H$ plane with $tan\beta = 1$.
MC generator filter efficiencies of the DMt samples in the tW1L channel. The maps include all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.
MC generator filter efficiencies of the DMt samples in the tW2L channel. The maps include all samples in the $m_a - m_H$ plane with $tan\beta = 1$.
MC generator filter efficiencies of the DMt samples in the tW2L channel. The maps include all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.
MC generator filter efficiencies of the DMt samples in the tj1L channel. The map includes all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.
Background-only fit results for the tW1L and tW2L signal regions. The backgrounds which contribute only a small amount (rare processes such as triboson, Higgs boson production processes, $t\bar{t}t\bar{t}$, $t\bar{t}WW$ and non-prompt or misidentified leptons background) are grouped and labelled as ``Others´´. The quoted uncertainties on the fitted SM background include both the statistical and systematic uncertainties.
Background-only fit results for the tj1L signal regions. The backgrounds which contribute only a small amount ($Z$+jets, rare processes such as $tWZ$, triboson, Higgs boson production processes, ,$t\bar{t}t\bar{t}$, $t\bar{t}WW$) are grouped and labelled as ``Others´´. The quoted uncertainties on the fitted SM background include both the statistical and systematic uncertainties.
Cutflow of the weighted events with statistical uncertainties for two DMt samples in all bins of the tW1L channel. The PreSelection includes at least 1 lepton in the event, at least 1 $b$-jet with $p_{\mathrm{T}} > 50~GeV$, $m\mathrm{_{T}^{lep}} > 30~GeV$, $\Delta\phi\mathrm{_{4jets, MET}^{min}} > 0.5$ and $E\mathrm{_{T}^{miss}} > 200~GeV$.
Cutflow of the weighted events with statistical uncertainties for two DMt samples in the tW2L channel. The PreSelection includes at least 2 leptons in the event, at least 1 $b$-jet with $p_{\mathrm{T}} > 40~GeV$, $m_{ll} > 40~GeV$, $m\mathrm{_{T2}} > 40~GeV$, $\Delta\phi\mathrm{_{4jets, MET}^{min}} > 0.5$ and $E\mathrm{_{T}^{miss}} > 200~GeV$.
Cutflow of the weighted events with the statistical uncertainties (except for the first cuts) for two DMt samples in all bins off the tj1L channel. The PreSelection includes at least 1 lepton in the event, at least 1 $b$-jet with $p_{\mathrm{T}} > 50~GeV$, $m\mathrm{_{T}^{lep}} > 30~GeV$, $\Delta\phi\mathrm{_{4jets, MET}^{min}} > 0.5$ and $E\mathrm{_{T}^{miss}} > 200~GeV$.
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 $139~fb^{-1}$.
A search for charged Higgs bosons decaying into $W^\pm W^\pm$ or $W^\pm Z$ bosons is performed, involving experimental signatures with two leptons of the same charge, or three or four leptons with a variety of charge combinations, missing transverse momentum and jets. A data sample of proton-proton collisions at a centre-of-mass energy of 13 TeV recorded with the ATLAS detector at the Large Hadron Collider between 2015 and 2018 is used. The data correspond to a total integrated luminosity of 139 fb$^{-1}$. The search is guided by a type-II seesaw model that extends the scalar sector of the Standard Model with a scalar triplet, leading to a phenomenology that includes doubly and singly charged Higgs bosons. Two scenarios are explored, corresponding to the pair production of doubly charged $H^{\pm\pm}$ bosons, or the associated production of a doubly charged $H^{\pm\pm}$ boson and a singly charged $H^\pm$ boson. No significant deviations from the Standard Model predictions are observed. $H^{\pm\pm}$ bosons are excluded at 95% confidence level up to 350 GeV and 230 GeV for the pair and associated production modes, respectively.
Distribution of $E_{T}^{miss}$, which is one of the discriminating variables used to define the $2\ell^{sc}$ SRs. The events are selected with the preselection requirements listed in Table 4 in the paper. The data (dots) are compared with the expected contributions from the relevant background sources (histograms). The expected signal distributions for $m_{H^{\pm\pm}} = 300~GeV$ are also shown, scaled to the observed number of events. The last bin includes overflows.
Distribution of $\Delta R_{\ell^{\pm}\ell^{\pm}}$, which is one of the discriminating variables used to define the $2\ell^{sc}$ SRs. The events are selected with the preselection requirements listed in Table 4 in the paper. The data (dots) are compared with the expected contributions from the relevant background sources (histograms). The expected signal distributions for $m_{H^{\pm\pm}} = 300~GeV$ are also shown, scaled to the observed number of events. The last bin includes overflows.
Distribution of $M_{jets}$, which is one of the discriminating variables used to define the $2\ell^{sc}$ SRs. The events are selected with the preselection requirements listed in Table 4 in the paper. The data (dots) are compared with the expected contributions from the relevant background sources (histograms). The expected signal distributions for $m_{H^{\pm\pm}} = 300~GeV$ are also shown, scaled to the observed number of events. The last bin includes overflows.
Distribution of $S$, which is one of the discriminating variables used to define the $2\ell^{sc}$ SRs. The events are selected with the preselection requirements listed in Table 4 in the paper. The data (dots) are compared with the expected contributions from the relevant background sources (histograms). The expected signal distributions for $m_{H^{\pm\pm}} = 300~GeV$ are also shown, scaled to the observed number of events. The last bin includes overflows.
Distribution of $E_{T}^{miss}$, which is one of the discriminating variables used to define the $3\ell$ SRs. The events are selected with the preselection requirements listed in Table 4 in the paper. The data (dots) are compared with the expected contributions from the relevant background sources (histograms). The expected signal distributions for $m_{H^{\pm\pm}} = 300~GeV$ are also shown, scaled to the observed number of events. The last bin includes overflows.
Distribution of $\Delta R_{\ell^{\pm}\ell^{\pm}}$, which is one of the discriminating variables used to define the $3\ell$ SRs. The events are selected with the preselection requirements listed in Table 4 in the paper. The data (dots) are compared with the expected contributions from the relevant background sources (histograms). The expected signal distributions for $m_{H^{\pm\pm}} = 300~GeV$ are also shown, scaled to the observed number of events. The last bin includes overflows.
Distribution of $m_{x\ell}$ ($x$=3), which is one of the discriminating variables used to define the $3\ell$ SRs. The events are selected with the preselection requirements listed in Table 4 in the paper. The data (dots) are compared with the expected contributions from the relevant background sources (histograms). The expected signal distributions for $m_{H^{\pm\pm}} = 300~GeV$ are also shown, scaled to the observed number of events. The last bin includes overflows.
Distribution of $p_{T}^{leading jet}$, which is one of the discriminating variables used to define the $3\ell$ SRs. The events are selected with the preselection requirements listed in Table 4 in the paper. The data (dots) are compared with the expected contributions from the relevant background sources (histograms). The expected signal distributions for $m_{H^{\pm\pm}} = 300~GeV$ are also shown, scaled to the observed number of events. The last bin includes overflows.
Distribution of $E_{T}^{miss}$, which is one of the discriminating variables used to define the $4\ell$ SRs. The events are selected with the preselection requirements listed in Table 4 in the paper. The data (dots) are compared with the expected contributions from the relevant background sources (histograms). The expected signal distributions for $m_{H^{\pm\pm}} = 300~GeV$ are also shown, scaled to the observed number of events. The last bin includes overflows.
