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.

The distributions of likelihood discriminant for data, simulated QCD multijet events, and simulated signal events. Data and simulated events are selected with the displaced-jet trigger. The offline $H_{T}$ is required to be larger than 400 GeV, and the jets are required to have $p_{T}>50\ \mathrm{GeV}$ and $|\eta|<2.0$. Three benchmark signal distributions are shown (dashed lines) for the jet-jet model with $m_{X}=300\ \mathrm{GeV}$ and varying lifetimes. For visualization each signal process is given a cross section, $\sigma$, such that $\sigma\ 35.9 \mathrm{fb}^{-1} = 1 \times 10^{6}$.

Numbers of predicted and observed background events for the nominal background method and the three cross-checks in the control region. Shown are the comparisons for likelihood discriminant thresholds of 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, and 0.9. The error bars represent the statistical uncertainties of the predictions and the observations. The data points at different likelihood discriminant thresholds are correlated, since the events passing higher likelihood discriminant thresholds also pass lower likelihood discriminant thresholds.

Numbers of predicted and observed background events for the nominal background method and the three cross-checks in the control region. Shown are the comparisons for likelihood discriminant thresholds of 0.95, 0.96, 0.97, 0.98, 0.99, and 0.9993. The error bars represent the statistical uncertainties of the predictions and the observations. The data points at different likelihood discriminant thresholds are correlated, since the events passing higher likelihood discriminant thresholds also pass lower likelihood discriminant thresholds.

The expected and observed $95\%$ $\text{CL}$ upper limits on the pair production cross section of the long-lived particle X, assuming a $100\%$ branching fraction for X to decay to a quark-antiquark pair, shown at different masses and different proper decay lengths for the jet-jet model.

the expected and observed $95\%$ $\text{CL}$ upper limits on the pair production cross section of the long-lived gluino, assuming a $100\%$ branching fraction for $\widetilde{\mathrm{g}}\to\mathrm{g}\widetilde{\mathrm{G}}$ decays.

the expected and observed $95\%$ $\text{CL}$ limits for the long-lived gluino model in the mass-lifetime plane, assuming a $100\%$ branching fraction for $\widetilde{\mathrm{g}}\to\mathrm{g}\widetilde{\mathrm{G}}$ decays, based on the NLO+NLL calculation of the gluino pair production cross section at $\sqrt{s}=13\ \mathrm{TeV}$.

the expected and observed $95\%$ $\text{CL}$ upper limits on the pair production cross section of the long-lived gluino, assuming a $100\%$ branching fraction for $\widetilde{\mathrm{g}}\to\mathrm{tbs}$ decays.

the expected and observed $95\%$ $\text{CL}$ limits for the long-lived gluino model in the mass-lifetime plane, assuming a $100\%$ branching fraction for $\widetilde{\mathrm{g}}\to\mathrm{tbs}$ decays, based on the NLO+NLL calculation of the gluino pair production cross section at $\sqrt{s}=13\ \mathrm{TeV}$.

the expected and observed $95\%$ $\text{CL}$ upper limits on the pair production cross section of the long-lived top squark, assuming a $100\%$ branching fraction for $\widetilde{\mathrm{t}}\to\mathrm{b}\ell$ decays.

the expected and observed $95\%$ $\text{CL}$ limits for the long-lived top squark model in the mass-lifetime plane, assuming a $100\%$ branching fraction for $\widetilde{\mathrm{t}}\to\mathrm{b}\ell$ decays, based on the NLO+NLL calculation of the top squark pair production cross section at $\sqrt{s}=13\ \mathrm{TeV}$.

the expected and observed $95\%$ $\text{CL}$ upper limits on the the pair production cross section of the long-lived top squark, assuming a $100\%$ branching fraction for $\widetilde{\mathrm{t}}\to\mathrm{\overline{d}\overline{d}}$ decays.

the expected and observed $95\%$ $\text{CL}$ limits for the long-lived top squark model in the mass-lifetime plane, assuming a $100\%$ branching fraction for $\widetilde{\mathrm{t}}\to\mathrm{\overline{d}\overline{d}}$ decays, based on an NLO+NLL calculation of the top squark pair production cross section at $\sqrt{s}=13\ \mathrm{TeV}$.

