The energy-energy correlator distributions constructed with charged particles with $p_{\mathrm{T}} > 1$ GeV for energy weight $n=1$ and jet $p_{\mathrm{T}}$ selection $180 < p_{\mathrm{T,jet}} < 200$ GeV. The results are shown for different centrality bins in PbPb collisions and for pp collisions.

The energy-energy correlator distributions constructed with charged particles with $p_{\mathrm{T}} > 1$ GeV for energy weight $n=2$ and jet $p_{\mathrm{T}}$ selection $120 < p_{\mathrm{T,jet}} < 140$ GeV. The results are shown for different centrality bins in PbPb collisions and for pp collisions.

The energy-energy correlator distributions constructed with charged particles with $p_{\mathrm{T}} > 1$ GeV for energy weight $n=2$ and jet $p_{\mathrm{T}}$ selection $140 < p_{\mathrm{T,jet}} < 160$ GeV. The results are shown for different centrality bins in PbPb collisions and for pp collisions.

The energy-energy correlator distributions constructed with charged particles with $p_{\mathrm{T}} > 1$ GeV for energy weight $n=2$ and jet $p_{\mathrm{T}}$ selection $160 < p_{\mathrm{T,jet}} < 180$ GeV. The results are shown for different centrality bins in PbPb collisions and for pp collisions.

The energy-energy correlator distributions constructed with charged particles with $p_{\mathrm{T}} > 1$ GeV for energy weight $n=2$ and jet $p_{\mathrm{T}}$ selection $180 < p_{\mathrm{T,jet}} < 200$ GeV. The results are shown for different centrality bins in PbPb collisions and for pp collisions.

The energy-energy correlator distributions constructed with charged particles with $p_{\mathrm{T}} > 2$ GeV for energy weight $n=1$ and jet $p_{\mathrm{T}}$ selection $120 < p_{\mathrm{T,jet}} < 140$ GeV. The results are shown for different centrality bins in PbPb collisions and for pp collisions.

The energy-energy correlator distributions constructed with charged particles with $p_{\mathrm{T}} > 2$ GeV for energy weight $n=1$ and jet $p_{\mathrm{T}}$ selection $140 < p_{\mathrm{T,jet}} < 160$ GeV. The results are shown for different centrality bins in PbPb collisions and for pp collisions.

The energy-energy correlator distributions constructed with charged particles with $p_{\mathrm{T}} > 2$ GeV for energy weight $n=1$ and jet $p_{\mathrm{T}}$ selection $160 < p_{\mathrm{T,jet}} < 180$ GeV. The results are shown for different centrality bins in PbPb collisions and for pp collisions.

The energy-energy correlator distributions constructed with charged particles with $p_{\mathrm{T}} > 2$ GeV for energy weight $n=1$ and jet $p_{\mathrm{T}}$ selection $180 < p_{\mathrm{T,jet}} < 200$ GeV. The results are shown for different centrality bins in PbPb collisions and for pp collisions.

The energy-energy correlator distributions constructed with charged particles with $p_{\mathrm{T}} > 2$ GeV for energy weight $n=2$ and jet $p_{\mathrm{T}}$ selection $120 < p_{\mathrm{T,jet}} < 140$ GeV. The results are shown for different centrality bins in PbPb collisions and for pp collisions.

The energy-energy correlator distributions constructed with charged particles with $p_{\mathrm{T}} > 2$ GeV for energy weight $n=2$ and jet $p_{\mathrm{T}}$ selection $140 < p_{\mathrm{T,jet}} < 160$ GeV. The results are shown for different centrality bins in PbPb collisions and for pp collisions.

The energy-energy correlator distributions constructed with charged particles with $p_{\mathrm{T}} > 2$ GeV for energy weight $n=2$ and jet $p_{\mathrm{T}}$ selection $160 < p_{\mathrm{T,jet}} < 180$ GeV. The results are shown for different centrality bins in PbPb collisions and for pp collisions.

The energy-energy correlator distributions constructed with charged particles with $p_{\mathrm{T}} > 2$ GeV for energy weight $n=2$ and jet $p_{\mathrm{T}}$ selection $180 < p_{\mathrm{T,jet}} < 200$ GeV. The results are shown for different centrality bins in PbPb collisions and for pp collisions.