Distribution of $\Delta R_{\ell^{\pm}\ell^{\pm}}^{min}$, which is one of the discriminating variables used to define the $4\ell$ SRs. The events are selected with the preselection requirements listed in Table 4 in the paper. The data (dots) are compared with the expected contributions from the relevant background sources (histograms). The expected signal distributions for $m_{H^{\pm\pm}} = 300~GeV$ are also shown, scaled to the observed number of events. The last bin includes overflows.
Distribution of $m_{x\ell}$ ($x$=4), which is one of the discriminating variables used to define the $4\ell$ SRs. The events are selected with the preselection requirements listed in Table 4 in the paper. The data (dots) are compared with the expected contributions from the relevant background sources (histograms). The expected signal distributions for $m_{H^{\pm\pm}} = 300~GeV$ are also shown, scaled to the observed number of events. The last bin includes overflows.
Distribution of $p_{T}^{\ell_{1}}$, which is one of the discriminating variables used to define the $4\ell$ SRs. The events are selected with the preselection requirements listed in Table 4 in the paper. The data (dots) are compared with the expected contributions from the relevant background sources (histograms). The expected signal distributions for $m_{H^{\pm\pm}} = 300~GeV$ are also shown, scaled to the observed number of events. The last bin includes overflows.
Contributions from different categories of uncertainties relative to the expected background yields in the defined SRs, as obtained after performing the likelihood ratio test discussed in Section 9 in the paper. The uncertainties are shown for the combination of the individual channels of the $2\ell^{sc}$, $3\ell$ and $4\ell$ SRs. The SRs are indicated along the horizontal axis. In the HEPData entry, the x-axis is simplified for easier visualisation. The first number indicates the sub channel (2:$2\ell^{sc}$, 3:$3\ell$, 4:$4\ell$), while the second number indicates the mass point (2:200, 3:300, 4:400, 5:500).
Data event yields compared with the expected contributions from relevant background sources, for the combination of the individual channels of the $2\ell^{sc}$, $3\ell$ and $4\ell$ SRs. The total uncertainties in the expected event yields are shown as the hatched bands. The SRs are indicated along the horizontal axis. In the HEPData entry, the x-axis is simplified for easier visualisation. The first number indicates the sub channel (2:$2\ell^{sc}$, 3:$3\ell$, 4:$4\ell$), while the second number indicates the mass point (2:200, 3:300, 4:400, 5:500).
The $E_{T}^{miss}$ distribution for the SRs of the $m_{H^{\pm\pm}} = 300~GeV$ signal mass hypothesis, where the selection requirement on $E_{T}^{miss}$ has been removed. In the attached plot, the signals are stacked on top of the backgrounds while individuals contributions of the $2\ell^{sc}$ channel are shown in HEPData. The last bin, isolated by a vertical red dashed line, is inclusive and corresponds to the SR.
The $E_{T}^{miss}$ distribution for the SRs of the $m_{H^{\pm\pm}} = 300~GeV$ signal mass hypothesis, where the selection requirement on $E_{T}^{miss}$ has been removed. In the attached plot, the signals are stacked on top of the backgrounds while individuals contributions of the $3\ell$ channel are shown in HEPData. The last bin, isolated by a vertical red dashed line, is inclusive and corresponds to the SR.
The $E_{T}^{miss}$ distribution for the SRs of the $m_{H^{\pm\pm}} = 300~GeV$ signal mass hypothesis, where the selection requirement on $E_{T}^{miss}$ has been removed. In the attached plot, the signals are stacked on top of the backgrounds while individuals contributions of the $4\ell$ channel are shown in HEPData. The last bin, isolated by a vertical red dashed line, is inclusive and corresponds to the SR.
Observed and expected upper limits of the $H^{\pm\pm}$ pair production cross section times branching fraction at 95% CL obtained from the combination of 2$\ell^{sc}$, 3$\ell$ and 4$\ell$ channels. The region above the observed limit is excluded by the measurement. The bands represent the expected exclusion curves within one and two standard deviations.
The theoretical prediction of Figure 9(a) in the paper.
Observed and expected upper limits of the $H^{\pm\pm}$ and $H^{\pm}$ production cross section times branching fraction at 95% CL obtained from the combination of 2$\ell^{sc}$, 3$\ell$ and 4$\ell$ channels. The region above the observed limit is excluded by the measurement. The bands represent the expected exclusion curves within one and two standard deviations.
The theoretical prediction of Figure 9(b) in the paper.
Data event yields compared with the estimated background in the $m_{H^{\pm\pm}} = 200~GeV$ or $m_{H^{\pm\pm}} = 220~GeV$ SRs. SFOC 0 and SFOC 1,2 refer to the number of same-flavour opposite charge lepton pairs. The total uncertainties in the estimated background yields are shown as the hashed bands. In the HEPData entry, the x-axis is simplified for easier visualisation (1:$e^{\pm}e^{\pm}$, 2:$e^{\pm}\mu^{\pm}$, 3:$\mu^{\pm}\mu^{\pm}$, 4:SFOC 0, 5:SFOC 1,2, 6:$4\ell$).
Data event yields compared with the estimated background in the $m_{H^{\pm\pm}} = 300~GeV$ or $m_{H^{\pm\pm}} = 350~GeV$ SRs. SFOC 0 and SFOC 1,2 refer to the number of same-flavour opposite charge lepton pairs. The total uncertainties in the estimated background yields are shown as the hashed bands. In the HEPData entry, the x-axis is simplified for easier visualisation (1:$e^{\pm}e^{\pm}$, 2:$e^{\pm}\mu^{\pm}$, 3:$\mu^{\pm}\mu^{\pm}$, 4:SFOC 0, 5:SFOC 1,2, 6:$4\ell$).
Data event yields compared with the estimated background in the $m_{H^{\pm\pm}} = 400~GeV$ or $m_{H^{\pm\pm}} = 450~GeV$ SRs. SFOC 0 and SFOC 1,2 refer to the number of same-flavour opposite charge lepton pairs. The total uncertainties in the estimated background yields are shown as the hashed bands. In the HEPData entry, the x-axis is simplified for easier visualisation (1:$e^{\pm}e^{\pm}$, 2:$e^{\pm}\mu^{\pm}$, 3:$\mu^{\pm}\mu^{\pm}$, 4:SFOC 0, 5:SFOC 1,2, 6:$4\ell$).
Data event yields compared with the estimated background in the $m_{H^{\pm\pm}} = 500~GeV$ or $m_{H^{\pm\pm}} = 550~GeV$ or $m_{H^{\pm\pm}} = 600~GeV$ SRs. SFOC 0 and SFOC 1,2 refer to the number of same-flavour opposite charge lepton pairs. The total uncertainties in the estimated background yields are shown as the hashed bands. In the HEPData entry, the x-axis is simplified for easier visualisation (1:$e^{\pm}e^{\pm}$, 2:$e^{\pm}\mu^{\pm}$, 3:$\mu^{\pm}\mu^{\pm}$, 4:SFOC 0, 5:SFOC 1,2, 6:$4\ell$).
