Antiparticle-to-particle yield ratio, 30-50% centrality

Antiparticle-to-particle yield ratio, 50-90% centrality

Electric-charge and baryon chemical potentials, $\mu_Q$ and $\mu_B$, extracted with the Thermal-FIST code, in the 0-5%, 5-10%, 10-30%, 30-50%, and 50-90% centrality classes

Covariance matrix of the centrality-uncorrelated uncertainties on $\mu_Q$ and $\mu_B$, extracted with the Thermal-FIST code, in the 0-5% centrality class

Covariance matrix of the centrality-uncorrelated uncertainties on $\mu_Q$ and $\mu_B$, extracted with the Thermal-FIST code, in the 5-10% centrality class

Covariance matrix of the centrality-uncorrelated uncertainties on $\mu_Q$ and $\mu_B$, extracted with the Thermal-FIST code, in the 10-30% centrality class

Covariance matrix of the centrality-uncorrelated uncertainties on $\mu_Q$ and $\mu_B$, extracted with the Thermal-FIST code, in the 30-50% centrality class

Covariance matrix of the centrality-uncorrelated uncertainties on $\mu_Q$ and $\mu_B$, extracted with the Thermal-FIST code, in the 50-90% centrality class

Baryon chemical potentials, $\mu_B$, extracted with the Thermal-FIST code, in the 0-90% centrality interval

$p_{\mathrm{T}}$-differential $\pi^{-}/\pi^{+}$ antiparticle-to-particle yield ratio, 0-5% centrality

$p_{\mathrm{T}}$-differential $\pi^{-}/\pi^{+}$ antiparticle-to-particle yield ratio, 5-10% centrality

$p_{\mathrm{T}}$-differential $\pi^{-}/\pi^{+}$ antiparticle-to-particle yield ratio, 10-30% centrality

$p_{\mathrm{T}}$-differential $\pi^{-}/\pi^{+}$ antiparticle-to-particle yield ratio, 30-50% centrality

$p_{\mathrm{T}}$-differential $\pi^{-}/\pi^{+}$ antiparticle-to-particle yield ratio, 50-90% centrality

$p_{\mathrm{T}}$-differential $\overline{\mathrm{p}}/\mathrm{p}$ antiparticle-to-particle yield ratio, 0-5% centrality

$p_{\mathrm{T}}$-differential $\overline{\mathrm{p}}/\mathrm{p}$ antiparticle-to-particle yield ratio, 5-10% centrality

$p_{\mathrm{T}}$-differential $\overline{\mathrm{p}}/\mathrm{p}$ antiparticle-to-particle yield ratio, 10-30% centrality

$p_{\mathrm{T}}$-differential $\overline{\mathrm{p}}/\mathrm{p}$ antiparticle-to-particle yield ratio, 30-50% centrality

$p_{\mathrm{T}}$-differential $\overline{\mathrm{p}}/\mathrm{p}$ antiparticle-to-particle yield ratio, 50-90% centrality

$c\mathrm{t}$-differential $\overline{ \Omega}^{+} / \Omega^-$ antiparticle-to-particle yield ratio, 0-5% centrality

$c\mathrm{t}$-differential $\overline{ \Omega}^{+} / \Omega^-$ antiparticle-to-particle yield ratio, 5-10% centrality

$c\mathrm{t}$-differential $\overline{ \Omega}^{+} / \Omega^-$ antiparticle-to-particle yield ratio, 10-30% centrality

$c\mathrm{t}$-differential $\overline{ \Omega}^{+} / \Omega^-$ antiparticle-to-particle yield ratio, 30-50% centrality

$c\mathrm{t}$-differential $\overline{ \Omega}^{+} / \Omega^-$ antiparticle-to-particle yield ratio, 50-90% centrality

$c\mathrm{t}$-differential ${}_{\overline{\Lambda}}^{3}\overline{\mathrm{H}} / ^{3}_{\Lambda}\mathrm{H}$ antiparticle-to-particle yield ratio, 0-5% centrality

$c\mathrm{t}$-differential ${}_{\overline{\Lambda}}^{3}\overline{\mathrm{H}} / ^{3}_{\Lambda}\mathrm{H}$ antiparticle-to-particle yield ratio, 5-10% centrality

$c\mathrm{t}$-differential ${}_{\overline{\Lambda}}^{3}\overline{\mathrm{H}} / ^{3}_{\Lambda}\mathrm{H}$ antiparticle-to-particle yield ratio, 10-30% centrality

$c\mathrm{t}$-differential ${}_{\overline{\Lambda}}^{3}\overline{\mathrm{H}} / ^{3}_{\Lambda}\mathrm{H}$ antiparticle-to-particle yield ratio, 30-50% centrality

$p_{\mathrm{T}}$-differential $^{3}\overline{\mathrm{H}} / ^{3}\mathrm{H}$ antiparticle-to-particle yield ratio, 0-5% centrality

$p_{\mathrm{T}}$-differential $^{3}\overline{\mathrm{H}} / ^{3}\mathrm{H}$ antiparticle-to-particle yield ratio, 5-10% centrality