The energy-energy correlator PbPb/pp ratios constructed with charged particles with $p_{\mathrm{T}} > 1$ GeV for energy weight $n=1$ and jet $p_{\mathrm{T}}$ selection $120 < p_{\mathrm{T,jet}} < 140$ GeV. The results are shown for different centrality bins in PbPb collisions.

The energy-energy correlator PbPb/pp ratios constructed with charged particles with $p_{\mathrm{T}} > 1$ GeV for energy weight $n=1$ and jet $p_{\mathrm{T}}$ selection $140 < p_{\mathrm{T,jet}} < 160$ GeV. The results are shown for different centrality bins in PbPb collisions.

The energy-energy correlator PbPb/pp ratios constructed with charged particles with $p_{\mathrm{T}} > 1$ GeV for energy weight $n=1$ and jet $p_{\mathrm{T}}$ selection $160 < p_{\mathrm{T,jet}} < 180$ GeV. The results are shown for different centrality bins in PbPb collisions.

The energy-energy correlator PbPb/pp ratios constructed with charged particles with $p_{\mathrm{T}} > 1$ GeV for energy weight $n=1$ and jet $p_{\mathrm{T}}$ selection $180 < p_{\mathrm{T,jet}} < 200$ GeV. The results are shown for different centrality bins in PbPb collisions.

The energy-energy correlator PbPb/pp ratios constructed with charged particles with $p_{\mathrm{T}} > 1$ GeV for energy weight $n=2$ and jet $p_{\mathrm{T}}$ selection $120 < p_{\mathrm{T,jet}} < 140$ GeV. The results are shown for different centrality bins in PbPb collisions.

The energy-energy correlator PbPb/pp ratios constructed with charged particles with $p_{\mathrm{T}} > 1$ GeV for energy weight $n=2$ and jet $p_{\mathrm{T}}$ selection $140 < p_{\mathrm{T,jet}} < 160$ GeV. The results are shown for different centrality bins in PbPb collisions.

The energy-energy correlator PbPb/pp ratios constructed with charged particles with $p_{\mathrm{T}} > 1$ GeV for energy weight $n=2$ and jet $p_{\mathrm{T}}$ selection $160 < p_{\mathrm{T,jet}} < 180$ GeV. The results are shown for different centrality bins in PbPb collisions.

The energy-energy correlator PbPb/pp ratios constructed with charged particles with $p_{\mathrm{T}} > 1$ GeV for energy weight $n=2$ and jet $p_{\mathrm{T}}$ selection $180 < p_{\mathrm{T,jet}} < 200$ GeV. The results are shown for different centrality bins in PbPb collisions.

The energy-energy correlator PbPb/pp ratios constructed with charged particles with $p_{\mathrm{T}} > 2$ GeV for energy weight $n=1$ and jet $p_{\mathrm{T}}$ selection $120 < p_{\mathrm{T,jet}} < 140$ GeV. The results are shown for different centrality bins in PbPb collisions.

The energy-energy correlator PbPb/pp ratios constructed with charged particles with $p_{\mathrm{T}} > 2$ GeV for energy weight $n=1$ and jet $p_{\mathrm{T}}$ selection $140 < p_{\mathrm{T,jet}} < 160$ GeV. The results are shown for different centrality bins in PbPb collisions.

The energy-energy correlator PbPb/pp ratios constructed with charged particles with $p_{\mathrm{T}} > 2$ GeV for energy weight $n=1$ and jet $p_{\mathrm{T}}$ selection $160 < p_{\mathrm{T,jet}} < 180$ GeV. The results are shown for different centrality bins in PbPb collisions.

The energy-energy correlator PbPb/pp ratios constructed with charged particles with $p_{\mathrm{T}} > 2$ GeV for energy weight $n=1$ and jet $p_{\mathrm{T}}$ selection $180 < p_{\mathrm{T,jet}} < 200$ GeV. The results are shown for different centrality bins in PbPb collisions.

The energy-energy correlator PbPb/pp ratios constructed with charged particles with $p_{\mathrm{T}} > 2$ GeV for energy weight $n=2$ and jet $p_{\mathrm{T}}$ selection $120 < p_{\mathrm{T,jet}} < 140$ GeV. The results are shown for different centrality bins in PbPb collisions.

The energy-energy correlator PbPb/pp ratios constructed with charged particles with $p_{\mathrm{T}} > 2$ GeV for energy weight $n=2$ and jet $p_{\mathrm{T}}$ selection $140 < p_{\mathrm{T,jet}} < 160$ GeV. The results are shown for different centrality bins in PbPb collisions.