A search for the supersymmetric partners of quarks and gluons (squarks and gluinos) in final states containing jets and missing transverse momentum, but no electrons or muons, is presented. The data used in this search were recorded by the ATLAS experiment in proton-proton collisions at a centre-of-mass energy of $\sqrt{s}$ = 13 TeV during Run 2 of the Large Hadron Collider, corresponding to an integrated luminosity of 139 fb$^{-1}$. The results are interpreted in the context of various $R$-parity-conserving models where squarks and gluinos are produced in pairs or in association and a neutralino is the lightest supersymmetric particle. An exclusion limit at the 95% confidence level on the mass of the gluino is set at 2.30 TeV for a simplified model containing only a gluino and the lightest neutralino, assuming the latter is massless. For a simplified model involving the strong production of mass-degenerate first- and second-generation squarks, squark masses below 1.85 TeV are excluded if the lightest neutralino is massless. These limits extend substantially beyond the region of supersymmetric parameter space excluded previously by similar searches with the ATLAS detector.
Observed $m_{\mathrm{eff}}$ distributions in signal regions MB-SSd. The histograms show the MC background predictions normalised by the background-only fit. The hatched (red) error bands indicate experimental and MC statistical uncertainties. Expected distributions for benchmark signal model points, normalised using the approximate NNLO+NNLL cross-section times integrated luminosity, are also shown for comparison (masses in GeV).
Observed $m_{\mathrm{eff}}$ distributions in signal regions MB-SSd. The histograms show the MC background predictions normalised by the background-only fit. The hatched (red) error bands indicate experimental and MC statistical uncertainties. Expected distributions for benchmark signal model points, normalised using the approximate NNLO+NNLL cross-section times integrated luminosity, are also shown for comparison (masses in GeV).
Observed metSig distributions in signal regions MB-SSd. The histograms show the MC background predictions normalised by the background-only fit. The hatched (red) error bands indicate experimental and MC statistical uncertainties. Expected distributions for benchmark signal model points, normalised using the approximate NNLO+NNLL cross-section times integrated luminosity, are also shown for comparison (masses in GeV).
Observed metSig distributions in signal regions MB-SSd. The histograms show the MC background predictions normalised by the background-only fit. The hatched (red) error bands indicate experimental and MC statistical uncertainties. Expected distributions for benchmark signal model points, normalised using the approximate NNLO+NNLL cross-section times integrated luminosity, are also shown for comparison (masses in GeV).
Observed $m_{\mathrm{eff}}$ distributions in signal regions MB-GGd. The histograms show the MC background predictions normalised by the background-only fit. The hatched (red) error bands indicate experimental and MC statistical uncertainties. Expected distributions for benchmark signal model points, normalised using the approximate NNLO+NNLL cross-section times integrated luminosity, are also shown for comparison (masses in GeV).
Observed $m_{\mathrm{eff}}$ distributions in signal regions MB-GGd. The histograms show the MC background predictions normalised by the background-only fit. The hatched (red) error bands indicate experimental and MC statistical uncertainties. Expected distributions for benchmark signal model points, normalised using the approximate NNLO+NNLL cross-section times integrated luminosity, are also shown for comparison (masses in GeV).
Observed metSig distributions in signal regions MB-GGd. The histograms show the MC background predictions normalised by the background-only fit. The hatched (red) error bands indicate experimental and MC statistical uncertainties. Expected distributions for benchmark signal model points, normalised using the approximate NNLO+NNLL cross-section times integrated luminosity, are also shown for comparison (masses in GeV).
Observed metSig distributions in signal regions MB-GGd. The histograms show the MC background predictions normalised by the background-only fit. The hatched (red) error bands indicate experimental and MC statistical uncertainties. Expected distributions for benchmark signal model points, normalised using the approximate NNLO+NNLL cross-section times integrated luminosity, are also shown for comparison (masses in GeV).
Observed $m_{\mathrm{eff}}$ distributions in signal regions MB-C. The histograms show the MC background predictions normalised by the background-only fit. The hatched (red) error bands indicate experimental and MC statistical uncertainties. Expected distributions for benchmark signal model points, normalised using the approximate NNLO+NNLL cross-section times integrated luminosity, are also shown for comparison (masses in GeV).
Observed $m_{\mathrm{eff}}$ distributions in signal regions MB-C. The histograms show the MC background predictions normalised by the background-only fit. The hatched (red) error bands indicate experimental and MC statistical uncertainties. Expected distributions for benchmark signal model points, normalised using the approximate NNLO+NNLL cross-section times integrated luminosity, are also shown for comparison (masses in GeV).
Observed metSig distributions in signal regions MB-C. The histograms show the MC background predictions normalised by the background-only fit. The hatched (red) error bands indicate experimental and MC statistical uncertainties. Expected distributions for benchmark signal model points, normalised using the approximate NNLO+NNLL cross-section times integrated luminosity, are also shown for comparison (masses in GeV).
Observed metSig distributions in signal regions MB-C. The histograms show the MC background predictions normalised by the background-only fit. The hatched (red) error bands indicate experimental and MC statistical uncertainties. Expected distributions for benchmark signal model points, normalised using the approximate NNLO+NNLL cross-section times integrated luminosity, are also shown for comparison (masses in GeV).
Observed BDT-GGd1 score distributions in signal regions GGd1. The histograms show the MC background predictions normalised by the background-only fit. The hatched (red) error bands indicate experimental and MC statistical uncertainties. Expected distributions for benchmark signal model points, normalised using the approximate NNLO+NNLL cross-section times integrated luminosity, are also shown for comparison (masses in GeV).
Observed BDT-GGd1 score distributions in signal regions GGd1. The histograms show the MC background predictions normalised by the background-only fit. The hatched (red) error bands indicate experimental and MC statistical uncertainties. Expected distributions for benchmark signal model points, normalised using the approximate NNLO+NNLL cross-section times integrated luminosity, are also shown for comparison (masses in GeV).
Observed BDT-GGo1 score distributions in signal regions GGo1. The histograms show the MC background predictions normalised by the background-only fit. The hatched (red) error bands indicate experimental and MC statistical uncertainties. Expected distributions for benchmark signal model points, normalised using the approximate NNLO+NNLL cross-section times integrated luminosity, are also shown for comparison (masses in GeV).
Observed BDT-GGo1 score distributions in signal regions GGo1. The histograms show the MC background predictions normalised by the background-only fit. The hatched (red) error bands indicate experimental and MC statistical uncertainties. Expected distributions for benchmark signal model points, normalised using the approximate NNLO+NNLL cross-section times integrated luminosity, are also shown for comparison (masses in GeV).
