Upper limit on the WIMP-nucleus scattering cross section from the single-scatter analysis.

Total acceptance evaluated on a simulated dataset of MIMP events. The mean and upper and lower bounds of the 1 sigma uncertainty band are provided.

Observed and expected (background-only fitted) invariant mass spectra of Wgamma events. The fitted function is ${ d N}/{ d m} = p_{0} * (m/\sqrt{s})^{p_{1} + p_{2} * \log(m/\sqrt{s}) + p_{3} * \log^{2}(m/\sqrt{s})}$

Expected and observed 95% CL upper limits on the product of the cross section and branching fraction for narrow scalar Wgamma resonances. Limits are compared to predicted cross sections for the heavy scalar triplet model described in arXiv:1912.08234

Expected and observed 95% CL upper limits on the product of the cross section and branching fraction for broad scalar Wgamma resonances.

Expected and observed 95% CL upper limits on the product of the cross section and branching fraction for narrow vector Wgamma resonances. Limits are compared to predicted cross sections for the heavy vector triplet model described in arXiv:1912.08234

Expected and observed 95% CL upper limits on the product of the cross section and branching fraction for broad vector Wgamma resonances.

Expected and observed model-independent 95% CL upper limits on the product of the cross section, branching fraction and signal acceptance for general Wgamma resonances.

Expected and observed model-independent 95% CL upper limits on the product of the cross section, branching fraction, signal acceptance and W tagging efficiency for general Jgamma resonances.

Figure 3 top left. Expected and observed 95% CL upper limits on the product of the production cross section and branching fraction as a function of the RS graviton mass $m_{G}$ for the full Run 2 data set are shown. Expected $1\sigma$ and $2\sigma$ limit bands are shown in green and yellow, respectively

Figure 3 top right. Expected and observed 95% CL upper limits on the product of the production cross section and branching fraction as a function of the heavy higgs mass $m_{S}$ for the full Run 2 data set are shown. Expected $1\sigma$ and $2\sigma$ limit bands are shown in green and yellow, respectively

Figure 3 mid left. Expected and observed 95% CL upper limits on the product of the production cross section and branching fraction as a function of the RS graviton mass $m_{G}$ for the full Run 2 data set are shown. Expected $1\sigma$ and $2\sigma$ limit bands are shown in green and yellow, respectively

Figure 3 mid right. Expected and observed 95% CL upper limits on the product of the production cross section and branching fraction as a function of the heavy higgs mass $m_{S}$ for the full Run 2 data set are shown. Expected $1\sigma$ and $2\sigma$ limit bands are shown in green and yellow, respectively

Figure 3 bottom left. Expected and observed 95% CL upper limits on the product of the production cross section and branching fraction as a function of the RS graviton mass $m_{G}$ for the full Run 2 data set are shown. Expected $1\sigma$ and $2\sigma$ limit bands are shown in green and yellow, respectively

Figure 3 bottom right. Expected and observed 95% CL upper limits on the product of the production cross section and branching fraction as a function of the heavy higgs mass $m_{S}$ for the full Run 2 data set are shown. Expected $1\sigma$ and $2\sigma$ limit bands are shown in green and yellow, respectively

Figure 4 top left. Expected 95% CL upper limits on the product of the cross section and branching fraction as a function of the $m_{G}$ versus the resonance width for the full Run 2 data set.

Figure 4 top right. Observed 95% CL upper limits on the product of the cross section and branching fraction as a function of the $m_{G}$ versus the resonance width for the full Run 2 data set.

Figure 4 bottom left. Expected 95% CL upper limits on the product of the cross section and branching fraction as a function of the $m_{S}$ versus the resonance width for the full Run 2 data set.

Figure 4 bottom right. Observed 95% CL upper limits on the product of the cross section and branching fraction as a function of the $m_{S}$ versus the resonance width for the full Run 2 data set.

