Distribution of ${E}_{T}^{miss}$ after the fit of the multijet backgrounds, in the electron channel, in the $t\bar{t}$ 3-jets VR, without applying the cut on ${E}_{T}^{miss}$. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit. The last bin includes the overflow. The uncertainty band indicates the simulation's statistical uncertainty, the normalisation uncertainties for different processes ($40$ % for $W$+jets production, $30$ % for multijet background and $6$ % for top-quark processes) and the multijet background shape uncertainty in each bin, summed in quadrature. The lower panel of the figure shows the ratio of the data to the prediction.

Distribution of ${E}_{T}^{miss}$ after the fit of the multijet backgrounds, in the electron channel, in the $t\bar{t}$ 4-jets VR, without applying the cut on ${E}_{T}^{miss}$. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit. The last bin includes the overflow. The uncertainty band indicates the simulation's statistical uncertainty, the normalisation uncertainties for different processes ($40$ % for $W$+jets production, $30$ % for multijet background and $6$ % for top-quark processes) and the multijet background shape uncertainty in each bin, summed in quadrature. The lower panel of the figure shows the ratio of the data to the prediction.

Distribution of $m_{T}^{W}$ after the fit of the multijet backgrounds, in the muon channel, in the signal region, without applying the cut on $m_{T}^{W}$. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit. The last bin includes the overflow. The uncertainty band indicates the simulation's statistical uncertainty, the normalisation uncertainties for different processes ($40$ % for $W$+jets production, $30$ % for multijet background and $6$ % for top-quark processes) and the multijet background shape uncertainty in each bin, summed in quadrature. The lower panel of the figure shows the ratio of the data to the prediction.

Distribution of $m_{T}^{W}$ after the fit of the multijet backgrounds, in the muon channel, in the $W$+jets VR, without applying the cut on $m_{T}^{W}$. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit. The last bin includes the overflow. The uncertainty band indicates the simulation's statistical uncertainty, the normalisation uncertainties for different processes ($40$ % for $W$+jets production, $30$ % for multijet background and $6$ % for top-quark processes) and the multijet background shape uncertainty in each bin, summed in quadrature. The lower panel of the figure shows the ratio of the data to the prediction.

Distribution of $m_{T}^{W}$ after the fit of the multijet backgrounds, in the muon channel, in the $t\bar{t}$ 3-jets VR, without applying the cut on $m_{T}^{W}$. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit. The last bin includes the overflow. The uncertainty band indicates the simulation's statistical uncertainty, the normalisation uncertainties for different processes ($40$ % for $W$+jets production, $30$ % for multijet background and $6$ % for top-quark processes) and the multijet background shape uncertainty in each bin, summed in quadrature. The lower panel of the figure shows the ratio of the data to the prediction.

Distribution of $m_{T}^{W}$ after the fit of the multijet backgrounds, in the muon channel, in the $t\bar{t}$ 4-jets VR, without applying the cut on $m_{T}^{W}$. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit. The last bin includes the overflow. The uncertainty band indicates the simulation's statistical uncertainty, the normalisation uncertainties for different processes ($40$ % for $W$+jets production, $30$ % for multijet background and $6$ % for top-quark processes) and the multijet background shape uncertainty in each bin, summed in quadrature. The lower panel of the figure shows the ratio of the data to the prediction.

Expected distributions of the MEM discriminant $P(S|X)$ in the SR, for the s-channel single-top signal, and for the $t\bar{t}$ and $W$+jets backgrounds, for MEM discriminant values larger than $2.0\times10^{-4}$. Each distribution is normalised to unity. The binning is the same as the optimised binning used in the signal extraction fit, resulting in a non-linear horizontal scale.

Distribution of the MEM discriminant $P(S|X)$ in the $W$+jets VR. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit presented in Section 5 in the paper. The uncertainty band indicates the simulation's statistical uncertainty and the normalisation uncertainties for the various processes in each bin, summed in quadrature. The ratio of the observed number to the predicted number of events in each bin is shown in the lower panel of the figure, with different vertical axis ranges. The binning is the same as the optimised binning used in the signal extraction fit described in Section 8 in the paper, resulting in a non-linear horizontal scale.

Distribution of the MEM discriminant $P(S|X)$ in the $t\bar{t}$ 3-jets VR. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit presented in Section 5 in the paper. The uncertainty band indicates the simulation's statistical uncertainty and the normalisation uncertainties for the various processes in each bin, summed in quadrature. The ratio of the observed number to the predicted number of events in each bin is shown in the lower panel of the figure, with different vertical axis ranges. The binning is the same as the optimised binning used in the signal extraction fit described in Section 8 in the paper, resulting in a non-linear horizontal scale.

Distribution of the MEM discriminant $P(S|X)$ in the $t\bar{t}$ 4-jets VR. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit presented in Section 5 in the paper. The uncertainty bands indicate the simulation's statistical uncertainty and the normalisation uncertainties for the various processes in each bin, summed in quadrature. The ratio of the observed number to the predicted number of events in each bin is shown in the lower panel of the figure, with different vertical axis ranges. The binning is the same as the optimised binning used in the signal extraction fit described in Section 8 in the paper, resulting in a non-linear horizontal scale.