The energy-energy correlator PbPb/pp ratios constructed with charged particles with $p_{\mathrm{T}} > 2$ GeV for energy weight $n=2$ and jet $p_{\mathrm{T}}$ selection $160 < p_{\mathrm{T,jet}} < 180$ GeV. The results are shown for different centrality bins in PbPb collisions.

The energy-energy correlator PbPb/pp ratios constructed with charged particles with $p_{\mathrm{T}} > 2$ GeV for energy weight $n=2$ and jet $p_{\mathrm{T}}$ selection $180 < p_{\mathrm{T,jet}} < 200$ GeV. The results are shown for different centrality bins in PbPb collisions.

The double ratios of PbPb to pp single ratios with $p_{\mathrm{T}}^{\mathrm{ch}}$ > 2 GeV and $p_{\mathrm{T}}^{\mathrm{ch}}$ > 1 GeV.

The double ratios of PbPb to pp single ratios with $p_{\mathrm{T}}^{\mathrm{ch}}$ > 2 GeV and $p_{\mathrm{T}}^{\mathrm{ch}}$ > 1 GeV.

The double ratios of PbPb to pp single ratios with $p_{\mathrm{T}}^{\mathrm{ch}}$ > 2 GeV and $p_{\mathrm{T}}^{\mathrm{ch}}$ > 1 GeV.

The double ratios of PbPb to pp single ratios with $p_{\mathrm{T}}^{\mathrm{ch}}$ > 2 GeV and $p_{\mathrm{T}}^{\mathrm{ch}}$ > 1 GeV.

The double ratios of PbPb to pp single ratios with $p_{\mathrm{T}}^{\mathrm{ch}}$ > 2 GeV and $p_{\mathrm{T}}^{\mathrm{ch}}$ > 1 GeV.

The double ratios of PbPb to pp single ratios with $p_{\mathrm{T}}^{\mathrm{ch}}$ > 2 GeV and $p_{\mathrm{T}}^{\mathrm{ch}}$ > 1 GeV.

The double ratios of PbPb to pp single ratios with $p_{\mathrm{T}}^{\mathrm{ch}}$ > 2 GeV and $p_{\mathrm{T}}^{\mathrm{ch}}$ > 1 GeV.

The double ratios of PbPb to pp single ratios with $p_{\mathrm{T}}^{\mathrm{ch}}$ > 2 GeV and $p_{\mathrm{T}}^{\mathrm{ch}}$ > 1 GeV.

Comparison of the shapes extrapolated with a linear or quadratic extrapolation of the QCD contribution in the W+ signal region.

Comparison of the shapes extrapolated with a linear or quadratic extrapolation of the QCD contribution in the W- signal region.

Post-fit distributions of the transverse mass in the W+ signal region.

Post-fit distributions of the transverse mass in the W- signal region.

Post-fit distributions of the dimuon mass in the Z boson signal region.

Example plot for the extrapolation of the QCD contribution from a region with inverted relative isolation criterion to the W+ signal region in the transverse mass bin 12 < mT < 18 GeV. The values corresponding to the smallest relative muon isolation are extrapolated with a linear (smaller value) and quadratic (larger value) function.

Example plot for the extrapolation of the QCD contribution from a region with inverted relative isolation criterion to the W- signal region in the transverse mass bin 12 < mT < 18 GeV.The values corresponding to the smallest relative muon isolation are extrapolated with a linear (smaller value) and quadratic (larger value) function.

Example plot for the extrapolation of the QCD contribution from a region with inverted relative isolation criterion to the W+ signal region in the transverse mass bin 102 < mT < 108 GeV.The values corresponding to the smallest relative muon isolation are extrapolated with a linear (larger value) and quadratic (smaller value) function.

Example plot for the extrapolation of the QCD contribution from a region with inverted relative isolation criterion to the W- signal region in the transverse mass bin 102 < mT < 108 GeV.The values corresponding to the smallest relative muon isolation are extrapolated with a linear (smaller value) and quadratic (larger value) function.

The table compares theoretical and measured values of the product of the fiducial cross sections and branching fractions. The theoretical predictions are generated with DYTurbo in combination with three different PDF sets. All values are normalized to the corresponding measured value. The relative uncertainties on the measured values are given separately with and without the contribution from the luminosity uncertainty.