$p_{\mathrm{T}}$-differential $^{3}\overline{\mathrm{H}} / ^{3}\mathrm{H}$ antiparticle-to-particle yield ratio, 10-30% centrality

$p_{\mathrm{T}}$-differential $^{3}\overline{\mathrm{H}} / ^{3}\mathrm{H}$ antiparticle-to-particle yield ratio, 30-50% centrality

$p_{\mathrm{T}}$-differential $^{3}\overline{\mathrm{H}} / ^{3}\mathrm{H}$ antiparticle-to-particle yield ratio, 50-90% centrality

$p_{\mathrm{T}}$-differential $^{3}\overline{\mathrm{He}} / ^{3}\mathrm{He}$ antiparticle-to-particle yield ratio, 0-5% centrality

$p_{\mathrm{T}}$-differential $^{3}\overline{\mathrm{He}} / ^{3}\mathrm{He}$ antiparticle-to-particle yield ratio, 5-10% centrality

$p_{\mathrm{T}}$-differential $^{3}\overline{\mathrm{He}} / ^{3}\mathrm{He}$ antiparticle-to-particle yield ratio, 10-30% centrality

$p_{\mathrm{T}}$-differential $^{3}\overline{\mathrm{He}} / ^{3}\mathrm{He}$ antiparticle-to-particle yield ratio, 30-50% centrality

$p_{\mathrm{T}}$-differential $^{3}\overline{\mathrm{He}} / ^{3}\mathrm{He}$ antiparticle-to-particle yield ratio, 50-90% centrality

Total covariance matrix of the baryon chemical potential, $\mu_B$, extracted with the Thermal-FIST code, in the 0-5%, 5-10%, 10-30%, 30-50%, and 50-90% centrality classes

Total covariance matrix of the electric-charge chemical potential, $\mu_Q$, extracted with the Thermal-FIST code, in the 0-5%, 5-10%, 10-30%, 30-50%, and 50-90% centrality classes

$\chi^{2}$ of the centrality-averaged baryon chemical potential, $\mu_B$, extracted with the Thermal-FIST code

$\chi^{2}$ of the centrality-averaged electric-charge chemical potential, $\mu_Q$, extracted with the Thermal-FIST code

$\chi^{2}$ of the centrality-averaged baryon chemical potential, $\mu_Q$, extracted with the Thermal-FIST code

Weights from b tagging efficiency ratios as functions of the five-jet invariant mass in 2018 data for the high-mass selection, connecting the 2M1L and 3M regions. The red line corresponds to the central value of the transfer function and the shaded area represents the 95% confidence level uncertainty band. For the high-mass analysis only signals with mass above 800GeV are tested, so primarily the lower part of the distribution contributes to the final result.

Weights from b tagging efficiency ratios as functions of the five-jet invariant mass in 2018 data for the high-mass selection, connecting the 3M and 3T regions. The red line corresponds to the central value of the transfer function and the shaded area represents the 95% confidence level uncertainty band. For the high-mass analysis only signals with mass above 800GeV are tested, so primarily the lower part of the distribution contributes to the final result.

The five-jet invariant mass distribution in the tH channel (black markers) after the high-mass selection in the QCD multijet 3T control region for the 2018 data set. The histograms are the corresponding reweighted 2M1L distributions. The background distribution is normalized to the number of entries in the data. The shaded area corresponds to the statistical uncertainties in the 2M1L control regions. A potential 900 GeV T' signal (red cross-hatched histogram) is added to the background histogram demonstrating a negligible contribution. Similar results are observed in the tZ channel, and for the other years, but with slightly larger statistical uncertainties.

The five-jet invariant mass distribution in the tH channel (black markers) after the high-mass selection in the ttbar 2T1L control region for the 2018 data set. The histograms are the corresponding reweighted 2M1L distributions. The background distribution is normalized to the number of entries in the data. The shaded area corresponds to the statistical uncertainties in the 2M1L control regions. A potential 900 GeV T' signal (red cross-hatched histogram) is added to the background histogram demonstrating a negligible contribution. Similar results are observed in the tZ channel, and for the other years, but with slightly larger statistical uncertainties.

The five-jet invariant mass distribution in the tH channel (black markers) after the high-mass selection in the 3M signal region for the 2018 data set. The histograms are the corresponding reweighted 2M1L distributions. The background distribution is normalized to the number of entries in the data. The shaded area corresponds to the statistical uncertainties in the 2M1L control regions. A potential 900 GeV T' signal (red cross-hatched histogram) is added to the background histogram demonstrating a negligible contribution. Similar results are observed in the tZ channel, and for the other years, but with slightly larger statistical uncertainties.

Background: Five-jet invariant mass distributions after a background-only fit (blue histogram) to the complete dataset (black markers) in the 2M1L regions for the low-mass selections. The dashed blue band represents the uncertainty on the fitted background estimate, and red dashed line shows the expected signal distribution for a 700 GeV T'. The fit is performed on the combined data from all 3 years in the all-tH channel.

Data: Five-jet invariant mass distributions after a background-only fit (blue histogram) to the complete dataset (black markers) in the 2M1L regions for the low-mass selections. The dashed blue band represents the uncertainty on the fitted background estimate, and red dashed line shows the expected signal distribution for a 700 GeV T'. The fit is performed on the combined data from all 3 years in the all-tH channel.