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and neutralino in SR BDT-GGd1
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and neutralino in SR BDT-GGd1
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and neutralino in SR BDT-GGd2
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and neutralino in SR BDT-GGd2
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and neutralino in SR BDT-GGd3
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and neutralino in SR BDT-GGd3
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and neutralino in SR BDT-GGd4
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and neutralino in SR BDT-GGd4
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and chargino in SR BDT-GGo1
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and chargino in SR BDT-GGo1
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and chargino in SR BDT-GGo2
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and chargino in SR BDT-GGo2
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and chargino in SR BDT-GGo3
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and chargino in SR BDT-GGo3
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and chargino in SR BDT-GGo4
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and chargino in SR BDT-GGo4
Signal region acceptance for simplified model with squark pair production and decays to a quark and neutralino in SR 2j-1600
Signal region acceptance for simplified model with squark pair production and decays to a quark and neutralino in SR 2j-1600
Signal region acceptance for simplified model with squark pair production and decays to a quark and neutralino in SR 2j-2200
Signal region acceptance for simplified model with squark pair production and decays to a quark and neutralino in SR 2j-2200
Signal region acceptance for simplified model with squark pair production and decays to a quark and neutralino in SR 2j-2800
Signal region acceptance for simplified model with squark pair production and decays to a quark and neutralino in SR 2j-2800
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and neutralino in SR 4j-1000
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and neutralino in SR 4j-1000
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and neutralino in SR 4j-2200
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and neutralino in SR 4j-2200
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and neutralino in SR 4j-3400
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and neutralino in SR 4j-3400
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and neutralino in SR 5j-1600
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and neutralino in SR 5j-1600
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and chargino in SR 6j-1000
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and chargino in SR 6j-1000
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and chargino in SR 6j-2200
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and chargino in SR 6j-2200
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and chargino in SR 6j-3400
Signal region acceptance for simplified model with gluino pair production and decays to two quarks and chargino in SR 6j-3400
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and neutralino in SR BDT-GGd1. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and neutralino in SR BDT-GGd1. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and neutralino in SR BDT-GGd2. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and neutralino in SR BDT-GGd2. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and neutralino in SR BDT-GGd3. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and neutralino in SR BDT-GGd3. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and neutralino in SR BDT-GGd4. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and neutralino in SR BDT-GGd4. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and chargino in SR BDT-GGo1. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and chargino in SR BDT-GGo1. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and chargino in SR BDT-GGo2. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and chargino in SR BDT-GGo2. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and chargino in SR BDT-GGo3. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and chargino in SR BDT-GGo3. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and chargino in SR BDT-GGo4. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and chargino in SR BDT-GGo4. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with squark pair production and decays to a quark and neutralino in SR 2j-1600. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with squark pair production and decays to a quark and neutralino in SR 2j-1600. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with squark pair production and decays to a quark and neutralino in SR 2j-2200. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with squark pair production and decays to a quark and neutralino in SR 2j-2200. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with squark pair production and decays to a quark and neutralino in SR 2j-2800. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with squark pair production and decays to a quark and neutralino in SR 2j-2800. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and neutralino in SR 4j-1000. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and neutralino in SR 4j-1000. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and neutralino in SR 4j-2200. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and neutralino in SR 4j-2200. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and neutralino in SR 4j-3400. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and neutralino in SR 4j-3400. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and neutralino in SR 5j-1600. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and neutralino in SR 5j-1600. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and chargino in SR 6j-1000. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and chargino in SR 6j-1000. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and chargino in SR 6j-2200. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and chargino in SR 6j-2200. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and chargino in SR 6j-3400. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Signal region efficiency for simplified model with gluino pair production and decays to two quarks and chargino in SR 6j-3400. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.
Exclusion limits in the mass plane of the lightest neutralino and first- and second-generation squarks assuming squark pair production and direct decays obtained by using the signal region with the best expected sensitivity at each point. The expected limits are indicated with a dark dashed curve, with the light (yellow) band indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.
Exclusion limits in the mass plane of the lightest neutralino and first- and second-generation squarks assuming squark pair production and direct decays obtained by using the signal region with the best expected sensitivity at each point. The expected limits are indicated with a dark dashed curve, with the light (yellow) band indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.
Exclusion limits in the mass plane of the lightest neutralino and first- and second-generation squarks assuming squark pair production and direct decays obtained by using the signal region with the best expected sensitivity at each point. The observed limits are indicated by the medium dark (maroon) curve where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.
Exclusion limits in the mass plane of the lightest neutralino and first- and second-generation squarks assuming squark pair production and direct decays obtained by using the signal region with the best expected sensitivity at each point. The observed limits are indicated by the medium dark (maroon) curve where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.
Exclusion limits in the mass plane of the lightest neutralino and non degenerated squark pair production and direct decays obtained by using the signal region with the best expected sensitivity at each point. The expected limits are indicated with a dark dashed curve, with the light (yellow) band indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.
Exclusion limits in the mass plane of the lightest neutralino and non degenerated squark pair production and direct decays obtained by using the signal region with the best expected sensitivity at each point. The expected limits are indicated with a dark dashed curve, with the light (yellow) band indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.
Exclusion limits in the mass plane of the lightest neutralino and non degenerated squark pair production and direct decays obtained by using the signal region with the best expected sensitivity at each point. The observed limits are indicated by the medium dark (maroon) curve where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.
Exclusion limits in the mass plane of the lightest neutralino and non degenerated squark pair production and direct decays obtained by using the signal region with the best expected sensitivity at each point. The observed limits are indicated by the medium dark (maroon) curve where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.
Exclusion limits in the mass plane of the lightest neutralino and the gluino for gluino pair production with direct decays obtained by using the signal region with the best expected sensitivity at each point. The expected limits are indicated with a dark dashed curve, with the light (yellow) band indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.
Exclusion limits in the mass plane of the lightest neutralino and the gluino for gluino pair production with direct decays obtained by using the signal region with the best expected sensitivity at each point. The expected limits are indicated with a dark dashed curve, with the light (yellow) band indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.
Exclusion limits in the mass plane of the lightest neutralino and the gluino for gluino pair production with direct decays obtained by using the signal region with the best expected sensitivity at each point. The observed limits are indicated by the medium dark (maroon) curve where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.
Exclusion limits in the mass plane of the lightest neutralino and the gluino for gluino pair production with direct decays obtained by using the signal region with the best expected sensitivity at each point. The observed limits are indicated by the medium dark (maroon) curve where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.
Exclusion limits in the mass plane of the lightest neutralino and squarks. The expected limits are indicated with dark dashed curves, with the light (yellow) bands indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.
Exclusion limits in the mass plane of the lightest neutralino and squarks. The expected limits are indicated with dark dashed curves, with the light (yellow) bands indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.
Exclusion limits in the mass plane of the lightest neutralino and squarks. The observed limits are indicated by the medium dark (maroon) curves where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.
Exclusion limits in the mass plane of the lightest neutralino and squarks. The observed limits are indicated by the medium dark (maroon) curves where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.
Exclusion limits for squark pair production with a one-step decay via an intermediate chargino. The neutralino mass is fixed at 60 GeV and exclusion limits are given for mass difference ratio, $X$, as a function of the squark mass. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The expected limits are indicated with dark dashed curves, with the light (yellow) bands indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.
Exclusion limits for squark pair production with a one-step decay via an intermediate chargino. The neutralino mass is fixed at 60 GeV and exclusion limits are given for mass difference ratio, $X$, as a function of the squark mass. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The expected limits are indicated with dark dashed curves, with the light (yellow) bands indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.
Exclusion limits for squark pair production with a one-step decay via an intermediate chargino. The neutralino mass is fixed at 60 GeV and exclusion limits are given for mass difference ratio, $X$, as a function of the squark mass. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The observed limits are indicated by the medium dark (maroon) curves where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.
Exclusion limits for squark pair production with a one-step decay via an intermediate chargino. The neutralino mass is fixed at 60 GeV and exclusion limits are given for mass difference ratio, $X$, as a function of the squark mass. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The observed limits are indicated by the medium dark (maroon) curves where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.
Exclusion limits in the mass plane of the lightest neutralino and gluinos. The expected limits are indicated with dark dashed curves, with the light (yellow) bands indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.
