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Global polarization of $\Xi$ and $\Omega$ hyperons has been measured for the first time in Au+Au collisions at $\sqrt{s_{_{NN}}}$ = 200 GeV. The measurements of the $\Xi^-$ and $\bar{\Xi}^+$ hyperon polarization have been performed by two independent methods, via analysis of the angular distribution of the daughter particles in the parity violating weak decay $\Xi\rightarrow\Lambda+\pi$, as well as by measuring the polarization of the daughter $\Lambda$-hyperon, polarized via polarization transfer from its parent. The polarization, obtained by combining the results from the two methods and averaged over $\Xi^-$ and $\bar{\Xi}^+$, is measured to be $\langle P_\Xi \rangle = 0.47\pm0.10~({\rm stat.})\pm0.23~({\rm syst.})\,\%$ for the collision centrality 20%-80%. The $\langle P_\Xi \rangle$ is found to be slightly larger than the inclusive $\Lambda$ polarization and in reasonable agreement with a multi-phase transport model (AMPT). The $\langle P_\Xi \rangle$ is found to follow the centrality dependence of the vorticity predicted in the model, increasing toward more peripheral collisions. The global polarization of $\Omega$, $\langle P_\Omega \rangle = 1.11\pm0.87~({\rm stat.})\pm1.97~({\rm syst.})\,\%$ was obtained by measuring the polarization of daughter $\Lambda$ in the decay $\Omega \rightarrow \Lambda + K$, assuming the polarization transfer factor $C_{\Omega\Lambda}=1$.
$\Xi$ and $\Omega$ global polarization in Au+Au collisions at 200 GeV. Decay parameter from PDG2020, $\alpha_{\Xi}$=-$\alpha_{\bar{\Xi}}$=-0.401, is used.
The energy dependence of $\Lambda$ and $\bar{\Lambda}$ global polarization. Note that the results from previous measurements are rescaled using updated decay parameters (PDG2020), $\alpha_{\Lambda}$=0.732 and $\alpha_{\bar{\Lambda}}$=-0.758. The original data can be found in <a href="https://www.hepdata.net/record/ins1510474">this page</a>.
Centrality dependence of $\Xi$ global poalrization in Au+Au collisions at 200 GeV. Decay parameter from PDG2020, $\alpha_{\Xi}$=-$\alpha_{\bar{\Xi}}$=-0.401, is used.
Centrality dependence of $\Lambda$ global polarization in Au+Au collisions at 200 GeV. Note that the results from previous measurement are rescaled using updated decay parameters (PDG2020), $\alpha_{\Lambda}$=0.732. The original data can be found in <a href="https://www.hepdata.net/record/ins1672785">this page</a>.
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.
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 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 SR4Jlx b-Veto bin3 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Tag bin2 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 SR6J b-Tag bin4 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J b-Veto bin1 region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR6J 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 SR6J b-Veto bin4 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 discovery low region for gluino production one-step x = 1/2 simplified models
Signal acceptance in SR2J b-Tag bin1 region for gluino production one-step variable-x simplified models
Signal acceptance in SR2J b-Tag bin2 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 SR2J b-Veto bin1 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 SR2J b-Veto bin3 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 SR2J discovery low 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 SR4Jhx b-Tag bin1 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 SR4Jhx b-Tag bin3 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 SR4Jhx b-Veto bin2 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 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
Modifications to the distribution of charged particles with respect to high transverse momentum ($p_\mathrm{T}$) jets passing through a quark-gluon plasma are explored using the CMS detector. Back-to-back dijets are analyzed in lead-lead and proton-proton collisions at $\sqrt{s_\mathrm{NN}} =$ 5.02 TeV via correlations of charged particles in bins of relative pseudorapidity and angular distance from the leading and subleading jet axes. In comparing the lead-lead and proton-proton collision results, modifications to the charged-particle relative distance distribution and to the momentum distributions around the jet axis are found to depend on the dijet momentum balance $x_j$, which is the ratio between the subleading and leading jet $p_\mathrm{T}$. For events with $x_j$$\approx$ 1, these modifications are observed for both the leading and subleading jets. However, while subleading jets show significant modifications for events with a larger dijet momentum imbalance, much smaller modifications are found for the leading jets in these events.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in pp collisions. The results are shown in different dijet momentum balance bins.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $0.7 < p_{\mathrm{T}}^{\mathrm{ch}} < 1$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $0.7 < p_{\mathrm{T}}^{\mathrm{ch}} < 1$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $0.7 < p_{\mathrm{T}}^{\mathrm{ch}} < 1$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $0.7 < p_{\mathrm{T}}^{\mathrm{ch}} < 1$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $0.7 < p_{\mathrm{T}}^{\mathrm{ch}} < 1$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $1 < p_{\mathrm{T}}^{\mathrm{ch}} < 2$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $1 < p_{\mathrm{T}}^{\mathrm{ch}} < 2$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $1 < p_{\mathrm{T}}^{\mathrm{ch}} < 2$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $1 < p_{\mathrm{T}}^{\mathrm{ch}} < 2$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $1 < p_{\mathrm{T}}^{\mathrm{ch}} < 2$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $2 < p_{\mathrm{T}}^{\mathrm{ch}} < 3$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $2 < p_{\mathrm{T}}^{\mathrm{ch}} < 3$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $2 < p_{\mathrm{T}}^{\mathrm{ch}} < 3$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $2 < p_{\mathrm{T}}^{\mathrm{ch}} < 3$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $2 < p_{\mathrm{T}}^{\mathrm{ch}} < 3$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $3 < p_{\mathrm{T}}^{\mathrm{ch}} < 4$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $3 < p_{\mathrm{T}}^{\mathrm{ch}} < 4$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $3 < p_{\mathrm{T}}^{\mathrm{ch}} < 4$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $3 < p_{\mathrm{T}}^{\mathrm{ch}} < 4$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $3 < p_{\mathrm{T}}^{\mathrm{ch}} < 4$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $4 < p_{\mathrm{T}}^{\mathrm{ch}} < 8$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $4 < p_{\mathrm{T}}^{\mathrm{ch}} < 8$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $4 < p_{\mathrm{T}}^{\mathrm{ch}} < 8$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $4 < p_{\mathrm{T}}^{\mathrm{ch}} < 8$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $4 < p_{\mathrm{T}}^{\mathrm{ch}} < 8$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $8 < p_{\mathrm{T}}^{\mathrm{ch}} < 12$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $8 < p_{\mathrm{T}}^{\mathrm{ch}} < 12$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $8 < p_{\mathrm{T}}^{\mathrm{ch}} < 12$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $8 < p_{\mathrm{T}}^{\mathrm{ch}} < 12$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $8 < p_{\mathrm{T}}^{\mathrm{ch}} < 12$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in pp collisions. The results are shown in different dijet momentum balance bins.