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.

Dijet mass distribution for the b-tagged category. Data, estimated background and uncertainties are shown. Events are collected using the combined trigger and contain a $E_T^{\gamma} > 95$ GeV photon and two $p_T^{jet} > 65$ GeV jets.

Upper limits on Gaussian-shape contributions to the dijet mass distributions from the flavour-inclusive category and masses below 450 GeV, for which the single-photon trigger was used.

Upper limits on Gaussian-shape contributions to the dijet mass distributions from the flavour-inclusive category and masses above 450 GeV, for which the combined trigger was used.

Upper limits on Gaussian-shape contributions to the dijet mass distributions from the b-tagged category and masses below 450 GeV, for which the single-photon trigger was used.

Upper limits on Gaussian-shape contributions to the dijet mass distributions from the b-tagged category and masses above 450 GeV, for which the combined trigger was used.

Kinematic acceptance values predicted for the $Z'$ model as a function of mass $m_{Z'}$ for the flavour-inclusive category using the single-photon trigger.

Kinematic acceptance values predicted for the $Z'$ model as a function of mass $m_{Z'}$ for the flavour-inclusive category using the combined trigger.

Kinematic acceptance values predicted for the $Z'$ model as a function of mass $m_{Z'}$ for the b-tagged category using the single-photon trigger.

Kinematic acceptance values predicted for the $Z'$ model as a function of mass $m_{Z'}$ for the b-tagged category using the combined trigger.

Reconstruction efficiency for $Z'$ model, flavour inclusive category, single-photon trigger.

Reconstruction efficiency for $Z'$ model, flavour inclusive category, combined trigger.

Reconstruction efficiency for $Z'$ model, b-tagged category, single-photon trigger.

Reconstruction efficiency for $Z'$ model, b-tagged category, combined trigger.

Sequential impact of each requirement on the number of events passing the selection for the high-$E_T$ analysis.

Sequential impact of each requirement on the number of events passing the selection for the low-$E_T$ analysis.

Application of the modified ABCD method to the final high-$E_T$ and low-$E_T$ selections.

The extrapolated signal efficiencies as a function of proper decay length of the $s$ for several simulated samples in the low-$E_T$ selections.

The extrapolated signal efficiencies as a function of proper decay length of the $s$ for several simulated samples in the high-$E_T$ selections.

The observed limits, expected limits and $\pm 1 \sigma$ and $\pm 2 \sigma$ bands for a model with $m_{\phi} = 125 ~\mathrm{GeV}$ and $m_{s} = 25 ~\mathrm{GeV}$.

The observed limits, expected limits and $\pm 1 \sigma$ and $\pm 2 \sigma$ bands for a model with $m_{\phi} = 600 ~\mathrm{GeV}$ and $m_{s} = 150 ~\mathrm{GeV}$.

Combined limits for the CalRatio and MS analyses, for a model with $m_{\phi} = 125 ~\mathrm{GeV}$ and $m_{s} = 25 ~\mathrm{GeV}$.

Combined limits for the CalRatio and MS analyses, for a model with $m_{\phi} = 600 ~\mathrm{GeV}$ and $m_{s} = 150 ~\mathrm{GeV}$.

The observed limits, expected limits and $\pm 1 \sigma$ and $\pm 2 \sigma$ bands for a model with $m_{\phi} = 125 ~\mathrm{GeV}$ and $m_{s} = 5 ~\mathrm{GeV}$.

The observed limits, expected limits and $\pm 1 \sigma$ and $\pm 2 \sigma$ bands for a model with $m_{\phi} = 125 ~\mathrm{GeV}$ and $m_{s} = 8 ~\mathrm{GeV}$.

The observed limits, expected limits and $\pm 1 \sigma$ and $\pm 2 \sigma$ bands for a model with $m_{\phi} = 125 ~\mathrm{GeV}$ and $m_{s} = 15 ~\mathrm{GeV}$.

The observed limits, expected limits and $\pm 1 \sigma$ and $\pm 2 \sigma$ bands for a model with $m_{\phi} = 125 ~\mathrm{GeV}$ and $m_{s} = 40 ~\mathrm{GeV}$.

The observed limits, expected limits and $\pm 1 \sigma$ and $\pm 2 \sigma$ bands for a model with $m_{\phi} = 125 ~\mathrm{GeV}$ and $m_{s} = 55 ~\mathrm{GeV}$.

The observed limits, expected limits and $\pm 1 \sigma$ and $\pm 2 \sigma$ bands for a model with $m_{\phi} = 200 ~\mathrm{GeV}$ and $m_{s} = 8 ~\mathrm{GeV}$.

The observed limits, expected limits and $\pm 1 \sigma$ and $\pm 2 \sigma$ bands for a model with $m_{\phi} = 200 ~\mathrm{GeV}$ and $m_{s} = 25 ~\mathrm{GeV}$.

The observed limits, expected limits and $\pm 1 \sigma$ and $\pm 2 \sigma$ bands for a model with $m_{\phi} = 200 ~\mathrm{GeV}$ and $m_{s} = 50 ~\mathrm{GeV}$.

The observed limits, expected limits and $\pm 1 \sigma$ and $\pm 2 \sigma$ bands for a model with $m_{\phi} = 400 ~\mathrm{GeV}$ and $m_{s} = 50 ~\mathrm{GeV}$.

The observed limits, expected limits and $\pm 1 \sigma$ and $\pm 2 \sigma$ bands for a model with $m_{\phi} = 400 ~\mathrm{GeV}$ and $m_{s} = 100 ~\mathrm{GeV}$.