Figure 6. The $m_{\gamma\gamma}$ spectra and background prediction after nuisance paramter marginalization (post-fit) due to SM diphoton production ($\gamma\gamma$) and fake photon production (j$\gamma$, jj) for the EBEB, combining the 2016, 2017, and 2018 data sets. The prediction with a large extra dimensions signal (GRW convention with $M_{S}$ = 9 TeV) is also shown. The pull distributions, normalized to the statistical uncertainty only, are shown underneath the spectra. The last bin contains the overflow of events beyond $m_{\gamma\gamma}$ > 3.5 TeV.

Figure 6. The $m_{\gamma\gamma}$ spectra and background prediction after nuisance paramter marginalization (post-fit) due to SM diphoton production ($\gamma\gamma$) and fake photon production (j$\gamma$, jj) for the EBEE, combining the 2016, 2017, and 2018 data sets. The prediction with a large extra dimensions signal (GRW convention with $M_{S}$ = 9 TeV) is also shown. The pull distributions, normalized to the statistical uncertainty only, are shown underneath the spectra. The last bin contains the overflow of events beyond $m_{\gamma\gamma}$ > 3.5 TeV.

Figure 7. The exclusion limit for the clockwork framework over the k--M5 parameter space. The shaded region denotes where the theory becomes nonperturbative. The region below and to the left of the solid line constitutes the excluded region. Expected 1std and 2std limit bands are shown in green and yellow, respectively.

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.

Breakdown of syst. uncertainties (fully bin-by-bin correlated) for differential cross section for $e^+e^-\rightarrow\pi^+\pi^-\gamma$, with $50^o<\theta_\gamma<130^o$

Bare cross section for $e^+e^-\rightarrow\pi^+\pi^-$

Statistical covariance matrix for bare cross section for $e^+e^-\rightarrow\pi^+\pi^-$

Inverse statistical covariance matrix for bare cross section for $e^+e^-\rightarrow\pi^+\pi$

Breakdown of syst. uncertainties (fully bin-by-bin correlated) for the cross section for $e^+e^-\rightarrow\pi^+\pi^-$

Pion form factor $|F_\pi|^2$

Statistical covariance matrix for pion form factor $|F_\pi|^2$

Inverse statistical covariance matrix $|F_\pi|^2$

Breakdown of syst. uncertainties (fully bin-by-bin correlated) for the pion form factor $|F_\pi|^2$

Vacuum polarisation correction $\delta_{VP}(s)=(\frac{\alpha_{em}(s)}{\alpha_{em}(0)})^2$, with $\sigma^{bare} = \sigma^{dressed}/\delta$ - calculated using the routine from F.Jegerlehner: https://web.archive.org/web/20170828074416/http://www-com.physik.hu-berlin.de/~fjeger/alphaQEDn.uu (2003, archived on August 28, 2017)

Final State Radiation correction $(1.+\eta_{FSR}(s))$, evaluated using the formula in Eur. Phys. J. C 24, 51-69 (2002)

The differential radiator function cross section $H(M_{\pi\pi}^2,s)\cdot \frac{\pi \alpha^2 \beta_\pi^3}{3 M_{\pi\pi}^2 s}$, inclusive in $\theta_\gamma$, in bins of 0.01 GeV$^2$ in $M_{\pi\pi}^2$. The value used for $s$ in the Monte Carlo production is $s = 999.85\; GeV^2$, corresponding to the mean value of DA$\Phi$NE energy for data collected in 2006. Obtained with the PHOKHARA5 MC generator, see Eur. Phys. J. C 27, 563 (2003) and https://looptreeduality.csic.es/phokhara/phokhara5.0.tar.gz

Fiducial differential cross section of the electroweak $W^\pm W^\pm jj$ production as a function of $N_{\mathrm{gap}\,\mathrm{jets}}$. The correlation of uncertainties of the measured cross section across bins is presented in Table 14.

Fiducial differential cross section of the electroweak $W^\pm W^\pm jj$ production as a function of $\xi_{\mathrm{j}3}$. The correlation of uncertainties of the measured cross section across bins is presented in Table 15.

Fiducial differential cross section of the inclusive $W^\pm W^\pm jj$ production as a function of $m_{\ell\ell}$. The correlation of uncertainties of the measured cross section across bins is presented in Table 16.

