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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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.

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.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

The 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.

Normalized differential cross section, $(1/\sigma_\text{fid})d\sigma_\text{fid}/d\log(m_{bb}/p_\text{T})$, as a function of $\log(m_{bb}/p_\text{T})$ for $m_{bb}$ the invariant mass of the two b-jets.

Data and SM predictions in SRs for the $1lb\bar{b}$ analysis for $E_{\mathrm{T}}^{\mathrm{miss}}$ in SR1Lbb-Medium. All SRs selections but the one on the quantity shown are applied. All uncertainties are included in the uncertainty band. Example SUSY models are superimposed for illustrative purposes.

Distributions of $m_{\gamma\gamma}$ before the final requirement on $m_{\gamma\gamma}$ in SR1Lyy-a. The expected contributions from both the peaking and non-peaking backgrounds are shown as stacked colored histograms. Two example SUSY models are superimposed for illustrative purposes.

Distributions of $m_{\gamma\gamma}$ before the final requirement on $m_{\gamma\gamma}$ in SR1Lyy-b. The expected contributions from both the peaking and non-peaking backgrounds are shown as stacked colored histograms. Two example SUSY models are superimposed for illustrative purposes.

Observed and predicted distributions for $m_{jj}$ in SRSS-j1. All SRs selections but the one on the quantity shown are applied. All uncertainties are included in the uncertainty band. An example SUSY model is superimposed for illustrative purposes.

Observed and predicted distributions for $m_{T2}$ in SRSS-j23. All SRs selections but the one on the quantity shown are applied. All uncertainties are included in the uncertainty band. An example SUSY model is superimposed for illustrative purposes.

The observed exclusion for the $0lb\bar{b}$ channel. Experimental and theoretical systematic uncertainties are applied to background and signal samples and illustrated by the yellow band and the red dotted contour lines, respectively. The red dotted lines indicate the $\pm$ 1 standard-deviation variation on the observed exclusion limit due to theoretical uncertainties in the signal cross-section.

The expected exclusion for the $0lb\bar{b}$ channel. Experimental and theoretical systematic uncertainties are applied to background and signal samples and illustrated by the yellow band and the red dotted contour lines, respectively. The red dotted lines indicate the $\pm$ 1 standard-deviation variation on the observed exclusion limit due to theoretical uncertainties in the signal cross-section.

The observed exclusion for the $1lb\bar{b}$ channel. Experimental and theoretical systematic uncertainties are applied to background and signal samples and illustrated by the yellow band and the red dotted contour lines, respectively. The red dotted lines indicate the $\pm$ 1 standard-deviation variation on the observed exclusion limit due to theoretical uncertainties in the signal cross-section.

The expected exclusion for the $1lb\bar{b}$ channel. Experimental and theoretical systematic uncertainties are applied to background and signal samples and illustrated by the yellow band and the red dotted contour lines, respectively. The red dotted lines indicate the $\pm$ 1 standard-deviation variation on the observed exclusion limit due to theoretical uncertainties in the signal cross-section.

The expected exclusion for the $1l\gamma\gamma$ channel. Experimental and theoretical systematic uncertainties are applied to background and signal samples and illustrated by the yellow band and the red dotted contour lines, respectively. The red dotted lines indicate the $\pm$ 1 standard-deviation variation on the observed exclusion limit due to theoretical uncertainties in the signal cross-section.

The observed exclusion for the $l^{\pm}l^{\pm}$ channel. Experimental and theoretical systematic uncertainties are applied to background and signal samples and illustrated by the yellow band and the red dotted contour lines, respectively. The red dotted lines indicate the $\pm$ 1 standard-deviation variation on the observed exclusion limit due to theoretical uncertainties in the signal cross-section.

The expected exclusion for the $l^{\pm}l^{\pm}$ channel. Experimental and theoretical systematic uncertainties are applied to background and signal samples and illustrated by the yellow band and the red dotted contour lines, respectively. The red dotted lines indicate the $\pm$ 1 standard-deviation variation on the observed exclusion limit due to theoretical uncertainties in the signal cross-section.

