Showing 10 of 490 results
Cross-section measurements for a $Z$ boson produced in association with high-transverse-momentum jets ($p_{\mathrm{T}} \geq 100$ GeV) and decaying into a charged-lepton pair ($e^+e^-,\mu^+\mu^-$) are presented. The measurements are performed using proton-proton collisions at $\sqrt{s}=13$ TeV corresponding to an integrated luminosity of $139$ fb$^{-1}$ collected by the ATLAS experiment at the LHC. Measurements of angular correlations between the $Z$ boson and the closest jet are performed in events with at least one jet with $p_{\mathrm{T}} \geq 500$ GeV. Event topologies of particular interest are the collinear emission of a $Z$ boson in dijet events and a boosted $Z$ boson recoiling against a jet. Fiducial cross sections are compared with state-of-the-art theoretical predictions. The data are found to agree with next-to-next-to-leading-order predictions by NNLOjet and with the next-to-leading-order multi-leg generators MadGraph5_aMC@NLO and Sherpa.
Measured fiducial differential cross sections for the Z boson p$_{\mathrm{T}}$ in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the leading jet p$_{\mathrm{T}}$ in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the jet multiplicity in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the jet multiplicity in the high-p$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the $\Delta R_{Z,j}^{min}$ in the high-p$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the $r_{Z,j}$ in the high-p$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the $r_{Z,j}$ in the collinear region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the $r_{Z,j}$ in the back-to-back region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the jet multiplicity in the collinear region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the jet multiplicity in the back-to-back region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the H$_{\mathrm{T}}$ in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the $\Delta R_{Z,j}^{min}$ in the high-S$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the jet multiplicity in the high-S$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The statistical, systematic, and luminosity uncertainties are given.
Systematic uncertainties for the Z boson p$_{\mathrm{T}}$ in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the leading jet p$_{\mathrm{T}}$ in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the jet multiplicity in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the jet multiplicity in the high-p$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the $\Delta R_{Z,j}^{min}$ in the high-p$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the $r_{Z,j}$ in the high-p$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the $r_{Z,j}$ in the collinear region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the $r_{Z,j}$ in the back-to-back region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the jet multiplicity in the collinear region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the jet multiplicity in the back-to-back region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the H$_{\mathrm{T}}$ in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the $\Delta R_{Z,j}^{min}$ in the high-S$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the jet multiplicity in the high-S$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Correction scale factor from the cross section calculated with leptons at the Born-level to the cross section calculated with dressed leptons as a function of the Z boson p$_{\mathrm{T}}$ in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with leptons at the Born-level to the cross section calculated with dressed leptons as a function of the leading jet p$_{\mathrm{T}}$ in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with leptons at the Born-level to the cross section calculated with dressed leptons as a function of the jet multiplicity in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with leptons at the Born-level to the cross section calculated with dressed leptons as a function of the jet multiplicity in the high-p$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with leptons at the Born-level to the cross section calculated with dressed leptons as a function of the $\Delta R_{Z,j}^{min}$ in the high-p$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with leptons at the Born-level to the cross section calculated with dressed leptons as a function of the $r_{Z,j}$ in the high-p$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with leptons at the Born-level to the cross section calculated with dressed leptons as a function of the $r_{Z,j}$ in the collinear region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with leptons at the Born-level to the cross section calculated with dressed leptons as a function of the $r_{Z,j}$ in the back-to-back region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with leptons at the Born-level to the cross section calculated with dressed leptons as a function of the jet multiplicity in the collinear region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with leptons at the Born-level to the cross section calculated with dressed leptons as a function of the jet multiplicity in the back-to-back region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with leptons at the Born-level to the cross section calculated with dressed leptons as a function of the H$_{\mathrm{T}}$ in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with leptons at the Born-level to the cross section calculated with dressed leptons as a function of the $\Delta R_{Z,j}^{min}$ in the high-S$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with leptons at the Born-level to the cross section calculated with dressed leptons as a function of the jet multiplicity in the high-S$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with an overlap removal with jets of pT greater than 100 GeV to the cross section calculated with an overlap removal with jets of pT greater than 30 GeV as a function of the Z boson p$_{\mathrm{T}}$ in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with an overlap removal with jets of pT greater than 100 GeV to the cross section calculated with an overlap removal with jets of pT greater than 30 GeV as a function of the leading jet p$_{\mathrm{T}}$ in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with an overlap removal with jets of pT greater than 100 GeV to the cross section calculated with an overlap removal with jets of pT greater than 30 GeV as a function of the jet multiplicity in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with an overlap removal with jets of pT greater than 100 GeV to the cross section calculated with an overlap removal with jets of pT greater than 30 GeV as a function of the jet multiplicity in the high-p$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with an overlap removal with jets of pT greater than 100 GeV to the cross section calculated with an overlap removal with jets of pT greater than 30 GeV as a function of the $\Delta R_{Z,j}^{min}$ in the high-p$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with an overlap removal with jets of pT greater than 100 GeV to the cross section calculated with an overlap removal with jets of pT greater than 30 GeV as a function of the $r_{Z,j}$ in the high-p$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with an overlap removal with jets of pT greater than 100 GeV to the cross section calculated with an overlap removal with jets of pT greater than 30 GeV as a function of the $r_{Z,j}$ in the collinear region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with an overlap removal with jets of pT greater than 100 GeV to the cross section calculated with an overlap removal with jets of pT greater than 30 GeV as a function of the $r_{Z,j}$ in the back-to-back region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with an overlap removal with jets of pT greater than 100 GeV to the cross section calculated with an overlap removal with jets of pT greater than 30 GeV as a function of the jet multiplicity in the collinear region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with an overlap removal with jets of pT greater than 100 GeV to the cross section calculated with an overlap removal with jets of pT greater than 30 GeV as a function of the jet multiplicity in the back-to-back region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with an overlap removal with jets of pT greater than 100 GeV to the cross section calculated with an overlap removal with jets of pT greater than 30 GeV as a function of the H$_{\mathrm{T}}$ in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with an overlap removal with jets of pT greater than 100 GeV to the cross section calculated with an overlap removal with jets of pT greater than 30 GeV as a function of the $\Delta R_{Z,j}^{min}$ in the high-S$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Correction scale factor from the cross section calculated with an overlap removal with jets of pT greater than 100 GeV to the cross section calculated with an overlap removal with jets of pT greater than 30 GeV as a function of the jet multiplicity in the high-S$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, averaging the electron and muon channels, derived with Sherpa2.2.11. The systematic uncertainty is obtained with an enveloppe around scale factors computed from Sherpa2.2.1 and MG5_aMC+Py8 CKKWL.
Measured fiducial differential cross sections for the Z boson p$_{\mathrm{T}}$ in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the leading jet p$_{\mathrm{T}}$ in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the jet multiplicity in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the jet multiplicity in the high-p$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the $\Delta R_{Z,j}^{min}$ in the high-p$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the $r_{Z,j}$ in the high-p$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the $r_{Z,j}$ in the collinear region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the $r_{Z,j}$ in the back-to-back region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the jet multiplicity in the collinear region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the jet multiplicity in the back-to-back region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the H$_{\mathrm{T}}$ in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the $\Delta R_{Z,j}^{min}$ in the high-S$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The statistical, systematic, and luminosity uncertainties are given.
Measured fiducial differential cross sections for the jet multiplicity in the high-S$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The statistical, systematic, and luminosity uncertainties are given.
Systematic uncertainties for the Z boson p$_{\mathrm{T}}$ in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the leading jet p$_{\mathrm{T}}$ in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the jet multiplicity in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the jet multiplicity in the high-p$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the $\Delta R_{Z,j}^{min}$ in the high-p$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the $r_{Z,j}$ in the high-p$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the $r_{Z,j}$ in the collinear region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the $r_{Z,j}$ in the back-to-back region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the jet multiplicity in the collinear region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the jet multiplicity in the back-to-back region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the H$_{\mathrm{T}}$ in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the $\Delta R_{Z,j}^{min}$ in the high-S$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Systematic uncertainties for the jet multiplicity in the high-S$_{\mathrm{T}}$ region in Z($\to \ell^{+} \ell^{-}$) + high p$_{\mathrm{T}}$ jets events, where the EW Zjj contribution is treated as signal and not subtracted as background. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.
Studies of the correlations of the two highest transverse momentum (leading) jets in individual Pb+Pb collision events can provide information about the mechanism of jet quenching by the hot and dense matter created in such collisions. In Pb+Pb and pp collisions at $\sqrt{s_{_\text{NN}}}$ = 5.02 TeV, measurements of the leading dijet transverse momentum ($p_{\mathrm{T}}$) correlations are presented. Additionally, measurements in Pb+Pb collisions of the dijet pair nuclear modification factors projected along leading and subleading jet $p_{\mathrm{T}}$ are made. The measurements are performed using the ATLAS detector at the LHC with 260 pb$^{-1}$ of pp data collected in 2017 and 2.2 nb$^{-1}$ of Pb+Pb data collected in 2015 and 2018. An unfolding procedure is applied to the two-dimensional leading and subleading jet $p_{\mathrm{T}}$ distributions to account for experimental effects in the measurement of both jets. Results are provided for dijets with leading jet $p_{\mathrm{T}}$ greater than 100 GeV. Measurements of the dijet-yield-normalized $x_{\mathrm{J}}$ distributions in Pb+Pb collisions show an increased fraction of imbalanced jets compared to pp collisions; these measurements are in agreement with previous measurements of the same quantity at 2.76 TeV in the overlapping kinematic range. Measurements of the absolutely-normalized dijet rate in Pb+Pb and pp collisions are also presented, and show that balanced dijets are significantly more suppressed than imbalanced dijets in Pb+Pb collisions. It is observed in the measurements of the pair nuclear modification factors that the subleading jets are significantly suppressed relative to leading jets with $p_{\mathrm{T}}$ between 100 and 316 GeV for all centralities in Pb+Pb collisions.
absolutely normalized dijet cross sections from pp collisions
absolutely normalized dijet yields scaled by 1/<TAA> in 0-10% central PbPb collisions
absolutely normalized dijet yields scaled by 1/<TAA> in 10-20% central PbPb collisions
absolutely normalized dijet yields scaled by 1/<TAA> in 20-40% central PbPb collisions
absolutely normalized dijet yields scaled by 1/<TAA> in 40-60% central PbPb collisions
absolutely normalized dijet yields scaled by 1/<TAA> in 60-80% central PbPb collisions
self normalized dijets from pp collisions
self normalized dijet distributions in 0-10% central PbPb collisions
self normalized dijet distributions in 10-20% central PbPb collisions
self normalized dijet distributions in 20-40% central PbPb collisions
self normalized dijet distributions in 40-60% central PbPb collisions
self normalized dijet distributions in 60-80% central PbPb collisions
leading jet RAA^pair in 0-10% central PbPb collisions
subleading jet RAA^pair in 0-10% central PbPb collisions
leading jet RAA^pair in 10-20% central PbPb collisions
subleading jet RAA^pair in 10-20% central PbPb collisions
leading jet RAA^pair in 20-40% central PbPb collisions
subleading jet RAA^pair in 20-40% central PbPb collisions
leading jet RAA^pair in 40-60% central PbPb collisions
subleading jet RAA^pair in 40-60% central PbPb collisions
leading jet RAA^pair in 60-80% central PbPb collisions
subleading jet RAA^pair in 60-80% central PbPb collisions
ratio of subleading jet RAA^pair to leading jet RAA^pair in PbPb collisions
The correlations between flow harmonics $v_n$ for $n=2$, 3 and 4 and mean transverse momentum $[p_\mathrm{T}]$ in $^{129}$Xe+$^{129}$Xe and $^{208}$Pb+$^{208}$Pb collisions at $\sqrt{s_{\mathrm{NN}}}=5.44$ TeV and 5.02 TeV, respectively, are measured using charged particles with the ATLAS detector. The correlations are sensitive to the shape and size of the initial geometry, nuclear deformation, and initial momentum anisotropy. The effects from non-flow and centrality fluctuations are minimized, respectively, via a subevent cumulant method and event activity selection based on particle production in the very forward rapidity. The results show strong dependences on centrality, harmonic number $n$, $p_{\mathrm{T}}$ and pseudorapidity range. Current models describe qualitatively the overall centrality- and system-dependent trends but fail to quantitatively reproduce all the data. In the central collisions, where models generally show good agreement, the $v_2$-$[p_\mathrm{T}]$ correlations are sensitive to the triaxiality of the quadruple deformation. The comparison of model to the Pb+Pb and Xe+Xe data suggests that the $^{129}$Xe nucleus is a highly deformed triaxial ellipsoid that is neither a prolate nor an oblate shape. This provides strong evidence for a triaxial deformation of $^{129}$Xe nucleus using high-energy heavy-ion collision.
$\rho_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{2}$ Standard method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{2}$ Two_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{2}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{3}$ Standard method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{3}$ Two_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{3}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{4}$ Standard method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{4}$ Two_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{4}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{2}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{3}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{3}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{4}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{4}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$
$\rho_{2}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$
$\rho_{3}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$
$\rho_{3}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$
$\rho_{4}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$
$\rho_{4}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$
$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{3}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{3}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{4}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{4}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{2}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{2}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{2}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.3< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{3}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{3}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{3}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.3< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{4}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{4}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{4}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.3< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{3}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{3}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{4}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{4}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$Cov_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$Cov_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$Cov_{3}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$Cov_{3}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$Cov_{4}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$Cov_{4}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality
$\rho_{3}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{3}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality
$\rho_{4}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{4}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality
$\rho_{2}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{2}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality
$\rho_{3}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{3}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality
$\rho_{4}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{4}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality
$\rho_{2}$ for peripheral events, Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality,
$\rho_{2}$ for peripheral events, Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality,
$\rho_{2}$ for peripheral events, Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality,
$\rho_{2}$ for peripheral events, Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality,
$\rho_{2}$ for peripheral events, Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality,
$\rho_{2}$ for peripheral events, Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality,
$\rho_{2}$ for peripheral events, Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality,
$\rho_{2}$ for peripheral events, Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality,
$\rho_{2}$ for peripheral events, Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality,
$\rho_{2}$ for peripheral events, Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality,
$\rho_{2}$ for peripheral events, Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality,
$\rho_{2}$ for peripheral events, Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality,
$\rho_{2}$, Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality,
$\rho_{2}$, Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality,
$\rho_{3}$, Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality,
$\rho_{3}$, Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality,
$\rho_{2}$, Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality,
$\rho_{2}$, Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality,
$\rho_{3}$, Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality,
$\rho_{3}$, Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality,
$\rho_{2}$ for central events, Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality,
$\rho_{2}$ for central events, Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality,
$\rho_{2}$ for central events, Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality,
$\rho_{2}$ for central events, Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality,
$\rho_{2}$ ratio between Xe+Xe 5.44 TeV and Pb+Pb 5.02 TeV for central events, Three_subevent method, for , $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality,
$\rho_{2}$ ratio between Xe+Xe 5.44 TeV and Pb+Pb 5.02 TeV for central events, Three_subevent method, for , $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality,
$\Sigma E_{T}$ vs $N^{rec}_{ch}$ for Pb+Pb 5.02 TeV
$\Sigma E_{T}$ vs $N^{rec}_{ch}$ for Xe+Xe 5.44 TeV
$\rho_{2}$ ratio between Xe+Xe 5.44 TeV and Pb+Pb 5.02 TeV for central events, Standard method, for , $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality,
$\rho_{2}$ ratio between Xe+Xe 5.44 TeV and Pb+Pb 5.02 TeV for central events, Standard method, for , $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality,
$\rho_{2}$ ratio between Xe+Xe 5.44 TeV and Pb+Pb 5.02 TeV for central events, Combined_subevent method, for , $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality,
$\rho_{2}$ ratio between Xe+Xe 5.44 TeV and Pb+Pb 5.02 TeV for central events, Combined_subevent method, for , $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality,
$\rho_{2}$ ratio between Xe+Xe 5.44 TeV and Pb+Pb 5.02 TeV for central events, Three_subevent method, for , $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality,
$\rho_{2}$ ratio between Xe+Xe 5.44 TeV and Pb+Pb 5.02 TeV for central events, Three_subevent method, for , $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality,
$\rho_{2}$ ratio between Xe+Xe 5.44 TeV and Pb+Pb 5.02 TeV for central events, Combined_subevent method, for , $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality,
$\rho_{2}$ ratio between Xe+Xe 5.44 TeV and Pb+Pb 5.02 TeV for central events, Combined_subevent method, for , $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality,
$\rho_{3}$ for central events, Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality,
$\rho_{3}$ for central events, Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality,
$\rho_{3}$ for central events, Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality,
$\rho_{3}$ for central events, Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality,
$\rho_{3}$ ratio between Xe+Xe 5.44 TeV and Pb+Pb 5.02 TeV for central events, Standard method, for , $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality,
$\rho_{3}$ ratio between Xe+Xe 5.44 TeV and Pb+Pb 5.02 TeV for central events, Standard method, for , $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality,
$\rho_{3}$ ratio between Xe+Xe 5.44 TeV and Pb+Pb 5.02 TeV for central events, Combined_subevent method, for , $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality,
$\rho_{3}$ ratio between Xe+Xe 5.44 TeV and Pb+Pb 5.02 TeV for central events, Combined_subevent method, for , $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality,
$\rho_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$
$\rho_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$
$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$
$\rho_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$
$\rho_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$
$\rho_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$
$\rho_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$
$\rho_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$
$\rho_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$
$\rho_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$
$\rho_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$
$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$
$\rho_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$
$\rho_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$
$\rho_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$
$\rho_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$
$\rho_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$
$\rho_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$
$\rho_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$
$\rho_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$
$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$
$\rho_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$
$\rho_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$
$\rho_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$
$\rho_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$
$\rho_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$
$\rho_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$
$\rho_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$
$\rho_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$
$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$
$\rho_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$
$\rho_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$
$\rho_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$
$\rho_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$
$\rho_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$
$\rho_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$
$\rho_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.
