The ratio of the production cross sections of inclusive $\Lambda_{c}^{+}$ to prompt $D^{0}$ versus $p_{T}$ from pp collisions. The $20\%$ normalization uncertainty in pp collisions is not included in the statistical and systematic uncertainties for each data point.

The ratio of the production cross sections of inclusive $\Lambda_{c}^{+}$ to prompt $D^{0}$ versus $p_{T}$ from $0-100\%$ centrality PbPb collisions. The $31\%$ normalization uncertainty in PbPb collisions, is not included in the statistical and systematic uncertainties for each data point.

Differential fiducial cross section (without the acceptance correction) for the DY process measured in the muon channel, as a function of $p_{\textrm{T}}$ for $15<m_{\mu\mu}<60$ GeV. The quoted error is the quadratic sum of the statistical and systematic uncertainties. The global normalisation uncertainty of 3.5% is listed separately.

Differential fiducial cross section (without the acceptance correction) for the DY process measured in the muon channel, as a function of $p_{\textrm{T}}$ for $60<m_{\mu\mu}<120$ GeV. The quoted error is the quadratic sum of the statistical and systematic uncertainties. The global normalisation uncertainty of 3.5% is listed separately.

Differential fiducial cross section (without the acceptance correction) for the DY process measured in the muon channel, as a function of $\phi^*$ for $15<m_{\mu\mu}<60$ GeV. The quoted error is the quadratic sum of the statistical and systematic uncertainties. The global normalisation uncertainty of 3.5% is listed separately.

Differential fiducial cross section (without the acceptance correction) for the DY process measured in the muon channel, as a function of $\phi^*$ for $60<m_{\mu\mu}<120$ GeV. The quoted error is the quadratic sum of the statistical and systematic uncertainties. The global normalisation uncertainty of 3.5% is listed separately.

Integrated fiducial cross section for the DY process measured in the muon channel. The quoted error is the quadratic sum of the statistical and systematic uncertainties. The global normalisation uncertainty of 3.5% is listed separately.

Differential cross section for the DY process measured in the muon channel, as a function of dimuon invariant mass. The quoted error is the quadratic sum of the statistical and systematic uncertainties. The global normalisation uncertainty of 3.5% is listed separately.

Differential cross section for the DY process measured in the muon channel, as a function of rapidity in the centre-of-mass frame for $15<m_{\mu\mu}<60$ GeV. The quoted error is the quadratic sum of the statistical and systematic uncertainties. The global normalisation uncertainty of 3.5% is listed separately.

Differential cross section for the DY process measured in the muon channel, as a function of rapidity in the centre-of-mass frame for $60<m_{\mu\mu}<120$ GeV. The quoted error is the quadratic sum of the statistical and systematic uncertainties. The global normalisation uncertainty of 3.5% is listed separately.

Differential cross section for the DY process measured in the muon channel, as a function of $p_{\textrm{T}}$ for $15<m_{\mu\mu}<60$ GeV. The quoted error is the quadratic sum of the statistical and systematic uncertainties. The global normalisation uncertainty of 3.5% is listed separately.

Differential cross section for the DY process measured in the muon channel, as a function of $p_{\textrm{T}}$ for $60<m_{\mu\mu}<120$ GeV. The quoted error is the quadratic sum of the statistical and systematic uncertainties. The global normalisation uncertainty of 3.5% is listed separately.

Differential cross section for the DY process measured in the muon channel, as a function of $\phi^*$ for $15<m_{\mu\mu}<60$ GeV. The quoted error is the quadratic sum of the statistical and systematic uncertainties. The global normalisation uncertainty of 3.5% is listed separately.

Differential cross section for the DY process measured in the muon channel, as a function of $\phi^*$ for $60<m_{\mu\mu}<120$ GeV. The quoted error is the quadratic sum of the statistical and systematic uncertainties. The global normalisation uncertainty of 3.5% is listed separately.

Integrated cross section for the DY process measured in the muon channel. The quoted error is the quadratic sum of the statistical and systematic uncertainties. The global normalisation uncertainty of 3.5% is listed separately.

Forward-backward ratios for $15<m_{\mu\mu}<60$ GeV. Quoted uncertainties are the quadratic sum of the statistical and systematic uncertainties.

Forward-backward ratios for $60<m_{\mu\mu}<120$ GeV. Quoted uncertainties are the quadratic sum of the statistical and systematic uncertainties.

Correlation matrix for the systematic uncertainties, excluding integrated luminosity, as a function of dimuon invariant mass.

Correlation matrix for the systematic uncertainties, excluding integrated luminosity, as a function of rapidity in the centre-of-mass frame for $15<m_{\mu\mu}<60$ GeV.

Correlation matrix for the systematic uncertainties, excluding integrated luminosity, as a function of rapidity in the centre-of-mass frame for $60<m_{\mu\mu}<120$ GeV.

Correlation matrix for the systematic uncertainties, excluding integrated luminosity, as a function of $p_{\textrm{T}}$ for $15<m_{\mu\mu}<60$ GeV.

Correlation matrix for the systematic uncertainties, excluding integrated luminosity, as a function of $p_{\textrm{T}}$ for $60<m_{\mu\mu}<120$ GeV.

Correlation matrix for the systematic uncertainties, excluding integrated luminosity, as a function of $\phi^*$ for $15<m_{\mu\mu}<60$ GeV.

Correlation matrix for the systematic uncertainties, excluding integrated luminosity, as a function of $\phi^*$ for $60<m_{\mu\mu}<120$ GeV.

Correlation matrix for the systematic uncertainties, excluding integrated luminosity, as a function of rapidity in the centre-of-mass frame, putting together low and high masses. Each bin is labeled lm_i or hm_i, where lm stands for $15<m_{\mu\mu}<60$ GeV, hm stands for $60<m_{\mu\mu}<120$ GeV, and i is the corresponding bin number in rapidity in the centre-of-mass frame. The global normalisation uncertainty of 3.5% is not included. Data from Figure [3, 4, 4].

Correlation matrix for the systematic uncertainties, excluding integrated luminosity, as a function of $p_{\textrm{T}}$, putting together low and high masses. Each bin is labeled lm_i or hm_i, where lm stands for $15<m_{\mu\mu}<60$ GeV, hm stands for $60<m_{\mu\mu}<120$ GeV, and i is the corresponding bin number in $p_{\textrm{T}}$. The global normalisation uncertainty of 3.5% is not included. Data from Figure [3, 4, 4].

Correlation matrix for the systematic uncertainties, excluding integrated luminosity, as a function of $\phi^*$, putting together low and high masses. Each bin is labeled lm_i or hm_i, where lm stands for $15<m_{\mu\mu}<60$ GeV, hm stands for $60<m_{\mu\mu}<120$ GeV, and i is the corresponding bin number in $\phi^*$. The global normalisation uncertainty of 3.5% is not included. Data from Figure [3, 4, 4].

Level-1 muon trigger efficiency in cosmic-ray muon data (blue) and signal simulation (red) as a function of $d_0$, for the Level-1 trigger $p_T$ threshold used in the 2018 analysis triggers. The denominator in the efficiency calculation is the number of STA muons with $|\eta| < 1.2$ and $p_T > 28$ GeV.

Fractions of signal events with zero (green), one (blue), and two (red) STA muons matched to TMS muons by the STA-to-TMS muon association procedure, as a function of true $L_{xy}$, in all simulated $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal samples combined. The fractions are computed relative to the number of signal events passing the trigger and containing two STA muons with more than 12 muon detector hits and $p_T > 10$ GeV matched to generated muons from $X \rightarrow \mu \mu$ decays.

Fractions of signal events with zero (green), one (blue), and two (red) STA muons matched to TMS muons by the STA-to-TMS muon association procedure, as a function of true $L_{xy}$, in all simulated $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal samples combined. The fractions are computed relative to the number of signal events passing the trigger and containing two STA muons with more than 12 muon detector hits and $p_T > 10$ GeV matched to generated muons from $X \rightarrow \mu \mu$ decays.

Comparison of the number of events observed in 2016 data in the STA-STA dimuon category with the expected number of background events, in representative $m_{\mu \mu}$ intervals. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 20 and 50 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility. The legends also include the total number of observed events as well as the number of expected background events obtained inclusively, by applying the background evaluation method to the events in all $m_{\mu \mu}$ intervals combined.