Distribution of the MEM discriminant $P(S|X)$ in the SR before the fit to data, for MEM discriminant values larger than $2.0\times10^{-4}$. The lower panel of the figure shows the ratio of the data to the prediction, with different vertical axis ranges. The uncertainty band indicates the total uncertainties and their correlations in each bin. The uncertainties in the $t\bar{t}$ and $W$+jets normalisation factors, as well as in the s-channel signal cross-section, are not defined pre-fit and therefore not included. The binning is the same as the optimised binning used in the fit, resulting in a non-linear horizontal scale.

Distribution of the MEM discriminant $P(S|X)$ in the SR after the fit to data, for MEM discriminant values larger than $2.0\times10^{-4}$. The lower panel of the figure shows the ratio of the data to the prediction, with different vertical axis ranges. The uncertainty band indicates the total uncertainties and their correlations in each bin. The binning is the same as the optimised binning used in the fit, resulting in a non-linear horizontal scale.

Distribution of the MEM discriminant $P(S|X)$ in the SR after the fit to data, for MEM discriminant values larger than $2.0\times10^{-4}$, after subtraction of all backgrounds. The fitted distribution for the simulation of the signal is shown together with the post-fit uncertainty in the backgrounds. The binning is the same as the optimised binning used in the fit, resulting in a non-linear horizontal scale.

Pre-fit and post-fit event yields in the SR, for MEM discriminant values larger than $2.0\times10^{-4}$. The central value of the event yield for each process is calculated by summing the values of the discriminant bin contents, using the nominal expected yield for the pre-fit value, and the best-fit estimate for the post-fit value. The error includes statistical and systematic uncertainties summed in quadrature. All sources of systematic uncertainties are included, taking into account correlations and anti-correlations in the post-fit case. The uncertainties in the $t\bar{t}$ and $W$+jets normalisation factors, as well as in the s-channel signal cross-section, are not defined pre-fit and therefore only included in the post-fit uncertainties.

Observed impact of the different sources of uncertainty on the measured s-channel signal cross-section, grouped by categories. The impact of each category is obtained by repeating the fit after having fixed the set of nuisance parameters corresponding to that category, subtracting the square of the resulting uncertainty from the square of the uncertainty found in the full fit, and calculating the square root. The 'Systematic uncertainties' category combines all sources of systematic uncertainties. The statistical uncertainty is obtained by repeating the fit after having fixed all nuisance parameters, including the $t\bar{t}$ and $W$+jets normalisation factors. 'Total' gives the total uncertainty on the measurement.

Observed impact of the different sources of $t\bar{t}$ modelling uncertainty on the measured s-channel signal cross-section. The impact of each category is obtained by repeating the fit after having fixed the set of nuisance parameters corresponding to that category, subtracting the square of the resulting uncertainty from the square of the uncertainty found in the full fit, and calculating the square root. 'PS & had.' refers to the parton shower and hadronisation model, and 'ME/PS matching' to the matching of the ME to the parton shower.

Observed impact of the different sources of s-channel modelling uncertainty on the measured s-channel signal cross-section. The impact of each category is obtained by repeating the fit after having fixed the set of nuisance parameters corresponding to that category, subtracting the square of the resulting uncertainty from the square of the uncertainty found in the full fit, and calculating the square root. 'PS & had.' refers to the parton shower and hadronisation model, as described in Section 7 in the paper.

Observed impact of the different sources of t-channel modelling uncertainty on the measured s-channel signal cross-section. The impact of each category is obtained by repeating the fit after having fixed the set of nuisance parameters corresponding to that category, subtracting the square of the resulting uncertainty from the square of the uncertainty found in the full fit, and calculating the square root. 'PS & had.' refers to the parton shower and hadronisation model, as described in Section 7 in the paper.

Observed impact of the different sources of $tW$ modelling uncertainty on the measured s-channel signal cross-section, grouped by categories. The impact of each category is obtained by repeating the fit after having fixed the set of nuisance parameters corresponding to that category, subtracting the square of the resulting uncertainty from the square of the uncertainty found in the full fit, and calculating the square root. 'PS & had.' refers to the parton shower and hadronisation model, and '$t\bar{t}$ overlap' to the algorithm removing the overlap between $tW$ and $t\bar{t}$ production at NLO, as described in Section 7 in the paper.

Observed impact of the different sources of PDF uncertainties on the measured s-channel signal cross-section, grouped by categories. The impact of each category is obtained by repeating the fit after having fixed the set of nuisance parameters corresponding to that category, subtracting the square of the resulting uncertainty from the square of the uncertainty found in the full fit, and calculating the square root.

Comparison between data and prediction after the fit to data in the signal region for the leading-jet $p_{T}$. The last bin includes the overflow. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.

Comparison between data and prediction after the fit to data in the signal region for the leading-jet $\eta$. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.