Exclusion limits in the mass plane of the lightest neutralino and gluinos. The expected limits are indicated with dark dashed curves, with the light (yellow) bands indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.
Exclusion limits in the mass plane of the lightest neutralino and gluinos. The observed limits are indicated by the medium dark (maroon) curve where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.
Exclusion limits in the mass plane of the lightest neutralino and gluinos. The observed limits are indicated by the medium dark (maroon) curve where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.
Exclusion limits for gluino pair production with a one-step decay via an intermediate chargino. The neutralino mass is fixed at 60 GeV and exclusion limits are given for mass difference ratio, $X$, as a function of the gluino mass. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The expected limits are indicated with dark dashed curves, with the light (yellow) bands indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.
Exclusion limits for gluino pair production with a one-step decay via an intermediate chargino. The neutralino mass is fixed at 60 GeV and exclusion limits are given for mass difference ratio, $X$, as a function of the gluino mass. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The expected limits are indicated with dark dashed curves, with the light (yellow) bands indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.
Exclusion limits for gluino pair production with a one-step decay via an intermediate chargino. The neutralino mass is fixed at 60 GeV and exclusion limits are given for mass difference ratio, $X$, as a function of the gluino mass. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The observed limits are indicated by the medium dark (maroon) curves where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.
Exclusion limits for gluino pair production with a one-step decay via an intermediate chargino. The neutralino mass is fixed at 60 GeV and exclusion limits are given for mass difference ratio, $X$, as a function of the gluino mass. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The observed limits are indicated by the medium dark (maroon) curves where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.
Exclusion limits for the model with combined production of squark pairs, gluino pairs, and of squark--gluino pairs. The neutralino mass is fixed at 0 GeV. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The expected limits are indicated with dark dashed curves, with the light (yellow) bands indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.
Exclusion limits for the model with combined production of squark pairs, gluino pairs, and of squark--gluino pairs. The neutralino mass is fixed at 0 GeV. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The expected limits are indicated with dark dashed curves, with the light (yellow) bands indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.
Exclusion limits for the model with combined production of squark pairs, gluino pairs, and of squark--gluino pairs. The neutralino mass is fixed at 0 GeV. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The observed limits are indicated by the medium dark (maroon) curves where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.
Exclusion limits for the model with combined production of squark pairs, gluino pairs, and of squark--gluino pairs. The neutralino mass is fixed at 0 GeV. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The observed limits are indicated by the medium dark (maroon) curves where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.
Exclusion limits for the model with combined production of squark pairs, gluino pairs, and of squark--gluino pairs. The neutralino mass is fixed at 995 GeV. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The expected limits are indicated with dark dashed curves, with the light (yellow) bands indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.
Exclusion limits for the model with combined production of squark pairs, gluino pairs, and of squark--gluino pairs. The neutralino mass is fixed at 995 GeV. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The expected limits are indicated with dark dashed curves, with the light (yellow) bands indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.
Exclusion limits for the model with combined production of squark pairs, gluino pairs, and of squark--gluino pairs. The neutralino mass is fixed at 995 GeV. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The observed limits are indicated by the medium dark (maroon) curves where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.
Exclusion limits for the model with combined production of squark pairs, gluino pairs, and of squark--gluino pairs. The neutralino mass is fixed at 995 GeV. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The observed limits are indicated by the medium dark (maroon) curves where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.
Exclusion limits for the model with combined production of squark pairs, gluino pairs, and of squark--gluino pairs. The neutralino mass is fixed at 1495 GeV. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The expected limits are indicated with dark dashed curves, with the light (yellow) bands indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.
Exclusion limits for the model with combined production of squark pairs, gluino pairs, and of squark--gluino pairs. The neutralino mass is fixed at 1495 GeV. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The expected limits are indicated with dark dashed curves, with the light (yellow) bands indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.
Exclusion limits for the model with combined production of squark pairs, gluino pairs, and of squark--gluino pairs. The neutralino mass is fixed at 1495 GeV. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The observed limits are indicated by the medium dark (maroon) curves where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.
Exclusion limits for the model with combined production of squark pairs, gluino pairs, and of squark--gluino pairs. The neutralino mass is fixed at 1495 GeV. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The observed limits are indicated by the medium dark (maroon) curves where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.
The observed upper limits on signal cross section corresponding to the best expected signal region in each mass point for squark-pair production with direct decays.
The observed upper limits on signal cross section corresponding to the best expected signal region in each mass point for squark-pair production with direct decays.
The observed upper limits on signal cross section corresponding to the best expected signal region in each mass point for gluino-pair production with direct decays
The observed upper limits on signal cross section corresponding to the best expected signal region in each mass point for gluino-pair production with direct decays
The observed upper limits on signal cross section corresponding to the best expected signal region in each mass point for squark-pair production with a one-step decay via an intermediate chargino.
The observed upper limits on signal cross section corresponding to the best expected signal region in each mass point for squark-pair production with a one-step decay via an intermediate chargino.
The observed upper limits on signal cross section corresponding to the best expected signal region in each mass point for squark-pair production with a one-step decay via an intermediate chargino. The neutralino mass is fixed at 60 GeV and exclusion limits are given for mass difference ratio, $X$, as a function of the squark mass.
The observed upper limits on signal cross section corresponding to the best expected signal region in each mass point for squark-pair production with a one-step decay via an intermediate chargino. The neutralino mass is fixed at 60 GeV and exclusion limits are given for mass difference ratio, $X$, as a function of the squark mass.
The observed upper limits on signal cross section corresponding to the best expected signal region in each mass point for gluino-pair production with a one-step decay via an intermediate chargino.
The observed upper limits on signal cross section corresponding to the best expected signal region in each mass point for gluino-pair production with a one-step decay via an intermediate chargino.
The observed upper limits on signal cross section corresponding to the best expected signal region in each mass point for gluino-pair production with a one-step decay via an intermediate chargino. The neutralino mass is fixed at 60~GeV and exclusio limits are given for mass difference ratio, $X$, as a function of the gluino mass.
The observed upper limits on signal cross section corresponding to the best expected signal region in each mass point for gluino-pair production with a one-step decay via an intermediate chargino. The neutralino mass is fixed at 60~GeV and exclusio limits are given for mass difference ratio, $X$, as a function of the gluino mass.
Cut-flow for model-independent search regions targeting squarks for SS direct model points. Expected yields are normalized to a luminosity of 139 fb$^{-1}$.
Cut-flow for model-independent search regions targeting squarks for SS direct model points. Expected yields are normalized to a luminosity of 139 fb$^{-1}$.
Cut-flow for model-independent search regions targeting gluinos for GG direct model points. Expected yields are normalized to a luminosity of 139 fb$^{-1}$.
Cut-flow for model-independent search regions targeting gluinos for GG direct model points. Expected yields are normalized to a luminosity of 139 fb$^{-1}$.
Cut-flow for model-independent search regions targeting squarks and gluinos in models with one-step decay. Expected yields are normalized to a luminosity of 139 $fb^{-1}$.
Cut-flow for model-independent search regions targeting squarks and gluinos in models with one-step decay. Expected yields are normalized to a luminosity of 139 $fb^{-1}$.
Cut-flow for BDT search regions targeting gluinos in models with one-step decays. Expected yields are normalized to a luminosity of 139 $fb^{-1}$.