$\rho_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.
$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.
$\rho_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.
$\rho_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.
$\rho_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.
$\rho_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.
$\rho_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.
$\rho_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.
$\rho_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$\rho_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$\rho_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$\rho_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$\rho_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$\rho_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$\rho_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$\rho_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$\rho_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.
$\rho_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.
$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.
$\rho_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.
$\rho_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.
$\rho_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.
$\rho_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.
$\rho_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.
$\rho_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.
$\rho_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$\rho_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$\rho_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$\rho_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$\rho_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$\rho_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$\rho_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$\rho_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$\rho_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$
$\rho_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$
$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$
$\rho_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$
$\rho_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$
$\rho_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$
$\rho_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$
$\rho_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$
$\rho_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$
$\rho_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$
$\rho_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$
$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$
$\rho_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$
$\rho_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$
$\rho_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$
$\rho_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$
$\rho_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$
$\rho_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$
$\rho_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$
$\rho_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$
$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$
$\rho_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$
$\rho_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$
$\rho_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$
$\rho_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$
$\rho_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$
$\rho_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$
$\rho_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$
$\rho_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$
$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$
$\rho_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$
$\rho_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$
$\rho_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$
$\rho_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$
$\rho_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$
$\rho_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$
$\rho_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$\rho_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$\rho_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$\rho_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$\rho_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$\rho_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$\rho_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$\rho_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$\rho_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$\rho_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$\rho_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$\rho_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$\rho_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$\rho_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$\rho_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$\rho_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$\rho_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$\rho_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$\rho_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$\rho_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$\rho_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$\rho_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$\rho_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$\rho_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$\rho_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$\rho_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$\rho_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$\rho_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$\rho_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$\rho_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$\rho_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$\rho_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$Cov_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.
$Cov_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.
$Cov_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.
$Cov_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.
$Cov_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.
$Cov_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.
$Cov_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.
$Cov_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.
$Cov_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.
$Cov_{2}$ Standard method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.
$Cov_{2}$ Two_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.
$Cov_{2}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.
$Cov_{3}$ Standard method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.
$Cov_{3}$ Two_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.
$Cov_{3}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.
$Cov_{4}$ Standard method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.
$Cov_{4}$ Two_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.
$Cov_{4}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.
$Cov_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{2}$ Standard method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{2}$ Two_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{2}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{3}$ Standard method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{3}$ Two_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{3}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{4}$ Standard method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{4}$ Two_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{4}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.
$Cov_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$Cov_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$Cov_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$Cov_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$Cov_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$Cov_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$Cov_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$Cov_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$Cov_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$Cov_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$Cov_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$Cov_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$Cov_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$Cov_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$Cov_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$Cov_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$Cov_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$Cov_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$Cov_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$Cov_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$Cov_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$Cov_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$Cov_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$Cov_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$Cov_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$Cov_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$Cov_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$Cov_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$Cov_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$Cov_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$Cov_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$Cov_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$Cov_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$Cov_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$Cov_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$Cov_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.
$c_{k}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.
$c_{k}$ Standard method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.
$var(v^{2}_{2})$ Combined subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.
$var(v^{2}_{2})$ Combined subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.
$var(v^{2}_{3})$ Combined subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.
$var(v^{2}_{3})$ Combined subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.
$var(v^{2}_{4})$ Combined subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.
$var(v^{2}_{4})$ Combined subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.
$c_{k}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$.
$c_{k}$ Standard method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$.
$var(v^{2}_{2})$ Combined subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$.
$var(v^{2}_{2})$ Combined subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$.
$var(v^{2}_{3})$ Combined subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$.
$var(v^{2}_{3})$ Combined subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$.
$var(v^{2}_{4})$ Combined subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$.
$var(v^{2}_{4})$ Combined subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$.
$c_{k}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.
$c_{k}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.
$var(v^{2}_{2})$ Combined subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.
$var(v^{2}_{2})$ Combined subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.
$var(v^{2}_{3})$ Combined subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.
$var(v^{2}_{3})$ Combined subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.
$var(v^{2}_{4})$ Combined subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.
$var(v^{2}_{4})$ Combined subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.
$c_{k}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$.
$c_{k}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$.
$var(v^{2}_{2})$ Combined subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$.
$var(v^{2}_{2})$ Combined subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$.
$var(v^{2}_{3})$ Combined subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$.
$var(v^{2}_{3})$ Combined subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$.
$var(v^{2}_{4})$ Combined subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$.
$var(v^{2}_{4})$ Combined subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$.
$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N_{ch}^{rec}$ based Centrality
$\rho_{3}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{3}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N_{ch}^{rec}$ based Centrality
$\rho_{4}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{4}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N_{ch}^{rec}$ based Centrality
$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality
$\rho_{3}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{3}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality
$\rho_{4}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{4}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality
$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N_{ch}^{rec}$ based Centrality
$\rho_{3}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{3}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N_{ch}^{rec}$ based Centrality
$\rho_{4}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{4}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N_{ch}^{rec}$ based Centrality
$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality
$\rho_{3}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{3}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality
$\rho_{4}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{4}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality
$\rho_{2}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{2}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N_{ch}^{rec}$ based Centrality
$\rho_{3}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{3}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N_{ch}^{rec}$ based Centrality
$\rho_{4}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{4}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N_{ch}^{rec}$ based Centrality
$\rho_{2}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{2}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality
$\rho_{3}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{3}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality
$\rho_{4}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{4}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality
$\rho_{2}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{2}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N_{ch}^{rec}$ based Centrality
$\rho_{3}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{3}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N_{ch}^{rec}$ based Centrality
$\rho_{4}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{4}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N_{ch}^{rec}$ based Centrality
$\rho_{2}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{2}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality
$\rho_{3}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{3}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality
$\rho_{4}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality
$\rho_{4}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality
Searches for new phenomena inspired by supersymmetry in final states containing an $e^+e^-$ or $\mu^+\mu^-$ pair, jets, and missing transverse momentum are presented. These searches make use of proton-proton collision data with an integrated luminosity of 139 $\text{fb}^{-1}$, collected during 2015-2018 at a centre-of-mass energy $\sqrt{s}=13 $TeV by the ATLAS detector at the Large Hadron Collider. Two searches target the pair production of charginos and neutralinos. One uses the recursive-jigsaw reconstruction technique to follow up on excesses observed in 36.1 $\text{fb}^{-1}$ of data, and the other uses conventional event variables. The third search targets pair production of coloured supersymmetric particles (squarks or gluinos) decaying through the next-to-lightest neutralino $(\tilde\chi_2^0)$ via a slepton $(\tilde\ell)$ or $Z$ boson into $\ell^+\ell^-\tilde\chi_1^0$, resulting in a kinematic endpoint or peak in the dilepton invariant mass spectrum. The data are found to be consistent with the Standard Model expectations. Results are interpreted using simplified models and exclude masses up to 900 GeV for electroweakinos, 1550 GeV for squarks, and 2250 GeV for gluinos.
- - - - - - - - Overview of HEPData Record - - - - - - - - <br/><br/> <b>EWK SR distributions:</b> <a href="116034?version=1&table=Figure 11a">SR-High_8-EWK</a>; <a href="116034?version=1&table=Figure 11b">SR-ℓℓ𝑏𝑏-EWK</a>; <a href="116034?version=1&table=Figure 11c">SR-Int-EWK</a>; <a href="116034?version=1&table=Figure 11d">SR-Low-EWK</a>; <a href="116034?version=1&table=Figure 11e">SR-OffShell-EWK</a><br/><br/> <b>Strong SR distributions:</b> <a href="116034?version=1&table=Figure 13a">SRC-STR</a>; <a href="116034?version=1&table=Figure 13b">SRLow-STR</a>; <a href="116034?version=1&table=Figure 13c">SRMed-STR</a>; <a href="116034?version=1&table=Figure 13d">SRHigh-STR</a><br/><br/> <b>RJR SR Yields:</b> <a href="116034?version=1&table=Table 16">SR2l-Low-RJR, SR2l-ISR-RJR</a><br/><br/> <b>EWK SR Yields:</b> <a href="116034?version=1&table=Table 18">SR-High_16a-EWK, SR-High_8a-EWK, SR-1J-High-EWK, SR-ℓℓ𝑏𝑏-EWK, SR-High_16b-EWK, SR-High_8b-EWK</a>; <a href="116034?version=1&table=Table 19">SR-Int_a-EWK, SR-Low_a-EWK, SR-Low-2-EWK, SR-OffShell_a-EWK, SR-Int_b-EWK, SR-Low_b-EWK, SR-OffShell_b-EWK </a><br/><br/> <b>Strong SR Yields:</b> <a href="116034?version=1&table=Table 21">SRC-STR, SRLow-STR, SRMed-STR, SRHigh-STR</a>; <a href="116034?version=1&table=Table 22">SRZLow-STR, SRZMed-STR, SRZHigh-STR</a><br/><br/> <b>C1N2 Model Limits:</b> <a href="116034?version=1&table=Table 15a C1N2 Observed Limit">Obs</a>; <a href="116034?version=1&table=Table 15a C1N2 Expected Limit">Exp</a>; <a href="116034?version=1&table=Auxiliary Figure 34a C1N2 Expected XS Upper Limit">Upper Limits</a><br/><br/> <b>GMSB Model Limits:</b> <a href="116034?version=1&table=Table 15b GMSB Observed Limit">Obs</a>; <a href="116034?version=1&table=Table 15b GMSB Expected Limit">Exp</a>; <a href="116034?version=1&table=Auxiliary Figure 34b GMSB Expected XS Upper Limit">Upper Limits</a><br/><br/> <b>Gluon-Slepton Model Limits:</b> <a href="116034?version=1&table=Figure 16a Observed Limit">Obs</a>; <a href="116034?version=1&table=Figure 16a Expected Limit">Exp</a>; <a href="116034?version=1&table=Auxiliary Figure 23a XS Upper Limit">Upper Limits</a><br/><br/> <b>Gluon-Z* Model Limits:</b> <a href="116034?version=1&table=Figure 16b Observed Limit">Obs</a>; <a href="116034?version=1&table=Figure 16b Expected Limit">Exp</a>; <a href="116034?version=1&table=Auxiliary Figure 23b XS Upper Limit">Upper Limits</a><br/><br/> <b>Squark-Z* Model Limits:</b> <a href="116034?version=1&table=Figure 16c Observed Limit">Obs</a>; <a href="116034?version=1&table=Figure 16c Expected Limit">Exp</a>; <a href="116034?version=1&table=Auxiliary Figure 23c XS Upper Limit">Upper Limits</a><br/><br/> <b>EWK VR distributions:</b> <a href="116034?version=1&table=Figure 4a S_ETmiss in VR-High-Sideband-EWK">VR-High-Sideband-EWK</a>; <a href="116034?version=1&table=Figure 4b S_Etmiss in VR-High-R-EWK">VR-High-R-EWK</a>; <a href="116034?version=1&table=Figure 4c S_Etmiss in VR-1J-High-EWK">VR-1J-High-EWK</a>; <a href="116034?version=1&table=Figure 4d S_Etmiss in VR-llbb-EWK">VR-ℓℓ𝑏𝑏-EWK</a>; <a href="116034?version=1&table=Figure 5a S_Etmiss in VR-Int-EWK">VR-Int-EWK</a>; <a href="116034?version=1&table=Figure 5b S_Etmiss in VR-Low-EWK">VR-Low-EWK</a>; <a href="116034?version=1&table=Figure 5c S_Etmiss in VR-Low-2-EWK">VR-Low-2-EWK</a>; <a href="116034?version=1&table=Figure 5d S_Etmiss in VR-OffShell-EWK">VR-OffShell-EWK</a><br/><br/> <b>Strong