Fiducial differential cross section of the inclusive $W^\pm W^\pm jj$ production as a function of $m_{\mathrm{T}}$. The correlation of uncertainties of the measured cross section across bins is presented in Table 17.

Fiducial differential cross section of the inclusive $W^\pm W^\pm jj$ production as a function of $m_{\mathrm{jj}}$. The correlation of uncertainties of the measured cross section across bins is presented in Table 18.

Fiducial differential cross section of the inclusive $W^\pm W^\pm jj$ production as a function of $N_{\mathrm{gap}\,\mathrm{jets}}$. The correlation of uncertainties of the measured cross section across bins is presented in Table 19.

Fiducial differential cross section of the inclusive $W^\pm W^\pm jj$ production as a function of $\xi_{\mathrm{j}3}$. The correlation of uncertainties of the measured cross section across bins is presented in Table 20.

Observed correlations between the bins of the LH-unfolded cross section of the electroweak $W^\pm W^\pm jj$ production as a function of $m_{\ell\ell}$. See Table 1.

Observed correlations between the bins of the LH-unfolded cross section of the electroweak $W^\pm W^\pm jj$ production as a function of $m_{\mathrm{T}}$. See Table 2.

Observed correlations between the bins of the LH-unfolded cross section of the electroweak $W^\pm W^\pm jj$ production as a function of $m_{\mathrm{jj}}$. See Table 3.

Observed correlations between the bins of the LH-unfolded cross section of the electroweak $W^\pm W^\pm jj$ production as a function of $N_{\mathrm{gap}\,\mathrm{jets}}$. See Table 4.

Observed correlations between the bins of the LH-unfolded cross section of the electroweak $W^\pm W^\pm jj$ production as a function of $\xi_{\mathrm{j}3}$. See Table 5.

Observed correlations between the bins of the LH-unfolded cross section of the inclusive $W^\pm W^\pm jj$ production as a function of $m_{\ell\ell}$. See Table 6.

Observed correlations between the bins of the LH-unfolded cross section of the inclusive $W^\pm W^\pm jj$ production as a function of $m_{\mathrm{T}}$. See Table 7.

Observed correlations between the bins of the LH-unfolded cross section of the inclusive $W^\pm W^\pm jj$ production as a function of $m_{\mathrm{jj}}$. See Table 8.

Observed correlations between the bins of the LH-unfolded cross section of the inclusive $W^\pm W^\pm jj$ production as a function of $N_{\mathrm{gap}\,\mathrm{jets}}$. See Table 9.

Observed correlations between the bins of the LH-unfolded cross section of the inclusive $W^\pm W^\pm jj$ production as a function of $\xi_{\mathrm{j}3}$. See Table 10.

Evolution of the one-dimensional expected and observed limits at 95% CL on the parameters corresponding to the quartic operators with label M0 as a function of the cut-off scale. The unitarity bounds as a function of the cut-off scale are defined for one non-zero Wilson coefficient.

Evolution of the one-dimensional expected and observed limits at 95% CL on the parameters corresponding to the quartic operators with label M1 as a function of the cut-off scale. The unitarity bounds as a function of the cut-off scale are defined for one non-zero Wilson coefficient.

Evolution of the one-dimensional expected and observed limits at 95% CL on the parameters corresponding to the quartic operators with label M7 as a function of the cut-off scale. The unitarity bounds as a function of the cut-off scale are defined for one non-zero Wilson coefficient. The limits on M7 were obtained without taking into account the SM-EFT interference for the EW W$^\pm$Zjj final state.

Evolution of the one-dimensional expected and observed limits at 95% CL on the parameters corresponding to the quartic operators with label S02 as a function of the cut-off scale. The unitarity bounds as a function of the cut-off scale are defined for one non-zero Wilson coefficient.

Evolution of the one-dimensional expected and observed limits at 95% CL on the parameters corresponding to the quartic operators with label S1 as a function of the cut-off scale. The unitarity bounds as a function of the cut-off scale are defined for one non-zero Wilson coefficient.

Evolution of the one-dimensional expected and observed limits at 95% CL on the parameters corresponding to the quartic operators with label T0 as a function of the cut-off scale. The unitarity bounds as a function of the cut-off scale are defined for one non-zero Wilson coefficient.

