Expected and observed 95\% \CL exclusion limits on the HH production cross section for the different channels and their combination for each benchmark model.

Expected and observed 95\% \CL exclusion limits on the HH production cross section for the bbVV channel and for each benchmark model.

Expected and observed 95\% \CL exclusion limits on the HH production cross section for the bbbb channel and for each benchmark model.

Expected and observed 95\% \CL exclusion limits on the HH production cross section for the bbtt channel and for each benchmark model.

Expected and observed 95\% \CL exclusion limits on the HH production cross section for the bbgg channel and for each benchmark model.

Expected and observed 95\% \CL exclusion limits on the HH production cross section for the combination of all channels and for each benchmark model.

Expected and observed 95\% \CL exclusion limits on the production of a narrow, spin two resonance (X) decaying into a pair of Higgs bosons.

Expected and observed exclusion limits (95% CL, in the asymptotic approximation) on the product of the production cross section and branching fraction into two photons for an additional SM-like Higgs boson, for the VBF plus VH processes, from the analysis of the 8 TeV data. The inner and outer bands indicate the regions containing the distribution of limits located within $pm 1 and 2 $sigma, respectively, of the expectation under the background-only hypothesis.

Expected and observed exclusion limits (95% CL, in the asymptotic approximation) on the product of the production cross section and branching fraction into two photons for an additional SM-like Higgs boson, for the ggH plus ttH processes, from the analysis of the 13 TeV data. The inner and outer bands indicate the regions containing the distribution of limits located within $pm 1 and 2 $sigma, respectively, of the expectation under the background-only hypothesis.

Expected and observed exclusion limits (95% CL, in the asymptotic approximation) on the product of the production cross section and branching fraction into two photons for an additional SM-like Higgs boson, for the VBF plus VH processes, from the analysis of the 13 (bottom) TeV data. The inner and outer bands indicate the regions containing the distribution of limits located within $pm 1 and 2 $sigma, respectively, of the expectation under the background-only hypothesis.

Expected and observed exclusion limits (95% CL, in the asymptotic approximation) on the product of the production cross section and branching fraction into two photons for an additional Higgs boson, relative to the expected SM-like value, from the analysis of the 8 and 13 TeV data. The inner and outer bands indicate the regions containing the distribution of limits located within $pm 1 and 2 $sigma , respectively, of the expectation under the background-only hypothesis.

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

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

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

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

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

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

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

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

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

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

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

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

The likelihood ratio for vertex track multiplicity

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

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

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.

Covariance matrix of the normalised differential cross section at parton level as a function of $p_{T}^{t}$.

Measured absolute differential cross section at particle level as a function of $p_{T}^{t}$.

Covariance matrix of the absolute differential cross section at particle level as a function of $p_{T}^{t}$.

Measured normalised differential cross section at particle level as a function of $p_{T}^{t}$.

Covariance matrix of the normalised differential cross section at particle level as a function of $p_{T}^{t}$.

Measured absolute differential cross section at parton level as a function of $p_{T}^{\bar{t}}$.

Covariance matrix of the absolute differential cross section at parton level as a function of $p_{T}^{\bar{t}}$.

Measured normalised differential cross section at parton level as a function of $p_{T}^{\bar{t}}$.

Covariance matrix of the normalised differential cross section at parton level as a function of $p_{T}^{\bar{t}}$.

Measured absolute differential cross section at particle level as a function of $p_{T}^{\bar{t}}$.

Covariance matrix of the absolute differential cross section at particle level as a function of $p_{T}^{\bar{t}}$.

Measured normalised differential cross section at particle level as a function of $p_{T}^{\bar{t}}$.

Covariance matrix of the normalised differential cross section at particle level as a function of $p_{T}^{\bar{t}}$.

Measured absolute differential cross section at parton level as a function of $p_{T}^{t}$ (leading).

Covariance matrix of the absolute differential cross section at parton level as a function of $p_{T}^{t}$ (leading).

Measured normalised differential cross section at parton level as a function of $p_{T}^{t}$ (leading).

Covariance matrix of the normalised differential cross section at parton level as a function of $p_{T}^{t}$ (leading).

Measured absolute differential cross section at particle level as a function of $p_{T}^{t}$ (leading).

Covariance matrix of the absolute differential cross section at particle level as a function of $p_{T}^{t}$ (leading).