The observed limits, expected limits and $\pm 1 \sigma$ and $\pm 2 \sigma$ bands for a model with $m_{\phi} = 600 ~\mathrm{GeV}$ and $m_{s} = 50 ~\mathrm{GeV}$.

The observed limits, expected limits and $\pm 1 \sigma$ and $\pm 2 \sigma$ bands for a model with $m_{\phi} = 1000 ~\mathrm{GeV}$ and $m_{s} = 50 ~\mathrm{GeV}$.

The observed limits, expected limits and $\pm 1 \sigma$ and $\pm 2 \sigma$ bands for a model with $m_{\phi} = 1000 ~\mathrm{GeV}$ and $m_{s} = 150 ~\mathrm{GeV}$.

The observed limits, expected limits and $\pm 1 \sigma$ and $\pm 2 \sigma$ bands for a model with $m_{\phi} = 1000 ~\mathrm{GeV}$ and $m_{s} = 400 ~\mathrm{GeV}$.

Combined limits for the CalRatio and MS analyses, for a model with $m_{\phi} = 125 ~\mathrm{GeV}$ and $m_{s} = 5 ~\mathrm{GeV}$.

Combined limits for the CalRatio and MS analyses, for a model with $m_{\phi} = 125 ~\mathrm{GeV}$ and $m_{s} = 8 ~\mathrm{GeV}$.

Combined limits for the CalRatio and MS analyses, for a model with $m_{\phi} = 125 ~\mathrm{GeV}$ and $m_{s} = 15 ~\mathrm{GeV}$.

Combined limits for the CalRatio and MS analyses, for a model with $m_{\phi} = 125 ~\mathrm{GeV}$ and $m_{s} = 40 ~\mathrm{GeV}$.

Combined limits for the CalRatio and MS analyses, for a model with $m_{\phi} = 200 ~\mathrm{GeV}$ and $m_{s} = 8 ~\mathrm{GeV}$.

Combined limits for the CalRatio and MS analyses, for a model with $m_{\phi} = 200 ~\mathrm{GeV}$ and $m_{s} = 25 ~\mathrm{GeV}$.

Combined limits for the CalRatio and MS analyses, for a model with $m_{\phi} = 200 ~\mathrm{GeV}$ and $m_{s} = 50 ~\mathrm{GeV}$.

Combined limits for the CalRatio and MS analyses, for a model with $m_{\phi} = 400 ~\mathrm{GeV}$ and $m_{s} = 50 ~\mathrm{GeV}$.

Combined limits for the CalRatio and MS analyses, for a model with $m_{\phi} = 400 ~\mathrm{GeV}$ and $m_{s} = 100 ~\mathrm{GeV}$.

Combined limits for the CalRatio and MS analyses, for a model with $m_{\phi} = 600 ~\mathrm{GeV}$ and $m_{s} = 50 ~\mathrm{GeV}$.

Combined limits for the CalRatio and MS analyses, for a model with $m_{\phi} = 1000 ~\mathrm{GeV}$ and $m_{s} = 50 ~\mathrm{GeV}$.

Combined limits for the CalRatio and MS analyses, for a model with $m_{\phi} = 1000 ~\mathrm{GeV}$ and $m_{s} = 150 ~\mathrm{GeV}$.

Combined limits for the CalRatio and MS analyses, for a model with $m_{\phi} = 1000 ~\mathrm{GeV}$ and $m_{s} = 400 ~\mathrm{GeV}$.

Measured fiducial cross section times leptonic branching ratio for W- production in the W- -> mu- nu final state.

Measured fiducial cross section times leptonic branching ratio for Z/gamma* production in the Z/gamma* -> e+ e- final state.

Measured fiducial cross section times leptonic branching ratio for Z/gamma* production in the Z/gamma* -> mu+ mu- final state.

Measured total cross section times leptonic branching ratio for W+ production in the W+ -> e+ nu final state.

Measured total cross section times leptonic branching ratio for W+ production in the W+ -> mu+ nu final state.

Measured total cross section times leptonic branching ratio for W- production in the W- -> e- nu final state.

Measured total cross section times leptonic branching ratio for W- production in the W- -> mu- nu final state.

Measured total cross section times leptonic branching ratio for Z/gamma* production in the Z/gamma* -> e+ e- final state.

Measured total cross section times leptonic branching ratio for Z/gamma* production in the Z/gamma* -> mu+ mu- final state.

Combined fiducial cross-section measurements for W+ boson production in the W+ -> l+ nu (l = e, mu) final state.

Combined fiducial cross-section measurements for W- boson production in the W- -> l- nu (l = e, mu) final state.

Combined fiducial cross-section measurements for W boson production in the W -> l nu (l = e, mu) final state.

Combined fiducial cross-section measurements for Z/gamma* production in the Z/gamma* -> l- l+ (l = e, mu) final state.

Combined total cross-section measurements for W+ boson production in the W+ -> l+ nu (l = e, mu) final state.

Combined total cross-section measurements for W- boson production in the W- -> l- nu (l = e, mu) final state.

Combined total cross-section measurements for W boson production in the W -> l nu (l = e, mu) final state.

Combined total cross-section measurements for Z/gamma* production in the Z/gamma* -> l- l+ (l = e, mu) final state.

Measured fiducial cross-section ratio R_{W+-/Z} = sigma (W+/- -> l+/- nu/nubar) / sigma (Z/gamma^* -> l+ l-) where l = e, mu.

Measured fiducial cross-section ratio R_{W+/W-} = sigma (W+ -> l+ nu) / sigma (W- -> l- nubar) where l = e, mu.