Signal: Five-jet invariant mass distributions after a background-only fit (blue histogram) to the complete dataset (black markers) in the 2M1L regions for the low-mass selections. The dashed blue band represents the uncertainty on the fitted background estimate, and red dashed line shows the expected signal distribution for a 700 GeV T'. The fit is performed on the combined data from all 3 years in the all-tH channel.

Background: Five-jet invariant mass distributions after a background-only fit (blue histogram) to the complete dataset (black markers) in the 2M1L regions for the high-mass selections. The dashed blue band represents the uncertainty on the fitted background estimate, and red dashed line shows the expected signal distribution for a 900 GeV T'. The fit is performed on the combined data from all 3 years in the all-tH channel.

Data: Five-jet invariant mass distributions after a background-only fit (blue histogram) to the complete dataset (black markers) in the 2M1L regions for the high-mass selections. The dashed blue band represents the uncertainty on the fitted background estimate, and red dashed line shows the expected signal distribution for a 900 GeV T'. The fit is performed on the combined data from all 3 years in the all-tH channel.

Signal: Five-jet invariant mass distributions after a background-only fit (blue histogram) to the complete dataset (black markers) in the 2M1L regions for the high-mass selections. The dashed blue band represents the uncertainty on the fitted background estimate, and red dashed line shows the expected signal distribution for a 900 GeV T'. The fit is performed on the combined data from all 3 years in the all-tH channel.

Background: Five-jet invariant mass distributions after a background-only fit (blue histogram) to the complete dataset (black markers) in the 3M regions for the low-mass selections. The dashed blue band represents the uncertainty on the fitted background estimate, and red dashed line shows the expected signal distribution for a 700 GeV T'. The fit is performed on the combined data from all 3 years in the all-tH channel.

Data: Five-jet invariant mass distributions after a background-only fit (blue histogram) to the complete dataset (black markers) in the 3M regions for the low-mass selections. The dashed blue band represents the uncertainty on the fitted background estimate, and red dashed line shows the expected signal distribution for a 700 GeV T'. The fit is performed on the combined data from all 3 years in the all-tH channel.

Signal: Five-jet invariant mass distributions after a background-only fit (blue histogram) to the complete dataset (black markers) in the 3M regions for the low-mass selections. The dashed blue band represents the uncertainty on the fitted background estimate, and red dashed line shows the expected signal distribution for a 700 GeV T'. The fit is performed on the combined data from all 3 years in the all-tH channel.

Background: Five-jet invariant mass distributions after a background-only fit (blue histogram) to the complete dataset (black markers) in the 3M regions for the high-mass selections. The dashed blue band represents the uncertainty on the fitted background estimate, and red dashed line shows the expected signal distribution for a 900 GeV T'. The fit is performed on the combined data from all 3 years in the all-tH channel.

Data: Five-jet invariant mass distributions after a background-only fit (blue histogram) to the complete dataset (black markers) in the 3M regions for the high-mass selections. The dashed blue band represents the uncertainty on the fitted background estimate, and red dashed line shows the expected signal distribution for a 900 GeV T'. The fit is performed on the combined data from all 3 years in the all-tH channel.

Signal: Five-jet invariant mass distributions after a background-only fit (blue histogram) to the complete dataset (black markers) in the 3M regions for the high-mass selections. The dashed blue band represents the uncertainty on the fitted background estimate, and red dashed line shows the expected signal distribution for a 900 GeV T'. The fit is performed on the combined data from all 3 years in the all-tH channel.

Background: Five-jet invariant mass distributions after a background-only fit (blue histogram) to the complete dataset (black markers) in the 3T regions for the low-mass selections. The dashed blue band represents the uncertainty on the fitted background estimate, and red dashed line shows the expected signal distribution for a 700 GeV T'. The fit is performed on the combined data from all 3 years in the all-tH channel.

Data: Five-jet invariant mass distributions after a background-only fit (blue histogram) to the complete dataset (black markers) in the 3T regions for the low-mass selections. The dashed blue band represents the uncertainty on the fitted background estimate, and red dashed line shows the expected signal distribution for a 700 GeV T'. The fit is performed on the combined data from all 3 years in the all-tH channel.

Signal: Five-jet invariant mass distributions after a background-only fit (blue histogram) to the complete dataset (black markers) in the 3T regions for the low-mass selections. The dashed blue band represents the uncertainty on the fitted background estimate, and red dashed line shows the expected signal distribution for a 700 GeV T'. The fit is performed on the combined data from all 3 years in the all-tH channel.

Background: Five-jet invariant mass distributions after a background-only fit (blue histogram) to the complete dataset (black markers) in the 3T regions for the high-mass selection. The dashed blue band represents the uncertainty on the fitted background estimate, and red dashed line shows the expected signal distribution for a 900 GeV T'. The fit is performed on the combined data from all 3 years in the all-tH channel.

Data: Five-jet invariant mass distributions after a background-only fit (blue histogram) to the complete dataset (black markers) in the 3T regions for the high-mass selection. The dashed blue band represents the uncertainty on the fitted background estimate, and red dashed line shows the expected signal distribution for a 900 GeV T'. The fit is performed on the combined data from all 3 years in the all-tH channel.

