Relative differential cross section as a function of the b-jet multiplicity in emu channel

Relative differential cross section as a function of H_T in emu channel

Relative differential cross section as a function of H_T in emu channel

Relative differential cross section as a function of H_Thad in emu channel

Relative differential cross section as a function of H_Thad in emu channel

Relative differential cross section as a function of H_T in leptons+jets channel

Relative differential cross section as a function of H_T in leptons+jets channel

Relative differential cross section as a function of H_Thad in leptons+jets channel

Relative differential cross section as a function of H_Thad in leptons+jets channel

Relative differential cross section as a function of pT of leading b-jet in emu channel

Relative differential cross section as a function of pT of leading b-jet in emu channel

Relative differential cross section as a function of pT of sub-leading b-jet in emu channel

Relative differential cross section as a function of pT of sub-leading b-jet in emu channel

Relative differential cross section as a function of pT of third-leading b-jet in emu channel

Relative differential cross section as a function of pT of third-leading b-jet in emu channel

Relative differential cross section as a function of pT of leading b-jet in lepton+jets channel

Relative differential cross section as a function of pT of leading b-jet in lepton+jets channel

Relative differential cross section as a function of pT of sub-leading b-jet in lepton+jets channel

Relative differential cross section as a function of pT of sub-leading b-jet in lepton+jets channel

Relative differential cross section as a function of pT of third-leading b-jet in lepton+jets channel

Relative differential cross section as a function of pT of third-leading b-jet in lepton+jets channel

Relative differential cross section as a function of pT of fourth-leading b-jet in lepton+jets channel

Relative differential cross section as a function of pT of fourth-leading b-jet in lepton+jets channel

Relative differential cross section as a function of invarant mass of two highest pT b-jets in emu channel

Relative differential cross section as a function of invarant mass of two highest pT b-jets in emu channel

Relative differential cross section as a function of pT of two highest pT b-jets in emu channel

Relative differential cross section as a function of pT of two highest pT b-jets in emu channel

Relative differential cross section as a function of deltaR of two highest pT b-jets in emu channel

Relative differential cross section as a function of deltaR of two highest pT b-jets in emu channel

Relative differential cross section as a function of invariant mass of two highest pT b-jets in lepton+jets channel

Relative differential cross section as a function of invariant mass of two highest pT b-jets in lepton+jets channel

Relative differential cross section as a function of pT of two highest pT b-jets in lepton+jets channel

Relative differential cross section as a function of pT of two highest pT b-jets in lepton+jets channel

Relative differential cross section as a function of deltaR of two highest pT b-jets in lepton+jets channel

Relative differential cross section as a function of deltaR of two highest pT b-jets in lepton+jets channel

Relative differential cross section as a function of invariant mass of two closest b-jets in deltaR in emu channel

Relative differential cross section as a function of invariant mass of two closest b-jets in deltaR in emu channel

Relative differential cross section as a function of pT of two closest b-jets in deltaR in emu channel

Relative differential cross section as a function of pT of two closest b-jets in deltaR in emu channel

Relative differential cross section as a function of deltaR of two closest b-jets in deltaR in emu channel

Relative differential cross section as a function of deltaR of two closest b-jets in deltaR in emu channel

Relative differential cross section as a function of invariant mass of two closest b-jets in deltaR in lepton+jets channel

Relative differential cross section as a function of invariant mass of two closest b-jets in deltaR in lepton+jets channel

Relative differential cross section as a function of pT of two closest b-jets in deltaR in lepton+jets channel

Relative differential cross section as a function of pT of two closest b-jets in deltaR in lepton+jets channel

Relative differential cross section as a function of deltaR of two closest b-jets in deltaR in lepton+jets channel

Relative differential cross section as a function of deltaR of two closest b-jets in deltaR in lepton+jets channel

Barrel Muon RoI Cluster trigger efficiencies (in %) for $m_{\Phi}=200$ GeV scalar benchmark samples. The trigger efficiency is defined as the fraction of LLPs selected by the Muon RoI Cluster trigger as a function of the LLP decay position. The trigger is efficient for hadronic decays of LLPs that occur anywhere from the outer regions of the HCal to the middle station of the MS. These efficiencies are obtained from the subset of events with only a single LLP decay in the muon spectrometer in order to ensure that the result of the trigger is due to a single burst of MS activity. The uncertainties shown are statistical only. The relative differences in efficiencies of the benchmark samples are a result of the different kinematics.

Barrel Muon RoI Cluster trigger efficiencies (in %) for $m_{\Phi}=400$ GeV scalar benchmark samples. The trigger efficiency is defined as the fraction of LLPs selected by the Muon RoI Cluster trigger as a function of the LLP decay position. The trigger is efficient for hadronic decays of LLPs that occur anywhere from the outer regions of the HCal to the middle station of the MS. These efficiencies are obtained from the subset of events with only a single LLP decay in the muon spectrometer in order to ensure that the result of the trigger is due to a single burst of MS activity. The uncertainties shown are statistical only. The relative differences in efficiencies of the benchmark samples are a result of the different kinematics.

Barrel Muon RoI Cluster trigger efficiencies (in %) for $m_{\Phi}=600$ GeV scalar benchmark samples. The trigger efficiency is defined as the fraction of LLPs selected by the Muon RoI Cluster trigger as a function of the LLP decay position. The trigger is efficient for hadronic decays of LLPs that occur anywhere from the outer regions of the HCal to the middle station of the MS. These efficiencies are obtained from the subset of events with only a single LLP decay in the muon spectrometer in order to ensure that the result of the trigger is due to a single burst of MS activity. The uncertainties shown are statistical only. The relative differences in efficiencies of the benchmark samples are a result of the different kinematics.

Barrel Muon RoI Cluster trigger efficiencies (in %) for $m_{\Phi}=1000$ GeV scalar benchmark samples. The trigger efficiency is defined as the fraction of LLPs selected by the Muon RoI Cluster trigger as a function of the LLP decay position. The trigger is efficient for hadronic decays of LLPs that occur anywhere from the outer regions of the HCal to the middle station of the MS. These efficiencies are obtained from the subset of events with only a single LLP decay in the muon spectrometer in order to ensure that the result of the trigger is due to a single burst of MS activity. The uncertainties shown are statistical only. The relative differences in efficiencies of the benchmark samples are a result of the different kinematics.

Barrel Muon RoI Cluster trigger efficiencies (in %) for all Stealth SUSY benchmark samples. The trigger efficiency is defined as the fraction of LLPs selected by the Muon RoI Cluster trigger as a function of the LLP decay position. The trigger is efficient for hadronic decays of LLPs that occur anywhere from the outer regions of the HCal to the middle station of the MS. These efficiencies are obtained from the subset of events with only a single LLP decay in the muon spectrometer in order to ensure that the result of the trigger is due to a single burst of MS activity. The uncertainties shown are statistical only. The relative differences in efficiencies of the benchmark samples are a result of the different kinematics.

Barrel Muon RoI Cluster trigger efficiencies (in %) for baryogenesis $\chi \rightarrow \nu b \bar{b}$ benchmark samples ($m_{h}=125$ GeV). The trigger efficiency is defined as the fraction of LLPs selected by the Muon RoI Cluster trigger as a function of the LLP decay position. The trigger is efficient for hadronic decays of LLPs that occur anywhere from the outer regions of the HCal to the middle station of the MS. These efficiencies are obtained from the subset of events with only a single LLP decay in the muon spectrometer in order to ensure that the result of the trigger is due to a single burst of MS activity. The uncertainties shown are statistical only. The relative differences in efficiencies of the benchmark samples are a result of the different kinematics.

Barrel Muon RoI Cluster trigger efficiencies (in %) for baryogenesis $\chi \rightarrow cbs$ benchmark samples ($m_{h}=125$ GeV). The trigger efficiency is defined as the fraction of LLPs selected by the Muon RoI Cluster trigger as a function of the LLP decay position. The trigger is efficient for hadronic decays of LLPs that occur anywhere from the outer regions of the HCal to the middle station of the MS. These efficiencies are obtained from the subset of events with only a single LLP decay in the muon spectrometer in order to ensure that the result of the trigger is due to a single burst of MS activity. The uncertainties shown are statistical only. The relative differences in efficiencies of the benchmark samples are a result of the different kinematics.

Barrel Muon RoI Cluster trigger efficiencies (in %) for baryogenesis $\chi \rightarrow lcb$ benchmark samples ($m_{h}=125$ GeV). The trigger efficiency is defined as the fraction of LLPs selected by the Muon RoI Cluster trigger as a function of the LLP decay position. The trigger is efficient for hadronic decays of LLPs that occur anywhere from the outer regions of the HCal to the middle station of the MS. These efficiencies are obtained from the subset of events with only a single LLP decay in the muon spectrometer in order to ensure that the result of the trigger is due to a single burst of MS activity. The uncertainties shown are statistical only. The relative differences in efficiencies of the benchmark samples are a result of the different kinematics.