The likelihood ratio for vertex track multiplicity

The likelihood ratio for vertex $L_{xy}$ significance

The likelihood ratio for cluster RMS, the point where cluster RMS equals $-1.0$ represents the case where there is no cluster being reconstructed for the dijet candidate

trigger particle momentum dependence of observables RMS for wide component in p-p collisions at 7 TeV with 0.2<xlong<0.4.

trigger particle momentum dependence of observables RMS for wide component in p-p collisions at 7 TeV with 0.4<xlong<0.6.

trigger particle momentum dependence of observables RMS for wide component in p-p collisions at 7 TeV with 0.6<xlong<1.0.

trigger particle momentum dependence of observables RMS for narrow component in p-Pb collisions at 5.02 TeV with 0.2<xlong<0.4.

trigger particle momentum dependence of observables RMS for narrow component in p-Pb collisions at 5.02 TeV with 0.4<xlong<0.6.

trigger particle momentum dependence of observables RMS for narrow component in p-Pb collisions at 5.02 TeV with 0.6<xlong<1.0.

trigger particle momentum dependence of observables RMS for wide component in p-Pb collisions at 5.02 TeV with 0.2<xlong<0.4.

trigger particle momentum dependence of observables RMS for wide component in p-Pb collisions at 5.02 TeV with 0.4<xlong<0.6.

trigger particle momentum dependence of observables RMS for wide component in p-Pb collisions at 5.02 TeV with 0.6<xlong<1.0.

trigger particle momentum dependence of observables per-trigger yield for narrow component in p-p collisions at 7 TeV with 0.2<xlong<0.4.

trigger particle momentum dependence of observables per-trigger yield for narrow component in p-p collisions at 7 TeV with 0.4<xlong<0.6.

trigger particle momentum dependence of observables per-trigger yield for narrow component in p-p collisions at 7 TeV with 0.6<xlong<1.0.

trigger particle momentum dependence of observables per-trigger yield for wide component in p-p collisions at 7 TeV with 0.2<xlong<0.4.

trigger particle momentum dependence of observables per-trigger yield for wide component in p-p collisions at 7 TeV with 0.4<xlong<0.6.

trigger particle momentum dependence of observables per-trigger yield for wide component in p-p collisions at 7 TeV with 0.6<xlong<1.0.

trigger particle momentum dependence of observables per-trigger yield for narrow component in p-Pb collisions at 5.02 TeV with 0.2<xlong<0.4.

trigger particle momentum dependence of observables per-trigger yield for narrow component in p-Pb collisions at 5.02 TeV with 0.4<xlong<0.6.

trigger particle momentum dependence of observables per-trigger yield for narrow component in p-Pb collisions at 5.02 TeV with 0.6<xlong<1.0.

trigger particle momentum dependence of observables per-trigger yield for wide component in p-Pb collisions at 5.02 TeV with 0.2<xlong<0.4.

trigger particle momentum dependence of observables per-trigger yield for wide component in p-Pb collisions at 5.02 TeV with 0.4<xlong<0.6.

trigger particle momentum dependence of observables per-trigger yield for wide component in p-Pb collisions at 5.02 TeV with 0.6<xlong<1.0.

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

The J/$\psi$ $v_3$ coefficient as a function of $p_{\rm T}$ in 0-10% centrality interval in Pb-Pb collisions at $\sqrt{s_{\rm NN}}$ = 5.02 TeV.

The J/$\psi$ $v_3$ coefficient as a function of $p_{\rm T}$ in 10-30% centrality interval in Pb-Pb collisions at $\sqrt{s_{\rm NN}}$ = 5.02 TeV.

The J/$\psi$ $v_3$ coefficient as a function of $p_{\rm T}$ in 30-50% centrality interval in Pb-Pb collisions at $\sqrt{s_{\rm NN}}$ = 5.02 TeV.

The J/$\psi$ $v_3$ coefficient as a function of $p_{\rm T}$ in 0-50% centrality interval in Pb-Pb collisions at $\sqrt{s_{\rm NN}}$ = 5.02 TeV.

The J/$\psi$ $v_3/v_2$ ratio as a function of $p_{\rm T}$ in 5-40% centrality interval in Pb-Pb collisions at $\sqrt{s_{\rm NN}}$ = 5.02 TeV.