Signal: Five-jet invariant mass distributions after a background-only fit (blue histogram) to the complete dataset (black markers) in the 3T regions for the high-mass selection. The dashed blue band represents the uncertainty on the fitted background estimate, and red dashed line shows the expected signal distribution for a 900 GeV T'. The fit is performed on the combined data from all 3 years in the all-tH channel.

Observed p-values when considering the tH channel for each year and their combination.

Observed and expected 95% CL upper limits on the product of the production cross section for a single VLQ T production and the branching ration given as functions of $m_{T'}$ for a relative width of 1%. 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 solid red curves show the theoretical expectation at LO.

Observed and expected 95% CL upper limits on the product of the production cross section for a single VLQ T production and the branching ration given as functions of $m_{T'}$ for a relative width of 1%. 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 solid red curves show the theoretical expectation at LO.

Observed and expected 95% CL upper limits on the product of the production cross section for a single VLQ T production and the branching ration given as functions of $m_{T'}$ for a relative width of 1%. 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 solid red curves show the theoretical expectation at LO.

Observed and expected 95% CL upper limits on the product of the production cross section for a single VLQ T production and the branching ration given as functions of $m_{T'}$ for a relative width of 1%. 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 solid red curves show the theoretical expectation at LO.

Weights from b tagging efficiency ratios as functions of the five-jet invariant mass in 2016 data for the low-mass selection, connecting the 2M1L and 3M regions. The red line corresponds to the central value of the transfer function and the shaded area represents the 95% confidence level uncertainty band. For the low-mass analysis only signals with mass below 800GeV are tested, so primarily the lower part of the distribution contributes to the final result.

Weights from b tagging efficiency ratios as functions of the five-jet invariant mass in 2017 data for the low-mass selection, connecting the 3M and 3T regions. The red line corresponds to the central value of the transfer function and the shaded area represents the 95% confidence level uncertainty band. For the low-mass analysis only signals with mass below 800GeV are tested, so primarily the lower part of the distribution contributes to the final result.

Weights from b tagging efficiency ratios as functions of the five-jet invariant mass in 2016 data for the low-mass selection, connecting the 3M and 3T regions. The red line corresponds to the central value of the transfer function and the shaded area represents the 95% confidence level uncertainty band. For the low-mass analysis only signals with mass below 800GeV are tested, so primarily the lower part of the distribution contributes to the final result.

Weights from b tagging efficiency ratios as functions of the five-jet invariant mass in 2017 data for the low-mass selection, connecting the 3M and 3T regions. The red line corresponds to the central value of the transfer function and the shaded area represents the 95% confidence level uncertainty band. For the low-mass analysis only signals with mass below 800GeV are tested, so primarily the lower part of the distribution contributes to the final result.

Weights from b tagging efficiency ratios as functions of the five-jet invariant mass in 2016 data for the high-mass selection, connecting the 2M1L and 3M regions. The red line corresponds to the central value of the transfer function and the shaded area represents the 95% confidence level uncertainty band. For the high-mass analysis only signals with mass above 800GeV are tested, so primarily the lower part of the distribution contributes to the final result.

Weights from b tagging efficiency ratios as functions of the five-jet invariant mass in 2017 data for the high-mass selection, connecting the 3M and 3T regions. The red line corresponds to the central value of the transfer function and the shaded area represents the 95% confidence level uncertainty band. For the high-mass analysis only signals with mass above 800GeV are tested, so primarily the lower part of the distribution contributes to the final result.

Weights from b tagging efficiency ratios as functions of the five-jet invariant mass in 2016 data for the high-mass selection, connecting the 3M and 3T regions. The red line corresponds to the central value of the transfer function and the shaded area represents the 95% confidence level uncertainty band. For the high-mass analysis only signals with mass above 800GeV are tested, so primarily the lower part of the distribution contributes to the final result.

Weights from b tagging efficiency ratios as functions of the five-jet invariant mass in 2017 data for the high-mass selection, connecting the 3M and 3T regions. The red line corresponds to the central value of the transfer function and the shaded area represents the 95% confidence level uncertainty band. For the high-mass analysis only signals with mass above 800GeV are tested, so primarily the lower part of the distribution contributes to the final result.

Background: Five-jet invariant mass distributions after a background-only fit (blue histogram) to the complete dataset (black markers) in the 2M1L regions for the low-mass selections. The dashed blue band represents the uncertainty on the fitted background estimate, and red dashed line shows the expected signal distribution for a 700 GeV T'. The fit is performed on the combined data from all 3 years in the tZ and tH channel.

Data: Five-jet invariant mass distributions after a background-only fit (blue histogram) to the complete dataset (black markers) in the 2M1L regions for the low-mass selections. The dashed blue band represents the uncertainty on the fitted background estimate, and red dashed line shows the expected signal distribution for a 700 GeV T'. The fit is performed on the combined data from all 3 years in the tZ and tH channel.