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $0.7 < p_{\mathrm{T}}^{\mathrm{ch}} < 1$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $0.7 < p_{\mathrm{T}}^{\mathrm{ch}} < 1$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $0.7 < p_{\mathrm{T}}^{\mathrm{ch}} < 1$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $0.7 < p_{\mathrm{T}}^{\mathrm{ch}} < 1$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $0.7 < p_{\mathrm{T}}^{\mathrm{ch}} < 1$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $1 < p_{\mathrm{T}}^{\mathrm{ch}} < 2$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $1 < p_{\mathrm{T}}^{\mathrm{ch}} < 2$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $1 < p_{\mathrm{T}}^{\mathrm{ch}} < 2$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $1 < p_{\mathrm{T}}^{\mathrm{ch}} < 2$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $1 < p_{\mathrm{T}}^{\mathrm{ch}} < 2$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $2 < p_{\mathrm{T}}^{\mathrm{ch}} < 3$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $2 < p_{\mathrm{T}}^{\mathrm{ch}} < 3$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $2 < p_{\mathrm{T}}^{\mathrm{ch}} < 3$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $2 < p_{\mathrm{T}}^{\mathrm{ch}} < 3$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $2 < p_{\mathrm{T}}^{\mathrm{ch}} < 3$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $3 < p_{\mathrm{T}}^{\mathrm{ch}} < 4$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $3 < p_{\mathrm{T}}^{\mathrm{ch}} < 4$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $3 < p_{\mathrm{T}}^{\mathrm{ch}} < 4$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $3 < p_{\mathrm{T}}^{\mathrm{ch}} < 4$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $3 < p_{\mathrm{T}}^{\mathrm{ch}} < 4$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $4 < p_{\mathrm{T}}^{\mathrm{ch}} < 8$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $4 < p_{\mathrm{T}}^{\mathrm{ch}} < 8$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $4 < p_{\mathrm{T}}^{\mathrm{ch}} < 8$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $4 < p_{\mathrm{T}}^{\mathrm{ch}} < 8$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $4 < p_{\mathrm{T}}^{\mathrm{ch}} < 8$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $8 < p_{\mathrm{T}}^{\mathrm{ch}} < 12$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $8 < p_{\mathrm{T}}^{\mathrm{ch}} < 12$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $8 < p_{\mathrm{T}}^{\mathrm{ch}} < 12$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $8 < p_{\mathrm{T}}^{\mathrm{ch}} < 12$ GeV.
The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $8 < p_{\mathrm{T}}^{\mathrm{ch}} < 12$ GeV.
The leading jet radial momentum profiles in pp and PbPb collisions and a function of $\Delta r$. The PbPb results are shown for different centrality regions.
The leading jet radial momentum profiles in pp and PbPb collisions and a function of $\Delta r$ for the charged particle $p_{\mathrm{T}}$ bin $0.7 < p_{\mathrm{T}}^{\mathrm{ch}} < 1$ GeV. The PbPb results are shown for different centrality regions.
The leading jet radial momentum profiles in pp and PbPb collisions and a function of $\Delta r$ for the charged particle $p_{\mathrm{T}}$ bin $1 < p_{\mathrm{T}}^{\mathrm{ch}} < 2$ GeV. The PbPb results are shown for different centrality regions.
The leading jet radial momentum profiles in pp and PbPb collisions and a function of $\Delta r$ for the charged particle $p_{\mathrm{T}}$ bin $2 < p_{\mathrm{T}}^{\mathrm{ch}} < 3$ GeV. The PbPb results are shown for different centrality regions.
The leading jet radial momentum profiles in pp and PbPb collisions and a function of $\Delta r$ for the charged particle $p_{\mathrm{T}}$ bin $3 < p_{\mathrm{T}}^{\mathrm{ch}} < 4$ GeV. The PbPb results are shown for different centrality regions.
The leading jet radial momentum profiles in pp and PbPb collisions and a function of $\Delta r$ for the charged particle $p_{\mathrm{T}}$ bin $4 < p_{\mathrm{T}}^{\mathrm{ch}} < 8$ GeV. The PbPb results are shown for different centrality regions.
The leading jet radial momentum profiles in pp and PbPb collisions and a function of $\Delta r$ for the charged particle $p_{\mathrm{T}}$ bin $8 < p_{\mathrm{T}}^{\mathrm{ch}} < 12$ GeV. The PbPb results are shown for different centrality regions.
The leading jet radial momentum profiles in pp and PbPb collisions and a function of $\Delta r$ for the charged particle $p_{\mathrm{T}}$ bin $12 < p_{\mathrm{T}}^{\mathrm{ch}} < 300$ GeV. The PbPb results are shown for different centrality regions.
The subleading jet radial momentum profiles in pp and PbPb collisions as a function of $\Delta r$. The PbPb results are shown for different centrality regions.
The subleading jet radial momentum profiles in pp and PbPb collisions as a function of $\Delta r$ for the charged particle $p_{\mathrm{T}}$ bin $0.7 < p_{\mathrm{T}}^{\mathrm{ch}} < 1$ GeV. The PbPb results are shown for different centrality regions.
The subleading jet radial momentum profiles in pp and PbPb collisions as a function of $\Delta r$ for the charged particle $p_{\mathrm{T}}$ bin $1 < p_{\mathrm{T}}^{\mathrm{ch}} < 2$ GeV. The PbPb results are shown for different centrality regions.
The subleading jet radial momentum profiles in pp and PbPb collisions as a function of $\Delta r$ for the charged particle $p_{\mathrm{T}}$ bin $2 < p_{\mathrm{T}}^{\mathrm{ch}} < 3$ GeV. The PbPb results are shown for different centrality regions.
The subleading jet radial momentum profiles in pp and PbPb collisions as a function of $\Delta r$ for the charged particle $p_{\mathrm{T}}$ bin $3 < p_{\mathrm{T}}^{\mathrm{ch}} < 4$ GeV. The PbPb results are shown for different centrality regions.
The subleading jet radial momentum profiles in pp and PbPb collisions as a function of $\Delta r$ for the charged particle $p_{\mathrm{T}}$ bin $4 < p_{\mathrm{T}}^{\mathrm{ch}} < 8$ GeV. The PbPb results are shown for different centrality regions.
The subleading jet radial momentum profiles in pp and PbPb collisions as a function of $\Delta r$ for the charged particle $p_{\mathrm{T}}$ bin $8 < p_{\mathrm{T}}^{\mathrm{ch}} < 12$ GeV. The PbPb results are shown for different centrality regions.
The subleading jet radial momentum profiles in pp and PbPb collisions as a function of $\Delta r$ for the charged particle $p_{\mathrm{T}}$ bin $12 < p_{\mathrm{T}}^{\mathrm{ch}} < 300$ GeV. The PbPb results are shown for different centrality regions.
The ratio between leading jet radial momentum profiles in PbPb and pp collisions as a function of $\Delta r$.
The ratio between subleading jet radial momentum profiles in PbPb and pp collisions as a function of $\Delta r$.
Jet shapes for leading jets in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins.
Jet shapes for leading jets in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins.
Jet shapes for leading jets in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins.