The table compares theoretical and measured values of the product of the total cross sections and branching fractions. The theoretical predictions are generated with DYTurbo in combination with three different PDF sets. All values are normalized to the corresponding measured value. The relative uncertainties on the measured values are given separately with and without the contribution from the luminosity uncertainty.

The table compares theoretical and measured ratios of the product of the fiducial cross sections and branching fractions. The theoretical predictions are generated with DYTurbo in combination with three different PDF sets. All values are normalized to the corresponding measured value.

The table compares theoretical and measured ratios of the product of the total cross sections and branching fractions. The theoretical predictions are generated with DYTurbo in combination with three different PDF sets. All values are normalized to the corresponding measured value.

Comparison of the measured and theoretical cross sections for Z, W+, W-, and W production at different center-of-mass energies. The theoretical predictions are generated with DYTurbo in combination with the NNPDF 3.1 PDF set.

The unfolded jet axis decorrelation distribution,$\frac{1}{N} \frac{dN}{d\Delta j}$, as a function of $\Delta j$ for the $0-10\%$, $10-30\%$, $30-50\%$, and $50-80\%$ centrality bins in the $230 < p_{\mathrm{T}} < 300$ GeV interval.

Breakdown of relative systematic uncertainties in the measured ${t\bar{t}}$ cross-section. The quoted uncertainties are obtained by repeating the fit with a group of nuisance parameters fixed to their fitted values and subtracting in quadrature the resulting total uncertainty from the uncertainty of the complete fit. However, the total uncertainty is not the quadratic sum of the grouped impacts, as this approach neglects the correlation among the different groups.

The figure shows the measurement of the top quark pair production cross-section, $\sigma_{t\bar{t}}$, in lead-lead (Pb+Pb) collisions at a center-of-mass energy of $\sqrt{s_{\mathrm{NN}}} = 5.02$ TeV, based on 1.9 nb$^{-1}$ of data.

Distributions for data and expected signal and background contributions of the MVA score for the µ + jets channel in the 3j1b category, before the maximum likelihood fit. The vertical error bars represent the statistical uncertainty in the data, and the shaded band the uncertainty in the prediction. All uncertainties considered in the analysis are included in the uncertainty band. The lower panels show the data-to-prediction ratio. The first and last bins in each distribution include underflow and overflow events, respectively.

Observed and predicted number of events in each of the eight categories of the signal region, before the maximum likelihood fit. The vertical error bars represent the statistical uncertainty in the data, and the shaded band the uncertainty in the prediction. All uncertainties considered in the analysis are included in the uncertainty band. The lower panels show the data-to-prediction ratio.

Distributions for the e + jets final state before the maximum likelihood fit, MVA score bins for the 3j1b category and ∆R med ( j, j 0 ) bins for the other categories. The vertical error bars represent the statistical uncertainty in the data, and the shaded band the uncertainty of the prediction. All uncertainties considered in the analysis are included in the uncertainty band. The lower panels show the data-to-simulation ratio, where the simulations are adjusted according to their normalization before the fit. The first and last bins in each distribution include underflow and overflow events, respectively.

Distributions for the e + jets final state after the maximum likelihood fit, MVA score bins for the 3j1b category and ∆R med ( j, j 0 ) bins for the other categories. The vertical error bars represent the statistical uncertainty in the data, and the shaded band the uncertainty of the prediction. All uncertainties considered in the analysis are included in the uncertainty band. The lower panels show the data-to-simulation ratio, where the simulations are adjusted according to their normalization after the fit. The first and last bins in each distribution include underflow and overflow events, respectively.

Distributions for the µ + jets final state before the maximum likelihood fit, MVA score bins for the 3j1b category and ∆R med ( j, j 0 ) bins for the other categories. The vertical error bars represent the statistical uncertainty in the data, and the shaded band the uncertainty of the prediction. All uncertainties considered in the analysis are included in the uncertainty band. The lower panels show the data-to-simulation ratio, where the simulations are adjusted according to their normalization before the fit. The first and last bins in each distribution include underflow and overflow events, respectively.

Distributions for the µ + jets final state after the maximum likelihood fit, MVA score bins for the 3j1b category and ∆R med ( j, j 0 ) bins for the other categories. The vertical error bars represent the statistical uncertainty in the data, and the shaded band the uncertainty of the prediction. All uncertainties considered in the analysis are included in the uncertainty band. The lower panels show the data-to-simulation ratio, where the simulations are adjusted according to their normalization after the fit. The first and last bins in each distribution include underflow and overflow events, respectively.

