The impact of the eight most important systematic uncertainties on \(R_t\), in %.

The post-fit yields in the two SRs. All uncertainties applied in the analysis are included.

Limits on EFT parameters and Vtb extracted from the analysis. The upper and lower limits correspond to 95% CL.

Results of the main analysis.

Pre-fit distribution of the NN discriminant \(D_{\text{nn}}\) in SR plus.

Post-fit distribution of the NN discriminant \(D_{\text{nn}}\) in SR plus.

Post-fit distribution of the \(\Delta\phi(\vec{p}_{T}^{miss},\mu)\) variable in the muon-plus CR.

Pre-fit distribution of the NN discriminant \(D_{\text{nn}}\) in SR minus.

Post-fit distribution of the NN discriminant \(D_{\text{nn}}\) in SR minus.

Post-fit distribution of the \(\Delta\phi(\vec{p}_{T}^{miss},\mu)\) variable in the muon-minus CR.

Pre-fit distribution of the invariant mass of the untagged jet and the b-tagged jet, \(m(jb)\), in SR plus.

Pre-fit distribution of the absolute value of the pseudorapidity of the untagged jet, \(|\eta(j)|\), in SR plus.

Pre-fit distribution of the absolute value of the difference in \(p_{\text{T}}\) between the reconstructed W boson and the jet pair, \(|\Delta p_{\text{T}}(W, jb)|\), in SR plus.

Pre-fit distribution of the difference in azimuth angle between the reconstructed W boson and the jet pair, \(|\Delta\phi(W, jb)|\), in SR plus.

Pre-fit distribution of the invariant mass of the reconstructed top quark, \(m(t)\), in SR plus.

Pre-fit distribution of the absolute value of the difference in pseudorapidity between the charged lepton and the untagged jet, \(|\Delta\eta(\ell ,j)|\), SR plus.

Pre-fit distribution of the angular distance of the charged lepton and the untagged jet, \(\Delta R(\ell ,j)\), in SR plus.

Pre-fit distribution of the absolute value of the difference in pseudorapidity between the b-tagged jet and the charged lepton, \(|\Delta\eta(b,\ell )|\), in SR plus.

Comparison of the observed (black points) and expected (histograms) numbers of events in nonoverlapping $m^{corr}_{\mu\mu}$ intervals in the STA-STA dimuon category, in the signal region optimized for the RPV SUSY model. Yellow and green stacked filled histograms represent mean expected background contributions from QCD and DY, respectively, while statistical uncertainties in the total expected background are shown as hatched histograms. Signal contributions expected from simulated signals indicated in the legends are shown in red and blue. Their yields are set to the corresponding median expected 95% CL exclusion limits obtained from the ensemble of both dimuon categories, scaled up as indicated in the legend to improve visibility. The last bin includes events in the histogram overflow.

Distribution of min($d_0 / \sigma_{d_0}$) for TMS-TMS dimuons with $|\Delta\Phi| < \pi/30$, for events in all mass intervals combined, for both the validation (min($d_0 / \sigma_{d_0}$) < 6) and signal (min($d_0 / \sigma_{d_0}$) > 6) regions. The number of observed events (black circles) is overlaid with the stacked histograms showing the expected numbers of QCD (yellow) and DY (green) background events. Statistical uncertainties in the total expected background are shown as hatched histograms. Signal contributions expected from simulated signals indicated in the legends are shown in red and blue. Their yields are set to the corresponding median expected 95% CL exclusion limits obtained from the ensemble of both dimuon categories, scaled up as indicated in the legend to improve visibility. Events are required to satisfy all nominal selection criteria with the exception of the $d_0 / \sigma_{d_0}$ requirement. The last bin includes events in the histogram overflow.

Distribution of min($d_0 / \sigma_{d_0}$) for TMS-TMS dimuons with $|\Delta\Phi| < \pi/4$, for events in all mass intervals combined, for both the validation (min($d_0 / \sigma_{d_0}$) < 6) and signal (min($d_0 / \sigma_{d_0}$) > 6) regions. The number of observed events (black circles) is overlaid with the stacked histograms showing the expected numbers of QCD (yellow) and DY (green) background events. Statistical uncertainties in the total expected background are shown as hatched histograms. Signal contributions expected from simulated signals indicated in the legends are shown in red and blue. Their yields are set to the corresponding median expected 95% CL exclusion limits obtained from the ensemble of both dimuon categories, scaled up as indicated in the legend to improve visibility. Events are required to satisfy all nominal selection criteria with the exception of the $d_0 / \sigma_{d_0}$ requirement. The last bin includes events in the histogram overflow.

Comparison of observed and expected numbers of events in bins of $m^{corr}_{\mu\mu}$ in the TMS-TMS dimuon category, in the signal regions optimized for the RPV SUSY model. The number of observed events (black circles) is overlaid with the stacked filled histograms showing the expected numbers of QCD (yellow) and DY (green) background events in bins of $m^{corr}_{\mu\mu}$ in min($d_0 / \sigma_{d_0}$) bin: 6-10. Hatched histograms show statistical uncertainties in the total expected background. Contributions expected from signal events predicted by the RPV SUSY model with the parameters indicated in the legends are shown as red and blue histograms. Their yields are set to the corresponding median expected 95% CL exclusion limits obtained from the ensemble of both dimuon categories, scaled up as indicated in the legend to improve visibility. The last bin includes events in the histogram overflow.

Comparison of observed and expected numbers of events in bins of $m^{corr}_{\mu\mu}$ in the TMS-TMS dimuon category, in the signal regions optimized for the RPV SUSY model. The number of observed events (black circles) is overlaid with the stacked filled histograms showing the expected numbers of QCD (yellow) and DY (green) background events in bins of $m^{corr}_{\mu\mu}$ in min($d_0 / \sigma_{d_0}$) bin: 10-20. Hatched histograms show statistical uncertainties in the total expected background. Contributions expected from signal events predicted by the RPV SUSY model with the parameters indicated in the legends are shown as red and blue histograms. Their yields are set to the corresponding median expected 95% CL exclusion limits obtained from the ensemble of both dimuon categories, scaled up as indicated in the legend to improve visibility. The last bin includes events in the histogram overflow.

Comparison of observed and expected numbers of events in bins of $m^{corr}_{\mu\mu}$ in the TMS-TMS dimuon category, in the signal regions optimized for the RPV SUSY model. The number of observed events (black circles) is overlaid with the stacked filled histograms showing the expected numbers of QCD (yellow) and DY (green) background events in bins of $m^{corr}_{\mu\mu}$ in min($d_0 / \sigma_{d_0}$) bin: >20. Hatched histograms show statistical uncertainties in the total expected background. Contributions expected from signal events predicted by the RPV SUSY model with the parameters indicated in the legends are shown as red and blue histograms. Their yields are set to the corresponding median expected 95% CL exclusion limits obtained from the ensemble of both dimuon categories, scaled up as indicated in the legend to improve visibility. The last bin includes events in the histogram overflow.

Comparison of observed and expected numbers of events in bins of $m_{\mu\mu}$ in the TMS-TMS dimuon category, in the signal regions optimized for the HAHM. The number of observed events (black circles) is overlaid with the stacked filled histograms showing the expected numbers of QCD (yellow) and DY (green) background events in bins of $m_{\mu\mu}$ in min($d_0 / \sigma_{d_0}$) bin: 6-10. Hatched histograms show statistical uncertainties in the total expected background. Signal contributions expected from simulated $H \rightarrow Z_DZ_D$ events with the parameters indicated in the legends are shown as red and blue histograms. Their yields are set to the corresponding median expected 95% CL exclusion limits obtained from the ensemble of both dimuon categories, scaled up as indicated in the legend to improve visibility. The last bin includes events in the histogram overflow.

Comparison of observed and expected numbers of events in bins of $m_{\mu\mu}$ in the TMS-TMS dimuon category, in the signal regions optimized for the HAHM. The number of observed events (black circles) is overlaid with the stacked filled histograms showing the expected numbers of QCD (yellow) and DY (green) background events in bins of $m_{\mu\mu}$ in min($d_0 / \sigma_{d_0}$) bin: 10-20. Hatched histograms show statistical uncertainties in the total expected background. Signal contributions expected from simulated $H \rightarrow Z_DZ_D$ events with the parameters indicated in the legends are shown as red and blue histograms. Their yields are set to the corresponding median expected 95% CL exclusion limits obtained from the ensemble of both dimuon categories, scaled up as indicated in the legend to improve visibility. The last bin includes events in the histogram overflow.

Comparison of observed and expected numbers of events in bins of $m_{\mu\mu}$ in the TMS-TMS dimuon category, in the signal regions optimized for the HAHM. The number of observed events (black circles) is overlaid with the stacked filled histograms showing the expected numbers of QCD (yellow) and DY (green) background events in bins of $m_{\mu\mu}$ in min($d_0 / \sigma_{d_0}$) bin: >20. Hatched histograms show statistical uncertainties in the total expected background. Signal contributions expected from simulated $H \rightarrow Z_DZ_D$ events with the parameters indicated in the legends are shown as red and blue histograms. Their yields are set to the corresponding median expected 95% CL exclusion limits obtained from the ensemble of both dimuon categories, scaled up as indicated in the legend to improve visibility. The last bin includes events in the histogram overflow.

The 95% CL upper limits on $B(H \rightarrow Z_DZ_D)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m(Z_D) = 10\ GeV$, in the STA-STA and TMS-TMS dimuon categories in 2022 data and their combination.The median expected limits obtained from the STA-STA and TMS-TMS dimuon categories are shown as dashed blue and red curves, respectively; the combined median expected limits are shown as dashed black curves; and the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.

The 95% CL upper limits on $B(H \rightarrow Z_DZ_D)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m(Z_D) = 20\ GeV$, in the STA-STA and TMS-TMS dimuon categories in 2022 data and their combination.The median expected limits obtained from the STA-STA and TMS-TMS dimuon categories are shown as dashed blue and red curves, respectively; the combined median expected limits are shown as dashed black curves; and the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.

The 95% CL upper limits on $B(H \rightarrow Z_DZ_D)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m(Z_D) = 30\ GeV$, in the STA-STA and TMS-TMS dimuon categories in 2022 data and their combination.The median expected limits obtained from the STA-STA and TMS-TMS dimuon categories are shown as dashed blue and red curves, respectively; the combined median expected limits are shown as dashed black curves; and the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.

The 95% CL upper limits on $B(H \rightarrow Z_DZ_D)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m(Z_D) = 40\ GeV$, in the STA-STA and TMS-TMS dimuon categories in 2022 data and their combination.The median expected limits obtained from the STA-STA and TMS-TMS dimuon categories are shown as dashed blue and red curves, respectively; the combined median expected limits are shown as dashed black curves; and the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.

The 95% CL upper limits on $B(H \rightarrow Z_DZ_D)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m(Z_D) = 50\ GeV$, in the STA-STA and TMS-TMS dimuon categories in 2022 data and their combination.The median expected limits obtained from the STA-STA and TMS-TMS dimuon categories are shown as dashed blue and red curves, respectively; the combined median expected limits are shown as dashed black curves; and the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.

The 95% CL upper limits on $B(H \rightarrow Z_DZ_D)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m(Z_D) = 60\ GeV$, in the STA-STA and TMS-TMS dimuon categories in 2022 data and their combination.The median expected limits obtained from the STA-STA and TMS-TMS dimuon categories are shown as dashed blue and red curves, respectively; the combined median expected limits are shown as dashed black curves; and the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.

The 95% CL upper limits on $B(H \rightarrow Z_DZ_D)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m(Z_D) = 10\ GeV$, obtained in this analysis, the Run 2 analysis, and their combination. The observed limits in this analysis and in the Run 2 analysis are shown as blue and red curves, respectively; the median combined expected limits are shown as dashed black curves; and the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.

The 95% CL upper limits on $B(H \rightarrow Z_DZ_D)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m(Z_D) = 20\ GeV$, obtained in this analysis, the Run 2 analysis, and their combination. The observed limits in this analysis and in the Run 2 analysis are shown as blue and red curves, respectively; the median combined expected limits are shown as dashed black curves; and the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.

The 95% CL upper limits on $B(H \rightarrow Z_DZ_D)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m(Z_D) = 30\ GeV$, obtained in this analysis, the Run 2 analysis, and their combination. The observed limits in this analysis and in the Run 2 analysis are shown as blue and red curves, respectively; the median combined expected limits are shown as dashed black curves; and the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.

The 95% CL upper limits on $B(H \rightarrow Z_DZ_D)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m(Z_D) = 40\ GeV$, obtained in this analysis, the Run 2 analysis, and their combination. The observed limits in this analysis and in the Run 2 analysis are shown as blue and red curves, respectively; the median combined expected limits are shown as dashed black curves; and the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.

The 95% CL upper limits on $B(H \rightarrow Z_DZ_D)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m(Z_D) = 50\ GeV$, obtained in this analysis, the Run 2 analysis, and their combination. The observed limits in this analysis and in the Run 2 analysis are shown as blue and red curves, respectively; the median combined expected limits are shown as dashed black curves; and the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.

The 95% CL upper limits on $B(H \rightarrow Z_DZ_D)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m(Z_D) = 60\ GeV$, obtained in this analysis, the Run 2 analysis, and their combination. The observed limits in this analysis and in the Run 2 analysis are shown as blue and red curves, respectively; the median combined expected limits are shown as dashed black curves; and the combined observed limits are shown as solid black curves. The green and yellow bands correspond, respectively, to the 68 and 95% quantiles for the combined expected limits.

The 95% CL upper limits on $\sigma(pp \rightarrow \tilde{q}\bar{\tilde{q}})B(\tilde{q} \rightarrow q\tilde{\chi}^{0}_{1})$ as a function of $c\tau(\tilde{\chi}^{0}_{1})$ in the RPV SUSY model, for $B(\tilde{\chi}^{0}_{1} \rightarrow \mu^{+}\mu^{-}\nu) = 0.5$ and $m(\tilde{q}) = 125\ GeV$. The observed limits for various $m(\tilde{\chi}^{0}_{1})$ indicated in the legends are shown as solid curves. The median expected limits and their 68 and 95% quantiles are shown, respectively, as dashed black curves and green and yellow bands for the case of $m(\tilde{\chi}^{0}_{1}) = 50\ GeV$ and omitted for other neutralino masses for clarity. The predicted cross section for $m(\tilde{q}) = 125\ GeV$ is 7200 pb, and falls outside the y-axis range.

The 95% CL upper limits on $\sigma(pp \rightarrow \tilde{q}\bar{\tilde{q}})B(\tilde{q} \rightarrow q\tilde{\chi}^{0}_{1})$ as a function of $c\tau(\tilde{\chi}^{0}_{1})$ in the RPV SUSY model, for $B(\tilde{\chi}^{0}_{1} \rightarrow \mu^{+}\mu^{-}\nu) = 0.5$ and $m(\tilde{q}) = 200\ GeV$. The observed limits for various $m(\tilde{\chi}^{0}_{1})$ indicated in the legends are shown as solid curves. The median expected limits and their 68 and 95% quantiles are shown, respectively, as dashed black curves and green and yellow bands for the case of $m(\tilde{\chi}^{0}_{1}) = 50\ GeV$ and omitted for other neutralino masses for clarity. The predicted cross section for $m(\tilde{q}) = 200 GeV$ is 840 pb, and falls outside the y-axis range.

The 95% CL upper limits on $\sigma(pp \rightarrow \tilde{q}\bar{\tilde{q}})B(\tilde{q} \rightarrow q\tilde{\chi}^{0}_{1})$ as a function of $c\tau(\tilde{\chi}^{0}_{1})$ in the RPV SUSY model, for $B(\tilde{\chi}^{0}_{1} \rightarrow \mu^{+}\mu^{-}\nu) = 0.5$ and $m(\tilde{q}) = 350\ GeV$. The observed limits for various $m(\tilde{\chi}^{0}_{1})$ indicated in the legends are shown as solid curves. The median expected limits and their 68 and 95% quantiles are shown, respectively, as dashed black curves and green and yellow bands for the case of $m(\tilde{\chi}^{0}_{1}) = 50\ GeV$ and omitted for other neutralino masses for clarity. The predicted cross section for $m(\tilde{q}) = 350\ GeV$ is 50 pb, and falls outside the y-axis range.

The 95% CL upper limits on $\sigma(pp \rightarrow \tilde{q}\bar{\tilde{q}})B(\tilde{q} \rightarrow q\tilde{\chi}^{0}_{1})$ as a function of $c\tau(\tilde{\chi}^{0}_{1})$ in the RPV SUSY model, for $B(\tilde{\chi}^{0}_{1} \rightarrow \mu^{+}\mu^{-}\nu) = 0.5$ and $m(\tilde{q}) = 700\ GeV$. The observed limits for various $m(\tilde{\chi}^{0}_{1})$ indicated in the legends are shown as solid curves. The median expected limits and their 68 and 95% quantiles are shown, respectively, as dashed black curves and green and yellow bands for the case of $m(\tilde{\chi}^{0}_{1}) = 50\ GeV$ and omitted for other neutralino masses for clarity. The gray horizontal line indicates the theoretical value of the squark-antisquark production cross section with the uncertainties shown as the gray shaded band.

The 95% CL upper limits on $\sigma(pp \rightarrow \tilde{q}\bar{\tilde{q}})B(\tilde{q} \rightarrow q\tilde{\chi}^{0}_{1})$ as a function of $c\tau(\tilde{\chi}^{0}_{1})$ in the RPV SUSY model, for $B(\tilde{\chi}^{0}_{1} \rightarrow \mu^{+}\mu^{-}\nu) = 0.5$ and $m(\tilde{q}) = 1150\ GeV$. The observed limits for various $m(\tilde{\chi}^{0}_{1})$ indicated in the legends are shown as solid curves. The median expected limits and their 68 and 95% quantiles are shown, respectively, as dashed black curves and green and yellow bands for the case of $m(\tilde{\chi}^{0}_{1}) = 50\ GeV$ and omitted for other neutralino masses for clarity. The gray horizontal line indicates the theoretical value of the squark-antisquark production cross section with the uncertainties shown as the gray shaded band.