Jet shapes for leading jets in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins.
Jet shapes for leading jets in pp collisions. The results are shown in different dijet momentum balance bins.
Jet shapes for leading jets in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $0.7 < p_{\mathrm{T}}^{\mathrm{ch}} < 1$ GeV.
Jet shapes for leading jets in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $0.7 < p_{\mathrm{T}}^{\mathrm{ch}} < 1$ GeV.
Jet shapes for leading jets in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $0.7 < p_{\mathrm{T}}^{\mathrm{ch}} < 1$ GeV.
Jet shapes for leading jets in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $0.7 < p_{\mathrm{T}}^{\mathrm{ch}} < 1$ GeV.
Jet shapes for leading jets in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $0.7 < p_{\mathrm{T}}^{\mathrm{ch}} < 1$ GeV.
Jet shapes for leading jets in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $1 < p_{\mathrm{T}}^{\mathrm{ch}} < 2$ GeV.
Jet shapes for leading jets in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $1 < p_{\mathrm{T}}^{\mathrm{ch}} < 2$ GeV.
Jet shapes for leading jets in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $1 < p_{\mathrm{T}}^{\mathrm{ch}} < 2$ GeV.
Jet shapes for leading jets in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $1 < p_{\mathrm{T}}^{\mathrm{ch}} < 2$ GeV.
Jet shapes for leading jets in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $1 < p_{\mathrm{T}}^{\mathrm{ch}} < 2$ GeV.
Jet shapes for leading jets in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $2 < p_{\mathrm{T}}^{\mathrm{ch}} < 3$ GeV.
Jet shapes for leading jets in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $2 < p_{\mathrm{T}}^{\mathrm{ch}} < 3$ GeV.
Jet shapes for leading jets in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $2 < p_{\mathrm{T}}^{\mathrm{ch}} < 3$ GeV.
Jet shapes for leading jets in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $2 < p_{\mathrm{T}}^{\mathrm{ch}} < 3$ GeV.
Jet shapes for leading jets in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $2 < p_{\mathrm{T}}^{\mathrm{ch}} < 3$ GeV.
Jet shapes for leading jets in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $3 < p_{\mathrm{T}}^{\mathrm{ch}} < 4$ GeV.
Jet shapes for leading jets in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $3 < p_{\mathrm{T}}^{\mathrm{ch}} < 4$ GeV.
Jet shapes for leading jets in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $3 < p_{\mathrm{T}}^{\mathrm{ch}} < 4$ GeV.
Jet shapes for leading jets in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $3 < p_{\mathrm{T}}^{\mathrm{ch}} < 4$ GeV.
Jet shapes for leading jets in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $3 < p_{\mathrm{T}}^{\mathrm{ch}} < 4$ GeV.
Jet shapes for leading jets in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $4 < p_{\mathrm{T}}^{\mathrm{ch}} < 8$ GeV.
Jet shapes for leading jets in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $4 < p_{\mathrm{T}}^{\mathrm{ch}} < 8$ GeV.
Jet shapes for leading jets in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $4 < p_{\mathrm{T}}^{\mathrm{ch}} < 8$ GeV.
Jet shapes for leading jets in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $4 < p_{\mathrm{T}}^{\mathrm{ch}} < 8$ GeV.
Jet shapes for leading jets in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $4 < p_{\mathrm{T}}^{\mathrm{ch}} < 8$ GeV.
Jet shapes for leading jets in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $8 < p_{\mathrm{T}}^{\mathrm{ch}} < 12$ GeV.
Jet shapes for leading jets in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $8 < p_{\mathrm{T}}^{\mathrm{ch}} < 12$ GeV.
Jet shapes for leading jets in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $8 < p_{\mathrm{T}}^{\mathrm{ch}} < 12$ GeV.
Jet shapes for leading jets in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $8 < p_{\mathrm{T}}^{\mathrm{ch}} < 12$ GeV.
Jet shapes for leading jets in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $8 < p_{\mathrm{T}}^{\mathrm{ch}} < 12$ GeV.
Jet shapes for leading jets in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $12 < p_{\mathrm{T}}^{\mathrm{ch}} < 300$ GeV.
Jet shapes for leading jets in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $12 < p_{\mathrm{T}}^{\mathrm{ch}} < 300$ GeV.
Jet shapes for leading jets in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $12 < p_{\mathrm{T}}^{\mathrm{ch}} < 300$ GeV.
Jet shapes for leading jets in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $12 < p_{\mathrm{T}}^{\mathrm{ch}} < 300$ GeV.
Jet shapes for leading jets in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $12 < p_{\mathrm{T}}^{\mathrm{ch}} < 300$ GeV.
Ratios of leading jet shapes between PbPb and pp collisions. The results from 0-10 % centrality bin in PbPb are compared to pp using several dijet momentum balance selections.
Ratios of leading jet shapes between PbPb and pp collisions. The results from 10-30 % centrality bin in PbPb are compared to pp using several dijet momentum balance selections.
Ratios of leading jet shapes between PbPb and pp collisions. The results from 30-50 % centrality bin in PbPb are compared to pp using several dijet momentum balance selections.
Ratios of leading jet shapes between PbPb and pp collisions. The results from 50-90 % centrality bin in PbPb are compared to pp using several dijet momentum balance selections.
Jet shapes for subleading jets in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins.
Jet shapes for subleading jets in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins.
Jet shapes for subleading jets in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins.
Jet shapes for subleading jets in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins.
Jet shapes for subleading jets in pp collisions. The results are shown in different dijet momentum balance bins.
Jet shapes for subleading jets in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $0.7 < p_{\mathrm{T}}^{\mathrm{ch}} < 1$ GeV.
Jet shapes for subleading jets in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $0.7 < p_{\mathrm{T}}^{\mathrm{ch}} < 1$ GeV.
Jet shapes for subleading jets in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $0.7 < p_{\mathrm{T}}^{\mathrm{ch}} < 1$ GeV.
Jet shapes for subleading jets in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $0.7 < p_{\mathrm{T}}^{\mathrm{ch}} < 1$ GeV.
Jet shapes for subleading jets in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $0.7 < p_{\mathrm{T}}^{\mathrm{ch}} < 1$ GeV.
Jet shapes for subleading jets in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $1 < p_{\mathrm{T}}^{\mathrm{ch}} < 2$ GeV.
Jet shapes for subleading jets in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $1 < p_{\mathrm{T}}^{\mathrm{ch}} < 2$ GeV.
Jet shapes for subleading jets in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $1 < p_{\mathrm{T}}^{\mathrm{ch}} < 2$ GeV.
Jet shapes for subleading jets in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $1 < p_{\mathrm{T}}^{\mathrm{ch}} < 2$ GeV.
Jet shapes for subleading jets in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $1 < p_{\mathrm{T}}^{\mathrm{ch}} < 2$ GeV.
Jet shapes for subleading jets in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $2 < p_{\mathrm{T}}^{\mathrm{ch}} < 3$ GeV.