Measured charge asymmetry in W-boson production A_{l} = ( sigma (W+ -> l+ nu) - sigma (W- -> l- nubar) ) / ( sigma (W+ -> l+ nu) + sigma (W- -> l- nubar) ) where l = e, mu.

The ratio of measured W+ cross-sections in the electron and muon decay channels R_{W+} = sigma (W+ -> e+ nu) / sigma (W+ -> mu+ nu)

The ratio of measured W- cross-sections in the electron and muon decay channels R_{W-} = sigma (W- -> e- nu) / sigma (W- -> mu- nu)

The ratio of measured W cross-sections in the electron and muon decay channels R_{W} = sigma (W -> e nu) / sigma (W -> mu nu)

The ratio of measured Z/gamma^* cross-sections in the electron and muon decay channels R_{Z/gamma^*} = sigma (Z/gamma^* -> e+ e-) / sigma (Z/gamma^* -> mu+ mu-)

Correlation coefficients among (W- -> l- nubar), (W+ -> l+ nu), (Z/gamma^* -> l+ l-) where (l = e, mu) excluding the common normalisation uncertainty due to the luminosity calibration.

The pseudorapidity ($|\eta|$) distribution for $K^{0}_{S}$ production inside $b$-jets for unfolded data to particle level, normalised to the total number of top pair dileptonic events and scaled to the bin width. The systematic uncertainties are, in order, due to; the MC modelling, the tracking ineficiencies, the jet energy scale (JES), the jet energy resolution (JER), out-of-fiducial events and the unfolding non-closure.

The multiplicity ($N_K$) distribution for $K^{0}_{S}$ production inside $b$-jets for unfolded data to particle level, including only visible decays ($K^0_S \rightarrow \pi^+ \pi^-$), normalised to the total number of top pair dileptonic events and scaled to the bin width. The systematic uncertainties are, in order, due to; the MC modelling, the tracking ineficiencies, the jet energy scale (JES), the jet energy resolution (JER), out-of-fiducial events and the unfolding non-closure.

The transverse momentum ($p_{T}$) distribution for $K^{0}_{S}$ production inside non $b$-jets for unfolded data to particle level, normalised to the total number of top pair dileptonic events and scaled to the bin width. The systematic uncertainties are, in order, due to; the MC modelling, the tracking ineficiencies, the jet energy scale (JES), the jet energy resolution (JER), out-of-fiducial events and the unfolding non-closure.

The energy fraction ($x_{K}$) distribution for $K^{0}_{S}$ production inside non $b$-jets for unfolded data to particle level, normalised to the total number of top pair dileptonic events and scaled to the bin width. The systematic uncertainties are, in order, due to; the MC modelling, the tracking ineficiencies, the jet energy scale (JES), the jet energy resolution (JER), out-of-fiducial events and the unfolding non-closure.

The energy distribution for $K^{0}_{S}$ production inside non $b$-jets for unfolded data to particle level, normalised to the total number of top pair dileptonic events and scaled to the bin width. The systematic uncertainties are, in order, due to; the MC modelling, the tracking ineficiencies, the jet energy scale (JES), the jet energy resolution (JER), out-of-fiducial events and the unfolding non-closure.

The pseudorapidity ($|\eta|$) distribution for $K^{0}_{S}$ production inside non $b$-jets for unfolded data to particle level, normalised to the total number of top pair dileptonic events and scaled to the bin width. The systematic uncertainties are, in order, due to; the MC modelling, the tracking ineficiencies, the jet energy scale (JES), the jet energy resolution (JER), out-of-fiducial events and the unfolding non-closure.

The multiplicity ($N_K$) distribution for $K^{0}_{S}$ production inside non $b$-jets for unfolded data to particle level, including only visible decays ($K^0_S \rightarrow \pi^+ \pi^-$), normalised to the total number of top pair dileptonic events and scaled to the bin width. The systematic uncertainties are, in order, due to; the MC modelling, the tracking ineficiencies, the jet energy scale (JES), the jet energy resolution (JER), out-of-fiducial events and the unfolding non-closure.

The transverse momentum ($p_{T}$) distribution for $K^{0}_{S}$ production not associated with jets for unfolded data to particle level, normalised to the total number of top pair dileptonic events and scaled to the bin width. The systematic uncertainties are, in order, due to; the MC modelling, the tracking ineficiencies, the jet energy scale (JES), the jet energy resolution (JER), the pile-up, out-of-fiducial events and the unfolding non-closure.

The energy distribution for $K^{0}_{S}$ production not associated with jets for unfolded data to particle level, normalised to the total number of top pair dileptonic events and scaled to the bin width. The systematic uncertainties are, in order, due to; the MC modelling, the tracking ineficiencies, the jet energy scale (JES), the jet energy resolution (JER), the pile-up, out-of-fiducial events and the unfolding non-closure.

The pseudorapidity ($|\eta|$) distribution for $K^{0}_{S}$ production not associated with jets for unfolded data to particle level, normalised to the total number of top pair dileptonic events and scaled to the bin width. The systematic uncertainties are, in order, due to; the MC modelling, the tracking ineficiencies, the jet energy scale (JES), the jet energy resolution (JER), the pile-up, out-of-fiducial events and the unfolding non-closure.

The multiplicity ($N_K$) distribution for $K^{0}_{S}$ production not associated with jets for unfolded data to particle level, including only visible decays ($K^0_S \rightarrow \pi^+ \pi^-$), normalised to the total number of top pair dileptonic events and scaled to the bin width. The systematic uncertainties are, in order, due to; the MC modelling, the tracking ineficiencies, the jet energy scale (JES), the jet energy resolution (JER), the pile-up, out-of-fiducial events and the unfolding non-closure.