Comparison between data and prediction after the fit to data in the signal region for the subleading-jet $p_{T}$. The last bin includes the overflow. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.

Comparison between data and prediction after the fit to data in the signal region for the subleading-jet $\eta$. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.

Comparison between data and prediction after the fit to data in the signal region for the lepton $p_{T}$. The last bin includes the overflow. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.

Comparison between data and prediction after the fit to data in the signal region for the lepton $\eta$. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.

Comparison between data and prediction after the fit to data in the signal region for the ${E}_{T}^{miss}$. The last bin includes the overflow. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.

Comparison between data and prediction after the fit to data in the signal region for the $m_{T}^{W}$. The last bin includes the overflow. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.

Nuisance parameters ranked according to their post-fit impacts on the best-fit value of the ratio $\mu$ of the measured cross-section to the predicted cross-section. In the figure, only the 20 nuisance parameters with the largest post-fit impacts are shown. The empty (solid) blue rectangles illustrate the pre-fit (post-fit) impact on $\mu$, corresponding to the upper axis. The pre-fit (post-fit) impact of each nuisance parameter, $\Delta\mu$, is calculated as the difference in the fitted value of $\mu$ between the nominal fit and the fit when fixing the corresponding nuisance parameter to $\hat{\theta}\pm\Delta\theta$ ($\hat{\theta}\pm\Delta\hat{\theta}$), where $\hat{\theta}$ is the best-fit value of the nuisance parameter and $\Delta\theta$ ($\Delta\hat{\theta}$) is its pre-fit (post-fit) uncertainty. Several systematic uncertainties are split into different nuisance parameters, which are indicated by NP. JES (JER) indicates jet energy scale (resolution), and $\gamma$ indicates a nuisance parameter associated to the MC statistics in one of the 18 bins numbered from 0 to 17. The black points show the best-fit values of the nuisance parameters, with the error bars representing the post-fit uncertainties. Each nuisance parameter is shown wrt. its nominal value, $\theta_0$, and in units of its pre-fit uncertainty, except the free-floating normalisation factors of the $t\bar{t}$ and $W$+jets backgrounds, and the parameters associated to the MC statistics in each bin, for which the post-fit values and uncertainties are shown.

Correlation matrix of the nuisance parameters and of the ratio $\mu$ of the measured cross-section to the predicted cross-section. The correlations are given after the fit to data. In the figure, only the parameters which have a correlation of at least 0.2 with any other parameter are shown.

Distribution of the MEM discriminant $P(S|X)$ in the SR for MEM discriminant values larger than $2.0\times10^{-4}$, for the collision data used for the measurement, and for 1000 pseudo-data replicas, generated using a bootstrapping technique, in order to assess the statistical correlations between this measurement and others, for the purpose of combinations. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the <a href="https://zenodo.org/record/5361038">BootstrapGenerator</a> software package , which implements a technique described in <a href="https://cds.cern.ch/record/2759945/">ATL-PHYS-PUB-2021-011</a>. The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. Each pseudo-data replica is assigned an index, ranging from 0 to 999, corresponding to the random number index used consistently for each observed data event.

Measured values of the signal cross-section and of the $t\bar{t}$ and $W$+jets normalisation factors, obtained by statistical-only fits to the collision data used for the measurement, and to 1000 pseudo-data replicas, generated using a bootstrapping technique, in order to assess the statistical correlations between this measurement and others, for the purpose of combinations. The central values and their statistical uncertainties are obtained by repeating the fit after having fixed all nuisance parameters, except the $t\bar{t}$ and $W$+jets normalisation factors, which are let free-floating (unlike for the statistical uncertainty on the cross-section quoted in the paper). The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the <a href="https://zenodo.org/record/5361038">BootstrapGenerator</a> software package , which implements a technique described in <a href="https://cds.cern.ch/record/2759945/">ATL-PHYS-PUB-2021-011</a>. The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. Each pseudo-data replica is assigned an index, ranging from 0 to 999, corresponding to the random number index used consistently for each observed data event.

$p_\mathrm{T}$-differential production yield of prompt $\mathrm{D_s^+}$ mesons in the 30-50% centrality class in Pb-Pb collisions at $\sqrt{{s_\mathrm{NN}}}=5.02~\mathrm{{TeV}}$ in the rapidity interval $|y|<0.5$. Branching ratio of $\mathrm{D_s^+\to \phi\pi^+\to K^-K^+\pi^+}$: 0.0224

$p_\mathrm{T}$-differential nuclear modification factor $R_\mathrm{AA}$ of prompt $\mathrm{D_s^+}$ mesons in the 0-10% centrality class in Pb-Pb collisions at $\sqrt{{s_\mathrm{NN}}}=5.02~\mathrm{{TeV}}$ in the rapidity interval $|y|<0.5$.

$p_\mathrm{T}$-differential nuclear modification factor $R_\mathrm{AA}$ of prompt $\mathrm{D_s^+}$ mesons in the 0-10% centrality class in Pb-Pb collisions at $\sqrt{{s_\mathrm{NN}}}=5.02~\mathrm{{TeV}}$ in the rapidity interval $|y|<0.5$.