Jet shapes for subleading jets in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $2 < p_{\mathrm{T}}^{\mathrm{ch}} < 3$ GeV.
Jet shapes for subleading jets in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $2 < p_{\mathrm{T}}^{\mathrm{ch}} < 3$ GeV.
Jet shapes for subleading jets in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $2 < p_{\mathrm{T}}^{\mathrm{ch}} < 3$ GeV.
Jet shapes for subleading jets in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $2 < p_{\mathrm{T}}^{\mathrm{ch}} < 3$ GeV.
Jet shapes for subleading jets in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $3 < p_{\mathrm{T}}^{\mathrm{ch}} < 4$ GeV.
Jet shapes for subleading jets in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $3 < p_{\mathrm{T}}^{\mathrm{ch}} < 4$ GeV.
Jet shapes for subleading jets in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $3 < p_{\mathrm{T}}^{\mathrm{ch}} < 4$ GeV.
Jet shapes for subleading jets in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $3 < p_{\mathrm{T}}^{\mathrm{ch}} < 4$ GeV.
Jet shapes for subleading jets in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $3 < p_{\mathrm{T}}^{\mathrm{ch}} < 4$ GeV.
Jet shapes for subleading jets in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $4 < p_{\mathrm{T}}^{\mathrm{ch}} < 8$ GeV.
Jet shapes for subleading jets in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $4 < p_{\mathrm{T}}^{\mathrm{ch}} < 8$ GeV.
Jet shapes for subleading jets in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $4 < p_{\mathrm{T}}^{\mathrm{ch}} < 8$ GeV.
Jet shapes for subleading jets in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $4 < p_{\mathrm{T}}^{\mathrm{ch}} < 8$ GeV.
Jet shapes for subleading jets in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $4 < p_{\mathrm{T}}^{\mathrm{ch}} < 8$ GeV.
Jet shapes for subleading jets in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $8 < p_{\mathrm{T}}^{\mathrm{ch}} < 12$ GeV.
Jet shapes for subleading jets in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $8 < p_{\mathrm{T}}^{\mathrm{ch}} < 12$ GeV.
Jet shapes for subleading jets in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $8 < p_{\mathrm{T}}^{\mathrm{ch}} < 12$ GeV.
Jet shapes for subleading jets in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $8 < p_{\mathrm{T}}^{\mathrm{ch}} < 12$ GeV.
Jet shapes for subleading jets in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $8 < p_{\mathrm{T}}^{\mathrm{ch}} < 12$ GeV.
Jet shapes for subleading jets in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $12 < p_{\mathrm{T}}^{\mathrm{ch}} < 300$ GeV.
Jet shapes for subleading jets in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $12 < p_{\mathrm{T}}^{\mathrm{ch}} < 300$ GeV.
Jet shapes for subleading jets in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $12 < p_{\mathrm{T}}^{\mathrm{ch}} < 300$ GeV.
Jet shapes for subleading jets in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $12 < p_{\mathrm{T}}^{\mathrm{ch}} < 300$ GeV.
Jet shapes for subleading jets in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $12 < p_{\mathrm{T}}^{\mathrm{ch}} < 300$ GeV.
Ratios of subleading jet shapes between PbPb and pp collisions. The results from 0-10 % centrality bin in PbPb are compared to pp using several dijet momentum balance selections.
Ratios of subleading jet shapes between PbPb and pp collisions. The results from 10-30 % centrality bin in PbPb are compared to pp using several dijet momentum balance selections.
Ratios of subleading jet shapes between PbPb and pp collisions. The results from 30-50 % centrality bin in PbPb are compared to pp using several dijet momentum balance selections.
Ratios of subleading jet shapes between PbPb and pp collisions. The results from 50-90 % centrality bin in PbPb are compared to pp using several dijet momentum balance selections.
Ratio between unbalanced selection of leading jet shapes to all leading jet shapes in pp and PbPb collisions. The PbPb results are shown for different centrality regions.
Ratio between balanced selection of leading jet shapes to all leading jet shapes in pp and PbPb collisions. The PbPb results are shown for different centrality regions.
Ratio between unbalanced selection of subleading jet shapes to all subleading jet shapes in pp and PbPb collisions. The PbPb results are shown for different centrality regions.
Ratio between balanced selection of subleading jet shapes to all subleading jet shapes in pp and PbPb collisions. The PbPb results are shown for different centrality regions.
Generator-level vs. reconstructed $x_{j}$ values in the analysis $x_{j}$ bins. The plots show the probability to find a generator level $x_{j}$ for a given reconstructed $x_{j}$.
Generator-level vs. reconstructed $x_{j}$ values in the analysis $x_{j}$ bins. The plots show the probability to find a reconstructed $x_{j}$ for a given generator level $x_{j}$.
Two-particle long-range azimuthal correlations are measured in photonuclear collisions using 1.7 nb$^{-1}$ of 5.02 TeV Pb+Pb collision data collected by the ATLAS experiment at the LHC. Candidate events are selected using a dedicated high-multiplicity photonuclear event trigger, a combination of information from the zero-degree calorimeters and forward calorimeters, and from pseudorapidity gaps constructed using calorimeter energy clusters and charged-particle tracks. Distributions of event properties are compared between data and Monte Carlo simulations of photonuclear processes. Two-particle correlation functions are formed using charged-particle tracks in the selected events, and a template-fitting method is employed to subtract the non-flow contribution to the correlation. Significant nonzero values of the second- and third-order flow coefficients are observed and presented as a function of charged-particle multiplicity and transverse momentum. The results are compared with flow coefficients obtained in proton-proton and proton-lead collisions in similar multiplicity ranges, and with theoretical expectations. The unique initial conditions present in this measurement provide a new way to probe the origin of the collective signatures previously observed only in hadronic collisions.
The measured $v_2$ and $v_3$ charged-particle anisotropies as a function of charged-particle multiplicity in photonuclear collisions
The measured $v_2$ and $v_3$ charged-particle anisotropies as a function of charged-particle transverse momentum in photonuclear collisions
We report on the first measurement of charm-strange meson $D_s^{\pm}$ production at midrapidity in Au+Au collisions at $\sqrt{s_{_{\rm NN}}}$ = 200 GeV from the STAR experiment. The yield ratio between strange ($D_{s}^{\pm}$) and non-strange ($D^{0}$) open-charm mesons is presented and compared to model calculations. A significant enhancement, relative to a PYTHIA simulation of $p$+$p$ collisions, is observed in the $D_{s}^{\pm}/D^0$ yield ratio in Au+Au collisions over a large range of collision centralities. Model calculations incorporating abundant strange-quark production in the quark-gluon plasma (QGP) and coalescence hadronization qualitatively reproduce the data. The transverse-momentum integrated yield ratio of $D_{s}^{\pm}/D^0$ at midrapidity is consistent with a prediction from a statistical hadronization model with the parameters constrained by the yields of light and strange hadrons measured at the same collision energy. These results suggest that the coalescence of charm quarks with strange quarks in the QGP plays an important role in $D_{s}^{\pm}$ meson production in heavy-ion collisions.