Comparison of the number of events observed in 2016 data in the STA-STA dimuon category with the expected number of background events, in representative $m_{\mu \mu}$ intervals. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 20 and 50 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility. The legends also include the total number of observed events as well as the number of expected background events obtained inclusively, by applying the background evaluation method to the events in all $m_{\mu \mu}$ intervals combined.

Comparison of the number of events observed in 2018 data in the STA-STA dimuon category with the expected number of background events, in representative $m_{\mu \mu}$ intervals. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 20 and 50 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility. The legends also include the total number of observed events as well as the number of expected background events obtained inclusively, by applying the background evaluation method to the events in all $m_{\mu \mu}$ intervals combined.

Comparison of the number of events observed in 2018 data in the STA-STA dimuon category with the expected number of background events, in representative $m_{\mu \mu}$ intervals. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 20 and 50 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility. The legends also include the total number of observed events as well as the number of expected background events obtained inclusively, by applying the background evaluation method to the events in all $m_{\mu \mu}$ intervals combined.

Comparison of the number of events observed in 2016 data in the STA-TMS dimuon category with the expected number of background events, in representative $m_{\mu \mu}$ intervals. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 30 and 60 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility. The legends also include the total number of observed events as well as the number of expected background events obtained inclusively, by applying the background evaluation method to the events in all $m_{\mu \mu}$ intervals combined.

Comparison of the number of events observed in 2016 data in the STA-TMS dimuon category with the expected number of background events, in representative $m_{\mu \mu}$ intervals. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 30 and 60 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility. The legends also include the total number of observed events as well as the number of expected background events obtained inclusively, by applying the background evaluation method to the events in all $m_{\mu \mu}$ intervals combined.

Comparison of the number of events observed in 2018 data in the STA-TMS dimuon category with the expected number of background events, in representative $m_{\mu \mu}$ intervals. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 30 and 60 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility. The legends also include the total number of observed events as well as the number of expected background events obtained inclusively, by applying the background evaluation method to the events in all $m_{\mu \mu}$ intervals combined.

Comparison of the number of events observed in 2018 data in the STA-TMS dimuon category with the expected number of background events, in representative $m_{\mu \mu}$ intervals. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 30 and 60 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility. The legends also include the total number of observed events as well as the number of expected background events obtained inclusively, by applying the background evaluation method to the events in all $m_{\mu \mu}$ intervals combined.

Comparison of the number of events observed in 2016 data in the TMS-TMS dimuon category with the expected number of background events, in representative $m_{\mu \mu}$ intervals in the $6 < min(d_0 / \sigma_{d_0}) \leq 10$ bin. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 20 and 50 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility. The legend also includes the total number of observed events as well as the number of expected background events obtained inclusively, by applying the background evaluation method to the events in all $m_{Z_D}$ and min($d_0 / \sigma_{d_0}$) intervals combined.

Comparison of the number of events observed in 2016 data in the TMS-TMS dimuon category with the expected number of background events, in representative $m_{\mu \mu}$ intervals in the $6 < min(d_0 / \sigma_{d_0}) \leq 10$ bin. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 20 and 50 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility. The legend also includes the total number of observed events as well as the number of expected background events obtained inclusively, by applying the background evaluation method to the events in all $m_{Z_D}$ and min($d_0 / \sigma_{d_0}$) intervals combined.

Comparison of the number of events observed in 2016 data in the TMS-TMS dimuon category with the expected number of background events, in representative $m_{\mu \mu}$ intervals in the $10 < min(d_0 / \sigma_{d_0}) \leq 20$ bin. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 20 and 50 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility. The legend also includes the total number of observed events as well as the number of expected background events obtained inclusively, by applying the background evaluation method to the events in all $m_{Z_D}$ and min($d_0 / \sigma_{d_0}$) intervals combined.

Comparison of the number of events observed in 2016 data in the TMS-TMS dimuon category with the expected number of background events, in representative $m_{\mu \mu}$ intervals in the $10 < min(d_0 / \sigma_{d_0}) \leq 20$ bin. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 20 and 50 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility. The legend also includes the total number of observed events as well as the number of expected background events obtained inclusively, by applying the background evaluation method to the events in all $m_{Z_D}$ and min($d_0 / \sigma_{d_0}$) intervals combined.

Comparison of the number of events observed in 2016 data in the TMS-TMS dimuon category with the expected number of background events, in representative $m_{\mu \mu}$ intervals in the $min(d_0 / \sigma_{d_0}) > 20$ bin. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 20 and 50 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility. The legend also includes the total number of observed events as well as the number of expected background events obtained inclusively, by applying the background evaluation method to the events in all $m_{Z_D}$ and min($d_0 / \sigma_{d_0}$) intervals combined.

Comparison of the number of events observed in 2016 data in the TMS-TMS dimuon category with the expected number of background events, in representative $m_{\mu \mu}$ intervals in the $min(d_0 / \sigma_{d_0}) > 20$ bin. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 20 and 50 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility. The legend also includes the total number of observed events as well as the number of expected background events obtained inclusively, by applying the background evaluation method to the events in all $m_{Z_D}$ and min($d_0 / \sigma_{d_0}$) intervals combined.

Comparison of the number of events observed in 2018 data in the TMS-TMS dimuon category with the expected number of background events, in representative $m_{\mu \mu}$ intervals in the $6 < min(d_0 / \sigma_{d_0}) \leq 10$ bin. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 20 and 50 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility. The legend also includes the total number of observed events as well as the number of expected background events obtained inclusively, by applying the background evaluation method to the events in all $m_{Z_D}$ and min($d_0 / \sigma_{d_0}$) intervals combined.

Comparison of the number of events observed in 2018 data in the TMS-TMS dimuon category with the expected number of background events, in representative $m_{\mu \mu}$ intervals in the $6 < min(d_0 / \sigma_{d_0}) \leq 10$ bin. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 20 and 50 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility. The legend also includes the total number of observed events as well as the number of expected background events obtained inclusively, by applying the background evaluation method to the events in all $m_{Z_D}$ and min($d_0 / \sigma_{d_0}$) intervals combined.

Comparison of the number of events observed in 2018 data in the TMS-TMS dimuon category with the expected number of background events, in representative $m_{\mu \mu}$ intervals in the $10 < min(d_0 / \sigma_{d_0}) \leq 20$ bin. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 20 and 50 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility. The legend also includes the total number of observed events as well as the number of expected background events obtained inclusively, by applying the background evaluation method to the events in all $m_{Z_D}$ and min($d_0 / \sigma_{d_0}$) intervals combined.

Comparison of the number of events observed in 2018 data in the TMS-TMS dimuon category with the expected number of background events, in representative $m_{\mu \mu}$ intervals in the $10 < min(d_0 / \sigma_{d_0}) \leq 20$ bin. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 20 and 50 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility. The legend also includes the total number of observed events as well as the number of expected background events obtained inclusively, by applying the background evaluation method to the events in all $m_{Z_D}$ and min($d_0 / \sigma_{d_0}$) intervals combined.

Comparison of the number of events observed in 2018 data in the TMS-TMS dimuon category with the expected number of background events, in representative $m_{\mu \mu}$ intervals in the $min(d_0 / \sigma_{d_0}) > 20$ bin. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 20 and 50 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility. The legend also includes the total number of observed events as well as the number of expected background events obtained inclusively, by applying the background evaluation method to the events in all $m_{Z_D}$ and min($d_0 / \sigma_{d_0}$) intervals combined.

Comparison of the number of events observed in 2018 data in the TMS-TMS dimuon category with the expected number of background events, in representative $m_{\mu \mu}$ intervals in the $min(d_0 / \sigma_{d_0}) > 20$ bin. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 20 and 50 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility. The legend also includes the total number of observed events as well as the number of expected background events obtained inclusively, by applying the background evaluation method to the events in all $m_{Z_D}$ and min($d_0 / \sigma_{d_0}$) intervals combined.

Comparison of the number of events observed in 2016 data in the TMS-TMS dimuon category with the expected number of background events, as a function of the smaller of the two $d_0 / \sigma_{d_0}$ values in the TMS-TMS dimuon. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 20 and 50 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility.

Comparison of the number of events observed in 2016 data in the TMS-TMS dimuon category with the expected number of background events, as a function of the smaller of the two $d_0 / \sigma_{d_0}$ values in the TMS-TMS dimuon. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 20 and 50 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility.

Comparison of the number of events observed in 2018 data in the TMS-TMS dimuon category with the expected number of background events, as a function of the smaller of the two $d_0 / \sigma_{d_0}$ values in the TMS-TMS dimuon. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 20 and 50 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility.

