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.

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.

Differential cross section at W= 1.720 GeV

Differential cross section at W= 1.750 GeV

Differential cross section at W= 1.775 GeV

Differential cross section at W= 1.795 GeV

Differential cross section at W= 1.815 GeV

Differential cross section at W= 1.835 GeV

Differential cross section at W= 1.855 GeV

Differential cross section at W= 1.630 GeV

Differential cross section at W= 1.660 GeV

Differential cross section at W= 1.690 GeV

Differential cross section at W= 1.720 GeV

Differential cross section at W= 1.750 GeV

Differential cross section at W= 1.775 GeV

Differential cross section at W= 1.795 GeV

Differential cross section at W= 1.815 GeV

Differential cross section at W= 1.835 GeV

Differential cross section at W= 1.855 GeV

Differential cross section at W= 1.690 GeV

Differential cross section at W= 1.720 GeV

Differential cross section at W= 1.750 GeV

Differential cross section at W= 1.775 GeV

Differential cross section at W= 1.795 GeV

Differential cross section at W= 1.815 GeV

Differential cross section at W= 1.835 GeV

Differential cross section at W= 1.855 GeV

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

2$\tau$ HighMass SR eff.

2$\tau$ multibin SR eff.

2$\tau$ GMSB SR eff.

1$\tau$ Compressed SR eff.

1$\tau$ MediumMass SR eff.

2$\tau$ Compressed SR eff.

2$\tau$ HighMass SR eff.

2$\tau$ multibin SR eff.

2$\tau$ GMSB SR eff.

1$\tau$ Compressed SR acceptance.

1$\tau$ MediumMass SR acceptance.

2$\tau$ Compressed SR acceptance.

2$\tau$ HighMass SR acceptance.

2$\tau$ multibin SR acceptance.

2$\tau$ GMSB SR acceptance.

1$\tau$ Compressed SR acceptance.

1$\tau$ MediumMass SR acceptance.

2$\tau$ Compressed SR acceptance.

2$\tau$ HighMass SR acceptance.

2$\tau$ multibin SR acceptance.

2$\tau$ GMSB SR acceptance.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Distribution of the reconstructed invariant mass of the $W^\prime$ boson candidate in the 4-jet 2-tag VR$_{t\bar{t}}$ electron validation region. Background templates are fit to data in each VR using the same statistical method as for the signal region except that the normalizations of $t\bar{t}$ and $W$+jets backgrounds are constrained to the post-fit rates obtained in the signal region. Uncertainties include all the systematic and statistical uncertainties.

Distribution of the reconstructed invariant mass of the $W^\prime$ boson candidate in the 4-jet 2-tag VR$_{t\bar{t}}$ muon validation region. Background templates are fit to data in each VR using the same statistical method as for the signal region except that the normalizations of $t\bar{t}$ and $W$+jets backgrounds are constrained to the post-fit rates obtained in the signal region. Uncertainties include all the systematic and statistical uncertainties.

Post-fit distribution of the reconstructed mass of the $W^\prime_{\textrm{R}}$ boson candidate in the 2-jet 1-tag signal region, for electron channel. Uncertainties include all the systematic and statistical uncertainties.

Post-fit distribution of the reconstructed mass of the $W^\prime_{\textrm{R}}$ boson candidate in the 2-jet 1-tag signal region, for muon channel. Uncertainties include all the systematic and statistical uncertainties.

Post-fit distribution of the reconstructed mass of the $W^\prime_{\textrm{R}}$ boson candidate in the 2-jet 2-tag signal region, for electron channel. Uncertainties include all the systematic and statistical uncertainties.

Post-fit distribution of the reconstructed mass of the $W^\prime_{\textrm{R}}$ boson candidate in the 2-jet 2-tag signal region, for muon channel. Uncertainties include all the systematic and statistical uncertainties.