Measured normalised differential cross section at particle level as a function of $p_{T}^{t}$ (leading).

Covariance matrix of the normalised differential cross section at particle level as a function of $p_{T}^{t}$ (leading).

Measured absolute differential cross section at parton level as a function of $p_{T}^{t}$ (trailing).

Covariance matrix of the absolute differential cross section at parton level as a function of $p_{T}^{t}$ (trailing).

Measured normalised differential cross section at parton level as a function of $p_{T}^{t}$ (trailing).

Covariance matrix of the normalised differential cross section at parton level as a function of $p_{T}^{t}$ (trailing).

Measured absolute differential cross section at particle level as a function of $p_{T}^{t}$ (trailing).

Covariance matrix of the absolute differential cross section at particle level as a function of $p_{T}^{t}$ (trailing).

Measured normalised differential cross section at particle level as a function of $p_{T}^{t}$ (trailing).

Covariance matrix of the normalised differential cross section at particle level as a function of $p_{T}^{t}$ (trailing).

Measured absolute differential cross section at parton level as a function of $p_{T}^{t}$($t\bar{t}$ RF).

Covariance matrix of the absolute differential cross section at parton level as a function of $p_{T}^{t}$($t\bar{t}$ RF).

Measured normalised differential cross section at parton level as a function of $p_{T}^{t}$($t\bar{t}$ RF).

Covariance matrix of the normalised differential cross section at parton level as a function of $p_{T}^{t}$($t\bar{t}$ RF).

Measured absolute differential cross section at particle level as a function of $p_{T}^{t}$($t\bar{t}$ RF).

Covariance matrix of the absolute differential cross section at particle level as a function of $p_{T}^{t}$($t\bar{t}$ RF).

Measured normalised differential cross section at particle level as a function of $p_{T}^{t}$($t\bar{t}$ RF).

Covariance matrix of the normalised differential cross section at particle level as a function of $p_{T}^{t}$($t\bar{t}$ RF).

Measured absolute differential cross section at parton level as a function of $y_{t}$.

Covariance matrix of the absolute differential cross section at parton level as a function of $y_{t}$.

Measured normalised differential cross section at parton level as a function of $y_{t}$.

Covariance matrix of the normalised differential cross section at parton level as a function of $y_{t}$.

Measured absolute differential cross section at particle level as a function of $y_{t}$.

Covariance matrix of the absolute differential cross section at particle level as a function of $y_{t}$.

Measured normalised differential cross section at particle level as a function of $y_{t}$.

Covariance matrix of the normalised differential cross section at particle level as a function of $y_{t}$.

Measured absolute differential cross section at parton level as a function of $y_{\bar{t}}$.

Covariance matrix of the absolute differential cross section at parton level as a function of $y_{\bar{t}}$.

Measured normalised differential cross section at parton level as a function of $y_{\bar{t}}$.

Covariance matrix of the normalised differential cross section at parton level as a function of $y_{\bar{t}}$.

Measured absolute differential cross section at particle level as a function of $y_{\bar{t}}$.

Covariance matrix of the absolute differential cross section at particle level as a function of $y_{\bar{t}}$.

Measured normalised differential cross section at particle level as a function of $y_{\bar{t}}$.

Covariance matrix of the normalised differential cross section at particle level as a function of $y_{\bar{t}}$.

Measured absolute differential cross section at parton level as a function of $y_{t}$ (leading).

Covariance matrix of the absolute differential cross section at parton level as a function of $y_{t}$ (leading).

Measured normalised differential cross section at parton level as a function of $y_{t}$ (leading).

Covariance matrix of the normalised differential cross section at parton level as a function of $y_{t}$ (leading).

Measured absolute differential cross section at particle level as a function of $y_{t}$ (leading).

Covariance matrix of the absolute differential cross section at particle level as a function of $y_{t}$ (leading).

Measured normalised differential cross section at particle level as a function of $y_{t}$ (leading).

Covariance matrix of the normalised differential cross section at particle level as a function of $y_{t}$ (leading).

Measured absolute differential cross section at parton level as a function of $y_{t}$ (trailing).

Covariance matrix of the absolute differential cross section at parton level as a function of $y_{t}$ (trailing).

Measured normalised differential cross section at parton level as a function of $y_{t}$ (trailing).

Covariance matrix of the normalised differential cross section at parton level as a function of $y_{t}$ (trailing).