Barrel Muon RoI Cluster trigger efficiencies (in %) for baryogenesis $\chi \rightarrow \tau\tau\nu$ benchmark samples ($m_{h}=125$ GeV). The trigger efficiency is defined as the fraction of LLPs selected by the Muon RoI Cluster trigger as a function of the LLP decay position. The trigger is efficient for hadronic decays of LLPs that occur anywhere from the outer regions of the HCal to the middle station of the MS. These efficiencies are obtained from the subset of events with only a single LLP decay in the muon spectrometer in order to ensure that the result of the trigger is due to a single burst of MS activity. The uncertainties shown are statistical only. The relative differences in efficiencies of the benchmark samples are a result of the different kinematics.

Endcap Muon RoI Cluster trigger efficiencies (in %) for $m_{\Phi}=100$ GeV scalar benchmark samples. The trigger efficiency is defined as the fraction of LLPs selected by the Muon RoI Cluster trigger as a function of the LLP decay position. The trigger is efficient for hadronic decays of LLPs that occur anywhere from the outer regions of the HCal to the middle station of the MS. These efficiencies are obtained from the subset of events with only a single LLP decay in the muon spectrometer in order to ensure that the result of the trigger is due to a single burst of MS activity. The uncertainties shown are statistical only. The relative differences in efficiencies of the benchmark samples are a result of the different kinematics.

Endcap Muon RoI Cluster trigger efficiencies (in %) for $m_{\Phi}=125$ GeV scalar benchmark samples. The trigger efficiency is defined as the fraction of LLPs selected by the Muon RoI Cluster trigger as a function of the LLP decay position. The trigger is efficient for hadronic decays of LLPs that occur anywhere from the outer regions of the HCal to the middle station of the MS. These efficiencies are obtained from the subset of events with only a single LLP decay in the muon spectrometer in order to ensure that the result of the trigger is due to a single burst of MS activity. The uncertainties shown are statistical only. The relative differences in efficiencies of the benchmark samples are a result of the different kinematics.

Endcap Muon RoI Cluster trigger efficiencies (in %) for $m_{\Phi}=200$ GeV scalar benchmark samples. The trigger efficiency is defined as the fraction of LLPs selected by the Muon RoI Cluster trigger as a function of the LLP decay position. The trigger is efficient for hadronic decays of LLPs that occur anywhere from the outer regions of the HCal to the middle station of the MS. These efficiencies are obtained from the subset of events with only a single LLP decay in the muon spectrometer in order to ensure that the result of the trigger is due to a single burst of MS activity. The uncertainties shown are statistical only. The relative differences in efficiencies of the benchmark samples are a result of the different kinematics.

Endcap Muon RoI Cluster trigger efficiencies (in %) for $m_{\Phi}=400$ GeV scalar benchmark samples. The trigger efficiency is defined as the fraction of LLPs selected by the Muon RoI Cluster trigger as a function of the LLP decay position. The trigger is efficient for hadronic decays of LLPs that occur anywhere from the outer regions of the HCal to the middle station of the MS. These efficiencies are obtained from the subset of events with only a single LLP decay in the muon spectrometer in order to ensure that the result of the trigger is due to a single burst of MS activity. The uncertainties shown are statistical only. The relative differences in efficiencies of the benchmark samples are a result of the different kinematics.

Endcap Muon RoI Cluster trigger efficiencies (in %) for $m_{\Phi}=600$ GeV scalar benchmark samples. The trigger efficiency is defined as the fraction of LLPs selected by the Muon RoI Cluster trigger as a function of the LLP decay position. The trigger is efficient for hadronic decays of LLPs that occur anywhere from the outer regions of the HCal to the middle station of the MS. These efficiencies are obtained from the subset of events with only a single LLP decay in the muon spectrometer in order to ensure that the result of the trigger is due to a single burst of MS activity. The uncertainties shown are statistical only. The relative differences in efficiencies of the benchmark samples are a result of the different kinematics.

Endcap Muon RoI Cluster trigger efficiencies (in %) for $m_{\Phi}=1000$ GeV scalar benchmark samples. The trigger efficiency is defined as the fraction of LLPs selected by the Muon RoI Cluster trigger as a function of the LLP decay position. The trigger is efficient for hadronic decays of LLPs that occur anywhere from the outer regions of the HCal to the middle station of the MS. These efficiencies are obtained from the subset of events with only a single LLP decay in the muon spectrometer in order to ensure that the result of the trigger is due to a single burst of MS activity. The uncertainties shown are statistical only. The relative differences in efficiencies of the benchmark samples are a result of the different kinematics.

Endcap Muon RoI Cluster trigger efficiencies (in %) for all Stealth SUSY benchmark samples. The trigger efficiency is defined as the fraction of LLPs selected by the Muon RoI Cluster trigger as a function of the LLP decay position. The trigger is efficient for hadronic decays of LLPs that occur anywhere from the outer regions of the HCal to the middle station of the MS. These efficiencies are obtained from the subset of events with only a single LLP decay in the muon spectrometer in order to ensure that the result of the trigger is due to a single burst of MS activity. The uncertainties shown are statistical only. The relative differences in efficiencies of the benchmark samples are a result of the different kinematics.

Endcap Muon RoI Cluster trigger efficiencies (in %) for baryogenesis $\chi \rightarrow \nu b \bar{b}$ benchmark samples ($m_{h}=125$ GeV). The trigger efficiency is defined as the fraction of LLPs selected by the Muon RoI Cluster trigger as a function of the LLP decay position. The trigger is efficient for hadronic decays of LLPs that occur anywhere from the outer regions of the HCal to the middle station of the MS. These efficiencies are obtained from the subset of events with only a single LLP decay in the muon spectrometer in order to ensure that the result of the trigger is due to a single burst of MS activity. The uncertainties shown are statistical only. The relative differences in efficiencies of the benchmark samples are a result of the different kinematics.

Endcap Muon RoI Cluster trigger efficiencies (in %) for baryogenesis $\chi \rightarrow cbs$ benchmark samples ($m_{h}=125$ GeV). The trigger efficiency is defined as the fraction of LLPs selected by the Muon RoI Cluster trigger as a function of the LLP decay position. The trigger is efficient for hadronic decays of LLPs that occur anywhere from the outer regions of the HCal to the middle station of the MS. These efficiencies are obtained from the subset of events with only a single LLP decay in the muon spectrometer in order to ensure that the result of the trigger is due to a single burst of MS activity. The uncertainties shown are statistical only. The relative differences in efficiencies of the benchmark samples are a result of the different kinematics.

Endcap Muon RoI Cluster trigger efficiencies (in %) for baryogenesis $\chi \rightarrow lcb$ benchmark samples ($m_{h}=125$ GeV). The trigger efficiency is defined as the fraction of LLPs selected by the Muon RoI Cluster trigger as a function of the LLP decay position. The trigger is efficient for hadronic decays of LLPs that occur anywhere from the outer regions of the HCal to the middle station of the MS. These efficiencies are obtained from the subset of events with only a single LLP decay in the muon spectrometer in order to ensure that the result of the trigger is due to a single burst of MS activity. The uncertainties shown are statistical only. The relative differences in efficiencies of the benchmark samples are a result of the different kinematics.

Endcap Muon RoI Cluster trigger efficiencies (in %) for baryogenesis $\chi \rightarrow \tau\tau\nu$ benchmark samples ($m_{h}=125$ GeV). The trigger efficiency is defined as the fraction of LLPs selected by the Muon RoI Cluster trigger as a function of the LLP decay position. The trigger is efficient for hadronic decays of LLPs that occur anywhere from the outer regions of the HCal to the middle station of the MS. These efficiencies are obtained from the subset of events with only a single LLP decay in the muon spectrometer in order to ensure that the result of the trigger is due to a single burst of MS activity. The uncertainties shown are statistical only. The relative differences in efficiencies of the benchmark samples are a result of the different kinematics.

Barrel MS vertex efficiencies (in %) for $m_{\Phi}=100$ GeV scalar benchmark samples. The vertex reconstruction efficiency is defined as the fraction of simulated LLP decays in the MS fiducial volume that match a reconstructed vertex ($\Delta R(\textrm{LLP,vertex}) = 0.4$) passing the baseline event selection and satisfying the vertex isolation criteria. A vertex is considered matched to a displaced decay if the vertex is within $\Delta R = 0.4$ of the simulated decay position. The MS vertex efficiency is parameterized as a function of the LLP decay position.

Barrel MS vertex efficiencies (in %) for $m_{\Phi}=125$ GeV scalar benchmark samples. The vertex reconstruction efficiency is defined as the fraction of simulated LLP decays in the MS fiducial volume that match a reconstructed vertex ($\Delta R(\textrm{LLP,vertex}) = 0.4$) passing the baseline event selection and satisfying the vertex isolation criteria. A vertex is considered matched to a displaced decay if the vertex is within $\Delta R = 0.4$ of the simulated decay position. The MS vertex efficiency is parameterized as a function of the LLP decay position.