Post-fit distribution of the reconstructed mass of the $W^\prime_{\textrm{R}}$ boson candidate in the 3-jet 1-tag signal region, for electron channel. Uncertainties include all the systematic and statistical uncertainties.

Post-fit distribution of the reconstructed mass of the $W^\prime_{\textrm{R}}$ boson candidate in the 3-jet 1-tag signal region, for muon channel. Uncertainties include all the systematic and statistical uncertainties.

Post-fit distribution of the reconstructed mass of the $W^\prime_{\textrm{R}}$ boson candidate in the 3-jet 2-tag signal region, for electron channel. Uncertainties include all the systematic and statistical uncertainties.

Post-fit distribution of the reconstructed mass of the $W^\prime_{\textrm{R}}$ boson candidate in the 3-jet 2-tag signal region, for muon channel. Uncertainties include all the systematic and statistical uncertainties.

Upper limits at the 95% CL on the $W^\prime_{\textrm{R}}$ production cross section times branching fraction as a function of resonance mass, assuming $g^\prime/g=1$.

Observed and expected 95% CL limit on the ratio $g^\prime/g$, as a function of resonance mass, for right-handed $W^\prime$ coupling. The impact of the increased $W^\prime_{\textrm{R}}$ width for coupling values of $g'/g>1$ on the acceptance and on kinematical distributions is taken into account.

Observed and expected 95% CL upper limit on the $W^\prime_{\textrm{R}}$ production cross section times branching fraction as a function of resonance mass for the combination of semileptonic and hadronic [Phys. Lett. B 781 (2018) 327] $W^\prime \rightarrow t\bar{b}$ searches, assuming $g^\prime/g=1$. The hadronic search covers a mass range between 1.0 and 5.0TeV.

The systematic uncertainty on the unfolded distribution as a function of minimax-mbl, broken down by components.

The covariance matrix for the unfolded, normalized data in bins of minimax-mbl shown in Figure 2. Redundant entries are suppressed.

Leading lepton transverse momentum distribution for events passing the signal selection in bins of minimax-mbl. The data here are not unfolded.

Sub-leading lepton transverse momentum distribution for events passing the signal selection in bins of minimax-mbl. The data here are not unfolded.

Leading lepton pseudorapidity distribution for events passing the signal selection in bins of minimax-mbl. The data here are not unfolded.

Sub-leading lepton pseudorapidity distribution for events passing the signal selection in bins of minimax-mbl. The data here are not unfolded.

Leading b-jet transverse momentum distribution for events passing the signal selection in bins of minimax-mbl. The data here are not unfolded.

Sub-leading b-jet transverse momentum distribution for events passing the signal selection in bins of minimax-mbl. The data here are not unfolded.

Leading b-jet pseudorapidity distribution for events passing the signal selection in bins of minimax-mbl. The data here are not unfolded.

Sub-leading b-jet pseudorapidity distribution for events passing the signal selection in bins of minimax-mbl. The data here are not unfolded.

The detector-level minimax-m(bl) distribution for events entering the Z+jets control region.

The detector-level minimax-m(bl) distribution for events entering the same-sign lepton control region.

Dijet mass spectra after the background only fit with the background prediction in the high-mass region with two b-tags.

Dijet mass spectra after the background only fit with the background prediction in the low-mass region with two b-tags.

The online b-tagging efficiency with respect to the offline b-tagging efficiency as a function of pT. The b-tagging online and offline working points correspond to an efficiency of 60% and 70%, respectively.

Observed and expected 95% credibility-level upper limits on the cross-section for the b* model in the high-mass region with inclusive b-jet selection.

Observed and expected 95% credibility-level upper limits on the cross-section times branching ratio for the SSM and leptophobic Z' models in the low- and high-mass region with two b-tags selection.

Observed and expected 95% credibility-level upper limits on the cross-section for DM Z' models in the low-mass region with two b-tags selection. The Z' is expected to decay to all five quark flavors other than the top quark and the mediator to SM quark coupling (gSM) equal to 0.1 is assumed.