Signal: Five-jet invariant mass distributions after a background-only fit (blue histogram) to the complete dataset (black markers) in the 2M1L regions for the low-mass selections. The dashed blue band represents the uncertainty on the fitted background estimate, and red dashed line shows the expected signal distribution for a 700 GeV T'. The fit is performed on the combined data from all 3 years in the tZ and tH channel.

Background: Five-jet invariant mass distributions after a background-only fit (blue histogram) to the complete dataset (black markers) in the 2M1L regions for the high-mass selections. The dashed blue band represents the uncertainty on the fitted background estimate, and red dashed line shows the expected signal distribution for a 900 GeV T'. The fit is performed on the combined data from all 3 years in the tZ and tH channel.

Data: Five-jet invariant mass distributions after a background-only fit (blue histogram) to the complete dataset (black markers) in the 2M1L regions for the high-mass selections. The dashed blue band represents the uncertainty on the fitted background estimate, and red dashed line shows the expected signal distribution for a 900 GeV T'. The fit is performed on the combined data from all 3 years in the tZ and tH channel.

Signal: Five-jet invariant mass distributions after a background-only fit (blue histogram) to the complete dataset (black markers) in the 2M1L regions for the high-mass selections. The dashed blue band represents the uncertainty on the fitted background estimate, and red dashed line shows the expected signal distribution for a 900 GeV T'. The fit is performed on the combined data from all 3 years in the tZ and tH channel.

Background: Five-jet invariant mass distributions after a background-only fit (blue histogram) to the complete dataset (black markers) in the 3M regions for the low-mass selections. The dashed blue band represents the uncertainty on the fitted background estimate, and red dashed line shows the expected signal distribution for a 700 GeV T'. The fit is performed on the combined data from all 3 years in the tZ and tH channel.

Data: Five-jet invariant mass distributions after a background-only fit (blue histogram) to the complete dataset (black markers) in the 3M regions for the low-mass selections. The dashed blue band represents the uncertainty on the fitted background estimate, and red dashed line shows the expected signal distribution for a 700 GeV T'. The fit is performed on the combined data from all 3 years in the tZ and tH channel.

Signal: Five-jet invariant mass distributions after a background-only fit (blue histogram) to the complete dataset (black markers) in the 3M regions for the low-mass selections. The dashed blue band represents the uncertainty on the fitted background estimate, and red dashed line shows the expected signal distribution for a 700 GeV T'. The fit is performed on the combined data from all 3 years in the tZ and tH channel.

Background: Five-jet invariant mass distributions after a background-only fit (blue histogram) to the complete dataset (black markers) in the 3M regions for the high-mass selections. The dashed blue band represents the uncertainty on the fitted background estimate, and red dashed line shows the expected signal distribution for a 900 GeV T'. The fit is performed on the combined data from all 3 years in the tZ and tH channel.

Data: Five-jet invariant mass distributions after a background-only fit (blue histogram) to the complete dataset (black markers) in the 3M regions for the high-mass selections. The dashed blue band represents the uncertainty on the fitted background estimate, and red dashed line shows the expected signal distribution for a 900 GeV T'. The fit is performed on the combined data from all 3 years in the tZ and tH channel.

Signal: Five-jet invariant mass distributions after a background-only fit (blue histogram) to the complete dataset (black markers) in the 3M regions for the high-mass selections. The dashed blue band represents the uncertainty on the fitted background estimate, and red dashed line shows the expected signal distribution for a 900 GeV T'. The fit is performed on the combined data from all 3 years in the tZ and tH channel.

Background: Five-jet invariant mass distributions after a background-only fit (blue histogram) to the complete dataset (black markers) in the 3T regions for the low-mass selections. The dashed blue band represents the uncertainty on the fitted background estimate, and red dashed line shows the expected signal distribution for a 700 GeV T'. The fit is performed on the combined data from all 3 years in the tZ and tH channel.

Data: Five-jet invariant mass distributions after a background-only fit (blue histogram) to the complete dataset (black markers) in the 3T regions for the low-mass selections. The dashed blue band represents the uncertainty on the fitted background estimate, and red dashed line shows the expected signal distribution for a 700 GeV T'. The fit is performed on the combined data from all 3 years in the tZ and tH channel.

Signal: Five-jet invariant mass distributions after a background-only fit (blue histogram) to the complete dataset (black markers) in the 3T regions for the low-mass selections. The dashed blue band represents the uncertainty on the fitted background estimate, and red dashed line shows the expected signal distribution for a 700 GeV T'. The fit is performed on the combined data from all 3 years in the tZ and tH channel.

Background: Five-jet invariant mass distributions after a background-only fit (blue histogram) to the complete dataset (black markers) in the 3T regions for the high-mass selection. The dashed blue band represents the uncertainty on the fitted background estimate, and red dashed line shows the expected signal distribution for a 900 GeV T'. The fit is performed on the combined data from all 3 years in the tZ and tH channel.

Data: Five-jet invariant mass distributions after a background-only fit (blue histogram) to the complete dataset (black markers) in the 3T regions for the high-mass selection. The dashed blue band represents the uncertainty on the fitted background estimate, and red dashed line shows the expected signal distribution for a 900 GeV T'. The fit is performed on the combined data from all 3 years in the tZ and tH channel.