Evolution of the one-dimensional expected and observed limits at 95% CL on the parameters corresponding to the quartic operators with label T1 as a function of the cut-off scale. The unitarity bounds as a function of the cut-off scale are defined for one non-zero Wilson coefficient.

Evolution of the one-dimensional expected and observed limits at 95% CL on the parameters corresponding to the quartic operators with label T2 as a function of the cut-off scale. The unitarity bounds as a function of the cut-off scale are defined for one non-zero Wilson coefficient.

Expected and observed exclusion limits at 95% CL for $\sigma_{\mathrm{VBF}}(\mathrm{H}^{\pm\pm}_5) \times \mathcal{B}(\mathrm{H}^{\pm\pm}_5 \rightarrow W^{\pm}W^{\pm})$ as a function of the doubly-charged Higgs mass.

Expected and observed exclusion limits at 95% CL for $\sin\theta_{\mathrm{H}}$ as a function of the doubly-charged Higgs mass in the Georgi-Machacek model.

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.

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.

Data requested from authors.

Fully corrected assorted $\pi^{0}$-hadron conditional pair distributions for $d$+Au collisions centrality 0-88% and $p$+$p$ collisions. The trigger $\pi^0$s are within 5 < $p_{T,trig}$ < 10 GeV/$c$ and are correlated with hadrons with $p_{T,assoc}$ of 1.5-2 GeV/$c$, 2-3GeV/$c$, 3-4 GeV/$c$, and 4-5 GeV/$c$.

Near- and far-side widths as a function of $p_{T, assoc}$ for charged hadron azimuthal correlations from minimumbias $d$+Au collisions.

Near-side width, far-side width as a function of $p_{T,assoc}$ for a charged pion and neutral pion triggers from the $p_{T,trig}$ range of 5-10 GeV/$c$ in minimum bias $d$+Au collisions.

Near-side width, far-side width as a function of $p_{T,assoc}$ for a charged pion and neutral pion triggers from the $p_{T,trig}$ range of 5-10 GeV/$c$ in minimum bias $d$+Au collisions.

Near- and far-side conditional yields as a function of $p_{T, assoc}$ for charged hadron triggers (2.5−4 GeV/$c$) and associated charged hadrons from $d$+Au collisions.

Near- and far-side conditional yields as a function of $p_{T, assoc}$ for charged hadron triggers (4−6 GeV/$c$) and associated charged hadrons from $d$+Au collisions.

Near- and far-side conditional yields as a function of $p_{T, assoc}$ for charged pion triggers (5−10 GeV/$c$) and associated charged hadrons from minimum-bias $d$+Au collisions.

Near- and far-side conditional yields as a function of $p_{T, assoc}$ for neutral pion triggers (5−10 GeV/$c$) and associated charged hadrons from minimum-bias $d$+Au collisions.

Near- and far-side widths and conditional yields as a function of $N_{coll}$ for charged hadron triggers (2.5−4 GeV/$c$) and associated charged hadrons (1–2.5 GeV/$c$) from $d$+Au collisions.

Near- and far-side widths and conditional yields as a function of centrality for neutral pion triggers (5−10 GeV/$c$) and associated charged hadrons (2–3 GeV/$c$) from $d$+Au collisions.

The extracted $\sqrt{<j^2_T>}$ for minimum-bias $d$+Au collisions from all four dihadron correlations. The trigger $p_T$ ranges are 3 - 5 GeV/$c$, 5 - 10 GeV/$c$ and 5 - 10 GeV/$c$ for $h^{\pm}$ - $h^{\pm}$, $\pi^0$ - $h^{\pm}$ and $\pi^{\pm}$ - $h^{\pm}$ assorted-$p_T$ correlations.

The extracted $\sqrt{<j^2_T>}$ for minimum-bias $d$+Au collisions from all four dihadron correlations. The trigger $p_T$ ranges are 3 - 5 GeV/$c$, 5 - 10 GeV/$c$ and 5 - 10 GeV/$c$ for $h^{\pm}$ - $h^{\pm}$, $\pi^0$ - $h^{\pm}$ and $\pi^{\pm}$ - $h^{\pm}$ assorted-$p_T$ correlations.