Cut-flow for BDT search regions targeting gluinos in models with one-step decays. Expected yields are normalized to a luminosity of 139 $fb^{-1}$.
Cut-flow for BDT search regions targeting gluinos in models with direct decays. Expected yields are normalized to a luminosity of 139 $fb^{-1}$.
Cut-flow for BDT search regions targeting gluinos in models with direct decays. Expected yields are normalized to a luminosity of 139 $fb^{-1}$.
A search for a heavy neutral Higgs boson, $A$, decaying into a $Z$ boson and another heavy Higgs boson, $H$, is performed using a data sample corresponding to an integrated luminosity of 139 fb$^{-1}$ from proton-proton collisions at $\sqrt{s}$ = 13 TeV recorded by the ATLAS detector at the LHC. The search considers the $Z$ boson decaying into electrons or muons and the $H$ boson into a pair of $b$-quarks or $W$ bosons. The mass range considered is 230-800 GeV for the $A$ boson and 130-700 GeV for the $H$ boson. The data are in good agreement with the background predicted by the Standard Model, and therefore 95% confidence-level upper limits for $\sigma \times B(A\rightarrow ZH) \times B(H\rightarrow bb$ or $H\rightarrow WW)$ are set. The upper limits are in the range 0.0062-0.380 pb for the $H\rightarrow bb$ channel and in the range 0.023-8.9 pb for the $H\rightarrow WW$ channel. An interpretation of the results in the context of two-Higgs-Doublet models is also given.
The mass distribution of the bb system before any mbb window cuts for the 2 tag category in b-associated production. The signal distribution for (mA, mH) = (600, 300) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mass distribution of the bb system before any mbb window cuts for the 3 tag category in b-associated production. The signal distribution for (mA, mH) = (600, 300) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH)=(600, 300) GeV in the 2 tag category with gluon-gluon fusion production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (600, 300) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH)=(600, 300) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (600, 300) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH)=(670, 500) GeV in the 2 tag category with gluon-gluon fusion production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (670, 500) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (670, 500) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (670, 500) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
Upper bounds at 95% CL on the production cross-section times the branching ratio B(A->ZH)xB(H->bb) in pb for a narrow width A boson produced via gluon-gluon fusion. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected.
Upper bounds at 95% CL on the production cross-section times the branching ratio B(A->ZH)xB(H->bb) in pb for a narrow width A boson produced via b-associated production. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected.
Upper bounds at 95% CL on the total production cross-section (ggA + bbA) times the branching ratio B(A->ZH)xB(H->bb) for an A boson in the 2HDM of type-1 with tan(beta)=1. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used and cos(beta-alpha)=0 is assumed. The excluded contours in the figure correspond to the points of the 2HDM parameter space where the expected and observed limits match the theoretical prediction for the cross-section in the model.
Upper bounds at 95% CL on the total production cross-section (ggA + bbA) times the branching ratio B(A->ZH)xB(H->bb) for an A boson in the 2HDM of type-1 with tan(beta)=5. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used and cos(beta-alpha)=0 is assumed. The excluded contours in the figure correspond to the points of the 2HDM parameter space where the expected and observed limits match the theoretical prediction for the cross-section in the model.
Upper bounds at 95% CL on the total production cross-section (ggA + bbA) times the branching ratio B(A->ZH)xB(H->bb) for an A boson in the 2HDM of type-1 with tan(beta)=10. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used and cos(beta-alpha)=0 is assumed. The excluded contours in the figure correspond to the points of the 2HDM parameter space where the expected and observed limits match the theoretical prediction for the cross-section in the model.
Upper bounds at 95% CL on the total production cross-section (ggA + bbA) times the branching ratio B(A->ZH)xB(H->bb) for an A boson in the 2HDM of type-2 with tan(beta)=1. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used and cos(beta-alpha)=0 is assumed. The excluded contours in the figure correspond to the points of the 2HDM parameter space where the expected and observed limits match the theoretical prediction for the cross-section in the model.
Upper bounds at 95% CL on the total production cross-section (ggA + bbA) times the branching ratio B(A->ZH)xB(H->bb) for an A boson in the 2HDM of type-2 with tan(beta)=5. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used and cos(beta-alpha)=0 is assumed. The excluded contours in the figure correspond to the points of the 2HDM parameter space where the expected and observed limits match the theoretical prediction for the cross-section in the model.
Upper bounds at 95% CL on the total production cross-section (ggA + bbA) times the branching ratio B(A->ZH)xB(H->bb) for an A boson in the 2HDM of type-2 with tan(beta)=10. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used and cos(beta-alpha)=0 is assumed. The excluded contours in the figure correspond to the points of the 2HDM parameter space where the expected and observed limits match the theoretical prediction for the cross-section in the model.
Upper bounds at 95% CL on the total production cross-section (ggA + bbA) times the branching ratio B(A->ZH)xB(H->bb) for an A boson in the 2HDM of type-2 with tan(beta)=20. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used and cos(beta-alpha)=0 is assumed. The excluded contours in the figure correspond to the points of the 2HDM parameter space where the expected and observed limits match the theoretical prediction for the cross-section in the model.
Upper bounds at 95% CL on the total production cross-section (ggA + bbA) times the branching ratio B(A->ZH)xB(H->bb) for an A boson in the lepton specific 2HDM with tan(beta)=1. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used and cos(beta-alpha)=0 is assumed. The excluded contours in the figure correspond to the points of the 2HDM parameter space where the expected and observed limits match the theoretical prediction for the cross-section in the model.
Upper bounds at 95% CL on the total production cross-section (ggA + bbA) times the branching ratio B(A->ZH)xB(H->bb) for an A boson in the lepton specific 2HDM with tan(beta)=2. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used and cos(beta-alpha)=0 is assumed. The excluded contours in the figure correspond to the points of the 2HDM parameter space where the expected and observed limits match the theoretical prediction for the cross-section in the model.
Upper bounds at 95% CL on the total production cross-section (ggA + bbA) times the branching ratio B(A->ZH)xB(H->bb) for an A boson in the lepton specific 2HDM with tan(beta)=3. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used and cos(beta-alpha)=0 is assumed. The excluded contours in the figure correspond to the points of the 2HDM parameter space where the expected and observed limits match the theoretical prediction for the cross-section in the model.
Upper bounds at 95% CL on the total production cross-section (ggA + bbA) times the branching ratio B(A->ZH)xB(H->bb) for an A boson in the flipped 2HDM with tan(beta)=1. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used and cos(beta-alpha)=0 is assumed. The excluded contours in the figure correspond to the points of the 2HDM parameter space where the expected and observed limits match the theoretical prediction for the cross-section in the model.
Upper bounds at 95% CL on the total production cross-section (ggA + bbA) times the branching ratio B(A->ZH)xB(H->bb) for an A boson in the flipped 2HDM with tan(beta)=5. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used and cos(beta-alpha)=0 is assumed. The excluded contours in the figure correspond to the points of the 2HDM parameter space where the expected and observed limits match the theoretical prediction for the cross-section in the model.
Upper bounds at 95% CL on the total production cross-section (ggA + bbA) times the branching ratio B(A->ZH)xB(H->bb) for an A boson in the flipped 2HDM with tan(beta)=10. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used and cos(beta-alpha)=0 is assumed. The excluded contours in the figure correspond to the points of the 2HDM parameter space where the expected and observed limits match the theoretical prediction for the cross-section in the model.