The $KK\pi$ invariant mass distribution (Counts per 8 MeV/$c^{2}$ bin) for right-sign combinations in 0-80% Au+Au collisions at $\sqrt{s_{_{\rm NN}}}$ = 200 GeV.
$D_s^{\pm}$ invariant yield as a function of $p_{T}$ in 0-10% centrality bin of Au+Au collisions at $\sqrt{s_{_{\rm NN}}}$ = 200 GeV. The $p_T$ bins are 1.5 < $p_T$ < 2.5 GeV/c, 2.5 < $p_T$ < 3.5 GeV/c, 3.5 < $p_T$ < 5.0 GeV/c and 5.0 < $p_T$ < 8.0 GeV/c.
$D_s^{\pm}$ invariant yield as a function of $p_{T}$ in 10-40% centrality bin of Au+Au collisions at $\sqrt{s_{_{\rm NN}}}$ = 200 GeV. The $p_T$ bins are 1.0 < $p_T$ < 2.0 GeV/c, 2.0 < $p_T$ < 2.5 GeV/c, 2.5 < $p_T$ < 3.5 GeV/c, 3.5 < $p_T$ < 5.0 GeV/c and 5.0 < $p_T$ < 8.0 GeV/c.
$D_s^{\pm}$ invariant yield as a function of $p_{T}$ in 40-80% centrality bin of Au+Au collisions at $\sqrt{s_{_{\rm NN}}}$ = 200 GeV. The $p_T$ bins are 1.5 < $p_T$ < 2.5 GeV/c, 2.5 < $p_T$ < 3.5 GeV/c, 3.5 < $p_T$ < 5.0 GeV/c and 5.0 < $p_T$ < 8.0 GeV/c.
$D_{s}/D^{0}$ yield ratio as a function of $p_{T}$ in 0-10% centrality bin of Au+Au collisions at $\sqrt{s_{_{\rm NN}}}$ = 200 GeV. The $p_T$ bins are 1.5 < $p_T$ < 2.5 GeV/c, 2.5 < $p_T$ < 3.5 GeV/c, 3.5 < $p_T$ < 5.0 GeV/c and 5.0 < $p_T$ < 8.0 GeV/c.
$D_{s}/D^{0}$ yield ratio as a function of $p_{T}$ in 10-40% centrality bin of Au+Au collisions at $\sqrt{s_{_{\rm NN}}}$ = 200 GeV. The $p_T$ bins are 1.0 < $p_T$ < 2.0 GeV/c, 2.0 < $p_T$ < 2.5 GeV/c, 2.5 < $p_T$ < 3.5 GeV/c, 3.5 < $p_T$ < 5.0 GeV/c and 5.0 < $p_T$ < 8.0 GeV/c.
$D_{s}/D^{0}$ yield ratio as a function of $p_{T}$ in 40-80% centrality bin of Au+Au collisions at $\sqrt{s_{_{\rm NN}}}$ = 200 GeV. The $p_T$ bins are 1.5 < $p_T$ < 2.5 GeV/c, 2.5 < $p_T$ < 3.5 GeV/c, 3.5 < $p_T$ < 5.0 GeV/c and 5.0 < $p_T$ < 8.0 GeV/c.
$D_{s}/D^{0}$ yield ratio as a function of $p_{T}$ in 10-20% centrality bin of Au+Au collisions at $\sqrt{s_{_{\rm NN}}}$ = 200 GeV. The $p_T$ bins are 1.5 < $p_T$ < 2.5 GeV/c, 2.5 < $p_T$ < 3.5 GeV/c, 3.5 < $p_T$ < 5.0 GeV/c and 5.0 < $p_T$ < 8.0 GeV/c.
$D_{s}/D^{0}$ yield ratio as a function of $p_{T}$ in 20-40% centrality bin of Au+Au collisions at $\sqrt{s_{_{\rm NN}}}$ = 200 GeV. The $p_T$ bins are 1.5 < $p_T$ < 2.5 GeV/c, 2.5 < $p_T$ < 3.5 GeV/c, 3.5 < $p_T$ < 5.0 GeV/c and 5.0 < $p_T$ < 8.0 GeV/c.
The integrated $D_{s}/D^{0}$ yield ratio within 1.5 < $p_{T}$ < 5.0 GeV/c as a function of collision centrality. The centrality bins are 60-80%, 40-60%, 20-40%, 10-20% and 0-10%.
A search for pair production of third-generation scalar leptoquarks decaying into a top quark and a $\tau$-lepton is presented. The search is based on a dataset of $pp$ collisions at $\sqrt{s}=13$ TeV recorded with the ATLAS detector during Run 2 of the Large Hadron Collider, corresponding to an integrated luminosity of 139 fb$^{-1}$. Events are selected if they have one light lepton (electron or muon) and at least one hadronically decaying $\tau$-lepton, or at least two light leptons. In addition, two or more jets, at least one of which must be identified as containing $b$-hadrons, are required. Six final states, defined by the multiplicity and flavour of lepton candidates, are considered in the analysis. Each of them is split into multiple event categories to simultaneously search for the signal and constrain several leading backgrounds. The signal-rich event categories require at least one hadronically decaying $\tau$-lepton candidate and exploit the presence of energetic final-state objects, which is characteristic of signal events. No significant excess above the Standard Model expectation is observed in any of the considered event categories, and 95% CL upper limits are set on the production cross section as a function of the leptoquark mass, for different assumptions about the branching fractions into $t\tau$ and $b\nu$. Scalar leptoquarks decaying exclusively into $t\tau$ are excluded up to masses of 1.43 TeV while, for a branching fraction of 50% into $t\tau$, the lower mass limit is 1.22 TeV.
Selection efficiency times acceptance summed over the seven signal regions as a function of $m_{\mathrm{LQ}_{3}^{\mathrm{d}}}$, assuming B = 1.
Summary of the observed and expected 95% CL upper limits on the cross section for $\mathrm{LQ}_{3}^{\mathrm{d}}$ pair production as a function of $m_{\mathrm{LQ}_{3}^{\mathrm{d}}}$ under the assumptions of B=1.
Summary of the observed and expected 95% CL upper limits on B as a function of $m_{\mathrm{LQ}_{3}^{\mathrm{d}}}$.
Cutflow of the preselection requirements (see Section 5) for $\mathrm{LQ}_{3}^{\mathrm{d}}$ signals with $m_{\mathrm{LQ}_{3}^{\mathrm{d}}}$=0.9, 1.1, and 1.3 TeV, assuming B=1. The yields correspond to an integrated luminosity of 139 fb$^{-1}$.
Cutflow of the signal region requirements in 1$\ell+\geq 1\tau$ channel (see Table 3) for $\mathrm{LQ}_{3}^{\mathrm{d}}$ signals with $m_{\mathrm{LQ}_{3}^{\mathrm{d}}}$=0.9, 1.1, and 1.3 TeV, assuming B=1. Events that satisfy the preselection requirements are considered. The yields correspond to an integrated luminosity of 139 fb$^{-1}$.