Covariance matrix for the lepton+jets ML fit.

Covariance matrix for the combination ML fit.

Data from Figure 1, panel c, $k_{2}$ vs $N_{ch}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Figure 1, panel c, $k_{2}$ vs $N_{ch}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Figure 1, panel d, $k_{3}$ vs $N_{ch}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Figure 1, panel d, $k_{3}$ vs $N_{ch}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Figure 2, panel a, $N_{ch}k_{2}$ vs $N_{ch}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Figure 2, panel a, $N_{ch}k_{2}$ vs $N_{ch}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Figure 2, panel b, $N^{2}_{ch}k_{3}$ vs $N_{ch}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Figure 2, panel b, $N^{2}_{ch}k_{3}$ vs $N_{ch}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Figure 2, panel c, $\Gamma$ vs $N_{ch}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Figure 2, panel c, $\Gamma$ vs $N_{ch}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Figure 3, panel a, $\left\langle[p_{T}]\right\rangle / \left\langle[p_{T}]\right\rangle^{5\%}$ vs $N_{ch}/N^{5\%}_{ch}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Figure 3, panel a, $\left\langle[p_{T}]\right\rangle / \left\langle[p_{T}]\right\rangle^{5\%}$ vs $N_{ch}/N^{5\%}_{ch}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Figure 3, panel b, $k_{2}/k^{5\%}_{2} vs N_{ch}/N^{5\%}_{ch}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Figure 3, panel b, $k_{2}/k^{5\%}_{2} vs N_{ch}/N^{5\%}_{ch}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Figure 3, panel c, $k_{3}/k^{5\%}_{3} vs N_{ch}/N^{5\%}_{ch}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Figure 3, panel c, $k_{3}/k^{5\%}_{3} vs N_{ch}/N^{5\%}_{ch}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Figure 3, panel d, $\Gamma/\Gamma^{5\%}$ vs $N_{ch}/N^{5\%}_{ch}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Figure 3, panel d, $\Gamma/\Gamma^{5\%}$ vs $N_{ch}/N^{5\%}_{ch}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Figure 4, $\Delta p_{T}/\left\langle[p_{T}]\right\rangle_{0-1\%}$ vs $\Delta N_{ch}/\left\langle N_{ch}\right\rangle_{0-1\%}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Figure 4, $\Delta p_{T}/\left\langle[p_{T}]\right\rangle_{0-1\%}$ vs $\Delta N_{ch}/\left\langle N_{ch}\right\rangle_{0-1\%}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Figure 4, $\Delta p_{T}/\left\langle[p_{T}]\right\rangle_{0-1\%}$ vs $\Delta N_{ch}/\left\langle N_{ch}\right\rangle_{0-1\%}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 2 GeV/c, $|\eta|< $ 2.5

Data from Figure 4, $\Delta p_{T}/\left\langle[p_{T}]\right\rangle_{0-1\%}$ vs $\Delta N_{ch}/\left\langle N_{ch}\right\rangle_{0-1\%}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 2 GeV/c, $|\eta|< $ 2.5

Data from Second Supplementary Figure, Fig 6, panel a, Correlation between FCal $\Sigma E_{T}$ and $N_{ch}$ in Pb+Pb collisions

Data from Second Supplementary Figure, Fig 6, panel b, Correlation between $[p_{T}]$ - $\left\langle[p_{T}]\right\rangle_{0-1\%}$ vs $\Delta N_{ch}$/$\left\langle N_{ch}\right\rangle_{0-1\%}$ in Pb+Pb collisions

Data from Third Supplementary Figure, Fig 7, Normalized Event distribution of $N_{ch}$ /$N^{5\%}_{ch}$ for Pb+Pb collisions

Data from Third Supplementary Figure, Fig 7, Normalized Event distribution of $N_{ch}$ / $N^{5\%}_{ch}$ for Xe+Xe collisions

Data from Fourth Supplementary Figure, Fig 8, panel a, $\gamma$ vs $N_{ch}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Fourth Supplementary Figure, Fig 8, panel a, $\gamma$ vs $N_{ch}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Fourth Supplementary Figure, Fig 8, panel b, $\gamma/\gamma^{5\%}$ vs $N_{ch}/N^{5\%}_{ch}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Fourth Supplementary Figure, Fig 8, panel b, $\gamma/\gamma^{5\%}$ vs $N_{ch}/N^{5\%}_{ch}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Auxiliary Fig 1 panel a, Correlation between FCal $\Sigma E_{T}$ and $N_{ch}$ in Xe+Xe collisions