VR distributions:</b> <a href="116034?version=1&table=Figure 6a">VRC-STR</a>; <a href="116034?version=1&table=Figure 6b">VRLow-STR</a>; <a href="116034?version=1&table=Figure 6c">VRMed-STR</a>; <a href="116034?version=1&table=Figure 6d">VRHigh-STR</a>; <a href="116034?version=1&table=Figure 8">VR3L-STR</a><br/><br/> <b>Other Strong distributions:</b> <a href="116034?version=1&table=Auxiliary Figure 17a">SRLow-STR + VRLow-STR</a><br/><br/> <b>Other EWK distributions:</b> <a href="116034?version=1&table=Auxiliary Figure 33a Mjj in CR-Z-EWK and SR-Low-EWK">CR-Z-EWK + SR-Low-EWK</a>; <a href="116034?version=1&table=Auxiliary Figure 33b S_ETmiss in CR-Z-met-EWK">CR-Z-met-EWK</a><br/><br/> <b>Strong Signal Cutflows:</b> <a href="116034?version=1&table=Auxiliary Table 30-31 SRC-STR Cutflow">SRC-STR GG_N2_ZN1</a>; <a href="116034?version=1&table=Auxiliary Table 30-31 SRMed-STR Cutflow">SRC-STR SS_N2_ZN1</a>; <a href="116034?version=1&table=Auxiliary Table 30-31 SRLow-STR Cutflow">SRLow-STR GG_N2_SLN1</a>; <a href="116034?version=1&table=Auxiliary Table 30-31 SRHigh-STR Cutflow">SRC-STR GG_N2_SLN1</a>; <a href="116034?version=1&table=Auxiliary Table 30-31 SRZLow-STR Cutflow">SRZLow-STR SS_N2_ZN1</a>; <a href="116034?version=1&table=Auxiliary Table 30-31 SRZMed-STR Cutflow">SRZMed-STR SS_N2_ZN1</a>; <a href="116034?version=1&table=Auxiliary Table 30-31 SRZHigh-STR Cutflow">SRZHigh-STR SS_N2_ZN1</a><br/><br/> <b>EWK Signal Cutflows:</b> <a href="116034?version=1&table=Auxiliary Table 36 SR-OffShell_a-EWK Cutflow"> SR-OffShell_a-EWK</a>; <a href="116034?version=1&table=Auxiliary Table 37 SR-OffShell_b-EWK Cutflow"> SR-OffShell_b-EWK</a>; <a href="116034?version=1&table=Auxiliary Table 38 SR-Low_a-EWK Cutflow"> SR-Low_a-EWK</a>; <a href="116034?version=1&table=Auxiliary Table 39 SR-Low_b-EWK Cutflow"> SR-Low_b-EWK</a>; <a href="116034?version=1&table=Auxiliary Table 40 SR-Low-2-EWK Cutflow"> SR-Low-2-E</a>; <a href="116034?version=1&table=Auxiliary Table 41 SR-Int_a-EWK Cutflow"> SR-Int_a-EWK</a>; <a href="116034?version=1&table=Auxiliary Table 42 SR-Int_b-EWK Cutflow"> SR-Int_b-EWK</a>; <a href="116034?version=1&table=Auxiliary Table 43 SR-High_16a-EWK Cutflow"> SR-High_16a-EWK</a>; <a href="116034?version=1&table=Auxiliary Table 44 SR-High_16b-EWK Cutflow"> SR-High_16b-EWK</a>; <a href="116034?version=1&table=Auxiliary Table 45 SR-High_8a-EWK Cutflow"> SR-High_8a-EWK</a>; <a href="116034?version=1&table=Auxiliary Table 46 SR-High_8b-EWK Cutflow"> SR-High_8b-EWK</a>; <a href="116034?version=1&table=Auxiliary Table 47 SR-1J-High-EWK Cutflow"> SR-1J-Hig</a>; <a href="116034?version=1&table=Auxiliary Table 48 SR-llbb-EWK Cutflow"> SR-llbb-EWK</a><br/><br/> <b>EWK Signal Number of MC Events:</b> <a href="116034?version=1&table=Auxiliary Table 36 SR-OffShell_a-EWK Generated"> SR-OffShell_a-EWK</a>; <a href="116034?version=1&table=Auxiliary Table 37 SR-OffShell_b-EWK Generated"> SR-OffShell_b-EWK</a>; <a href="116034?version=1&table=Auxiliary Table 38 SR-Low_a-EWK Generated"> SR-Low_a-EWK</a>; <a href="116034?version=1&table=Auxiliary Table 39 SR-Low_b-EWK Generated"> SR-Low_b-EWK</a>; <a href="116034?version=1&table=Auxiliary Table 40 SR-Low-2-EWK Generated"> SR-Low-2-E</a>; <a href="116034?version=1&table=Auxiliary Table 41 SR-Int_a-EWK Generated"> SR-Int_a-EWK</a>; <a href="116034?version=1&table=Auxiliary Table 42 SR-Int_b-EWK Generated"> SR-Int_b-EWK</a>; <a href="116034?version=1&table=Auxiliary Table 43 SR-High_16a-EWK Generated"> SR-High_16a-EWK</a>; <a href="116034?version=1&table=Auxiliary Table 44 SR-High_16b-EWK Generated"> SR-High_16b-EWK</a>; <a href="116034?version=1&table=Auxiliary Table 45 SR-High_8a-EWK Generated"> SR-High_8a-EWK</a>; <a href="116034?version=1&table=Auxiliary Table 46 SR-High_8b-EWK Generated"> SR-High_8b-EWK</a>; <a href="116034?version=1&table=Auxiliary Table 47 SR-1J-High-EWK Generated"> SR-1J-Hig</a>; <a href="116034?version=1&table=Auxiliary Table 48 SR-llbb-EWK Generated"> SR-llbb-EWK</a><br/><br/> <b>SRC-STR Signal Acceptance:</b> <a href="116034?version=1&table=GG_N2_SLN1 acc in SRC">GG_N2_SLN1</a>; <a href="116034?version=1&table=GG_N2_ZN1 acc in SRC">GG_N2_ZN1</a>; <a href="116034?version=1&table=SS_N2_ZN1 acc in SRC">SS_N2_ZN1</a><br/><br/> <b>SRLow-STR Signal Acceptance:</b> <a href="116034?version=1&table=GG_N2_SLN1 acc in SRLow">GG_N2_SLN1</a>; <a href="116034?version=1&table=GG_N2_ZN1 acc in SRLow">GG_N2_ZN1</a>; <a href="116034?version=1&table=SS_N2_ZN1 acc in SRLow">SS_N2_ZN1</a><br/><br/> <b>SRMed-STR Signal Acceptance:</b> <a href="116034?version=1&table=GG_N2_SLN1 acc in SRMed">GG_N2_SLN1</a>; <a href="116034?version=1&table=GG_N2_ZN1 acc in SRMed">GG_N2_ZN1</a>; <a href="116034?version=1&table=SS_N2_ZN1 acc in SRMed">SS_N2_ZN1</a><br/><br/> <b>SRHigh-STR Signal Acceptance:</b> <a href="116034?version=1&table=GG_N2_SLN1 acc in SRHigh">GG_N2_SLN1</a>; <a href="116034?version=1&table=GG_N2_ZN1 acc in SRHigh">GG_N2_ZN1</a>; <a href="116034?version=1&table=SS_N2_ZN1 acc in SRHigh">SS_N2_ZN1</a><br/><br/> <b>SRZLow-STR Signal Acceptance:</b> <a href="116034?version=1&table=GG_N2_ZN1 acc in SRZLow">GG_N2_ZN1</a>; <a href="116034?version=1&table=SS_N2_ZN1 acc in SRZLow">SS_N2_ZN1</a><br/><br/> <b>SRZMed-STR Signal Acceptance:</b> <a href="116034?version=1&table=GG_N2_ZN1 acc in SRZMed">GG_N2_ZN1</a>; <a href="116034?version=1&table=SS_N2_ZN1 acc in SRZMed">SS_N2_ZN1</a><br/><br/> <b>SRZHigh-STR Signal Acceptance:</b> <a href="116034?version=1&table=GG_N2_ZN1 acc in SRZHigh">GG_N2_ZN1</a>; <a href="116034?version=1&table=SS_N2_ZN1 acc in SRZHigh">SS_N2_ZN1</a><br/><br/> <b>SRC-STR Signal Efficiency:</b> <a href="116034?version=1&table=GG_N2_SLN1 eff in SRC">GG_N2_SLN1</a>; <a href="116034?version=1&table=GG_N2_ZN1 eff in SRC">GG_N2_ZN1</a>; <a href="116034?version=1&table=SS_N2_ZN1 eff in SRC">SS_N2_ZN1</a><br/><br/> <b>SRLow-STR Signal Efficiency:</b> <a href="116034?version=1&table=GG_N2_SLN1 eff in SRLow">GG_N2_SLN1</a>; <a href="116034?version=1&table=GG_N2_ZN1 eff in SRLow">GG_N2_ZN1</a>; <a href="116034?version=1&table=SS_N2_ZN1 eff in SRLow">SS_N2_ZN1</a><br/><br/> <b>SRMed-STR Signal Efficiency:</b> <a href="116034?version=1&table=GG_N2_SLN1 eff in SRMed">GG_N2_SLN1</a>; <a href="116034?version=1&table=GG_N2_ZN1 eff in SRMed">GG_N2_ZN1</a>; <a href="116034?version=1&table=SS_N2_ZN1 eff in SRMed">SS_N2_ZN1</a><br/><br/> <b>SRHigh-STR Signal Efficiency:</b> <a href="116034?version=1&table=GG_N2_SLN1 eff in SRHigh">GG_N2_SLN1</a>; <a href="116034?version=1&table=GG_N2_ZN1 eff in SRHigh">GG_N2_ZN1</a>; <a href="116034?version=1&table=SS_N2_ZN1 eff in SRHigh">SS_N2_ZN1</a><br/><br/> <b>SRZLow-STR Signal Efficiency:</b> <a href="116034?version=1&table=GG_N2_ZN1 eff in SRZLow">GG_N2_ZN1</a>; <a href="116034?version=1&table=SS_N2_ZN1 eff in SRZLow">SS_N2_ZN1</a><br/><br/> <b>SRZMed-STR Signal Efficiency:</b> <a href="116034?version=1&table=GG_N2_ZN1 eff in SRZMed">GG_N2_ZN1</a>; <a href="116034?version=1&table=SS_N2_ZN1 eff in SRZMed">SS_N2_ZN1</a><br/><br/> <b>SRZHigh-STR Signal Efficiency:</b> <a href="116034?version=1&table=GG_N2_ZN1 eff in SRZHigh">GG_N2_ZN1</a>; <a href="116034?version=1&table=SS_N2_ZN1 eff in SRZHigh">SS_N2_ZN1</a><br/><br/> <b>SR-OffShell_a-EWK Signal Acceptance:</b><a href="116034?version=1&table=GMSB acc in SR-OffShell_a-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 acc in SR-OffShell_a-EWK">C1N2</a>; <br/><br/> <b>SR-OffShell_b-EWK Signal Acceptance:</b><a href="116034?version=1&table=GMSB acc in SR-OffShell_b-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 acc in SR-OffShell_b-EWK">C1N2</a>; <br/><br/> <b>SR-Low_a-EWK Signal Acceptance:</b><a href="116034?version=1&table=GMSB acc in C1N2 acc in SR-Low_a-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 acc in C1N2 acc in SR-Low_a-EWK">C1N2</a>; <br/><br/> <b>SR-Low_b-EWK Signal Acceptance:</b><a href="116034?version=1&table=GMSB acc in SR-Low_b-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 acc in SR-Low_b-EWK">C1N2</a>; <br/><br/> <b>SR-Int_a-EWK Signal Acceptance:</b><a href="116034?version=1&table=GMSB acc in SR-Int_a-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 acc in SR-Int_a-EWK">C1N2</a>; <br/><br/> <b>SR-Int_b-EWK Signal Acceptance:</b><a href="116034?version=1&table=GMSB acc in SR-Int_b-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 acc in SR-Int_b-EWK">C1N2</a>; <br/><br/> <b>SR-High_16a-EWK Signal Acceptance:</b><a href="116034?version=1&table=GMSB acc in SR-High_16a-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 acc in SR-High_16a-EWK">C1N2</a>; <br/><br/> <b>SR-High_16b-EWK Signal Acceptance:</b><a href="116034?version=1&table=GMSB acc in SR-High_16b-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 acc in SR-High_16b-EWK">C1N2</a>; <br/><br/> <b>SR-High_8a-EWK Signal Acceptance:</b><a href="116034?version=1&table=GMSB acc in SR-High_8a-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 acc in SR-High_8a-EWK">C1N2</a>; <br/><br/> <b>SR-High_8b-EWK Signal Acceptance:</b><a href="116034?version=1&table=GMSB acc in SR-High_8b-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 acc in SR-High_8b-EWK">C1N2</a>; <br/><br/> <b>SR-1J-High-EWK Signal Acceptance:</b><a href="116034?version=1&table=GMSB acc in SR-1J-High-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 acc in SR-1J-High-EWK">C1N2</a>; <br/><br/> <b>SR-llbb-EWK Signal Acceptance:</b><a href="116034?version=1&table=GMSB acc in SR-llbb-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 acc in SR-llbb-EWK">C1N2</a>; <br/><br/> <b>SR-OffShell_a-EWK Signal Efficiency:</b><a href="116034?version=1&table=GMSB eff in SR-OffShell_a-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 eff in SR-OffShell_a-EWK">C1N2</a>; <br/><br/> <b>SR-OffShell_b-EWK Signal Efficiency:</b><a href="116034?version=1&table=GMSB eff in SR-OffShell_b-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 eff in SR-OffShell_b-EWK">C1N2</a>; <br/><br/> <b>SR-Low_a-EWK Signal Efficiency:</b><a href="116034?version=1&table=GMSB eff in C1N2 eff in SR-Low_a-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 eff in C1N2 eff in SR-Low_a-EWK">C1N2</a>; <br/><br/> <b>SR-Low_b-EWK Signal Efficiency:</b><a href="116034?version=1&table=GMSB eff in SR-Low_b-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 eff in SR-Low_b-EWK">C1N2</a>; <br/><br/> <b>SR-Int_a-EWK Signal Efficiency:</b><a href="116034?version=1&table=GMSB eff in SR-Int_a-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 eff in SR-Int_a-EWK">C1N2</a>; <br/><br/> <b>SR-Int_b-EWK Signal Efficiency:</b><a href="116034?version=1&table=GMSB eff in SR-Int_b-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 eff in SR-Int_b-EWK">C1N2</a>; <br/><br/> <b>SR-High_16a-EWK Signal Efficiency:</b><a href="116034?version=1&table=GMSB eff in SR-High_16a-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 eff in SR-High_16a-EWK">C1N2</a>; <br/><br/> <b>SR-High_16b-EWK Signal Efficiency:</b><a href="116034?version=1&table=GMSB eff in SR-High_16b-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 eff in SR-High_16b-EWK">C1N2</a>; <br/><br/> <b>SR-High_8a-EWK Signal Efficiency:</b><a href="116034?version=1&table=GMSB eff in SR-High_8a-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 eff in SR-High_8a-EWK">C1N2</a>; <br/><br/> <b>SR-High_8b-EWK Signal Efficiency:</b><a href="116034?version=1&table=GMSB eff in SR-High_8b-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 eff in SR-High_8b-EWK">C1N2</a>; <br/><br/> <b>SR-1J-High-EWK Signal Efficiency:</b><a href="116034?version=1&table=GMSB eff in SR-1J-High-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 eff in SR-1J-High-EWK">C1N2</a>; <br/><br/> <b>SR-llbb-EWK Signal Efficiency:</b><a href="116034?version=1&table=GMSB eff in SR-llbb-EWK">GMSB</a>; <a href="116034?version=1&table=C1N2 eff in SR-llbb-EWK">C1N2</a>; <br/><br/> <b>Truth Code snippets</b>, <b>SLHA files</b>, and <b>PYHF json likelihoods</b> are available under "Resources" (purple button on the left) ---- Record created with hepdata_lib 0.7.0: https://zenodo.org/record/4946277 and PYHF: https://doi.org/10.5281/zenodo.1169739
Breakdown of expected and observed yields in the two recursive-jigsaw reconstruction signal regions after a simultaneous fit of the the CRs. The two sets of regions are fit separately. The uncertainties include both statistical and systematic sources.
Breakdown of expected and observed yields in the electroweak search High and $\ell\ell bb$ signal regions after a simultaneous fit to the signal regions and control regions. All statistical and systematic uncertainties are included.
Breakdown of expected and observed yields in the electroweak search Int, Low, and OffShell signal regions after a simultaneous fit to the signal regions and control regions. All statistical and systematic uncertainties are included.
Breakdown of expected and observed yields in the four edge signal regions, integrated over the $m_{\ell\ell}$ distribution after a separate simultaneous fit to each signal region and control region pair. The uncertainties include both the statistical and systematic sources.
Breakdown of expected and observed yields in the three on-$Z$ signal regions after a separate simultaneous fit to each signal region and control region pair. The uncertainties include both the statistical and systematic sources.
Distributions of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in VR-High-Sideband-EWK (top-left), VR-High-R-EWK (top-right), VR-1J-High-EWK (bottom-left), and VR-$\ell\ell bb$-EWK (bottom-right) from the EWK search after a simultaneous fit of the control regions. The hatched band includes both the systematic and statistical uncertainties. The last bin includes the overflow.
Distributions of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in VR-High-Sideband-EWK (top-left), VR-High-R-EWK (top-right), VR-1J-High-EWK (bottom-left), and VR-$\ell\ell bb$-EWK (bottom-right) from the EWK search after a simultaneous fit of the control regions. The hatched band includes both the systematic and statistical uncertainties. The last bin includes the overflow.
Distributions of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in VR-High-Sideband-EWK (top-left), VR-High-R-EWK (top-right), VR-1J-High-EWK (bottom-left), and VR-$\ell\ell bb$-EWK (bottom-right) from the EWK search after a simultaneous fit of the control regions. The hatched band includes both the systematic and statistical uncertainties. The last bin includes the overflow.
Distributions of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in VR-High-Sideband-EWK (top-left), VR-High-R-EWK (top-right), VR-1J-High-EWK (bottom-left), and VR-$\ell\ell bb$-EWK (bottom-right) from the EWK search after a simultaneous fit of the control regions. The hatched band includes both the systematic and statistical uncertainties. The last bin includes the overflow.
Distributions of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in VR-Int-EWK (top-left), VR-Low-EWK (top-right), VR-Low-2-EWK (bottom-left), and VR-OffShell-EWK (bottom-right) from the EWK search after a simultaneous fit of the control regions. The hatched band includes both the systematic and statistical uncertainties. The last bin includes the overflow.
Distributions of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in VR-Int-EWK (top-left), VR-Low-EWK (top-right), VR-Low-2-EWK (bottom-left), and VR-OffShell-EWK (bottom-right) from the EWK search after a simultaneous fit of the control regions. The hatched band includes both the systematic and statistical uncertainties. The last bin includes the overflow.
Distributions of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in VR-Int-EWK (top-left), VR-Low-EWK (top-right), VR-Low-2-EWK (bottom-left), and VR-OffShell-EWK (bottom-right) from the EWK search after a simultaneous fit of the control regions. The hatched band includes both the systematic and statistical uncertainties. The last bin includes the overflow.
Distributions of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in VR-Int-EWK (top-left), VR-Low-EWK (top-right), VR-Low-2-EWK (bottom-left), and VR-OffShell-EWK (bottom-right) from the EWK search after a simultaneous fit of the control regions. The hatched band includes both the systematic and statistical uncertainties. The last bin includes the overflow.
Observed and expected dilepton mass distributions in VRC-STR (top-left), VRLow-STR (top-right), VRMed-STR (bottom-left), and VRHigh-STR (bottom-right). Each validation region is fit separately with the corresponding control region. All statistical and systematic uncertainties are included in the hatched band. The entries are normalized to the bin width, and the last bin is the overflow.
Observed and expected dilepton mass distributions in VRC-STR (top-left), VRLow-STR (top-right), VRMed-STR (bottom-left), and VRHigh-STR (bottom-right). Each validation region is fit separately with the corresponding control region. All statistical and systematic uncertainties are included in the hatched band. The entries are normalized to the bin width, and the last bin is the overflow.
Observed and expected dilepton mass distributions in VRC-STR (top-left), VRLow-STR (top-right), VRMed-STR (bottom-left), and VRHigh-STR (bottom-right). Each validation region is fit separately with the corresponding control region. All statistical and systematic uncertainties are included in the hatched band. The entries are normalized to the bin width, and the last bin is the overflow.
Observed and expected dilepton mass distributions in VRC-STR (top-left), VRLow-STR (top-right), VRMed-STR (bottom-left), and VRHigh-STR (bottom-right). Each validation region is fit separately with the corresponding control region. All statistical and systematic uncertainties are included in the hatched band. The entries are normalized to the bin width, and the last bin is the overflow.
Observed and expected jet multiplicity in VRLow-STR (top-left), VRMed-STR (top-right), and VRHigh-STR (bottom) after a fit performed on the $m_{\ell\ell}$ distribution and corresponding control region. All statistical and systematic uncertainties are included in the hatched band. The last bin contains the overflow.
Observed and expected jet multiplicity in VRLow-STR (top-left), VRMed-STR (top-right), and VRHigh-STR (bottom) after a fit performed on the $m_{\ell\ell}$ distribution and corresponding control region. All statistical and systematic uncertainties are included in the hatched band. The last bin contains the overflow.
Observed and expected jet multiplicity in VRLow-STR (top-left), VRMed-STR (top-right), and VRHigh-STR (bottom) after a fit performed on the $m_{\ell\ell}$ distribution and corresponding control region. All statistical and systematic uncertainties are included in the hatched band. The last bin contains the overflow.
Observed and expected dilepton mass distributions in VR3L-STR without a fit to the data. The 'Other' category includes the negligible contributions from $t\bar{t}$ and $Z/\gamma^*$+jets processes. The hatched band contains the statistical uncertainty and the theoretical systematic uncertainties of the $WZ$/$ZZ$ prediction, which are the dominant sources of uncertainty. No fit is performed. The last bin contains the overflow.
Observed and expected distributions in five EWK search regions after a simultaneous fit to the SR and CR. In the top row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-High_8-EWK and $m_{bb}$ in SR-$\ell\ell bb$-EWK. In the middle row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Int-EWK and $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Low-EWK. In the bottom row is $m_{\ell\ell}$ in SR-OffShell-EWK. Overlaid are example C1N2 and GMSB signal models, where the numbers in the brackets indicate the masses, in $\mathrm{GeV}$, of the $\tilde{\chi}_1^\pm$ and $\tilde{\chi}_2^0$ or the mass of the $\tilde{\chi}_1^0$ and branching ratio to the Higgs boson respectively. All statistical and systematic uncertainties are included in the hatched bands. The last bin includes the overflow.