Barrel MS vertex efficiencies (in %) for $m_{\Phi}=200$ GeV scalar benchmark samples. The vertex reconstruction efficiency is defined as the fraction of simulated LLP decays in the MS fiducial volume that match a reconstructed vertex ($\Delta R(\textrm{LLP,vertex}) = 0.4$) passing the baseline event selection and satisfying the vertex isolation criteria. A vertex is considered matched to a displaced decay if the vertex is within $\Delta R = 0.4$ of the simulated decay position. The MS vertex efficiency is parameterized as a function of the LLP decay position.

Barrel MS vertex efficiencies (in %) for $m_{\Phi}=400$ GeV scalar benchmark samples. The vertex reconstruction efficiency is defined as the fraction of simulated LLP decays in the MS fiducial volume that match a reconstructed vertex ($\Delta R(\textrm{LLP,vertex}) = 0.4$) passing the baseline event selection and satisfying the vertex isolation criteria. A vertex is considered matched to a displaced decay if the vertex is within $\Delta R = 0.4$ of the simulated decay position. The MS vertex efficiency is parameterized as a function of the LLP decay position.

Barrel MS vertex efficiencies (in %) for $m_{\Phi}=600$ GeV scalar benchmark samples. The vertex reconstruction efficiency is defined as the fraction of simulated LLP decays in the MS fiducial volume that match a reconstructed vertex ($\Delta R(\textrm{LLP,vertex}) = 0.4$) passing the baseline event selection and satisfying the vertex isolation criteria. A vertex is considered matched to a displaced decay if the vertex is within $\Delta R = 0.4$ of the simulated decay position. The MS vertex efficiency is parameterized as a function of the LLP decay position.

Barrel MS vertex efficiencies (in %) for $m_{\Phi}=1000$ GeV scalar benchmark samples. The vertex reconstruction efficiency is defined as the fraction of simulated LLP decays in the MS fiducial volume that match a reconstructed vertex ($\Delta R(\textrm{LLP,vertex}) = 0.4$) passing the baseline event selection and satisfying the vertex isolation criteria. A vertex is considered matched to a displaced decay if the vertex is within $\Delta R = 0.4$ of the simulated decay position. The MS vertex efficiency is parameterized as a function of the LLP decay position.

Barrel MS vertex efficiencies (in %) for all Stealth SUSY benchmark samples. The vertex reconstruction efficiency is defined as the fraction of simulated LLP decays in the MS fiducial volume that match a reconstructed vertex ($\Delta R(\textrm{LLP,vertex}) = 0.4$) passing the baseline event selection and satisfying the vertex isolation criteria. A vertex is considered matched to a displaced decay if the vertex is within $\Delta R = 0.4$ of the simulated decay position. The MS vertex efficiency is parameterized as a function of the LLP decay position.

Barrel MS vertex efficiencies (in %) for baryogenesis $\chi \rightarrow \nu b \bar{b}$ benchmark samples ($m_{h}=125$ GeV). The vertex reconstruction efficiency is defined as the fraction of simulated LLP decays in the MS fiducial volume that match a reconstructed vertex ($\Delta R(\textrm{LLP,vertex}) = 0.4$) passing the baseline event selection and satisfying the vertex isolation criteria. A vertex is considered matched to a displaced decay if the vertex is within $\Delta R = 0.4$ of the simulated decay position. The MS vertex efficiency is parameterized as a function of the LLP decay position.

Barrel MS vertex efficiencies (in %) for baryogenesis $\chi \rightarrow cbs$ benchmark samples ($m_{h}=125$ GeV). The vertex reconstruction efficiency is defined as the fraction of simulated LLP decays in the MS fiducial volume that match a reconstructed vertex ($\Delta R(\textrm{LLP,vertex}) = 0.4$) passing the baseline event selection and satisfying the vertex isolation criteria. A vertex is considered matched to a displaced decay if the vertex is within $\Delta R = 0.4$ of the simulated decay position. The MS vertex efficiency is parameterized as a function of the LLP decay position.

Barrel MS vertex efficiencies (in %) for baryogenesis $\chi \rightarrow lcb$ benchmark samples ($m_{h}=125$ GeV). The vertex reconstruction efficiency is defined as the fraction of simulated LLP decays in the MS fiducial volume that match a reconstructed vertex ($\Delta R(\textrm{LLP,vertex}) = 0.4$) passing the baseline event selection and satisfying the vertex isolation criteria. A vertex is considered matched to a displaced decay if the vertex is within $\Delta R = 0.4$ of the simulated decay position. The MS vertex efficiency is parameterized as a function of the LLP decay position.

Barrel MS vertex efficiencies (in %) for baryogenesis $\chi \rightarrow \tau\tau\nu$ benchmark samples ($m_{h}=125$ GeV). The vertex reconstruction efficiency is defined as the fraction of simulated LLP decays in the MS fiducial volume that match a reconstructed vertex ($\Delta R(\textrm{LLP,vertex}) = 0.4$) passing the baseline event selection and satisfying the vertex isolation criteria. A vertex is considered matched to a displaced decay if the vertex is within $\Delta R = 0.4$ of the simulated decay position. The MS vertex efficiency is parameterized as a function of the LLP decay position.

Endcap MS vertex efficiencies (in %) for $m_{\Phi}=100$ GeV scalar benchmark samples. The vertex reconstruction efficiency is defined as the fraction of simulated LLP decays in the MS fiducial volume that match a reconstructed vertex ($\Delta R(\textrm{LLP,vertex}) = 0.4$) passing the baseline event selection and satisfying the vertex isolation criteria. A vertex is considered matched to a displaced decay if the vertex is within $\Delta R = 0.4$ of the simulated decay position. The MS vertex efficiency is parameterized as a function of the LLP decay position.

Endcap MS vertex efficiencies (in %) for $m_{\Phi}=125$ GeV scalar benchmark samples. The vertex reconstruction efficiency is defined as the fraction of simulated LLP decays in the MS fiducial volume that match a reconstructed vertex ($\Delta R(\textrm{LLP,vertex}) = 0.4$) passing the baseline event selection and satisfying the vertex isolation criteria. A vertex is considered matched to a displaced decay if the vertex is within $\Delta R = 0.4$ of the simulated decay position. The MS vertex efficiency is parameterized as a function of the LLP decay position.

Endcap MS vertex efficiencies (in %) for $m_{\Phi}=200$ GeV scalar benchmark samples. The vertex reconstruction efficiency is defined as the fraction of simulated LLP decays in the MS fiducial volume that match a reconstructed vertex ($\Delta R(\textrm{LLP,vertex}) = 0.4$) passing the baseline event selection and satisfying the vertex isolation criteria. A vertex is considered matched to a displaced decay if the vertex is within $\Delta R = 0.4$ of the simulated decay position. The MS vertex efficiency is parameterized as a function of the LLP decay position.

Endcap MS vertex efficiencies (in %) for $m_{\Phi}=400$ GeV scalar benchmark samples. The vertex reconstruction efficiency is defined as the fraction of simulated LLP decays in the MS fiducial volume that match a reconstructed vertex ($\Delta R(\textrm{LLP,vertex}) = 0.4$) passing the baseline event selection and satisfying the vertex isolation criteria. A vertex is considered matched to a displaced decay if the vertex is within $\Delta R = 0.4$ of the simulated decay position. The MS vertex efficiency is parameterized as a function of the LLP decay position.

Endcap MS vertex efficiencies (in %) for $m_{\Phi}=600$ GeV scalar benchmark samples. The vertex reconstruction efficiency is defined as the fraction of simulated LLP decays in the MS fiducial volume that match a reconstructed vertex ($\Delta R(\textrm{LLP,vertex}) = 0.4$) passing the baseline event selection and satisfying the vertex isolation criteria. A vertex is considered matched to a displaced decay if the vertex is within $\Delta R = 0.4$ of the simulated decay position. The MS vertex efficiency is parameterized as a function of the LLP decay position.

Endcap MS vertex efficiencies (in %) for $m_{\Phi}=1000$ GeV scalar benchmark samples. The vertex reconstruction efficiency is defined as the fraction of simulated LLP decays in the MS fiducial volume that match a reconstructed vertex ($\Delta R(\textrm{LLP,vertex}) = 0.4$) passing the baseline event selection and satisfying the vertex isolation criteria. A vertex is considered matched to a displaced decay if the vertex is within $\Delta R = 0.4$ of the simulated decay position. The MS vertex efficiency is parameterized as a function of the LLP decay position.