Comparison of the number of events observed in 2018 data in the TMS-TMS dimuon category with the expected number of background events, as a function of the smaller of the two $d_0 / \sigma_{d_0}$ values in the TMS-TMS dimuon. The black points with crosses show the number of observed events; the green and yellow components of the stacked histograms represent the estimated numbers of DY and QCD events, respectively. The last bin includes events in the overflow. The uncertainties in the total expected background (shaded area) are statistical only. Signal contributions expected from simulated $H \rightarrow Z_D Z_D$ with $m_{Z_D}$ of 20 and 50 GeV are shown in red and blue, respectively. Their yields are set to the corresponding combined median expected exclusion limits at 95% CL, scaled up as indicated in the legend to improve visibility.

The 95% CL upper limits on $\sigma(\Phi \rightarrow XX)B(X \rightarrow \mu \mu)$ as a function of $c\tau(X)$ in the heavy-scalar model, for $m(\Phi) = 125\ GeV$ and $m(X) = 20\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; 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 $\sigma(\Phi \rightarrow XX)B(X \rightarrow \mu \mu)$ as a function of $c\tau(X)$ in the heavy-scalar model, for $m(\Phi) = 125\ GeV$ and $m(X) = 20\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; 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 $\sigma(\Phi \rightarrow XX)B(X \rightarrow \mu \mu)$ as a function of $c\tau(X)$ in the heavy-scalar model, for $m(\Phi) = 125\ GeV$ and $m(X) = 50\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; 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 $\sigma(\Phi \rightarrow XX)B(X \rightarrow \mu \mu)$ as a function of $c\tau(X)$ in the heavy-scalar model, for $m(\Phi) = 125\ GeV$ and $m(X) = 50\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; 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 $\sigma(\Phi \rightarrow XX)B(X \rightarrow \mu \mu)$ as a function of $c\tau(X)$ in the heavy-scalar model, for $m(\Phi) = 200\ GeV$ and $m(X) = 20\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; 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 $\sigma(\Phi \rightarrow XX)B(X \rightarrow \mu \mu)$ as a function of $c\tau(X)$ in the heavy-scalar model, for $m(\Phi) = 200\ GeV$ and $m(X) = 20\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; 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 $\sigma(\Phi \rightarrow XX)B(X \rightarrow \mu \mu)$ as a function of $c\tau(X)$ in the heavy-scalar model, for $m(\Phi) = 200\ GeV$ and $m(X) = 50\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; 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 $\sigma(\Phi \rightarrow XX)B(X \rightarrow \mu \mu)$ as a function of $c\tau(X)$ in the heavy-scalar model, for $m(\Phi) = 200\ GeV$ and $m(X) = 50\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; 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 $\sigma(\Phi \rightarrow XX)B(X \rightarrow \mu \mu)$ as a function of $c\tau(X)$ in the heavy-scalar model, for $m(\Phi) = 400\ GeV$ and $m(X) = 20\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; 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 $\sigma(\Phi \rightarrow XX)B(X \rightarrow \mu \mu)$ as a function of $c\tau(X)$ in the heavy-scalar model, for $m(\Phi) = 400\ GeV$ and $m(X) = 20\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; 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 $\sigma(\Phi \rightarrow XX)B(X \rightarrow \mu \mu)$ as a function of $c\tau(X)$ in the heavy-scalar model, for $m(\Phi) = 400\ GeV$ and $m(X) = 50\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; 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 $\sigma(\Phi \rightarrow XX)B(X \rightarrow \mu \mu)$ as a function of $c\tau(X)$ in the heavy-scalar model, for $m(\Phi) = 400\ GeV$ and $m(X) = 50\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; 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 $\sigma(\Phi \rightarrow XX)B(X \rightarrow \mu \mu)$ as a function of $c\tau(X)$ in the heavy-scalar model, for $m(\Phi) = 400\ GeV$ and $m(X) = 150\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; 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 $\sigma(\Phi \rightarrow XX)B(X \rightarrow \mu \mu)$ as a function of $c\tau(X)$ in the heavy-scalar model, for $m(\Phi) = 400\ GeV$ and $m(X) = 150\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; 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 $\sigma(\Phi \rightarrow XX)B(X \rightarrow \mu \mu)$ as a function of $c\tau(X)$ in the heavy-scalar model, for $m(\Phi) = 1000\ GeV$ and $m(X) = 20\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; 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 $\sigma(\Phi \rightarrow XX)B(X \rightarrow \mu \mu)$ as a function of $c\tau(X)$ in the heavy-scalar model, for $m(\Phi) = 1000\ GeV$ and $m(X) = 20\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; 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 $\sigma(\Phi \rightarrow XX)B(X \rightarrow \mu \mu)$ as a function of $c\tau(X)$ in the heavy-scalar model, for $m(\Phi) = 1000\ GeV$ and $m(X) = 50\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; 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 $\sigma(\Phi \rightarrow XX)B(X \rightarrow \mu \mu)$ as a function of $c\tau(X)$ in the heavy-scalar model, for $m(\Phi) = 1000\ GeV$ and $m(X) = 50\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; 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 $\sigma(\Phi \rightarrow XX)B(X \rightarrow \mu \mu)$ as a function of $c\tau(X)$ in the heavy-scalar model, for $m(\Phi) = 1000\ GeV$ and $m(X) = 150\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; 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 $\sigma(\Phi \rightarrow XX)B(X \rightarrow \mu \mu)$ as a function of $c\tau(X)$ in the heavy-scalar model, for $m(\Phi) = 1000\ GeV$ and $m(X) = 150\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; 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 $\sigma(\Phi \rightarrow XX)B(X \rightarrow \mu \mu)$ as a function of $c\tau(X)$ in the heavy-scalar model, for $m(\Phi) = 1000\ GeV$ and $m(X) = 350\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; 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 $\sigma(\Phi \rightarrow XX)B(X \rightarrow \mu \mu)$ as a function of $c\tau(X)$ in the heavy-scalar model, for $m(\Phi) = 1000\ GeV$ and $m(X) = 350\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; 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 $\sigma(H \rightarrow Z_DZ_D)B(Z_D \rightarrow \mu \mu)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m_{Z_D} = 10\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; 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 horizontal lines in gray correspond to the theoretical predictions for values of $B(H \rightarrow Z_DZ_D)$ indicated next to the lines.

The 95% CL upper limits on $\sigma(H \rightarrow Z_DZ_D)B(Z_D \rightarrow \mu \mu)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m_{Z_D} = 10\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; 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 horizontal lines in gray correspond to the theoretical predictions for values of $B(H \rightarrow Z_DZ_D)$ indicated next to the lines.

The 95% CL upper limits on $\sigma(H \rightarrow Z_DZ_D)B(Z_D \rightarrow \mu \mu)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m_{Z_D} = 20\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; 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 horizontal lines in gray correspond to the theoretical predictions for values of $B(H \rightarrow Z_DZ_D)$ indicated next to the lines.

The 95% CL upper limits on $\sigma(H \rightarrow Z_DZ_D)B(Z_D \rightarrow \mu \mu)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m_{Z_D} = 20\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; 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 horizontal lines in gray correspond to the theoretical predictions for values of $B(H \rightarrow Z_DZ_D)$ indicated next to the lines.

The 95% CL upper limits on $\sigma(H \rightarrow Z_DZ_D)B(Z_D \rightarrow \mu \mu)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m_{Z_D} = 30\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; 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 horizontal lines in gray correspond to the theoretical predictions for values of $B(H \rightarrow Z_DZ_D)$ indicated next to the lines.

The 95% CL upper limits on $\sigma(H \rightarrow Z_DZ_D)B(Z_D \rightarrow \mu \mu)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m_{Z_D} = 30\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; 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 horizontal lines in gray correspond to the theoretical predictions for values of $B(H \rightarrow Z_DZ_D)$ indicated next to the lines.

The 95% CL upper limits on $\sigma(H \rightarrow Z_DZ_D)B(Z_D \rightarrow \mu \mu)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m_{Z_D} = 40\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; 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 horizontal lines in gray correspond to the theoretical predictions for values of $B(H \rightarrow Z_DZ_D)$ indicated next to the lines.

The 95% CL upper limits on $\sigma(H \rightarrow Z_DZ_D)B(Z_D \rightarrow \mu \mu)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m_{Z_D} = 40\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; 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 horizontal lines in gray correspond to the theoretical predictions for values of $B(H \rightarrow Z_DZ_D)$ indicated next to the lines.