Observed and expected distributions in five EWK search regions after a simultaneous fit to the SR and CR. In the top row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-High_8-EWK and $m_{bb}$ in SR-$\ell\ell bb$-EWK. In the middle row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Int-EWK and $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Low-EWK. In the bottom row is $m_{\ell\ell}$ in SR-OffShell-EWK. Overlaid are example C1N2 and GMSB signal models, where the numbers in the brackets indicate the masses, in $\mathrm{GeV}$, of the $\tilde{\chi}_1^\pm$ and $\tilde{\chi}_2^0$ or the mass of the $\tilde{\chi}_1^0$ and branching ratio to the Higgs boson respectively. All statistical and systematic uncertainties are included in the hatched bands. The last bin includes the overflow.
Observed and expected distributions in five EWK search regions after a simultaneous fit to the SR and CR. In the top row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-High_8-EWK and $m_{bb}$ in SR-$\ell\ell bb$-EWK. In the middle row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Int-EWK and $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Low-EWK. In the bottom row is $m_{\ell\ell}$ in SR-OffShell-EWK. Overlaid are example C1N2 and GMSB signal models, where the numbers in the brackets indicate the masses, in $\mathrm{GeV}$, of the $\tilde{\chi}_1^\pm$ and $\tilde{\chi}_2^0$ or the mass of the $\tilde{\chi}_1^0$ and branching ratio to the Higgs boson respectively. All statistical and systematic uncertainties are included in the hatched bands. The last bin includes the overflow.
Observed and expected distributions in five EWK search regions after a simultaneous fit to the SR and CR. In the top row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-High_8-EWK and $m_{bb}$ in SR-$\ell\ell bb$-EWK. In the middle row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Int-EWK and $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Low-EWK. In the bottom row is $m_{\ell\ell}$ in SR-OffShell-EWK. Overlaid are example C1N2 and GMSB signal models, where the numbers in the brackets indicate the masses, in $\mathrm{GeV}$, of the $\tilde{\chi}_1^\pm$ and $\tilde{\chi}_2^0$ or the mass of the $\tilde{\chi}_1^0$ and branching ratio to the Higgs boson respectively. All statistical and systematic uncertainties are included in the hatched bands. The last bin includes the overflow.
Observed and expected distributions in five EWK search regions after a simultaneous fit to the SR and CR. In the top row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-High_8-EWK and $m_{bb}$ in SR-$\ell\ell bb$-EWK. In the middle row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Int-EWK and $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Low-EWK. In the bottom row is $m_{\ell\ell}$ in SR-OffShell-EWK. Overlaid are example C1N2 and GMSB signal models, where the numbers in the brackets indicate the masses, in $\mathrm{GeV}$, of the $\tilde{\chi}_1^\pm$ and $\tilde{\chi}_2^0$ or the mass of the $\tilde{\chi}_1^0$ and branching ratio to the Higgs boson respectively. All statistical and systematic uncertainties are included in the hatched bands. The last bin includes the overflow.
Observed and expected dilepton mass distributions in SRC-STR (top-left), SRLow-STR (top-right), SRMed-STR (bottom-left), and SRHigh-STR (bottom-right), with the binning used for interpretations after a separate simultaneous fit to each signal region and control region pair. The red dashed lines are example signal models overlaid on the figure. All statistical and systematic uncertainties are included in the hatched bands. The last bins are the overflow.
Observed and expected dilepton mass distributions in SRC-STR (top-left), SRLow-STR (top-right), SRMed-STR (bottom-left), and SRHigh-STR (bottom-right), with the binning used for interpretations after a separate simultaneous fit to each signal region and control region pair. The red dashed lines are example signal models overlaid on the figure. All statistical and systematic uncertainties are included in the hatched bands. The last bins are the overflow.
Observed and expected dilepton mass distributions in SRC-STR (top-left), SRLow-STR (top-right), SRMed-STR (bottom-left), and SRHigh-STR (bottom-right), with the binning used for interpretations after a separate simultaneous fit to each signal region and control region pair. The red dashed lines are example signal models overlaid on the figure. All statistical and systematic uncertainties are included in the hatched bands. The last bins are the overflow.
Observed and expected dilepton mass distributions in SRC-STR (top-left), SRLow-STR (top-right), SRMed-STR (bottom-left), and SRHigh-STR (bottom-right), with the binning used for interpretations after a separate simultaneous fit to each signal region and control region pair. The red dashed lines are example signal models overlaid on the figure. All statistical and systematic uncertainties are included in the hatched bands. The last bins are the overflow.
Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].
Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].
Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].
Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].
Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].
Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].
Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].
Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].
Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].
Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].
Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].
Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].
Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294]. The grey numbers indicate the observed 95\% CLs upper limit on the cross section.
Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294]. The grey numbers indicate the observed 95$\%$ CLs upper limit on the cross section.
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$ ilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$ ilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$ ilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$ ilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].The grey numbers indicated the observed 95\% CL upper limit on the cross section.
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].The grey numbers indicated the observed 95\% CL upper limit on the cross section.
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].The grey numbers indicated the observed 95\% CL upper limit on the cross section.
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].
The combined $E_{\mathrm{T}}^{\mathrm{miss}}$ distribution of VRLow-STR and SRLow-STR (left), and the same region with the $\Delta\phi(\boldsymbol{j}_{1,2},\boldsymbol{\mathit{p}}_{ ext{T}}^{ ext{miss}})<0.4$ requirement, used as a control region to normalize the $Z/\gamma^*+\mathrm{jets}$ process (right). Separate fits for the SR and VR are performed, as for the results in the paper, and the resulting distributions are merged. All statistical and systematic uncertainties are included in the hatched bands. The last bins contain the overflow.
Cutflow of expected events in the four Strong search edge signal regions. `Leptons' refers to electrons and muons only. The gluino-$Z^{(*)}$ model with $m_{ ilde{g}}=800~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for SRC-STR with 60000 Monte Carlo (MC) events generated. The slepton-$Z^{(*)}$ model with $m_{ ilde{\ell}}=1200~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for SRMed-STR with 30000 (MC) events generated. The gluino-slepton model with $m_{ ilde{g}}=2~TeV$ and $m_{ ilde{\ell}}=1.3~TeV$ is used for SRLow-STR and SRHigh-STR with 30000 MC events generated. The Generator Filter requires two 5~GeV leptons and 100~GeV of \met. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~GeV$ or at least one lepton with $p_{\mathrm{T}}>25~GeV$ and a photon with $p_{\mathrm{T}}>40~GeV$, with all objects within $|\eta|=2.6$.
Cutflow of expected events in the four Strong search edge signal regions. `Leptons' refers to electrons and muons only. The gluino-$Z^{(*)}$ model with $m_{ ilde{g}}=800~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for SRC-STR with 60000 Monte Carlo (MC) events generated. The slepton-$Z^{(*)}$ model with $m_{ ilde{\ell}}=1200~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for SRMed-STR with 30000 (MC) events generated. The gluino-slepton model with $m_{ ilde{g}}=2~TeV$ and $m_{ ilde{\ell}}=1.3~TeV$ is used for SRLow-STR and SRHigh-STR with 30000 MC events generated. The Generator Filter requires two 5~GeV leptons and 100~GeV of \met. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~GeV$ or at least one lepton with $p_{\mathrm{T}}>25~GeV$ and a photon with $p_{\mathrm{T}}>40~GeV$, with all objects within $|\eta|=2.6$.
Cutflow of expected events in the four Strong search edge signal regions. `Leptons' refers to electrons and muons only. The gluino-$Z^{(*)}$ model with $m_{ ilde{g}}=800~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for SRC-STR with 60000 Monte Carlo (MC) events generated. The slepton-$Z^{(*)}$ model with $m_{ ilde{\ell}}=1200~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for SRMed-STR with 30000 (MC) events generated. The gluino-slepton model with $m_{ ilde{g}}=2~TeV$ and $m_{ ilde{\ell}}=1.3~TeV$ is used for SRLow-STR and SRHigh-STR with 30000 MC events generated. The Generator Filter requires two 5~GeV leptons and 100~GeV of \met. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~GeV$ or at least one lepton with $p_{\mathrm{T}}>25~GeV$ and a photon with $p_{\mathrm{T}}>40~GeV$, with all objects within $|\eta|=2.6$.
Cutflow of expected events in the four Strong search edge signal regions. `Leptons' refers to electrons and muons only. The gluino-$Z^{(*)}$ model with $m_{ ilde{g}}=800~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for SRC-STR with 60000 Monte Carlo (MC) events generated. The slepton-$Z^{(*)}$ model with $m_{ ilde{\ell}}=1200~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for SRMed-STR with 30000 (MC) events generated. The gluino-slepton model with $m_{ ilde{g}}=2~TeV$ and $m_{ ilde{\ell}}=1.3~TeV$ is used for SRLow-STR and SRHigh-STR with 30000 MC events generated. The Generator Filter requires two 5~GeV leptons and 100~GeV of \met. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~GeV$ or at least one lepton with $p_{\mathrm{T}}>25~GeV$ and a photon with $p_{\mathrm{T}}>40~GeV$, with all objects within $|\eta|=2.6$.
Cutflow of expected events in the three Strong search on-$Z$ signal regions. The cutflow up to the signal region specific requirements is the same as in the Strong search edge cutflow. The slepton-$Z^{(*)}$ model with $m_{ ilde{\ell}}=1200~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for all of the on-$Z$ signal regions with 30000 (MC) events generated.
Cutflow of expected events in the three Strong search on-$Z$ signal regions. The cutflow up to the signal region specific requirements is the same as in the Strong search edge cutflow. The slepton-$Z^{(*)}$ model with $m_{ ilde{\ell}}=1200~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for all of the on-$Z$ signal regions with 30000 (MC) events generated.
Cutflow of expected events in the three Strong search on-$Z$ signal regions. The cutflow up to the signal region specific requirements is the same as in the Strong search edge cutflow. The slepton-$Z^{(*)}$ model with $m_{ ilde{\ell}}=1200~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for all of the on-$Z$ signal regions with 30000 (MC) events generated.
Table 36: Cutflow of expected events in the region SR-OffShell_a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 36: Cutflow of expected events in the region SR-OffShell_a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 37: Cutflow of expected events in the region SR-OffShell_b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 37: Cutflow of expected events in the region SR-OffShell_b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 38: Cutflow of expected events in the region SR-Low_a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 38: Cutflow of expected events in the region SR-Low_a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 39: Cutflow of expected events in the region SR-Low_b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 39: Cutflow of expected events in the region SR-Low_b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 40: Cutflow of expected events in the region SR-Low-2-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 40: Cutflow of expected events in the region SR-Low-2-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 41: Cutflow of expected events in the region SR-Int_a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 41: Cutflow of expected events in the region SR-Int_a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 42: Cutflow of expected events in the region SR-Int_b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 42: Cutflow of expected events in the region SR-Int_b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 43: Cutflow of expected events in the region SR-High_16a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 43: Cutflow of expected events in the region SR-High_16a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 44: Cutflow of expected events in the region SR-High_16b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 44: Cutflow of expected events in the region SR-High_16b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 45: Cutflow of expected events in the region SR-High_8a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 45: Cutflow of expected events in the region SR-High_8a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 46: Cutflow of expected events in the region SR-High_8b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 46: Cutflow of expected events in the region SR-High_8b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 47: Cutflow of expected events in the region SR-1J-High-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 47: Cutflow of expected events in the region SR-1J-High-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 48: Cutflow of expected events in the region SR-llbb-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
Table 48: Cutflow of expected events in the region SR-llbb-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.
The combined $m_{jj}$ distribution of CR-Z-EWK and SR-Low-EWK (left), and the $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ distribution in CR-Z-met-EWK (right), which removes the upper limit of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}}) < 9$ from the definition of CR-Z-EWK. This $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ tail overlaps other control and validation regions, but not signal regions. The arrows indicate the signal region SR-Low-EWK (left), and the $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ phase space which is not included in CR-Z-EWK (right). All EWK search control and signal regions are included in the fit. All statistical and systematic uncertainties are included in the hatched bands. The theoretical uncertainties from CR-Z-EWK are applied to CR-Z-met-EWK. The last bins contain the overflow.
The combined $m_{jj}$ distribution of CR-Z-EWK and SR-Low-EWK (left), and the $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ distribution in CR-Z-met-EWK (right), which removes the upper limit of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}}) < 9$ from the definition of CR-Z-EWK. This $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ tail overlaps other control and validation regions, but not signal regions. The arrows indicate the signal region SR-Low-EWK (left), and the $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ phase space which is not included in CR-Z-EWK (right). All EWK search control and signal regions are included in the fit. All statistical and systematic uncertainties are included in the hatched bands. The theoretical uncertainties from CR-Z-EWK are applied to CR-Z-met-EWK. The last bins contain the overflow.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-1J-High-EWK and SR-$\ell\ell bb$-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-1J-High-EWK and SR-$\ell\ell bb$-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-1J-High-EWK and SR-$\ell\ell bb$-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-1J-High-EWK and SR-$\ell\ell bb$-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-1J-High-EWK and SR-$\ell\ell bb$-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-1J-High-EWK and SR-$\ell\ell bb$-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-1J-High-EWK and SR-$\ell\ell bb$-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-1J-High-EWK and SR-$\ell\ell bb$-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_SLN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_SLN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_SLN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_SLN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_SLN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_SLN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_SLN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_SLN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.
A search for a long-lived, heavy neutral lepton ($\mathcal{N}$) in 139 fb$^{-1}$ of $\sqrt{s}=13$ TeV $pp$ collision data collected by the ATLAS detector at the Large Hadron Collider is reported. The $\mathcal{N}$ is produced via $W \rightarrow \mathcal{N} \mu$ or $W \rightarrow \mathcal{N} e$ and decays into two charged leptons and a neutrino, forming a displaced vertex. The $\mathcal{N}$ mass is used to discriminate between signal and background. No signal is observed, and limits are set on the squared mixing parameters of the $\mathcal{N}$ with the left-handed neutrino states for the $\mathcal{N}$ mass range $3$ GeV $< m_{\mathcal{N}} < 15$ GeV. For the first time, limits are given for both single-flavor and multiflavor mixing scenarios motivated by neutrino flavor oscillation results for both the normal and inverted neutrino-mass hierarchies.
Expected and observed 95% CL for the 1SFH e Dirac model.
Expected and observed 95% CL for the 1SFH e Majorana model.
Expected and observed 95% CL for the 1SFH mu Dirac model.
Expected and observed 95% CL for the 1SFH mu Majorana model.
Expected and observed 95% CL for the 2QDH NH Dirac model.
Expected and observed 95% CL for the 2QDH NH Majorana model.
Expected and observed 95% CL for the 2QDH IH Dirac model.
Expected and observed 95% CL for the 2QDH IH Majorana model.
Cutflow for six simulated signal channels showing the weighted number of expected events based on the single-flavour mixing model in the Majorana limit. Each column uses the generated signal sample with the mass hypothesis $m_N = 10$ GeV and proper decay length $c\tau_N = 10$ mm.
Cutflow for the six channels in data showing the number of events passing each successive signal selection for Majorana HNLs.
The event selection efficiency for each mass-lifetime point in all six studied channels. Shown is the fraction of the produced MC simulation events that pass all signal region selections. An entry of 0 indicates no events were selected.
The dominant signal uncertainty is due to differences in reconstruction of displaced vertices and tracks between data and MC. This is evaluated by comparing $K^{0}_{S} \rightarrow \pi^+\pi^-$ event yields in the VR and in MC produced with Pythia8.186 in bins of $p_\mathrm{T}$ and $r_\mathrm{DV}$. The data/MC ratio is normalized to the bin nearest the IP where the tracking and vertexing reconstruction algorithms are expected to be most robust. The symmetrized difference from 1.0 is applied to each signal vertex as a per-event systematic variation.
Expected and observed yields in the different analysis regions (prefit) for the 1SFH e Dirac model (10 GeV, 10mm).
Expected and observed yields in the different analysis regions (postfit) for the 1SFH e Dirac model (10 GeV, 10mm).
Expected and observed yields in the different analysis regions (prefit) for the 1SFH e Majorana model (10 GeV, 10mm).
Expected and observed yields in the different analysis regions (postfit) for the 1SFH e Majorana model (10 GeV, 10mm).
Expected and observed yields in the different analysis regions (prefit) for the 1SFH u Dirac model (10 GeV, 10mm).
Expected and observed yields in the different analysis regions (postfit) for the 1SFH u Dirac model (10 GeV, 10mm).
Expected and observed yields in the different analysis regions (prefit) for the 1SFH u Majorana model (10 GeV, 10mm).
Expected and observed yields in the different analysis regions (postfit) for the 1SFH u Majorana model (10 GeV, 10mm).
Expected and observed yields in the different analysis regions (prefit) for the 2QDH (NH) Dirac model (10 GeV, 10mm).
Expected and observed yields in the different analysis regions (postfit) for the 2QDH (NH) Dirac model (10 GeV, 10mm).
Expected and observed yields in the different analysis regions (prefit) for the 2QDH (NH) Majorana model (10 GeV, 10mm).
Expected and observed yields in the different analysis regions (postfit) for the 2QDH (NH) Majorana model (10 GeV, 10mm).
Expected and observed yields in the different analysis regions (prefit) for the 2QDH (IH) Dirac model (10 GeV, 10mm).
Expected and observed yields in the different analysis regions (postfit) for the 2QDH (IH) Dirac model (10 GeV, 10mm).
Expected and observed yields in the different analysis regions (prefit) for the 2QDH (IH) Majorana model (10 GeV, 10mm).
Expected and observed yields in the different analysis regions (postfit) for the 2QDH (IH) Majorana model (10 GeV, 10mm).