The 95% CL upper limits on $\sigma(pp \rightarrow \tilde{q}\bar{\tilde{q}})B(\tilde{q} \rightarrow q\tilde{\chi}^{0}_{1})$ as a function of $c\tau(\tilde{\chi}^{0}_{1})$ in the RPV SUSY model, for $B(\tilde{\chi}^{0}_{1} \rightarrow \mu^{+}\mu^{-}\nu) = 0.5$ and $m(\tilde{q}) = 1600\ GeV$. The observed limits for various $m(\tilde{\chi}^{0}_{1})$ indicated in the legends are shown as solid curves. The median expected limits and their 68 and 95% quantiles are shown, respectively, as dashed black curves and green and yellow bands for the case of $m(\tilde{\chi}^{0}_{1}) = 50\ GeV$ and omitted for other neutralino masses for clarity. The gray horizontal line indicates the theoretical value of the squark-antisquark production cross section with the uncertainties shown as the gray shaded band.

Efficiencies of the Run 2 and Run 3 displaced dimuon triggers as a function of $c\tau$ for the HAHM signal events with $m(Z_D) = 50\ GeV$. The efficiency is defined as the fraction of simulated events that satisfy the requirements of the following sets of trigger paths: the Run 2 (2018) triggers (dashed black); the Run 3 (2022, L3) triggers (blue); the Run 3 (2022, L2) triggers (red); and the OR of all these triggers (Run 3 (2022), black). The lower panel shows the ratio of the overall Run 3 (2022) efficiency to the Run 2 (2018) efficiency.

Efficiencies of the Run 2 (2018) (red) and Run 3 (2022) (black) sets of displaced dimuon triggers as a function of $m(Z_D)$ for the HAHM signal events with $c\tau = 1\ cm$. The efficiency is defined as the fraction of simulated events that satisfy the detector acceptance and the requirements of the indicated set of trigger paths. The lower panel shows the ratio of the Run 3 (2022) efficiency to the Run 2 (2018) efficiency.

Efficiencies of the Run 2 (2018) (red) and Run 3 (2022) (black) sets of displaced dimuon triggers as a function of $m(Z_D)$ for the HAHM signal events with $c\tau = 10\ m$. The efficiency is defined as the fraction of simulated events that satisfy the detector acceptance and the requirements of the indicated set of trigger paths. The lower panel shows the ratio of the Run 3 (2022) efficiency to the Run 2 (2018) efficiency.

Overall selection efficiencies as a function of $c\tau(Z_D)$ for the HAHM signal with $m(Z_D) = 20\ GeV$ in different years of data taking. Efficiencies are computed as the ratios of the number of simulated signal events in which at least one dimuon candidate passes all 2016 (dashed green), 2018 (dashed red), and 2022 (solid black) trigger and offline selection criteria to the total number of simulated signal events. The lower panel shows the ratio of the 2022 efficiency to the 2018 efficiency (dashed red) and to the 2016 efficiency (dashed green).

Overall selection efficiencies as a function of $c\tau(Z_D)$ for the HAHM signal with $m(Z_D) = 50\ GeV$ in different years of data taking. Efficiencies are computed as the ratios of the number of simulated signal events in which at least one dimuon candidate passes all 2016 (dashed green), 2018 (dashed red), and 2022 (solid black) trigger and offline selection criteria to the total number of simulated signal events. The lower panel shows the ratio of the 2022 efficiency to the 2018 efficiency (dashed red) and to the 2016 efficiency (dashed green).

Overall selection efficiencies as a function of $c\tau(Z_D)$ for the HAHM model with $m(Z_D) = 10\ GeV$. The plot shows efficiencies of the two dimuon categories, TMS-TMS (dashed red) and STA-STA (dashed green), as well as their combination (solid black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper.

Overall selection efficiencies as a function of $c\tau(Z_D)$ for the HAHM model with $m(Z_D) = 20\ GeV$. The plot shows efficiencies of the two dimuon categories, TMS-TMS (dashed red) and STA-STA (dashed green), as well as their combination (solid black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper.

Overall selection efficiencies as a function of $c\tau(Z_D)$ for the HAHM model with $m(Z_D) = 30\ GeV$. The plot shows efficiencies of the two dimuon categories, TMS-TMS (dashed red) and STA-STA (dashed green), as well as their combination (solid black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper.

Overall selection efficiencies as a function of $c\tau(Z_D)$ for the HAHM model with $m(Z_D) = 40\ GeV$. The plot shows efficiencies of the two dimuon categories, TMS-TMS (dashed red) and STA-STA (dashed green), as well as their combination (solid black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper.

Overall selection efficiencies as a function of $c\tau(Z_D)$ for the HAHM model with $m(Z_D) = 50\ GeV$. The plot shows efficiencies of the two dimuon categories, TMS-TMS (dashed red) and STA-STA (dashed green), as well as their combination (solid black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper.

Overall selection efficiencies as a function of $c\tau(Z_D)$ for the HAHM model with $m(Z_D) = 60\ GeV$. The plot shows efficiencies of the two dimuon categories, TMS-TMS (dashed red) and STA-STA (dashed green), as well as their combination (solid black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper.

Overall selection efficiencies as a function of $c\tau(\tilde{\chi}^{0}_{1})$ for the RPV SUSY model, for events with $m(\tilde{q}) = 125\ GeV$ and $m(\tilde{\chi}^{0}_{1}) = 50\ GeV$. The plot shows efficiencies of the two dimuon categories, TMS-TMS (dashed red) and STA-STA (dashed green), as well as their combination (solid black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper.

Overall selection efficiencies as a function of $c\tau(\tilde{\chi}^{0}_{1})$ for the RPV SUSY model, for events with $m(\tilde{q}) = 200\ GeV$ and $m(\tilde{\chi}^{0}_{1}) = 50\ GeV$. The plot shows efficiencies of the two dimuon categories, TMS-TMS (dashed red) and STA-STA (dashed green), as well as their combination (solid black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper.

Overall selection efficiencies as a function of $c\tau(\tilde{\chi}^{0}_{1})$ for the RPV SUSY model, for events with $m(\tilde{q}) = 350\ GeV$ and $m(\tilde{\chi}^{0}_{1}) = 50\ GeV$. The plot shows efficiencies of the two dimuon categories, TMS-TMS (dashed red) and STA-STA (dashed green), as well as their combination (solid black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper.

Overall selection efficiencies as a function of $c\tau(\tilde{\chi}^{0}_{1})$ for the RPV SUSY model, for events with $m(\tilde{q}) = 700\ GeV$ and $m(\tilde{\chi}^{0}_{1}) = 50\ GeV$. The plot shows efficiencies of the two dimuon categories, TMS-TMS (dashed red) and STA-STA (dashed green), as well as their combination (solid black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper.

Overall selection efficiencies as a function of $c\tau(\tilde{\chi}^{0}_{1})$ for the RPV SUSY model, for events with $m(\tilde{q}) = 1150\ GeV$ and $m(\tilde{\chi}^{0}_{1}) = 50\ GeV$. The plot shows efficiencies of the two dimuon categories, TMS-TMS (dashed red) and STA-STA (dashed green), as well as their combination (solid black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper.

Overall selection efficiencies as a function of $c\tau(\tilde{\chi}^{0}_{1})$ for the RPV SUSY model, for events with $m(\tilde{q}) = 1600\ GeV$ and $m(\tilde{\chi}^{0}_{1}) = 50\ GeV$. The plot shows efficiencies of the two dimuon categories, TMS-TMS (dashed red) and STA-STA (dashed green), as well as their combination (solid black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper.

Overall selection efficiencies as a function of $c\tau(\tilde{\chi}^{0}_{1})$ for the RPV SUSY model, for events with $m(\tilde{q}) = 700\ GeV$ and $m(\tilde{\chi}^{0}_{1}) = 500\ GeV$. The plot shows efficiencies of the two dimuon categories, TMS-TMS (dashed red) and STA-STA (dashed green), as well as their combination (solid black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper.

Overall selection efficiencies as a function of $c\tau(\tilde{\chi}^{0}_{1})$ for the RPV SUSY model, for events with $m(\tilde{q}) = 1150\ GeV$ and $m(\tilde{\chi}^{0}_{1}) = 500\ GeV$. The plot shows efficiencies of the two dimuon categories, TMS-TMS (dashed red) and STA-STA (dashed green), as well as their combination (solid black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper.

Overall selection efficiencies as a function of $c\tau(\tilde{\chi}^{0}_{1})$ for the RPV SUSY model, for events with $m(\tilde{q}) = 1600\ GeV$ and $m(\tilde{\chi}^{0}_{1}) = 500\ GeV$. The plot shows efficiencies of the two dimuon categories, TMS-TMS (dashed red) and STA-STA (dashed green), as well as their combination (solid black). Each efficiency is computed as the ratio of the number of simulated signal events in which at least one dimuon candidate of a given type (or any type for the combined efficiency) passes all selection criteria (including the trigger) to the total number of simulated signal events. All efficiencies are corrected by the data-to-simulation scale factors described in the paper.

Signal efficiencies in the TMS-TMS dimuon category as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $L_{xy}^\mathrm{true}$ smaller than 20 cm in the HAHM signal model. The efficiency in each bin is computed as the ratio of the number of simulated signal dimuons in that bin that pass the trigger requirements and selection criteria to the total number of simulated signal dimuons in that bin and within the geometric acceptance. The geometric acceptance is defined as the generated longitudinal decay length $L_{z}$ smaller than $8\ m$ and $|\eta^\mathrm{true}|$ of both generated muons forming the dimuon smaller than 2.0. The efficiencies obtained from simulation were further corrected by the data-to-simulation scale factors described in the paper.

Signal efficiencies in the STA-STA dimuon category as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $L_{xy}^\mathrm{true}$ smaller than 20 cm in the HAHM signal model. The efficiency in each bin is computed as the ratio of the number of simulated signal dimuons in that bin that pass the trigger requirements and selection criteria to the total number of simulated signal dimuons in that bin and within the geometric acceptance. The geometric acceptance is defined as the generated longitudinal decay length $L_{z}$ smaller than $8\ m$ and $|\eta^\mathrm{true}|$ of both generated muons forming the dimuon smaller than 2.0. The efficiencies obtained from simulation were further corrected by the data-to-simulation scale factors described in the paper.

Signal efficiencies in the TMS-TMS dimuon category as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $L_{xy}^\mathrm{true}$ 20-70 cm in the HAHM signal model. The efficiency in each bin is computed as the ratio of the number of simulated signal dimuons in that bin that pass the trigger requirements and selection criteria to the total number of simulated signal dimuons in that bin and within the geometric acceptance. The geometric acceptance is defined as the generated longitudinal decay length $L_{z}$ smaller than $8\ m$ and $|\eta^\mathrm{true}|$ of both generated muons forming the dimuon smaller than 2.0. The efficiencies obtained from simulation were further corrected by the data-to-simulation scale factors described in the paper.

Signal efficiencies in the STA-STA dimuon category as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $L_{xy}^\mathrm{true}$ 20-70 cm in the HAHM signal model. The efficiency in each bin is computed as the ratio of the number of simulated signal dimuons in that bin that pass the trigger requirements and selection criteria to the total number of simulated signal dimuons in that bin and within the geometric acceptance. The geometric acceptance is defined as the generated longitudinal decay length $L_{z}$ smaller than $8\ m$ and $|\eta^\mathrm{true}|$ of both generated muons forming the dimuon smaller than 2.0. The efficiencies obtained from simulation were further corrected by the data-to-simulation scale factors described in the paper.

Signal efficiencies in the STA-STA dimuon category as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $L_{xy}^\mathrm{true}$ 70-500 cm in the HAHM signal model. The efficiency in each bin is computed as the ratio of the number of simulated signal dimuons in that bin that pass the trigger requirements and selection criteria to the total number of simulated signal dimuons in that bin and within the geometric acceptance. The geometric acceptance is defined as the generated longitudinal decay length $L_{z}$ smaller than $8\ m$ and $|\eta^\mathrm{true}|$ of both generated muons forming the dimuon smaller than 2.0. The efficiencies obtained from simulation were further corrected by the data-to-simulation scale factors described in the paper.

Signal efficiencies in the TMS-TMS dimuon category as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $L_{xy}^\mathrm{true}$ smaller than 20 cm in the RPV SUSY signal model. The efficiency in each bin is computed as the ratio of the number of simulated signal dimuons in that bin that pass the trigger requirements and selection criteria to the total number of simulated signal dimuons in that bin and within the geometric acceptance. The geometric acceptance is defined as the generated longitudinal decay length $L_{z}$ smaller than $8\ m$ and $|\eta^\mathrm{true}|$ of both generated muons forming the dimuon smaller than 2.0. The efficiencies obtained from simulation were further corrected by the data-to-simulation scale factors described in the paper.

Signal efficiencies in the STA-STA dimuon category as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $L_{xy}^\mathrm{true}$ smaller than 20 cm in the RPV SUSY signal model. The efficiency in each bin is computed as the ratio of the number of simulated signal dimuons in that bin that pass the trigger requirements and selection criteria to the total number of simulated signal dimuons in that bin and within the geometric acceptance. The geometric acceptance is defined as the generated longitudinal decay length $L_{z}$ smaller than $8\ m$ and $|\eta^\mathrm{true}|$ of both generated muons forming the dimuon smaller than 2.0. The efficiencies obtained from simulation were further corrected by the data-to-simulation scale factors described in the paper.

Signal efficiencies in the TMS-TMS dimuon category as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $L_{xy}^\mathrm{true}$ 20-70 cm in the RPV SUSY signal model. The efficiency in each bin is computed as the ratio of the number of simulated signal dimuons in that bin that pass the trigger requirements and selection criteria to the total number of simulated signal dimuons in that bin and within the geometric acceptance. The geometric acceptance is defined as the generated longitudinal decay length $L_{z}$ smaller than $8\ m$ and $|\eta^\mathrm{true}|$ of both generated muons forming the dimuon smaller than 2.0. The efficiencies obtained from simulation were further corrected by the data-to-simulation scale factors described in the paper.

Signal efficiencies in the STA-STA dimuon category as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $L_{xy}^\mathrm{true}$ 20-70 cm in the RPV SUSY signal model. The efficiency in each bin is computed as the ratio of the number of simulated signal dimuons in that bin that pass the trigger requirements and selection criteria to the total number of simulated signal dimuons in that bin and within the geometric acceptance. The geometric acceptance is defined as the generated longitudinal decay length $L_{z}$ smaller than $8\ m$ and $|\eta^\mathrm{true}|$ of both generated muons forming the dimuon smaller than 2.0. The efficiencies obtained from simulation were further corrected by the data-to-simulation scale factors described in the paper.

Signal efficiencies in the STA-STA dimuon category as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $L_{xy}^\mathrm{true}$ 70-500 cm in the RPV SUSY signal model. The efficiency in each bin is computed as the ratio of the number of simulated signal dimuons in that bin that pass the trigger requirements and selection criteria to the total number of simulated signal dimuons in that bin and within the geometric acceptance. The geometric acceptance is defined as the generated longitudinal decay length $L_{z}$ smaller than $8\ m$ and $|\eta^\mathrm{true}|$ of both generated muons forming the dimuon smaller than 2.0. The efficiencies obtained from simulation were further corrected by the data-to-simulation scale factors described in the paper.

Corrected $m(HH)$ distribution in the resolved $4b$ signal region (dots), after the fit under the background-only hypothesis. The error bars on the $4b$ points represent the Poisson uncertainties corresponding to their event yields. The background model (teal histogram) is shown with its total post-fit uncertainty (gray band). The final bin includes overflow. Representative spin-0 signal hypotheses (dashed, dotted, and dashed-dotted lines) are overlaid, normalized to the overall expected limits on their cross-sections. The bottom panel shows the difference between the $4b$ distribution and the background model, relative to the background model. No significant excess of data relative to the SM background is observed.

Corrected $m(HH)$ distribution in the resolved $4b$ signal region (dots), after the fit under the background-only hypothesis. The error bars on the $4b$ points represent the Poisson uncertainties corresponding to their event yields. The background model (teal histogram) is shown with its total post-fit uncertainty (gray band). The final bin includes overflow. Representative spin-2 signal hypotheses (dashed, dotted, and dashed-dotted lines) are overlaid, normalized to the overall expected limits on their cross-sections. The bottom panel shows the difference between the $4b$ distribution and the background model, relative to the background model. No significant excess of data relative to the SM background is observed.

Cumulative signal acceptance times efficiency as a function of the resonance mass for various selection steps in the boosted channel. The steps up to the $b$-tag categorization are shown for the spin-0.

Cumulative signal acceptance times efficiency as a function of the resonance mass for various selection steps in the boosted channel. The steps up to the $b$-tag categorization are shown for the spin-2.

Cumulative signal acceptance times efficiency as a function of the resonance mass for various selection steps in the boosted channel. The efficiencies of the three b-tag categories are shown for the spin-0 scenario; this efficiency is obtained after the other selection steps including the SR definition. The signal efficiency in the 4b region has a maximum around 1.5 TeV. Above that value the track-jets start to merge together, and for the highest resonance masses the 2b category becomes the most efficient.

Cumulative signal acceptance times efficiency as a function of the resonance mass for various selection steps in the boosted channel. The efficiencies of the three b-tag categories are shown for the spin-2 scenario; this efficiency is obtained after the other selection steps including the SR definition. The signal efficiency in the 4b region has a maximum around 1.5 TeV. Above that value the track-jets start to merge together, and for the highest resonance masses the 2b category becomes the most efficient.

Comparison of the background model (stacked histograms) with data (dots) in the $2b$ validation region. The error bars on the data points represent the Poisson uncertainties corresponding to their event yields. The background uncertainty (gray band) is computed by adding all individual components in quadrature and is not allowed to extend below zero.