The transverse momentum ($p_{T}$) distribution for the total $K^{0}_{S}$ production for unfolded data to particle level, normalised to the total number of top pair dileptonic events and scaled to the bin width. The systematic uncertainties are, in order, due to; the MC modelling, the tracking ineficiencies, the jet energy scale (JES), the jet energy resolution (JER), the pile-up, out-of-fiducial events and the unfolding non-closure.

The energy distribution for the total $K^{0}_{S}$ production for unfolded data to particle level, normalised to the total number of top pair dileptonic events and scaled to the bin width. The systematic uncertainties are, in order, due to; the MC modelling, the tracking ineficiencies, the jet energy scale (JES), the jet energy resolution (JER), the pile-up, out-of-fiducial events and the unfolding non-closure.

The pseudorapidity ($|\eta|$) distribution for the total $K^{0}_{S}$ production for unfolded data to particle level, normalised to the total number of top pair dileptonic events and scaled to the bin width. The systematic uncertainties are, in order, due to; the MC modelling, the tracking ineficiencies, the jet energy scale (JES), the jet energy resolution (JER), the pile-up, out-of-fiducial events and the unfolding non-closure.

The multiplicity ($N_K$) distribution for the total $K^{0}_{S}$ production for unfolded data to particle level, including only visible decays ($K^0_S \rightarrow \pi^+ \pi^-$), normalised to the total number of top pair dileptonic events and scaled to the bin width. The systematic uncertainties are, in order, due to; the MC modelling, the tracking ineficiencies, the jet energy scale (JES), the jet energy resolution (JER), the pile-up, out-of-fiducial events and the unfolding non-closure.

The transverse momentum ($p_{T}$) distribution for the total $\Lambda$ production for unfolded data to particle level, normalised to the total number of top pair dileptonic events and scaled to the bin width. The systematic uncertainties are, in order, due to; the MC modelling, the tracking ineficiencies, the jet energy scale (JES), the jet energy resolution (JER), the pile-up, out-of-fiducial events and the unfolding non-closure.

The energy distribution for the total $\Lambda$ production for unfolded data to particle level, normalised to the total number of top pair dileptonic events and scaled to the bin width. The systematic uncertainties are, in order, due to; the MC modelling, the tracking ineficiencies, the jet energy scale (JES), the jet energy resolution (JER), the pile-up, out-of-fiducial events and the unfolding non-closure.

The pseudorapidity ($|\eta|$) distribution for the total $\Lambda$ production for unfolded data to particle level, normalised to the total number of top pair dileptonic events and scaled to the bin width. The systematic uncertainties are, in order, due to; the MC modelling, the tracking ineficiencies, the jet energy scale (JES), the jet energy resolution (JER), the pile-up, out-of-fiducial events and the unfolding non-closure.

$K^0_S$ and $\Lambda$ unfolded (particle-level) average multiplicities per event ($\langle n_{K,\Lambda}\rangle$), including statistical and systematic uncertainties, for each class and for the total sample.

The $c_{k}$ for the 0.3-2 GeV $p_{T}$ range as a function of event multiplicity $N_{ch}$ in p+Pb collisions.

The $c_{k}$ for the 0.3-5 GeV $p_{T}$ range as a function of event multiplicity $N_{ch}$ in p+Pb collisions.

The $c_{k}$ for the 0.5-2 GeV $p_{T}$ range as a function of event multiplicity $N_{ch}$ in p+Pb collisions.

The $Var(v_{2}^{2})_{dyn}$ for Pb+Pb collisions for the $p_T$ 0.5-2 GeV interval as a function $N_{ch}$.

The $Var(v_{2}^{2})_{dyn}$ for Pb+Pb collisions for the $p_T$ 0.5-5 GeV interval as a function $N_{ch}$.

The $Var(v_{2}^{2})_{dyn}$ for Pb+Pb collisions for the $p_T$ 1-2 GeV interval as a function $N_{ch}$.

The $Var(v_{3}^{2})_{dyn}$ for Pb+Pb collisions for the $p_T$ 0.5-2 GeV interval as a function $N_{ch}$.

The $Var(v_{3}^{2})_{dyn}$ for Pb+Pb collisions for the $p_T$ 0.5-5 GeV interval as a function $N_{ch}$.

The $Var(v_{3}^{2})_{dyn}$ for Pb+Pb collisions for the $p_T$ 1-2 GeV interval as a function $N_{ch}$.

The $Var(v_{4}^{2})_{dyn}$ for Pb+Pb collisions for the $p_T$ 0.5-2 GeV interval as a function $N_{ch}$.

The $Var(v_{4}^{2})_{dyn}$ for Pb+Pb collisions for the $p_T$ 0.5-5 GeV interval as a function $N_{ch}$.

The $Var(v_{4}^{2})_{dyn}$ for Pb+Pb collisions for the $p_T$ 1-2 GeV interval as a function $N_{ch}$.

The $Var(v_{2}^{2})_{dyn}$ for p+Pb collisions for the $p_T$ 0.3-2 GeV interval as a function $N_{ch}$.

The $Var(v_{2}^{2})_{dyn}$ for p+Pb collisions for the $p_T$ 0.3-5 GeV interval as a function $N_{ch}$.

The $Var(v_{2}^{2})_{dyn}$ for p+Pb collisions for the $p_T$ 0.5-2 GeV interval as a function $N_{ch}$.

The $cov(v_{2}^{2},[p_{T}])$ for Pb+Pb collisions for the $p_T$ 0.5-2 GeV interval as a function $N_{ch}$.