$p_\mathrm{T}$-differential nuclear modification factor $R_\mathrm{AA}$ of prompt $\mathrm{D_s^+}$ mesons in the 30-50% centrality class in Pb-Pb collisions at $\sqrt{{s_\mathrm{NN}}}=5.02~\mathrm{{TeV}}$ in the rapidity interval $|y|<0.5$.

$p_\mathrm{T}$-differential nuclear modification factor $R_\mathrm{AA}$ of prompt $\mathrm{D_s^+}$ mesons in the 30-50% centrality class in Pb-Pb collisions at $\sqrt{{s_\mathrm{NN}}}=5.02~\mathrm{{TeV}}$ in the rapidity interval $|y|<0.5$.

$p_\mathrm{{T}}$-differential production ratios of prompt $\mathrm{D}_s^+/\mathrm{D}^0$ mesons in the 0-10% centrality class in Pb-Pb collisions at $\sqrt{{s_\mathrm{NN}}}=5.02~\mathrm{{TeV}}$ in the rapidity interval $|y|<0.5$. Branching ratio of $\mathrm{D_s^+\to \phi\pi^+\to K^-K^+\pi^+}$: 0.0224 Branching ratio of $\mathrm{D^0 \to K^-\pi^+}$: 0.0395

$p_\mathrm{{T}}$-differential production ratios of prompt $\mathrm{D}_s^+/\mathrm{D}^0$ mesons in the 0-10% centrality class in Pb-Pb collisions at $\sqrt{{s_\mathrm{NN}}}=5.02~\mathrm{{TeV}}$ in the rapidity interval $|y|<0.5$. Branching ratio of $\mathrm{D_s^+\to \phi\pi^+\to K^-K^+\pi^+}$: 0.0224 Branching ratio of $\mathrm{D^0 \to K^-\pi^+}$: 0.0395

$p_\mathrm{{T}}$-differential production ratios of prompt $\mathrm{D}_s^+/\mathrm{D}^0$ mesons in the 30-50% centrality class in Pb-Pb collisions at $\sqrt{{s_\mathrm{NN}}}=5.02~\mathrm{{TeV}}$ in the rapidity interval $|y|<0.5$. Branching ratio of $\mathrm{D_s^+\to \phi\pi^+\to K^-K^+\pi^+}$: 0.0224 Branching ratio of $\mathrm{D^0 \to K^-\pi^+}$: 0.0395

$p_\mathrm{{T}}$-differential production ratios of prompt $\mathrm{D}_s^+/\mathrm{D}^0$ mesons in the 30-50% centrality class in Pb-Pb collisions at $\sqrt{{s_\mathrm{NN}}}=5.02~\mathrm{{TeV}}$ in the rapidity interval $|y|<0.5$. Branching ratio of $\mathrm{D_s^+\to \phi\pi^+\to K^-K^+\pi^+}$: 0.0224 Branching ratio of $\mathrm{D^0 \to K^-\pi^+}$: 0.0395

$p_\mathrm{{T}}$-differential prompt $\mathrm{D}_s^+/\mathrm{D}^0$ ratios in Pb-Pb collisions in the 0-10% centrality class at $\sqrt{s_\mathrm{NN}}=5.02~\mathrm{TeV}$ divided by those in pp collisions at the same energy.

$p_\mathrm{{T}}$-differential prompt $\mathrm{D}_s^+/\mathrm{D}^0$ ratios in Pb-Pb collisions in the 0-10% centrality class at $\sqrt{s_\mathrm{NN}}=5.02~\mathrm{TeV}$ divided by those in pp collisions at the same energy.

$p_\mathrm{{T}}$-differential prompt $\mathrm{D}_s^+/\mathrm{D}^0$ ratios in Pb-Pb collisions in the 30-50% centrality class at $\sqrt{s_\mathrm{NN}}=5.02~\mathrm{TeV}$ divided by those in pp collisions at the same energy.

$p_\mathrm{{T}}$-differential prompt $\mathrm{D}_s^+/\mathrm{D}^0$ ratios in Pb-Pb collisions in the 30-50% centrality class at $\sqrt{s_\mathrm{NN}}=5.02~\mathrm{TeV}$ divided by those in pp collisions at the same energy.

$p_\mathrm{T}$-differential elliptic flow coefficient $v_2$ of prompt $\mathrm{D_s^+}$ mesons in the 30-50% centrality class in Pb-Pb collisions at $\sqrt{{s_\mathrm{NN}}}=5.02~\mathrm{{TeV}}$.

$p_\mathrm{T}$-differential elliptic flow coefficient $v_2$ of prompt $\mathrm{D_s^+}$ mesons in the 30-50% centrality class in Pb-Pb collisions at $\sqrt{{s_\mathrm{NN}}}=5.02~\mathrm{{TeV}}$.