Comparison of the background model (stacked histograms) with data (dots) in the $3b$ validation region. The error bars on the data points represent the Poisson uncertainties corresponding to their event yields. The background uncertainty (gray band) is computed by adding all individual components in quadrature and is not allowed to extend below zero.

Comparison of the background model (stacked histograms) with data (dots) in the $4b$ validation region. The error bars on the data points represent the Poisson uncertainties corresponding to their event yields. The background uncertainty (gray band) is computed by adding all individual components in quadrature and is not allowed to extend below zero.

The $m(HH)$ distributions in the boosted $2b$ signal regions (dots), after the fit under the background-only hypothesis. The error bars on the data points represent the Poisson uncertainties corresponding to their event yields. The background model (stacked histogram) is shown with its total post-fit uncertainty (gray band). The uncertainty bands are defined using an ensemble of curves constructed by sampling a multivariate Gaussian probability density function built from the covariance matrix of the fit. Representative spin-0 signal hypotheses (dashed and dashed-dotted lines) are overlaid, normalized to the overall expected limits on their cross-sections. No significant excess of data relative to the SM background is observed.

The $m(HH)$ distributions in the boosted $2b$ signal regions (dots), after the fit under the background-only hypothesis. The error bars on the data points represent the Poisson uncertainties corresponding to their event yields. The background model (stacked histogram) is shown with its total post-fit uncertainty (gray band). The uncertainty bands are defined using an ensemble of curves constructed by sampling a multivariate Gaussian probability density function built from the covariance matrix of the fit. Representative spin-2 signal hypotheses (dashed and dashed-dotted lines) are overlaid, normalized to the overall expected limits on their cross-sections. No significant excess of data relative to the SM background is observed.

The $m(HH)$ distributions in the boosted $3b$ signal regions (dots), after the fit under the background-only hypothesis. The error bars on the data points represent the Poisson uncertainties corresponding to their event yields. The background model (stacked histogram) is shown with its total post-fit uncertainty (gray band). The uncertainty bands are defined using an ensemble of curves constructed by sampling a multivariate Gaussian probability density function built from the covariance matrix of the fit. Representative spin-0 signal hypotheses (dashed and dashed-dotted lines) are overlaid, normalized to the overall expected limits on their cross-sections. No significant excess of data relative to the SM background is observed.

The $m(HH)$ distributions in the boosted $3b$ signal regions (dots), after the fit under the background-only hypothesis. The error bars on the data points represent the Poisson uncertainties corresponding to their event yields. The background model (stacked histogram) is shown with its total post-fit uncertainty (gray band). The uncertainty bands are defined using an ensemble of curves constructed by sampling a multivariate Gaussian probability density function built from the covariance matrix of the fit. Representative spin-2 signal hypotheses (dashed and dashed-dotted lines) are overlaid, normalized to the overall expected limits on their cross-sections. No significant excess of data relative to the SM background is observed.

The $m(HH)$ distributions in the boosted $4b$ signal regions (dots), after the fit under the background-only hypothesis. The error bars on the data points represent the Poisson uncertainties corresponding to their event yields. The background model (stacked histogram) is shown with its total post-fit uncertainty (gray band). The uncertainty bands are defined using an ensemble of curves constructed by sampling a multivariate Gaussian probability density function built from the covariance matrix of the fit. Representative spin-0 signal hypotheses (dashed and dashed-dotted lines) are overlaid, normalized to the overall expected limits on their cross-sections. No significant excess of data relative to the SM background is observed.

The $m(HH)$ distributions in the boosted $4b$ signal regions (dots), after the fit under the background-only hypothesis. The error bars on the data points represent the Poisson uncertainties corresponding to their event yields. The background model (stacked histogram) is shown with its total post-fit uncertainty (gray band). The uncertainty bands are defined using an ensemble of curves constructed by sampling a multivariate Gaussian probability density function built from the covariance matrix of the fit. Representative spin-2 signal hypotheses (dashed and dashed-dotted lines) are overlaid, normalized to the overall expected limits on their cross-sections. No significant excess of data relative to the SM background is observed.

Expected (dashed black lines) and observed (solid black lines) 95% CL upper limits on the cross-section of resonant $HH$ production in the spin-0 signal models. The $\pm 1 \sigma$ and $\pm 2 \sigma$ uncertainty ranges for the expected limits (colored bands) are shown. Expected limits using each of the resolved and boosted channels individually (dashed colored lines) are shown. The nominal $H\rightarrow b\bar{b}$ branching ratio is taken as 0.582.

Expected (dashed black lines) and observed (solid black lines) 95% CL upper limits on the cross-section of resonant $HH$ production in the spin-2 signal models. The $\pm 1 \sigma$ and $\pm 2 \sigma$ uncertainty ranges for the expected limits (colored bands) are shown. Expected limits using each of the resolved and boosted channels individually (dashed colored lines) are shown. The theoretical prediction for the bulk RS model with $k/\bar{M}_{\text{Pl}} = 1$ (solid red line) is shown; the decrease below 350 GeV is due to a sharp reduction in the $G^{*}_{\text{KK}} \rightarrow HH$ branching ratio. The nominal $H\rightarrow b\bar{b}$ branching ratio is taken as 0.582.

$v_3\{\Psi_1\}$ vs. centrality for $\pi^+$, $\pi^-$, and protons using the event plane method in $\sqrt{s_{\textrm{NN}}}=3$ GeV Au+Au collisions at STAR.

$v_3\{\Psi_1\}$ vs. centrality for $K^+$, and $K^-$ using the event plane method in $\sqrt{s_{\textrm{NN}}}=3$ GeV Au+Au collisions at STAR.

$v_3\{\Psi_1\}$ vs. centrality for $K^+$, and $K^-$ using the event plane method in $\sqrt{s_{\textrm{NN}}}=3$ GeV Au+Au collisions at STAR.

$v_3\{\Psi_1\}$ vs. rapidity for protons in three large centrality bins from a symmetric acceptance across midrapidity in $\sqrt{s_{\textrm{NN}}}=3$ GeV Au+Au collisions at STAR. Protons exhibit an increasingly negative slope as the centrality increases.

$v_3\{\Psi_1\}$ vs. rapidity for protons in three large centrality bins from a symmetric acceptance across midrapidity in $\sqrt{s_{\textrm{NN}}}=3$ GeV Au+Au collisions at STAR. Protons exhibit an increasingly negative slope as the centrality increases.

$v_3\{\Psi_1\}$ vs. rapidity for protons in three large centrality bins from only the backward region in $\sqrt{s_{\textrm{NN}}}=3$ GeV Au+Au collisions at STAR. Note that the $p_{\mathrm{T}}$ acceptance extends to a lower limit than in Fig. 6.

$v_3\{\Psi_1\}$ vs. rapidity for protons in three large centrality bins from only the backward region in $\sqrt{s_{\textrm{NN}}}=3$ GeV Au+Au collisions at STAR. Note that the $p_{\mathrm{T}}$ acceptance extends to a lower limit than in Fig. 6.

$v_3\{\Psi_1\}$ vs. $p_{\mathrm{T}}$ for protons in three large centrality bins in $\sqrt{s_{\textrm{NN}}}=3$ GeV Au+Au collisions at STAR. $v_3\{\Psi_1\}$ becomes increasingly negative as $p_{\mathrm{T}}$ and centrality increase.

$v_3\{\Psi_1\}$ vs. $p_{\mathrm{T}}$ for protons in three large centrality bins in $\sqrt{s_{\textrm{NN}}}=3$ GeV Au+Au collisions at STAR. $v_3\{\Psi_1\}$ becomes increasingly negative as $p_{\mathrm{T}}$ and centrality increase.

Expected and observed candidates for $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) as a function of the reduced mediator candidate mass.

Expected and observed candidates for $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) as a function of the reduced mediator candidate mass.

Expected and observed candidates for $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) as a function of the reduced mediator candidate mass.

Expected and observed candidates for $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) as a function of the reduced mediator candidate mass.

Expected and observed candidates for $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) as a function of the reduced mediator candidate mass.

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$0.001cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$0.003cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$0.005cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$0.007cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$0.01cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$0.025cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$0.05cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$0.1cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$0.25cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$0.5cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$1.0cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$2.5cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$5.0cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$10.0cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$25.0cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$50.0cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$100.0cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$200.0cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$400.0cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$0.001cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$0.003cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$0.005cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$0.007cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$0.01cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$0.025cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$0.05cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$0.1cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$0.25cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$0.5cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$1.0cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$2.5cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$5.0cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$10.0cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$25.0cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$50.0cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$100.0cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$200.0cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$400.0cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$0.001cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$0.003cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$0.005cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$0.007cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$0.01cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$0.025cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$0.05cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$0.1cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$0.25cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$0.5cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$1.0cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$2.5cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$5.0cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$10.0cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$25.0cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$50.0cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$100.0cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$200.0cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$400.0cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$0.001cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$0.003cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$0.005cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$0.007cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$0.01cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$0.025cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$0.05cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$0.1cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$0.25cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$0.5cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$1.0cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$2.5cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$5.0cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$10.0cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$25.0cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$50.0cm

Expected and observed limits on $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$100.0cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$0.001cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$0.003cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$0.005cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$0.007cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$0.01cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$0.025cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$0.05cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$0.1cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$0.25cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$0.5cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$1.0cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$2.5cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$5.0cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$10.0cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$25.0cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$50.0cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$100.0cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$200.0cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to e^+e^-$) for a lifetime of $c\tau=$400.0cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$0.001cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$0.003cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$0.005cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$0.007cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$0.01cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$0.025cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$0.05cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$0.1cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$0.25cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$0.5cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$1.0cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$2.5cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$5.0cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$10.0cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$25.0cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$50.0cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$100.0cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$200.0cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$) for a lifetime of $c\tau=$400.0cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$0.001cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$0.003cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$0.005cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$0.007cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$0.01cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$0.025cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$0.05cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$0.1cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$0.25cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$0.5cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$1.0cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$2.5cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$5.0cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$10.0cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$25.0cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$50.0cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$100.0cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$200.0cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$) for a lifetime of $c\tau=$400.0cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$0.001cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$0.003cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$0.005cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$0.007cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$0.01cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$0.025cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$0.05cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$0.1cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$0.25cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$0.5cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$1.0cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$2.5cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$5.0cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$10.0cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$25.0cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$50.0cm

Expected and observed limits on $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to K^+K^-$) for a lifetime of $c\tau=$100.0cm

Efficiencies for $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to e^+e^-$)

Efficiencies for $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$)

Efficiencies for $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$)

Efficiencies for $\mathcal{B}($$B^+\to K^+S$$) \times$ $\mathcal{B}($$S\to K^+K^-$)

Efficiencies for $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to e^+e^-$)

Efficiencies for $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \mu^+\mu^-$)

Efficiencies for $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to \pi^+\pi^-$)

Efficiencies for $\mathcal{B}($$B^0\to K^{*0}(\to K^+\pi^-)S$$) \times$ $\mathcal{B}($$S\to K^+K^-$)

Upper 95% CL limits on HH signal cross section scanned over the $\kappa_{\lambda}$ parameter while fixing the $\kappa_{2V}$ and $\kappa_{V}$ to their SM-predicted values.

Upper 95% CL limits on VHH signal cross section scanned over the $\kappa_{2V}$ parameter while fixing the $\kappa_{\lambda}$ and $\kappa_{V}$ to their SM-predicted values.

Upper 95% CL limits on HH signal cross section scanned over the $\kappa_{2V}$ parameter while fixing the $\kappa_{\lambda}$ and $\kappa_{V}$ to their SM-predicted values.

Upper 95% CL limits on VHH signal cross section scanned over the $\kappa_{V}$ parameter while fixing the $\kappa_{2V}$ and $\kappa_{\lambda}$ to their SM-predicted values.

Upper 95% CL limits on HH signal cross section scanned over the $\kappa_{V}$ parameter while fixing the $\kappa_{2V}$ and $\kappa_{\lambda}$ to their SM-predicted values.

$\Delta\phi$ projection of balance function in low $p_{T}$ in 0-10% centrality

$\Delta\phi$ projection of balance function in low $p_{T}$ in 30-40% centrality

1D $\Delta\eta$ projection of balance function in low $p_{T}$ in 70-80% centrality

$\Delta\eta$ projection of balance function in low $p_{T}$ in 0-40 $N_{trk}$

$\Delta\eta$ projection of balance function in low $p_{T}$ in 120-150 $N_{trk}$

$\Delta\eta$ projection of balance function in low $p_{T}$ in 270-300 $N_{trk}$

$\Delta\phi$ projection of balance function in low $p_{T}$ in 0-40 $N_{trk}$

$\Delta\phi$ projection of balance function in low $p_{T}$ in 120-150 $N_{trk}$

$\Delta\phi$ projection of balance function in low $p_{T}$ in 270-300 $N_{trk}$

The width of balance function in $<|\Delta\eta|>$ in low $p_{T}$ for PbPb collisions

Balance function width in low $p_{T}$ PbPb relative $<|\Delta\eta|>/<|\Delta\eta|>_{N_{ch}<65}$

The width of balance function in $<|\Delta\eta|>$ in low $p_{T}$ for pPb collisions

Balance function width in low $p_{T}$ in pPb relative $<|\Delta\eta|>/<|\Delta\eta|>_{N_{ch}<24}$

The width of the balance function in $<|\Delta\phi|>$ in low $p_{T}$ for PbPb collisions

Balance function width in low $p_{T}$ in PbPb for relative $<|\Delta\phi|>/<|\Delta\phi|>_{N_{ch}<65}$

The width of the balance function in $<|\Delta\phi|>$ in low $p_{T}$ for pPb collisions

Balance function width in low $p_{T}$ in pPb for relative $|\Delta\phi|/<|\Delta\phi|>_{N_{ch}<24}$

Balance function projection as a function of $\Delta\eta$ in intermediate $p_{T}$ in PbPb for 0-10% centrality

Balance function projection as a function of $\Delta\eta$ in intermediate $p_{T}$ in PbPb for 30-40% centrality

Balance function projection as a function of $\Delta\eta$ in intermediate $p_{T}$ in PbPb for 70-80% centrality

Balance function projection as a function of $\Delta\phi$ in intermediate $p_{T}$ in PbPb for 0-10% centrality

Balance function projection as a function of $\Delta\phi$ in intermediate $p_{T}$ in PbPb for 30-40% centrality

Balance function projection as a function of $\Delta\phi$ in intermediate $p_{T}$ in PbPb for 70-80% centrality

Balance function projection as a function of $\Delta\eta$ in intermediate $p_{T}$ in pPb for 0-40 $N_{trk}$

Balance function projection as a function of $\Delta\eta$ in intermediate $p_{T}$ in pPb for 120-150 $N_{trk}$

Balance function projection as a function of $\Delta\eta$ in intermediate $p_{T}$ in pPb for 270-300 $N_{trk}$

Balance function projection as a function of $\Delta\phi$ in intermediate $p_{T}$ in pPb for $N_{trk}$ 0-40

Balance function projection as a function of $\Delta\phi$ in intermediate $p_{T}$ in pPb for $N_{trk}$ 120-150

Balance function projection as a function of $\Delta\phi$ in intermediate $p_{T}$ in pPb for $N_{trk}$ 270-300

Balance function projection as a function of $\Delta\eta$ in high $p_{T}$ in PbPb for 0-10% centrality

Balance function projection as a function of $\Delta\eta$ in high $p_{T}$ in PbPb for 30-40% centrality

Balance function projection as a function of $\Delta\eta$ in high $p_{T}$ in PbPb for 70-80% centrality

Balance function projection as a function of $\Delta\phi$ in high $p_{T}$ in PbPb for 0-10% centrality

Balance function projection as a function of $\Delta\phi$ in high $p_{T}$ in PbPb for 30-40% centrality

Balance function projection as a function of $\Delta\phi$ in high $p_{T}$ in PbPb for 70-80% centrality

Balance function projection as a function of $\Delta\eta$ in high $p_{T}$ in pPb for $N_{trk}$ 0-40

Balance function projection as a function of $\Delta\eta$ in high $p_{T}$ in pPb for $N_{trk}$ 120-150

Balance function projection as a function of $\Delta\eta$ in high $p_{T}$ in pPb for $N_{trk}$ 270-300

Balance function projection as a function of $\Delta\phi$ in high $p_{T}$ in PbPb for $N_{trk}$ 0-40

Balance function projection as a function of $\Delta\phi$ in high $p_{T}$ in PbPb for $N_{trk}$ 120-150

Balance function projection as a function of $\Delta\phi$ in high $p_{T}$ in PbPb for $N_{trk}$ 270-300

Average width of the balance function in $\Delta \eta$ with $N_{ch}$ for low $p_{T}$

Average width of the balance function in $\Delta \eta$ with $N_{ch}$ for intermediate $p_{T}$

Average width of the balance function in $\Delta \eta$ with $N_{ch}$ for high $p_{T}$

Average width of the balance function in $\Delta \phi$ with $p_{T}$ for low $p_{T}$

Average width of the balance function in $\Delta \phi$ with $N_{ch}$ for intermediate $p_{T}$

Average width of the balance function in $\Delta \phi$ with $N_{ch}$ for high $p_{T}$

Average width of the balance function in $\Delta \eta$ with $N_{ch}$ for low $p_{T}$

Average width of the balance function in $\Delta \eta$ with $N_{ch}$ for intermediate $p_{T}$

Average width of the balance function in $\Delta \phi$ with $N_{ch}$ for high $p_{T}$

Average width of the balance function in $\Delta \phi$ with $N_{ch}$ for low $p_{T}$

Average width of the balance function in $\Delta \phi$ with $N_{ch}$ for intermediate $p_{T}$

Average width of the balance function in $\Delta \phi$ with $N_{ch}$ for high $p_{T}$

The total coherent $\mathrm{J}/\psi$ photoproduction cross section as a function of photon-nuclear center-of-mass energy per nucleon $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$, measured in PbPb ultra-peripheral collisions at $\sqrt{s_{\mathrm{NN}}}$ = 5.02 TeV. The $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$ values used correspond to the center of each rapidity range. The theoretical uncertainties is due to the uncertainties in the photon flux.