Upper bounds at 95% CL on the total production cross-section (ggA + bbA) times the branching ratio B(A->ZH)xB(H->bb) for an A boson in the flipped 2HDM with tan(beta)=20. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used and cos(beta-alpha)=0 is assumed. The excluded contours in the figure correspond to the points of the 2HDM parameter space where the expected and observed limits match the theoretical prediction for the cross-section in the model.
The mass distribution of the 4q system before any m4q window cuts for gluon-gluon fusion for the llWW channel. The signal distribution for (mA, mH) = (600, 300) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH)=(600, 300) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (600, 300) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH)=(670, 500) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (670, 500) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
Upper bounds at 95% CL on the production cross-section times the branching ratio B(A->ZH)xB(H->WW) in pb for a narrow width A boson produced via gluon-gluon fusion production. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected.
Upper bounds at 95% CL on the production cross-section times the branching ratio B(A->ZH)xB(H->bb) in pb for an A boson with a natural width that is 10% with respect to its mass, produced via gluon-gluon fusion for the llbb final state. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected.
Upper bounds at 95% CL on the production cross-section times the branching ratio B(A->ZH)xB(H->bb) in pb for an A boson with a natural width that is 10% with respect to its mass, via b-associated production for the llbb final state. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected.
Upper bounds at 95% CL on the production cross-section times the branching ratio B(A->ZH)xB(H->bb) in pb for an A boson with a natural width that is 20% with respect to its mass, produced via gluon-gluon fusion for the llbb final state. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected.
Upper bounds at 95% CL on the production cross-section times the branching ratio B(A->ZH)xB(H->bb) in pb for an A boson with a natural width that is 20% with respect to its mass, via b-associated production for the llbb final state. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected.
Upper bounds at 95% CL on the production cross-section times the branching ratio B(A->ZH)xB(H->WW) in pb for an A boson with a natural width that is 10% with respect to its mass, produced via gluon-gluon fusion for the llWW final state. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected.
Upper bounds at 95% CL on the production cross-section times the branching ratio B(A->ZH)xB(H->WW) in pb for an A boson with a natural width that is 20% with respect to its mass, produced via gluon-gluon fusion for the llWW final state. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (440, 130) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (440, 130) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (450, 140) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (450, 140) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (460, 150) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (460, 150) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (460, 160) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (460, 160) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (470, 170) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (470, 170) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (470, 180) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (470, 180) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (420, 190) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (420, 190) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (490, 200) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (490, 200) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (430, 210) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (430, 210) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (440, 220) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (440, 220) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (500, 230) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (500, 230) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (510, 240) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (510, 240) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (520, 250) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (520, 250) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (520, 260) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (520, 260) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (530, 270) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (530, 270) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (540, 280) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (540, 280) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (540, 290) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (540, 290) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (550, 300) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (550, 300) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (550, 310) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (550, 310) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (560, 320) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (560, 320) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (570, 330) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (570, 330) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (570, 340) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (570, 340) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (580, 350) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (580, 350) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (580, 360) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (580, 360) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (590, 370) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (590, 370) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (600, 380) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (600, 380) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (600, 390) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (600, 390) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (610, 400) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (610, 400) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (620, 410) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (620, 410) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (620, 420) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (620, 420) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (630, 430) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (630, 430) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (630, 440) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (630, 440) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (640, 450) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (640, 450) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (650, 460) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (650, 460) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (650, 470) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (650, 470) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (660, 480) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (660, 480) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (670, 490) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (670, 490) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (670, 500) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (670, 500) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (680, 510) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (680, 510) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (680, 520) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (680, 520) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (690, 530) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (690, 530) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (700, 540) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (700, 540) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (700, 550) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (700, 550) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (710, 560) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (710, 560) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (710, 570) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (710, 570) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (720, 580) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (720, 580) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (730, 590) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (730, 590) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (730, 600) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (730, 600) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (740, 610) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (740, 610) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (750, 620) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (750, 620) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (750, 630) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (750, 630) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (760, 640) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (760, 640) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (760, 650) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (760, 650) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (770, 660) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (770, 660) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (780, 670) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (780, 670) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (780, 680) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (780, 680) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (790, 690) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (790, 690) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (440, 130) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (440, 130) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (450, 140) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (450, 140) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (460, 150) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (460, 150) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (460, 160) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (460, 160) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (470, 170) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (470, 170) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (470, 180) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (470, 180) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (420, 190) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (420, 190) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (490, 200) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (490, 200) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (430, 210) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (430, 210) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (440, 220) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (440, 220) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (500, 230) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (500, 230) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (510, 240) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (510, 240) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (520, 250) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (520, 250) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (520, 260) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (520, 260) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (530, 270) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (530, 270) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (540, 280) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (540, 280) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (540, 290) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (540, 290) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (550, 300) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (550, 300) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (550, 310) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (550, 310) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (560, 320) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (560, 320) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (570, 330) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (570, 330) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (570, 340) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (570, 340) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (580, 350) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (580, 350) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (580, 360) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (580, 360) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (590, 370) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (590, 370) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (600, 380) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (600, 380) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (600, 390) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (600, 390) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (610, 400) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (610, 400) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (620, 410) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (620, 410) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (620, 420) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (620, 420) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (630, 430) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (630, 430) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (630, 440) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (630, 440) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (640, 450) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (640, 450) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (650, 460) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (650, 460) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (650, 470) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (650, 470) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (660, 480) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (660, 480) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (670, 490) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (670, 490) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (670, 500) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (670, 500) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (680, 510) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (680, 510) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (680, 520) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (680, 520) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (690, 530) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (690, 530) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (700, 540) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (700, 540) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (700, 550) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (700, 550) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (710, 560) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (710, 560) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (710, 570) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (710, 570) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (720, 580) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (720, 580) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (730, 590) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (730, 590) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (730, 600) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (730, 600) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (740, 610) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (740, 610) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (750, 620) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (750, 620) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (750, 630) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (750, 630) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (760, 640) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (760, 640) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (760, 650) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (760, 650) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (770, 660) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (770, 660) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (780, 670) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (780, 670) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (780, 680) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (780, 680) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The mllbb mass distribution for the mbb window defined for (mA, mH) = (790, 690) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (790, 690) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (400, 200) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (400, 200) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (430, 210) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (430, 210) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (440, 220) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (440, 220) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (500, 230) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (500, 230) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (510, 240) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (510, 240) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (520, 250) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (520, 250) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (520, 260) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (520, 260) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (530, 270) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (530, 270) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (540, 280) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (540, 280) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (540, 290) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (540, 290) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (550, 300) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (550, 300) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (550, 310) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (550, 310) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (560, 320) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (560, 320) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (570, 330) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (570, 330) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (570, 340) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (570, 340) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (580, 350) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (580, 350) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (580, 360) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (580, 360) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (590, 370) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (590, 370) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (600, 380) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (600, 380) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (600, 390) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (600, 390) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (610, 400) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (610, 400) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (620, 410) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (620, 410) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (620, 420) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (620, 420) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (630, 430) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (630, 430) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (630, 440) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (630, 440) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (640, 450) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (640, 450) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (650, 460) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (650, 460) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (650, 470) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (650, 470) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (660, 480) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (660, 480) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (670, 490) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (670, 490) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (670, 500) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (670, 500) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (680, 510) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (680, 510) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (680, 520) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (680, 520) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (690, 530) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (690, 530) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (700, 540) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (700, 540) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (700, 550) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (700, 550) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (710, 560) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (710, 560) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (710, 570) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (710, 570) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (720, 580) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (720, 580) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (730, 590) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (730, 590) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (730, 600) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (730, 600) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (740, 610) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (740, 610) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (750, 620) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (750, 620) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (750, 630) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (750, 630) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (760, 640) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (760, 640) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (760, 650) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (760, 650) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (770, 660) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (770, 660) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (780, 670) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (780, 670) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (780, 680) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (780, 680) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (790, 690) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (790, 690) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
The m2l4q mass distribution for the m4q window defined for (mA, mH) = (800, 700) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (800, 700) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.