The observed cross-section exclusion as a function of the $\tilde{\chi}_{1}^{\pm}$/$\tilde{\chi}_{2}^{0}$ masses for the $3l$ analysis for signal models with $m(\tilde{\chi}_{2}^{0}) - m(\tilde{\chi}_{1}^{0}) = 130$ GeV.

The expected cross-section exclusion as a function of the $\tilde{\chi}_{1}^{\pm}$/$\tilde{\chi}_{2}^{0}$ masses for the $3l$ analysis for signal models with $m(\tilde{\chi}_{2}^{0}) - m(\tilde{\chi}_{1}^{0}) = 130$ GeV.

The observed cross-section exclusion as a function of the $\tilde{\chi}_{1}^{\pm}$/$\tilde{\chi}_{2}^{0}$ masses for the $1lb\bar{b}$ analysis for signal models with $m(\tilde{\chi}_{2}^{0}) - m(\tilde{\chi}_{1}^{0}) = 130$ GeV.

The expected cross-section exclusion as a function of the $\tilde{\chi}_{1}^{\pm}$/$\tilde{\chi}_{2}^{0}$ masses for the $1lb\bar{b}$ analysis for signal models with $m(\tilde{\chi}_{2}^{0}) - m(\tilde{\chi}_{1}^{0}) = 130$ GeV.

The observed cross-section exclusion as a function of the $\tilde{\chi}_{1}^{\pm}$/$\tilde{\chi}_{2}^{0}$ masses for the $1l\gamma\gamma$ analysis for signal models with $m(\tilde{\chi}_{2}^{0}) - m(\tilde{\chi}_{1}^{0}) = 130$ GeV.

The expected cross-section exclusion as a function of the $\tilde{\chi}_{1}^{\pm}$/$\tilde{\chi}_{2}^{0}$ masses for the $1l\gamma\gamma$ analysis for signal models with $m(\tilde{\chi}_{2}^{0}) - m(\tilde{\chi}_{1}^{0}) = 130$ GeV.

The observed cross-section exclusion as a function of the $\tilde{\chi}_{1}^{\pm}$/$\tilde{\chi}_{2}^{0}$ masses for the $l^{\pm}l^{\pm}$ analysis for signal models with $m(\tilde{\chi}_{2}^{0}) - m(\tilde{\chi}_{1}^{0}) = 130$ GeV.

The expected cross-section exclusion as a function of the $\tilde{\chi}_{1}^{\pm}$/$\tilde{\chi}_{2}^{0}$ masses for the $l^{\pm}l^{\pm}$ analysis for signal models with $m(\tilde{\chi}_{2}^{0}) - m(\tilde{\chi}_{1}^{0}) = 130$ GeV.

The observed cross-section exclusion as a function of the $\tilde{\chi}_{1}^{\pm}$/$\tilde{\chi}_{2}^{0}$ masses for the $0lb\bar{b}$ analysis for signal models assuming $m(\tilde{\chi}_{1}^{0}) = 0$ GeV.

The expected cross-section exclusion as a function of the $\tilde{\chi}_{1}^{\pm}$/$\tilde{\chi}_{2}^{0}$ masses for the $0lb\bar{b}$ analysis for signal models assuming $m(\tilde{\chi}_{1}^{0}) = 0$ GeV.

The observed cross-section exclusion as a function of the $\tilde{\chi}_{1}^{\pm}$/$\tilde{\chi}_{2}^{0}$ masses for the $1lb\bar{b}$ analysis for signal models assuming $m(\tilde{\chi}_{1}^{0}) = 0$ GeV.

The expected cross-section exclusion as a function of the $\tilde{\chi}_{1}^{\pm}$/$\tilde{\chi}_{2}^{0}$ masses for the $1lb\bar{b}$ analysis for signal models assuming $m(\tilde{\chi}_{1}^{0}) = 0$ GeV.