$p_{T}$-distributions of pions ($\pi^{+}+\pi^{-}$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 5-10%.

$p_{T}$-distributions of kaons ($K^{+}+K^{-}$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 5-10%.

$p_{T}$-distributions of protons ($p+pbar$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 5-10%.

$p_{T}$-distributions of pions ($\pi^{+}+\pi^{-}$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 10-20%.

$p_{T}$-distributions of kaons ($K^{+}+K^{-}$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 10-20%.

$p_{T}$-distributions of protons ($p+pbar$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 10-20%.

$p_{T}$-distributions of pions ($\pi^{+}+\pi^{-}$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 20-30%.

$p_{T}$-distributions of kaons ($K^{+}+K^{-}$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 20-30%.

$p_{T}$-distributions of protons ($p+pbar$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 20-30%.

$p_{T}$-distributions of pions ($\pi^{+}+\pi^{-}$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 30-40%.

$p_{T}$-distributions of kaons ($K^{+}+K^{-}$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 30-40%.

$p_{T}$-distributions of protons ($p+pbar$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 30-40%.

$p_{T}$-distributions of pions ($\pi^{+}+\pi^{-}$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 40-50%.

$p_{T}$-distributions of kaons ($K^{+}+K^{-}$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 40-50%.

$p_{T}$-distributions of protons ($p+pbar$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 40-50%.

$p_{T}$-distributions of pions ($\pi^{+}+\pi^{-}$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 50-60%.

$p_{T}$-distributions of kaons ($K^{+}+K^{-}$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 50-60%.

$p_{T}$-distributions of protons ($p+pbar$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 50-60%.

$p_{T}$-distributions of pions ($\pi^{+}+\pi^{-}$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 60-70%.

$p_{T}$-distributions of kaons ($K^{+}+K^{-}$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 60-70%.

$p_{T}$-distributions of protons ($p+pbar$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 60-70%.

$p_{T}$-distributions of pions ($\pi^{+}+\pi^{-}$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 70-90%.

$p_{T}$-distributions of kaons ($K^{+}+K^{-}$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 70-90%.

$p_{T}$-distributions of protons ($p+pbar$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 70-90%.

$p_{T}$-distributions of phi ($\phi$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 0-10%.

$p_{T}$-distributions of phi ($\phi$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 10-30%.

$p_{T}$-distributions of phi ($\phi$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 30-50%.

$p_{T}$-distributions of phi ($\phi$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 50-70%.

$p_{T}$-distributions of phi ($\phi$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 70-90%.

$p_{T}$-distributions of kaons ($K^{+}+K^{-}$)/pions ($\pi^{+}+\pi^{-}$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 0-5%.

$p_{T}$-distributions of protons ($p+pbar$)/pions ($\pi^{+}+\pi^{-}$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 0-5%.

$p_{T}$-distributions of kaons ($K^{+}+K^{-}$)/pions ($\pi^{+}+\pi^{-}$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 5-10%.

$p_{T}$-distributions of protons ($p+pbar$)/pions ($\pi^{+}+\pi^{-}$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 5-10%.

$p_{T}$-distributions of kaons ($K^{+}+K^{-}$)/pions ($\pi^{+}+\pi^{-}$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 10-20%.

$p_{T}$-distributions of protons ($p+pbar$)/pions ($\pi^{+}+\pi^{-}$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 10-20%.

$p_{T}$-distributions of kaons ($K^{+}+K^{-}$)/pions ($\pi^{+}+\pi^{-}$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 20-30%.

$p_{T}$-distributions of protons ($p+pbar$)/pions ($\pi^{+}+\pi^{-}$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 20-30%.

$p_{T}$-distributions of kaons ($K^{+}+K^{-}$)/pions ($\pi^{+}+\pi^{-}$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 30-40%.

$p_{T}$-distributions of protons ($p+pbar$)/pions ($\pi^{+}+\pi^{-}$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 30-40%.

$p_{T}$-distributions of kaons ($K^{+}+K^{-}$)/pions ($\pi^{+}+\pi^{-}$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 40-50%.

$p_{T}$-distributions of protons ($p+pbar$)/pions ($\pi^{+}+\pi^{-}$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 40-50%.

$p_{T}$-distributions of kaons ($K^{+}+K^{-}$)/pions ($\pi^{+}+\pi^{-}$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 50-60%.

$p_{T}$-distributions of protons ($p+pbar$)/pions ($\pi^{+}+\pi^{-}$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 50-60%.

$p_{T}$-distributions of kaons ($K^{+}+K^{-}$)/pions ($\pi^{+}+\pi^{-}$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 60-70%.

$p_{T}$-distributions of protons ($p+pbar$)/pions ($\pi^{+}+\pi^{-}$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 60-70%.

$p_{T}$-distributions of kaons ($K^{+}+K^{-}$)/pions ($\pi^{+}+\pi^{-}$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 70-90%.

$p_{T}$-distributions of protons ($p+pbar$)/pions ($\pi^{+}+\pi^{-}$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 70-90%.