The $cov(v_{2}^{2},[p_{T}])$ for Pb+Pb collisions for the $p_T$ 0.5-5 GeV interval as a function $N_{ch}$.

The $cov(v_{2}^{2},[p_{T}])$ for Pb+Pb collisions for the $p_T$ 1-2 GeV interval as a function $N_{ch}$.

The $cov(v_{3}^{2},[p_{T}])$ for Pb+Pb collisions for the $p_T$ 0.5-2 GeV interval as a function $N_{ch}$.

The $cov(v_{3}^{2},[p_{T}])$ for Pb+Pb collisions for the $p_T$ 0.5-5 GeV interval as a function $N_{ch}$.

The $cov(v_{3}^{2},[p_{T}])$ for Pb+Pb collisions for the $p_T$ 1-2 GeV interval as a function $N_{ch}$.

The $cov(v_{4}^{2},[p_{T}])$ for Pb+Pb collisions for the $p_T$ 0.5-2 GeV interval as a function $N_{ch}$.

The $cov(v_{4}^{2},[p_{T}])$ for Pb+Pb collisions for the $p_T$ 0.5-5 GeV interval as a function $N_{ch}$.

The $cov(v_{4}^{2},[p_{T}])$ for Pb+Pb collisions for the $p_T$ 1-2 GeV interval as a function $N_{ch}$.

The $cov(v_{2}^{2},[p_{T}])$ for p+Pb collisions for the $p_T$ 0.3-2 GeV interval as a function $N_{ch}$.

The $cov(v_{2}^{2},[p_{T}])$ for p+Pb collisions for the $p_T$ 0.3-5 GeV interval as a function $N_{ch}$.

The $cov(v_{2}^{2},[p_{T}])$ for p+Pb collisions for the $p_T$ 0.5-2 GeV interval as a function $N_{ch}$.

The $\rho(v_{2}^{2},[p_{T}])$ for Pb+Pb collisions for the $p_T$ 0.5-2 GeV interval as a function $N_{ch}$.

The $\rho(v_{2}^{2},[p_{T}])$ for Pb+Pb collisions for the $p_T$ 0.5-5 GeV interval as a function $N_{ch}$.

The $\rho(v_{2}^{2},[p_{T}])$ for Pb+Pb collisions for the $p_T$ 1-2 GeV interval as a function $N_{ch}$.

The $\rho(v_{3}^{2},[p_{T}])$ for Pb+Pb collisions for the $p_T$ 0.5-2 GeV interval as a function $N_{ch}$.

The $\rho(v_{3}^{2},[p_{T}])$ for Pb+Pb collisions for the $p_T$ 0.5-5 GeV interval as a function $N_{ch}$.

The $\rho(v_{3}^{2},[p_{T}])$ for Pb+Pb collisions for the $p_T$ 1-2 GeV interval as a function $N_{ch}$.

The $\rho(v_{4}^{2},[p_{T}])$ for Pb+Pb collisions for the $p_T$ 0.5-2 GeV interval as a function $N_{ch}$.

The $\rho(v_{4}^{2},[p_{T}])$ for Pb+Pb collisions for the $p_T$ 0.5-5 GeV interval as a function $N_{ch}$.

The $\rho(v_{4}^{2},[p_{T}])$ for Pb+Pb collisions for the $p_T$ 1-2 GeV interval as a function $N_{ch}$.

The $\rho(v_{2}^{2},[p_{T}])$ for p+Pb collisions for the $p_T$ 0.3-2 GeV interval as a function $N_{ch}$.

The $\rho(v_{2}^{2},[p_{T}])$ for p+Pb collisions for the $p_T$ 0.3-5 GeV interval as a function $N_{ch}$.

The $\rho(v_{2}^{2},[p_{T}])$ for p+Pb collisions for the $p_T$ 0.5-2 GeV interval as a function $N_{ch}$.

The $\rho(v_{2}^{2},[p_{T}])$ for Pb+Pb collisions for the $p_T$ 0.5-2 GeV interval as a function $N_{part}$.

The $\rho(v_{2}^{2},[p_{T}])$ for Pb+Pb collisions for the $p_T$ 0.5-5 GeV interval as a function $N_{part}$.

The $\rho(v_{2}^{2},[p_{T}])$ for Pb+Pb collisions for the $p_T$ 1-2 GeV interval as a function $N_{part}$.

The $\rho(v_{3}^{2},[p_{T}])$ for Pb+Pb collisions for the $p_T$ 0.5-2 GeV interval as a function $N_{part}$.

The $\rho(v_{3}^{2},[p_{T}])$ for Pb+Pb collisions for the $p_T$ 0.5-5 GeV interval as a function $N_{part}$.

The $\rho(v_{3}^{2},[p_{T}])$ for Pb+Pb collisions for the $p_T$ 1-2 GeV interval as a function $N_{part}$.

The $\rho(v_{4}^{2},[p_{T}])$ for Pb+Pb collisions for the $p_T$ 0.5-2 GeV interval as a function $N_{part}$.

The $\rho(v_{4}^{2},[p_{T}])$ for Pb+Pb collisions for the $p_T$ 0.5-5 GeV interval as a function $N_{part}$.

The $\rho(v_{4}^{2},[p_{T}])$ for Pb+Pb collisions for the $p_T$ 1-2 GeV interval as a function $N_{part}$.

Displaced HNL search observed 95% confidence level exclusion contour in $|U_{\mu}|^2$ as a function of HNL mass (LNV case).

Prompt HNL search observed and expected 95% confidence level exclusion upper limits in $|U_{e}|^2$ as a function of HNL mass.

Prompt HNL search observed and expected 95% confidence level exclusion upper limits in $|U_{\mu}|^2$ as a function of HNL mass.