Measured absolute differential cross section at particle level as a function of $y_{t}$ (trailing).

Covariance matrix of the absolute differential cross section at particle level as a function of $y_{t}$ (trailing).

Measured normalised differential cross section at particle level as a function of $y_{t}$ (trailing).

Covariance matrix of the normalised differential cross section at particle level as a function of $y_{t}$ (trailing).

Measured absolute differential cross section at parton level as a function of $p_{T}^{t\bar{t}}$.

Covariance matrix of the absolute differential cross section at parton level as a function of $p_{T}^{t\bar{t}}$.

Measured normalised differential cross section at parton level as a function of $p_{T}^{t\bar{t}}$.

Covariance matrix of the normalised differential cross section at parton level as a function of $p_{T}^{t\bar{t}}$.

Measured absolute differential cross section at particle level as a function of $p_{T}^{t\bar{t}}$.

Covariance matrix of the absolute differential cross section at particle level as a function of $p_{T}^{t\bar{t}}$.

Measured normalised differential cross section at particle level as a function of $p_{T}^{t\bar{t}}$.

Covariance matrix of the normalised differential cross section at particle level as a function of $p_{T}^{t\bar{t}}$.

Measured absolute differential cross section at parton level as a function of $y_{t\bar{t}}$.

Covariance matrix of the absolute differential cross section at parton level as a function of $y_{t\bar{t}}$.

Measured normalised differential cross section at parton level as a function of $y_{t\bar{t}}$.

Covariance matrix of the normalised differential cross section at parton level as a function of $y_{t\bar{t}}$.

Measured absolute differential cross section at particle level as a function of $y_{t\bar{t}}$.

Covariance matrix of the absolute differential cross section at particle level as a function of $y_{t\bar{t}}$.

Measured normalised differential cross section at particle level as a function of $y_{t\bar{t}}$.

Covariance matrix of the normalised differential cross section at particle level as a function of $y_{t\bar{t}}$.

Measured absolute differential cross section at parton level as a function of $m_{t\bar{t}}$.

Covariance matrix of the absolute differential cross section at parton level as a function of $m_{t\bar{t}}$.

Measured normalised differential cross section at parton level as a function of $m_{t\bar{t}}$.

Covariance matrix of the normalised differential cross section at parton level as a function of $m_{t\bar{t}}$.

Measured absolute differential cross section at particle level as a function of $m_{t\bar{t}}$.

Covariance matrix of the absolute differential cross section at particle level as a function of $m_{t\bar{t}}$.

Measured normalised differential cross section at particle level as a function of $m_{t\bar{t}}$.

Covariance matrix of the normalised differential cross section at particle level as a function of $m_{t\bar{t}}$.

Measured absolute differential cross section at parton level as a function of $\Delta|y|(t,\bar{t})$.

Covariance matrix of the absolute differential cross section at parton level as a function of $\Delta|y|(t,\bar{t})$.

Measured normalised differential cross section at parton level as a function of $\Delta|y|(t,\bar{t})$.

Covariance matrix of the normalised differential cross section at parton level as a function of $\Delta|y|(t,\bar{t})$.

Measured absolute differential cross section at particle level as a function of $\Delta|y|(t,\bar{t})$.

Covariance matrix of the absolute differential cross section at particle level as a function of $\Delta|y|(t,\bar{t})$.

Measured normalised differential cross section at particle level as a function of $\Delta|y|(t,\bar{t})$.

Covariance matrix of the normalised differential cross section at particle level as a function of $\Delta|y|(t,\bar{t})$.

Measured absolute differential cross section at parton level as a function of $\Delta\phi(t,\bar{t})$.

Covariance matrix of the absolute differential cross section at parton level as a function of $\Delta\phi(t,\bar{t})$.

Measured normalised differential cross section at parton level as a function of $\Delta\phi(t,\bar{t})$.

Covariance matrix of the normalised differential cross section at parton level as a function of $\Delta\phi(t,\bar{t})$.

Measured absolute differential cross section at particle level as a function of $\Delta\phi(t,\bar{t})$.

Covariance matrix of the absolute differential cross section at particle level as a function of $\Delta\phi(t,\bar{t})$.

Measured normalised differential cross section at particle level as a function of $\Delta\phi(t,\bar{t})$.

Covariance matrix of the normalised differential cross section at particle level as a function of $\Delta\phi(t,\bar{t})$.