The nuclear gluon suppression factor $R_{\mathrm{g}}^{\mathrm{Pb}}$ as a function of Bjorken $x$ extracted from the CMS measurement of the coherent $\mathrm{J}/\psi$ photoproduction in PbPb ultra-peripheral collisions at $\sqrt{s_{\mathrm{NN}}}$ = 5.02 TeV. The $x$ values are evaluated at the centers of their corresponding rapidity ranges. The theoretical uncertainties are due to the uncertainties in the photon flux and the impulse approximation model.

The nuclear gluon suppression factor $R_{\mathrm{g}}^{\mathrm{Pb}}$ as a function of Bjorken $x$ extracted from the CMS measurement of the coherent $\mathrm{J}/\psi$ photoproduction in PbPb ultra-peripheral collisions at $\sqrt{s_{\mathrm{NN}}}$ = 5.02 TeV. The $x$ values are evaluated at the centers of their corresponding rapidity ranges. The theoretical uncertainties are due to the uncertainties in the photon flux and the impulse approximation model.

The total covariance matrix of the total coherent photoproduction cross section as a function of photon-nuclear center-of-mass energy per nucleon $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$. The covariance matrix includes both the experimental and theoretical (photon flux) uncertainties. The bins are ordered as increasing in $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$.

The photon flux values from STARLight as a function of rapidity, in different neutron multiplicity classes: 0n0n, 0nXn, and XnXn.

The experimental covariance matrix of the total coherent photoproduction cross section as a function of photon-nuclear center-of-mass energy per nucleon $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$. The bins are ordered as increasing in $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$.

The covariance matrix for the flux in the 0n0n neutron multiplicity class.

The theoretical (photon flux) covariance matrix of the total coherent photoproduction cross section as a function of photon-nuclear center-of-mass energy per nucleon $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$. The bins are ordered as increasing in $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$.

The covariance matrix for the flux in the 0nXn neutron multiplicity class.

The covariance matrix for the flux in the XnXn neutron multiplicity class.

The total covariance matrix of the total coherent photoproduction cross section as a function of photon-nuclear center-of-mass energy per nucleon $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$. The covariance matrix includes both the experimental and theoretical (photon flux) uncertainties. The bins are ordered as increasing in $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$.

The experimental covariance matrix of the total coherent photoproduction cross section as a function of photon-nuclear center-of-mass energy per nucleon $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$. The bins are ordered as increasing in $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$.

The theoretical (photon flux) covariance matrix of the total coherent photoproduction cross section as a function of photon-nuclear center-of-mass energy per nucleon $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$. The bins are ordered as increasing in $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$.

The elliptic flow after nonflow subtraction, $v_{2}^{sub}/4$, for $f_0(980)$ as a function of $<KE_{T}>/4$ in pPb collision at 8.16 TeV.

The elliptic flow after nonflow subtraction, $v_{2}^{sub}/2$, for $f_0(980)$ as a function of $<p_{T}>/2$ in pPb collision at 8.16 TeV.

The elliptic flow after nonflow subtraction, $v_{2}^{sub}/4$, for $f_0(980)$ as a function of $<p_{T}>/4$ in pPb collision at 8.16 TeV.

Two-dimensional distribution of the invariant mass $m_{DV}$ and the track multiplicity in the High-pT jet SR for expected signal events in the strong gluino pair pair production model with m(gluino)=1.8 TeV, m(chi0)=0.2 TeV, tau(chi0)=0.1 ns

Two-dimensional distribution of the invariant mass $m_{DV}$ and the track multiplicity in the Trackless jet SR for observed data events

Two-dimensional distribution of the invariant mass $m_{DV}$ and the track multiplicity in the Trackless jet SR for expected signal events in the electroweak pair production model

Expected exclusion limits at 95% CL on the lifetime and mass of the neutralino in electroweakino pair production models

Expected (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in electroweakino pair production models

Expected (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in electroweakino pair production models

Observed exclusion limits at 95% CL on the lifetime and mass of the neutralino in electroweakino pair production models

Observed (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in electroweakino pair production models

Observed (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in electroweakino pair production models

Expected exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.4 TeV

Expected (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.4 TeV

Expected (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.4 TeV

Observed exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.4 TeV

Observed (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.4 TeV

Observed (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.4 TeV

Exclusion limits at 95% CL on the production cross section in the electroweak pair production model.

Exclusion limits at 95% CL on the production cross section in the strong gluino pair production models and m(gluino)=2.4 TeV

Expected exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.0 TeV

Expected (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.0 TeV

Expected (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.0 TeV

Observed exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.0 TeV

Observed (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.0 TeV

Observed (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.0 TeV

Expected exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.2 TeV

Expected (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.2 TeV

Expected (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.2 TeV

Observed exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.2 TeV

Observed (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.2 TeV

Observed (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.2 TeV

Expected exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=50 GeV

Expected (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=50 GeV

Expected (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=50 GeV

Observed exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=50 GeV

Observed (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=50 GeV

Observed (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=50 GeV

Expected exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=450 GeV

Expected (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=450 GeV

Expected (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=450 GeV

Observed exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=450 GeV

Observed (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=450 GeV

Observed (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=450 GeV

Expected exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.01 ns

Expected (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.01 ns

Expected (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.01 ns

Observed exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.01 ns

Observed (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.01 ns

Observed (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.01 ns

Expected exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.1 ns

Expected (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.1 ns

Expected (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.1 ns

Observed exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.1 ns

Observed (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.1 ns

Observed (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.1 ns

Expected exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=1 ns

Expected (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=1 ns

Expected (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=1 ns

Observed exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=1 ns

Observed (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=1 ns

Observed (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=1 ns

Expected exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=10 ns

Expected (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=10 ns

Expected (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=10 ns

Observed exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=10 ns

Observed (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=10 ns

Observed (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=10 ns

Exclusion limits at 95% CL on the production cross section in the strong gluino pair production models and m($ ilde{\chi}^0_1$)=1.25 TeV

Acceptance cutflow for the High-pT SR for representative points in the strong gluino pair production model. See additional resources for more information.

Acceptance cutflow for the Trackless SR for representative points in the electroweak pair production model. See additional resources for more information.

Acceptance cutflow for the Trackless SR for representative points in the electroweak pair production model with heavy-flavor quarks final state. See additional resources for more information.

Acceptance cutflow for the High-pT SR for representative points in the electroweak pair production model with heavy-flavor quarks final state. See additional resources for more information.

Reinterpretation Material: Event-level Efficiency for HighPt SR selections, R < 1150 mm

Reinterpretation Material: Event-level Efficiency for HighPt SR selections, R [1150, 3870] mm

Reinterpretation Material: Event-level Efficiency for HighPt SR selections, R > 3870 mm

Reinterpretation Material: Event-level Efficiency for Trackless SR selections, R < 1150 mm

Reinterpretation Material: Event-level Efficiency for Trackless SR selections, R [1150, 3870] mm

Reinterpretation Material: Event-level Efficiency for Trackless SR selections, R > 3870 mm

Reinterpretation Material: Vertex-level Efficiency for R < 22 mm

Reinterpretation Material: Vertex-level Efficiency for R [22, 25] mm

Reinterpretation Material: Vertex-level Efficiency for R [25, 29] mm

Reinterpretation Material: Vertex-level Efficiency for R [29, 38] mm

Reinterpretation Material: Vertex-level Efficiency for R [38, 46] mm

Reinterpretation Material: Vertex-level Efficiency for R [46, 73] mm

Reinterpretation Material: Vertex-level Efficiency for R [73, 84] mm

Reinterpretation Material: Vertex-level Efficiency for R [84, 111] mm

Reinterpretation Material: Vertex-level Efficiency for R [111, 120] mm

Reinterpretation Material: Vertex-level Efficiency for R [120, 145] mm

Reinterpretation Material: Vertex-level Efficiency for R [145, 180] mm

Reinterpretation Material: Vertex-level Efficiency for R [180, 300] mm

Cutflow (acceptance x efficiency) for the High-pT SR for representative points in the strong gluino pair production model. See additional resources for more information.

Cutflow (acceptance x efficiency) for the Trackless SR for representative points in the electroweak pair production model. See additional resources for more information.

Cutflow (acceptance x efficiency) for the Trackless SR for representative points in the electroweak pair production model with heavy-flavor quarks. See additional resources for more information.

Cutflow (acceptance x efficiency) for the High-pT SR for representative points in the electroweak pair production model with heavy-flavor quarks. See additional resources for more information.

Distribution of the missing transverse momentum in validation region VR2. The solid histograms are stacked to show the SM expectations after the 2&times;2D background estimation technique is applied. Background and signal predictions are normalised to the luminosity. The background category "h (other)" includes events originating from VBF, Vh, ggF, thq, thW and bb&#772;h, all subdominant in this signature. Statistical and systematic uncertainties are indicated by the shaded area. The lower panel of each plot shows the ratio of the data to the SM prediction for the respective bin. The first and last bins include the underflows and overflows respectively.

Distribution of the diphoton invariant mass with all selections of the signal regions applied, except on m_{&gamma;&gamma;} itself, for signal region SR1h. The background estimation techniques described in the text are applied. The different backgrounds are stacked to add up to the total SM prediction in each bin. The predicted yields for signal benchmark models of varying &chi;&#771;⁰₁ mass are also overlaid (not stacked) assuming B(&chi;&#771;⁰₁ &rarr; hG&#771; ) to equal 100%. Background and signal predictions are normalised to the luminosity. The background category "h (other)" includes events originating from VBF, Vh, ggF, thq, thW and bb&#772;h, all subdominant in this signature. The sizes of the statistical and systematic uncertainties are indicated by the shaded areas. The lower panels show the ratio of the data to the SM prediction. Arrows indicate the borders of the signal region (|m_{&gamma;&gamma;}-125 GeV|&lt;5 GeV). The first and last bins include the underflows and overflows respectively.

Distribution of the diphoton invariant mass with all selections of the signal regions applied, except on m_{&gamma;&gamma;} itself, for signal region SR1Z. The background estimation techniques described in the text are applied. The different backgrounds are stacked to add up to the total SM prediction in each bin. The predicted yields for signal benchmark models of varying &chi;&#771;⁰₁ mass are also overlaid (not stacked) assuming B(&chi;&#771;⁰₁ &rarr; hG&#771; ) to equal 50%. Background and signal predictions are normalised to the luminosity. The background category "h (other)" includes events originating from VBF, Vh, ggF, thq, thW and bb&#772;h, all subdominant in this signature. The sizes of the statistical and systematic uncertainties are indicated by the shaded areas. The lower panels show the ratio of the data to the SM prediction. Arrows indicate the borders of the signal region (|m_{&gamma;&gamma;}-125 GeV|&lt;5 GeV). The first and last bins include the underflows and overflows respectively.

Distribution of the diphoton invariant mass with all selections of the signal regions applied, except on m_{&gamma;&gamma;} itself, for signal region SR2. The background estimation techniques described in the text are applied. The different backgrounds are stacked to add up to the total SM prediction in each bin. The predicted yields for signal benchmark models of varying &chi;&#771;⁰₁ mass are also overlaid (not stacked) assuming B(&chi;&#771;⁰₁ &rarr; hG&#771; ) to equal 100%. Background and signal predictions are normalised to the luminosity. The background category "h (other)" includes events originating from VBF, Vh, ggF, thq, thW and bb&#772;h, all subdominant in this signature. The sizes of the statistical and systematic uncertainties are indicated by the shaded areas. The lower panels show the ratio of the data to the SM prediction. Arrows indicate the borders of the signal region (|m_{&gamma;&gamma;}-125 GeV|&lt;5 GeV). The first and last bins include the underflows and overflows respectively.

Observed and expected limits on the pure higgsino cross-section at 95% CL assuming B(&chi;&#771;⁰₁ &rarr; hG&#771; )=100% for different &chi;&#771;⁰₁ masses, obtained by a statistical combination of the three signal regions SR1h, SR1Z and SR2. The inner and outer bands indicate the 1&sigma; and 2&sigma; variation on the expected limit respectively.

Observed and expected 95% CL limits on the pure-higgsino branching fraction to B(&chi;&#771;⁰₁ &rarr; hG&#771; ) as a function of the higgsino mass m(&chi;&#771;⁰₁) assuming it decays via either &chi;&#771;⁰₁&rarr; hG&#771; or &chi;&#771;⁰₁&rarr; ZG&#771;. Limits are obtained by performing a statistical combination of the three signal regions SR1h, SR1Z and SR2. The &plusmn; 1&sigma; variation on the expected limit is shown. The dotted lines indicate the observed limit obtained by a variation of theoretical prediction for the neutralino production cross-section by &plusmn;1 &sigma;. Values of B(&chi;&#771;⁰₁ &rarr; hG&#771; ) larger than the observed 95% CL limit are excluded, as indicated by the hatched area.

Observed and expected 95% CL limits on the pure-higgsino branching fraction to B(&chi;&#771;⁰₁ &rarr; hG&#771; ) as a function of the higgsino mass m(&chi;&#771;⁰₁) assuming it decays via either &chi;&#771;⁰₁&rarr; hG&#771; or &chi;&#771;⁰₁&rarr; ZG&#771;. Limits are obtained by performing a statistical combination of the three signal regions SR1h, SR1Z and SR2. The &plusmn; 1&sigma; variation on the expected limit is shown. The dotted lines indicate the observed limit obtained by a variation of theoretical prediction for the neutralino production cross-section by &plusmn;1 &sigma;. Values of B(&chi;&#771;⁰₁ &rarr; hG&#771; ) larger than the observed 95% CL limit are excluded, as indicated by the hatched area.

Observed and expected 95% CL limits on the pure-higgsino branching fraction to B(&chi;&#771;⁰₁ &rarr; hG&#771; ) as a function of the higgsino mass m(&chi;&#771;⁰₁) assuming it decays via either &chi;&#771;⁰₁&rarr; hG&#771; or &chi;&#771;⁰₁&rarr; ZG&#771;. Limits are obtained by performing a statistical combination of the three signal regions SR1h, SR1Z and SR2. The &plusmn; 1&sigma; variation on the expected limit is shown. The dotted lines indicate the observed limit obtained by a variation of theoretical prediction for the neutralino production cross-section by &plusmn;1 &sigma;. Values of B(&chi;&#771;⁰₁ &rarr; hG&#771; ) larger than the observed 95% CL limit are excluded, as indicated by the hatched area.

Observed and expected 95% CL limits on the pure-higgsino branching fraction to B(&chi;&#771;⁰₁ &rarr; hG&#771; ) as a function of the higgsino mass m(&chi;&#771;⁰₁) assuming it decays via either &chi;&#771;⁰₁&rarr; hG&#771; or &chi;&#771;⁰₁&rarr; ZG&#771;. Limits are obtained by performing a statistical combination of the three signal regions SR1h, SR1Z and SR2. The &plusmn; 1&sigma; variation on the expected limit is shown. The dotted lines indicate the observed limit obtained by a variation of theoretical prediction for the neutralino production cross-section by &plusmn;1 &sigma;. Values of B(&chi;&#771;⁰₁ &rarr; hG&#771; ) larger than the observed 95% CL limit are excluded, as indicated by the hatched area.

Observed and expected 95% CL limits on the pure-higgsino branching fraction to B(&chi;&#771;⁰₁ &rarr; hG&#771; ) as a function of the higgsino mass m(&chi;&#771;⁰₁) assuming it decays via either &chi;&#771;⁰₁&rarr; hG&#771; or &chi;&#771;⁰₁&rarr; ZG&#771;. Limits are obtained by performing a statistical combination of the three signal regions SR1h, SR1Z and SR2. The &plusmn; 1&sigma; variation on the expected limit is shown. The dotted lines indicate the observed limit obtained by a variation of theoretical prediction for the neutralino production cross-section by &plusmn;1 &sigma;. Values of B(&chi;&#771;⁰₁ &rarr; hG&#771; ) larger than the observed 95% CL limit are excluded, as indicated by the hatched area.

Observed and expected 95% CL limits on the pure-higgsino branching fraction to B(&chi;&#771;⁰₁ &rarr; hG&#771; ) as a function of the higgsino mass m(&chi;&#771;⁰₁) assuming it decays via either &chi;&#771;⁰₁&rarr; hG&#771; or &chi;&#771;⁰₁&rarr; ZG&#771;. Limits are obtained by performing a statistical combination of the three signal regions SR1h, SR1Z and SR2. The &plusmn; 1&sigma; variation on the expected limit is shown. The dotted lines indicate the observed limit obtained by a variation of theoretical prediction for the neutralino production cross-section by &plusmn;1 &sigma;. Values of B(&chi;&#771;⁰₁ &rarr; hG&#771; ) larger than the observed 95% CL limit are excluded, as indicated by the hatched area.

Numbers of signal and background events in the signal regions. The respective background estimation techniques are applied. The background category "h (other)" includes events originating from VBF, Vh, ggF, thq, thW and bb&#772;h, all subdominant in this signature. The different backgrounds are stacked to add up to the total Standard Model prediction in each bin. The predicted yields for signal benchmark models of varying &chi;&#771;⁰₁ mass are also plotted (not stacked), assuming B(&chi;&#771;⁰₁ &rarr; hG&#771; )=100% and a &chi;&#771;⁰₁ mass of 130 or 200 GeV. The statistical and systematic uncertainties are indicated by the shaded areas in the top plot. The bottom panel shows the statistical significance&nbsp;<a href="https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2020-025/">[Ref]</a> of the difference between the SM prediction and the observed data in each region.