Endcap MS vertex efficiencies (in %) for all Stealth SUSY benchmark samples. The vertex reconstruction efficiency is defined as the fraction of simulated LLP decays in the MS fiducial volume that match a reconstructed vertex ($\Delta R(\textrm{LLP,vertex}) = 0.4$) passing the baseline event selection and satisfying the vertex isolation criteria. A vertex is considered matched to a displaced decay if the vertex is within $\Delta R = 0.4$ of the simulated decay position. The MS vertex efficiency is parameterized as a function of the LLP decay position.

Endcap MS vertex efficiencies (in %) for baryogenesis $\chi \rightarrow \nu b \bar{b}$ benchmark samples ($m_{h}=125$ GeV). The vertex reconstruction efficiency is defined as the fraction of simulated LLP decays in the MS fiducial volume that match a reconstructed vertex ($\Delta R(\textrm{LLP,vertex}) = 0.4$) passing the baseline event selection and satisfying the vertex isolation criteria. A vertex is considered matched to a displaced decay if the vertex is within $\Delta R = 0.4$ of the simulated decay position. The MS vertex efficiency is parameterized as a function of the LLP decay position.

Endcap MS vertex efficiencies (in %) for baryogenesis $\chi \rightarrow cbs$ benchmark samples ($m_{h}=125$ GeV). The vertex reconstruction efficiency is defined as the fraction of simulated LLP decays in the MS fiducial volume that match a reconstructed vertex ($\Delta R(\textrm{LLP,vertex}) = 0.4$) passing the baseline event selection and satisfying the vertex isolation criteria. A vertex is considered matched to a displaced decay if the vertex is within $\Delta R = 0.4$ of the simulated decay position. The MS vertex efficiency is parameterized as a function of the LLP decay position.

Endcap MS vertex efficiencies (in %) for baryogenesis $\chi \rightarrow lcb$ benchmark samples ($m_{h}=125$ GeV). The vertex reconstruction efficiency is defined as the fraction of simulated LLP decays in the MS fiducial volume that match a reconstructed vertex ($\Delta R(\textrm{LLP,vertex}) = 0.4$) passing the baseline event selection and satisfying the vertex isolation criteria. A vertex is considered matched to a displaced decay if the vertex is within $\Delta R = 0.4$ of the simulated decay position. The MS vertex efficiency is parameterized as a function of the LLP decay position.

Endcap MS vertex efficiencies (in %) for baryogenesis $\chi \rightarrow \tau\tau\nu$ benchmark samples ($m_{h}=125$ GeV). The vertex reconstruction efficiency is defined as the fraction of simulated LLP decays in the MS fiducial volume that match a reconstructed vertex ($\Delta R(\textrm{LLP,vertex}) = 0.4$) passing the baseline event selection and satisfying the vertex isolation criteria. A vertex is considered matched to a displaced decay if the vertex is within $\Delta R = 0.4$ of the simulated decay position. The MS vertex efficiency is parameterized as a function of the LLP decay position.

Upper 95% CL limits on $\sigma/\sigma_{\textrm{SM}}\times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=125$ GeV and $m_{s}=5$ GeV scalar benchmark sample for 2MSVx strategy.

Upper 95% CL limits on $\sigma/\sigma_{\textrm{SM}}\times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=125$ GeV and $m_{s}=5$ GeV scalar benchmark sample for 1MSVx strategy.

Upper 95% CL limits on $\sigma/\sigma_{\textrm{SM}}\times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=125$ GeV and $m_{s}=5$ GeV scalar benchmark sample for the combination of 1MSVx and 2MSVx strategies.

Upper 95% CL limits on $\sigma/\sigma_{\textrm{SM}}\times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=125$ GeV and $m_{s}=8$ GeV scalar benchmark sample for 2MSVx strategy.

Upper 95% CL limits on $\sigma/\sigma_{\textrm{SM}}\times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=125$ GeV and $m_{s}=8$ GeV scalar benchmark sample for 1MSVx strategy.

Upper 95% CL limits on $\sigma/\sigma_{\textrm{SM}}\times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=125$ GeV and $m_{s}=8$ GeV scalar benchmark sample for the combination of 1MSVx and 2MSVx strategies.

Upper 95% CL limits on $\sigma/\sigma_{\textrm{SM}}\times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=125$ GeV and $m_{s}=15$ GeV scalar benchmark sample for 2MSVx strategy.

Upper 95% CL limits on $\sigma/\sigma_{\textrm{SM}}\times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=125$ GeV and $m_{s}=15$ GeV scalar benchmark sample for 1MSVx strategy.

Upper 95% CL limits on $\sigma/\sigma_{\textrm{SM}}\times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=125$ GeV and $m_{s}=15$ GeV scalar benchmark sample for the combination of 1MSVx and 2MSVx strategies.

Upper 95% CL limits on $\sigma/\sigma_{\textrm{SM}}\times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=125$ GeV and $m_{s}=25$ GeV scalar benchmark sample for 2MSVx strategy.

Upper 95% CL limits on $\sigma/\sigma_{\textrm{SM}}\times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=125$ GeV and $m_{s}=25$ GeV scalar benchmark sample for 1MSVx strategy.

Upper 95% CL limits on $\sigma/\sigma_{\textrm{SM}}\times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=125$ GeV and $m_{s}=25$ GeV scalar benchmark sample for the combination of 1MSVx and 2MSVx strategies.

Upper 95% CL limits on $\sigma/\sigma_{\textrm{SM}}\times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=125$ GeV and $m_{s}=40$ GeV scalar benchmark sample for 2MSVx strategy.

Upper 95% CL limits on $\sigma/\sigma_{\textrm{SM}}\times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=125$ GeV and $m_{s}=40$ GeV scalar benchmark sample for 1MSVx strategy.

Upper 95% CL limits on $\sigma/\sigma_{\textrm{SM}}\times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=125$ GeV and $m_{s}=40$ GeV scalar benchmark sample for the combination of 1MSVx and 2MSVx strategies.

Upper 95% CL limits on $\sigma \times B_{\tilde{g} \rightarrow \tilde{S} g}$ as a function of the proper lifetime $c\tau$ for $m_{\tilde{g}}=250$ GeV for 2MSVx strategy.

Upper 95% CL limits on $\sigma \times B_{\tilde{g} \rightarrow \tilde{S} g}$ as a function of the proper lifetime $c\tau$ for $m_{\tilde{g}}=500$ GeV for 2MSVx strategy.

Upper 95% CL limits on $\sigma \times B_{\tilde{g} \rightarrow \tilde{S} g}$ as a function of the proper lifetime $c\tau$ for $m_{\tilde{g}}=500$ GeV for 1MSVx strategy.

Upper 95% CL limits on $\sigma \times B_{\tilde{g} \rightarrow \tilde{S} g}$ as a function of the proper lifetime $c\tau$ for $m_{\tilde{g}}=500$ GeV for the combination of 1MSVx and 2MSVx strategies.

Upper 95% CL limits $\sigma \times B_{\tilde{g} \rightarrow \tilde{S} g}$ as a function of the proper lifetime $c\tau$ for $m_{\tilde{g}}=800$ GeV for 2MSVx strategy.

Upper 95% CL limits $\sigma \times B_{\tilde{g} \rightarrow \tilde{S} g}$ as a function of the proper lifetime $c\tau$ for $m_{\tilde{g}}=800$ GeV for 1MSVx strategy.

Upper 95% CL limits $\sigma \times B_{\tilde{g} \rightarrow \tilde{S} g}$ as a function of the proper lifetime $c\tau$ for $m_{\tilde{g}}=800$ GeV for the combination of 1MSVx and 2MSVx strategies.

Upper 95% CL limits $\sigma \times B_{\tilde{g} \rightarrow \tilde{S} g}$ as a function of the proper lifetime $c\tau$ for $m_{\tilde{g}}=1200$ GeV for 2MSVx strategy.

Upper 95% CL limits $\sigma \times B_{\tilde{g} \rightarrow \tilde{S} g}$ as a function of the proper lifetime $c\tau$ for $m_{\tilde{g}}=1200$ GeV for 1MSVx strategy.

Upper 95% CL limits $\sigma \times B_{\tilde{g} \rightarrow \tilde{S} g}$ as a function of the proper lifetime $c\tau$ for $m_{\tilde{g}}=1200$ GeV for the combination of 1MSVx and 2MSVx strategies.

Upper 95% CL limits $\sigma \times B_{\tilde{g} \rightarrow \tilde{S} g}$ as a function of the proper lifetime $c\tau$ for $m_{\tilde{g}}=1500$ GeV for 2MSVx strategy.

Upper 95% CL limits $\sigma \times B_{\tilde{g} \rightarrow \tilde{S} g}$ as a function of the proper lifetime $c\tau$ for $m_{\tilde{g}}=1500$ GeV for 1MSVx strategy.

Upper 95% CL limits $\sigma \times B_{\tilde{g} \rightarrow \tilde{S} g}$ as a function of the proper lifetime $c\tau$ for $m_{\tilde{g}}=1500$ GeV for the combination of 1MSVx and 2MSVx strategies.