The 95% CL upper limits on $\sigma(H \rightarrow Z_DZ_D)B(Z_D \rightarrow \mu \mu)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m_{Z_D} = 50\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; 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 horizontal lines in gray correspond to the theoretical predictions for values of $B(H \rightarrow Z_DZ_D)$ indicated next to the lines.

The 95% CL upper limits on $\sigma(H \rightarrow Z_DZ_D)B(Z_D \rightarrow \mu \mu)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m_{Z_D} = 50\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; 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 horizontal lines in gray correspond to the theoretical predictions for values of $B(H \rightarrow Z_DZ_D)$ indicated next to the lines.

The 95% CL upper limits on $\sigma(H \rightarrow Z_DZ_D)B(Z_D \rightarrow \mu \mu)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m_{Z_D} = 60\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; 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 horizontal lines in gray correspond to the theoretical predictions for values of $B(H \rightarrow Z_DZ_D)$ indicated next to the lines.

The 95% CL upper limits on $\sigma(H \rightarrow Z_DZ_D)B(Z_D \rightarrow \mu \mu)$ as a function of $c\tau(Z_D)$ in the HAHM model, for $m_{Z_D} = 60\ GeV$. The median expected limits obtained from the STA-STA, STA-TMS, and TMS-TMS dimuon categories are shown as dashed green, blue, and red curves, respectively; the combined median expected limits are shown as dashed black curves; 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 horizontal lines in gray correspond to the theoretical predictions for values of $B(H \rightarrow Z_DZ_D)$ indicated next to the lines.

Observed 95% CL exclusion contours in the HAHM model, in the ($m(Z_D)$, $c\tau(Z_D)$) plane. The contours correspond to several representative values of $B(H \rightarrow Z_DZ_D$) ranging from 0.005 to 1%.

Observed 95% CL exclusion contours in the HAHM model, in the ($m(Z_D)$, $c\tau(Z_D)$) plane. The contours correspond to several representative values of $B(H \rightarrow Z_DZ_D$) ranging from 0.005 to 1%.

Observed 95% CL exclusion contours in the HAHM model, in the ($m(Z_D)$, $\epsilon$) plane. The contours correspond to several representative values of $B(H \rightarrow Z_DZ_D$) ranging from 0.005 to 1%.

Observed 95% CL exclusion contours in the HAHM model, in the ($m(Z_D)$, $\epsilon$) plane. The contours correspond to several representative values of $B(H \rightarrow Z_DZ_D$) ranging from 0.005 to 1%.

Background estimation and observed number of events in the STA-STA dimuon category in 2016 and 2018 data. For each probed LLP mass, the chosen mass interval is shown. The mass interval is followed by the estimated and observed counts for the given year. The quoted uncertainties are statistical only.

Background estimations and observed numbers of events in the STA-STA dimuon category in 2016 and 2018 data. For each probed LLP mass, the chosen mass interval is shown, followed by the predicted background yield $N^\text{est}_\text{bkg}$ and the observed number of events $N^\text{obs}$ for the given year. The quoted uncertainties are statistical only.

Background estimation and observed number of events in the TMS-TMS dimuon category in 2016 data. The mass interval is followed by the estimated and observed counts within each $min(d_0 / \sigma_{d_0})$ bin in this mass interval. The quoted uncertainties are statistical only.

Background estimations and observed numbers of events in the TMS-TMS dimuon category in 2016 data. For each mass interval, the table shows the predicted background yield $N^\text{est}_\text{bkg}$ and the observed number of events $N^\text{obs}$ in each of the three $\text{min}(d_0 / \sigma_{d_0})$ bins. The quoted uncertainties are statistical only

Background estimation and observed number of events in the TMS-TMS dimuon category in 2018 data. The mass interval is followed by the estimated and observed counts within each $min(d_0 / \sigma_{d_0})$ bin in this mass interval. The quoted uncertainties are statistical only.

Background estimations and observed numbers of events in the TMS-TMS dimuon category in 2016 data. For each mass interval, the table shows the predicted background yield $N^\text{est}_\text{bkg}$ and the observed number of events $N^\text{obs}$ in each of the three $\text{min}(d_0 / \sigma_{d_0})$ bins. The quoted uncertainties are statistical only

Correspondence between the mass intervals in the TMS-TMS category and the parameters of the simulated signal samples.

Correspondence between the probed LLP masses and the chosen mass intervals in the TMS-TMS category.

Background estimation and observed number of events in the STA-TMS dimuon category in 2016 and 2018 data. For each probed LLP mass, the chosen mass interval is shown. The mass interval is followed by the estimated and observed counts for the given year. The quoted uncertainties are statistical only.

Background estimations and observed numbers of events in the STA-TMS dimuon category in 2016 and 2018 data. For each probed LLP mass, the chosen mass interval is shown, followed by the predicted background yield $N^\text{est}_\text{bkg}$ and the observed number of events $N^\text{obs}$ for the given year. The quoted uncertainties are statistical only.

Number of events passing consecutive sets of selection criteria for 2018 collision data and the signal process $\Phi(125) \rightarrow XX(20\ GeV, c\tau = 13\ cm) \rightarrow \mu\mu$. Each row introduces a new criterion that is applied in addition to the selection of the previous row. In addition to the total number of events, N(events), the event yields of the individual dimuon vertex categories, STA-STA, TMS-TMS, and STA-TMS, are shown in separate columns for each data set. In these columns, events containing selected dimuons of different categories are independently counted for each category.