$p_{T}$-distributions of phi ($\phi$)/protons ($p+pbar$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 0-10%.

$p_{T}$-distributions of phi ($\phi$)/protons ($p+pbar$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 10-30%.

$p_{T}$-distributions of phi ($\phi$)/protons ($p+pbar$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 30-50%.

$p_{T}$-distributions of phi ($\phi$)/protons ($p+pbar$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 50-70%.

$p_{T}$-distributions of phi ($\phi$)/protons ($p+pbar$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV. Centrality class 70-90%.

Integrated yield ratios of kaons ($K^{+}+K^{-}$) to pions ($\pi^{+}+\pi^{-}$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV.

Integrated yield ratios of protons ($p+pbar$) to pions ($\pi^{+}+\pi^{-}$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV.

Integrated yield ratios of phi ($\phi$) to pions ($\pi^{+}+\pi^{-}$) measured in Xe-Xe collisions at $\sqrt{s_{NN}}$ = 5.44 TeV.

The $p_T ^{miss}$ distributions for muon channel comparing the data and background model with systematic uncertainty.

The $m_T$ distributions for electron channel comparing the data and background model with systematic uncertainty, after fitting the background-only model to the data.

The $m_T$ distributions for muon channel comparing the data and background model with systematic uncertainty, after fitting the background-only model to the data.

Expected and observed limits on the product of cross section and branching fraction of a new spin-2 heavy resonance X$\rightarrow$ZZ, assuming zero width, based on the combined analysis of the electron and muon channels.

Expected and observed limits on the product of cross section and branching fraction of a new spin-2 heavy resonance X$\rightarrow$ZZ, assuming zero width, based on the combined analysis of the electron channels.

Expected and observed limits on the product of cross section and branching fraction of a new spin-2 heavy resonance X$\rightarrow$ZZ, assuming zero width, based on the combined analysis of the muon channels.

Expected and observed limits on the product of cross section and branching fraction of a new spin-2 heavy resonance X$\rightarrow$ZZ based on a combined analysis of the electron and muon channels. The more generic version of the bulk graviton model takes 0/10%/20%/30% mass width of the resonance into consideration, assuming gluon-gluon fusion production.

Expected and observed limits on the product of cross section and branching fraction of a new spin-2 heavy resonance X$\rightarrow$ZZ based on a combined analysis of the electron and muon channels. The more generic version of the bulk graviton model takes 0/10%/20%/30% mass width of the resonance into consideration, assuming qq annihilation production.

Expected and observed 95% CL cross section exclusion contours for top squark pair production in the plane of top squark lifetime ($c\tau$) and top squark mass. These limits assume a branching fraction of 100\% through the RPV vertex $\tilde{t}$ $\to$ b l, where the branching fraction to any lepton flavor is equal to 1/3. As indicated in the plot, the region to the left of the contours is excluded by this search.

Electron reconstruction efficiency as function of its tranverse impact parameter, $d_0$.

Muon reconstruction efficiency as function of its tranverse impact parameter, $d_0$.

Electron selection efficiency as function of its tranverse momentum, $p_T$.

Muon selection efficiency as function of its tranverse momentum, $p_T$.

D(z) distribution for R=0.4 jets.

D(z) distribution for R=0.4 jets.

D(z) distribution for R=0.4 jets.

D(z) distribution for R=0.4 jets.

D(z) distribution for R=0.4 jets.

D(z) distribution for R=0.4 jets.

D(z) distribution for R=0.3 jets.

D(z) distribution for R=0.3 jets.

D(z) distribution for R=0.3 jets.

D(z) distribution for R=0.3 jets.

D(z) distribution for R=0.3 jets.

D(z) distribution for R=0.3 jets.

D(z) distribution for R=0.3 jets.

D(z) distribution for R=0.2 jets.

D(z) distribution for R=0.2 jets.

D(z) distribution for R=0.2 jets.

D(z) distribution for R=0.2 jets.

D(z) distribution for R=0.2 jets.

D(z) distribution for R=0.2 jets.

D(z) distribution for R=0.2 jets.

D(pt) distribution for R=0.4 jets.

D(pt) distribution for R=0.4 jets.

D(pt) distribution for R=0.4 jets.

D(pt) distribution for R=0.4 jets.

D(pt) distribution for R=0.4 jets.

D(pt) distribution for R=0.4 jets.

D(pt) distribution for R=0.4 jets.

D(pt) distribution for R=0.3 jets.

D(pt) distribution for R=0.3 jets.

D(pt) distribution for R=0.3 jets.

D(pt) distribution for R=0.3 jets.

D(pt) distribution for R=0.3 jets.

D(pt) distribution for R=0.3 jets.

D(pt) distribution for R=0.3 jets.

D(pt) distribution for R=0.2 jets.

D(pt) distribution for R=0.2 jets.

D(pt) distribution for R=0.2 jets.

D(pt) distribution for R=0.2 jets.

D(pt) distribution for R=0.2 jets.

D(pt) distribution for R=0.2 jets.