Data from Auxiliary Fig 1 panel b, Correlation between $[p_{T}]$ - $\left\langle[p_{T}]\right\rangle_{0-1\%}$ vs $\Delta N_{ch}$/$\left\langle N_{ch}\right\rangle_{0-1\%}$ in Xe+Xe collisions

Data from Auxiliary Fig 2 panel b, $N_{ch}$ /$N^{5\%}_{ch}$ vs Centrality [\%] for Pb+Pb collisions

Data from Auxiliary Fig 2 panel b, $N_{ch}$ /$N^{5\%}_{ch}$ vs Centrality [\%] for Xe+Xe collisions

Data from Auxiliary Fig 3 panel b, $[p_{T}]$ vs $N_{ch}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Auxiliary Figure 4, $\Delta p_{T}/\left\langle[p_{T}]\right\rangle_{0-0.5\%}$ vs $\Delta N_{ch}/\left\langle N_{ch}\right\rangle_{0-0.5\%}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Auxiliary Figure 4, $\Delta p_{T}/\left\langle[p_{T}]\right\rangle_{0-0.5\%}$ vs $\Delta N_{ch}/\left\langle N_{ch}\right\rangle_{0-0.5\%}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 5 GeV/c, $|\eta|< $ 2.5

Data from Auxiliary Figure 4, $\Delta p_{T}/\left\langle[p_{T}]\right\rangle_{0-0.5\%}$ vs $\Delta N_{ch}/\left\langle N_{ch}\right\rangle_{0-0.5\%}$ for Pb+Pb collisions, 0.5 $ <p_{T}< $ 2 GeV/c, $|\eta|< $ 2.5

Data from Auxiliary Figure 4, $\Delta p_{T}/\left\langle[p_{T}]\right\rangle_{0-0.5\%}$ vs $\Delta N_{ch}/\left\langle N_{ch}\right\rangle_{0-0.5\%}$ for Xe+Xe collisions, 0.5 $ <p_{T}< $ 2 GeV/c, $|\eta|< $ 2.5

Unfolded groomed jet radius distribution in PbPb normalized to the number of jets that pass the $x_J$>0.4 selection. All systematic uncertainties are bin-to-bin fully correlated (allowing for sign-changes bin-to-bin).The covaraince matrices are provided for the statistical uncertainties from data and MC in this HepData record.The negative (-0.05,0) bin accounts for jets that failed the soft-drop grooming condition.

Covariance matrix of the statistical uncertainty in data for the unfolded groomed jet radius distribution in PbPb for jets that pass the $x_J$>0.4 selection.The bin indices correspond to the bins used in the groomed jet radius distribution.

Covariance matrix of the statistical uncertainty in MC for the unfolded groomed jet radius distribution in PbPb for jets that pass the $x_J$>0.4 selection.The bin indices correspond to the bins used in the groomed jet radius distribution.

Unfolded jet girth distribution in PbPb normalized to the number of jets that pass the $x_J$>0.8 selection. All systematic uncertainties are bin-to-bin fully correlated (allowing for sign-changes bin-to-bin).The covaraince matrices are provided for the statistical uncertainties from data and MC in this HepData record.

Covariance matrix of the statistical uncertainty in data for the unfolded jet girth distribution in PbPb for jets that pass the $x_J$>0.4 selection.The bin indices correspond to the bins used in the jet girth distribution.

Covariance matrix of the statistical uncertainty in MC for the unfolded jet girth distribution in PbPb for jets that pass the $x_J$>0.8 selection.The bin indices correspond to the bins used in the jet girth distribution.

Unfolded groomed jet radius distribution in PbPb normalized to the number of jets that pass the $x_J$>0.8 selection. All systematic uncertainties are bin-to-bin fully correlated (allowing for sign-changes bin-to-bin).The covaraince matrices are provided for the statistical uncertainties from data and MC in this HepData record.The negative (-0.05,0) bin accounts for jets that failed the soft-drop grooming condition.

Covariance matrix of the statistical uncertainty in data for the unfolded groomed jet radius distribution in PbPb for jets that pass the $x_J$>0.8 selection.The bin indices correspond to the bins used in the groomed jet radius distribution.

Covariance matrix of the statistical uncertainty in MC for the unfolded groomed jet radius distribution in PbPb for jets that pass the $x_J$>0.8 selection.The bin indices correspond to the bins used in the groomed jet radius distribution.