The extracted $\sqrt{<j^2_T>}$ for minimum-bias $d$+Au collisions from all four dihadron correlations. The trigger $p_T$ ranges are 3 - 5 GeV/$c$, 5 - 10 GeV/$c$ and 5 - 10 GeV/$c$ for $h^{\pm}$ - $h^{\pm}$, $\pi^0$ - $h^{\pm}$ and $\pi^{\pm}$ - $h^{\pm}$ assorted-$p_T$ correlations.

The extracted $\sqrt{<j^2_T>}$ for minimum-bias $d$+Au collisions from all four dihadron correlations. The trigger $p_T$ ranges are 3 - 5 GeV/$c$, 5 - 10 GeV/$c$ and 5 - 10 GeV/$c$ for $h^{\pm}$ - $h^{\pm}$, $\pi^0$ - $h^{\pm}$ and $\pi^{\pm}$ - $h^{\pm}$ assorted-$p_T$ correlations.

$<sin^2(\phi_{jj})>$ for minimum bias $d$+Au collisions as function of associated particle $p_T$ for $\pi^{\pm}$ - $h^{\pm}$ and $\pi^0$ - $h^{\pm}$ correlations where the trigger particles have a $p_T$ between 5 - 10 GeV/$c$.

$<sin^2(\phi_{jj})>$ for minimum bias $d$+Au collisions as function of associated particle $p_T$ for $\pi^{\pm}$ - $h^{\pm}$ and $\pi^0$ - $h^{\pm}$ correlations where the trigger particles have a $p_T$ between 5 - 10 GeV/$c$.

$<sin^2(\phi_{jj})>$ for minimum bias $d$+Au collisions as function of trigger particle $p_T$ for $\pi^{\pm}$ - $h^{\pm}$ and $\pi^0$ - $h^{\pm}$ correlations.

$<sin^2(\phi_{jj})>$ for minimum bias $d$+Au collisions as function of trigger particle $p_T$ for $\pi^{\pm}$ - $h^{\pm}$ and $\pi^0$ - $h^{\pm}$ correlations.

Near-side and far-side $p_{out}$ distributions for minimum bias $d$+Au collisions obtained from $\pi^{\pm}$ - $h^{\pm}$ correlation. The trigger is 5 < $p_{T,trig}$ < 10 GeV/$c$, the associated particle is 0.5 < $p_{T,assoc}$ < 5.0 GeV/$c$.

Conditional yield as a function of $x_E$ for near-side and far-side for $\pi^{\pm}$ - $h^{\pm}$ and $\pi^0$ - $h^{\pm}$ from minimum-bias $d$+Au collisions.

Conditional yield as a function of $x_E$ for near-side and far-side for $\pi^{\pm}$ - $h^{\pm}$ and $\pi^0$ - $h^{\pm}$ from minimum-bias $d$+Au collisions.

Conditional yield as a function of $x_E$ for near-side and far-side correlations for $\pi^{\pm}$ - $h^{\pm}$ correlations from minimum-bias $d$+Au collisions. The trigger pions are 5 < $p_{T,trig}$ < 6 GeV/$c$.

Conditional yield as a function of $x_E$ for near-side and far-side correlation for $\pi^{\pm}$ - $h^{\pm}$ correlation for several different trigger $p_T$s for minimum-bias $d$+Au collisions.

Far-side conditional yield as a function of $p_{T,trig}$ for different ranges of $x_E$ for $\pi^{\pm}$ - $h^{\pm}$ correlation for minimum-bias $d$+Au collisions.

Far-side conditional yield as a function of $p_{T,trig}$ for different ranges of $x_E$ for $\pi^{\pm}$ - $h^{\pm}$ correlation for minimum-bias $d$+Au collisions.

Far-side conditional yield as a function of $p_{T,trig}$ for different ranges of $x_E$ for $\pi^{\pm}$ - $h^{\pm}$ correlation for minimum-bias $d$+Au collisions.