Upper 95% CL limits $\sigma \times B_{\tilde{g} \rightarrow \tilde{S} g}$ as a function of the proper lifetime $c\tau$ for $m_{\tilde{g}}=2000$ GeV for 2MSVx strategy.

Upper 95% CL limits $\sigma \times B_{\tilde{g} \rightarrow \tilde{S} g}$ as a function of the proper lifetime $c\tau$ for $m_{\tilde{g}}=2000$ GeV for 1MSVx strategy.

Upper 95% CL limits $\sigma \times B_{\tilde{g} \rightarrow \tilde{S} g}$ as a function of the proper lifetime $c\tau$ for $m_{\tilde{g}}=2000$ GeV for the combination of 1MSVx and 2MSVx strategies.

Upper 95% CL limits on $\sigma \times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=100$ GeV and $m_{s}=8$ GeV scalar benchmark sample for 2MSVx strategy.

Upper 95% CL limits on $\sigma \times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=100$ GeV and $m_{s}=25$ GeV scalar benchmark sample for 2MSVx strategy.

Upper 95% CL limits on $\sigma \times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=200$ GeV and $m_{s}=8$ GeV scalar benchmark sample for 2MSVx strategy.

Upper 95% CL limits on $\sigma \times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=200$ GeV and $m_{s}=25$ GeV scalar benchmark sample for 2MSVx strategy.

Upper 95% CL limits on $\sigma \times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=200$ GeV and $m_{s}=50$ GeV scalar benchmark sample for 2MSVx strategy.

Upper 95% CL limits on $\sigma \times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=400$ GeV and $m_{s}=50$ GeV scalar benchmark sample for 2MSVx strategy.

Upper 95% CL limits on $\sigma \times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=400$ GeV and $m_{s}=100$ GeV scalar benchmark sample for 2MSVx strategy.

Upper 95% CL limits on $\sigma \times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=600$ GeV and $m_{s}=50$ GeV scalar benchmark sample for 2MSVx strategy.

Upper 95% CL limits on $\sigma \times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=600$ GeV and $m_{s}=150$ GeV scalar benchmark sample for 2MSVx strategy.

Upper 95% CL limits on $\sigma \times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=1000$ GeV and $m_{s}=50$ GeV scalar benchmark sample for 2MSVx strategy.

Upper 95% CL limits on $\sigma \times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=1000$ GeV and $m_{s}=150$ GeV scalar benchmark sample for 2MSVx strategy.

Upper 95% CL limits on $\sigma \times B$ as a function of the proper lifetime $c\tau$ for $m_{\Phi}=1000$ GeV and $m_{s}=400$ GeV scalar benchmark sample for 2MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow \nu b \bar{b}$ channel with $m_{\chi}=10$ GeV ($m_{h}=125$ GeV) for 2MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow \nu b \bar{b}$ channel with $m_{\chi}=10$ GeV ($m_{h}=125$ GeV) for 1MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow \nu b \bar{b}$ channel with $m_{\chi}=10$ GeV ($m_{h}=125$ GeV) for the combination of 1MSVx and 2MSVx strategies.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow \nu b \bar{b}$ channel with $m_{\chi}=30$ GeV ($m_{h}=125$ GeV) for 2MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow \nu b \bar{b}$ channel with $m_{\chi}=30$ GeV ($m_{h}=125$ GeV) for 1MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow \nu b \bar{b}$ channel with $m_{\chi}=30$ GeV ($m_{h}=125$ GeV) for the combination of 1MSVx and 2MSVx strategies.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow \nu b \bar{b}$ channel with $m_{\chi}=50$ GeV ($m_{h}=125$ GeV) for 2MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow \nu b \bar{b}$ channel with $m_{\chi}=50$ GeV ($m_{h}=125$ GeV) for 1MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow \nu b \bar{b}$ channel with $m_{\chi}=50$ GeV ($m_{h}=125$ GeV) for the combination of 1MSVx and 2MSVx strategies.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow \nu b \bar{b}$ channel with $m_{\chi}=100$ GeV ($m_{h}=125$ GeV) for 2MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow c b s$ channel with $m_{\chi}=10$ GeV ($m_{h}=125$ GeV) for 2MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow c b s$ channel with $m_{\chi}=10$ GeV ($m_{h}=125$ GeV) for 1MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow c b s$ channel with $m_{\chi}=10$ GeV ($m_{h}=125$ GeV) for the combination of 1MSVx and 2MSVx strategies.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow c b s$ channel with $m_{\chi}=30$ GeV ($m_{h}=125$ GeV) for 2MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow c b s$ channel with $m_{\chi}=30$ GeV ($m_{h}=125$ GeV) for 1MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow c b s$ channel with $m_{\chi}=30$ GeV ($m_{h}=125$ GeV) for the combination of 1MSVx and 2MSVx strategies.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow c b s$ channel with $m_{\chi}=50$ GeV ($m_{h}=125$ GeV) for 2MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow c b s$ channel with $m_{\chi}=50$ GeV ($m_{h}=125$ GeV) for 1MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow c b s$ channel with $m_{\chi}=50$ GeV ($m_{h}=125$ GeV) for the combination of 1MSVx and 2MSVx strategies.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow c b s$ channel with $m_{\chi}=100$ GeV ($m_{h}=125$ GeV) for 2MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow l c b$ channel with $m_{\chi}=10$ GeV ($m_{h}=125$ GeV) for 2MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow l c b$ channel with $m_{\chi}=10$ GeV ($m_{h}=125$ GeV) for 1MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow l c b$ channel with $m_{\chi}=10$ GeV ($m_{h}=125$ GeV) for the combination of 1MSVx and 2MSVx strategies.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow l c b$ channel with $m_{\chi}=30$ GeV ($m_{h}=125$ GeV) for 2MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow l c b$ channel with $m_{\chi}=30$ GeV ($m_{h}=125$ GeV) for 1MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow l c b$ channel with $m_{\chi}=30$ GeV ($m_{h}=125$ GeV) for the combination of 1MSVx and 2MSVx strategies.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow l c b$ channel with $m_{\chi}=50$ GeV ($m_{h}=125$ GeV) for 2MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow l c b$ channel with $m_{\chi}=50$ GeV ($m_{h}=125$ GeV) for 1MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow l c b$ channel with $m_{\chi}=50$ GeV ($m_{h}=125$ GeV) for the combination of 1MSVx and 2MSVx strategies.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow l c b$ channel with $m_{\chi}=100$ GeV ($m_{h}=125$ GeV) for 2MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow \tau \tau \nu$ channel with $m_{\chi}=10$ GeV ($m_{h}=125$ GeV) for 2MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow \tau \tau \nu$ channel with $m_{\chi}=30$ GeV ($m_{h}=125$ GeV) for 2MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow \tau \tau \nu$ channel with $m_{\chi}=50$ GeV ($m_{h}=125$ GeV) for 2MSVx strategy.

Upper 95% CL limits on $\sigma\times B$ as a function of the proper lifetime $c\tau$ for $\chi \rightarrow \tau \tau \nu$ channel with $m_{\chi}=100$ GeV ($m_{h}=125$ GeV) for 2MSVx strategy.

Measured differential cross sections for the $pp \rightarrow \nu\bar{\nu}\gamma$ process as a function of $p_{T}^{\nu\bar{\nu}}$ in the inclusive $N_{jets} \geq 0$ extended fiducial region defined in the paper.

Measured differential cross sections for the $pp \rightarrow \nu\bar{\nu}\gamma$ process as a function of $p_{T}^{\nu\bar{\nu}}$ in the exclusive $N_{jets} = 0$ extended fiducial region defined in the paper.

Measured differential cross sections as a function of $N_{jets}$ in the extended fiducial region defined in the paper.

Observed and expected one dimensional 95% C.L. limits on vertex function parameters for the $ZZ\gamma$ and $Z\gamma\gamma$ vertices.

Observed and expected one dimensional 95% C.L. limits on EFT parameters for the $ZZ\gamma$ and $Z\gamma\gamma$ vertices.

Expected 95% CL exclusion contour in the $m_{W_R}–m_{N_R}$ plane for the Majorana $N_R$ neutrino $\mu\mu$ channel.

Observed 95% CL exclusion contour in the $m_{W_R}–m_{N_R}$ plane for the Majorana $N_R$ neutrino $\mu\mu$ channel.

Observed and expected 95% CL exclusion, for the tested signal mass hypotheses in the $m_{W_R}–m_{N_R}$ plane, for the Majorana $N_R$ neutrino $\mu\mu$ channel.

Expected 95% CL exclusion contour in the $m_{W_R}–m_{N_R}$ plane for the Dirac $N_R$ neutrino $ee$ channel.