The total displaced vertexing efficiency as a function of $r_{DV}$ for the custom configuration used in this analysis. The definition of the secondary vertex efficiency can be found in defined in \cite{ATL-PHYS-PUB-2019-013}. The efficiency is shown for $\mu-\mu\mu$, $\mu-\mu e$ and $\mu-ee$ signals with $m_N=10$~GeV and $c\tau_N=10$~mm.
A search for a heavy resonance decaying into a top quark and a W boson in proton-proton collisions at $\sqrt{s} =$ 13 TeV is presented. The data analyzed were recorded with the CMS detector at the LHC and correspond to an integrated luminosity of 138 fb$^{-1}$. The top quark is reconstructed as a single jet and the W boson, from its decay into an electron or muon and the corresponding neutrino. A top quark tagging technique based on jet clustering with a variable distance parameter and simultaneous jet grooming is used to identify jets from the collimated top quark decay. The results are interpreted in the context of two benchmark models, where the heavy resonance is either an excited bottom quark b$^*$ or a vector-like quark B. A statistical combination with an earlier search by the CMS Collaboration in the all-hadronic final state is performed to place upper cross section limits on these two models. The new analysis extends the lower range of resonance mass probed from 1.4 down to 0.7 TeV. For left-handed, right-handed, and vector-like couplings, b$^*$ masses up to 3.0, 3.0, and 3.2 TeV are excluded at 95% confidence level, respectively. The observed upper limits represent the most stringent constraints on the b$^*$ model to date.
Distributions of MtW in the 1b category. The data are shown by filled markers, where the horizontal bars indicate the bin widths. The individual background contributions are given by filled histograms. The expected signal for a LH b* with mb∗ = 2.4 TeV is shown by a dashed line. The shaded region is the uncertainty in the total background estimate. The lower panel shows the ratio of data to the background estimate, with the total uncertainty on the predicted background displayed as the gray band.
Distributions of MtW in the 2b category. The data are shown by filled markers, where the horizontal bars indicate the bin widths. The individual background contributions are given by filled histograms. The expected signal for a LH b* with mb∗ = 2.4 TeV is shown by a dashed line. The shaded region is the uncertainty in the total background estimate. The lower panel shows the ratio of data to the background estimate, with the total uncertainty on the predicted background displayed as the gray band.
Upper limits on the production cross section times branching fraction of the b* LH hypothesis at a 95% CL. Dashed colored lines show the expected limits from the l+jets and all-hadronic channels, where the latter start at resonance masses of 1.4 TeV. The observed and expected limits from the combination are shown as solid and dashed black lines, respectively. The green and yellow bands show the 68 and 95% confidence intervals on the combined expected limits.
Upper limits on the production cross section times branching fraction of the b* RH hypothesis at a 95% CL. Dashed colored lines show the expected limits from the l+jets and all-hadronic channels, where the latter start at resonance masses of 1.4 TeV. The observed and expected limits from the combination are shown as solid and dashed black lines, respectively. The green and yellow bands show the 68 and 95% confidence intervals on the combined expected limits.
Upper limits on the production cross section times branching fraction of the b* VL hypothesis at a 95% CL. Dashed colored lines show the expected limits from the l+jets and all-hadronic channels, where the latter start at resonance masses of 1.4 TeV. The observed and expected limits from the combination are shown as solid and dashed black lines, respectively. The green and yellow bands show the 68 and 95% confidence intervals on the combined expected limits.
Upper limits on the production cross section times branching fraction of the B+b hypothesis at a 95% CL. Dashed colored lines show the expected limits from the l+jets and all-hadronic channels, where the latter start at resonance masses of 1.4 TeV. The observed and expected limits from the combination are shown as solid and dashed black lines, respectively. The green and yellow bands show the 68 and 95% confidence intervals on the combined expected limits.
Upper limits on the production cross section times branching fraction of the B+t hypothesis at a 95% CL. Dashed colored lines show the expected limits from the l+jets and all-hadronic channels, where the latter start at resonance masses of 1.4 TeV. The observed and expected limits from the combination are shown as solid and dashed black lines, respectively. The green and yellow bands show the 68 and 95% confidence intervals on the combined expected limits.
Proton-proton interactions resulting in final states with two photons are studied in a search for the signature of flavor-changing neutral current interactions of top quarks (t) and Higgs bosons (H). The analysis is based on data collected at a center-of-mass energy of 13 TeV with the CMS detector at the LHC, corresponding to an integrated luminosity of 137 fb$^{-1}$. No significant excess above the background prediction is observed. Upper limits on the branching fractions ($\mathcal{B}$) of the top quark decaying to a Higgs boson and an up (u) or charm quark (c) are derived through a binned fit to the diphoton invariant mass spectrum. The observed (expected) 95% confidence level upper limits are found to be 0.019 (0.031)% for $\mathcal B$(t $\to$ Hu) and 0.073 (0.051)% for $\mathcal{B}$(t $\to$ Hc). These are the strictest upper limits yet determined.
Expected and observed 95\% CL upper limits on the branching fraction of the top quark decaying to the Higgs boson and a light-flavor quark (either an up or a charm quark)
A search for low-mass dilepton resonances in Higgs boson decays is conducted in the four-lepton final state. The decay is assumed to proceed via a pair of beyond the standard model particles, or one such particle and a Z boson. The search uses proton-proton collision data collected with the CMS detector at the CERN LHC, corresponding to an integrated luminosity of 137 fb$^{-1}$, at a center-of-mass energy $\sqrt{s} =$ 13 TeV. No significant deviation from the standard model expectation is observed. Upper limits at 95% confidence level are set on model-independent Higgs boson decay branching fractions. Additionally, limits on dark photon and axion-like particle production, based on two specific models, are reported.
Exclusion limit for BrHXX_Br2Xee
Exclusion limit for BrHXX_Br2Xmumu
Exclusion limit for BrHXX_Br2Xll
Exclusion limit for BrHZX_BrXee
Exclusion limit for BrHZX_BrXmumu
Exclusion limit for BrHZX_BrXll
Exclusion limit for cah
Exclusion limit for cZh
Exclusion limit for kappa
A search for chargino$-$neutralino pair production in three-lepton final states with missing transverse momentum is presented. The study is based on a dataset of $\sqrt{s} = 13$ TeV $pp$ collisions recorded with the ATLAS detector at the LHC, corresponding to an integrated luminosity of 139 fb$^{-1}$. No significant excess relative to the Standard Model predictions is found in data. The results are interpreted in simplified models of supersymmetry, and statistically combined with results from a previous ATLAS search for compressed spectra in two-lepton final states. Various scenarios for the production and decay of charginos ($\tilde\chi^\pm_1$) and neutralinos ($\tilde\chi^0_2$) are considered. For pure higgsino $\tilde\chi^\pm_1\tilde\chi^0_2$ pair-production scenarios, exclusion limits at 95% confidence level are set on $\tilde\chi^0_2$ masses up to 210 GeV. Limits are also set for pure wino $\tilde\chi^\pm_1\tilde\chi^0_2$ pair production, on $\tilde\chi^0_2$ masses up to 640 GeV for decays via on-shell $W$ and $Z$ bosons, up to 300 GeV for decays via off-shell $W$ and $Z$ bosons, and up to 190 GeV for decays via $W$ and Standard Model Higgs bosons.
This is the HEPData space for the ATLAS SUSY EWK three-lepton search. The full resolution figures can be found at https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/SUSY-2019-09/ The full statistical likelihoods have been provided for this analysis. They can be downloaded by clicking on the purple 'Resources' button above and selecting the 'Common Resources' category. <b>Region yields:</b> <ul display="inline-block"> <li><a href="?table=Tab%2012%20Onshell%20WZ%20Signal%20Region%20Yields%20Table">Tab 12 Onshell WZ Signal Region Yields Table</a> <li><a href="?table=Tab%2013%20Onshell%20Wh%20Signal%20Region%20Yields%20Table">Tab 13 Onshell Wh Signal Region Yields Table</a> <li><a href="?table=Tab%2014%20Offshell%20low-$E_{T}^{miss}$%20Signal%20Region%20Yields%20Table">Tab 14 Offshell low-$E_{T}^{miss}$ Signal Region Yields Table</a> <li><a href="?table=Tab%2015%20Offshell%20high-$E_{T}^{miss}$%20Signal%20Region%20Yields%20Table">Tab 15 Offshell high-$E_{T}^{miss}$ Signal Region Yields Table</a> <li><a href="?table=Tab%2020%20RJR%20Signal%20Region%20Yields%20Table">Tab 20 RJR Signal Region Yields Table</a> <li><a href="?table=Fig%204%20Onshell%20Control%20and%20Validation%20Region%20Yields">Fig 4 Onshell Control and Validation Region Yields</a> <li><a href="?table=Fig%208%20Offshell%20Control%20and%20Validation%20Region%20Yields">Fig 8 Offshell Control and Validation Region Yields</a> <li><a href="?table=Fig%2010%20Onshell%20WZ%20Signal%20Region%20Yields">Fig 10 Onshell WZ Signal Region Yields</a> <li><a href="?table=Fig%2011%20Onshell%20Wh%20Signal%20Region%20Yields">Fig 11 Onshell Wh Signal Region Yields</a> <li><a href="?table=Fig%2012%20Offshell%20Signal%20Region%20Yields">Fig 12 Offshell Signal Region Yields</a> <li><a href="?table=Fig%2018%20RJR%20Control%20and%20Validation%20Region%20Yields">Fig 18 RJR Control and Validation Region Yields</a> </ul> <b>Exclusion contours:</b> <ul display="inline-block"> <li><a href="?table=Fig%2016a%20WZ%20Exclusion:%20Wino-bino(%2b),%20Obs">Fig 16a WZ Exclusion: Wino-bino(+), Obs</a> <li><a href="?table=Fig%2016a%20WZ%20Exclusion:%20Wino-bino(%2b),%20Obs_Up">Fig 16a WZ Exclusion: Wino-bino(+), Obs_Up</a> <li><a href="?table=Fig%2016a%20WZ%20Exclusion:%20Wino-bino(%2b),%20Obs_Down">Fig 16a WZ Exclusion: Wino-bino(+), Obs_Down</a> <li><a href="?table=Fig%2016a%20WZ%20Exclusion:%20Wino-bino(%2b),%20Exp">Fig 16a WZ Exclusion: Wino-bino(+), Exp</a> <li><a href="?table=Fig%2016a%20WZ%20Exclusion:%20Wino-bino(%2b),%20Exp_Up">Fig 16a WZ Exclusion: Wino-bino(+), Exp_Up</a> <li><a href="?table=Fig%2016a%20WZ%20Exclusion:%20Wino-bino(%2b),%20Exp_Down">Fig 16a WZ Exclusion: Wino-bino(+), Exp_Down</a> <li><a href="?table=Fig%2016a%20WZ%20Exclusion:%20Wino-bino(%2b),%20compressed_Obs">Fig 16a WZ Exclusion: Wino-bino(+), compressed_Obs</a> <li><a href="?table=Fig%2016a%20WZ%20Exclusion:%20Wino-bino(%2b),%20compressed_Exp">Fig 16a WZ Exclusion: Wino-bino(+), compressed_Exp</a> <li><a href="?table=Fig%2016a%20WZ%20Exclusion:%20Wino-bino(%2b),%20offshell_Obs">Fig 16a WZ Exclusion: Wino-bino(+), offshell_Obs</a> <li><a href="?table=Fig%2016a%20WZ%20Exclusion:%20Wino-bino(%2b),%20offshell_Exp">Fig 16a WZ Exclusion: Wino-bino(+), offshell_Exp</a> <li><a href="?table=Fig%2016a%20WZ%20Exclusion:%20Wino-bino(%2b),%20onshell_Obs">Fig 16a WZ Exclusion: Wino-bino(+), onshell_Obs</a> <li><a href="?table=Fig%2016a%20WZ%20Exclusion:%20Wino-bino(%2b),%20onshell_Exp">Fig 16a WZ Exclusion: Wino-bino(+), onshell_Exp</a> <li><a href="?table=Fig%2016b%20WZ%20Exclusion:%20Wino-bino(%2b)%20($\Delta%20m$),%20Obs">Fig 16b WZ Exclusion: Wino-bino(+) ($\Delta m$), Obs</a> <li><a href="?table=Fig%2016b%20WZ%20Exclusion:%20Wino-bino(%2b)%20($\Delta%20m$),%20Obs_Up">Fig 16b WZ Exclusion: Wino-bino(+) ($\Delta m$), Obs_Up</a> <li><a href="?table=Fig%2016b%20WZ%20Exclusion:%20Wino-bino(%2b)%20($\Delta%20m$),%20Obs_Down">Fig 16b WZ Exclusion: Wino-bino(+) ($\Delta m$), Obs_Down</a> <li><a href="?table=Fig%2016b%20WZ%20Exclusion:%20Wino-bino(%2b)%20($\Delta%20m$),%20Exp">Fig 16b WZ Exclusion: Wino-bino(+) ($\Delta m$), Exp</a> <li><a href="?table=Fig%2016b%20WZ%20Exclusion:%20Wino-bino(%2b)%20($\Delta%20m$),%20Exp_Up">Fig 16b WZ Exclusion: Wino-bino(+) ($\Delta m$), Exp_Up</a> <li><a href="?table=Fig%2016b%20WZ%20Exclusion:%20Wino-bino(%2b)%20($\Delta%20m$),%20Exp_Down">Fig 16b WZ Exclusion: Wino-bino(+) ($\Delta m$), Exp_Down</a> <li><a href="?table=Fig%2016b%20WZ%20Exclusion:%20Wino-bino(%2b)%20($\Delta%20m$),%20compressed_Obs">Fig 16b WZ Exclusion: Wino-bino(+) ($\Delta m$), compressed_Obs</a> <li><a href="?table=Fig%2016b%20WZ%20Exclusion:%20Wino-bino(%2b)%20($\Delta%20m$),%20compressed_Exp">Fig 16b WZ Exclusion: Wino-bino(+) ($\Delta m$), compressed_Exp</a> <li><a href="?table=Fig%2016b%20WZ%20Exclusion:%20Wino-bino(%2b)%20($\Delta%20m$),%20offshell_Obs">Fig 16b WZ Exclusion: Wino-bino(+) ($\Delta m$), offshell_Obs</a> <li><a href="?table=Fig%2016b%20WZ%20Exclusion:%20Wino-bino(%2b)%20($\Delta%20m$),%20offshell_Exp">Fig 16b WZ Exclusion: Wino-bino(+) ($\Delta m$), offshell_Exp</a> <li><a href="?table=Fig%2016b%20WZ%20Exclusion:%20Wino-bino(%2b)%20($\Delta%20m$),%20onshell_Obs">Fig 16b WZ Exclusion: Wino-bino(+) ($\Delta m$), onshell_Obs</a> <li><a href="?table=Fig%2016b%20WZ%20Exclusion:%20Wino-bino(%2b)%20($\Delta%20m$),%20onshell_Exp">Fig 16b WZ Exclusion: Wino-bino(+) ($\Delta m$), onshell_Exp</a> <li><a href="?table=Fig%2016c%20WZ%20Exclusion:%20Wino-bino(-)%20($\Delta%20m$),%20Obs">Fig 16c WZ Exclusion: Wino-bino(-) ($\Delta m$), Obs</a> <li><a href="?table=Fig%2016c%20WZ%20Exclusion:%20Wino-bino(-)%20($\Delta%20m$),%20Obs_Up">Fig 16c WZ Exclusion: Wino-bino(-) ($\Delta m$), Obs_Up</a> <li><a href="?table=Fig%2016c%20WZ%20Exclusion:%20Wino-bino(-)%20($\Delta%20m$),%20Obs_Down">Fig 