Cutflow of the signal region requirements in the 2$\ell$OS+$\geq 1\tau$ channel (see Table 4) for $\mathrm{LQ}_{3}^{\mathrm{d}}$ signals with $m_{\mathrm{LQ}_{3}^{\mathrm{d}}}$=0.9, 1.1, and 1.3 TeV, assuming B=1. Events that satisfy the preselection requirements are considered. The yields correspond to an integrated luminosity of 139 fb$^{-1}$.
Cutflow of the signal region requirements in the $2\ell$SS/$3\ell+\geq 1\tau$ channel (see Table 5) for $\mathrm{LQ}_{3}^{\mathrm{d}}$ signals with $m_{\mathrm{LQ}_{3}^{\mathrm{d}}}$=0.9, 1.1, and 1.3 TeV, assuming B=1. Events that satisfy the preselection requirements are considered. In this channel, two signal regions (SR-L and SR-H) are defined based on $p_{\mathrm{T}, 1}^{\tau}$, with SR-L and SR-H requiring $125< p_{\mathrm{T}, 1}^{\tau} < 225$ GeV and $p_{\mathrm{T}, 1}^{\tau}>225$ GeV, respectively. The yields correspond 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$).
We report a systematic measurement of cumulants, $C_{n}$, for net-proton, proton and antiproton multiplicity distributions, and correlation functions, $\kappa_n$, for proton and antiproton multiplicity distributions up to the fourth order in Au+Au collisions at $\sqrt{s_{\mathrm {NN}}}$ = 7.7, 11.5, 14.5, 19.6, 27, 39, 54.4, 62.4 and 200 GeV. The $C_{n}$ and $\kappa_n$ are presented as a function of collision energy, centrality and kinematic acceptance in rapidity, $y$, and transverse momentum, $p_{T}$. The data were taken during the first phase of the Beam Energy Scan (BES) program (2010 -- 2017) at the BNL Relativistic Heavy Ion Collider (RHIC) facility. The measurements are carried out at midrapidity ($|y| <$ 0.5) and transverse momentum 0.4 $<$$p_{\rm T}$$<$ 2.0 GeV/$c$, using the STAR detector at RHIC. We observe a non-monotonic energy dependence ($\sqrt{s_{\mathrm {NN}}}$ = 7.7 -- 62.4 GeV) of the net-proton $C_{4}$/$C_{2}$ with the significance of 3.1$\sigma$ for the 0-5% central Au+Au collisions. This is consistent with the expectations of critical fluctuations in a QCD-inspired model. Thermal and transport model calculations show a monotonic variation with $\sqrt{s_{\mathrm {NN}}}$. For the multiparticle correlation functions, we observe significant negative values for a two-particle correlation function, $\kappa_2$, of protons and antiprotons, which are mainly due to the effects of baryon number conservation. Furthermore, it is found that the four-particle correlation function, $\kappa_4$, of protons plays a role in determining the energy dependence of proton $C_4/C_1$ below 19.6 GeV, which cannot be understood by the effect of baryon number conservation.
Reference charged particle multiplicity distributions using only pions and kaons ...
Reference charged particle multiplicity distributions using only pions and kaons ...
Reference charged particle multiplicity distributions using only pions and kaons ...
Reference charged particle multiplicity distributions using only pions and kaons ...
Reference charged particle multiplicity distributions using only pions and kaons ...
Reference charged particle multiplicity distributions using only pions and kaons ...
Reference charged particle multiplicity distributions using only pions and kaons ...
Reference charged particle multiplicity distributions using only pions and kaons ...
Reference charged particle multiplicity distributions using only pions and kaons ...
$\Delta N_\mathrm{p}$ multiplicity distributions in Au+Au collisions at various $\sqrt{s_\text{NN}}$ for 0-5%, ...
$\Delta N_\mathrm{p}$ multiplicity distributions in Au+Au collisions at various $\sqrt{s_\text{NN}}$ for 0-5%, ...
$\Delta N_\mathrm{p}$ multiplicity distributions in Au+Au collisions at various $\sqrt{s_\text{NN}}$ for 0-5%, ...
$\Delta N_\mathrm{p}$ multiplicity distributions in Au+Au collisions at various $\sqrt{s_\text{NN}}$ for 0-5%, ...
$\Delta N_\mathrm{p}$ multiplicity distributions in Au+Au collisions at various $\sqrt{s_\text{NN}}$ for 0-5%, ...
$\Delta N_\mathrm{p}$ multiplicity distributions in Au+Au collisions at various $\sqrt{s_\text{NN}}$ for 0-5%, ...
$\Delta N_\mathrm{p}$ multiplicity distributions in Au+Au collisions at various $\sqrt{s_\text{NN}}$ for 0-5%, ...
$\Delta N_\mathrm{p}$ multiplicity distributions in Au+Au collisions at various $\sqrt{s_\text{NN}}$ for 0-5%, ...
$\Delta N_\mathrm{p}$ multiplicity distributions in Au+Au collisions at various $\sqrt{s_\text{NN}}$ for 0-5%, ...
$\Delta N_\mathrm{p}$ multiplicity distributions in Au+Au collisions at various $\sqrt{s_\text{NN}}$ for 0-5%, ...
$\Delta N_\mathrm{p}$ multiplicity distributions in Au+Au collisions at various $\sqrt{s_\text{NN}}$ for 0-5%, ...
$\Delta N_\mathrm{p}$ multiplicity distributions in Au+Au collisions at various $\sqrt{s_\text{NN}}$ for 0-5%, ...
$\Delta N_\mathrm{p}$ multiplicity distributions in Au+Au collisions at various $\sqrt{s_\text{NN}}$ for 0-5%, ...
$\Delta N_\mathrm{p}$ multiplicity distributions in Au+Au collisions at various $\sqrt{s_\text{NN}}$ for 0-5%, ...
$\Delta N_\mathrm{p}$ multiplicity distributions in Au+Au collisions at various $\sqrt{s_\text{NN}}$ for 0-5%, ...
$\Delta N_\mathrm{p}$ multiplicity distributions in Au+Au collisions at various $\sqrt{s_\text{NN}}$ for 0-5%, ...
$\Delta N_\mathrm{p}$ multiplicity distributions in Au+Au collisions at various $\sqrt{s_\text{NN}}$ for 0-5%, ...
$\Delta N_\mathrm{p}$ multiplicity distributions in Au+Au collisions at various $\sqrt{s_\text{NN}}$ for 0-5%, ...
$\Delta N_\mathrm{p}$ multiplicity distributions in Au+Au collisions at various $\sqrt{s_\text{NN}}$ for 0-5%, ...
$\Delta N_\mathrm{p}$ multiplicity distributions in Au+Au collisions at various $\sqrt{s_\text{NN}}$ for 0-5%, ...