Observed 95% CL limits in pb on the pure higgsino cross-section, shown in the m(&chi;&#771;⁰₁)-B(&chi;&#771;⁰₁ &rarr; hG&#771; ) plane. Limits are obtained by a statistical combination of the three signal regions SR1h, SR1Z and SR2, assuming the neutralino to decay via either &chi;&#771;⁰₁&rarr; hG&#771; or &chi;&#771;⁰₁&rarr; ZG&#771;.

Acceptances for all signal model points considered in the analysis, shown in the m(&chi;&#771;⁰₁)-B(&chi;&#771;⁰₁ &rarr; hG&#771; ) plane. Acceptances are provided separately for signal region SR1h, assuming the neutralino to decay via either &chi;&#771;⁰₁&rarr; hG&#771; or &chi;&#771;⁰₁&rarr; ZG&#771;.

Acceptances for all signal model points considered in the analysis, shown in the m(&chi;&#771;⁰₁)-B(&chi;&#771;⁰₁ &rarr; hG&#771; ) plane. Acceptances are provided separately for signal region SR1Z, assuming the neutralino to decay via either &chi;&#771;⁰₁&rarr; hG&#771; or &chi;&#771;⁰₁&rarr; ZG&#771;.

Acceptances for all signal model points considered in the analysis, shown in the m(&chi;&#771;⁰₁)-B(&chi;&#771;⁰₁ &rarr; hG&#771; ) plane. Acceptances are provided separately for signal region SR2, assuming the neutralino to decay via either &chi;&#771;⁰₁&rarr; hG&#771; or &chi;&#771;⁰₁&rarr; ZG&#771;.

Efficiencies for all signal model points considered in the analysis, shown in the m(&chi;&#771;⁰₁)-B(&chi;&#771;⁰₁ &rarr; hG&#771; ) plane. Efficiencies are provided separately for signal region SR1h, assuming the neutralino to decay via either &chi;&#771;⁰₁&rarr; hG&#771; or &chi;&#771;⁰₁&rarr; ZG&#771;.

Efficiencies for all signal model points considered in the analysis, shown in the m(&chi;&#771;⁰₁)-B(&chi;&#771;⁰₁ &rarr; hG&#771; ) plane. Efficiencies are provided separately for signal region SR1Z, assuming the neutralino to decay via either &chi;&#771;⁰₁&rarr; hG&#771; or &chi;&#771;⁰₁&rarr; ZG&#771;.

Efficiencies for all signal model points considered in the analysis, shown in the m(&chi;&#771;⁰₁)-B(&chi;&#771;⁰₁ &rarr; hG&#771; ) plane. Efficiencies are provided separately for signal region SR2, assuming the neutralino to decay via either &chi;&#771;⁰₁&rarr; hG&#771; or &chi;&#771;⁰₁&rarr; ZG&#771;.

Observed and expected numbers of events in the three signal regions. The background category "h (other)" includes events originating from VBF, Vh, ggF, thq, thW and bb&#772;h, all subdominant in this signature. The table also includes model-independent 95% CL upper limits on the visible number of BSM events (S⁹⁵_obs), the number of BSM events given the expected number of background events (S⁹⁵_exp) and the visible BSM cross-section (&lang;&epsilon; &sigma;&rang;_obs⁹⁵), all calculated from pseudo-experiments. The discovery p-value (p₀) is also shown and its value is capped at 0.5 if the observed number of events is below the expected number of events.

Cutflows of two benchmark signal points assuming B(&chi;&#771;⁰₁ &rarr; hG&#771; )=100% for all three discovery signal regions. The initial selection includes the leptons veto. Only statistical uncertainties are included. Expected yields are normalised to a luminosity of 139 fb^-1.

Unfolded E2C distributions in data compared to MC predictions.

Unfolded E2C distributions in data compared to MC predictions.

Unfolded E2C distributions in data compared to MC predictions.

Unfolded E2C distributions in data compared to MC predictions.

Unfolded E2C distributions in data compared to MC predictions.

Unfolded E3C distributions in data compared to MC predictions.

Unfolded E3C distributions in data compared to MC predictions.

Unfolded E3C distributions in data compared to MC predictions.

Unfolded E3C distributions in data compared to MC predictions.

Unfolded E3C distributions in data compared to MC predictions.

Unfolded E3C distributions in data compared to MC predictions.

Unfolded E3C distributions in data compared to MC predictions.

Unfolded E3C distributions in data compared to MC predictions.

Unfolded E3C/E2C distributions in data compared to NLO+NNLL_approx predictions. Theoretial uncertainty in each bin is handled fully correlated as shape uncertainty. For the one-sided uncertainties, we symmetrize them when performing the fit.

Unfolded E3C/E2C distributions in data compared to NLO+NNLL_approx predictions. Theoretial uncertainty in each bin is handled fully correlated as shape uncertainty. For the one-sided uncertainties, we symmetrize them when performing the fit.

Unfolded E3C/E2C distributions in data compared to NLO+NNLL_approx predictions. Theoretial uncertainty in each bin is handled fully correlated as shape uncertainty. For the one-sided uncertainties, we symmetrize them when performing the fit.

Unfolded E3C/E2C distributions in data compared to NLO+NNLL_approx predictions. Theoretial uncertainty in each bin is handled fully correlated as shape uncertainty. For the one-sided uncertainties, we symmetrize them when performing the fit.

Unfolded E3C/E2C distributions in data compared to NLO+NNLL_approx predictions. Theoretial uncertainty in each bin is handled fully correlated as shape uncertainty. For the one-sided uncertainties, we symmetrize them when performing the fit.

Unfolded E3C/E2C distributions in data compared to NLO+NNLL_approx predictions. Theoretial uncertainty in each bin is handled fully correlated as shape uncertainty. For the one-sided uncertainties, we symmetrize them when performing the fit.

Unfolded E3C/E2C distributions in data compared to NLO+NNLL_approx predictions. Theoretial uncertainty in each bin is handled fully correlated as shape uncertainty. For the one-sided uncertainties, we symmetrize them when performing the fit.

Unfolded E3C/E2C distributions in data compared to NLO+NNLL_approx predictions. Theoretial uncertainty in each bin is handled fully correlated as shape uncertainty. For the one-sided uncertainties, we symmetrize them when performing the fit.

The fitted slopes of the E3C/E2C data distributions as a function of jet pt are used to illustrate the dependency of alphas on jet pt.

Unfolded E3C/E2C distributions in data compared to MC predictions.

Unfolded E3C/E2C distributions in data compared to MC predictions.

Unfolded E3C/E2C distributions in data compared to MC predictions.

Unfolded E3C/E2C distributions in data compared to MC predictions.

Unfolded E3C/E2C distributions in data compared to MC predictions.

Unfolded E3C/E2C distributions in data compared to MC predictions.

Unfolded E3C/E2C distributions in data compared to MC predictions.

Unfolded E3C/E2C distributions in data compared to MC predictions.

The chi2 scan result using eq.3 for different alphas.

The correlation matrix is composed by 10 jet pt region, each region is represented by a block in the plot. Inside each block, there are 22 xL bins same as the E2C, E3C and E3C/E2C distributions. Therefore, the x and y bins of the correlation matrix is given by, binNumber = pT_index * 22 + xL_index.

The correlation matrix is composed by 10 jet pt region, each region is represented by a block in the plot. Inside each block, there are 22 xL bins same as the E2C, E3C and E3C/E2C distributions. Therefore, the x and y bins of the correlation matrix is given by, binNumber = pT_index * 22 + xL_index.

The correlation matrix is composed by 10 jet pt region, each region is represented by a block in the plot. Inside each block, there are 22 xL bins same as the E2C, E3C and E3C/E2C distributions. Therefore, the x and y bins of the correlation matrix is given by, binNumber = pT_index * 22 + xL_index.

The energy weight of E2C as defined in eq.1 in the paper is used in the unfolding, the binning is listed in this table.

The energy weight of E3C as defined in eq.1 in the paper is used in the unfolding, the binning is listed in this table.

Differential cross sections normalized to the fiducial cross section as a function of the $|\eta|$ of the highest-$p_T$ jet

Differential cross sections normalized to the fiducial cross section as a function of the $|\eta|$ of the second-highest-$p_T$ jet

Differential cross sections normalized to the fiducial cross section as a function of the pseudorapidity difference between the two highest-$p_T$ jets in the event

Differential cross sections normalized to the fiducial cross section as a function of the invariant mass of the two highest-$p_T$ jets in the event

Differential cross sections normalized to the fiducial cross section as a function of the invariant mass of the four-lepton system, in the full $m_{4l}$ range

Differential cross sections normalized to the fiducial cross section as a function of the invariant mass of the four-lepton system in events with 0 jet, in the on-shell ZZ region

Differential cross sections normalized to the fiducial cross section as a function of the invariant mass of the four-lepton system in events with 1 jet, in the on-shell ZZ region

Differential cross sections normalized to the fiducial cross section as a function of the invariant mass of the four-lepton system in events with 2 jets, in the on-shell ZZ region

Differential cross sections normalized to the fiducial cross section as a function of the invariant mass of the four-lepton system in events with at least 3 jets, in the on-shell ZZ region

Differential cross sections normalized to the fiducial cross section as a function of the invariant mass of the four-lepton system in events with 0 jet, in the full $m_{4l}$ range

Differential cross sections normalized to the fiducial cross section as a function of the invariant mass of the four-lepton system in events with 1 jet, in the full $m_{4l}$ range

Differential cross sections normalized to the fiducial cross section as a function of the invariant mass of the four-lepton system in events with 2 jets, in the full $m_{4l}$ range

Differential cross sections normalized to the fiducial cross section as a function of the invariant mass of the four-lepton system in events with at least 3 jets, in the full $m_{4l}$ range

Bayesian upper exclusion limits at 95% CL on the product of the production cross section and branching fraction of a QBH in an associated $ au$ lepton and neutrino final state. Minimum threshold masses $m_{th}$ of up to 6.6 TeV are excluded at 95% CL. The observed limit (solid line) is obtained from the intersection with the LO QBH cross section (blue dotted curve). The 68 and 95% quantiles of the limits are represented by the green and yellow bands, respectively.

Bayesian upper limits at 95% CL on the cross section of the process $pp\rightarrow\tau\nu$ mediated via LQ exchange in the t-channel. The inner (green) band and the outer (yellow) band indicate the regions containing 68 and 95%, respectively, of the distribution of limits expected under the background-only hypothesis. The predicted LQ cross section at LO in the three coupling benchmark scenarios is depicted in different colors for $g_{U}=1$. The uncertainty bandy correspond to the sum in quadrature of PDF and scale variations. The first benchmark scenario considers only couplings to left-handed SM fermions (i.e. $\beta_{\text{R}}^{ij}=0$) and is referred to as "best fit LH". The second benchmark, referred to as "best fit LH+RH", considers $|\beta_{\text{R}}^{\text{b}\tau}|=1$ and all other $\beta_{\text{R}}^{ij}=0$. In the third "democratic" benchmark, equal couplings only to LH fermions are assumed, i.e. $\beta_{\text{L}}^{ij}=1$ and $\beta_{\text{R}}^{ij}=0$ for all $i$ and $j$.

Expected and observed lower limits of the LQ mass as a function of the coupling $g_{U}$ in the LH scenario. The blue band shows the 68% and 95% regions of $g_{U}$ preferred by the fit to the b anomalies data.

Expected and observed lower limits of the LQ mass as a function of the coupling $g_{U}$ in the LH+RH scenario. The blue band shows the 68% and 95% regions of $g_{U}$ preferred by the fit to the b anomalies data.

Expected and observed lower limits of the LQ mass as a function of the coupling $g_{U}$ in the democratic scenario. The blue band shows the 68% and 95% regions of $g_{U}$ preferred by the fit to the b anomalies data.

Summary of exclusion limits (expected and observed) calculated at 95% CL for full Run-2 CMS data.

Comparison between the data and SM background predictions for the number of muons in the long track final state.

Comparison between the data and SM background predictions for the m_{DTk; stopping power} in the long track final state.

Comparison between the data and SM background predictions for the number of electrons in the long track final state.

Comparison between the data and SM background predictions for the number of b-tagged jets in the short track final state.

Comparison between the data and SM background predictions for the number of jets in the short track final state.

Comparison between the data and SM background predictions for the hard missing transverse momentum in the short track final state.

Comparison between the data and SM background predictions for the number of muons in the short track final state.

Comparison between the data and SM background predictions for the m_{DTk; stopping power} in the short track final state.

Comparison between the data and SM background predictions for the number of electrons in the short track final state.

Comparison between the data and post-fit SM background predictions for the 49 search regions in the global search region.

Expected (dashed line) value of $-2\ln\Lambda$ as a function of $\kappa_{2V}$, when all other coupling modifiers are fixed to their SM predictions.

Likelihood observed contours at 68% CL (solid line) and 95% CL (dashed line) in the $\kappa_{\lambda}$, $\kappa_{2V}$ parameter space, when all other coupling modifiers are fixed to their SM predictions. The best-fit value, denoted by a cross in the plot, corresponds to the very first entry in the table.

Likelihood expected contours at 68% CL (teal shaded region) and 95% CL (yellow shaded region) in the $\kappa_{\lambda}$, $\kappa_{2V}$ parameter space, when all other coupling modifiers are fixed to their SM predictions.In the plot, the SM prediction is indicated by the star.

Likelihood observed contours at 68% CL (solid line) and 95% CL (dashed line) in the $c_{gghh}$ versus $c_{hhh}$ HEFT parameter space, with the remaining coefficient fixed to its SM value. The best-fit value, denoted by a cross in the plot, corresponds to the very first entry in the table.

Likelihood expected contours at 68% CL (teal shaded region) 95% CL (yellow shaded region) in the $c_{gghh}$ versus $c_{hhh}$ HEFT parameter space, with the remaining coefficient fixed to its SM value. In the plot, the SM prediction is indicated by the star.

Likelihood observed contours at 68% CL (solid line) and 95% CL (dashed line) in the $c_{tthh}$ versus $c_{hhh}$ HEFT parameter space, with the remaining coefficient fixed to its SM value. The best-fit value, denoted by a cross in the plot, corresponds to the very first entry in the table.

Likelihood exptected contours at 68% CL (teal shaded region) and 95% CL (yellow shaded region) in the $c_{tthh}$ versus $c_{hhh}$ HEFT parameter space, with the remaining coefficient fixed to its SM value. In the plot, the SM prediction is indicated by the star.

The observed (filled circles) and expected (hollow circles) 95% CL upper limits on the $HH$ ggF production cross-section in the Standard Model and for seven HEFT benchmark points. The teal and yellow colored bands indicate the $\pm 1\sigma$ and $\pm 2\sigma$ variations on the expected limit due to statistical and systematic uncertainties. The predicted cross-sections of each of the models under consideration are shown by the red crosses. The contribution from VBF production to the total $HH$ production cross-section is neglected.

Likelihood observed contours at 68% CL (solid line) and 95% CL (dashed line) in the $c_{{H}\boxed{}}$ versus $c_{H}$ SMEFT parameter space, with the remaining coefficient fixed to its SM value. The best-fit value, denoted by a cross in the plot, corresponds to the very first entry in the table.

Likelihood expected contours at 68% CL (teal shaded region) 95% CL (yellow shaded region) in the $c_{{H}\boxed{}}$ versus $c_{H}$ SMEFT parameter space, with the remaining coefficient fixed to its SM value. In the plot, the SM prediction is indicated by the star.

The acceptance times efficiency for the signal ggF $HH$ process as a function of the coupling modifier $\kappa_{\lambda}$ in each analysis category. The other coupling modifiers affecting ggF $HH$ production are fixed to their SM predictions. The bands indicate the simulation statistical uncertainty.

The acceptance times efficiency for the signal VBF $HH$ process as a function of the coupling modifier $\kappa_{\lambda}$ in each analysis category. When varying $\kappa_{\lambda}$, the other coupling modifiers affecting the VBF $HH$ production mode are set to their SM predictions. The bands indicate the simulation statistical uncertainty.

The acceptance times efficiency for the signal VBF $HH$ process as a function of the coupling modifier $\kappa_{2V}$ in each analysis category. When varying $\kappa_{2V}$, the other coupling modifiers affecting the VBF $HH$ production mode are set to their SM predictions. The bands indicate the simulation statistical uncertainty.

Expected yields of the signal $HH$ process as a function of the coupling modifier $\kappa_{\lambda}$ after applying the analysis preselection and in each analysis category after the final selection. The $HH$ yield is obtained considering both the $ggF$ and $VBF$ contributions. The other coupling modifiers affecting $HH$ production are fixed to their SM predictions. The bands indicate the simulation statistical uncertainty.

The acceptance times efficiency for the signal ggF $HH$ process in each analysis category as a function of the $c_{hhh}$ HEFT coefficients. The dashed lines denote values that are excluded at 95% CL. The bottom panels show the efficiency of the sum of all analysis categories.

The acceptance times efficiency for the signal ggF $HH$ process in each analysis category as a function of the $c_{tthh}$ HEFT coefficients. The dashed lines denote values that are excluded at 95% CL. The bottom panels show the efficiency of the sum of all analysis categories.

The acceptance times efficiency for the signal ggF $HH$ process in each analysis category as a function of the $c_{gghh}$ HEFT coefficients. The dashed lines denote values that are excluded at 95% CL. The bottom panels show the efficiency of the sum of all analysis categories.

The acceptance times efficiency for the signal ggF $HH$ process in each analysis category as a function of the $c_{H}$ SMEFT coefficients. The dashed lines denote values that are excluded at 95% CL. The bottom panels show the efficiency of the sum of all analysis categories.

The acceptance times efficiency for the signal ggF $HH$ process in each analysis category as a function of the $c_{{H}\boxed{}}$ SMEFT coefficients. The dashed lines denote values that are excluded at 95% CL. The bottom panels show the efficiency of the sum of all analysis categories.

The yield of the signal ggF $HH$ process in each analysis category as a function of the $c_{hhh}$ HEFT coefficients. The dashed lines denote values that are excluded at 95% CL. The bottom panels show the efficiency of the sum of all analysis categories.