Displaced HNL search expected 95% confidence level exclusion contour in $|U_{\mu}|^2$ as a function of HNL mass (LNC case).

Displaced HNL search expected 95% confidence level exclusion contour in $|U_{\mu}|^2$ as a function of HNL mass (LNV case).

Upper limits at 95% CL on the cross section times branching fraction for the process $H \to 2\gamma_d + X$ with $m_H$ = 800 GeV in the hadron-hadron final state.

Upper limits at 95% CL on the cross section times branching fraction for the process $H \to 2\gamma_d + X$ with $m_H$ = 800 GeV in the muon-hadron final state.

Upper limits at 95% CL on the cross section times branching fraction for the process $H \to 4\gamma_d + X$ with $m_H$ = 800 GeV in the muon-muon final state.

Upper limits at 95% CL on the cross section times branching fraction for the process $H \to 4\gamma_d + X$ with $m_H$ = 800 GeV in the muon-hadron final state.

Upper limits at 95% CL on the cross section times branching fraction for the process $H \to 4\gamma_d + X$ with $m_H$ = 800 GeV in the hadron-hadron final state.

Extrapolated signal efficiencies as a function of proper decay length of the dark photon for the $H \to 4\gamma_d + X$ process with $m_H$ = 125 GeV in the muon-muon final state.

Extrapolated signal efficiencies as a function of proper decay length of the dark photon for the $H \to 2\gamma_d + X$ process with $m_H$ = 125 GeV in the muon-muon final state.

Extrapolated signal efficiencies as a function of proper decay length of the dark photon for the $H \to 2\gamma_d + X$ process with $m_H$ = 800 GeV in the muon-muon final state.

Extrapolated signal efficiencies as a function of proper decay length of the dark photon for the $H \to 4\gamma_d + X$ process with $m_H$ = 800 GeV in the muon-muon final state.

Extrapolated signal efficiencies as a function of proper decay length of the dark photon for the $H \to 4\gamma_d + X$ process with $m_H$ = 125 GeV in the muon-hadron final state.

Extrapolated signal efficiencies as a function of proper decay length of the dark photon for the $H \to 2\gamma_d + X$ process with $m_H$ = 125 GeV in the muon-hadron final state.

Extrapolated signal efficiencies as a function of proper decay length of the dark photon for the $H \to 2\gamma_d + X$ process with $m_H$ = 800 GeV in the muon-hadron final state.

Extrapolated signal efficiencies as a function of proper decay length of the dark photon for the $H \to 4\gamma_d + X$ process with $m_H$ = 800 GeV in the muon-hadron final state.

Extrapolated signal efficiencies as a function of proper decay length of the dark photon for the $H \to 2\gamma_d + X$ process with $m_H$ = 125 GeV in the hadron-hadron final state.

Extrapolated signal efficiencies as a function of proper decay length of the dark photon for the $H \to 2\gamma_d + X$ process with $m_H$ = 800 GeV in the hadron-hadron final state.

Extrapolated signal efficiencies as a function of proper decay length of the dark photon for the $H \to 4\gamma_d + X$ process with $m_H$ = 800 GeV in the hadron-hadron final state.

The measured fiducial cross section vs $E_{\mathrm{T}}^\gamma$. The central values are provided along with the statistical and systematic uncertainties together with the sign information. The statistical and "Uncor" uncertainty should be treated as uncorrelated bin-to-bin, while the rest are correlated between bins, and they are written as signed NP variations. The parton-to-particle correction factor $C_{theory}$ is the ratio of the cross-section predicted by Sherpa LO samples at particle level within the fiducial phase-space region defined in Table 4 to the predicted cross-section at parton level within the same fiducial region but with the smooth-cone isolation prescription defined above replacing the particle-level photon isolation criterion, and with Born-level leptons in place of dressed leptons. This correction should be applied on fixed order parton-level calculations. The systematic uncertainty is evaluated from a comparison with the correction factor obtained using events generated with Sherpa 2.2.2 at NLO. The uncertainty is defined as Max(stat error, systematic difference between Sherpa LO and Sherpa 2.2.2 NLO), and cannot be considered correlated bin-to-bin. In the case that the calculations are valid for dressed leptons, a modified correction factor excluding the Born-to-dressed lepton correction should be applied instead. This correction only takes into account the particle-level isolation criteria, and is provided separately here. The Sherpa 2.2.8 NLO cross-sections given below include a small contribution from EW $Z\gamma jj$ production.

The measured fiducial cross section vs $|\eta^\gamma|$. The central values are provided along with the statistical and systematic uncertainties together with the sign information. The statistical and "Uncor" uncertainty should be treated as uncorrelated bin-to-bin, while the rest are correlated between bins, and they are written as signed NP variations. The parton-to-particle correction factor $C_{theory}$ is the ratio of the cross-section predicted by Sherpa LO samples at particle level within the fiducial phase-space region defined in Table 4 to the predicted cross-section at parton level within the same fiducial region but with the smooth-cone isolation prescription defined above replacing the particle-level photon isolation criterion, and with Born-level leptons in place of dressed leptons. This correction should be applied on fixed order parton-level calculations. The systematic uncertainty is evaluated from a comparison with the correction factor obtained using events generated with SHERPA 2.2.2 at NLO. In the case that the calculations are valid for dressed leptons, a modified correction factor excluding the Born-to-dressed lepton correction should be applied instead. This correction only takes into account the particle-level isolation criteria, and is provided separately here. The Sherpa 2.2.8 NLO cross-sections given below include a small contribution from EW $Z\gamma jj$ production.