Far-side conditional yield as a function of $p_{T,trig}$ for different ranges of $x_E$ for $\pi^{\pm}$ - $h^{\pm}$ correlation for minimum-bias $d$+Au collisions.

The comparison of the $\sqrt{<j^2_T>}$ values between $d$+Au and $p$+$p$ for the $\pi^{\pm}$ - $h^{\pm}$ correlations and $\pi^0$ - $h^{\pm}$ correlations. The trigger pion range is 5 - 10 GeV/$c$.

The comparison of the $\sqrt{<j^2_T>}$ values between $d$+Au and $p$+$p$ for the $\pi^{\pm}$ - $h^{\pm}$ correlations and $\pi^0$ - $h^{\pm}$ correlations. The trigger pion range is 5 - 10 GeV/$c$.

Quadrature difference between minimum-bias $d$+Au and $p$+$p$ $<sin^2(\phi_{jj})>$ values.

Quadrature difference between minimum-bias $d$+Au and $p$+$p$ $<sin^2(\phi_{jj})>$ values.

The comparison of the $p_{out}$ distribution at the near-side and far-side between central $d$+Au collisions and $p$+$p$ collisions. Results are obtained for $\pi^{\pm}$ - $h^{\pm}$ correlations with the associated hadron range 0.5 < $p_{T,assoc}$ < 5 GeV/$c$ and trigger pion range of 5 < $p_{T,trig}$ < 10 GeV/$c$.

The comparison of the $x_E$ distribution from $\pi^{\pm}$ - $h^{\pm}$ correlation at the near-side and far-side between minimum bias $d$+Au collisions and $p$+$p$ collisions. The trigger $\pi^{\pm}$ are from 5 - 10 GeV/$c$.

Far-side conditional yield as a function of $p_{T,trig}$ for different ranges of $x_E$ from $p$+$p$ collisions, triggers are $\pi^{\pm}$ from 5 - 10 GeV/$c$.

Far-side conditional yield as a function of $p_{T,trig}$ for different ranges of $x_E$ from $p$+$p$ collisions, triggers are $\pi^{\pm}$ from 5 - 10 GeV/$c$.

Far-side conditional yield as a function of $p_{T,trig}$ for different ranges of $x_E$ from $p$+$p$ collisions, triggers are $\pi^{\pm}$ from 5 - 10 GeV/$c$.

The fitted fractional change in $dN/d_{x_E}$ per unit $p_{T,trig}$ of the far-side conditional yield for different ranges of $x_E$.

Centrality dependent near and far $CY(p_T)$ for $\pi^{\pm}$ - $h^{\pm}$ correlations and $\pi^0$ - $h^{\pm}$ correlations.

Centrality dependent near and far $CY(p_T)$ for $\pi^{\pm}$ - $h^{\pm}$ correlations and $\pi^0$ - $h^{\pm}$ correlations.

Centrality dependence to the ratio of near and far $CY(p_T)$ for $d$+Au to $p$+$p$.

Centrality dependence to the ratio of near and far $CY(p_T)$ for $d$+Au to $p$+$p$.

Near- and far-side widths as a function of $p_{T, trig}$ for charged pion triggers and associated charged hadrons (2–4.5 Gev/$c$) from minimum-bias $d$+Au collisions.

Near- and far-side widths as a function of $p_{T, trig}$ for neutral pion triggers and associated charged hadrons (2–4.5 Gev/$c$) from minimum-bias $d$+Au collisions.

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.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Unfolded E2C distributions in data compared to MC predictions.

Unfolded E2C distributions in data compared to MC predictions.

Unfolded E2C distributions in data compared to MC predictions.

Unfolded E2C distributions in data compared to MC predictions.

Unfolded E2C distributions in data compared to MC predictions.

Unfolded E3C distributions in data compared to MC predictions.

Unfolded E3C distributions in data compared to MC predictions.

Unfolded E3C distributions in data compared to MC predictions.

Unfolded E3C distributions in data compared to MC predictions.

Unfolded E3C distributions in data compared to MC predictions.

Unfolded E3C distributions in data compared to MC predictions.

Unfolded E3C distributions in data compared to MC predictions.

Unfolded E3C distributions in data compared to MC predictions.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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