Measured absolute differential cross section at particle level as a function of $p_{T}^{l}$.

Covariance matrix of the absolute differential cross section at particle level as a function of $p_{T}^{l}$.

Measured normalised differential cross section at particle level as a function of $p_{T}^{l}$.

Covariance matrix of the normalised differential cross section at particle level as a function of $p_{T}^{l}$.

Measured absolute differential cross section at particle level as a function of $p_{T}^{\bar{l}}$.

Covariance matrix of the absolute differential cross section at particle level as a function of $p_{T}^{\bar{l}}$.

Measured normalised differential cross section at particle level as a function of $p_{T}^{\bar{l}}$.

Covariance matrix of the normalised differential cross section at particle level as a function of $p_{T}^{\bar{l}}$.

Measured absolute differential cross section at particle level as a function of $p_{T}^{l}$ (leading).

Covariance matrix of the absolute differential cross section at particle level as a function of $p_{T}^{l}$ (leading).

Measured normalised differential cross section at particle level as a function of $p_{T}^{l}$ (leading).

Covariance matrix of the normalised differential cross section at particle level as a function of $p_{T}^{l}$ (leading).

Measured absolute differential cross section at particle level as a function of $p_{T}^{l}$ (trailing).

Covariance matrix of the absolute differential cross section at particle level as a function of $p_{T}^{l}$ (trailing).

Measured normalised differential cross section at particle level as a function of $p_{T}^{l}$ (trailing).

Covariance matrix of the normalised differential cross section at particle level as a function of $p_{T}^{l}$ (trailing).

Measured absolute differential cross section at particle level as a function of $\eta_{l}$.

Covariance matrix of the absolute differential cross section at particle level as a function of $\eta_{l}$.

Measured normalised differential cross section at particle level as a function of $\eta_{l}$.

Covariance matrix of the normalised differential cross section at particle level as a function of $\eta_{l}$.

Measured absolute differential cross section at particle level as a function of $\eta_{\bar{l}}$.

Covariance matrix of the absolute differential cross section at particle level as a function of $\eta_{\bar{l}}$.

Measured normalised differential cross section at particle level as a function of $\eta_{\bar{l}}$.

Covariance matrix of the normalised differential cross section at particle level as a function of $\eta_{\bar{l}}$.

Measured absolute differential cross section at particle level as a function of $\eta_{l}$ (leading).

Covariance matrix of the absolute differential cross section at particle level as a function of $\eta_{l}$ (leading).

Measured normalised differential cross section at particle level as a function of $\eta_{l}$ (leading).

Covariance matrix of the normalised differential cross section at particle level as a function of $\eta_{l}$ (leading).

Measured absolute differential cross section at particle level as a function of $\eta_{l}$ (trailing).

Covariance matrix of the absolute differential cross section at particle level as a function of $\eta_{l}$ (trailing).

Measured normalised differential cross section at particle level as a function of $\eta_{l}$ (trailing).

Covariance matrix of the normalised differential cross section at particle level as a function of $\eta_{l}$ (trailing).

Measured absolute differential cross section at particle level as a function of $p_{T}^{l\bar{l}}$.

Covariance matrix of the absolute differential cross section at particle level as a function of $p_{T}^{l\bar{l}}$.

Measured normalised differential cross section at particle level as a function of $p_{T}^{l\bar{l}}$.

Covariance matrix of the normalised differential cross section at particle level as a function of $p_{T}^{l\bar{l}}$.

Measured absolute differential cross section at particle level as a function of $m_{l\bar{l}}$.

Covariance matrix of the absolute differential cross section at particle level as a function of $m_{l\bar{l}}$.

Measured normalised differential cross section at particle level as a function of $m_{l\bar{l}}$.

Covariance matrix of the normalised differential cross section at particle level as a function of $m_{l\bar{l}}$.

Measured absolute differential cross section at particle level as a function of $\Delta\phi(l,\bar{l})$.

Covariance matrix of the absolute differential cross section at particle level as a function of $\Delta\phi(l,\bar{l})$.

Measured normalised differential cross section at particle level as a function of $\Delta\phi(l,\bar{l})$.

Covariance matrix of the normalised differential cross section at particle level as a function of $\Delta\phi(l,\bar{l})$.

Measured absolute differential cross section at particle level as a function of $\Delta|\eta|(l,\bar{l})$.