The yield of the signal ggF $HH$ process in each analysis category as a function of the $c_{tthh}$ HEFT coefficients. The dashed lines denote values that are excluded at 95% CL. The bottom panels show the efficiency of the sum of all analysis categories.

The yield of the signal ggF $HH$ process in each analysis category as a function of the $c_{gghh}$ HEFT coefficients. The dashed lines denote values that are excluded at 95% CL. The bottom panels show the efficiency of the sum of all analysis categories.

The yield of the signal ggF $HH$ process in each analysis category as a function of the $c_{H}$ SMEFT coefficients. The dashed lines denote values that are excluded at 95% CL. The bottom panels show the efficiency of the sum of all analysis categories.

The yield of the signal ggF $HH$ process in each analysis category as a function of the $c_{{H}\boxed{}}$ SMEFT coefficients. The dashed lines denote values that are excluded at 95% CL. The bottom panels show the efficiency of the sum of all analysis categories.

Distributions of the diphoton invariant mass for events in data (black dots with error bars) compared to the sum of the expected signal and backgrounds (histograms) in the low mass 1 region.

Distributions of the diphoton invariant mass for events in data (black dots with error bars) compared to the sum of the expected signal and backgrounds (histograms) in the low mass 2 region.

Distributions of the diphoton invariant mass for events in data (black dots with error bars) compared to the sum of the expected signal and backgrounds (histograms) in the low mass 3 region.

Distributions of the diphoton invariant mass for events in data (black dots with error bars) compared to the sum of the expected signal and backgrounds (histograms) in the low mass 4 region.

Distributions of the diphoton invariant mass for events in data (black dots with error bars) compared to the sum of the expected signal and backgrounds (histograms) in the high mass 1 region.

Distributions of the diphoton invariant mass for events in data (black dots with error bars) compared to the sum of the expected signal and backgrounds (histograms) in the high mass 2 region.

Distributions of the diphoton invariant mass for events in data (black dots with error bars) compared to the sum of the expected signal and backgrounds (histograms) in the high mass 3 region.

Observed (solid line) value of $-2\ln\Lambda$ as a function of the $c_{hhh}$ HEFT coefficients when all other coupling modifiers are fixed to the SM value

Expected (dashed line) value of $-2\ln\Lambda$ as a function of the $c_{hhh}$ HEFT coefficients when all other coupling modifiers are fixed to the SM value

Observed (solid line) value of $-2\ln\Lambda$ as a function of the $c_{gghh}$ HEFT coefficients when all other coupling modifiers are fixed to the SM value

Expected (dashed line) value of $-2\ln\Lambda$ as a function of the $c_{gghh}$ HEFT coefficients when all other coupling modifiers are fixed to the SM value

Observed (solid line) value of $-2\ln\Lambda$ as a function of the $c_{tthh}$ HEFT coefficients when all other coupling modifiers are fixed to the SM value

Expected (dashed line) value of $-2\ln\Lambda$ as a function of the $c_{tthh}$ HEFT coefficients when all other coupling modifiers are fixed to the SM value

Observed (solid line) value of $-2\ln\Lambda$ as a function of the $c_{H}$ SMEFT coefficients when all other coupling modifiers are fixed to the SM value.

Expected (dashed line) value of $-2\ln\Lambda$ as a function of the $c_{H}$ SMEFT coefficients when all other coupling modifiers are fixed to the SM value.

Observed (solid line) value of $-2\ln\Lambda$ as a function of the $c_{{H}\boxed{}}$ SMEFT coefficients when all other coupling modifiers are fixed to the SM value.

Expected (dashed line) value of $-2\ln\Lambda$ as a function of the $c_{{H}\boxed{}}$ SMEFT coefficients when all other coupling modifiers are fixed to the SM value.

Summary of the expected (blue) and observed (orange) one-dimensional constraints at 68% (solid error bars) and 95% (dashed error bars) CL on the coefficients of selected HEFT (top) and SMEFT (bottom) operators describing Higgs boson interactions affecting $HH$ production through gluon--gluon fusion. The results are obtained from one dimensional scans of the profile log-likelihood assuming that all other Wilson coefficients are fixed to their SM values. The contribution from VBF $HH$ production is neglected.

Upper limits at 95% CL on $\sigma$B(pp→X→Y(bb)H) for combination as a function of m$_Y$.

Expected upper limits at 95% CL on the X → HH cross section as a function of mX from the combination of the three channels bbγγ, bbττ, and bbbb for an integrated luminosity of 3000 fb−1 with different assumptions on the systematic uncertainties.

Expected upper limits on the X → YH cross section times B(Y → bb) for mX ≤ 1000 GeV at 95 % CL as a function of m$_X$ and m$_Y$ from the combination of all considered channels projected to an integrated luminosity of 3000 fb$^{-1}$. Systematic uncertainties according to the ”S2” scenario are assumed.

Covariance matrix for the extrapolation uncertainty for the measurement of the absolute differential cross section as a function of the rho observable at parton level.

Normalized differential cross section as a function of the rho observable at parton level.

Covariance matrix for the total uncertainty (i.e. fit including stat., not extrapolation) for the measurement of the normalized differential cross section as a function of the rho observable at parton level.

Covariance matrix for the statistical uncertainty for the measurement of the normalized differential cross section as a function of the rho observable at parton level.

Covariance matrix for the extrapolation uncertainty for the measurement of the normalized differential cross section as a function of the rho observable at parton level.

Correlation matrix for all nuisance parameters and parameters of interest of the Likelihood fit.

This table is a numerical representation of Fig. 8 for all nuisance parameters.

Transverse momentum spectra for the jet region, obtained as toward-transverse. Events with a leading track with PT>5 GEV at midrapidity are selected. The spectrum is shown in Figure 1 (right panel).

Coalescence parameter B2 as a function of the transverse momentum per nucleon pT/A, in the underlying event (transverse region). Events with a leading track with PT>5 GEV at midrapidity are selected. The B2 is shown in Figure 2 (both panels).

Coalescence parameter B2 as a function of the transverse momentum per nucleon pT/A, in the jet (transverse-toward region). Events with a leading track with PT>5 GEV at midrapidity are selected. The B2 is shown in Figure 2 (both panels).

Expected exclusion limits at 95% CL from Fig 7(a) for $\tilde{g}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

One $\sigma$ band of expected exclusion limits at 95% CL from Fig 7(a) for $\tilde{g}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

Observed exclusion limits at 95% CL from Fig 7(c) for $\tilde{g}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Positive one $\sigma$ observed exclusion limits at 95% CL from Fig 7(c) for $\tilde{g}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Negative one $\sigma$ observed exclusion limits at 95% CL from Fig 7(c) for $\tilde{g}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Expected exclusion limits at 95% CL from Fig 7(c) for $\tilde{g}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

One $\sigma$ band of expected exclusion limits at 95% CL from Fig 7(c) for $\tilde{g}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Observed exclusion limits at 95% CL from Fig 7(f) for $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$

Positive one $\sigma$ observed exclusion limits at 95% CL from Fig 7(f) for $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$

Negative one $\sigma$ observed exclusion limits at 95% CL from Fig 7(f) for $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$

Expected exclusion limits at 95% CL from Fig 7(f) for $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$

One $\sigma$ band of expected exclusion limits at 95% CL from Fig 7(f) for $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$

Observed exclusion limits at 95% CL from Fig 7(e) for direct $\tilde{\chi_{1}^{0}}$ decay into SM leptons and quarks via a non-zero RPV coupling $\lambda'$

Positive one $\sigma$ observed exclusion limits at 95% CL from Fig 7(e) for direct $\tilde{\chi_{1}^{0}}$ decay into SM leptons and quarks via a non-zero RPV coupling $\lambda'$

Negative one $\sigma$ observed exclusion limits at 95% CL from Fig 7(e) for direct $\tilde{\chi_{1}^{0}}$ decay into SM leptons and quarks via a non-zero RPV coupling $\lambda'$

Expected exclusion limits at 95% CL from Fig 7(e) for direct $\tilde{\chi_{1}^{0}}$ decay into SM leptons and quarks via a non-zero RPV coupling $\lambda'$

One $\sigma$ band of expected exclusion limits at 95% CL from Fig 7(e) for direct $\tilde{\chi_{1}^{0}}$ decay into SM leptons and quarks via a non-zero RPV coupling $\lambda'$

Observed exclusion limits at 95% CL from Fig 7(b) for $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

Positive one $\sigma$ observed exclusion limits at 95% CL from Fig 7(b) for $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

Negative one $\sigma$ observed exclusion limits at 95% CL from Fig 7(b) for $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

Expected exclusion limits at 95% CL from Fig 7(b) for $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

One $\sigma$ band of expected exclusion limits at 95% CL from Fig 7(b) for $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

Observed exclusion limits at 95% CL from Fig 7(d) for $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Positive one $\sigma$ observed exclusion limits at 95% CL from Fig 7(d) for $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Negative one $\sigma$ observed exclusion limits at 95% CL from Fig 7(d) for $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Expected exclusion limits at 95% CL from Fig 7(d) for $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

One $\sigma$ band of expected exclusion limits at 95% CL from Fig 7(d) for $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

N-1 distribution for $m_{\mathrm{eff}}$of observed data and expected background in SRGGWZ-H.

N-1 distribution for $E_{\mathrm{T}}^{\mathrm{miss}}$of observed data and expected background in SRGGSlep-M.

N-1 distribution for $\sum{p_{\mathrm{T}}^\mathrm{jet}}$of observed data and expected background in SRUDD-ge2b.

N-1 distribution for $m_{\mathrm{eff}}$of observed data and expected background in SRLQD.

N-1 distribution for $m_{\mathrm{eff}}$of observed data and expected background in SRSSWZ-H.

N-1 distribution for $m_{\mathrm{eff}}$of observed data and expected background in SRSSSlep-H(loose).

Signal acceptance for SRGGWZ-H signal region from Fig 10(c) in a SUSY scenario where $\tilde{g}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

Signal efficiency for SRGGWZ-H signal region from Fig 15(c) in a SUSY scenario where $\tilde{g}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

Signal acceptance for SRGGWZ-M signal region from Fig 10(b) in a SUSY scenario where $\tilde{g}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

Signal efficiency for SRGGWZ-M signal region from Fig 15(b) in a SUSY scenario where $\tilde{g}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

Signal acceptance for SRGGWZ-L signal region from Fig 10(a) in a SUSY scenario where $\tilde{g}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

Signal efficiency for SRGGWZ-L signal region from Fig 15(a) in a SUSY scenario where $\tilde{g}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

Signal acceptance for SRGGSlep-L signal region from Fig 12(a) in a SUSY scenario where $\tilde{g}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Signal efficiency for SRGGSlep-L signal region from Fig 17(a) in a SUSY scenario where $\tilde{g}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Signal acceptance for SRGGSlep-M signal region from Fig 12(b) in a SUSY scenario where $\tilde{g}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Signal efficiency for SRGGSlep-M signal region from Fig 17(b) in a SUSY scenario where $\tilde{g}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Signal acceptance for SRGGSlep-H signal region from Fig 12(c) in a SUSY scenario where $\tilde{g}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Signal efficiency for SRGGSlep-H signal region from Fig 17(c) in a SUSY scenario where $\tilde{g}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Signal acceptance for SRUDD-1b signal region from Fig 14(b) in a SUSY scenario where $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$

Signal efficiency for SRUDD-1b signal region from Fig 19(b) in a SUSY scenario where $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$

Signal acceptance for SRUDD-2b signal region from Fig 14(c) in a SUSY scenario where $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$

Signal efficiency for SRUDD-2b signal region from Fig 19(c) in a SUSY scenario where $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$

Signal acceptance for SRUDD-ge2b signal region from Fig 14(d) in a SUSY scenario where $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$

Signal efficiency for SRUDD-ge2b signal region from Fig 19(d) in a SUSY scenario where $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$

Signal acceptance for SRUDD-ge3b signal region from Fig 14(e) in a SUSY scenario where $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$

Signal efficiency for SRUDD-ge3b signal region from Fig 19(e) in a SUSY scenario where $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$

Signal acceptance for SRLQD signal region from Fig 14(a) in a SUSY scenario where direct $\tilde{\chi_{1}^{0}}$ decay into SM leptons and quarks via a non-zero RPV coupling $\lambda'$

Signal efficiency for SRLQD signal region from Fig 19(a) in a SUSY scenario where direct $\tilde{\chi_{1}^{0}}$ decay into SM leptons and quarks via a non-zero RPV coupling $\lambda'$

Signal acceptance for SRSSWZ-L signal region from Fig 11(a) in a SUSY scenario where $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

Signal efficiency for SRSSWZ-L signal region from Fig 16(a) in a SUSY scenario where $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

Signal acceptance for SRSSWZ-ML signal region from Fig 11(b) in a SUSY scenario where $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

Signal efficiency for SRSSWZ-ML signal region from Fig 16(b) in a SUSY scenario where $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

Signal acceptance for SRSSWZ-MH signal region from Fig 11(c) in a SUSY scenario where $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

Signal efficiency for SRSSWZ-MH signal region from Fig 16(c) in a SUSY scenario where $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

Signal acceptance for SRSSWZ-H signal region from Fig 11(d) in a SUSY scenario where $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

Signal efficiency for SRSSWZ-H signal region from Fig 16(d) in a SUSY scenario where $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

Signal acceptance for SRSSSlep-H signal region from Fig 13(d) in a SUSY scenario where $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Signal efficiency for SRSSSlep-H signal region from Fig 18(d) in a SUSY scenario where $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Signal acceptance for SRSSSlep-MH signal region from Fig 13(c) in a SUSY scenario where $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Signal efficiency for SRSSSlep-MH signal region from Fig 18(c) in a SUSY scenario where $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Signal acceptance for SRSSSlep-L signal region from Fig 13(a) in a SUSY scenario where $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Signal efficiency for SRSSSlep-L signal region from Fig 18(a) in a SUSY scenario where $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Signal acceptance for SRSSSlep-ML signal region from Fig 13(b) in a SUSY scenario where $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Signal efficiency for SRSSSlep-ML signal region from Fig 18(b) in a SUSY scenario where $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Signal acceptance for SRSSSlep-H(loose) signal region from Fig 13(e) in a SUSY scenario where $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Signal efficiency for SRSSSlep-H(loose) signal region from Fig 18(e) in a SUSY scenario where $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRGGWZ-H in a susy scenario where $\tilde{g}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$. The masses of the superpartners involved in the process are set to $m(\tilde{g})$ = 1400 GeV, $m(\tilde{\chi_{1}^{0}})$ = 1000 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRGGWZ-M in a susy scenario where $\tilde{g}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$. The masses of the superpartners involved in the process are set to $m(\tilde{g})$ = 1400 GeV, $m(\tilde{\chi_{1}^{0}})$ = 1000 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRGGWZ-L in a susy scenario where $\tilde{g}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$. The masses of the superpartners involved in the process are set to $m(\tilde{g})$ = 1400 GeV, $m(\tilde{\chi_{1}^{0}})$ = 1000 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRGGSlep-L in a susy scenario where $\tilde{g}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$. The masses of the superpartners involved in the process are set to $m(\tilde{g})$ = 2000 GeV, $m(\tilde{\chi_{1}^{0}})$ = 500 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRGGSlep-M in a susy scenario where $\tilde{g}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$. The masses of the superpartners involved in the process are set to $m(\tilde{g})$ = 2000 GeV, $m(\tilde{\chi_{1}^{0}})$ = 500 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRGGSlep-H in a susy scenario where $\tilde{g}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$. The masses of the superpartners involved in the process are set to $m(\tilde{g})$ = 2000 GeV, $m(\tilde{\chi_{1}^{0}})$ = 500 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRUDD-1b in a susy scenario where $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$. The masses of the superpartners involved in the process are set to $m(\tilde{g})$ = 1600 GeV, $m(\tilde{t})$ = 600 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRUDD-2b in a susy scenario where $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$. The masses of the superpartners involved in the process are set to $m(\tilde{g})$ = 1600 GeV, $m(\tilde{t})$ = 600 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRUDD-ge2b in a susy scenario where $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$. The masses of the superpartners involved in the process are set to $m(\tilde{g})$ = 1600 GeV, $m(\tilde{t})$ = 600 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRUDD-ge3b in a susy scenario where $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$. The masses of the superpartners involved in the process are set to $m(\tilde{g})$ = 1600 GeV, $m(\tilde{t})$ = 600 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRLQD in a susy scenario where direct $\tilde{\chi_{1}^{0}}$ decay into SM leptons and quarks via a non-zero RPV coupling $\lambda'$. The masses of the superpartners involved in the process are set to $m(\tilde{g})$ = 2200 GeV, $m(\tilde{\chi_{1}^{0}})$ = 1870 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRSSWZ-L in a susy scenario where $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$. The masses of the superpartners involved in the process are set to $m(\tilde{q})$ = 800 GeV, $m(\tilde{\chi_{1}^{0}})$ = 600 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRSSWZ-ML in a susy scenario where $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$. The masses of the superpartners involved in the process are set to $m(\tilde{q})$ = 800 GeV, $m(\tilde{\chi_{1}^{0}})$ = 600 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRSSWZ-MH in a susy scenario where $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$. The masses of the superpartners involved in the process are set to $m(\tilde{q})$ = 800 GeV, $m(\tilde{\chi_{1}^{0}})$ = 600 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRSSWZ-H in a susy scenario where $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$. The masses of the superpartners involved in the process are set to $m(\tilde{q})$ = 800 GeV, $m(\tilde{\chi_{1}^{0}})$ = 600 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRSSSlep-H in a susy scenario where $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$. The masses of the superpartners involved in the process are set to $m(\tilde{q})$ = 1000 GeV, $m(\tilde{\chi_{1}^{0}})$ = 800 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRSSSlep-MH in a susy scenario where $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$. The masses of the superpartners involved in the process are set to $m(\tilde{q})$ = 1000 GeV, $m(\tilde{\chi_{1}^{0}})$ = 800 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRSSSlep-L in a susy scenario where $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$. The masses of the superpartners involved in the process are set to $m(\tilde{q})$ = 1000 GeV, $m(\tilde{\chi_{1}^{0}})$ = 800 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRSSSlep-ML in a susy scenario where $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$. The masses of the superpartners involved in the process are set to $m(\tilde{q})$ = 1000 GeV, $m(\tilde{\chi_{1}^{0}})$ = 800 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRSSSlep-H(loose) in a susy scenario where $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$. The masses of the superpartners involved in the process are set to $m(\tilde{q})$ = 1000 GeV, $m(\tilde{\chi_{1}^{0}})$ = 800 GeV. Only statistical uncertainties are shown.