The measured fiducial cross section vs $|\eta^\gamma|$. The central values are provided along with the statistical and systematic uncertainties together with the sign information. The statistical and "Uncor" uncertainty should be treated as uncorrelated bin-to-bin, while the rest are correlated between bins, and they are written as signed NP variations. The parton-to-particle correction factor $C_{theory}$ is the ratio of the cross-section predicted by Sherpa LO samples at particle level within the fiducial phase-space region defined in Table 4 to the predicted cross-section at parton level within the same fiducial region but with the smooth-cone isolation prescription defined above replacing the particle-level photon isolation criterion, and with Born-level leptons in place of dressed leptons. This correction should be applied on fixed order parton-level calculations. The systematic uncertainty is evaluated from a comparison with the correction factor obtained using events generated with Sherpa 2.2.2 at NLO. The uncertainty is defined as Max(stat error, systematic difference between Sherpa LO and Sherpa 2.2.2 NLO), and cannot be considered correlated bin-to-bin. In the case that the calculations are valid for dressed leptons, a modified correction factor excluding the Born-to-dressed lepton correction should be applied instead. This correction only takes into account the particle-level isolation criteria, and is provided separately here. The Sherpa 2.2.8 NLO cross-sections given below include a small contribution from EW $Z\gamma jj$ production.

The measured fiducial cross section vs $m(\ell\ell\gamma)$. The central values are provided along with the statistical and systematic uncertainties together with the sign information. The statistical and "Uncor" uncertainty should be treated as uncorrelated bin-to-bin, while the rest are correlated between bins, and they are written as signed NP variations. The parton-to-particle correction factor $C_{theory}$ is the ratio of the cross-section predicted by Sherpa LO samples at particle level within the fiducial phase-space region defined in Table 4 to the predicted cross-section at parton level within the same fiducial region but with the smooth-cone isolation prescription defined above replacing the particle-level photon isolation criterion, and with Born-level leptons in place of dressed leptons. This correction should be applied on fixed order parton-level calculations. The systematic uncertainty is evaluated from a comparison with the correction factor obtained using events generated with SHERPA 2.2.2 at NLO. In the case that the calculations are valid for dressed leptons, a modified correction factor excluding the Born-to-dressed lepton correction should be applied instead. This correction only takes into account the particle-level isolation criteria, and is provided separately here. The Sherpa 2.2.8 NLO cross-sections given below include a small contribution from EW $Z\gamma jj$ production.

The measured fiducial cross section vs $m(\ell\ell\gamma)$. The central values are provided along with the statistical and systematic uncertainties together with the sign information. The statistical and "Uncor" uncertainty should be treated as uncorrelated bin-to-bin, while the rest are correlated between bins, and they are written as signed NP variations. The parton-to-particle correction factor $C_{theory}$ is the ratio of the cross-section predicted by Sherpa LO samples at particle level within the fiducial phase-space region defined in Table 4 to the predicted cross-section at parton level within the same fiducial region but with the smooth-cone isolation prescription defined above replacing the particle-level photon isolation criterion, and with Born-level leptons in place of dressed leptons. This correction should be applied on fixed order parton-level calculations. The systematic uncertainty is evaluated from a comparison with the correction factor obtained using events generated with Sherpa 2.2.2 at NLO. The uncertainty is defined as Max(stat error, systematic difference between Sherpa LO and Sherpa 2.2.2 NLO), and cannot be considered correlated bin-to-bin. In the case that the calculations are valid for dressed leptons, a modified correction factor excluding the Born-to-dressed lepton correction should be applied instead. This correction only takes into account the particle-level isolation criteria, and is provided separately here. The Sherpa 2.2.8 NLO cross-sections given below include a small contribution from EW $Z\gamma jj$ production.

The measured fiducial cross section vs $p_{\mathrm{T}}^{\ell\ell\gamma}$. The central values are provided along with the statistical and systematic uncertainties together with the sign information. The statistical and "Uncor" uncertainty should be treated as uncorrelated bin-to-bin, while the rest are correlated between bins, and they are written as signed NP variations. The parton-to-particle correction factor $C_{theory}$ is the ratio of the cross-section predicted by Sherpa LO samples at particle level within the fiducial phase-space region defined in Table 4 to the predicted cross-section at parton level within the same fiducial region but with the smooth-cone isolation prescription defined above replacing the particle-level photon isolation criterion, and with Born-level leptons in place of dressed leptons. This correction should be applied on fixed order parton-level calculations. The systematic uncertainty is evaluated from a comparison with the correction factor obtained using events generated with SHERPA 2.2.2 at NLO. In the case that the calculations are valid for dressed leptons, a modified correction factor excluding the Born-to-dressed lepton correction should be applied instead. This correction only takes into account the particle-level isolation criteria, and is provided separately here. The Sherpa 2.2.8 NLO cross-sections given below include a small contribution from EW $Z\gamma jj$ production.

The measured fiducial cross section vs $p_{\mathrm{T}}^{\ell\ell\gamma}$. The central values are provided along with the statistical and systematic uncertainties together with the sign information. The statistical and "Uncor" uncertainty should be treated as uncorrelated bin-to-bin, while the rest are correlated between bins, and they are written as signed NP variations. The parton-to-particle correction factor $C_{theory}$ is the ratio of the cross-section predicted by Sherpa LO samples at particle level within the fiducial phase-space region defined in Table 4 to the predicted cross-section at parton level within the same fiducial region but with the smooth-cone isolation prescription defined above replacing the particle-level photon isolation criterion, and with Born-level leptons in place of dressed leptons. This correction should be applied on fixed order parton-level calculations. The systematic uncertainty is evaluated from a comparison with the correction factor obtained using events generated with Sherpa 2.2.2 at NLO. The uncertainty is defined as Max(stat error, systematic difference between Sherpa LO and Sherpa 2.2.2 NLO), and cannot be considered correlated bin-to-bin. In the case that the calculations are valid for dressed leptons, a modified correction factor excluding the Born-to-dressed lepton correction should be applied instead. This correction only takes into account the particle-level isolation criteria, and is provided separately here. The Sherpa 2.2.8 NLO cross-sections given below include a small contribution from EW $Z\gamma jj$ production.