16c WZ Exclusion: Wino-bino(-) ($\Delta m$), Obs_Down</a> <li><a href="?table=Fig%2016c%20WZ%20Exclusion:%20Wino-bino(-)%20($\Delta%20m$),%20Exp">Fig 16c WZ Exclusion: Wino-bino(-) ($\Delta m$), Exp</a> <li><a href="?table=Fig%2016c%20WZ%20Exclusion:%20Wino-bino(-)%20($\Delta%20m$),%20Exp_Up">Fig 16c WZ Exclusion: Wino-bino(-) ($\Delta m$), Exp_Up</a> <li><a href="?table=Fig%2016c%20WZ%20Exclusion:%20Wino-bino(-)%20($\Delta%20m$),%20Exp_Down">Fig 16c WZ Exclusion: Wino-bino(-) ($\Delta m$), Exp_Down</a> <li><a href="?table=Fig%2016c%20WZ%20Exclusion:%20Wino-bino(-)%20($\Delta%20m$),%20compressed_Obs">Fig 16c WZ Exclusion: Wino-bino(-) ($\Delta m$), compressed_Obs</a> <li><a href="?table=Fig%2016c%20WZ%20Exclusion:%20Wino-bino(-)%20($\Delta%20m$),%20compressed_Exp">Fig 16c WZ Exclusion: Wino-bino(-) ($\Delta m$), compressed_Exp</a> <li><a href="?table=Fig%2016c%20WZ%20Exclusion:%20Wino-bino(-)%20($\Delta%20m$),%20offshell_Obs">Fig 16c WZ Exclusion: Wino-bino(-) ($\Delta m$), offshell_Obs</a> <li><a href="?table=Fig%2016c%20WZ%20Exclusion:%20Wino-bino(-)%20($\Delta%20m$),%20offshell_Exp">Fig 16c WZ Exclusion: Wino-bino(-) ($\Delta m$), offshell_Exp</a> <li><a href="?table=Fig%2016d%20WZ%20Exclusion:%20Higgsino%20($\Delta%20m$),%20Obs">Fig 16d WZ Exclusion: Higgsino ($\Delta m$), Obs</a> <li><a href="?table=Fig%2016d%20WZ%20Exclusion:%20Higgsino%20($\Delta%20m$),%20Obs_Up">Fig 16d WZ Exclusion: Higgsino ($\Delta m$), Obs_Up</a> <li><a href="?table=Fig%2016d%20WZ%20Exclusion:%20Higgsino%20($\Delta%20m$),%20Obs_Down">Fig 16d WZ Exclusion: Higgsino ($\Delta m$), Obs_Down</a> <li><a href="?table=Fig%2016d%20WZ%20Exclusion:%20Higgsino%20($\Delta%20m$),%20Exp">Fig 16d WZ Exclusion: Higgsino ($\Delta m$), Exp</a> <li><a href="?table=Fig%2016d%20WZ%20Exclusion:%20Higgsino%20($\Delta%20m$),%20Exp_Up">Fig 16d WZ Exclusion: Higgsino ($\Delta m$), Exp_Up</a> <li><a href="?table=Fig%2016d%20WZ%20Exclusion:%20Higgsino%20($\Delta%20m$),%20Exp_Down">Fig 16d WZ Exclusion: Higgsino ($\Delta m$), Exp_Down</a> <li><a href="?table=Fig%2016d%20WZ%20Exclusion:%20Higgsino%20($\Delta%20m$),%20compressed_Obs">Fig 16d WZ Exclusion: Higgsino ($\Delta m$), compressed_Obs</a> <li><a href="?table=Fig%2016d%20WZ%20Exclusion:%20Higgsino%20($\Delta%20m$),%20compressed_Exp">Fig 16d WZ Exclusion: Higgsino ($\Delta m$), compressed_Exp</a> <li><a href="?table=Fig%2016d%20WZ%20Exclusion:%20Higgsino%20($\Delta%20m$),%20offshell_Obs">Fig 16d WZ Exclusion: Higgsino ($\Delta m$), offshell_Obs</a> <li><a href="?table=Fig%2016d%20WZ%20Exclusion:%20Higgsino%20($\Delta%20m$),%20offshell_Exp">Fig 16d WZ Exclusion: Higgsino ($\Delta m$), offshell_Exp</a> <li><a href="?table=Fig%2017%20Wh%20Exclusion,%20Obs">Fig 17 Wh Exclusion, Obs</a> <li><a href="?table=Fig%2017%20Wh%20Exclusion,%20Obs_Up">Fig 17 Wh Exclusion, Obs_Up</a> <li><a href="?table=Fig%2017%20Wh%20Exclusion,%20Obs_Down">Fig 17 Wh Exclusion, Obs_Down</a> <li><a href="?table=Fig%2017%20Wh%20Exclusion,%20Exp">Fig 17 Wh Exclusion, Exp</a> <li><a href="?table=Fig%2017%20Wh%20Exclusion,%20Exp_Up">Fig 17 Wh Exclusion, Exp_Up</a> <li><a href="?table=Fig%2017%20Wh%20Exclusion,%20Exp_Down">Fig 17 Wh Exclusion, Exp_Down</a> </ul> <b>Upper limits:</b> <ul display="inline-block"> <li><a href="?table=AuxFig%208a%20WZ%20Excl.%20Upper%20Limit%20Obs.%20Wino-bino(%2b)%20($\Delta%20m$)">AuxFig 8a WZ Excl. Upper Limit Obs. Wino-bino(+) ($\Delta m$)</a> <li><a href="?table=AuxFig%208b%20WZ%20Excl.%20Upper%20Limit%20Exp.%20Wino-bino(%2b)%20($\Delta%20m$)">AuxFig 8b WZ Excl. Upper Limit Exp. Wino-bino(+) ($\Delta m$)</a> <li><a href="?table=AuxFig%208c%20WZ%20Excl.%20Upper%20Limit%20Obs.%20Wino-bino(%2b)%20($\Delta%20m$)">AuxFig 8c WZ Excl. Upper Limit Obs. Wino-bino(+) ($\Delta m$)</a> <li><a href="?table=AuxFig%208d%20WZ%20Excl.%20Upper%20Limit%20Exp.%20Wino-bino(%2b)%20($\Delta%20m$)">AuxFig 8d WZ Excl. Upper Limit Exp. Wino-bino(+) ($\Delta m$)</a> <li><a href="?table=AuxFig%208e%20WZ%20Excl.%20Upper%20Limit%20Obs.%20Wino-bino(-)%20($\Delta%20m$)">AuxFig 8e WZ Excl. Upper Limit Obs. Wino-bino(-) ($\Delta m$)</a> <li><a href="?table=AuxFig%208f%20WZ%20Excl.%20Upper%20Limit%20Exp.%20Wino-bino(-)%20($\Delta%20m$)">AuxFig 8f WZ Excl. Upper Limit Exp. Wino-bino(-) ($\Delta m$)</a> <li><a href="?table=AuxFig%208g%20WZ%20Excl.%20Upper%20Limit%20Obs.%20Higgsino%20($\Delta%20m$)">AuxFig 8g WZ Excl. Upper Limit Obs. Higgsino ($\Delta m$)</a> <li><a href="?table=AuxFig%208h%20WZ%20Excl.%20Upper%20Limit%20Exp.%20Higgsino%20($\Delta%20m$)">AuxFig 8h WZ Excl. Upper Limit Exp. Higgsino ($\Delta m$)</a> <li><a href="?table=AuxFig%209a%20Wh%20Excl.%20Upper%20Limit%20Obs.">AuxFig 9a Wh Excl. Upper Limit Obs.</a> <li><a href="?table=AuxFig%209b%20Wh%20Excl.%20Upper%20Limit%20Exp.">AuxFig 9b Wh Excl. Upper Limit Exp.</a> </ul> <b>Model-independent discovery fits:</b> <ul display="inline-block"> <li><a href="?table=Tab%2018%20Onshell%20Discovery%20Fit%20Table">Tab 18 Onshell Discovery Fit Table</a> <li><a href="?table=Tab%2019%20Offshell%20Discovery%20Fit%20Table">Tab 19 Offshell Discovery Fit Table</a> <li><a href="?table=Tab%2021%20RJR%20Discovery%20Fit%20Table">Tab 21 RJR Discovery Fit Table</a> </ul> <b>Kinematic distributions:</b> <ul display="inline-block"> <li><a href="?table=Fig%2013a%20SR$_{DFOS}^{Wh}$-1%20($\Delta%20R_{OS,%20near}$)">Fig 13a SR$_{DFOS}^{Wh}$-1 ($\Delta R_{OS, near}$)</a> <li><a href="?table=Fig%2013b%20SR$_{DFOS}^{Wh}$-2%20(3rd%20Lep.%20$p_{T}$)">Fig 13b SR$_{DFOS}^{Wh}$-2 (3rd Lep. $p_{T}$)</a> <li><a href="?table=Fig%2013c%20SR$_{0j}^{WZ}$%20($E_{T}^{miss}$)">Fig 13c SR$_{0j}^{WZ}$ ($E_{T}^{miss}$)</a> <li><a href="?table=Fig%2013d%20SR$_{0j}^{WZ}$%20($m_{T}$)">Fig 13d SR$_{0j}^{WZ}$ ($m_{T}$)</a> <li><a href="?table=Fig%2014a%20SR$^{offWZ}_{LowETmiss}$-0j%20($m_{T}^{minmll}$)">Fig 14a SR$^{offWZ}_{LowETmiss}$-0j ($m_{T}^{minmll}$)</a> <li><a href="?table=Fig%2014b%20SR$^{offWZ}_{LowETmiss}$-nj%20($m_{T}^{minmll}$)">Fig 14b SR$^{offWZ}_{LowETmiss}$-nj ($m_{T}^{minmll}$)</a> <li><a href="?table=Fig%2014c%20SR$^{offWZ}_{HighETmiss}$-0j%20($m_{T}^{minmll}$)">Fig 14c SR$^{offWZ}_{HighETmiss}$-0j ($m_{T}^{minmll}$)</a> <li><a href="?table=Fig%2014d%20SR$^{offWZ}_{HighETmiss}$-nj%20($p_T^l%20\div%20E_T^{miss}$)">Fig 14d SR$^{offWZ}_{HighETmiss}$-nj ($p_T^l \div E_T^{miss}$)</a> <li><a href="?table=Fig%2020a%20RJR%20SR3$\ell$-Low%20($p_{T}^{\ell%201}$)">Fig 20a RJR SR3$\ell$-Low ($p_{T}^{\ell 1}$)</a> <li><a href="?table=Fig%2020b%20RJR%20SR3$\ell$-Low%20($H_{3,1}^{PP}$)">Fig 20b RJR SR3$\ell$-Low ($H_{3,1}^{PP}$)</a> <li><a href="?table=Fig%2020c%20RJR%20SR3$\ell$-ISR%20($p_{T~ISR}^{CM}$)">Fig 20c RJR SR3$\ell$-ISR ($p_{T~ISR}^{CM}$)</a> <li><a href="?table=Fig%2020d%20RJR%20SR3$\ell$-ISR%20($R_{ISR}$)">Fig 20d RJR SR3$\ell$-ISR ($R_{ISR}$)</a> </ul> <b>Cutflows:</b> <ul display="inline-block"> <li><a href="?table=AuxTab%205%20Cutflow:%20Onshell%20WZ">AuxTab 5 Cutflow: Onshell WZ</a> <li><a href="?table=AuxTab%206%20Cutflow:%20Onshell%20Wh">AuxTab 6 Cutflow: Onshell Wh</a> <li><a href="?table=AuxTab%207%20Cutflow:%20Offshell%20Wino-bino(%2b)%20(250,235)">AuxTab 7 Cutflow: Offshell Wino-bino(+) (250,235)</a> <li><a href="?table=AuxTab%208%20Cutflow:%20Offshell%20Wino-bino(%2b)%20(125,85)">AuxTab 8 Cutflow: Offshell Wino-bino(+) (125,85)</a> <li><a href="?table=AuxTab%209%20Cutflow:%20Offshell%20Wino-bino(%2b)%20(250,170)">AuxTab 9 Cutflow: Offshell Wino-bino(+) (250,170)</a> <li><a href="?table=AuxTab%2010%20Cutflow:%20Offshell%20Wino-bino(-)%20(250,235)">AuxTab 10 Cutflow: Offshell Wino-bino(-) (250,235)</a> <li><a href="?table=AuxTab%2011%20Cutflow:%20Offshell%20Wino-bino(-)%20(125,85)">AuxTab 11 Cutflow: Offshell Wino-bino(-) (125,85)</a> <li><a href="?table=AuxTab%2012%20Cutflow:%20Offshell%20Wino-bino(-)%20(250,170)">AuxTab 12 Cutflow: Offshell Wino-bino(-) (250,170)</a> <li><a href="?table=AuxTab%2013%20Cutflow:%20Offshell%20Higgsino%20(120,100)">AuxTab 13 Cutflow: Offshell Higgsino (120,100)</a> <li><a href="?table=AuxTab%2014%20Cutflow:%20Offshell%20Higgsino%20(100,40)">AuxTab 14 Cutflow: Offshell Higgsino (100,40)</a> <li><a href="?table=AuxTab%2015%20Cutflow:%20Offshell%20Higgsino%20(185,125)">AuxTab 15 Cutflow: Offshell Higgsino (185,125)</a> </ul> <b>Acceptances and Efficiencies:</b> <ul display="inline-block"> <li><a href="?table=AuxFig%2010a%20Acc:%20Onshell%20SR$_{0j}^{WZ}$">AuxFig 10a Acc: Onshell SR$_{0j}^{WZ}$</a> <li><a href="?table=AuxFig%2010b%20Eff:%20Onshell%20SR$_{0j}^{WZ}$">AuxFig 10b Eff: Onshell SR$_{0j}^{WZ}$</a> <li><a href="?table=AuxFig%2010c%20Acc:%20Onshell%20SR$_{nj}^{WZ}$">AuxFig 10c Acc: Onshell SR$_{nj}^{WZ}$</a> <li><a href="?table=AuxFig%2010d%20Eff:%20Onshell%20SR$_{nj}^{WZ}$">AuxFig 10d Eff: Onshell SR$_{nj}^{WZ}$</a> <li><a href="?table=AuxFig%2011a%20Acc:%20Onshell%20SR$_{low-m_{ll}-0j}^{Wh}$">AuxFig 11a Acc: Onshell SR$_{low-m_{ll}-0j}^{Wh}$</a> <li><a href="?table=AuxFig%2011b%20Eff:%20Onshell%20SR$_{low-m_{ll}-0j}^{Wh}$">AuxFig 11b Eff: Onshell SR$_{low-m_{ll}-0j}^{Wh}$</a> <li><a href="?table=AuxFig%2011c%20Acc:%20Onshell%20SR$_{low-m_{ll}-nj}^{Wh}$">AuxFig 11c Acc: Onshell SR$_{low-m_{ll}-nj}^{Wh}$</a> <li><a href="?table=AuxFig%2011d%20Eff:%20Onshell%20SR$_{low-m_{ll}-nj}^{Wh}$">AuxFig 11d Eff: Onshell SR$_{low-m_{ll}-nj}^{Wh}$</a> <li><a href="?table=AuxFig%2011e%20Acc:%20Onshell%20SR$_{DFOS}^{Wh}$">AuxFig 11e Acc: Onshell SR$_{DFOS}^{Wh}$</a> <li><a href="?table=AuxFig%2011f%20Eff:%20Onshell%20SR$_{DFOS}^{Wh}$">AuxFig 11f Eff: Onshell SR$_{DFOS}^{Wh}$</a> <li><a href="?table=AuxFig%2012a%20Acc:%20Off.%20Wino-bino(%2b)%20SR$^{offWZ}_{lowETmiss}$-0j">AuxFig 12a Acc: Off. Wino-bino(+) SR$^{offWZ}_{lowETmiss}$-0j</a> <li><a href="?table=AuxFig%2012b%20Eff:%20Off.%20Wino-bino(%2b)%20SR$^{offWZ}_{lowETmiss}$-0j">AuxFig 12b Eff: Off. Wino-bino(+) SR$^{offWZ}_{lowETmiss}$-0j</a> <li><a href="?table=AuxFig%2012c%20Acc:%20Off.%20Wino-bino(%2b)%20SR$^{offWZ}_{lowETmiss}$-nj">AuxFig 12c Acc: Off. Wino-bino(+) SR$^{offWZ}_{lowETmiss}$-nj</a> <li><a href="?table=AuxFig%2012d%20Eff:%20Off.%20Wino-bino(%2b)%20SR$^{offWZ}_{lowETmiss}$-nj">AuxFig 12d Eff: Off. Wino-bino(+) SR$^{offWZ}_{lowETmiss}$-nj</a> <li><a href="?table=AuxFig%2012e%20Acc:%20Off.%20Wino-bino(%2b)%20SR$^{offWZ}_{highETmiss}$-0j">AuxFig 12e Acc: Off. Wino-bino(+) SR$^{offWZ}_{highETmiss}$-0j</a> <li><a href="?table=AuxFig%2012f%20Eff:%20Off.%20Wino-bino(%2b)%20SR$^{offWZ}_{highETmiss}$-0j">AuxFig 12f Eff: Off. Wino-bino(+) SR$^{offWZ}_{highETmiss}$-0j</a> <li><a href="?table=AuxFig%2012g%20Acc:%20Off.%20Wino-bino(%2b)%20SR$^{offWZ}_{highETmiss}$-nj">AuxFig 12g Acc: Off. Wino-bino(+) SR$^{offWZ}_{highETmiss}$-nj</a> <li><a href="?table=AuxFig%2012h%20Eff:%20Off.%20Wino-bino(%2b)%20SR$^{offWZ}_{highETmiss}$-nj">AuxFig 12h Eff: Off. Wino-bino(+) SR$^{offWZ}_{highETmiss}$-nj</a> <li><a href="?table=AuxFig%2013a%20Acc:%20Off.%20Wino-bino(-)%20SR$^{offWZ}_{lowETmiss}$-0j">AuxFig 13a Acc: Off. Wino-bino(-) SR$^{offWZ}_{lowETmiss}$-0j</a> <li><a href="?table=AuxFig%2013b%20Eff:%20Off.%20Wino-bino(-)%20SR$^{offWZ}_{lowETmiss}$-0j">AuxFig 13b Eff: Off. Wino-bino(-) SR$^{offWZ}_{lowETmiss}$-0j</a> <li><a href="?table=AuxFig%2013c%20Acc:%20Off.%20Wino-bino(-)%20SR$^{offWZ}_{lowETmiss}$-nj">AuxFig 13c Acc: Off. Wino-bino(-) SR$^{offWZ}_{lowETmiss}$-nj</a> <li><a href="?table=AuxFig%2013d%20Eff:%20Off.%20Wino-bino(-)%20SR$^{offWZ}_{lowETmiss}$-nj">AuxFig 13d Eff: Off. Wino-bino(-) SR$^{offWZ}_{lowETmiss}$-nj</a> <li><a href="?table=AuxFig%2013e%20Acc:%20Off.%20Wino-bino(-)%20SR$^{offWZ}_{highETmiss}$-0j">AuxFig 13e Acc: Off. Wino-bino(-) SR$^{offWZ}_{highETmiss}$-0j</a> <li><a href="?table=AuxFig%2013f%20Eff:%20Off.%20Wino-bino(-)%20SR$^{offWZ}_{highETmiss}$-0j">AuxFig 13f Eff: Off. Wino-bino(-) SR$^{offWZ}_{highETmiss}$-0j</a> <li><a href="?table=AuxFig%2013g%20Acc:%20Off.%20Wino-bino(-)%20SR$^{offWZ}_{highETmiss}$-nj">AuxFig 13g Acc: Off. Wino-bino(-) SR$^{offWZ}_{highETmiss}$-nj</a> <li><a href="?table=AuxFig%2013h%20Eff:%20Off.%20Wino-bino(-)%20SR$^{offWZ}_{highETmiss}$-nj">AuxFig 13h Eff: Off. Wino-bino(-) SR$^{offWZ}_{highETmiss}$-nj</a> <li><a href="?table=AuxFig%2014a%20Acc:%20Off.%20Higgsino%20SR$^{offWZ}_{lowETmiss}$-0j">AuxFig 14a Acc: Off. Higgsino SR$^{offWZ}_{lowETmiss}$-0j</a> <li><a href="?table=AuxFig%2014b%20Eff:%20Off.%20Higgsino%20SR$^{offWZ}_{lowETmiss}$-0j">AuxFig 14b Eff: Off. Higgsino SR$^{offWZ}_{lowETmiss}$-0j</a> <li><a href="?table=AuxFig%2014c%20Acc:%20Off.%20Higgsino%20SR$^{offWZ}_{lowETmiss}$-nj">AuxFig 14c Acc: Off. Higgsino SR$^{offWZ}_{lowETmiss}$-nj</a> <li><a href="?table=AuxFig%2014d%20Eff:%20Off.%20Higgsino%20SR$^{offWZ}_{lowETmiss}$-nj">AuxFig 14d Eff: Off. Higgsino SR$^{offWZ}_{lowETmiss}$-nj</a> <li><a href="?table=AuxFig%2014e%20Acc:%20Off.%20Higgsino%20SR$^{offWZ}_{highETmiss}$-0j">AuxFig 14e Acc: Off. Higgsino SR$^{offWZ}_{highETmiss}$-0j</a> <li><a href="?table=AuxFig%2014f%20Eff:%20Off.%20Higgsino%20SR$^{offWZ}_{highETmiss}$-0j">AuxFig 14f Eff: Off. Higgsino SR$^{offWZ}_{highETmiss}$-0j</a> <li><a href="?table=AuxFig%2014g%20Acc:%20Off.%20Higgsino%20SR$^{offWZ}_{highETmiss}$-nj">AuxFig 14g Acc: Off. Higgsino SR$^{offWZ}_{highETmiss}$-nj</a> <li><a href="?table=AuxFig%2014h%20Eff:%20Off.%20Higgsino%20SR$^{offWZ}_{highETmiss}$-nj">AuxFig 14h Eff: Off. Higgsino SR$^{offWZ}_{highETmiss}$-nj</a> </ul>
Comparison of the observed data and expected SM background yields in the CRs (pre-fit) and VRs (post-fit) of the onshell $W\!Z$ and $W\!h$ selections. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. The hatched band indicates the combined theoretical, experimental, and MC statistical uncertainties. The bottom panel shows the relative difference between the observed data and expected yields for the CRs and the significance of the difference for the VRs, calculated with the profile likelihood method from [169], adding a minus sign if the yield is below the prediction.