The observed cross-section exclusion as a function of the $\tilde{\chi}_{1}^{\pm}$/$\tilde{\chi}_{2}^{0}$ masses for the $1l\gamma\gamma$ analysis for signal models assuming $m(\tilde{\chi}_{1}^{0}) = 0$ GeV.

The expected cross-section exclusion as a function of the $\tilde{\chi}_{1}^{\pm}$/$\tilde{\chi}_{2}^{0}$ masses for the $1l\gamma\gamma$ analysis for signal models assuming $m(\tilde{\chi}_{1}^{0}) = 0$ GeV.

The observed cross-section exclusion as a function of the $\tilde{\chi}_{1}^{\pm}$/$\tilde{\chi}_{2}^{0}$ masses for the $l^{\pm}l^{\pm}$ analysis for signal models assuming $m(\tilde{\chi}_{1}^{0}) = 0$ GeV.

The expected cross-section exclusion as a function of the $\tilde{\chi}_{1}^{\pm}$/$\tilde{\chi}_{2}^{0}$ masses for the $l^{\pm}l^{\pm}$ analysis for signal models assuming $m(\tilde{\chi}_{1}^{0}) = 0$ GeV.

The observed cross-section exclusion as a function of the $\tilde{\chi}_{1}^{\pm}$/$\tilde{\chi}_{2}^{0}$ masses for the $3l$ analysis for signal models assuming $m(\tilde{\chi}_{1}^{0}) = 0$ GeV.

The expected cross-section exclusion as a function of the $\tilde{\chi}_{1}^{\pm}$/$\tilde{\chi}_{2}^{0}$ masses for the $3l$ analysis for signal models assuming $m(\tilde{\chi}_{1}^{0}) = 0$ GeV.

Acceptance for $0lb\bar{b}$ SRHad-Low signal region. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Efficiencies for $0lb\bar{b}$ SRHad-Low signal region.

Acceptance for $0lb\bar{b}$ SRHad-High signal region. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Efficiencies for $0lb\bar{b}$ SRHad-High signal region.

Upper cross section limits for the $0lb\bar{b}$ analysis.

Acceptance for $1lb\bar{b}$ SR1Lbb-Low signal region. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Efficiency for $1lb\bar{b}$ SR1Lbb-Low signal region. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Acceptance for $1lb\bar{b}$ SR1Lbb-Medium signal region. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Efficiency for $1lb\bar{b}$ SR1Lbb-Medium signal region. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Acceptance for $1lb\bar{b}$ SR1Lbb-High signal region. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Efficiency for $1lb\bar{b}$ SR1Lbb-High signal region. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Upper cross section limits for the $1lb\bar{b}$ analysis.

Acceptance for $1l\gamma\gamma$ signal region SR1Lyy-a. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Efficiencies for $1l\gamma\gamma$ signal region SR1Lyy-a.

Acceptance for $1l\gamma\gamma$ signal region SR1Lyy-b. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Efficiencies for $1l\gamma\gamma$ signal region SR1Lyy-b.

Upper cross section limits for the $1l\gamma\gamma$ analysis.

Acceptance for $l^{\pm}l^{\pm}$ signal region SRSS-j1. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Efficiencies for $l^{\pm}l^{\pm}$ signal region SRSS-j1. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Acceptance for $l^{\pm}l^{\pm}$ signal region SRSS-j23. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Efficiencies for $l^{\pm}l^{\pm}$ signal region SRSS-j23. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Acceptance for $3L$ SFOS signal region SR3L-SFOS-1J. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Efficiencies for $3L$ SFOS signal region SR3L-SFOS-1J. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Acceptance for $3L$ SFOS signal region SR3L-SFOS-0Ja. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Efficiencies for $3L$ SFOS signal region SR3L-SFOS-0Ja. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Acceptance for $3L$ SFOS signal region SR3L-SFOS-0Jb. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Efficiencies for $3L$ SFOS signal region SR3L-SFOS-0Jb. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Acceptance for $3L$ DFOS signal region SR3L-DFOS-0J. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Efficiencies for $3L$ DFOS signal region SR3L-DFOS-0J. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Acceptance for $3L$ DFOS signal region SR3L-DFOS-1Ja. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Efficiencies for $3L$ DFOS signal region SR3L-DFOS-1Ja. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Acceptance for $3L$ DFOS signal region SR3L-DFOS-1Jb. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Efficiencies for $3L$ DFOS signal region SR3L-DFOS-1Jb. Note that the acceptance is relative to the total chargino-neutralino production cross section.