Observed 95% CL exclusion contour in the $m_{W_R}–m_{N_R}$ plane for the Dirac $N_R$ neutrino $ee$ channel.

Observed and expected 95% CL exclusion, for the tested signal mass hypotheses in the $m_{W_R}–m_{N_R}$ plane, for the Dirac $N_R$ neutrino $ee$ channel.

Expected 95% CL exclusion contour in the $m_{W_R}–m_{N_R}$ plane for the Dirac $N_R$ neutrino $\mu\mu$ channel.

Observed 95% CL exclusion contour in the $m_{W_R}–m_{N_R}$ plane for the Dirac $N_R$ neutrino $\mu\mu$ channel.

Observed and expected 95% CL exclusion, for the tested signal mass hypotheses in the $m_{W_R}–m_{N_R}$ plane, for the Dirac $N_R$ neutrino $\mu\mu$ channel.

Observed 95% CL upper limit on cross-section times branching ratio to the $ee$ final state for the Keung-Senjanovic process in the $m_{W_R}–m_{N_R}$ plane for the Majorana $N_R$ neutrino $ee$ channel.

Observed 95% CL upper limit on cross-section times branching ratio to the $\mu\mu$ final state for the Keung-Senjanovic process in the $m_{W_R}–m_{N_R}$ plane for the Majorana $N_R$ neutrino $\mu\mu$ channel.

Observed 95% CL upper limit on cross-section times branching ratio to the $\mu\mu$ final state for the Keung-Senjanovic process in the $m_{W_R}–m_{N_R}$ plane for the Dirac $N_R$ neutrino $ee$ channel.

Observed 95% CL upper limit on cross-section times branching ratio to the $\mu\mu$ final state for the Keung-Senjanovic process in the $m_{W_R}–m_{N_R}$ plane for the Dirac $N_R$ neutrino $\mu\mu$ channel.

Efficiencies times acceptance for signal region selection as a function of the signal $W_R$ and $N_R$ masses for the SS $e^{\pm}e^{\pm}$ channel.

Efficiencies times acceptance for signal region selection as a function of the signal $W_R$ and $N_R$ masses for the SS $\mu^{\pm}\mu^{\pm}$ channel.

Efficiencies times acceptance for signal region selection as a function of the signal $W_R$ and $N_R$ masses for the OS $e^{\pm}e^{\mp}$ channel.

Efficiencies times acceptance for signal region selection as a function of the signal $W_R$ and $N_R$ masses for the OS $\mu^{\pm}\mu^{\mp}$ channel.

The expected upper limits on the production cross-section times the product of branching ratios for the benchmark signal scenario involving a scalar particle $X$ with narrow width decaying via $X\rightarrow aa\rightarrow 4\gamma$, $\sigma_X\times B(X\rightarrow aa)\times B(a\rightarrow\gamma\gamma)^2$. The limits for $m_{a}$ = 5 GeV and 10 GeV do not cover as large a range as the other mass points, since the region of interest is limited to $ m_{a} < 0.01 \times m_{X}$. Additionally, the expected limits are not provided for a small number of points, indicated with a hyphen, because of a technical failure with the computation.

The observed upper limits on the production cross-section times the product of branching ratios for the benchmark signal scenario involving a scalar particle $X$ with narrow width decaying via $X\rightarrow aa\rightarrow 6\pi^0$, $\sigma_X\times B(X\rightarrow aa)\times B(a\rightarrow 3\pi^0)^2$. The limits for $m_{a}$ = 5 GeV and 10 GeV do not cover as large a range as the other mass points, since the region of interest is limited to $ m_{a} < 0.01 \times m_{X}$.

The expected upper limits on the production cross-section times the product of branching ratios for the benchmark signal scenario involving a scalar particle $X$ with narrow width decaying via $X\rightarrow aa\rightarrow 6\pi^0$, $\sigma_X\times B(X\rightarrow aa)\times B(a\rightarrow 3\pi^0)^2$. The limits for $m_{a}$ = 5 GeV and 10 GeV do not cover as large a range as the other mass points, since the region of interest is limited to $ m_{a} < 0.01 \times m_{X}$. Additionally, the expected limits are not provided for a small number of points, indicated with a hyphen, because of a technical failure with the computation.

Observed 95% CL upper limits on the visible cross section as a function of $m_X$ and the fraction of events in the low-$\Delta E$ category.

Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 0.1 GeV.

Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 0.5 GeV.

Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 0.7 GeV.

Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 1 GeV.

Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 2 GeV.

Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 5 GeV.

Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 10 GeV.

Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 0.5 GeV.

Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 0.7 GeV.

Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 1 GeV.

Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 2 GeV.

Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 5 GeV.

Selection efficiency for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 10 GeV.

Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 0.1 GeV.

Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 0.5 GeV.

Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 0.7 GeV.

Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 1 GeV.

Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 2 GeV.

Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 5 GeV.

Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 2\gamma$ with $m_a$ = 10 GeV.

Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 0.5 GeV.

Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 0.7 GeV.

Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 1 GeV.

Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 2 GeV.

Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 5 GeV.

Fraction of reconstructed photons with a value of shower shape variable $\Delta E$ lower than the threshold, for reconstructed photons originating from the decay $a\rightarrow 3\pi^0\rightarrow 6\gamma$ with $m_a$ = 10 GeV.

Selection efficiency for photons originating from the BSM process $X\rightarrow\gamma\gamma$, where the $X$ particle is a high-mass narrow-width scalar particle originating from the gluon--gluon fusion process.

Fraction of photons with a value of shower shape variable $\Delta E$ lower than the threshold, for photons originating from the BSM process $X\rightarrow\gamma\gamma$, where the $X$ particle is a high-mass narrow-width scalar particle originating from the gluon--gluon fusion process.

2$\tau$ HighMass SR eff.

2$\tau$ multibin SR eff.

2$\tau$ GMSB SR eff.

1$\tau$ Compressed SR eff.

1$\tau$ MediumMass SR eff.

2$\tau$ Compressed SR eff.

2$\tau$ HighMass SR eff.

2$\tau$ multibin SR eff.

2$\tau$ GMSB SR eff.

1$\tau$ Compressed SR acceptance.

1$\tau$ MediumMass SR acceptance.

2$\tau$ Compressed SR acceptance.

2$\tau$ HighMass SR acceptance.

2$\tau$ multibin SR acceptance.

2$\tau$ GMSB SR acceptance.

1$\tau$ Compressed SR acceptance.

1$\tau$ MediumMass SR acceptance.

2$\tau$ Compressed SR acceptance.

2$\tau$ HighMass SR acceptance.

2$\tau$ multibin SR acceptance.

2$\tau$ GMSB SR acceptance.

Cutflow table of the $1\tau$ compressed SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $1\tau$ medium-mass SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $2\tau$ compressed SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $2\tau$ high-mass SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $2\tau$ multibin SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $2\tau$ GMSB SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Best performing fit setups entering the final combination as a function of the LSP mass and the gluino mass. 'S' marks the simultaneous fit of the four simplified model single-bin SRs, 'M' denotes the simultaneous fit of the two $1\tau$ SRs and the $2\tau$ multibin SR.

Observed exclusion contour at 95% CL as a function of tanBeta and the SUSY-breaking mass scale Lambda.

Expected exclusion contour at 95% CL as a function of tanBeta and the SUSY-breaking mass scale Lambda.

Observed exclusion contour at 95% CL as a function of the LSP mass and the gluino mass.

Expected exclusion contour at 95% CL as a function of the LSP mass and the gluino mass.

Observed upper limits on the production cross section at 95% CL in pb as a function of tanBeta and SUSY breaking mass scale Lambda.

Observed upper limits on the production cross section at 95% CL in pb as a function of the LSP mass and the gluino mass.

Yields of the expected background from the SM in the bins of the multibin SR of the $2\tau$ channel with all bins being simultaneously used to constrain the background prediction. Expectation is given with the scalings computed in the combined fit applied. Uncertainties are statistial plus systematrics. Only the subsamples contributing the respective region are considered.