Number of events passing consecutive sets of selection criteria, in 2018 data and in a sample of simulated $\Phi \rightarrow XX \rightarrow \mu\mu$ signal events with $m(H) = 125\ GeV$, $m(X) = 20\ GeV$, and $c\tau = 13\ cm$. Each row introduces a new criterion that is applied in addition to the selection of the previous row. In addition to the total number of events $N(\text{total})$, the event yields in the individual dimuon categories, STA-STA, TMS-TMS, and STA-TMS, are shown in separate columns for each data set. In these columns, events containing selected dimuons of different categories are counted independently for each category.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal process with $m(\Phi) = 125\ GeV$ and $m(X) = 20\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal process with $m(\Phi) = 125\ GeV$ and $m(X) = 20\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (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. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal process with $m(\Phi) = 125\ GeV$ and $m(X) = 50\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal process with $m(\Phi) = 125\ GeV$ and $m(X) = 50\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (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. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal process with $m(\Phi) = 200\ GeV$ and $m(X) = 20\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal process with $m(\Phi) = 200\ GeV$ and $m(X) = 20\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (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. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal process with $m(\Phi) = 200\ GeV$ and $m(X) = 50\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal process with $m(\Phi) = 200\ GeV$ and $m(X) = 50\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (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. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal process with $m(\Phi) = 400\ GeV$ and $m(X) = 20\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal process with $m(\Phi) = 400\ GeV$ and $m(X) = 20\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (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. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal process with $m(\Phi) = 400\ GeV$ and $m(X) = 50\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal process with $m(\Phi) = 400\ GeV$ and $m(X) = 50\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (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. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal process with $m(\Phi) = 400\ GeV$ and $m(X) = 150\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal process with $m(\Phi) = 400\ GeV$ and $m(X) = 150\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (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. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal process with $m(\Phi) = 1000\ GeV$ and $m(X) = 20\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal process with $m(\Phi) = 1\ TeV$ and $m(X) = 20\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (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. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal process with $m(\Phi) = 1000\ GeV$ and $m(X) = 50\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal process with $m(\Phi) = 1\ TeV$ and $m(X) = 50\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (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. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal process with $m(\Phi) = 1000\ GeV$ and $m(X) = 150\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal process with $m(\Phi) = 1\ TeV$ and $m(X) = 150\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (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. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal process with $m(\Phi) = 1000\ GeV$ and $m(X) = 350\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal process with $m(\Phi) = 1\ TeV$ and $m(X) = 350\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (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. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow 4\mu$ signal process with $m(\Phi) = 125\ GeV$ and $m(X) = 20\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow 4\mu$ signal process with $m(\Phi) = 125\ GeV$ and $m(X) = 20\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (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. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow 4\mu$ signal process with $m(\Phi) = 125\ GeV$ and $m(X) = 50\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow 4\mu$ signal process with $m(\Phi) = 125\ GeV$ and $m(X) = 50\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (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. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow 4\mu$ signal process with $m(\Phi) = 200\ GeV$ and $m(X) = 20\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow 4\mu$ signal process with $m(\Phi) = 200\ GeV$ and $m(X) = 20\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (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. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow 4\mu$ signal process with $m(\Phi) = 200\ GeV$ and $m(X) = 50\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow 4\mu$ signal process with $m(\Phi) = 200\ GeV$ and $m(X) = 50\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (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. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow 4\mu$ signal process with $m(\Phi) = 400\ GeV$ and $m(X) = 20\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow 4\mu$ signal process with $m(\Phi) = 400\ GeV$ and $m(X) = 20\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (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. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow 4\mu$ signal process with $m(\Phi) = 400\ GeV$ and $m(X) = 50\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow 4\mu$ signal process with $m(\Phi) = 400\ GeV$ and $m(X) = 50\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (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. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow 4\mu$ signal process with $m(\Phi) = 400\ GeV$ and $m(X) = 150\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow 4\mu$ signal process with $m(\Phi) = 400\ GeV$ and $m(X) = 150\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (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. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow 4\mu$ signal process with $m(\Phi) = 1000\ GeV$ and $m(X) = 20\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow 4\mu$ signal process with $m(\Phi) = 1\ TeV$ and $m(X) = 20\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (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. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow 4\mu$ signal process with $m(\Phi) = 1000\ GeV$ and $m(X) = 50\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow 4\mu$ signal process with $m(\Phi) = 1\ TeV$ and $m(X) = 50\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (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. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow 4\mu$ signal process with $m(\Phi) = 1000\ GeV$ and $m(X) = 150\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow 4\mu$ signal process with $m(\Phi) = 1\ TeV$ and $m(X) = 150\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (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. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow 4\mu$ signal process with $m(\Phi) = 1000\ GeV$ and $m(X) = 350\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $\Phi \rightarrow XX \rightarrow 4\mu$ signal process with $m(\Phi) = 1\ TeV$ and $m(X) = 350\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (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. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $H \rightarrow Z_DZ_D \rightarrow \mu\mu + anything$ signal process with $m(H) = 125\ GeV$ and $m(Z_D) = 10\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $H \rightarrow Z_DZ_D \rightarrow \mu\mu + anything$ signal process with $m(H) = 125\ GeV$ and $m(Z_D) = 10\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well the combined efficiency (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. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $H \rightarrow Z_DZ_D \rightarrow \mu\mu + anything$ signal process with $m(H) = 125\ GeV$ and $m(Z_D) = 20\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $H \rightarrow Z_DZ_D \rightarrow \mu\mu + anything$ signal process with $m(H) = 125\ GeV$ and $m(Z_D) = 20\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well the combined efficiency (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. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $H \rightarrow Z_DZ_D \rightarrow \mu\mu + anything$ signal process with $m(H) = 125\ GeV$ and $m(Z_D) = 30\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $H \rightarrow Z_DZ_D \rightarrow \mu\mu + anything$ signal process with $m(H) = 125\ GeV$ and $m(Z_D) = 30\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well the combined efficiency (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. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $H \rightarrow Z_DZ_D \rightarrow \mu\mu + anything$ signal process with $m(H) = 125\ GeV$ and $m(Z_D) = 40\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $H \rightarrow Z_DZ_D \rightarrow \mu\mu + anything$ signal process with $m(H) = 125\ GeV$ and $m(Z_D) = 40\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well the combined efficiency (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. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $H \rightarrow Z_DZ_D \rightarrow \mu\mu + anything$ signal process with $m(H) = 125\ GeV$ and $m(Z_D) = 50\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $H \rightarrow Z_DZ_D \rightarrow \mu\mu + anything$ signal process with $m(H) = 125\ GeV$ and $m(Z_D) = 50\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well the combined efficiency (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. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $H \rightarrow Z_DZ_D \rightarrow \mu\mu + anything$ signal process with $m(H) = 125\ GeV$ and $m(Z_D) = 60\ GeV$. The figure shows efficiencies in the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well as the combined efficiency (black) calculated as the sum of the efficiencies of the individual categories. The signal efficiencies for the 2016 and 2018 datasets are shown as dashed and solid lines, respectively.

Overall signal efficiencies as a function of $c\tau$ for the $H \rightarrow Z_DZ_D \rightarrow \mu\mu + anything$ signal process with $m(H) = 125\ GeV$ and $m(Z_D) = 60\ GeV$. The plot shows efficiencies of the three dimuon categories, STA-STA (green), TMS-TMS (red), and STA-TMS (blue), as well the combined efficiency (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. The efficiencies in the 2016 and 2018 data sets are shown as dashed and solid curves, respectively.

Signal efficiencies as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $L_{xy}^\mathrm{true} < 20\ cm$ in the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal model, in 2016 samples. 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 applied in the STA-STA dimuon category 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 as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $L_{xy}^\mathrm{true} < 20\ cm$ in the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal model, in 2018 samples. 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 applied in the STA-STA dimuon category 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 as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $L_{xy}^\mathrm{true} < 20\ cm$ in the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal model, in 2016 samples. 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 applied in the STA-TMS dimuon category 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 as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $L_{xy}^\mathrm{true} < 20\ cm$ in the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal model, in 2018 samples. 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 applied in the STA-TMS dimuon category 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 as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $L_{xy}^\mathrm{true} < 20\ cm$ in the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal model, in 2016 samples. 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 applied in the TMS-TMS dimuon category 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 as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $L_{xy}^\mathrm{true} < 20\ cm$ in the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal model, in 2018 samples. 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 applied in the TMS-TMS dimuon category 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 as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $20\ cm < L_{xy}^\mathrm{true} < 70\ cm$ in the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal model, in 2016 samples. 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 applied in the STA-STA dimuon category 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 as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $20\ cm < L_{xy}^\mathrm{true} < 70\ cm$ in the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal model, in 2018 samples. 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 applied in the STA-STA dimuon category 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 as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $20\ cm < L_{xy}^\mathrm{true} < 70\ cm$ in the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal model, in 2016 samples. 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 applied in the STA-TMS dimuon category 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 as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $20\ cm < L_{xy}^\mathrm{true} < 70\ cm$ in the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal model, in 2018 samples. 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 applied in the STA-TMS dimuon category 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 as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $20\ cm < L_{xy}^\mathrm{true} < 70\ cm$ in the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal model, in 2016 samples. 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 applied in the TMS-TMS dimuon category 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 as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $20\ cm < L_{xy}^\mathrm{true} < 70\ cm$ in the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal model, in 2018 samples. 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 applied in the TMS-TMS dimuon category 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 as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $70\ cm < L_{xy}^\mathrm{true} < 320\ cm$ in the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal model, in 2016 samples. 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 applied in the STA-STA dimuon category 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. Efficiencies for dimuons with $70\ cm < L_{xy}^\mathrm{true} < 320\ cm$ in the STA-TMS and TMS-TMS dimuon categories are equal to zero.

Signal efficiencies as a function of the smaller of the two values of generated muon $p_T$ and $d_0$ in dimuons with $70\ cm < L_{xy}^\mathrm{true} < 320\ cm$ in the $\Phi \rightarrow XX \rightarrow \mu\mu + anything$ signal model, in 2018 samples. 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 applied in the STA-STA dimuon category 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. Efficiencies for dimuons with $70\ cm < L_{xy}^\mathrm{true} < 320\ cm$ in the STA-TMS and TMS-TMS dimuon categories are equal to zero.

Self-normalized zg distributions in PbPb and smeared pp collisions in the 30-50 centrality event class for jets with PTJET 160-180 GeV.

Self-normalized zg distributions in PbPb and smeared pp collisions in the 10-30 centrality event class for jets with PTJET 160-180 GeV.

Self-normalized zg distributions in PbPb and smeared pp collisions in the 0-10 centrality event class for jets with PTJET 160-180 GeV.

Ratio of zg distributions in PbPb and smeared pp collisions in the 50-80 centrality event class for jets with PTJET 160-180 GeV.

Ratio of zg distributions in PbPb and smeared pp collisions in the 30-50 centrality event class for jets with PTJET 160-180 GeV.

Ratio of zg distributions in PbPb and smeared pp collisions in the 10-30 centrality event class for jets with PTJET 160-180 GeV.

Ratio of zg distributions in PbPb and smeared pp collisions in the 0-10 centrality event class for jets with PTJET 160-180 GeV.

Ratio of zg distributions in PbPb and smeared pp collisions in the 10% most central events for jets with PTJET 140-160 GeV.

Ratio of zg distributions in PbPb and smeared pp collisions in the 10% most central events for jets with PTJET 160-180 GeV.