Covariance matrix of the absolute differential cross section at particle level as a function of $\Delta|\eta|(l,\bar{l})$.

Measured normalised differential cross section at particle level as a function of $\Delta|\eta|(l,\bar{l})$.

Covariance matrix of the normalised differential cross section at particle level as a function of $\Delta|\eta|(l,\bar{l})$.

Measured absolute differential cross section at particle level as a function of $p_{T}^{b}$ (leading).

Covariance matrix of the absolute differential cross section at particle level as a function of $p_{T}^{b}$ (leading).

Measured normalised differential cross section at particle level as a function of $p_{T}^{b}$ (leading).

Covariance matrix of the normalised differential cross section at particle level as a function of $p_{T}^{b}$ (leading).

Measured absolute differential cross section at particle level as a function of $p_{T}^{b}$ (trailing).

Covariance matrix of the absolute differential cross section at particle level as a function of $p_{T}^{b}$ (trailing).

Measured normalised differential cross section at particle level as a function of $p_{T}^{b}$ (trailing).

Covariance matrix of the normalised differential cross section at particle level as a function of $p_{T}^{b}$ (trailing).

Measured absolute differential cross section at particle level as a function of $\eta_{b}$ (leading).

Covariance matrix of the absolute differential cross section at particle level as a function of $\eta_{b}$ (leading).

Measured normalised differential cross section at particle level as a function of $\eta_{b}$ (leading).

Covariance matrix of the normalised differential cross section at particle level as a function of $\eta_{b}$ (leading).

Measured absolute differential cross section at particle level as a function of $\eta_{b}$ (trailing).

Covariance matrix of the absolute differential cross section at particle level as a function of $\eta_{b}$ (trailing).

Measured normalised differential cross section at particle level as a function of $\eta_{b}$ (trailing).

Covariance matrix of the normalised differential cross section at particle level as a function of $\eta_{b}$ (trailing).

Measured absolute differential cross section at particle level as a function of $p_{T}^{b\bar{b}}$.

Covariance matrix of the absolute differential cross section at particle level as a function of $p_{T}^{b\bar{b}}$.

Measured normalised differential cross section at particle level as a function of $p_{T}^{b\bar{b}}$.

Covariance matrix of the normalised differential cross section at particle level as a function of $p_{T}^{b\bar{b}}$.

Measured absolute differential cross section at particle level as a function of $m_{b\bar{b}}$.

Covariance matrix of the absolute differential cross section at particle level as a function of $m_{b\bar{b}}$.

Measured normalised differential cross section at particle level as a function of $m_{b\bar{b}}$.

Covariance matrix of the normalised differential cross section at particle level as a function of $m_{b\bar{b}}$.

Measured absolute differential cross section at particle level as a function of $N_{jets}$.

Covariance matrix of the absolute differential cross section at particle level as a function of $N_{jets}$.

Measured normalised differential cross section at particle level as a function of $N_{jets}$.

Covariance matrix of the normalised differential cross section at particle level as a function of $N_{jets}$.

Normalized differential distributions of unfolded data for $\tau_{\perp}$ for $225 < H_{T,2} < 298$ GeV

Normalized differential distributions of unfolded data for $\tau_{\perp}$ for $298 < H_{T,2} < 365$ GeV

Normalized differential distributions of unfolded data for $\tau_{\perp}$ for $365 < H_{T,2} < 452$ GeV

Normalized differential distributions of unfolded data for $\tau_{\perp}$ for $452 < H_{T,2} < 557$ GeV

Normalized differential distributions of unfolded data for $\tau_{\perp}$ for $H_{T,2} > 557$ GeV

Normalized differential distributions of unfolded data for $\rho_{Tot}$ for $73 < H_{T,2} < 93$ GeV

Normalized differential distributions of unfolded data for $\rho_{Tot}$ for $93 < H_{T,2} < 165$ GeV

Normalized differential distributions of unfolded data for $\rho_{Tot}$ for $165 < H_{T,2} < 225$ GeV

Normalized differential distributions of unfolded data for $\rho_{Tot}$ for $225 < H_{T,2} < 298$ GeV

Normalized differential distributions of unfolded data for $\rho_{Tot}$ for $298 < H_{T,2} < 365$ GeV

Normalized differential distributions of unfolded data for $\rho_{Tot}$ for $365 < H_{T,2} < 452$ GeV