$m_{\mathrm{T}}^{\tau}$ in the compressed $m_{\mathrm{T}}^{\tau}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$E_{\mathrm{T}}^{\mathrm{miss}}$ in the compressed $E_{\mathrm{T}}^{\mathrm{miss}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$m_{\mathrm{T}}^{\tau}$ in the medium-mass $m_{\mathrm{T}}^{\tau}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$E_{\mathrm{T}}^{\mathrm{miss}}$ in the medium-mass $E_{\mathrm{T}}^{\mathrm{miss}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$H_{\mathrm{T}}$ in the medium-mass $H_{\mathrm{T}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$m_{\mathrm{T}}^{\tau_1}$ + $m_{\mathrm{T}}^{\tau_2}$ in the top VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$H_{\mathrm{T}}$ in the $W$ VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$m_{\mathrm{T}}^{\tau_1}$ + $m_{\mathrm{T}}^{\tau_2}$ in the $Z$ VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$m_{\mathrm{T}}^{\tau}$ in the compressed SR of the $1\tau$ channel before application of the $m_{\mathrm{T}}^{\tau}$ > 80 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

$H_{\mathrm{T}}$ in the medium-mass SR of the $1\tau$ channel before application of the $H_{\mathrm{T}}$ > 1000 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

$m_{\mathrm{T}}^{\mathrm{sum}}$ in the compressed SR of the $2\tau$ channel before application of the $m_{\mathrm{T}}^{\mathrm{sum}}$ > 1600 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

$H_{\mathrm{T}}$ in the high-mass SR of the $2\tau$ channel before application of the $H_{\mathrm{T}}$ > 1100 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

mT(tau_1) + mT(tau_2) in the multibin SR of the 2T channel. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

$H_{\mathrm{T}}$ in the GMSB SR of the $2\tau$ channel before application of the $H_{\mathrm{T}}$ > 1900 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

The observed and expected 95% CL upper limits on model-independent visible cross-sections, along with the observed $p0$ values, for the stable signal region, as a function of different mass windows, for which the lower bound is shown. The upper boundary on the mass window is 5 TeV for all windows.

The observed and expected 95% CL upper limits on model-independent visible cross-sections, along with the observed $p0$ values, for the metastable signal region, as a function of different mass windows, for which the lower bound is shown. The upper boundary on the mass window is 5 TeV for all windows.

For each gluino lifetime and mass in the signal samples, the lower boundary of the mass window in which at least $70\%$ of the reconstructed signal appears. The upper boundary for all mass windows is 5 TeV.

Acceptance and efficiency for a representative set of pair-produced gluino signal samples. The mass of the gluino ($m(\tilde{g})$), its lifetime ($\tau(\tilde{g})$) and the mass of the neutralino ($m(\tilde{\chi}^{0})$) are given in the first three columns. The Pythia 6.4.27 signal samples shown in this table are not reweighted to match the transverse momentum of the gluino-gluino system as simulated by MadGraph5_aMC@NLO. The acceptance is defined as the fraction of events passing a loose set of fiducial requirements. The full simulation efficiency (Full sim. $\epsilon$) is defined as the ratio of the number of reconstructed events, as expected by the full ATLAS simulation, and the number of events passing the fiducial requirements. The parameterised simulation efficiency (Param. sim. $\epsilon$) is defined as the ratio of the number of events estimated using a set of parametrised efficiencies (see auxiliary Figures 9,10,11,12) and the number of events passing the fiducial requirements alone.

The reconstructed candidate track mass distributions for observed data, predicted background, and the expected contribution from two signal models in the metastable R-hadron signal region. The yellow band around the background estimation includes both the statistical and systematic uncertainties.

The reconstructed candidate track mass distributions for observed data, predicted background, and the expected contribution from two signal models in the stable R-hadron signal region. The yellow band around the background estimation includes both the statistical and systematic uncertainties.

The 95% CL upper limit on the cross-section as a function of mass for gluinos with lifetime $\tau = 10$ ns decaying into $q\bar{q}$ and a 100 GeV neutralino, with the observed limit shown as a solid black line. The predicted production cross-section values are shown in purple along with their uncertainty. The expected upper limit in the case of only background is shown by the dashed black line, with a green $\pm 1\sigma$ and a yellow $\pm 2\sigma$ band.

The 95% CL upper limit on the cross-section as a function of mass for stable gluino $R$-hadrons, with the observed limit shown as a solid black line. The predicted production cross-section values are shown in purple along with their uncertainty. The expected upper limit in the case of only background is shown by the dashed black line, with a green $\pm 1\sigma$ and a yellow $\pm 2\sigma$ band.

Observed 95% lower limits on the gluino mass in the gluino lifetime--mass plane. The excluded area is to the left of the curves.

Expected 95% lower limits on the gluino mass in the gluino lifetime--mass plane. The excluded area is to the left of the curves.

The 95% CL upper limit on the cross-section as a function of mass for gluinos with lifetime $\tau = 1$ ns decaying into $q\bar{q}$ and a 100 GeV neutralino, with the observed limit shown as a solid black line. The predicted production cross-section values are shown in purple along with their uncertainty. The expected upper limit in the case of only background is shown by the dashed black line, with a green $\pm 1\sigma$ and a yellow $\pm 2\sigma$ band.

The 95% CL upper limit on the cross-section as a function of mass for gluinos with lifetime $\tau = 3$ ns decaying into $q\bar{q}$ and a 100 GeV neutralino, with the observed limit shown as a solid black line. The predicted production cross-section values are shown in purple along with their uncertainty. The expected upper limit in the case of only background is shown by the dashed black line, with a green $\pm 1\sigma$ and a yellow $\pm 2\sigma$ band.

The 95% CL upper limit on the cross-section as a function of mass for gluinos with lifetime $\tau = 30$ ns decaying into $q\bar{q}$ and a 100 GeV neutralino, with the observed limit shown as a solid black line. The predicted production cross-section values are shown in purple along with their uncertainty. The expected upper limit in the case of only background is shown by the dashed black line, with a green $\pm 1\sigma$ and a yellow $\pm 2\sigma$ band.

The 95% CL upper limit on the cross-section as a function of mass for gluinos with lifetime $\tau = 50$ ns decaying into $q\bar{q}$ and a 100 GeV neutralino, with the observed limit shown as a solid black line. The predicted production cross-section values are shown in purple along with their uncertainty. The expected upper limit in the case of only background is shown by the dashed black line, with a green $\pm 1\sigma$ and a yellow $\pm 2\sigma$ band.

The relationship between generated and reconstructed mass for gluino $R$-hadrons. Above 1500 GeV, the reconstructed mass falls below the generated mass due to bias in the reconstructed momentum. The uncertainty on the reconstructed mass is dominated by momentum uncertainty. The black dots represent the reconstructed mass computed as the most probable value of a Gaussian fit function, with the error bars showing its statistical uncertainty, while the orange band is the full-width at half maximum of the reconstructed mass distribution.

The parameterised efficiency for events to pass metastable event selections (including trigger, E$_{T}^{miss}$, and event cleaning requirements) as a function of the true E$_{T}^{miss}$ in the system, which is calculated at generator level. Event-level efficiencies are evaluated for events which have at least true E$_{T}^{miss} > 50$ GeV. The metastable event efficiencies are evaluated for different radial regions depending on the smallest radial distance, R, at which an R-hadron decays in the detector.

The parameterised efficiency for events to pass metastable event selections (including trigger, E$_{T}^{miss}$, and event cleaning requirements) as a function of the true E$_{T}^{miss}$ in the system, which is calculated at generator level. Event-level efficiencies are evaluated for events which have at least true E$_{T}^{miss} > 50$ GeV. The stable event efficiencies are evaluated for samples in which no R-hadron decays within the detector.

The parameterised efficiency for particles to pass full track selections in the metastable signal region, as function of the particle’s $\beta$, in different bins of transverse momentum, $p_{T}$, and for different radial decay positions of the particle. The efficiency is evaluated for particles which pass a loose set of fiducial requirements at generator level.

The parameterised efficiency for particles to pass full track selections in the metastable signal region, as function of the particle’s $\beta$, in different bins of transverse momentum, $p_{T}$, and for different radial decay positions of the particle. The efficiency is evaluated for particles which pass a loose set of fiducial requirements at generator level.

The parameterised efficiency for particles to pass full track selections in the metastable signal region, as function of the particle’s $\beta$, in different bins of transverse momentum, $p_{T}$, and for different radial decay positions of the particle. The efficiency is evaluated for particles which pass a loose set of fiducial requirements at generator level.

The parameterised efficiency for particles to pass full track selections in the metastable signal region, as function of the particle’s $\beta$, in different bins of transverse momentum, $p_{T}$, and for different radial decay positions of the particle. The efficiency is evaluated for particles which pass a loose set of fiducial requirements at generator level.

The parameterised efficiency for particles to pass full track selections in the metastable signal region, as function of the particle’s $\beta$, in different bins of transverse momentum, $p_{T}$, and for different radial decay positions of the particle. The efficiency is evaluated for particles which pass a loose set of fiducial requirements at generator level.

The parameterised efficiency for particles to pass full track selections in the metastable signal region, as function of the particle’s $\beta$, in different bins of transverse momentum, $p_{T}$. The stable efficiency is evaluated for samples which do not decay within the detector. The efficiency is evaluated for particles which pass a loose set of fiducial requirements at generator level.

Expected and observed upper limits on $\tan\beta$ as a function of $m_{H^{+}}$ in the hMSSM scenario of the MSSM. Limits are shown for $\tan\beta$ values in the range of 0.5-60, where predictions are available from both scenarios. The bands surrounding the expected limits show the 68% and 95% confidence intervals. The limits are based on the combination of the $\ell+$jets and $\ell\ell$ final states. The production cross-section of $t\bar{t}H$ and $tH$, as well as the branching ratios of the $H$, are fixed to their SM values at each point in the plane. Uncertainties on the predicted $H^{+}$ cross-sections or branching ratios are not considered.