Ratio of zg distributions in PbPb and smeared pp collisions in the 10% most central events for jets with PTJET 180-200 GeV.

Ratio of zg distributions in PbPb and smeared pp collisions in the 10% most central events for jets with PTJET 200-250 GeV.

Ratio of zg distributions in PbPb and smeared pp collisions in the 10% most central events for jets with PTJET 250-300 GeV.

Ratio of zg distributions in PbPb and smeared pp collisions in the 10% most central events for jets with PTJET 300-500 GeV.

Invariant charged particle differential yield in the centrality regions 30 TO 50%, 50 TO 70% and 70 TO 90%.

Nuclear modification factor RAA in the centrality regions 0 TO 5%, 5 TO 10% and 10 TO 30%.

Nuclear modification factor RAA in the centrality regions 30 TO 50%, 50 TO 70% and 70 TO 90%.

TAA-scaled ratio of PT spectra in central and peripheral bins, RCP.

95% CL intervals on the double ratio of measured yields, $(N_{\varUpsilon(3S)} / N_{\varUpsilon(1S)})_{\mathrm{PbPb}} / (N_{\varUpsilon(3S)} / N_{\varUpsilon(1S)})_{pp}$, as a function of centrality, for upsilon $|y|<2.4$ and $p_T<30$GeV, and $p_{T}^{\mu}>4$GeV.

68% CL intervals on the double ratio of measured yields, $(N_{\varUpsilon(3S)} / N_{\varUpsilon(1S)})_{\mathrm{PbPb}} / (N_{\varUpsilon(3S)} / N_{\varUpsilon(1S)})_{pp}$, as a function of centrality, for upsilon $|y|<2.4$ and $p_T<30$GeV, and $p_{T}^{\mu}>4$GeV.

Covariance matrix (statistical and systematic uncertainties combined) with the muon $p_{T}>35$ GeV. The units are in $10^{-4}$.

The $v_{3}$ values as a function of centrality for prompt and nonprompt J/$\psi$ mesons.The kinematic range is 6.5 $< p_{\text{T}} <$ 50 GeV/c and $|y| < 2.4$.

The $v_{2}$ values of prompt J/$\psi$ mesons as a function of $p_{\text{T}}$ in the 10–60% centrality range. The results for 3 $< p_{\text{T}} <$ 6.5 and 6.5 $< p_{\text{T}} <$ 50 GeV/c are studied in the rapidity range of 1.6 $< |y| <$ 2.4 and $|y| <$ 2.4, respectively.

The $v_{2}$ values as functions of $p_{\text{T}}$ for prompt J/$\psi$ and prompt $\psi$(2S) mesons in the 10–60% centrality range. The results for $p_{\text{T}}$ < 6.5 and $p_{\text{T}}$ > 6.5 GeV/c are studied in the rapidity range of 1.6 $< |y| <$ 2.4 and $|y| <$ 2.4, respectively.

The $v_{2}$ values as functions of centrality for prompt J/$\psi$ and prompt $\psi$(2S) mesons. The kinematic range is 6.5 $< p_{\text{T}} <$ 50 GeV/c and $|y| <$ 2.4.

The $v_{3}$ values as functions of $p_{\text{T}}$ for prompt J/$\psi$ and prompt $\psi$(2S) mesons in the 10–60% centrality range. The results for $p_{\text{T}}$ < 6.5 and $p_{\text{T}}$ > 6.5 GeV/c are studied in the rapidity range of 1.6 $< |y| <$ 2.4 and $|y| <$ 2.4, respectively.

The $v_{3}$ values as functions of centrality for prompt J/$\psi$ and prompt $\psi$(2S) mesons. The kinematic range is 6.5 $< p_{\text{T}} <$ 50 GeV/c and $|y| <$ 2.4.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in pp collisions. The results are shown in different dijet momentum balance bins.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $0.7 < p_{\mathrm{T}}^{\mathrm{ch}} < 1$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $0.7 < p_{\mathrm{T}}^{\mathrm{ch}} < 1$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $0.7 < p_{\mathrm{T}}^{\mathrm{ch}} < 1$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $0.7 < p_{\mathrm{T}}^{\mathrm{ch}} < 1$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $0.7 < p_{\mathrm{T}}^{\mathrm{ch}} < 1$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $1 < p_{\mathrm{T}}^{\mathrm{ch}} < 2$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $1 < p_{\mathrm{T}}^{\mathrm{ch}} < 2$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $1 < p_{\mathrm{T}}^{\mathrm{ch}} < 2$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $1 < p_{\mathrm{T}}^{\mathrm{ch}} < 2$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $1 < p_{\mathrm{T}}^{\mathrm{ch}} < 2$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $2 < p_{\mathrm{T}}^{\mathrm{ch}} < 3$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $2 < p_{\mathrm{T}}^{\mathrm{ch}} < 3$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $2 < p_{\mathrm{T}}^{\mathrm{ch}} < 3$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $2 < p_{\mathrm{T}}^{\mathrm{ch}} < 3$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $2 < p_{\mathrm{T}}^{\mathrm{ch}} < 3$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $3 < p_{\mathrm{T}}^{\mathrm{ch}} < 4$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $3 < p_{\mathrm{T}}^{\mathrm{ch}} < 4$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $3 < p_{\mathrm{T}}^{\mathrm{ch}} < 4$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $3 < p_{\mathrm{T}}^{\mathrm{ch}} < 4$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $3 < p_{\mathrm{T}}^{\mathrm{ch}} < 4$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $4 < p_{\mathrm{T}}^{\mathrm{ch}} < 8$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $4 < p_{\mathrm{T}}^{\mathrm{ch}} < 8$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $4 < p_{\mathrm{T}}^{\mathrm{ch}} < 8$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $4 < p_{\mathrm{T}}^{\mathrm{ch}} < 8$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $4 < p_{\mathrm{T}}^{\mathrm{ch}} < 8$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $8 < p_{\mathrm{T}}^{\mathrm{ch}} < 12$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $8 < p_{\mathrm{T}}^{\mathrm{ch}} < 12$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $8 < p_{\mathrm{T}}^{\mathrm{ch}} < 12$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $8 < p_{\mathrm{T}}^{\mathrm{ch}} < 12$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the leading jets as a function of $\Delta\eta$ in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $8 < p_{\mathrm{T}}^{\mathrm{ch}} < 12$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in pp collisions. The results are shown in different dijet momentum balance bins.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $0.7 < p_{\mathrm{T}}^{\mathrm{ch}} < 1$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $0.7 < p_{\mathrm{T}}^{\mathrm{ch}} < 1$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $0.7 < p_{\mathrm{T}}^{\mathrm{ch}} < 1$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $0.7 < p_{\mathrm{T}}^{\mathrm{ch}} < 1$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $0.7 < p_{\mathrm{T}}^{\mathrm{ch}} < 1$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $1 < p_{\mathrm{T}}^{\mathrm{ch}} < 2$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $1 < p_{\mathrm{T}}^{\mathrm{ch}} < 2$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $1 < p_{\mathrm{T}}^{\mathrm{ch}} < 2$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $1 < p_{\mathrm{T}}^{\mathrm{ch}} < 2$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $1 < p_{\mathrm{T}}^{\mathrm{ch}} < 2$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $2 < p_{\mathrm{T}}^{\mathrm{ch}} < 3$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $2 < p_{\mathrm{T}}^{\mathrm{ch}} < 3$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $2 < p_{\mathrm{T}}^{\mathrm{ch}} < 3$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $2 < p_{\mathrm{T}}^{\mathrm{ch}} < 3$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $2 < p_{\mathrm{T}}^{\mathrm{ch}} < 3$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $3 < p_{\mathrm{T}}^{\mathrm{ch}} < 4$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $3 < p_{\mathrm{T}}^{\mathrm{ch}} < 4$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $3 < p_{\mathrm{T}}^{\mathrm{ch}} < 4$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $3 < p_{\mathrm{T}}^{\mathrm{ch}} < 4$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $3 < p_{\mathrm{T}}^{\mathrm{ch}} < 4$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $4 < p_{\mathrm{T}}^{\mathrm{ch}} < 8$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $4 < p_{\mathrm{T}}^{\mathrm{ch}} < 8$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $4 < p_{\mathrm{T}}^{\mathrm{ch}} < 8$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $4 < p_{\mathrm{T}}^{\mathrm{ch}} < 8$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $4 < p_{\mathrm{T}}^{\mathrm{ch}} < 8$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $8 < p_{\mathrm{T}}^{\mathrm{ch}} < 12$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $8 < p_{\mathrm{T}}^{\mathrm{ch}} < 12$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $8 < p_{\mathrm{T}}^{\mathrm{ch}} < 12$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $8 < p_{\mathrm{T}}^{\mathrm{ch}} < 12$ GeV.