Unfolded jet girth distribution in pp normalized to the number of jets that pass the $x_J$>0.4 selection. All systematic uncertainties are bin-to-bin fully correlated (allowing for sign-changes bin-to-bin).The covaraince matrices are provided for the statistical uncertainties from data and MC in this HepData record.

Covariance matrix of the statistical uncertainty in data for the unfolded jet girth distribution in pp for jets that pass the $x_J$>0.4 selection.The bin indices correspond to the bins used in the jet girth distribution.

Covariance matrix of the statistical uncertainty in MC for the unfolded jet girth distribution in pp for jets that pass the $x_J$>0.4 selection.The bin indices correspond to the bins used in the jet girth distribution.

Unfolded groomed jet radius distribution in pp normalized to the number of jets that pass the $x_J$>0.4 selection. All systematic uncertainties are bin-to-bin fully correlated (allowing for sign-changes bin-to-bin).The covaraince matrices are provided for the statistical uncertainties from data and MC in this HepData record.The negative (-0.05,0) bin accounts for jets that failed the soft-drop grooming condition.

Covariance matrix of the statistical uncertainty in data for the unfolded groomed jet radius distribution in pp for jets that pass the $x_J$>0.4 selection.The bin indices correspond to the bins used in the groomed jet radius distribution.

Covariance matrix of the statistical uncertainty in MC for the unfolded groomed jet radius distribution in pp for jets that pass the $x_J$>0.4 selection.The bin indices correspond to the bins used in the groomed jet radius distribution.

Unfolded jet girth distribution in pp normalized to the number of jets that pass the $x_J$>0.8 selection. All systematic uncertainties are bin-to-bin fully correlated (allowing for sign-changes bin-to-bin).The covaraince matrices are provided for the statistical uncertainties from data and MC in this HepData record.

Covariance matrix of the statistical uncertainty in data for the unfolded jet girth distribution in pp for jets that pass the $x_J$>0.8 selection.The bin indices correspond to the bins used in the jet girth distribution.

Covariance matrix of the statistical uncertainty in MC for the unfolded jet girth distribution in pp for jets that pass the $x_J$>0.8 selection.The bin indices correspond to the bins used in the jet girth distribution.

Unfolded groomed jet radius distribution in pp normalized to the number of jets that pass the $x_J$>0.8 selection. All systematic uncertainties are bin-to-bin fully correlated (allowing for sign-changes bin-to-bin).The covaraince matrices are provided for the statistical uncertainties from data and MC in this HepData record.The negative (-0.05,0) bin accounts for jets that failed the soft-drop grooming condition.

Covariance matrix of the statistical uncertainty in data for the unfolded groomed jet radius distribution in pp for jets that pass the $x_J$>0.8 selection.The bin indices correspond to the bins used in the groomed jet radius distribution.

Covariance matrix of the statistical uncertainty in MC for the unfolded groomed jet radius distribution in pp for jets that pass the $x_J$>0.8 selection.The bin indices correspond to the bins used in the groomed jet radius distribution.

Ratio of yields in PbPb to pp for the unfolded jet girth distribution normalized to the number of jets that pass the $x_J$>0.4 selection. Each uncertainty is symmetrized and added in quadrature.All systematic uncertainties have been obtained assuming the PbPb and pp uncertainties are uncorrelated.

Ratio of yields in PbPb to pp for the unfolded groomed jet radius distribution normalized to the number of jets that pass the $x_J$>0.4 selection. Each uncertainty is symmetrized and added in quadrature.All systematic uncertainties have been obtained assuming the PbPb and pp uncertainties are uncorrelated.The negative (-0.05,0) bin accounts for jets that failed the soft-drop grooming condition.

Ratio of yields in PbPb to pp for the unfolded jet girth distribution normalized to the number of jets that pass the $x_J$>0.8 selection. Each uncertainty is symmetrized and added in quadrature.All systematic uncertainties have been obtained assuming the PbPb and pp uncertainties are uncorrelated.

Ratio of yields in PbPb to pp for the unfolded groomed jet radius distribution normalized to the number of jets that pass the $x_J$>0.8 selection. Each uncertainty is symmetrized and added in quadrature.All systematic uncertainties have been obtained assuming the PbPb and pp uncertainties are uncorrelated.The negative (-0.05,0) bin accounts for jets that failed the soft-drop grooming condition.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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