Upper cross section limits for the $l^{\pm}l^{\pm}$ analysis.

Upper cross section limits for the $3l$ analysis.

Event selection cutflow for SM background (pre-fit) and representative signal samples for the $0lb\bar{b}$ SR. The masses of next-lightest-neutralinos and LSPs are reported. Only statistical uncertainties are shown. The MC statistics for the signal samples is 50K and 44K events, respectively. Samples are produced with generator filters which selects $h \rightarrow b\bar{b}$ and $W \rightarrow qq'$ decays. ``All events" for SUSY scenarios represent the total number of signal events for the models considered taking into account the BR of $W \rightarrow qq'$ (0.674) and $h \rightarrow b\bar{b}$ (0.582).

Event selection cutflow for SM background (pre-fit) and representative signal samples for the $1lb\bar{b}$ channel. The masses of next-lightest-neutralinos and LSPs are reported. Only statistical uncertainties are shown. The MC statistics for the signal samples is 28K, 29K and 29K events, respectively. Samples are produced with generator filters which selects $h \rightarrow b\bar{b}$ and $W \rightarrow l \nu$ decays. ``All events" for SUSY scenarios represent the total number of signal events for the models considered taking into account the BR of $W \rightarrow l \nu$ (0.324) and $h \rightarrow b\bar{b}$ (0.582).

Event selection cutflow is presented for SM background (pre-fit) and three signal scenarios for the $1l\gamma\gamma$ channel SRs. The masses of next-lightest-neutralinos and LSPs are reported. The uncertainties only include statistical uncertainties. The MC statistics for the signal samples is 10K events in all cases. Samples are produced with generator filters which selects $h \rightarrow \gamma\gamma$ and $W \rightarrow l \nu$ decays. The data-driven-estimated non-peaking background is not evaluated at each stage of the selection, hence only the peaking background cutflow is presented.

Event selection cutflow is presented for one signal scenario for SRSS-j23. The model with next-to-lightest neutralino mass of 175 GeV and massless $\tilde{\chi}^{0}_{1})$ with 100% BR is considered. The MC statistics for the signal samples is 75K events. Samples are produced with a generator filter which selects events with at least two leptons with $p_{\mathrm{T}} > 7$ GeV. ``2SS leptons" indicates the selection of two same-sign electrons or muons as described in the text (Section 6.4).

Event selection cutflow is presented for one signal scenario for SRSS-j1. The model with next-to-lightest neutralino mass of 175 GeV and massless $\tilde{\chi}^{0}_{1})$ with 100% BR is considered. The MC statistics for the signal samples is 75K events. Samples are produced with a generator filter which selects events with at least two leptons with $p_{\mathrm{T}} > 7$ GeV. ``2SS leptons" indicates the selection of two same-sign electrons or muons as described in the text (Section 6.4).

Event selection cut-flow is presented for one signal scenario for each signal regions. The model with next-to-lightest neutralino mass of 150 GeV and massless LSP with 100 \% BR is considered. The MC statistics for the signal samples is 123K events. Samples are produced with a generator filter which selects events with at least two leptons with pT $>$ 7 GeV. ``3L+Trigger" indicates three-lepton and trigger requirements. ``Preselection" includes the veto on bjets, ETmiss above 20 GeV and invariant mass of the three leptons above 20 GeV.