The distribution of charged particle yields within $|\Delta\varphi| < 1.0$ correlated with the subleading jets as a function of $\Delta\eta$ in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $8 < p_{\mathrm{T}}^{\mathrm{ch}} < 12$ GeV.

The leading jet radial momentum profiles in pp and PbPb collisions and a function of $\Delta r$. The PbPb results are shown for different centrality regions.

The leading jet radial momentum profiles in pp and PbPb collisions and a function of $\Delta r$ for the charged particle $p_{\mathrm{T}}$ bin $0.7 < p_{\mathrm{T}}^{\mathrm{ch}} < 1$ GeV. The PbPb results are shown for different centrality regions.

The leading jet radial momentum profiles in pp and PbPb collisions and a function of $\Delta r$ for the charged particle $p_{\mathrm{T}}$ bin $1 < p_{\mathrm{T}}^{\mathrm{ch}} < 2$ GeV. The PbPb results are shown for different centrality regions.

The leading jet radial momentum profiles in pp and PbPb collisions and a function of $\Delta r$ for the charged particle $p_{\mathrm{T}}$ bin $2 < p_{\mathrm{T}}^{\mathrm{ch}} < 3$ GeV. The PbPb results are shown for different centrality regions.

The leading jet radial momentum profiles in pp and PbPb collisions and a function of $\Delta r$ for the charged particle $p_{\mathrm{T}}$ bin $3 < p_{\mathrm{T}}^{\mathrm{ch}} < 4$ GeV. The PbPb results are shown for different centrality regions.

The leading jet radial momentum profiles in pp and PbPb collisions and a function of $\Delta r$ for the charged particle $p_{\mathrm{T}}$ bin $4 < p_{\mathrm{T}}^{\mathrm{ch}} < 8$ GeV. The PbPb results are shown for different centrality regions.

The leading jet radial momentum profiles in pp and PbPb collisions and a function of $\Delta r$ for the charged particle $p_{\mathrm{T}}$ bin $8 < p_{\mathrm{T}}^{\mathrm{ch}} < 12$ GeV. The PbPb results are shown for different centrality regions.

The leading jet radial momentum profiles in pp and PbPb collisions and a function of $\Delta r$ for the charged particle $p_{\mathrm{T}}$ bin $12 < p_{\mathrm{T}}^{\mathrm{ch}} < 300$ GeV. The PbPb results are shown for different centrality regions.

The subleading jet radial momentum profiles in pp and PbPb collisions as a function of $\Delta r$. The PbPb results are shown for different centrality regions.

The subleading jet radial momentum profiles in pp and PbPb collisions as a function of $\Delta r$ for the charged particle $p_{\mathrm{T}}$ bin $0.7 < p_{\mathrm{T}}^{\mathrm{ch}} < 1$ GeV. The PbPb results are shown for different centrality regions.

The subleading jet radial momentum profiles in pp and PbPb collisions as a function of $\Delta r$ for the charged particle $p_{\mathrm{T}}$ bin $1 < p_{\mathrm{T}}^{\mathrm{ch}} < 2$ GeV. The PbPb results are shown for different centrality regions.

The subleading jet radial momentum profiles in pp and PbPb collisions as a function of $\Delta r$ for the charged particle $p_{\mathrm{T}}$ bin $2 < p_{\mathrm{T}}^{\mathrm{ch}} < 3$ GeV. The PbPb results are shown for different centrality regions.

The subleading jet radial momentum profiles in pp and PbPb collisions as a function of $\Delta r$ for the charged particle $p_{\mathrm{T}}$ bin $3 < p_{\mathrm{T}}^{\mathrm{ch}} < 4$ GeV. The PbPb results are shown for different centrality regions.

The subleading jet radial momentum profiles in pp and PbPb collisions as a function of $\Delta r$ for the charged particle $p_{\mathrm{T}}$ bin $4 < p_{\mathrm{T}}^{\mathrm{ch}} < 8$ GeV. The PbPb results are shown for different centrality regions.

The subleading jet radial momentum profiles in pp and PbPb collisions as a function of $\Delta r$ for the charged particle $p_{\mathrm{T}}$ bin $8 < p_{\mathrm{T}}^{\mathrm{ch}} < 12$ GeV. The PbPb results are shown for different centrality regions.

The subleading jet radial momentum profiles in pp and PbPb collisions as a function of $\Delta r$ for the charged particle $p_{\mathrm{T}}$ bin $12 < p_{\mathrm{T}}^{\mathrm{ch}} < 300$ GeV. The PbPb results are shown for different centrality regions.

The ratio between leading jet radial momentum profiles in PbPb and pp collisions as a function of $\Delta r$.

The ratio between subleading jet radial momentum profiles in PbPb and pp collisions as a function of $\Delta r$.

Jet shapes for leading jets in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins.

Jet shapes for leading jets in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins.

Jet shapes for leading jets in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins.

Jet shapes for leading jets in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins.

Jet shapes for leading jets in pp collisions. The results are shown in different dijet momentum balance bins.

Jet shapes for leading jets in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $0.7 < p_{\mathrm{T}}^{\mathrm{ch}} < 1$ GeV.

Jet shapes for leading jets in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $0.7 < p_{\mathrm{T}}^{\mathrm{ch}} < 1$ GeV.

Jet shapes for leading jets in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $0.7 < p_{\mathrm{T}}^{\mathrm{ch}} < 1$ GeV.

Jet shapes for leading jets in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $0.7 < p_{\mathrm{T}}^{\mathrm{ch}} < 1$ GeV.

Jet shapes for leading jets in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $0.7 < p_{\mathrm{T}}^{\mathrm{ch}} < 1$ GeV.

Jet shapes for leading jets in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $1 < p_{\mathrm{T}}^{\mathrm{ch}} < 2$ GeV.

Jet shapes for leading jets in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $1 < p_{\mathrm{T}}^{\mathrm{ch}} < 2$ GeV.

Jet shapes for leading jets in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $1 < p_{\mathrm{T}}^{\mathrm{ch}} < 2$ GeV.

Jet shapes for leading jets in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $1 < p_{\mathrm{T}}^{\mathrm{ch}} < 2$ GeV.

Jet shapes for leading jets in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $1 < p_{\mathrm{T}}^{\mathrm{ch}} < 2$ GeV.

Jet shapes for leading jets in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $2 < p_{\mathrm{T}}^{\mathrm{ch}} < 3$ GeV.

Jet shapes for leading jets in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $2 < p_{\mathrm{T}}^{\mathrm{ch}} < 3$ GeV.

Jet shapes for leading jets in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $2 < p_{\mathrm{T}}^{\mathrm{ch}} < 3$ GeV.

Jet shapes for leading jets in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $2 < p_{\mathrm{T}}^{\mathrm{ch}} < 3$ GeV.

Jet shapes for leading jets in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $2 < p_{\mathrm{T}}^{\mathrm{ch}} < 3$ GeV.

Jet shapes for leading jets in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $3 < p_{\mathrm{T}}^{\mathrm{ch}} < 4$ GeV.

Jet shapes for leading jets in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $3 < p_{\mathrm{T}}^{\mathrm{ch}} < 4$ GeV.

Jet shapes for leading jets in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $3 < p_{\mathrm{T}}^{\mathrm{ch}} < 4$ GeV.

Jet shapes for leading jets in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $3 < p_{\mathrm{T}}^{\mathrm{ch}} < 4$ GeV.

Jet shapes for leading jets in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $3 < p_{\mathrm{T}}^{\mathrm{ch}} < 4$ GeV.

Jet shapes for leading jets in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $4 < p_{\mathrm{T}}^{\mathrm{ch}} < 8$ GeV.

Jet shapes for leading jets in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $4 < p_{\mathrm{T}}^{\mathrm{ch}} < 8$ GeV.

Jet shapes for leading jets in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $4 < p_{\mathrm{T}}^{\mathrm{ch}} < 8$ GeV.

Jet shapes for leading jets in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $4 < p_{\mathrm{T}}^{\mathrm{ch}} < 8$ GeV.

Jet shapes for leading jets in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $4 < p_{\mathrm{T}}^{\mathrm{ch}} < 8$ GeV.