Cross-section upper limits at 95% CL from Fig1(a) for $\tilde{g}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

Cross-section upper limits at 95% CL from Fig1(c) for $\tilde{g}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Cross-section upper limits at 95% CL from Fig1(f) for $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$

Cross-section upper limits at 95% CL from Fig1(e) for direct $\tilde{\chi_{1}^{0}}$ decay into SM leptons and quarks via a non-zero RPV coupling $\lambda'$

Cross-section upper limits at 95% CL from Fig1(b) for $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

Cross-section upper limits at 95% CL from Fig1(d) for $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Net-proton cumulant ratios C4/C2, C5/C1, C6/C2 (0-40$\%$ and 50-60$\%$ centrality) and C3/C1 (0-40$\%$ centrality) in Au+Au collisions from $\sqrt{s_{NN}}$ = 3 - 200 GeV. At $\sqrt{s_{NN}}$ = 3 GeV, measurement is done for protons instead of net-protons, and with halfrapdity coverage (-0.5 $<$ y $<$ 0) while for rest of energies the rapidity coverage is (-0.5 $<$ y $<$ -0.5).

Net-proton cumulant ratios C4/C2, C5/C1, C6/C2 (0-40$\%$ and 50-60$\%$ centrality) and C3/C1 (0-40$\%$ centrality) from UrQMD model in Au+Au collisions from $\sqrt{s_{NN}}$ = 3 -200 GeV. At $\sqrt{s_{NN}}$ = 3 GeV, UrQMD calculation is done for protons instead of net-protons, and with halfrapdity coverage (-0.5 $<$ y $<$ 0) while for rest of energies the rapidity coverage is (-0.5 $<$ y $<$ -0.5).

Fifth-to-first (KS5/KS1) and sixth-to-second (KS6/KS2) order K-statistic ratios of net-proton distributions in Au+Au collisions at $\sqrt{s_{NN}}$ = 7.7 GeV for 0-40$\%$ and 50-60$\%$ centrality.

Net-proton cumulant ratio C6/C2 and corresponding K-statistic ratio (0-40$\%$) in Au+Au collisions at $\sqrt{s_{NN}}$ = 7.7 GeV as a function of sample size. Uncertainties are only statistical.

Cumulant ratios C4/C2, C5/C1, C6/C2 and C3/C1 of net-proton distributions measured with half rapdity coverage (-0.5 $<$ y $<$ 0) in 0-40$\%$ central Au+Au collisions for collider energies from $\sqrt{s_{NN}}$ = 7.7 - 54.4 GeV.

Cumulant ratios C5/C1 of net-proton distributions measured in 40-50$\%$, 60-70$\%$, and 70-80$\%$ Au+Au collisions at $\sqrt{s_{NN}}$ = 200 GeV. This is supplemental data and was not part of the original paper.

The expected minus one standard deviation exclusion limit at 95% CL for the clockwork gravity model projected in the $k–M_{5}$ parameter space for the $ee$ channel for the case with mass thresholds.

The expected plus two standard deviation exclusion limit at 95% CL for the clockwork gravity model projected in the $k–M_{5}$ parameter space for the $ee$ channel for the case with mass thresholds.

The expected minus two standard deviation exclusion limit at 95% CL for the clockwork gravity model projected in the $k–M_{5}$ parameter space for the $ee$ channel for the case with mass thresholds.

The observed exclusion limit at 95% CL for the clockwork gravity model projected in the $k–M_{5}$ parameter space for the $\gamma\gamma$ channel for the case with mass thresholds.

The median expected exclusion limit at 95% CL for the clockwork gravity model projected in the $k–M_{5}$ parameter space for the $\gamma\gamma$ channel for the case with mass thresholds.

The expected plus one standard deviation exclusion limit at 95% CL for the clockwork gravity model projected in the $k–M_{5}$ parameter space for the $\gamma\gamma$ channel for the case with mass thresholds.

The expected minus one standard deviation exclusion limit at 95% CL for the clockwork gravity model projected in the $k–M_{5}$ parameter space for the $\gamma\gamma$ channel for the case with mass thresholds.

The expected plus two standard deviation exclusion limit at 95% CL for the clockwork gravity model projected in the $k–M_{5}$ parameter space for the $\gamma\gamma$ channel for the case with mass thresholds.

The expected minus two standard deviation exclusion limit at 95% CL for the clockwork gravity model projected in the $k–M_{5}$ parameter space for the $\gamma\gamma$ channel for the case with mass thresholds.

The observed exclusion limit at 95% CL for the clockwork gravity model projected in the $k–M_{5}$ parameter space for the $ee$ channel for the case without mass thresholds.

The median expected exclusion limit at 95% CL for the clockwork gravity model projected in the $k–M_{5}$ parameter space for the $ee$ channel for the case without mass thresholds.

The expected plus one standard deviation exclusion limit at 95% CL for the clockwork gravity model projected in the $k–M_{5}$ parameter space for the $ee$ channel for the case without mass thresholds.

The expected minus one standard deviation exclusion limit at 95% CL for the clockwork gravity model projected in the $k–M_{5}$ parameter space for the $ee$ channel for the case without mass thresholds.

The expected plus two standard deviation exclusion limit at 95% CL for the clockwork gravity model projected in the $k–M_{5}$ parameter space for the $ee$ channel for the case without mass thresholds.

The expected minus two standard deviation exclusion limit at 95% CL for the clockwork gravity model projected in the $k–M_{5}$ parameter space for the $ee$ channel for the case without mass thresholds.

The observed exclusion limit at 95% CL for the clockwork gravity model projected in the $k–M_{5}$ parameter space for the $\gamma\gamma$ channel for the case without mass thresholds.

The median expected exclusion limit at 95% CL for the clockwork gravity model projected in the $k–M_{5}$ parameter space for the $\gamma\gamma$ channel for the case without mass thresholds.

The expected plus one standard deviation exclusion limit at 95% CL for the clockwork gravity model projected in the $k–M_{5}$ parameter space for the $\gamma\gamma$ channel for the case without mass thresholds.

The expected minus one standard deviation exclusion limit at 95% CL for the clockwork gravity model projected in the $k–M_{5}$ parameter space for the $\gamma\gamma$ channel for the case without mass thresholds.

The expected plus two standard deviation exclusion limit at 95% CL for the clockwork gravity model projected in the $k–M_{5}$ parameter space for the $\gamma\gamma$ channel for the case without mass thresholds.

The expected minus two standard deviation exclusion limit at 95% CL for the clockwork gravity model projected in the $k–M_{5}$ parameter space for the $\gamma\gamma$ channel for the case without mass thresholds.

SM background observation/prediction in the WH signal region

SM background prediction vs. observation in the W signal region

SM background observation/prediction in the W signal region

SM background prediction vs. observation in the H signal region

SM background observation/prediction in the H signal region

Observed exclusion limits assuming the approximate-NLO+NLL cross sections

Expected exclusion limits assuming the approximate-NLO+NLL cross sections

The 95% CL observed upper limits on the production cross sections for $\widetilde{\chi}^\pm_1$ $\widetilde{\chi}^\mp_1$ assuming that each $\widetilde{\chi}^\pm_1$ decays to a W boson and $\widetilde{\chi}^0_1$

Observed exclusion limits assuming the approximate-NLO+NLL cross sections

Expected exclusion limits assuming the approximate-NLO+NLL cross sections

The 95% CL observed upper limits on the production cross sections for $\widetilde{\chi}^\pm_1$ $\widetilde{\chi}^0_2$ assuming that each $\widetilde{\chi}^\pm_1$ decays to a W boson and $\widetilde{\chi}^0_1$ and the $\widetilde{\chi}^0_2$ decays to a Z boson and $\widetilde{\chi}^0_1$

Observed exclusion limits assuming the approximate-NLO+NLL cross sections

Expected exclusion limits assuming the approximate-NLO+NLL cross sections

The 95% CL observed upper limits on the production cross sections for $\widetilde{\chi}^\pm_1$ $\widetilde{\chi}^0_2$ assuming that each $\widetilde{\chi}^\pm_1$ decays to a W boson and $\widetilde{\chi}^0_1$ and the $\widetilde{\chi}^0_2$ decays to a H boson and $\widetilde{\chi}^0_1$

Observed exclusion limits assuming the approximate-NLO+NLL cross sections

Expected exclusion limits assuming the approximate-NLO+NLL cross sections

Observed exclusion limits assuming the approximate-NLO+NLL cross sections

Expected exclusion limits assuming the approximate-NLO+NLL cross sections

Observed exclusion limits assuming the approximate-NLO+NLL cross sections

Expected exclusion limits assuming the approximate-NLO+NLL cross sections

The 95% CL observed upper limits on the production cross sections for mass-degenerate higgsino-like$\widetilde{\chi}^\pm_1$ $\widetilde{\chi}^\mp_1$, $\widetilde{\chi}^\pm_1$ $\widetilde{\chi}^0_2$, $\widetilde{\chi}^\pm_1$ $\widetilde{\chi}^0_3$ and $\widetilde{\chi}^0_2$ $\widetilde{\chi}^0_3$ as functions of the NLSP and LSP masses.

Efficiency of bb-tagger for H(bb), Z(bb) and Z(cc) decays.

Efficiency of W- and V-tagger for W(qq) and Z(qq) decays.

Acceptance times efficiency values with statistical uncertainties for TChiWW in the b-Veto region.

Acceptance times efficiency values with statistical uncertainties for TChiWZ in the b-Veto region.

Acceptance times efficiency values with statistical uncertainties for TChiWH in the b-Veto region.

Acceptance times efficiency values with statistical uncertainties for TChiHZ in the b-Veto region.

Acceptance times efficiency values with statistical uncertainties for TChiWW in the WHSR region.

Acceptance times efficiency values with statistical uncertainties for TChiWW in the WSR region.

Acceptance times efficiency values with statistical uncertainties for TChiWW in the HSR region.

Acceptance times efficiency values with statistical uncertainties for TChiWZ in the WHSR region.

Acceptance times efficiency values with statistical uncertainties for TChiWZ in the WSR region.

Acceptance times efficiency values with statistical uncertainties for TChiWZ in the HSR region.

Acceptance times efficiency values with statistical uncertainties for TChiWH in the WHSR region.

Acceptance times efficiency values with statistical uncertainties for TChiWH in the WSR region.

Acceptance times efficiency values with statistical uncertainties for TChiWH in the HSR region.

Acceptance times efficiency values with uncertainties for TChiHZ in the WHSR region.

Acceptance times efficiency values with uncertainties for TChiHZ in the WSR region.

Acceptance times efficiency values with statistical uncertainties for TChiHZ in the HSR region.

Covariance matrix for the signal regions, derived from a fit to the control regions only under the background-only hypothesis.

Correlation matrix for the signal regions, derived from a fit to the control regions only under the background-only hypothesis.

Post-fit distribution of the $M(ll)$ variable for the ultrahigh-$p_{\mathrm{T}}^{\mathrm{miss}}$ bins in the '2l soft' signal region of the '2/3l soft' analysis.

Post-fit distribution of the $M(ll)$ variable for the low-$p_{\mathrm{T}}^{\mathrm{miss}}$ bins in the '3l soft' signal region of the the '2/3l soft' analysis.

Post-fit distribution of the $M(ll)$ variable for the medium-$p_{\mathrm{T}}^{\mathrm{miss}}$ bins in the '3l soft' signal region of the the '2/3l soft' analysis.

Post-fit distribution of the $m_{\mathrm{T2}}(ll)$ variable for low-$p_{\mathrm{T}}^{\mathrm{miss}}$ bins in the '2l soft' signal region of the '2/3l soft' analysis.

Post-fit distribution of the $m_{\mathrm{T2}}(ll)$ variable for medium-$p_{\mathrm{T}}^{\mathrm{miss}}$ bins in the '2l soft' signal region of the '2/3l soft' analysis.

Post-fit distribution of the $m_{\mathrm{T2}}(ll)$ variable for high-$p_{\mathrm{T}}^{\mathrm{miss}}$ bins in the '2l soft' signal region of the '2/3l soft' analysis.

Post-fit distribution of the $m_{\mathrm{T2}}(ll)$ variable for ultrahigh-$p_{\mathrm{T}}^{\mathrm{miss}}$ bins in the '2l soft' signal region of the '2/3l soft' analysis.

2SS $\ell/{\geq}\,3\ell$ search: observed and expected yields across the SRs in category A, events with three light leptons of which at least two form an OSSF pair, after the requirement that the leading-lepton $p_{\mathrm{T}}$ be greater than 30 GeV is applied.

2SS $\ell/{\geq}\,3\ell$ search: observed and expected yields across the SRs of the '${\geq}\ 3\ell$' search in category B, events with three light leptons and no OSSF pair, after the requirement that the leading-lepton $p_{\mathrm{T}}$ be greater than 30 GeV is applied.

Wino-bino model: cross section limits in the model parameter space, for wino-like chargino-neutralino production in the WZ topology for the full parameter space.

Wino-bino model: cross section limits in the model parameter space, for wino-like chargino-neutralino production in the WZ topology for the compressed space.

Wino-bino model: cross section limits in the model parameter space, for wino-like chargino-neutralino production in the WH topology for the full parameter space.

Wino-bino model: cross section limits in the model parameter space, for wino-like chargino-neutralino production with mixed topology with equal branching fraction to WZ and WH.

GMSB model: expected and observed cross section limits for the neutralino-neutralino production for the ZZ topology.

GMSB model: expected and observed cross section limits for the neutralino-neutralino production for the HH topology.

GMSB model: expected and observed cross section limits for the neutralino-neutralino production for the mixed topology with equal branching fraction to H and Z.

GMSB model: cross section limits for neutralino-neutralino production as a function of the NSLP mass and the branching fraction to the H boson for the combination of the searches.

Cross section upper limit(s) in the mass plane of NLSP and LSP masses for the higgsino-bino model.

Mass plane cross section upper limit for direct slepton pair production, with observed and expected exclusion limits in the full mass plane from the combination.

Mass plane cross section upper limit for direct slepton pair production, with observed and expected exclusion limits in the compressed region from '2/3l' soft search.

Distribution of an input to the BDT classifier in the $3\ell$ category: The linear discrimminant $p_{T}^{miss,LD}$. The discriminant is defined by the relation $p_{T}^{miss,LD} = 0.6 p_{T}^{miss} + 0.4 H_{T}^{miss}$, where $H_{T}^{miss}$ corresponds to the magnitude of the vector $p_{T}$ sum of all electrons, muons, taus and small radius jets passing the selection critertia, and $p_{T}^{miss}$ represents the missing transverse momentum vector computed as the negative vector $p_{T}$ sum of all the particles reconstructed by the PF algorithm in the event.

Distributions of the transverse mass $m_{T}$ of the lepton that is not originating from the Z boson decay and the missing transverse momentum in the $3\ell$/WZ control region. The distributions expected for the WZ and ZZ as well as for other background processes are shown for the values of nuisance parameters obtained from the ML fit used in the signal extraction.

Distributions of the four lepton invariant mass $m_{4\ell}$ in the $4\ell$/ZZ control region. The distributions expected for the ZZ as well as for other background processes are shown for the values of nuisance parameters obtained from the ML fit used in the signal extraction.

Distributions of the transverse mass $m_{T}$ of the leading lepton and the missing transverse momentum in the $2\ell$(ss) control region. The distributions expected for the misidentified $\ell$ background as well as for other background processes is shown for the values of nuisance parameters obtained from the background-only ML fit, in which the HH signal is constrained to be zero.

Distributions of the reconstructed HH mass $m_{HH}$ in the $2\ell+2 au_{h}$ control region. The distributions expected for the misidentified $\ell/ au_{h}$ background as well as for other background processes is shown for the values of nuisance parameters obtained from the background-only ML fit, in which the HH signal is constrained to be zero.

Distribution in the output of the BDT trained for nonresonant HH production and evaluated for the benchmark scenario JHEP04 BM7 for the $2\ell$(ss) category. The SM HH signal is shown for a cross section amounting to $30$ times the value predicted in the SM. The distributions expected for the background processes are shown for the values of nuisance parameters obtained from the ML fit of the signal+background hypothesis to the data. The binning is chosen to approximate signal quantiles.

Distribution in the output of the BDT trained for nonresonant HH production and evaluated for the benchmark scenario JHEP04 BM7 for the $3\ell$ category. The SM HH signal is shown for a cross section amounting to $30$ times the value predicted in the SM. The distributions expected for the background processes are shown for the values of nuisance parameters obtained from the ML fit of the signal+background hypothesis to the data. The binning is chosen to approximate signal quantiles.

Distribution in the output of the BDT trained for nonresonant HH production and evaluated for the benchmark scenario JHEP04 BM7 for the $4\ell$ category. The SM HH signal is shown for a cross section amounting to $30$ times the value predicted in the SM. The distributions expected for the background processes are shown for the values of nuisance parameters obtained from the ML fit of the signal+background hypothesis to the data. The binning is chosen to approximate signal quantiles.

Distribution in the output of the BDT trained for nonresonant HH production and evaluated for the benchmark scenario JHEP04 BM7 for the $3\ell+1 au_{h}$ category. The SM HH signal is shown for a cross section amounting to $30$ times the value predicted in the SM. The distributions expected for the background processes are shown for the values of nuisance parameters obtained from the ML fit of the signal+background hypothesis to the data. The binning is chosen to approximate background quantiles.