Normalized differential distributions of unfolded data for $\rho_{Tot}$ for $452 < H_{T,2} < 557$ GeV

Normalized differential distributions of unfolded data for $\rho_{Tot}$ for $H_{T,2} > 557$ GeV

Normalized differential distributions of unfolded data for $B_{Tot}$ for $73 < H_{T,2} < 93$ GeV

Normalized differential distributions of unfolded data for $B_{Tot}$ for $93 < H_{T,2} < 165$ GeV

Normalized differential distributions of unfolded data for $B_{Tot}$ for $165 < H_{T,2} < 225$ GeV

Normalized differential distributions of unfolded data for $B_{Tot}$ for $225 < H_{T,2} < 298$ GeV

Normalized differential distributions of unfolded data for $B_{Tot}$ for $298 < H_{T,2} < 365$ GeV

Normalized differential distributions of unfolded data for $B_{Tot}$ for $365 < H_{T,2} < 452$ GeV

Normalized differential distributions of unfolded data for $B_{Tot}$ for $452 < H_{T,2} < 557$ GeV

Normalized differential distributions of unfolded data for $B_{Tot}$ for $H_{T,2} > 557$ GeV

Normalized differential distributions of unfolded data for $\rho_{Tot}^{T}$ for $73 < H_{T,2} < 93$ GeV

Normalized differential distributions of unfolded data for $\rho_{Tot}^{T}$ for $93 < H_{T,2} < 165$ GeV

Normalized differential distributions of unfolded data for $\rho_{Tot}^{T}$ for $165 < H_{T,2} < 225$ GeV

Normalized differential distributions of unfolded data for $\rho_{Tot}^{T}$ for $225 < H_{T,2} < 298$ GeV

Normalized differential distributions of unfolded data for $\rho_{Tot}^{T}$ for $298 < H_{T,2} < 365$ GeV

Normalized differential distributions of unfolded data for $\rho_{Tot}^{T}$ for $365 < H_{T,2} < 452$ GeV

Normalized differential distributions of unfolded data for $\rho_{Tot}^{T}$ for $452 < H_{T,2} < 557$ GeV

Normalized differential distributions of unfolded data for $\rho_{Tot}^{T}$ for $H_{T,2} > 557$ GeV

The $ {{{\mathrm {B}}}\to {\mathrm {D^0}}} $ nuclear modification factor $ {R_{\mathrm {AA}}} $ for PbPb collisions at ${\sqrt {\smash [b]{s_{_{\mathrm {NN}}}}}} = $ 5.02 TeV.

Measured misidentification probability distribution as a function of track multiplicity for the EMJ-1 criteria group defined in Table 2. The red up-pointing triangles are for b jets while the blue down-pointing triangles are for light-flavor jets. The horizontal lines on the data points indicate the variable bin width.

The $H_\mathrm{T}$ distribution for the observed data events (black points) and the predicted background estimation (blue) for selection set 8 (SM QCD-enhanced), requiring at least two jets tagged by loose emerging jet criteria.

The number of associated tracks distribution for the observed data events (black points) and the predicted background estimation (blue) for selection set 8 (SM QCD-enhanced), requiring at least two jets tagged by loose emerging jet criteria.

The $H_\mathrm{T}$ distribution for the observed data events (black points) and the predicted background estimation (blue) for selection set 9 (SM QCD-enhanced), requiring at least one jet tagged by loose emerging jet criteria and large $p_\mathrm{T}^\mathrm{miss}$.

The number of associated tracks distribution for the observed data events (black points) and the predicted background estimation (blue) for selection set 9 (SM QCD-enhanced), requiring at least one jet tagged by loose emerging jet criteria and large $p_\mathrm{T}^\mathrm{miss}$.

Upper limits at 95% CL on the signal cross section for models with dark pion mass $(m_{\pi_\mathrm{DK}})$ of 5 GeV in the proper decay length $(c\tau_{\pi_\mathrm{DK}})$ versus dark mediator mass $(m_{\mathrm{X_{DK}}})$ plane.

Dark mediator mass exclusion limits at 95% CL derived from theoretical cross sections for models with dark pion mass $(m_{\pi_\mathrm{DK}})$ of 5 GeV in the proper decay length $(c\tau_{\pi_\mathrm{DK}})$ versus dark mediator mass $(m_{\mathrm{X_{DK}}})$ plane.