The measured fiducial cross section vs $\Delta\phi(ll,\gamma)$. The central values are provided along with the statistical and systematic uncertainties together with the sign information. The statistical and "Uncor" uncertainty should be treated as uncorrelated bin-to-bin, while the rest are correlated between bins, and they are written as signed NP variations. The parton-to-particle correction factor $C_{theory}$ is the ratio of the cross-section predicted by Sherpa LO samples at particle level within the fiducial phase-space region defined in Table 4 to the predicted cross-section at parton level within the same fiducial region but with the smooth-cone isolation prescription defined above replacing the particle-level photon isolation criterion, and with Born-level leptons in place of dressed leptons. This correction should be applied on fixed order parton-level calculations. The systematic uncertainty is evaluated from a comparison with the correction factor obtained using events generated with SHERPA 2.2.2 at NLO. In the case that the calculations are valid for dressed leptons, a modified correction factor excluding the Born-to-dressed lepton correction should be applied instead. This correction only takes into account the particle-level isolation criteria, and is provided separately here. The Sherpa 2.2.8 NLO cross-sections given below include a small contribution from EW $Z\gamma jj$ production.

The measured fiducial cross section vs $\Delta\phi(ll,\gamma)$. The central values are provided along with the statistical and systematic uncertainties together with the sign information. The statistical and "Uncor" uncertainty should be treated as uncorrelated bin-to-bin, while the rest are correlated between bins, and they are written as signed NP variations. The parton-to-particle correction factor $C_{theory}$ is the ratio of the cross-section predicted by Sherpa LO samples at particle level within the fiducial phase-space region defined in Table 4 to the predicted cross-section at parton level within the same fiducial region but with the smooth-cone isolation prescription defined above replacing the particle-level photon isolation criterion, and with Born-level leptons in place of dressed leptons. This correction should be applied on fixed order parton-level calculations. The systematic uncertainty is evaluated from a comparison with the correction factor obtained using events generated with Sherpa 2.2.2 at NLO. The uncertainty is defined as Max(stat error, systematic difference between Sherpa LO and Sherpa 2.2.2 NLO), and cannot be considered correlated bin-to-bin. In the case that the calculations are valid for dressed leptons, a modified correction factor excluding the Born-to-dressed lepton correction should be applied instead. This correction only takes into account the particle-level isolation criteria, and is provided separately here. The Sherpa 2.2.8 NLO cross-sections given below include a small contribution from EW $Z\gamma jj$ production.

The measured fiducial cross section vs $p_{\mathrm{T}}^{\ell\ell\gamma}/m(\ell\ell\gamma)$. The central values are provided along with the statistical and systematic uncertainties together with the sign information. The statistical and "Uncor" uncertainty should be treated as uncorrelated bin-to-bin, while the rest are correlated between bins, and they are written as signed NP variations. The parton-to-particle correction factor $C_{theory}$ is the ratio of the cross-section predicted by Sherpa LO samples at particle level within the fiducial phase-space region defined in Table 4 to the predicted cross-section at parton level within the same fiducial region but with the smooth-cone isolation prescription defined above replacing the particle-level photon isolation criterion, and with Born-level leptons in place of dressed leptons. This correction should be applied on fixed order parton-level calculations. The systematic uncertainty is evaluated from a comparison with the correction factor obtained using events generated with SHERPA 2.2.2 at NLO. In the case that the calculations are valid for dressed leptons, a modified correction factor excluding the Born-to-dressed lepton correction should be applied instead. This correction only takes into account the particle-level isolation criteria, and is provided separately here. The Sherpa 2.2.8 NLO cross-sections given below include a small contribution from EW $Z\gamma jj$ production.

The measured fiducial cross section vs $p_{\mathrm{T}}^{\ell\ell\gamma}/m(\ell\ell\gamma)$. The central values are provided along with the statistical and systematic uncertainties together with the sign information. The statistical and "Uncor" uncertainty should be treated as uncorrelated bin-to-bin, while the rest are correlated between bins, and they are written as signed NP variations. The parton-to-particle correction factor $C_{theory}$ is the ratio of the cross-section predicted by Sherpa LO samples at particle level within the fiducial phase-space region defined in Table 4 to the predicted cross-section at parton level within the same fiducial region but with the smooth-cone isolation prescription defined above replacing the particle-level photon isolation criterion, and with Born-level leptons in place of dressed leptons. This correction should be applied on fixed order parton-level calculations. The systematic uncertainty is evaluated from a comparison with the correction factor obtained using events generated with Sherpa 2.2.2 at NLO. The uncertainty is defined as Max(stat error, systematic difference between Sherpa LO and Sherpa 2.2.2 NLO), and cannot be considered correlated bin-to-bin. In the case that the calculations are valid for dressed leptons, a modified correction factor excluding the Born-to-dressed lepton correction should be applied instead. This correction only takes into account the particle-level isolation criteria, and is provided separately here. The Sherpa 2.2.8 NLO cross-sections given below include a small contribution from EW $Z\gamma jj$ production.