$\Delta N_\mathrm{p}$ multiplicity distributions in Au+Au collisions at various $\sqrt{s_\text{NN}}$ for 0-5%, ...
$\Delta N_\mathrm{p}$ multiplicity distributions in Au+Au collisions at various $\sqrt{s_\text{NN}}$ for 0-5%, ...
$\Delta N_\mathrm{p}$ multiplicity distributions in Au+Au collisions at various $\sqrt{s_\text{NN}}$ for 0-5%, ...
$\Delta N_\mathrm{p}$ multiplicity distributions in Au+Au collisions at various $\sqrt{s_\text{NN}}$ for 0-5%, ...
$\Delta N_\mathrm{p}$ multiplicity distributions in Au+Au collisions at various $\sqrt{s_\text{NN}}$ for 0-5%, ...
$\Delta N_\mathrm{p}$ multiplicity distributions in Au+Au collisions at various $\sqrt{s_\text{NN}}$ for 0-5%, ...
$\Delta N_\mathrm{p}$ multiplicity distributions in Au+Au collisions at various $\sqrt{s_\text{NN}}$ for 0-5%, ...
$C_{n}$ of net-proton distribution in Au+Au collisions at $\sqrt{s_{NN}}$ = 7.7 GeV as a function of $N_{part}$.
$C_{n}$ of net-proton distribution in Au+Au collisions at $\sqrt{s_{NN}}$ = 7.7 GeV as a function of $N_{part}$.
$C_{n}$ of net-proton distribution in Au+Au collisions at $\sqrt{s_{NN}}$ = 7.7 GeV as a function of $N_{part}$.
$C_{n}$ of net-proton distribution in Au+Au collisions at $\sqrt{s_{NN}}$ = 7.7 GeV as a function of $N_{part}$.
$C_{n}$ of net-proton distribution in Au+Au collisions at $\sqrt{s_{NN}}$ = 19.6 GeV as a function of $N_{part}$.
$C_{n}$ of net-proton distribution in Au+Au collisions at $\sqrt{s_{NN}}$ = 19.6 GeV as a function of $N_{part}$.
$C_{n}$ of net-proton distribution in Au+Au collisions at $\sqrt{s_{NN}}$ = 19.6 GeV as a function of $N_{part}$.
$C_{n}$ of net-proton distribution in Au+Au collisions at $\sqrt{s_{NN}}$ = 19.6 GeV as a function of $N_{part}$.
$C_{n}$ of net-proton distribution in Au+Au collisions at $\sqrt{s_{NN}}$ = 62.4 GeV as a function of $N_{part}$.
$C_{n}$ of net-proton distribution in Au+Au collisions at $\sqrt{s_{NN}}$ = 62.4 GeV as a function of $N_{part}$.
$C_{n}$ of net-proton distribution in Au+Au collisions at $\sqrt{s_{NN}}$ = 62.4 GeV as a function of $N_{part}$.
$C_{n}$ of net-proton distribution in Au+Au collisions at $\sqrt{s_{NN}}$ = 62.4 GeV as a function of $N_{part}$.
$\kappa\sigma^2$ as a function of collision energy for Au+Au collisions for 0-5% centrality.
Efficiency uncorrected $C_n$ of net-proton proton and anti-proton multiplicity distribution in Au+Au collisions at $\sqrt{s_\text{NN}}$ = 7.7 - 200 GeV as function of $\left\langle N_\text{part} \right\rangle$.
Efficiencies of proton and anti-proton as a function of $p_\mathrm{T}$ in Au+Au collisions for various $\sqrt{s_\text{NN}}$ and collision centralities.
Distribution of reconstructed protons from embedding simulations in 200 GeV top 2.5%-central Au+Au collisions.
Distribution of reconstructed protons from embedding simulations in 200 GeV top 2.5%-central Au+Au collisions.
Distribution of reconstructed protons from embedding simulations in 200 GeV top 2.5%-central Au+Au collisions.
Distribution of reconstructed protons from embedding simulations in 200 GeV top 2.5%-central Au+Au collisions.
Distribution of reconstructed protons from embedding simulations in 200 GeV top 2.5%-central Au+Au collisions.
Distribution of reconstructed protons from embedding simulations in 200 GeV top 2.5%-central Au+Au collisions.
Distribution of reconstructed protons from embedding simulations in 200 GeV top 2.5%-central Au+Au collisions.
Distribution of reconstructed protons from embedding simulations in 200 GeV top 2.5%-central Au+Au collisions.
Distribution of reconstructed protons from embedding simulations in 200 GeV top 2.5%-central Au+Au collisions.
Distribution of reconstructed protons from embedding simulations in 200 GeV top 2.5%-central Au+Au collisions.
Distribution of reconstructed protons from embedding simulations in 200 GeV top 2.5%-central Au+Au collisions.
Distribution of reconstructed protons from embedding simulations in 200 GeV top 2.5%-central Au+Au collisions.
Distribution of reconstructed protons from embedding simulations in 200 GeV top 2.5%-central Au+Au collisions.
Distribution of reconstructed protons from embedding simulations in 200 GeV top 2.5%-central Au+Au collisions.
Distribution of reconstructed protons from embedding simulations in 200 GeV top 2.5%-central Au+Au collisions.
Distribution of reconstructed protons from embedding simulations in 200 GeV top 2.5%-central Au+Au collisions.
Distribution of reconstructed protons from embedding simulations in 200 GeV top 2.5%-central Au+Au collisions.
Distribution of reconstructed protons from embedding simulations in 200 GeV top 2.5%-central Au+Au collisions.
Distribution of reconstructed protons from embedding simulations in 200 GeV top 2.5%-central Au+Au collisions.
Distribution of reconstructed protons from embedding simulations in 200 GeV top 2.5%-central Au+Au collisions.
Distribution of reconstructed protons from embedding simulations in 200 GeV top 2.5%-central Au+Au collisions.
Distribution of reconstructed protons from embedding simulations in 200 GeV top 2.5%-central Au+Au collisions.
Distribution of reconstructed protons from embedding simulations in 200 GeV top 2.5%-central Au+Au collisions.
Distribution of reconstructed protons from embedding simulations in 200 GeV top 2.5%-central Au+Au collisions.
Distribution of reconstructed protons from embedding simulations in 200 GeV top 2.5%-central Au+Au collisions.
Distribution of reconstructed protons from embedding simulations in 200 GeV top 2.5%-central Au+Au collisions.
Distribution of reconstructed protons from embedding simulations in 200 GeV top 2.5%-central Au+Au collisions.
Distribution of reconstructed protons from embedding simulations in 200 GeV top 2.5%-central Au+Au collisions.
Distribution of reconstructed protons from embedding simulations in 200 GeV top 2.5%-central Au+Au collisions.
Distribution of reconstructed protons from embedding simulations in 200 GeV top 2.5%-central Au+Au collisions.
Distribution of reconstructed protons from embedding simulations in 200 GeV top 2.5%-central Au+Au collisions.