Comparison of the observed data and expected SM background yields in the CRs and VRs of the offshell $W\!Z$ selection. The SM prediction is taken from the background-only fit. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. The hatched band indicates the combined theoretical, experimental, and MC statistical uncertainties. The bottom panel shows the significance of the difference between the observed and expected yields, calculated with the profile likelihood method from [169], adding a minus sign if the yield is below the prediction.
Observed and expected yields after the background-only fit in the SRs for the onshell $W\!Z$ selection. The normalization factors of the $W\!Z$ sample are extracted separately for the 0j, low-H<sub>T</sub> and high-H<sub>T</sub> regions, and are treated separately in the combined fit. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. Combined statistical and systematic uncertainties are presented.
Observed and expected yields after the background-only fit in the SRs for the $W\!h$ selection. The normalization factors of the $W\!Z$ sample are extracted separately for the 0j, low-H<sub>T</sub> and high-H<sub>T</sub> regions, and are treated separately in the combined fit. The "Others" category contains the single-top, WW, tt̄+X and rare top processes. Combined statistical and systematic uncertainties are presented.
Comparison of the observed data and expected SM background yields in the SRs of the onshell $W\!Z$ selection. The SM prediction is taken from the background-only fit. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. The hatched band indicates the combined theoretical, experimental, and MC statistical uncertainties. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the significance of the difference between the observed and expected yields, calculated with the profile likelihood method from [169], adding a minus sign if the yield is below the prediction.
Comparison of the observed data and expected SM background yields in the SRs of the $W\!h$ selection. The SM prediction is taken from the background-only fit. The "Others" category contains the single-top, WW, tt̄+X and rare top processes. The hatched band indicates the combined theoretical, experimental, and MC statistical uncertainties. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!h$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the significance of the difference between the observed and expected yields, calculated with the profile likelihood method from [169], adding a minus sign if the yield is below the prediction.
Observed and expected yields after the background-only fit in SR<sup>offWZ</sup><sub>lowETmiss</sub>. The normalization factors of the $W\!Z$ sample extracted separately for 0j and nj, and are treated separately in the combined fit. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. Combined statistical and systematic uncertainties are presented.
Observed and expected yields after the background-only fit in SR<sup>offWZ</sup><sub>highETmiss</sub>. The normalization factors of the $W\!Z$ sample extracted separately for 0j and nj, and are treated separately in the combined fit. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. Combined statistical and systematic uncertainties are presented.
Comparison of the observed data and expected SM background yields in the SRs of the offshell $W\!Z$ selection. The SM prediction is taken from the background-only fit. The "Others" category contains the single-top, WW, triboson, Higgs and rare top processes. The hatched band indicates the combined theoretical, experimental, and MC statistical uncertainties. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W^{*}\!Z^{*}$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the significance of the difference between the observed and expected yields, calculated with the profile likelihood method from [169], adding a minus sign if the yield is below the prediction.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the onshell $W\!Z$ and $W\!h$ selections. The figure shows (a) the ΔR<sub>OS,near</sub> distribution in SR<sup>Wh</sup><sub>DF</sub>-1, (b) the 3rd leading lepton p<sub>T</sub> in SR<sup>Wh</sup><sub>DF</sub>-2, and the (c) E<sub>T</sub><sup>miss</sup> and (d) m<sub>T</sub> distributions in SR<sup>WZ</sup><sub>0j</sub> (with all SR-i bins of SR<sup>WZ</sup><sub>0j</sub> summed up). The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes, except in the top panels, where triboson and Higgs production contributions are shown separately, and tt̄+X is merged into Others. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$/$W\!h$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the onshell $W\!Z$ and $W\!h$ selections. The figure shows (a) the ΔR<sub>OS,near</sub> distribution in SR<sup>Wh</sup><sub>DF</sub>-1, (b) the 3rd leading lepton p<sub>T</sub> in SR<sup>Wh</sup><sub>DF</sub>-2, and the (c) E<sub>T</sub><sup>miss</sup> and (d) m<sub>T</sub> distributions in SR<sup>WZ</sup><sub>0j</sub> (with all SR-i bins of SR<sup>WZ</sup><sub>0j</sub> summed up). The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes, except in the top panels, where triboson and Higgs production contributions are shown separately, and tt̄+X is merged into Others. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$/$W\!h$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the onshell $W\!Z$ and $W\!h$ selections. The figure shows (a) the ΔR<sub>OS,near</sub> distribution in SR<sup>Wh</sup><sub>DF</sub>-1, (b) the 3rd leading lepton p<sub>T</sub> in SR<sup>Wh</sup><sub>DF</sub>-2, and the (c) E<sub>T</sub><sup>miss</sup> and (d) m<sub>T</sub> distributions in SR<sup>WZ</sup><sub>0j</sub> (with all SR-i bins of SR<sup>WZ</sup><sub>0j</sub> summed up). The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes, except in the top panels, where triboson and Higgs production contributions are shown separately, and tt̄+X is merged into Others. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$/$W\!h$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the onshell $W\!Z$ and $W\!h$ selections. The figure shows (a) the ΔR<sub>OS,near</sub> distribution in SR<sup>Wh</sup><sub>DF</sub>-1, (b) the 3rd leading lepton p<sub>T</sub> in SR<sup>Wh</sup><sub>DF</sub>-2, and the (c) E<sub>T</sub><sup>miss</sup> and (d) m<sub>T</sub> distributions in SR<sup>WZ</sup><sub>0j</sub> (with all SR-i bins of SR<sup>WZ</sup><sub>0j</sub> summed up). The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes, except in the top panels, where triboson and Higgs production contributions are shown separately, and tt̄+X is merged into Others. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$/$W\!h$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the offshell $W\!Z$ selection. The figure shows the m<sub>T</sub><sup>m<sub>ll</sub>min</sup> distribution in (a) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj and (c) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and the |p<sub>T</sub><sup>lep</sup>|/E<sub>T</sub><sup>miss</sup> distribution in (d) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj. The contributing m<sub>ll</sub><sup>min</sup> mass bins within each SR<sup>offWZ</sup> category are summed together. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the offshell $W\!Z$ selection. The figure shows the m<sub>T</sub><sup>m<sub>ll</sub>min</sup> distribution in (a) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj and (c) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and the |p<sub>T</sub><sup>lep</sup>|/E<sub>T</sub><sup>miss</sup> distribution in (d) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj. The contributing m<sub>ll</sub><sup>min</sup> mass bins within each SR<sup>offWZ</sup> category are summed together. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the offshell $W\!Z$ selection. The figure shows the m<sub>T</sub><sup>m<sub>ll</sub>min</sup> distribution in (a) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj and (c) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and the |p<sub>T</sub><sup>lep</sup>|/E<sub>T</sub><sup>miss</sup> distribution in (d) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj. The contributing m<sub>ll</sub><sup>min</sup> mass bins within each SR<sup>offWZ</sup> category are summed together. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Kinematic distributions after the background-only fit showing the data and the post-fit expected background, in SRs of the offshell $W\!Z$ selection. The figure shows the m<sub>T</sub><sup>m<sub>ll</sub>min</sup> distribution in (a) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj and (c) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and the |p<sub>T</sub><sup>lep</sup>|/E<sub>T</sub><sup>miss</sup> distribution in (d) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj. The contributing m<sub>ll</sub><sup>min</sup> mass bins within each SR<sup>offWZ</sup> category are summed together. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by an arrow. The last bin includes overflow. The "Others" category contains backgrounds from single-top, WW, triboson, Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Observed (N<sub>obs</sub>) yields after the discovery-fit and expected (N<sub>exp</sub>) after the background-only fit, for the inclusive SRs of the onshell $W\!Z$ and $W\!h$ selections. The third and fourth column list the 95 CL upper limits on the visible cross-section (σ<sub>vis</sub><sup>95</sup>) and on the number of signal events (S<sub>obs</sub><sup>95</sup>). The fifth column (S<sub>exp</sub><sup>95</sup>) shows the 95 CL upper limit on the number of signal events, given the expected number (and ± 1σ excursions on the expectation) of background events. The last two columns indicate the CLb value, i.e. the confidence level observed for the background-only hypothesis, and the discovery p-value (p(s = 0)). If the observed yield is below the expected yield, the p-value is capped at 0.5.
Observed (N<sub>obs</sub>) yields after the discovery-fit and expected (N<sub>exp</sub>) after the background-only fit, for the inclusive SRs of the offshell $W\!Z$ selection. The third and fourth column list the 95 CL upper limits on the visible cross section (σ<sub>vis</sub><sup>95</sup>) and on the number of signal events (S<sub>obs</sub><sup>95</sup>). The fifth column (S<sub>exp</sub><sup>95</sup>) shows the 95 CL upper limit on the number of signal events, given the expected number (and ± 1σ excursions on the expectation) of background events. The last two columns indicate the CLb value, i.e. the confidence level observed for the background-only hypothesis, and the discovery p-value (p(s = 0)). If the observed yield is below the expected yield, the p-value is capped at 0.5.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!Z$-mediated models in the (a,b) wino/bino (+) scenario, (c) the wino/bino (-) scenario, and (d) the higgsino scenario. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>exp</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties. The statistical combination of the onshell $W\!Z$, offshell $W\!Z$, and compressed results is shown as the main contour, while the observed (expected) limits for each individual selection are overlaid in green, blue, and orange solid (dashed) lines, respectively. The exclusion is shown projected (a) onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane or (b,c,d) onto the m(χ̃<sub>2</sub><sup>0</sup>) vs Δm plane. The light grey area denotes (top) the constraints obtained by the previous equivalent analysis in ATLAS using the 8 TeV 20.3 fb<sup>-1</sup> dataset [17], and (d) the LEP lower χ̃<sub>1</sub><sup>±</sup> mass limit [56]. The pale blue line in the top right panel represents the mass splitting range that yields a dark matter relic density equal to the observed relic density, Ω h<sup>2</sup>=0.1186±0.0020 [172], when the mass parameters of all the decoupled SUSY partners are set to 5 TeV and tanβ is chosen such that the SM-like Higgs boson mass is consistent with the observed value [43]. The area above (below) the blue line represents a dark-matter relic density larger (smaller) than the observed.
Exclusion limits obtained for the $W\!h$med in the wino/bino (+) scenario, calculated using the $W\!h$ SRs and projected onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>{exp}</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties.
Exclusion limits obtained for the $W\!h$med in the wino/bino (+) scenario, calculated using the $W\!h$ SRs and projected onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>{exp}</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties.
Exclusion limits obtained for the $W\!h$med in the wino/bino (+) scenario, calculated using the $W\!h$ SRs and projected onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>{exp}</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties.
Exclusion limits obtained for the $W\!h$med in the wino/bino (+) scenario, calculated using the $W\!h$ SRs and projected onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>{exp}</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties.
Exclusion limits obtained for the $W\!h$med in the wino/bino (+) scenario, calculated using the $W\!h$ SRs and projected onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>{exp}</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties.
Exclusion limits obtained for the $W\!h$med in the wino/bino (+) scenario, calculated using the $W\!h$ SRs and projected onto the m(χ̃<sub>1</sub><sup>±</sup>, χ̃<sub>2</sub><sup>0</sup>) vs m(χ̃<sub>1</sub><sup>0</sup>) plane. The expected 95 CL sensitivity (dashed black line) is shown with ±1σ<sub>{exp}</sub> (yellow band) from experimental systematic uncertainties and statistical uncertainties on the data yields, the observed limit (red solid line) is shown with ±1σ<sub>theory</sub> (dotted red lines) from signal cross-section uncertainties.
Comparison of the observed data and expected SM background yields in the CRs and VRs of the RJR selection. The SM prediction is taken from the background-only fit. The "FNP leptons" category contains backgrounds from tt̄, tW, WW and Z+jets processes. The "Others" category contains backgrounds from Higgs and rare top processes. The hatched band indicates the combined theoretical, experimental, and MC statistical uncertainties. The bottom panel shows the significance of the difference between the observed and expected yields, calculated with the profile likelihood method from [169], adding a minus sign if the yield is below the prediction.
Observed and expected yields after the background-only fit in the SRs for the RJR selection. The "FNP leptons" category contains backgrounds from tt̄, tW, WW and Z+jets processes. The "Others" category contains backgrounds from Higgs and rare top processes. Combined statistical and systematic uncertainties are presented.
Example of kinematic distributions after the background-only fit, showing the data and the post-fit expected background, in regions of the RJR selection. The figure shows the (a) p<sub>T</sub><sup>ℓ<sub>1</sub></sup> and (b) H<sup>PP</sup><sub>3,1</sub> distributions in SR3ℓ-Low, and the (c) p<sup>CM</sup><sub>T ISR</sub> and (d) R<sub>ISR</sub> distributions in SR3ℓ-ISR. The last bin includes overflow. The "FNP leptons" category contains backgrounds from tt̄, tW, WW and Z+jets processes. The "Others" category contains backgrounds from Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Example of kinematic distributions after the background-only fit, showing the data and the post-fit expected background, in regions of the RJR selection. The figure shows the (a) p<sub>T</sub><sup>ℓ<sub>1</sub></sup> and (b) H<sup>PP</sup><sub>3,1</sub> distributions in SR3ℓ-Low, and the (c) p<sup>CM</sup><sub>T ISR</sub> and (d) R<sub>ISR</sub> distributions in SR3ℓ-ISR. The last bin includes overflow. The "FNP leptons" category contains backgrounds from tt̄, tW, WW and Z+jets processes. The "Others" category contains backgrounds from Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Example of kinematic distributions after the background-only fit, showing the data and the post-fit expected background, in regions of the RJR selection. The figure shows the (a) p<sub>T</sub><sup>ℓ<sub>1</sub></sup> and (b) H<sup>PP</sup><sub>3,1</sub> distributions in SR3ℓ-Low, and the (c) p<sup>CM</sup><sub>T ISR</sub> and (d) R<sub>ISR</sub> distributions in SR3ℓ-ISR. The last bin includes overflow. The "FNP leptons" category contains backgrounds from tt̄, tW, WW and Z+jets processes. The "Others" category contains backgrounds from Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
Example of kinematic distributions after the background-only fit, showing the data and the post-fit expected background, in regions of the RJR selection. The figure shows the (a) p<sub>T</sub><sup>ℓ<sub>1</sub></sup> and (b) H<sup>PP</sup><sub>3,1</sub> distributions in SR3ℓ-Low, and the (c) p<sup>CM</sup><sub>T ISR</sub> and (d) R<sub>ISR</sub> distributions in SR3ℓ-ISR. The last bin includes overflow. The "FNP leptons" category contains backgrounds from tt̄, tW, WW and Z+jets processes. The "Others" category contains backgrounds from Higgs and rare top processes. Distributions for wino/bino (+) χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> → $W\!Z$ signals are overlaid, with mass values given as (m(χ̃<sub>1</sub><sup>±</sup>),m(χ̃<sub>1</sub><sup>0</sup>)) GeV. The bottom panel shows the ratio of the observed data to the predicted yields. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.