Signal: Five-jet invariant mass distributions after a background-only fit (blue histogram) to the complete dataset (black markers) in the 3T regions for the high-mass selection. The dashed blue band represents the uncertainty on the fitted background estimate, and red dashed line shows the expected signal distribution for a 900 GeV T'. The fit is performed on the combined data from all 3 years in the tZ and tH channel.

Observed differential $m_{\Gamma\Gamma}$ mass spectrum for 0.4$ < \alpha < $0.44%, where $\alpha = m_\phi/m_X$. The cross-section is calculated by dividing the event yield by the bin width and luminosity.

Observed differential $m_{\Gamma\Gamma}$ mass spectrum for 0.49$ < \alpha < $0.55%, where $\alpha = m_\phi/m_X$. The cross-section is calculated by dividing the event yield by the bin width and luminosity.

Observed differential $m_{\Gamma\Gamma}$ mass spectrum for 0.55$ < \alpha < $0.6%, where $\alpha = m_\phi/m_X$. The cross-section is calculated by dividing the event yield by the bin width and luminosity.

Observed differential $m_{\Gamma\Gamma}$ mass spectrum for 0.6$ < \alpha < $0.7%, where $\alpha = m_\phi/m_X$. The cross-section is calculated by dividing the event yield by the bin width and luminosity.

Observed differential $m_{\Gamma\Gamma}$ mass spectrum for 0.7$ < \alpha < $0.81%, where $\alpha = m_\phi/m_X$. The cross-section is calculated by dividing the event yield by the bin width and luminosity.

Observed differential $m_{\Gamma\Gamma}$ mass spectrum for 0.81$ < \alpha < $3.0%, where $\alpha = m_\phi/m_X$. The cross-section is calculated by dividing the event yield by the bin width and luminosity.

Two dimensional plot where the Z-axis is the observed (paper Fig. 3) or expected (Supp. Fig. 20) 95% CL upper limits on the product of the cross section for $X \to \phi\phi \to (\gamma\gamma)(\gamma\gamma)$. The corresponding expected limits and their variations at the 1 and 2 standard deviation levels are also shown. Limits are compared to various extended higgs sector model cross sections as a function of the parameter $m_X N / f$.

Expected exclusion limits for $m_X N / f = 1/9$ for signal cross sections for for the production of $X \to \phi\phi \to (\gamma\gamma)(\gamma\gamma)$.

Expected exclusion limits for $m_X N / f = 1$ for signal cross sections for for the production of $X \to \phi\phi \to (\gamma\gamma)(\gamma\gamma)$

The observed 95% CL upper limits on the product of the cross section, and branching fraction for the production of $X \to \phi\phi \to (\gamma\gamma)(\gamma\gamma)$, with $\alpha = m_\phi/m_X = 0.005$. The corresponding expected limits and their variations at the 1 and 2 standard deviation levels are also shown. Limits are compared to various extended higgs sector model cross sections as a function of the parameter $m_X N / f$.

The observed 95% CL upper limits on the product of the cross section, and branching fraction for the production of $X \to \phi\phi \to (\gamma\gamma)(\gamma\gamma)$, with $\alpha = m_\phi/m_X = 0.006$. The corresponding expected limits and their variations at the 1 and 2 standard deviation levels are also shown. Limits are compared to various extended higgs sector model cross sections as a function of the parameter $m_X N / f$.

The observed 95% CL upper limits on the product of the cross section, and branching fraction for the production of $X \to \phi\phi \to (\gamma\gamma)(\gamma\gamma)$, with $\alpha = m_\phi/m_X = 0.007$. The corresponding expected limits and their variations at the 1 and 2 standard deviation levels are also shown. Limits are compared to various extended higgs sector model cross sections as a function of the parameter $m_X N / f$.

The observed 95% CL upper limits on the product of the cross section, and branching fraction for the production of $X \to \phi\phi \to (\gamma\gamma)(\gamma\gamma)$, with $\alpha = m_\phi/m_X = 0.008$. The corresponding expected limits and their variations at the 1 and 2 standard deviation levels are also shown. Limits are compared to various extended higgs sector model cross sections as a function of the parameter $m_X N / f$.

The observed 95% CL upper limits on the product of the cross section, and branching fraction for the production of $X \to \phi\phi \to (\gamma\gamma)(\gamma\gamma)$, with $\alpha = m_\phi/m_X = 0.009$. The corresponding expected limits and their variations at the 1 and 2 standard deviation levels are also shown. Limits are compared to various extended higgs sector model cross sections as a function of the parameter $m_X N / f$.

The observed 95% CL upper limits on the product of the cross section, and branching fraction for the production of $X \to \phi\phi \to (\gamma\gamma)(\gamma\gamma)$, with $\alpha = m_\phi/m_X = 0.01$. The corresponding expected limits and their variations at the 1 and 2 standard deviation levels are also shown. Limits are compared to various extended higgs sector model cross sections as a function of the parameter $m_X N / f$.

The observed 95% CL upper limits on the product of the cross section, and branching fraction for the production of $X \to \phi\phi \to (\gamma\gamma)(\gamma\gamma)$, with $\alpha = m_\phi/m_X = 0.011$. The corresponding expected limits and their variations at the 1 and 2 standard deviation levels are also shown. Limits are compared to various extended higgs sector model cross sections as a function of the parameter $m_X N / f$.