Distribution of reconstructed protons from embedding simulations in 200 GeV top 2.5%-central Au+Au collisions.
Distribution of reconstructed protons from embedding simulations in 200 GeV top 2.5%-central Au+Au collisions.
Unfolded net-proton multiplicity distributions for $\sqrt{s_{NN}$ = 200 GeV Au+Au collisions.
Unfolded net-proton multiplicity distributions for $\sqrt{s_{NN}$ = 200 GeV Au+Au collisions.
Unfolded net-proton multiplicity distributions for $\sqrt{s_{NN}$ = 200 GeV Au+Au collisions.
Unfolded net-proton multiplicity distributions for $\sqrt{s_{NN}$ = 200 GeV Au+Au collisions.
Unfolded net-proton multiplicity distributions for $\sqrt{s_{NN}$ = 200 GeV Au+Au collisions.
Unfolded net-proton multiplicity distributions for $\sqrt{s_{NN}$ = 200 GeV Au+Au collisions.
Unfolded net-proton multiplicity distributions for $\sqrt{s_{NN}$ = 200 GeV Au+Au collisions.
Cumulant ratios as a function of $N_{part}$ for net-proton distributions in Au+Au collisions at $\sqrt{s_{NN}}$ = 200 GeV
Cumulant ratios as a function of $N_{part}$ for net-proton distributions in Au+Au collisions at $\sqrt{s_{NN}}$ = 200 GeV
Collision centrality dependence of proton, anti-proton and net-proton cumulants
Cumulants and their ratios as a function of $<N_{part}>$, for the net-proton distribution
Centrality dependence of normalized correlation functions $\kappa_n/$kappa_1$ for proton and anti-proton multiplicity distribution
Rapidity acceptance dependence of cumulants of proton, anti-proton and net-proton multiplicity distributions in 0-5% central Au+Au collision ...
Rapidity acceptance dependence of normalized correlation functions up to fourth order.
Rapidity-acceptance dependence of cumulant ratios of proton, anti-proton and net-proton multiplicity distributions in 0-5% central Au+Au collisions...
pT-acceptance dependence of cumulants of proton, anti-proton and net-proton multiplicity distributions for 0-5% central Au+Au collisions ...
pT-acceptance dependence of the normalized correlation functions up to fourth order ($\kappa_n/\kappa_1$, $n$ = 2, 3, 4) for proton and anti-proton multiplicity distributions in 0-5% central Au+Au collisions ...
pT-acceptance dependence of cumulant ratios of proton, anti-proton and net-proton multiplicity distributions for 0-5% central Au+Au collisions ...
Cumulant ratios from HRG model as a function of collision energy $\sqrt{s_{NN}}$
UrQMD results on pT acceptance dependence for cumulant ratios for proton and baryon
Polynomial fit of cumulant ratios as a function of collision energy $\sqrt{s_{NN}}$
Polynomial fit of cumulant ratios as a function of collision energy $\sqrt{s_{NN}}$
Polynomial fit of cumulant ratios as a function of collision energy $\sqrt{s_{NN}}$
Collision energy dependence of $C_2/C_1$, $C_3/C_2$ and $C_4/C_2$ for net-proton multiplicity distribution in 0-5% central Au+Au collisions. The expreimental net-proton measurements are compared to corresponding values from UrQMD and HRG models within the expreimental acceptances.
Collision energy dependence of $C_2/C_1$, $C_3/C_2$ and $C_4/C_2$ for net-proton multiplicity distribution in 0-5% central Au+Au collisions. The expreimental net-proton measurements are compared to corresponding values from UrQMD and HRG models within the expreimental acceptances.
Collision energy dependence of $C_2/C_1$, $C_3/C_2$ and $C_4/C_2$ for net-proton multiplicity distribution in 0-5% central Au+Au collisions. The expreimental net-proton measurements are compared to corresponding values from UrQMD and HRG models within the expreimental acceptances.
Collision energy dependence of $C_2/C_1$, $C_3/C_2$ and $C_4/C_2$ for net-proton multiplicity distribution in 0-5% central Au+Au collisions. The expreimental net-proton measurements are compared to corresponding values from UrQMD and HRG models within the expreimental acceptances.
Collision energy dependence of $C_2/C_1$, $C_3/C_2$ and $C_4/C_2$ for net-proton multiplicity distribution in 0-5% central Au+Au collisions. The expreimental net-proton measurements are compared to corresponding values from UrQMD and HRG models within the expreimental acceptances.
Collision energy dependence of $C_2/C_1$, $C_3/C_2$ and $C_4/C_2$ for net-proton multiplicity distribution in 0-5% central Au+Au collisions. The expreimental net-proton measurements are compared to corresponding values from UrQMD and HRG models within the expreimental acceptances.
Collision energy dependence of $C_2/C_1$, $C_3/C_2$ and $C_4/C_2$ for net-proton multiplicity distribution in 0-5% central Au+Au collisions. The expreimental net-proton measurements are compared to corresponding values from UrQMD and HRG models within the expreimental acceptances.
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 fiducial cross section for W$\gamma$ production in proton-proton collisions is measured at a center-of-mass energy of 13 TeV in 137 fb$^{-1}$ of data collected using the CMS detector at the LHC. The W $\to$ e$\nu$ and $\mu\nu$ decay modes are used in a maximum-likelihood fit to the lepton-photon invariant mass distribution to extract the combined cross section. The measured cross section is compared with theoretical expectations at next-to-leading order in quantum chromodynamics. In addition, 95% confidence level intervals are reported for anomalous triple-gauge couplings within the framework of effective field theory.
The measured Wgamma fiducial cross section and corresponding theoretical predictions from MadGraph5_aMC@NLO and POWHEG. The MadGraph5_aMC@NLO prediction includes 0 and 1 jets in the matrix element at NLO in QCD. The POWHEG prediction uses the C-NLO method described in https://arxiv.org/abs/1408.5766. The cross section is measured in a fiducial region defined with isolated prompt photons and isolated prompt dressed leptons (electrons and muons). A lepton or photon is considered isolated if the pt sum of all stable particles within Delta R = 0.4, divided by the pt of the lepton or photon, is less than 0.5. A lepton is considered prompt if it originates from the hard process or from the decay of a tau lepton that originates from the hard process; a photon is considered prompt if it originates from the hard process or an FSR or ISR process involving a particle that originates from the hard process. A lepton is dressed by adding to its four-momentum the four-momenta of all photons within DeltaR = 0.1; this procedure is intended to restore the lepton to its pre-FSR state. The fiducial region kinematic requirements are: photon and lepton |eta|<2.5 and pt > 25 GeV, and DeltaR(lepton,photon) > 0.5.
Data and SM expected event yields corresponding to photon pt distribution used to extract aTGC limits.
95% CL limits on effective field theory parameters in Wgamma events. No unitarity regularisation scheme is applied. All parameters are fixed to their SM values except the one that is fitted.
95% CL limits on the Lagrangian approach (a.k.a. LEP parametrization) parameters in Wgamma events.
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