{Results of the discovery-fit for the SRs of the RJR selection, calculated using pseudo-experiments.} The first and second column list the 95 CL upper limits on the visible cross section (σ<sub>vis</sub><sup>95</sup>) and on the number of signal events (S<sub>obs</sub><sup>95</sup>). The third column (S<sub>exp</sub><sup>95</sup>) shows the 95 CL upper limit on the number of signal events, given the expected number (and ± 1σ excursions on the expectation) of background events. The last two columns indicate the CLb value, i.e. the confidence level observed for the background-only hypothesis, and the discovery p-value (p(s = 0)). If the observed yield is below the expected yield, the p-value is capped at 0.5. vspace{0.5em}
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!Z$-mediated model, for the (1st and 2nd row) wino/bino (+) scenario, (3rd row) the wino/bino (-) scenario, and (4th row) the higgsino scenario, as in Figure 16. Black numbers represent the observed (a) and expected (b) upper cross-section limits.
Exclusion limits obtained for the $W\!h$-mediated model, for the wino/bino (+) scenario, as in Figure 17. The black numbers represent the observed (a,c,e,g) and expected (b,d,f,h) upper cross-section limits.
Exclusion limits obtained for the $W\!h$-mediated model, for the wino/bino (+) scenario, as in Figure 17. The black numbers represent the observed (a,c,e,g) and expected (b,d,f,h) upper cross-section limits.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c) truth-level acceptances and (b,d) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>WZ</sup><sub>0j</sub>, (c,d) SR<sup>WZ</sup><sub>nj</sub> regions of the onshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c) truth-level acceptances and (b,d) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>WZ</sup><sub>0j</sub>, (c,d) SR<sup>WZ</sup><sub>nj</sub> regions of the onshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c) truth-level acceptances and (b,d) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>WZ</sup><sub>0j</sub>, (c,d) SR<sup>WZ</sup><sub>nj</sub> regions of the onshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c) truth-level acceptances and (b,d) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>WZ</sup><sub>0j</sub>, (c,d) SR<sup>WZ</sup><sub>nj</sub> regions of the onshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e) truth-level acceptances and (b,d,f) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-0j</sub>, (c,d) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-nj</sub>, and (e,f) SR<sup>Wh</sup><sub>DF</sub> regions of the $W\!h$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e) truth-level acceptances and (b,d,f) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-0j</sub>, (c,d) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-nj</sub>, and (e,f) SR<sup>Wh</sup><sub>DF</sub> regions of the $W\!h$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e) truth-level acceptances and (b,d,f) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-0j</sub>, (c,d) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-nj</sub>, and (e,f) SR<sup>Wh</sup><sub>DF</sub> regions of the $W\!h$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e) truth-level acceptances and (b,d,f) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-0j</sub>, (c,d) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-nj</sub>, and (e,f) SR<sup>Wh</sup><sub>DF</sub> regions of the $W\!h$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e) truth-level acceptances and (b,d,f) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-0j</sub>, (c,d) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-nj</sub>, and (e,f) SR<sup>Wh</sup><sub>DF</sub> regions of the $W\!h$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e) truth-level acceptances and (b,d,f) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-0j</sub>, (c,d) SR<sup>Wh</sup><sub>low-m<sub>ll</sub>-nj</sub>, and (e,f) SR<sup>Wh</sup><sub>DF</sub> regions of the $W\!h$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (+) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the wino/bino (-) scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
The χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> (a,c,e,g) truth-level acceptances and (b,d,f,h) reconstruction efficiencies for the higgsino scenario, in the inclusive (a,b) SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, (c,d) SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, (e,f) SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and (g,h) SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions of the offshell $W\!Z$ selection, after MC-to-data efficiency weights are applied.
Summary of onshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (300,200) GeV and m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (600,100) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal points, for the wino/bino (+) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks per inclusive regions, and then further for each SR. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5.
Summary of $W\!h$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (190,60) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (+) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks per inclusive regions, and then further for each SR. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (250,235) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (+) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (125,85) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (+) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (250,170) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (+) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (250,235) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (-) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (125,85) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (-) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (250,170) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the wino/bino (-) interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (120,100) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the higgsino interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (100,40) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the higgsino interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
Summary of offshell $W\!Z$ event selections for the m(χ̃<sub>2</sub><sup>0</sup>,χ̃<sub>1</sub><sup>0</sup>) = (185,125) GeV χ̃<sub>1</sub><sup>±</sup>/χ̃<sub>2</sub><sup>0</sup> signal point, for the higgsino interpretation. The yields are normalised to a luminosity of 139 fb<sup>-1</sup>, and MC-to-data efficiency weights from triggering and from the reconstruction and identification of individual physics objects are applied to the final yields in each signal region. After the initial selections, the table is split in row blocks for the inclusive SR<sup>offWZ</sup><sub>lowETmiss</sub>-0j, SR<sup>offWZ</sup><sub>lowETmiss</sub>-nj, SR<sup>offWZ</sup><sub>highETmiss</sub>-0j, and SR<sup>offWZ</sup><sub>highETmiss</sub>-nj regions, with the individual SR results in columns. The inclusive OR of regions a through g2 is given in the last column. Selection details per bin are indicated in bracketed blue as relevant, and the final yield for each SR is highlighted in bold green at the end of each block. The generator filters are discussed in detail in Section 4. The "3 isolated lepton selection" includes the common event selection as discussed in Section 5 and the initial SFOS lepton pair selection.
A search is presented for long-lived particles produced in pairs in proton-proton collisions at the LHC operating at a center-of-mass energy of 13 TeV. The data were collected with the CMS detector during the period from 2015 through 2018, and correspond to a total integrated luminosity of 140 fb$^{-1}$. This search targets pairs of long-lived particles with mean proper decay lengths between 0.1 and 100 mm, each of which decays into at least two quarks that hadronize to jets, resulting in a final state with two displaced vertices. No significant excess of events with two displaced vertices is observed. In the context of $R$-parity violating supersymmetry models, the pair production of long-lived neutralinos, gluinos, and top squarks is excluded at 95% confidence level for cross sections larger than 0.08 fb, masses between 800 and 3000 GeV, and mean proper decay lengths between 1 and 25 mm.
Event yields in the control samples in data. The ''one-vertex'' events correspond to events containing exactly one vertex with the specified number of tracks. The ''two-vertex'' events have two or more vertices containing the specified numbers of tracks. We seek the signal in the $\geq$5-track two-vertex sample.
The distribution of distances between vertices in the $x$-$y$ plane, $d_{\mathrm{VV}}$, for three simulated multijet signals each with a mass of 1600 GeV, with the background template distribution overlaid. The production cross section for each signal model is assumed to be the lower limit excluded by CMS-EXO-17-018, corresponding to values of 0.8, 0.25, and 0.15 fb for the samples with $c\tau =$ 0.3, 1.0, and 10 mm, respectively. The last bin includes the overflow events. The two vertical pink dashed lines separate the regions used in the fit.
Multijet signal efficiencies as a function of the signal mass and lifetime for events satisfying all event and vertex requirements, with corrections based on systematic differences in the vertex reconstruction efficiency between data and simulation.
Dijet signal efficiencies as a function of the signal mass and lifetime for events satisfying all event and vertex requirements, with corrections based on systematic differences in the vertex reconstruction efficiency between data and simulation.
The distribution of $d_{\mathrm{BV}}$ for $\geq$5-track one-vertex events in data and three simulated multijet signal samples each with a mass of 1600 GeV. The production cross section for each signal model is assumed to be the lower limit excluded by CMS-EXO-17-018, corresponding to values of 0.8, 0.25, and 0.15 fb for the samples with $c\tau =$ 0.3, 1.0, and 10 mm, respectively. The last bin includes the overflow events. This bin includes one event in data with a vertex with large $d_{\mathrm{BV}}$ that appears to arise from tracks originating from separate pp interaction vertices, consistent with background.
Distribution of the $x$-$y$ distances between vertices, $d_{\mathrm{VV}}$, for 2017 and 2018 data. The background distribution $d_{\mathrm{VV}}^{\kern 0.15em\mathrm{C}}$ (blue continuous line) is constructed from one-vertex events in data, and is normalized to the number of two-vertex events in data with two 3-track vertices. The two vertical red dashed lines separate the regions used in the fit.
Distribution of the $x$-$y$ distances between vertices, $d_{\mathrm{VV}}$, for 2017 and 2018 data. The background distribution $d_{\mathrm{VV}}^{\kern 0.15em\mathrm{C}}$ (blue continuous line) is constructed from one-vertex events in data, and is normalized to the number of two-vertex events in data which have exactly one 4-track vertex and one 3-track vertex. The two vertical red dashed lines separate the regions used in the fit.
Distribution of the $x$-$y$ distances between vertices, $d_{\mathrm{VV}}$, for 2017 and 2018 data. The background distribution $d_{\mathrm{VV}}^{\kern 0.15em\mathrm{C}}$ (blue continuous line) is constructed from one-vertex events in data, and is normalized to the number of two-vertex events in data with two 4-track vertices. The two vertical red dashed lines separate the regions used in the fit.
Distribution of the $x$-$y$ distances between vertices, $d_{\mathrm{VV}}$, for 2017 and 2018 data. The background distribution $d_{\mathrm{VV}}^{\kern 0.15em\mathrm{C}}$ (blue continuous line) is constructed from one-vertex events in data, and is normalized using $\geq$5-track one-vertex event information. The two vertical red dashed lines separate the regions used in the fit.
Predicted yields for the background-only normalized template, predicted yields for three simulated multijet signals each with a mass of 1600 GeV, and the observed yield in each $d_{\mathrm{VV}}$ bin. The production cross section for each signal model is assumed to be the lower limit excluded by CMS-EXO-17-018, corresponding to values of 0.8, 0.25, and 0.15 fb for samples with $c\tau =$ 0.3, 1.0, and 10 mm, respectively. The uncertainties in the signal yields and the systematic uncertainties in the background prediction reflect the systematic uncertainties given in the text.
Observed 95% CL upper limits on the product of cross section and branching fraction squared for the multijet signals, as a function of mass and $c\tau$. The overlaid mass-lifetime exclusion curves assume pair-production cross sections for the neutralino (red) and gluino (purple) with 100% branching fraction to each model's respective decay mode specified. The solid black (dashed colored) lines represent the observed (median expected) limits at 95% CL. The thin black lines represent the variation of the observed limit within theoretical uncertainties of the signal cross section. The thin dashed colored lines represent the region containing 68% of the expected limit distribution under the background-only hypothesis. The observed limits from the CMS displaced jets search (CMS-EXO-19-021) are also shown in teal for comparison.
Observed 95% CL upper limits on the product of cross section and branching fraction squared for the multijet signals, as a function of mass and $c\tau$. The overlaid mass-lifetime exclusion curves assume pair-production cross sections for the neutralino (red) and gluino (purple) with 100% branching fraction to each model's respective decay mode specified. The solid black (dashed colored) lines represent the observed (median expected) limits at 95% CL. The thin black lines represent the variation of the observed limit within theoretical uncertainties of the signal cross section. The thin dashed colored lines represent the region containing 68% of the expected limit distribution under the background-only hypothesis. The observed limits from the CMS displaced jets search (CMS-EXO-19-021) are also shown in teal for comparison.
Observed 95% CL upper limits on the product of cross section and branching fraction squared for the multijet signals, as a function of mass and $c\tau$. The overlaid mass-lifetime exclusion curves assume pair-production cross sections for the neutralino (red) and gluino (purple) with 100% branching fraction to each model's respective decay mode specified. The solid black (dashed colored) lines represent the observed (median expected) limits at 95% CL. The thin black lines represent the variation of the observed limit within theoretical uncertainties of the signal cross section. The thin dashed colored lines represent the region containing 68% of the expected limit distribution under the background-only hypothesis. The observed limits from the CMS displaced jets search (CMS-EXO-19-021) are also shown in teal for comparison.
Observed 95% CL upper limits on the product of cross section and branching fraction squared for the dijet signals, as a function of mass and $c\tau$. The overlaid mass-lifetime exclusion curves assume pair-production cross sections for the top squark with 100% branching fraction to each model's respective decay mode specified. The solid black (dashed colored) lines represent the observed (median expected) limits at 95% CL. The thin black lines represent the variation of the observed limit within theoretical uncertainties of the signal cross section. The thin dashed colored lines represent the region containing 68% of the expected limit distribution under the background-only hypothesis. The observed limits from the CMS displaced jets search (CMS-EXO-19-021) are also shown in teal for comparison.
Observed 95% CL upper limits on the product of cross section and branching fraction squared for the dijet signals, as a function of mass and $c\tau$. The overlaid mass-lifetime exclusion curves assume pair-production cross sections for the top squark with 100% branching fraction to each model's respective decay mode specified. The solid black (dashed colored) lines represent the observed (median expected) limits at 95% CL. The thin black lines represent the variation of the observed limit within theoretical uncertainties of the signal cross section. The thin dashed colored lines represent the region containing 68% of the expected limit distribution under the background-only hypothesis. The observed limits from the CMS displaced jets search (CMS-EXO-19-021) are also shown in teal for comparison.
Observed and expected 95% CL upper limits on the product of cross section and branching fraction squared, as a function of mass for multijet signals, for a fixed $c\tau$ of 300um in the full Run-2 data set. The neutralino and gluino pair production cross sections are shown for the multijet signals.
Observed and expected 95% CL upper limits on the product of cross section and branching fraction squared, as a function of mass for dijet signals, for a fixed $c\tau$ of 300um in the full Run-2 data set. The top squark pair-production cross section is shown for the dijet signals.
Observed and expected 95% CL upper limits on the product of cross section and branching fraction squared, as a function of mass for multijet signals, for a fixed $c\tau$ of 1 mm in the full Run-2 data set. The neutralino and gluino pair production cross sections are shown for the multijet signals.
Observed and expected 95% CL upper limits on the product of cross section and branching fraction squared, as a function of mass for dijet signals, for a fixed $c\tau$ of 1 mm in the full Run-2 data set. The top squark pair-production cross section is shown for the dijet signals.
Observed and expected 95% CL upper limits on the product of cross section and branching fraction squared, as a function of mass for multijet signals, for a fixed $c\tau$ of 10 mm in the full Run-2 data set. The neutralino and gluino pair production cross sections are shown for the multijet signals.
Observed and expected 95% CL upper limits on the product of cross section and branching fraction squared, as a function of mass for dijet signals, for a fixed $c\tau$ of 10 mm in the full Run-2 data set. The top squark pair-production cross section is shown for the dijet signals.
Observed and expected 95% CL upper limits on the product of cross section and branching fraction squared, as a function of $c\tau$ for multijet signals, for a fixed mass of 800 GeV in the full Run-2 data set. The neutralino and gluino pair production cross sections are shown for the multijet signals.
Observed and expected 95% CL upper limits on the product of cross section and branching fraction squared, as a function of $c\tau$ for dijet signals, for a fixed mass of 800 GeV in the full Run-2 data set. The top squark pair-production cross section is shown for the dijet signals.
Observed and expected 95% CL upper limits on the product of cross section and branching fraction squared, as a function of $c\tau$ for multijet signals, for a fixed mass of 1600 GeV in the full Run-2 data set. The neutralino and gluino pair production cross sections are shown for the multijet signals.
Observed and expected 95% CL upper limits on the product of cross section and branching fraction squared, as a function of $c\tau$ for dijet signals, for a fixed mass of 1600 GeV in the full Run-2 data set. The top squark pair-production cross section is shown for the dijet signals.
Observed and expected 95% CL upper limits on the product of cross section and branching fraction squared, as a function of $c\tau$ for multijet signals, for a fixed mass of 2400 GeV in the full Run-2 data set. The neutralino and gluino pair production cross sections are shown for the multijet signals. For $m$ = 2400 GeV, the expected neutralino cross section is $\approx 8\times 10^{-5}$ fb and is not shown.
Observed and expected 95% CL upper limits on the product of cross section and branching fraction squared, as a function of $c\tau$ for dijet signals, for a fixed mass of 2400 GeV in the full Run-2 data set. The top squark pair-production cross section is shown for the dijet signals.
Data-to-simulation efficiency correction factors, shown for multijet and dijet signal topologies in several ranges of $c\tau$. Note that these correction factors account for the two long-lived particles in the simulated events, and are therefore the total correction factors used to scale event yields rather than the correction factors one would apply to individual vertices.
Distribution of the azimuthal angle between vertices, $\Delta\phi_{\mathrm{VV}}$, for 2017 and 2018 data. The background distribution (blue continuous line) is constructed from 3-track one-vertex events in data, and is normalized to the number of 3-track two-vertex events in data.
Distribution of the azimuthal angle between vertices, $\Delta\phi_{\mathrm{VV}}$, for 2017 and 2018 data. The background distribution (blue continuous line) is constructed from 4-track and 3-track one-vertex events in data, and is normalized to the number of two-vertex events in data which have exactly one 4-track vertex and one 3-track vertex.
Distribution of the azimuthal angle between vertices, $\Delta\phi_{\mathrm{VV}}$, for 2017 and 2018 data. The background distribution (blue continuous line) is constructed from 4-track one-vertex events in data, and is normalized to the number of 4-track two-vertex events in data.
Distribution of the azimuthal angle between vertices, $\Delta\phi_{\mathrm{VV}}$, for 2017 and 2018 data. The background distribution (blue continuous line) is constructed from $\geq$5-track one-vertex events in data, and is normalized using one-vertex event information. No $\geq$5-track two-vertex data events pass the selection.
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