Observed and expected 95% credibility-level upper limits on the cross-section times branching ratio for DM Z'->bb models in the high-mass region with two b-tags selection. The Z' is expected to decay to bb only and the mediator to SM quark coupling (gSM) equal to 0.25 is assumed.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances with intrinsic width smaller than the detector resolution. The width of the Gaussian reconstructed shape is dominated by the dijet mass resolution. The table shows the limits obtained from the high-mass inclusive one b-tag selection.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances with intrinsic width smaller than the detector resolution. The width of the Gaussian reconstructed shape is dominated by the dijet mass resolution. The table shows the limits obtained from the combined low- and high-mass two b-tags selection.

The mass distributions for the inclusive one b-tagged selection and two b-tagged selection using an integrated luminosity of 36.1 $fb^{-1}$. The inclusive one b-tagged Pythia8 MC distribution is normalized to the inclusive one b-tagged data. The two b-tagged Pythia8 MC distribution is normalized to the two b-tagged data. The systematic uncertainty band is dominated by the b-tagging scale factor and the b-jet energy scale.

Signal acceptance times efficiency for inclusive 1 b-tag and 2 b-tag categories as a function of the simulated b* and the Z' masses.

Signal acceptance times efficiency for 2 b-tag categories as a function of the simulated Z' masses.

The flavor composition of the simulated dijet background as a function of dijet mass before tagging. The fraction of the six combinations of the b-jet , c-jet and light-flavor jet are shown. All offline selections are applied.

The flavor composition of the simulated dijet background as a function of dijet mass with inclusive one b-tag. The fraction of the six combinations of the b-jet , c-jet and light-flavor jet are shown. All offline selections are applied.

The flavor composition of the simulated dijet background as a function of dijet mass with two b-tags. The fraction of the six combinations of the b-jet , c-jet and light-flavor jet are shown. All offline selections are applied.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances exhibiting a generic Gaussian shape at particle level. The table shows the limits obtained from the inclusive b-jet selection. The limits corresponding to Gaussian-shaped resonances with width of Γ(X)/m(X) = 3%.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances exhibiting a generic Gaussian shape at particle level. The table shows the limits obtained from the inclusive b-jet selection. The limits corresponding to Gaussian-shaped resonances with width of Γ(X)/m(X) = 7%.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances exhibiting a generic Gaussian shape at particle level. The table shows the limits obtained from the inclusive b-jet selection. The limits corresponding to Gaussian-shaped resonances with width of Γ(X)/m(X) = 10%.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances exhibiting a generic Gaussian shape at particle level. The table shows the limits obtained from the inclusive b-jet selection. The limits corresponding to Gaussian-shaped resonances with width of Γ(X)/m(X) = 15%.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances exhibiting a generic Gaussian shape at particle level. The table shows the limits obtained from the combined low- and high-mass two b-tags selection. The limits corresponding to Gaussian-shaped resonances with width of Γ(X)/m(X) = 3%.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances exhibiting a generic Gaussian shape at particle level. The table shows the limits obtained from the combined low- and high-mass two b-tags selection. The limits corresponding to Gaussian-shaped resonances with width of Γ(X)/m(X) = 7%.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances exhibiting a generic Gaussian shape at particle level. The table shows the limits obtained from the combined low- and high-mass two b-tags selection. The limits corresponding to Gaussian-shaped resonances with width of Γ(X)/m(X) = 10%.

Observed and expected 95% credibility-level upper limits on cross section times acceptance times branching ratio of X --> bb, including kinematic acceptance and b-tagging efficiencies, for resonances exhibiting a generic Gaussian shape at particle level. The table shows the limits obtained from the combined low- and high-mass two b-tags selection. The limits corresponding to Gaussian-shaped resonances with width of Γ(X)/m(X) = 15%.

The observed and expected 95% CL upper limits on the production cross section times branching ratio for SM non-resonant Higgs pair production.