D(pt) distribution for R=0.2 jets.

Ratio of D(z) distributions for R=0.4 jets for central to peripheral events.

Ratio of D(z) distributions for R=0.4 jets for central to peripheral events.

Ratio of D(z) distributions for R=0.4 jets for central to peripheral events.

Ratio of D(z) distributions for R=0.4 jets for central to peripheral events.

Ratio of D(z) distributions for R=0.4 jets for central to peripheral events.

Ratio of D(z) distributions for R=0.4 jets for central to peripheral events.

Ratio of D(z) distributions for R=0.3 jets for central to peripheral events.

Ratio of D(z) distributions for R=0.3 jets for central to peripheral events.

Ratio of D(z) distributions for R=0.3 jets for central to peripheral events.

Ratio of D(z) distributions for R=0.3 jets for central to peripheral events.

Ratio of D(z) distributions for R=0.3 jets for central to peripheral events.

Ratio of D(z) distributions for R=0.3 jets for central to peripheral events.

Ratio of D(z) distributions for R=0.2 jets for central to peripheral events.

Ratio of D(z) distributions for R=0.2 jets for central to peripheral events.

Ratio of D(z) distributions for R=0.2 jets for central to peripheral events.

Ratio of D(z) distributions for R=0.2 jets for central to peripheral events.

Ratio of D(z) distributions for R=0.2 jets for central to peripheral events.

Ratio of D(z) distributions for R=0.2 jets for central to peripheral events.

Ratio of D(pt) distributions for R=0.4 jets for central to peripheral events.

Ratio of D(pt) distributions for R=0.4 jets for central to peripheral events.

Ratio of D(pt) distributions for R=0.4 jets for central to peripheral events.

Ratio of D(pt) distributions for R=0.4 jets for central to peripheral events.

Ratio of D(pt) distributions for R=0.4 jets for central to peripheral events.

Ratio of D(pt) distributions for R=0.4 jets for central to peripheral events.

Ratio of D(pt) distributions for R=0.3 jets for central to peripheral events.

Ratio of D(pt) distributions for R=0.3 jets for central to peripheral events.

Ratio of D(pt) distributions for R=0.3 jets for central to peripheral events.

Ratio of D(pt) distributions for R=0.3 jets for central to peripheral events.

Ratio of D(pt) distributions for R=0.3 jets for central to peripheral events.

Ratio of D(pt) distributions for R=0.3 jets for central to peripheral events.

Ratio of D(pt) distributions for R=0.2 jets for central to peripheral events.

Ratio of D(pt) distributions for R=0.2 jets for central to peripheral events.

Ratio of D(pt) distributions for R=0.2 jets for central to peripheral events.

Ratio of D(pt) distributions for R=0.2 jets for central to peripheral events.

Ratio of D(pt) distributions for R=0.2 jets for central to peripheral events.

Ratio of D(pt) distributions for R=0.2 jets for central to peripheral events.

The b-jet yield as a function of pT is for the 30-50% centrality class of PbPb collisions. The yields are scaled by the equivalent number of minimum bias events sampled and by TAA.

The b-jet yield as a function of pT is for the 50-100% centrality class of PbPb collisions. The yields are scaled by the equivalent number of minimum bias events sampled and by TAA.

The b-jet cross section as a function of pT in pp collisions.

The b-jet nuclear modification factor as a function of the pT for the centrality class 0-100%.

The b-jet nuclear modification factor as a function of centrality for 80 < jet pT < 90 GeV/c.

The b-jet nuclear modification factor as a function centrality for 80 < jet pT < 90 GeV/c.

The b-jet nuclear modification factor as a function of the pT for the centrality class 0-10%.

The b-jet nuclear modification factor as a function of the pT for the centrality class 10-30%.

The b-jet nuclear modification factor as a function of the pT for the centrality class 30-50%.

The b-jet nuclear modification factor as a function of the pT for the centrality class 50-100%.

Kinematic distributions of single l + > 5-jet events in data (points), compared to MC simulation normalized to the number of events observed in data. Shown are pT spectra for muons (a) and electrons (b), and jet spectra for the channels $\mu$+jets (c) and e+jets (d). The reconstructed mtg distribution is shown for the $\mu$+jets channel in (e) and for e+jets in (f).

Kinematic distributions of single l + > 5-jet events in data (points), compared to MC simulation normalized to the number of events observed in data. Shown are pT spectra for muons (a) and electrons (b), and jet spectra for the channels $\mu$+jets (c) and e+jets (d). The reconstructed mtg distribution is shown for the $\mu$+jets channel in (e) and for e+jets in (f).

Kinematic distributions of single l + > 5-jet events in data (points), compared to MC simulation normalized to the number of events observed in data. Shown are pT spectra for muons (a) and electrons (b), and jet spectra for the channels $\mu$+jets (c) and e+jets (d). The reconstructed mtg distribution is shown for the $\mu$+jets channel in (e) and for e+jets in (f).