Jet shapes for leading jets in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $8 < p_{\mathrm{T}}^{\mathrm{ch}} < 12$ GeV.

Jet shapes for leading jets in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $8 < p_{\mathrm{T}}^{\mathrm{ch}} < 12$ GeV.

Jet shapes for leading jets in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $8 < p_{\mathrm{T}}^{\mathrm{ch}} < 12$ GeV.

Jet shapes for leading jets in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $8 < p_{\mathrm{T}}^{\mathrm{ch}} < 12$ GeV.

Jet shapes for leading jets in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $8 < p_{\mathrm{T}}^{\mathrm{ch}} < 12$ GeV.

Jet shapes for leading jets in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $12 < p_{\mathrm{T}}^{\mathrm{ch}} < 300$ GeV.

Jet shapes for leading jets in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $12 < p_{\mathrm{T}}^{\mathrm{ch}} < 300$ GeV.

Jet shapes for leading jets in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $12 < p_{\mathrm{T}}^{\mathrm{ch}} < 300$ GeV.

Jet shapes for leading jets in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $12 < p_{\mathrm{T}}^{\mathrm{ch}} < 300$ GeV.

Jet shapes for leading jets in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $12 < p_{\mathrm{T}}^{\mathrm{ch}} < 300$ GeV.

Ratios of leading jet shapes between PbPb and pp collisions. The results from 0-10 % centrality bin in PbPb are compared to pp using several dijet momentum balance selections.

Ratios of leading jet shapes between PbPb and pp collisions. The results from 10-30 % centrality bin in PbPb are compared to pp using several dijet momentum balance selections.

Ratios of leading jet shapes between PbPb and pp collisions. The results from 30-50 % centrality bin in PbPb are compared to pp using several dijet momentum balance selections.

Ratios of leading jet shapes between PbPb and pp collisions. The results from 50-90 % centrality bin in PbPb are compared to pp using several dijet momentum balance selections.

Jet shapes for subleading jets in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins.

Jet shapes for subleading jets in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins.

Jet shapes for subleading jets in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins.

Jet shapes for subleading jets in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins.

Jet shapes for subleading jets in pp collisions. The results are shown in different dijet momentum balance bins.

Jet shapes for subleading jets in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $0.7 < p_{\mathrm{T}}^{\mathrm{ch}} < 1$ GeV.

Jet shapes for subleading jets in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $0.7 < p_{\mathrm{T}}^{\mathrm{ch}} < 1$ GeV.

Jet shapes for subleading jets in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $0.7 < p_{\mathrm{T}}^{\mathrm{ch}} < 1$ GeV.

Jet shapes for subleading jets in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $0.7 < p_{\mathrm{T}}^{\mathrm{ch}} < 1$ GeV.

Jet shapes for subleading jets in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $0.7 < p_{\mathrm{T}}^{\mathrm{ch}} < 1$ GeV.

Jet shapes for subleading jets in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $1 < p_{\mathrm{T}}^{\mathrm{ch}} < 2$ GeV.

Jet shapes for subleading jets in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $1 < p_{\mathrm{T}}^{\mathrm{ch}} < 2$ GeV.

Jet shapes for subleading jets in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $1 < p_{\mathrm{T}}^{\mathrm{ch}} < 2$ GeV.

Jet shapes for subleading jets in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $1 < p_{\mathrm{T}}^{\mathrm{ch}} < 2$ GeV.

Jet shapes for subleading jets in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $1 < p_{\mathrm{T}}^{\mathrm{ch}} < 2$ GeV.

Jet shapes for subleading jets in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $2 < p_{\mathrm{T}}^{\mathrm{ch}} < 3$ GeV.

Jet shapes for subleading jets in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $2 < p_{\mathrm{T}}^{\mathrm{ch}} < 3$ GeV.

Jet shapes for subleading jets in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $2 < p_{\mathrm{T}}^{\mathrm{ch}} < 3$ GeV.

Jet shapes for subleading jets in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $2 < p_{\mathrm{T}}^{\mathrm{ch}} < 3$ GeV.

Jet shapes for subleading jets in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $2 < p_{\mathrm{T}}^{\mathrm{ch}} < 3$ GeV.

Jet shapes for subleading jets in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $3 < p_{\mathrm{T}}^{\mathrm{ch}} < 4$ GeV.

Jet shapes for subleading jets in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $3 < p_{\mathrm{T}}^{\mathrm{ch}} < 4$ GeV.

Jet shapes for subleading jets in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $3 < p_{\mathrm{T}}^{\mathrm{ch}} < 4$ GeV.

Jet shapes for subleading jets in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $3 < p_{\mathrm{T}}^{\mathrm{ch}} < 4$ GeV.

Jet shapes for subleading jets in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $3 < p_{\mathrm{T}}^{\mathrm{ch}} < 4$ GeV.

Jet shapes for subleading jets in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $4 < p_{\mathrm{T}}^{\mathrm{ch}} < 8$ GeV.

Jet shapes for subleading jets in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $4 < p_{\mathrm{T}}^{\mathrm{ch}} < 8$ GeV.

Jet shapes for subleading jets in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $4 < p_{\mathrm{T}}^{\mathrm{ch}} < 8$ GeV.

Jet shapes for subleading jets in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $4 < p_{\mathrm{T}}^{\mathrm{ch}} < 8$ GeV.

Jet shapes for subleading jets in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $4 < p_{\mathrm{T}}^{\mathrm{ch}} < 8$ GeV.

Jet shapes for subleading jets in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $8 < p_{\mathrm{T}}^{\mathrm{ch}} < 12$ GeV.

Jet shapes for subleading jets in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $8 < p_{\mathrm{T}}^{\mathrm{ch}} < 12$ GeV.

Jet shapes for subleading jets in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $8 < p_{\mathrm{T}}^{\mathrm{ch}} < 12$ GeV.

Jet shapes for subleading jets in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $8 < p_{\mathrm{T}}^{\mathrm{ch}} < 12$ GeV.

Jet shapes for subleading jets in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $8 < p_{\mathrm{T}}^{\mathrm{ch}} < 12$ GeV.

Jet shapes for subleading jets in the 0-10 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $12 < p_{\mathrm{T}}^{\mathrm{ch}} < 300$ GeV.

Jet shapes for subleading jets in the 10-30 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $12 < p_{\mathrm{T}}^{\mathrm{ch}} < 300$ GeV.

Jet shapes for subleading jets in the 30-50 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $12 < p_{\mathrm{T}}^{\mathrm{ch}} < 300$ GeV.

Jet shapes for subleading jets in the 50-90 % centrality bin in PbPb collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $12 < p_{\mathrm{T}}^{\mathrm{ch}} < 300$ GeV.

Jet shapes for subleading jets in pp collisions. The results are shown in different dijet momentum balance bins for the charged particle $p_{\mathrm{T}}$ bin $12 < p_{\mathrm{T}}^{\mathrm{ch}} < 300$ GeV.

Ratios of subleading jet shapes between PbPb and pp collisions. The results from 0-10 % centrality bin in PbPb are compared to pp using several dijet momentum balance selections.

Ratios of subleading jet shapes between PbPb and pp collisions. The results from 10-30 % centrality bin in PbPb are compared to pp using several dijet momentum balance selections.

Ratios of subleading jet shapes between PbPb and pp collisions. The results from 30-50 % centrality bin in PbPb are compared to pp using several dijet momentum balance selections.

Ratios of subleading jet shapes between PbPb and pp collisions. The results from 50-90 % centrality bin in PbPb are compared to pp using several dijet momentum balance selections.

Ratio between unbalanced selection of leading jet shapes to all leading jet shapes in pp and PbPb collisions. The PbPb results are shown for different centrality regions.

Ratio between balanced selection of leading jet shapes to all leading jet shapes in pp and PbPb collisions. The PbPb results are shown for different centrality regions.

Ratio between unbalanced selection of subleading jet shapes to all subleading jet shapes in pp and PbPb collisions. The PbPb results are shown for different centrality regions.

Ratio between balanced selection of subleading jet shapes to all subleading jet shapes in pp and PbPb collisions. The PbPb results are shown for different centrality regions.

Generator-level vs. reconstructed $x_{j}$ values in the analysis $x_{j}$ bins. The plots show the probability to find a generator level $x_{j}$ for a given reconstructed $x_{j}$.

Generator-level vs. reconstructed $x_{j}$ values in the analysis $x_{j}$ bins. The plots show the probability to find a reconstructed $x_{j}$ for a given generator level $x_{j}$.