The J/$\psi$ $v_3/v_2$ ratio as a function of $p_{\rm T}$ in 10-50% centrality interval in Pb-Pb collisions at $\sqrt{s_{\rm NN}}$ = 5.02 TeV.

The J/$\psi$ $v_2$ as a function of $p_{\rm T}$ for unbiased events (no event-shape selection) in the 5-40% centrality interval in Pb--Pb collisions at $\sqrt{s_{\rm NN}}$ = 5.02 TeV.

The J/$\psi$ $v_2$ as a function of $p_{\rm T}$ for lowest $q_2^{\rm V0A}$ event-shape class in the 5-40% centrality interval in Pb--Pb collisions at $\sqrt{s_{\rm NN}}$ = 5.02 TeV. The systematic uncertainties are the same as the ones given in Table 10 for the unbiased event sample.

The J/$\psi$ $v_2$ as a function of $p_{\rm T}$ for highest $q_2^{\rm V0A}$ event-shape class in the 5-40% centrality interval in Pb--Pb collisions at $\sqrt{s_{\rm NN}}$ = 5.02 TeV. The systematic uncertainties are the same as the ones given in Table 10 for the unbiased event sample.

The measured normalized differential cross section as a function of the photon $|\eta|$ in the single lepton channel. The uncertainty is decomposed into five components which are the signal modelling uncertainty, the experimental uncertainty, the ttbar modelling uncertainty, the other background estimation uncertainty, and the data statistical uncertainty.

The measured normalized differential cross section as a function of the $\Delta R$ between the photon and the lepton in the single lepton channel. The uncertainty is decomposed into five components which are the signal modelling uncertainty, the experimental uncertainty, the ttbar modelling uncertainty, the other background estimation uncertainty, and the data statistical uncertainty.

The measured normalized differential cross section as a function of the photon pT in the dilepton channel. The uncertainty is decomposed into five components which are the signal modelling uncertainty, the experimental uncertainty, the ttbar modelling uncertainty, the other background estimation uncertainty, and the data statistical uncertainty.

The measured normalized differential cross section as a function of the photon $|\eta|$ in the dilepton channel. The uncertainty is decomposed into five components which are the signal modelling uncertainty, the experimental uncertainty, the ttbar modelling uncertainty, the other background estimation uncertainty, and the data statistical uncertainty.

The measured normalized differential cross section as a function of minimum $\Delta R) between the photon and the leptons in the dilepton channel. The uncertainty is decomposed into five components which are the signal modelling uncertainty, the experimental uncertainty, the ttbar modelling uncertainty, the other background estimation uncertainty, and the data statistical uncertainty.

The measured normalized differential cross section as a function of $|\Delta\eta|$ between the two leptons in the dilepton channel. The uncertainty is decomposed into five components which are the signal modelling uncertainty, the experimental uncertainty, the ttbar modelling uncertainty, the other background estimation uncertainty, and the data statistical uncertainty.

The measured normalized differential cross section as a function of $\Delta\phi$ between the two leptons in the dilepton channel. The uncertainty is decomposed into five components which are the signal modelling uncertainty, the experimental uncertainty, the ttbar modelling uncertainty, the other background estimation uncertainty, and the data statistical uncertainty.

The total correlation matrix of the measured normalized differential cross section as a function of the photon pT in the single lepton channel. The individual systematic uncertainties are symmetrized before deriving the correlation matrix.

The total correlation matrix of the measured normalized differential cross section as a function of the photon $|\eta|$ in the single lepton channel. The individual systematic uncertainties are symmetrized before deriving the correlation matrix.

The total correlation matrix of the measured normalized differential cross section as a function of the $\Delta R$ between the photon and the lepton in the single lepton channel. The individual systematic uncertainties are symmetrized before deriving the correlation matrix.

The total correlation matrix of the measured normalized differential cross section as a function of the photon pT in the dilepton channel. The individual systematic uncertainties are symmetrized before deriving the correlation matrix.

The total correlation matrix of the measured normalized differential cross section as a function of the photon $|\eta|$ in the dilepton channel. The individual systematic uncertainties are symmetrized before deriving the correlation matrix.