Expected and observed lower limits on $\tan\beta$ as a function of $m_{H^{+}}$ in the hMSSM scenario of the MSSM. Limits are shown for $\tan\beta$ values in the range of 0.5-60, where predictions are available from both scenarios. The bands surrounding the expected limits show the 68% and 95% confidence intervals. The limits are based on the combination of the $\ell+$jets and $\ell\ell$ final states. The production cross-section of $t\bar{t}H$ and $tH$, as well as the branching ratios of the $H$, are fixed to their SM values at each point in the plane. Uncertainties on the predicted $H^{+}$ cross-sections or branching ratios are not considered.

Expected and observed 95% upper limits on the vector-like top quark pair-production signal strength (i.e. the ratio sigma_exclusion/sigma_VLQ) as a function of the branching ratio for a vector-like quark mass of 900 GeV, asumming that the vector-like quarks exclusively decay to SM particles (and third generation quarks). If interpreting these results in models with decays to non-Standard-Model particles, one must check that the additional decays will not end up in any control regions of the relevant analyses.

Expected and observed 95% upper limits on the vector-like top quark pair-production signal strength (i.e. the ratio sigma_exclusion/sigma_VLQ) as a function of the branching ratio for a vector-like quark mass of 950 GeV, asumming that the vector-like quarks exclusively decay to SM particles (and third generation quarks). If interpreting these results in models with decays to non-Standard-Model particles, one must check that the additional decays will not end up in any control regions of the relevant analyses.

Expected and observed 95% upper limits on the vector-like top quark pair-production signal strength (i.e. the ratio sigma_exclusion/sigma_VLQ) as a function of the branching ratio for a vector-like quark mass of 1000 GeV, asumming that the vector-like quarks exclusively decay to SM particles (and third generation quarks). If interpreting these results in models with decays to non-Standard-Model particles, one must check that the additional decays will not end up in any control regions of the relevant analyses.

Expected and observed 95% upper limits on the vector-like top quark pair-production signal strength (i.e. the ratio sigma_exclusion/sigma_VLQ) as a function of the branching ratio for a vector-like quark mass of 1050 GeV, asumming that the vector-like quarks exclusively decay to SM particles (and third generation quarks). If interpreting these results in models with decays to non-Standard-Model particles, one must check that the additional decays will not end up in any control regions of the relevant analyses.

Expected and observed 95% upper limits on the vector-like top quark pair-production signal strength (i.e. the ratio sigma_exclusion/sigma_VLQ) as a function of the branching ratio for a vector-like quark mass of 1100 GeV, asumming that the vector-like quarks exclusively decay to SM particles (and third generation quarks). If interpreting these results in models with decays to non-Standard-Model particles, one must check that the additional decays will not end up in any control regions of the relevant analyses.

Expected and observed 95% upper limits on the vector-like top quark pair-production signal strength (i.e. the ratio sigma_exclusion/sigma_VLQ) as a function of the branching ratio for a vector-like quark mass of 1150 GeV, asumming that the vector-like quarks exclusively decay to SM particles (and third generation quarks). If interpreting these results in models with decays to non-Standard-Model particles, one must check that the additional decays will not end up in any control regions of the relevant analyses.

Expected and observed 95% upper limits on the vector-like top quark pair-production signal strength (i.e. the ratio sigma_exclusion/sigma_VLQ) as a function of the branching ratio for a vector-like quark mass of 1200 GeV, asumming that the vector-like quarks exclusively decay to SM particles (and third generation quarks). If interpreting these results in models with decays to non-Standard-Model particles, one must check that the additional decays will not end up in any control regions of the relevant analyses.

Expected and observed 95% upper limits on the vector-like top quark pair-production signal strength (i.e. the ratio sigma_exclusion/sigma_VLQ) as a function of the branching ratio for a vector-like quark mass of 1300 GeV, asumming that the vector-like quarks exclusively decay to SM particles (and third generation quarks). If interpreting these results in models with decays to non-Standard-Model particles, one must check that the additional decays will not end up in any control regions of the relevant analyses.

Expected and observed 95% upper limits on the vector-like top quark pair-production signal strength (i.e. the ratio sigma_exclusion/sigma_VLQ) as a function of the branching ratio for a vector-like quark mass of 1400 GeV, asumming that the vector-like quarks exclusively decay to SM particles (and third generation quarks). If interpreting these results in models with decays to non-Standard-Model particles, one must check that the additional decays will not end up in any control regions of the relevant analyses.

Expected and observed 95% upper limits on the vector-like bottom quark pair-production signal strength (i.e. the ratio sigma_exclusion/sigma_VLQ) as a function of the branching ratio for a vector-like quark mass of 800 GeV, asumming that the vector-like quarks exclusively decay to SM particles (and third generation quarks). If interpreting these results in models with decays to non-Standard-Model particles, one must check that the additional decays will not end up in any control regions of the relevant analyses.

Expected and observed 95% upper limits on the vector-like bottom quark pair-production signal strength (i.e. the ratio sigma_exclusion/sigma_VLQ) as a function of the branching ratio for a vector-like quark mass of 900 GeV, asumming that the vector-like quarks exclusively decay to SM particles (and third generation quarks). If interpreting these results in models with decays to non-Standard-Model particles, one must check that the additional decays will not end up in any control regions of the relevant analyses.

Expected and observed 95% upper limits on the vector-like bottom quark pair-production signal strength (i.e. the ratio sigma_exclusion/sigma_VLQ) as a function of the branching ratio for a vector-like quark mass of 950 GeV, asumming that the vector-like quarks exclusively decay to SM particles (and third generation quarks). If interpreting these results in models with decays to non-Standard-Model particles, one must check that the additional decays will not end up in any control regions of the relevant analyses.

Expected and observed 95% upper limits on the vector-like bottom quark pair-production signal strength (i.e. the ratio sigma_exclusion/sigma_VLQ) as a function of the branching ratio for a vector-like quark mass of 1000 GeV, asumming that the vector-like quarks exclusively decay to SM particles (and third generation quarks). If interpreting these results in models with decays to non-Standard-Model particles, one must check that the additional decays will not end up in any control regions of the relevant analyses.

Expected and observed 95% upper limits on the vector-like bottom quark pair-production signal strength (i.e. the ratio sigma_exclusion/sigma_VLQ) as a function of the branching ratio for a vector-like quark mass of 1050 GeV, asumming that the vector-like quarks exclusively decay to SM particles (and third generation quarks). If interpreting these results in models with decays to non-Standard-Model particles, one must check that the additional decays will not end up in any control regions of the relevant analyses.

Expected and observed 95% upper limits on the vector-like bottom quark pair-production signal strength (i.e. the ratio sigma_exclusion/sigma_VLQ) as a function of the branching ratio for a vector-like quark mass of 1100 GeV, asumming that the vector-like quarks exclusively decay to SM particles (and third generation quarks). If interpreting these results in models with decays to non-Standard-Model particles, one must check that the additional decays will not end up in any control regions of the relevant analyses.

Expected and observed 95% upper limits on the vector-like bottom quark pair-production signal strength (i.e. the ratio sigma_exclusion/sigma_VLQ) as a function of the branching ratio for a vector-like quark mass of 1150 GeV, asumming that the vector-like quarks exclusively decay to SM particles (and third generation quarks). If interpreting these results in models with decays to non-Standard-Model particles, one must check that the additional decays will not end up in any control regions of the relevant analyses.

Expected and observed 95% upper limits on the vector-like bottom quark pair-production signal strength (i.e. the ratio sigma_exclusion/sigma_VLQ) as a function of the branching ratio for a vector-like quark mass of 1200 GeV, asumming that the vector-like quarks exclusively decay to SM particles (and third generation quarks). If interpreting these results in models with decays to non-Standard-Model particles, one must check that the additional decays will not end up in any control regions of the relevant analyses.

Expected and observed 95% upper limits on the vector-like bottom quark pair-production signal strength (i.e. the ratio sigma_exclusion/sigma_VLQ) as a function of the branching ratio for a vector-like quark mass of 1300 GeV, asumming that the vector-like quarks exclusively decay to SM particles (and third generation quarks). If interpreting these results in models with decays to non-Standard-Model particles, one must check that the additional decays will not end up in any control regions of the relevant analyses.

Expected and observed 95% upper limits on the vector-like bottom quark pair-production signal strength (i.e. the ratio sigma_exclusion/sigma_VLQ) as a function of the branching ratio for a vector-like quark mass of 1400 GeV, asumming that the vector-like quarks exclusively decay to SM particles (and third generation quarks). If interpreting these results in models with decays to non-Standard-Model particles, one must check that the additional decays will not end up in any control regions of the relevant analyses.