Distribution in the output of the BDT trained for nonresonant HH production and evaluated for the benchmark scenario JHEP04 BM7 for the $2\ell+2 au_{h}$ category. The SM HH signal is shown for a cross section amounting to $30$ times the value predicted in the SM. The distributions expected for the background processes are shown for the values of nuisance parameters obtained from the ML fit of the signal+background hypothesis to the data. The binning is chosen to approximate background quantiles.

Distribution in the output of the BDT trained for nonresonant HH production and evaluated for the benchmark scenario JHEP04 BM7 for the $1\ell+3 au_{h}$ category. The SM HH signal is shown for a cross section amounting to $30$ times the value predicted in the SM. The distributions expected for the background processes are shown for the values of nuisance parameters obtained from the ML fit of the signal+background hypothesis to the data. The binning is chosen to approximate background quantiles.

Distribution in the output of the BDT trained for nonresonant HH production and evaluated for the benchmark scenario JHEP04 BM7 for the $4 au_{h}$ category. The SM HH signal is shown for a cross section amounting to $30$ times the value predicted in the SM. The distributions expected for the background processes are shown for the values of nuisance parameters obtained from the ML fit of the signal+background hypothesis to the data. The binning is chosen to approximate background quantiles.

Observed and expected $95\%$ CL upper limits on the SM HH production cross section, obtained for both individual search categories and from a simultaneous fit of all seven categories combined.

Observed and expected $95\%$ CL upper limits on the HH production cross section as a function of the Higgs boson self-coupling strength modifier $\kappa_\lambda$ for the combination of all seven categories. All Higgs boson couplings other than $\lambda$ are assumed to have the values predicted in the SM.

Observed and expected $95\%$ CL upper limits on the HH production cross section as a function of the Higgs boson self-coupling strength modifier $\kappa_\lambda$ for the seven different categories as well as their combination. All Higgs boson couplings other than $\lambda$ are assumed to have the values predicted in the SM.

Observed and expected $95\%$ CL upper limits on the HH production cross section for the twelve benchmark scenarios from doi:10.1007/JHEP04(2016)126, the additional benchmark scenario 8a from doi:10.1007/JHEP09(2018)057, the seven benchmark scenarios from doi:10.1007/JHEP03(2020)091, and for the SM.

Observed and expected $95\%$ CL upper limits on the HH production cross section for the twelve benchmark scenarios from doi:10.1007/JHEP04(2016)126, the additional benchmark scenario 8a from doi:10.1007/JHEP09(2018)057, the seven benchmark scenarios from doi:10.1007/JHEP03(2020)091, and for the SM. The limits are shown for all seven search categories as well as for their combination.

Observed and expected $95\%$ CL upper limits on the HH production cross section as a function of the effective coupling $c_{2}$ for the combination of all seven categories. All Higgs boson couplings other than $c_{2}$ are assumed to have the values predicted in the SM.

Observed and expected $95\%$ CL upper limits on the HH production cross section as a function of the effective coupling $c_{2}$ and the top Yukawa coupling modifier $\kappa_{t}$ for the combination of all seven categories. All Higgs boson couplings other than $c_{2}$ and $\kappa_{t}$ are assumed to have the values predicted in the SM. The position of the SM in the ($c_{2}-\kappa_{t}$) plane, as well as the best fit value of $(c_{2},\kappa_{t})=(1.05, 1.74)$ together with contours for the theory cross section are shown as well.

Observed and expected $95\%$ CL upper limits on the HH production cross section as a function of the Higgs boson self-coupling modifier $\kappa_{\lambda}$ and the top Yukawa coupling modifier $\kappa_{t}$ for the combination of all seven categories. All Higgs boson couplings other than $\kappa_{\lambda}$ and $\kappa_{t}$ are assumed to have the values predicted in the SM. The position of the SM in the ($\kappa_{\lambda}-\kappa_{t}$) plane, as well as the best fit value of $(\kappa_{\lambda},\kappa_{t})=(-3.54, -1.70)$ together with contours for the theory cross section are shown as well.

Observed and expected $95\%$ CL upper limits on the HH production cross section as a function of the effective coupling $c_{2}$ and the Higgs boson self-coupling modifier $\kappa_{\lambda}$ for the combination of all seven categories. All Higgs boson couplings other than $c_{2}$ and $\kappa_{\lambda}$ are assumed to have the values predicted in the SM. The position of the SM in the ($c_{2}-\kappa_{\lambda}$) plane, as well as the best fit value of $(c_{2},\kappa_{\lambda})=(-0.66, 5.33)$ together with contours for the theory cross section are shown as well.

Observed and expected $95\%$ CL upper limits on the production of new particles X of spin $0$ and mass $m_{X}$ in the range $250$-$1000$ GeV, which decay to Higgs boson pairs.

Observed and expected $95\%$ CL upper limits on the production of new particles X of spin $0$ and mass $m_{X}$ in the range $250$-$1000$ GeV, which decay to Higgs boson pairs. The Limit is shown for the seven different search categories as well as their combination.

Observed and expected $95\%$ CL upper limits on the production of new particles X of spin $2$ and mass $m_{X}$ in the range $250$-$1000$ GeV, which decay to Higgs boson pairs.

Observed and expected $95\%$ CL upper limits on the production of new particles X of spin $2$ and mass $m_{X}$ in the range $250$-$1000$ GeV, which decay to Higgs boson pairs. The Limit is shown for the seven different search categories as well as their combination.

Distribution in the output of the BDT trained for resonances of spin 2 and mass $750\,$GeV production for the $2\ell$(ss) category. The resonant HH signal is shown for a cross section amounting to $1\,$pb. The distributions expected for the background processes are shown for the values of nuisance parameters obtained from the ML fit of the signal+background hypothesis to the data. The binning is chosen to approximate signal quantiles.

Distribution in the output of the BDT trained for resonances of spin 2 and mass $750\,$GeV production for the $3\ell$ category. The resonant HH signal is shown for a cross section amounting to $1\,$pb. The distributions expected for the background processes are shown for the values of nuisance parameters obtained from the ML fit of the signal+background hypothesis to the data. The binning is chosen to approximate signal quantiles.

Predicted and observed yields as a function of $m_{4\ell}$ in the VBS-Suppressed region. Overflow events are included in the last bin of the distribution.

Differential cross-sections for inclusive 4ljj production in the VBS-Enhanced region as a function of $m_{jj}$. Overflow events are included in the last bin of the distribution.

Differential cross-sections for inclusive 4ljj production in the VBS-Suppressed region as a function of $m_{jj}$. Overflow events are included in the last bin of the distribution.

Differential cross-sections for inclusive 4ljj production in the VBS-Enhanced region as a function of $m_{4\ell}$. Overflow events are included in the last bin of the distribution.

Differential cross-sections for inclusive 4ljj production in the VBS-Suppressed region as a function of $m_{4\ell}$. Overflow events are included in the last bin of the distribution.

Differential cross-sections for inclusive 4ljj production in the VBS-Enhanced region as a function of $ p_{T,4l}$. Overflow events are included in the last bin of the distribution.

Differential cross-sections for inclusive 4ljj production in the VBS-Suppressed region as a function of $ p_{T,4l}$. Overflow events are included in the last bin of the distribution.

Differential cross-sections for inclusive 4ljj production in the VBS-Enhanced region as a function of $\Delta\phi_{jj}$. Overflow events are included in the last bin of the distribution.

Differential cross-sections for inclusive 4ljj production in the VBS-Suppressed region as a function of $\Delta\phi_{jj}$. Overflow events are included in the last bin of the distribution.

Differential cross-sections for inclusive 4ljj production in the VBS-Enhanced region as a function of $|\Delta y_{jj}|$. Overflow events are included in the last bin of the distribution.

Differential cross-sections for inclusive 4ljj production in the VBS-Suppressed region as a function of $|\Delta y_{jj}|$. Overflow events are included in the last bin of the distribution.

Differential cross-sections for inclusive 4ljj production in the VBS-Enhanced region as a function of $cos(\theta^{*}_{12})$. Overflow events are included in the last bin of the distribution.

Differential cross-sections for inclusive 4ljj production in the VBS-Suppressed region as a function of $cos(\theta^{*}_{12})$. Overflow events are included in the last bin of the distribution.

Differential cross-sections for inclusive 4ljj production in the VBS-Enhanced region as a function of $cos(\theta^{*}_{34})$. Overflow events are included in the last bin of the distribution.

Differential cross-sections for inclusive 4ljj production in the VBS-Suppressed region as a function of $cos(\theta^{*}_{34})$. Overflow events are included in the last bin of the distribution.

Differential cross-sections for inclusive 4ljj production in the VBS-Enhanced region as a function of $p_{T,jj}$. Overflow events are included in the last bin of the distribution.

Differential cross-sections for inclusive 4ljj production in the VBS-Suppressed region as a function of $p_{T,jj}$. Overflow events are included in the last bin of the distribution.

Differential cross-sections for inclusive 4ljj production in the VBS-Enhanced region as a function of $p_{T,4ljj}$. Overflow events are included in the last bin of the distribution.

Differential cross-sections for inclusive 4ljj production in the VBS-Suppressed region as a function of $p_{T,4ljj}$. Overflow events are included in the last bin of the distribution.

Differential cross-sections for inclusive 4ljj production in the VBS-Enhanced region as a function of $S_{T,4ljj}$. Overflow events are included in the last bin of the distribution.

Differential cross-sections for inclusive 4ljj production in the VBS-Suppressed region as a function of $S_{T,4ljj}$. Overflow events are included in the last bin of the distribution.

Statistical correlation between different bins of the unfolded cross-section for all the measured observables in the VBS-Enhanced region.

Statistical correlation between different bins of the unfolded cross-section for all the measured observables in the VBS-Suppressed region.

Observed profiled likelihood on $f_{\Lambda1}$ using Approach 1. The signal strength modifiers are treated as free parameters. Axis scales are varied to improve the visibility of important features.

Expected profiled likelihood on $f_{a3}$ using Approach 1. The signal strength modifiers are treated as free parameters.

Observed profiled likelihood on $f_{a3}$ using Approach 1. The signal strength modifiers are treated as free parameters.

Expected profiled likelihood on $f_{\Lambda1}^{Z\gamma}$ using Approach 1. The signal strength modifiers are treated as free parameters.

Observed profiled likelihood on $f_{\Lambda1}^{Z\gamma}$ using Approach 1. The signal strength modifiers are treated as free parameters.

Expected profiled likelihood on $f_{a2}$ using Approach 2. The other two anomalous coupling cross section fractions are fixed to zero. The signal strength modifiers are treated as free parameters. Axis scales are varied to improve the visibility of important features.

Observed profiled likelihood on $f_{a2}$ using Approach 2. The other two anomalous coupling cross section fractions are fixed to zero. The signal strength modifiers are treated as free parameters. Axis scales are varied to improve the visibility of important features.

Expected profiled likelihood on $f_{\Lambda1}$ using Approach 2. The other two anomalous coupling cross section fractions are fixed to zero. The signal strength modifiers are treated as free parameters. Axis scales are varied to improve the visibility of important features.

Observed profiled likelihood on $f_{\Lambda1}$ using Approach 2. The other two anomalous coupling cross section fractions are fixed to zero. The signal strength modifiers are treated as free parameters. Axis scales are varied to improve the visibility of important features.

Expected profiled likelihood on $f_{a3}$ using Approach 2. The other two anomalous coupling cross section fractions are fixed to zero. The signal strength modifiers are treated as free parameters.

Observed profiled likelihood on $f_{a3}$ using Approach 2. The other two anomalous coupling cross section fractions are fixed to zero. The signal strength modifiers are treated as free parameters.

Expected profiled likelihood on $f_{a2}$ using Approach 2. The other two anomalous coupling cross section fractions are left floating in the fit. The signal strength modifiers are treated as free parameters. Axis scales are varied to improve the visibility of important features.

Observed profiled likelihood on $f_{a2}$ using Approach 2. The other two anomalous coupling cross section fractions are left floating in the fit. The signal strength modifiers are treated as free parameters. Axis scales are varied to improve the visibility of important features.

Expected profiled likelihood on $f_{\Lambda1}$ using Approach 2. The other two anomalous coupling cross section fractions are left floating in the fit. The signal strength modifiers are treated as free parameters. Axis scales are varied to improve the visibility of important features.

Observed profiled likelihood on $f_{\Lambda1}$ using Approach 2. The other two anomalous coupling cross section fractions are left floating in the fit. The signal strength modifiers are treated as free parameters. Axis scales are varied to improve the visibility of important features.

Expected profiled likelihood on $f_{a3}$ using Approach 2. The other two anomalous coupling cross section fractions are left floating in the fit. The signal strength modifiers are treated as free parameters.

Observed profiled likelihood on $f_{a3}$ using Approach 2. The other two anomalous coupling cross section fractions are left floating in the fit. The signal strength modifiers are treated as free parameters.

Expected profiled likelihood on the $\delta c_{Z}$ coupling of the SMEFT Higgs basis.

Observed profiled likelihood on the $\delta c_{Z}$ coupling of the SMEFT Higgs basis.

Expected profiled likelihood on the $c_{Z\Box}$ coupling of the SMEFT Higgs basis.

Observed profiled likelihood on the $c_{Z\Box}$ coupling of the SMEFT Higgs basis.

Expected profiled likelihood on the $c_{ZZ}$ coupling of the SMEFT Higgs basis.

Observed profiled likelihood on the $c_{ZZ}$ coupling of the SMEFT Higgs basis.

Expected profiled likelihood on the $\tilde{c}_{ZZ}$ coupling of the SMEFT Higgs basis.

Observed profiled likelihood on the $\tilde{c}_{ZZ}$ coupling of the SMEFT Higgs basis.

Expected profiled likelihood on $f_{a3}^{ggH}$. The signal strength modifiers and the CP-odd HVV anomalous coupling cross section fraction are treated as free parameters.

Observed profiled likelihood on $f_{a3}^{ggH}$. The signal strength modifiers and the CP-odd HVV anomalous coupling cross section fraction are treated as free parameters.

Measured natural width

The measured inclusive ratio of production cross sections

Distributions of $S_{\mathrm{ML}}$ for data, simulated background and signal events with $n_{\mathrm{track}}$ of 4. The distributions are shown for split-SUSY signals with a gluino mass of 2000 GeV and neutralino mass of 1800 GeV. Different gluino proper decay lengths are shown as $c\tau$ in the legend. All distributions are normalized to unity.

Distributions of $S_{\mathrm{ML}}$ for data, simulated background and signal events with $n_{\mathrm{track}}$ of $\geq$ 5. The distributions are shown for split-SUSY signals with a gluino mass of 2000 GeV and neutralino mass of 1900 GeV. Different gluino proper decay lengths are shown as $c\tau$ in the legend. All distributions are normalized to unity.

Distributions of $S_{\mathrm{ML}}$ for data, simulated background and signal events with $n_{\mathrm{track}}$ of $\geq$ 5. The distributions are shown for split-SUSY signals with a gluino mass of 2000 GeV and neutralino mass of 1800 GeV. Different gluino proper decay lengths are shown as $c\tau$ in the legend. All distributions are normalized to unity.

The distribution of $n_{\mathrm{track}}$ in different $S_{\mathrm{ML}}$ regions for simulated background events. Events with 0 $ < S_{\mathrm{ML}} < $ 0.2 (blue), 0.2 $ < S_{\mathrm{ML}} < $ 0.6 (red), and 0.6 $ < S_{\mathrm{ML}} < $ 1.0 (green) are compared. All distributions are normalized to unity. The similar $n_{\mathrm{track}}$ distributions demonstrate that $n_{\mathrm{track}}$ and $S_{\mathrm{ML}}$ are decorrelated.

The distribution of $d_{\mathrm{BV}}$ in $K_{\mathrm{S}}^{\mathrm{0}}$ vertices in data (black) and simulation (purple). The lower panel shows the ratio between data and simulation.

The vertex reconstruction efficiency for artificially displaced vertices in data (black) and simulation (red). In this example, the artificially displaced vertices are corrected to mimic split-SUSY signal events with gluino mass of 2000 GeV and neutralino mass of 1800 GeV.

The ML tagging efficiency for artificially displaced vertices in data (black) and simulation (red). In this example, the artificially displaced vertices are corrected to mimic split-SUSY signal events with gluino mass of 2000 GeV and neutralino mass of 1800 GeV.

The 95% CL upper limit on the product of the cross section and branching fraction squared for the split-SUSY signal model with a mass splitting of 100 GeV, shown as a function of gluino mass and $c\tau$. The observed (solid black) and expected (dashed red) exclusion curves are overlaid on the limit plot.

The 95% CL upper limit on the product of the cross section and branching fraction squared for the split-SUSY signal model with a mass splitting of 100 GeV, shown as a function of gluino mass and $c\tau$. The observed (solid black) and expected (dashed red) exclusion curves are overlaid on the limit plot.

The 95% CL upper limit on the product of the cross section and branching fraction squared for the split-SUSY model with a $c\tau$ of 10 mm, shown as a function of gluino mass and mass splitting. The observed (solid black) and expected (dashed red) exclusion curves are overlaid on the limit plot.

The 95% CL upper limit on the product of the cross section and branching fraction squared for the split-SUSY model with a $c\tau$ of 10 mm, shown as a function of gluino mass and mass splitting. The observed (solid black) and expected (dashed red) exclusion curves are overlaid on the limit plot.

The 95% CL upper limit on the product of the cross section and branching fraction squared for the GMSB SUSY signal model, shown as a function of gluino mass and $c\tau$. The observed (solid black) and expected (dashed red) exclusion curves are overlaid on the limit plot.

The 95% CL upper limit on the product of the cross section and branching fraction squared for the GMSB SUSY signal model, shown as a function of gluino mass and $c\tau$. The observed (solid black) and expected (dashed red) exclusion curves are overlaid on the limit plot.