The total correlation matrix of the measured normalized differential cross section as a function of the minimum $\Delta R$ between the photon and the leptons in the dilepton channel. The individual systematic uncertainties are symmetrized before deriving the correlation matrix.

The total correlation matrix of the measured normalized differential cross section as a function of the $|\Delta\eta|$ between the two leptons in the dilepton channel. The individual systematic uncertainties are symmetrized before deriving the correlation matrix.

The total correlation matrix of the measured normalized differential cross section as a function of the $\Delta\phi$ between the two leptons in the dilepton channel. The individual systematic uncertainties are symmetrized before deriving the correlation matrix.

The statistical correlation matrix of all the measured normalized differential cross sections in the single lepton channel.

The statistical correlation matrix of all the measured normalized differential cross sections in the dilepton channel.

Pseudorapidity density of charged particles in p–Pb NSD collisions at 8.16 TeV for 5-10% centrality class and CL1 estimator.

Pseudorapidity density of charged particles in p–Pb NSD collisions at 8.16 TeV for 10-20% centrality class and CL1 estimator.

Pseudorapidity density of charged particles in p–Pb NSD collisions at 8.16 TeV for 20-40% centrality class and CL1 estimator.

Pseudorapidity density of charged particles in p–Pb NSD collisions at 8.16 TeV for 40-60% centrality class and CL1 estimator.

Pseudorapidity density of charged particles in p–Pb NSD collisions at 8.16 TeV for 60-80% centrality class and CL1 estimator.

Pseudorapidity density of charged particles in p–Pb NSD collisions at 8.16 TeV for 80-100% centrality class and CL1 estimator.

Pseudorapidity density of charged particles in p–Pb NSD collisions at 8.16 TeV for 0-5% centrality class and V0A estimator.

Pseudorapidity density of charged particles in p–Pb NSD collisions at 8.16 TeV for 5-10% centrality class and V0A estimator.

Pseudorapidity density of charged particles in p–Pb NSD collisions at 8.16 TeV for 10-20% centrality class and V0A estimator.

Pseudorapidity density of charged particles in p–Pb NSD collisions at 8.16 TeV for 20-40% centrality class and V0A estimator.

Pseudorapidity density of charged particles in p–Pb NSD collisions at 8.16 TeV for 40-60% centrality class and V0A estimator.

Pseudorapidity density of charged particles in p–Pb NSD collisions at 8.16 TeV for 60-80% centrality class and V0A estimator.

Pseudorapidity density of charged particles in p–Pb NSD collisions at 8.16 TeV for 80-100% centrality class and V0A estimator.

Pseudorapidity density of charged particles in p–Pb NSD collisions at 8.16 TeV for 0-5% centrality class and ZNA estimator.

Pseudorapidity density of charged particles in p–Pb NSD collisions at 8.16 TeV for 5-10% centrality class and ZNA estimator.

Pseudorapidity density of charged particles in p–Pb NSD collisions at 8.16 TeV for 10-20% centrality class and ZNA estimator.

Pseudorapidity density of charged particles in p–Pb NSD collisions at 8.16 TeV for 20-40% centrality class and ZNA estimator.

Pseudorapidity density of charged particles in p–Pb NSD collisions at 8.16 TeV for 40-60% centrality class and ZNA estimator.

Pseudorapidity density of charged particles in p–Pb NSD collisions at 8.16 TeV for 60-80% centrality class and ZNA estimator.

Pseudorapidity density of charged particles in p–Pb NSD collisions at 8.16 TeV for 80-100% centrality class and ZNA estimator.

Average pseudorapidity density of charged particles in p–Pb NSD collisions as a function of the number of participants for CL1 estimator.

Average pseudorapidity density of charged particles in p–Pb NSD collisions as a function of the number of participants for V0A estimator.

Average pseudorapidity density of charged particles in p–Pb NSD collisions as a function of the number of participants for ZNAmult estimator.

Average pseudorapidity density of charged particles in p–Pb NSD collisions as a function of the number of participants for ZNAPb estimator.

Average pseudorapidity density of charged particles in p–Pb NSD collisions for 5 participant quarks as a function of the number of participants for CL1 estimator.

Average pseudorapidity density of charged particles in p–Pb NSD collisions for 5 participant quarks as a function of the number of participants for V0A estimator.