Several extensions of the Standard Model predict the production of dark matter particles at the LHC. An uncharted signature of dark matter particles produced in association with $VV=W^\pm W^\mp$ or $ZZ$ pairs from a decay of a dark Higgs boson $s$ is searched for using 139 fb$^{-1}$ of $pp$ collisions recorded by the ATLAS detector at a center-of-mass energy of 13 TeV. The $s\to V(q\bar q)V(q\bar q)$ decays are reconstructed with a novel technique aimed at resolving the dense topology from boosted $VV$ pairs using jets in the calorimeter and tracking information. Dark Higgs scenarios with $m_s > 160$ GeV are excluded.
Data overlaid on SM background post-fit yields stacked in each SR and CR category and E<sub>T</sub><sup>miss</sup> bin with the maximum-likelihood estimators set to the conditional values of the CR-only fit, and propagated to SR and CRs. Pre-fit uncertainties cover differences between the data and pre-fit background prediction.
Dominant sources of uncertainty for three dark Higgs scenarios after the fit to Asimov data generated from the expected values of the maximum-likelihood estimators including predicted signals with m<sub>Z'</sub> = 1 TeV and m<sub>s</sub> of (a) 160 GeV, (b) 235 GeV, and (c) 310 GeV. The uncertainty in the fitted signal yield relative to the theory prediction is presented. Total is the quadrature sum of statistical and total systematic uncertainties, which consider correlations.
The ratios (μ) of the 95% C.L. upper limits on the combined s→ W<sup>±</sup>W<sup>∓</sup> and s→ ZZ cross section to simplified model expectations for the m<sub>Z'</sub>=0.5 TeV scenario, for various m<sub>s</sub> hypotheses. The observed limits (solid line) are consistent with the expectation under the SM-only hypothesis (dashed line) within uncertainties (filled band), except for a small excess for m<sub>s</sub>=160 GeV, discussed in the text.
The ratios (μ) of the 95% C.L. upper limits on the combined s→ W<sup>±</sup>W<sup>∓</sup> and s→ ZZ cross section to simplified model expectations for the m<sub>Z'</sub>=1 TeV scenario, for various m<sub>s</sub> hypotheses. The observed limits (solid line) are consistent with the expectation under the SM-only hypothesis (dashed line) within uncertainties (filled band), except for a small excess for m<sub>s</sub>=160 GeV, discussed in the text.
The ratios (μ) of the 95% C.L. upper limits on the combined s→ W<sup>±</sup>W<sup>∓</sup> and s→ ZZ cross section to simplified model expectations for the m<sub>Z'</sub>=1.7 TeV scenario, for various m<sub>s</sub> hypotheses. The observed limits (solid line) are consistent with the expectation under the SM-only hypothesis (dashed line) within uncertainties (filled band), except for a small excess for m<sub>s</sub>=160 GeV, discussed in the text.
Observed upper limits at 95% C.L. on σ(pp → s χχ) × B(s→ VV) for m<sub>Z'</sub>=0.5 TeV signal points. The expected limits, varied up and down by one and two standard deviations, are shown as green and yellow bands, respectively. The observed and expected limits are compared to the theoretical LO cross section for the σ(pp → s χχ) × B(s→ VV) process for m<sub>Z'</sub>=0.5 TeV, shown in dashed blue.
Observed upper limits at 95% C.L. on σ(pp → s χχ) × B(s→ VV) for m<sub>Z'</sub>=1 TeV signal points. The expected limits, varied up and down by one and two standard deviations, are shown as green and yellow bands, respectively. The observed and expected limits are compared to the theoretical LO cross section for the σ(pp → s χχ) × B(s→ VV) process for m<sub>Z'</sub>=1 TeV, shown in dashed blue.
Observed upper limits at 95% C.L. on σ(pp → s χχ) × B(s→ VV) for m<sub>Z'</sub>=1.7 TeV signal points. The expected limits, varied up and down by one and two standard deviations, are shown as green and yellow bands, respectively. The observed and expected limits are compared to the theoretical LO cross section for the σ(pp → s χχ) × B(s→ VV) process for m<sub>Z'</sub>=1.7 TeV, shown in dashed blue.
SM background post-fit yields stacked in each SR and CR category and E<sub>T</sub><sup>miss</sup> bin and data overlaid with the maximum likelihood estimators set to the conditional values of the combined signal and control region fit. The hatched uncertainty band shown includes simulation statistics uncertainties, experimental systematic uncertainties, and V+jets theory modelling systematic uncertainties. Pre-fit uncertainties cover differences between the data and pre-fit background prediction.
Cumulative efficiencies for the merged category for signal samples with m<sub>s</sub>=160 GeV (a), m<sub>s</sub>=235 GeV (b) and m<sub>s</sub>=310 GeV (c), each with m<sub>Z'</sub>=1 TeV. The dark Higgs candidate selection includes stringent jet substructure requirements and typically at most one candidate is present in signal events. Here, Δ φ<sub>jets<sub>1,2,3</sub> E<sub>T</sub><sup>miss</sup></sub> is the smallest azimuthal angle between the E<sub>T</sub><sup>miss</sup> and any of the three highest-p<sub>T</sub> (leading) small-R jets.
Cumulative efficiencies for the intermediate category for signal samples with m<sub>s</sub>=160 GeV (a), m<sub>s</sub>=235 GeV (b) and m<sub>s</sub>=310 GeV (c), each with m<sub>Z'</sub>=1 TeV. The TAR+Comb algorithm reconstructs the dark Higgs candidate from a TAR jet with m<sup>TAR</sup>>60 GeV that is supplemented by up to two additional small-R jets within ΔR<sub>cone</sub>=2.5 of the TAR jet. Here, Δ φ<sub>jets<sub>1,2,3</sub> E<sub>T</sub><sup>miss</sup></sub> is the smallest azimuthal angle between the E<sub>T</sub><sup>miss</sup> and any of the three highest-p<sub>T</sub> (leading) small-R jets. For details see text.
The product of acceptance and efficiency (A × ϵ), defined as the number of signal events satisfying the full set of selection criteria in the merged or intermediate signal regions, divided by the total number of generated signal events, for the s(W<sup>±</sup>W<sup>∓</sup>) dark Higgs signal points with dark Higgs boson mass m<sub>s</sub> and Z' boson mass m<sub>Z'</sub>.
The product of acceptance and efficiency (A × ϵ), defined as the number of signal events satisfying the full set of selection criteria in the merged or intermediate signal regions, divided by the total number of generated signal events, for the s(ZZ) dark Higgs signal points with dark Higgs boson mass m<sub>s</sub> and Z' boson mass m<sub>Z'</sub>.
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