Reconstructed mass spectrum for the $tg$ system in data (points), along with a fit of the background $f(m)$ to the data in the $\mu$+jets channel (a) and $e$+jets channel (b). The reconstructed masses correspond to the results of kinematic fits for the jet-quark assignments that provide the best match to the $t^{*}\bar{t}^{*}$ hypothesis. Also shown are the expectations of $t^*$ signals for $m_{t^*}=750$ and 850 GeV normalized to the integrated luminosity of the data. Information about the fit: F = 501885/(1+exp((x+251.828)/112.311)) where x = $M_{tg}$.

Reconstructed mass spectrum for the $tg$ system in data (points), along with a fit of the background $f(m)$ to the data in the $\mu$+jets channel (a) and $e$+jets channel (b). The reconstructed masses correspond to the results of kinematic fits for the jet-quark assignments that provide the best match to the $t^{*}\bar{t}^{*}$ hypothesis. Also shown are the expectations of $t^*$ signals for $m_{t^*}=750$ and 850 GeV normalized to the integrated luminosity of the data. Information about the fit: F = 62101.5/(1+exp((x+6.58811)/107.886)) where x = $M_{tg}$.

The observed (solid line) and expected (dashed line) 95%CL upper limits for the product of the inclusive $t^{*}\bar{t}^{*}$ production cross section and the branching fraction $B(t^{*}{\rightarrow}tg)$, as a function of the $t^{*}$ mass, for the combined lepton data. The ranges for ${\pm}1$ and ${\pm}2$ standard deviations for the expected limits are shown by the bands.

Mean $p_T$, leading in-jet charged particle.

Mean $p_T$, charged particle jets, $p^{ch.jet}_T > 5$ GeV, $|\eta^{ch.jet}| < 1.9$.

Charged jet rate, $p^\text{ch.jet}_T > 5$ GeV, $|\eta^{ch.jet}| < 1.9$.

Charged jet rate, $p^\text{ch.jet}_T > 30$ GeV, $|\eta^{ch.jet}| < 1.9$.

Jet $p_T$ spectrum, $|\eta^{ch.jet}| < 1.9$, $10 < N_\text{ch} \le 30$.

Jet $p_T$ spectrum, $|\eta^{ch.jet}| < 1.9$, $30 < N_\text{ch} \le 50$.

Jet $p_T$ spectrum, $|\eta^{ch.jet}| < 1.9$, $50 < N_\text{ch} \le 80$.

Jet $p_T$ spectrum, $|\eta^{ch.jet}| < 1.9$, $80 < N_\text{ch} \le 110$.

Jet $p_T$ spectrum, $|\eta^{ch.jet}| < 1.9$, $110 < N_\text{ch} \le 140$.

Intrajet ring $p_{T}$ density, $10 < N_\text{ch} \le 30$.

Intrajet ring $p_{T}$ density, $30 < N_\text{ch} \le 50$.

Intrajet ring $p_{T}$ density, $50 < N_\text{ch} \le 80$.

Intrajet ring $p_{T}$ density, $80 < N_\text{ch} \le 110$.

Intrajet ring $p_{T}$ density, $110 < N_\text{ch} \le 140$.

Observed CLs contour with plus 1-sigma signal cross-section uncertainty in the ( M(CHARGINO), TAU(CHARGINO) ) space for tan(beta) = 5 and mu > 0.

Expected CLs contour in the ( M(CHARGINO), TAU(CHARGINO) ) space for tan(beta) = 5 and mu > 0.

Expected CLs contour with minus 1-sigma experimental uncertainty in the ( M(CHARGINO), TAU(CHARGINO) ) space for tan(beta) = 5 and mu > 0.

Expected CLs contour with plus 1-sigma experimental uncertainty in the ( M(CHARGINO), TAU(CHARGINO) ) space for tan(beta) = 5 and mu > 0.

Observed CLs contour in the ( M(CHARGINO), M(CHARGINO)-M(NEUTRALINO) ) space of the AMSB model for tan(beta) = 5 and mu > 0.

Observed CLs contour with minus 1-sigma signal cross-section uncertainty in the ( M(CHARGINO), M(CHARGINO)-M(NEUTRALINO) ) space of the AMSB model for tan(beta) = 5 and mu > 0.

Observed CLs contour with plus 1-sigma signal cross-section uncertainty in the ( M(CHARGINO), M(CHARGINO)-M(NEUTRALINO) ) space of the AMSB model for tan(beta) = 5 and mu > 0.

Expected CLs contour in the ( M(CHARGINO), M(CHARGINO)-M(NEUTRALINO) ) space of the AMSB model for tan(beta) = 5 and mu > 0.

Expected CLs contour with minus 1-sigma experimental uncertainty in the ( M(CHARGINO), M(CHARGINO)-M(NEUTRALINO) ) space of the AMSB model for tan(beta) = 5 and mu > 0.

Expected CLs contour with plus 1-sigma experimental uncertainty in the ( M(CHARGINO), M(CHARGINO)-M(NEUTRALINO) ) space of the AMSB model for tan(beta) = 5 and mu > 0.