The observed 95% CL upper limits on the product of the cross section, and branching fraction for the production of $X \to \phi\phi \to (\gamma\gamma)(\gamma\gamma)$, with $\alpha = m_\phi/m_X = 0.012$. The corresponding expected limits and their variations at the 1 and 2 standard deviation levels are also shown. Limits are compared to various extended higgs sector model cross sections as a function of the parameter $m_X N / f$.

The observed 95% CL upper limits on the product of the cross section, and branching fraction for the production of $X \to \phi\phi \to (\gamma\gamma)(\gamma\gamma)$, with $\alpha = m_\phi/m_X = 0.013$. The corresponding expected limits and their variations at the 1 and 2 standard deviation levels are also shown. Limits are compared to various extended higgs sector model cross sections as a function of the parameter $m_X N / f$.

The observed 95% CL upper limits on the product of the cross section, and branching fraction for the production of $X \to \phi\phi \to (\gamma\gamma)(\gamma\gamma)$, with $\alpha = m_\phi/m_X = 0.014$. The corresponding expected limits and their variations at the 1 and 2 standard deviation levels are also shown. Limits are compared to various extended higgs sector model cross sections as a function of the parameter $m_X N / f$.

The observed 95% CL upper limits on the product of the cross section, and branching fraction for the production of $X \to \phi\phi \to (\gamma\gamma)(\gamma\gamma)$, with $\alpha = m_\phi/m_X = 0.015$. The corresponding expected limits and their variations at the 1 and 2 standard deviation levels are also shown. Limits are compared to various extended higgs sector model cross sections as a function of the parameter $m_X N / f$.

The observed 95% CL upper limits on the product of the cross section, and branching fraction for the production of $X \to \phi\phi \to (\gamma\gamma)(\gamma\gamma)$, with $\alpha = m_\phi/m_X = 0.016$. The corresponding expected limits and their variations at the 1 and 2 standard deviation levels are also shown. Limits are compared to various extended higgs sector model cross sections as a function of the parameter $m_X N / f$.

The observed 95% CL upper limits on the product of the cross section, and branching fraction for the production of $X \to \phi\phi \to (\gamma\gamma)(\gamma\gamma)$, with $\alpha = m_\phi/m_X = 0.017$. The corresponding expected limits and their variations at the 1 and 2 standard deviation levels are also shown. Limits are compared to various extended higgs sector model cross sections as a function of the parameter $m_X N / f$.

The observed 95% CL upper limits on the product of the cross section, and branching fraction for the production of $X \to \phi\phi \to (\gamma\gamma)(\gamma\gamma)$, with $\alpha = m_\phi/m_X = 0.018$. The corresponding expected limits and their variations at the 1 and 2 standard deviation levels are also shown. Limits are compared to various extended higgs sector model cross sections as a function of the parameter $m_X N / f$.

The observed 95% CL upper limits on the product of the cross section, and branching fraction for the production of $X \to \phi\phi \to (\gamma\gamma)(\gamma\gamma)$, with $\alpha = m_\phi/m_X = 0.019$. The corresponding expected limits and their variations at the 1 and 2 standard deviation levels are also shown. Limits are compared to various extended higgs sector model cross sections as a function of the parameter $m_X N / f$.

The observed 95% CL upper limits on the product of the cross section, and branching fraction for the production of $X \to \phi\phi \to (\gamma\gamma)(\gamma\gamma)$, with $\alpha = m_\phi/m_X = 0.02$. The corresponding expected limits and their variations at the 1 and 2 standard deviation levels are also shown. Limits are compared to various extended higgs sector model cross sections as a function of the parameter $m_X N / f$.

The observed 95% CL upper limits on the product of the cross section, and branching fraction for the production of $X \to \phi\phi \to (\gamma\gamma)(\gamma\gamma)$, with $\alpha = m_\phi/m_X = 0.021$. The corresponding expected limits and their variations at the 1 and 2 standard deviation levels are also shown. Limits are compared to various extended higgs sector model cross sections as a function of the parameter $m_X N / f$.

The observed 95% CL upper limits on the product of the cross section, and branching fraction for the production of $X \to \phi\phi \to (\gamma\gamma)(\gamma\gamma)$, with $\alpha = m_\phi/m_X = 0.022$. The corresponding expected limits and their variations at the 1 and 2 standard deviation levels are also shown. Limits are compared to various extended higgs sector model cross sections as a function of the parameter $m_X N / f$.

The observed 95% CL upper limits on the product of the cross section, and branching fraction for the production of $X \to \phi\phi \to (\gamma\gamma)(\gamma\gamma)$, with $\alpha = m_\phi/m_X = 0.023$. The corresponding expected limits and their variations at the 1 and 2 standard deviation levels are also shown. Limits are compared to various extended higgs sector model cross sections as a function of the parameter $m_X N / f$.

The observed 95% CL upper limits on the product of the cross section, and branching fraction for the production of $X \to \phi\phi \to (\gamma\gamma)(\gamma\gamma)$, with $\alpha = m_\phi/m_X = 0.024$. The corresponding expected limits and their variations at the 1 and 2 standard deviation levels are also shown. Limits are compared to various extended higgs sector model cross sections as a function of the parameter $m_X N / f$.

The observed 95% CL upper limits on the product of the cross section, and branching fraction for the production of $X \to \phi\phi \to (\gamma\gamma)(\gamma\gamma)$, with $\alpha = m_\phi/m_X = 0.025$. The corresponding expected limits and their variations at the 1 and 2 standard deviation levels are also shown. Limits are compared to various extended higgs sector model cross sections as a function of the parameter $m_X N / f$.

Signal fractional efficiencies

Local significance in units of standard deviations in the $(m_\phi/m_X) − m_X$ plane.

The double ratio of particle yield of f0((980) to K*(892)0

Transverse-momentum-differential particle yield ratio of f$_{0}$(980) to charged pions and its double ratio

Transverse-momentum-differential particle yield ratio of f$_{0}$(980) to K$^{*}(892)$^{0}$ and its double ratio

Nuclear modification factor of f0(980) in p-Pb collisions at 5.02 TeV

Measured $R_\text{AA}$ for the $\Upsilon(3S)$ state in the 0–90% centrality interval, integrated over the full kinematic range $p_\text{T}$ < 30 GeV/c and |y| < 2.4. The global uncertainty "PP MB" represents the pp luminosity and PbPb $N_\text{MB}$ combined uncertainties, whereas the global uncertainty "PP 3S" corresponds to the uncertainty on the$\Upsilon(3S)$ pp yields.

Measured $R_\text{AA}$ for the $\Upsilon(2S)$ state as functions of transverse momentum $p_\text{T}$, integrated over the rapidity range of |y| < 2.4 and the 0–90% centrality interval. The global uncertainty combines the uncertainties of $T_\text{AA}$ , pp luminosity, and PbPb $N_\text{MB}$.

Measured $R_\text{AA}$ for the $\Upsilon(3S)$ state as functions of transverse momentum $p_\text{T}$, integrated over the rapidity range of |y| < 2.4 and the 0–90% centrality interval. The global uncertainty combines the uncertainties of $T_\text{AA}$ , pp luminosity, and PbPb $N_\text{MB}$.

The double ratios of $\Upsilon(3S)$ /$\Upsilon(2S)$ as functions of PbPb collision centrality, integrated over the full kinematic range $p_\text{T}$ < 30 GeV/c and |y| < 2.4. The global uncertainty represents the combined systematic and statistical uncertainties from pp data.

The double ratios of $\Upsilon(3S)$ /$\Upsilon(2S)$ in the 0–90% centrality interval, integrated over the full kinematic range $p_\text{T}$ < 30 GeV/c and |y| < 2.4. The global uncertainty represents the combined systematic and statistical uncertainties from pp data.

The double ratios of $\Upsilon(3S)$ /$\Upsilon(2S)$ as functions of transverse momentum $p_\text{T}$, integrated over the rapidity range of |y| < 2.4 and the 0–90% centrality interval.

Yields for $\Upsilon(2S)$ mesons in PbPb collisions in centrality $0--90\%$ and $|y| < 2.4$, corrected for acceptance and efficiency, and normalized by the nuclear thickness function $\langle T_{AA} \rangle$ and the number of minimum bias events $N_{MB}$. The numbers are in units of pb$/GeV/c$.

Yields for $\Upsilon(2S)$ mesons in PbPb collisions in $p_\text{T} < 30GeV/c$ and $|y| < 2.4$, corrected for acceptance and efficiency, and normalized by the nuclear thickness function $\langle T_{AA} \rangle$ and the number of minimum bias events $N_{MB}$. The numbers are in units of pb$/GeV/c$.

Yields for $\Upsilon(3S)$ mesons in PbPb collisions in centrality $0--90\%$ and $|y| < 2.4$, corrected for acceptance and efficiency, and normalized by the nuclear thickness function $\langle T_{AA} \rangle$ and the number of minimum bias events $N_{MB}$. The numbers are in units of pb$/GeV/c$.

Yields for $\Upsilon(3S)$ mesons in PbPb collisions in $p_\text{T} < 30GeV/c$ and $|y| < 2.4$, corrected for acceptance and efficiency, and normalized by the nuclear thickness function $\langle T_{AA} \rangle$ and the number of minimum bias events $N_{MB}$. The numbers are in units of pb$/GeV/c$.

Yields for $\Upsilon(1S)$ mesons in PbPb collisions in $p_\text{T} < 30GeV/c$ and $|y| < 2.4$, corrected for acceptance and efficiency, and normalized by the nuclear thickness function $\langle T_{AA} \rangle$ and the number of minimum bias events $N_{MB}$. The numbers are in units of pb$/GeV/c$. The values and global integrated luminosity uncertainty are quoted from data taken from CMS in 2018 LHC PbPb run.

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.

Fractions of signal events with zero (green), one (blue), and two (red) STA muons matched to TMS muons by the STA to TMS association procedure, as a function of generated $L_{xy}$, in all HAHM signal samples combined.

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.