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 nuclear suppression factor $S^{\mathrm{J}/\psi}$ of incoherent $\mathrm{J}/\psi$ meson photoproduction as a function of Bjorken $x$ in PbPb ultra-peripheral collisions at $\sqrt{s_{\mathrm{NN}}}$ = 5.02 TeV. The $x$ values are evaluated at the centers of their corresponding rapidity ranges. The theoretical uncertainties are due to the uncertainties in the photon flux.

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

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

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

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

The 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.

The elliptic anisotropy $v_2\{4\}$ as a function of $\langle N_{trk}^{offline} \rangle$ with 4-subevent method compared between pPb collisions at 8.16 TeV and PbPb collisions at 5.02 TeV with $p_{T}^{POI}>6$ GeV.

The elliptic anisotropy $v_2\{4\}$ as a function of $\langle N_{trk}^{corrected} \rangle$ with 4-subevent method compared between pPb collisions at 8.16 TeV and PbPb collisions at 5.02 TeV with $p_{T}^{POI}>6$ GeV.

The differential cumulant $d_2\{4\}$ as a function of $p_T$ in generator level HIJING for $60 \le N_{trk}^{gen} <120$ are compared to the experimental pPb results with $60 \le N_{trk}^{offline} <120$ and $185 \le N_{trk}^{offline} <250$.

Differential cross sections for exclusive dielectron production, in the fiducial phase space of Table 1, as functions of the pair invariant mass. Data are compared with SUPERCHIC + FSR(PHOTOS++), STARLIGHT + FSR(PY8), and gamma-UPC + FSR(PY8) predictions.

Differential cross sections for exclusive dielectron production, in the fiducial phase space of Table 1, as functions of the pair |cos $\theta$*|. Data are compared with SUPERCHIC + FSR(PHOTOS++), STARLIGHT + FSR(PY8), and gamma-UPC + FSR(PY8) predictions.

Differential exclusive diphoton cross sections in the fiducial phase space of Table 1 as a function of the diphoton rapidity measured in data compared with SUPERCHIC and gamma-UPC@NLO predictions.

Differential exclusive diphoton cross sections in the fiducial phase space of Table 1 as a function of the diphoton invariant mass measured in data compared with SUPERCHIC and gamma-UPC@NLO predictions.

Observed and expected 95% CL limits on the production cross section $\sigma(\gamma\gamma \rightarrow a \rightarrow \gamma\gamma)$ as a function of the ALP mass $m_{a}$. The uncertainties indicate regions containing 68 and 95% of the distribution of limits expected under the background-only hypothesis. The additional datasets indicate the expected ALP cross sections as a function of $m_{a}$ for decreasing photon couplings ($g_{a\gamma} = 0.3, 0.1, 0.05 TeV^{-1}$).

Exclusion limits at 95% CL in the axion-photon coupling $g_{a\gamma}$ versus axion mass $m_a$ plane, for the operator $\frac{1}{4\Lambda}aF\widetilde{F}$ (assuming ALPs coupled only to photons) extracted in this analysis.

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.

Tuned intrinsic kT parameters ShowerHandler:IntrinsicPtGaussian in Herwig with the underlying-event tune CH2 at nucleon-nucleon center-of-mass energy from 38.8 GeV to 13 TeV.

Tuned intrinsic kT parameters ShowerHandler:IntrinsicPtGaussian in Herwig with the underlying-event tune CH3 at nucleon-nucleon center-of-mass energy from 38.8 GeV to 13 TeV.

Tuned intrinsic kT parameters BeamRemnants:PrimordialkThard in Pythia with the underlying-event tune CP5 and ISR starting scale SpaceShower:pT0Ref = 1 GeV at nucleon-nucleon center-of-mass energy from 38.8 GeV to 13 TeV.

Tuned intrinsic kT parameters ShowerHandler:IntrinsicPtGaussian in Herwig with the underlying-event tune CH3 and ISR starting scale SudakovCommon:pTmin=0.7 GeV at nucleon-nucleon center-of-mass energy from 38.8 GeV to 13 TeV.

Tuned intrinsic kT parameters BeamRemnants:PrimordialkThard in Pythia with the underlying-event tune CP5 at proton-proton center-of-mass energy 38.8 GeV versus the dilepton mass range of the process.

Tuned intrinsic kT parameters BeamRemnants:PrimordialkThard in Pythia with the underlying-event tune CP5 at proton-proton center-of-mass energy 8000 GeV versus the dilepton mass range of the process.

Tuned intrinsic kT parameters BeamRemnants:PrimordialkThard in Pythia with the underlying-event tune CP5 at proton-nucleon center-of-mass energy 8160 GeV versus the dilepton mass range of the process.

Tuned intrinsic kT parameters BeamRemnants:PrimordialkThard in Pythia with the underlying-event tune CP5 at proton-nucleon center-of-mass energy 13000 GeV versus the dilepton mass range of the process.

Tuned intrinsic kT parameters ShowerHandler:IntrinsicPtGaussian in Herwig with the underlying-event tune CH2 at proton-proton center-of-mass energy 38.8 GeV versus the dilepton mass range of the process.

Tuned intrinsic kT parameters ShowerHandler:IntrinsicPtGaussian in Herwig with the underlying-event tune CH2 at proton-proton center-of-mass energy 8000 GeV versus the dilepton mass range of the process.

Tuned intrinsic kT parameters ShowerHandler:IntrinsicPtGaussian in Herwig with the underlying-event tune CH2 at proton-nucleon center-of-mass energy 8160 GeV versus the dilepton mass range of the process.

Tuned intrinsic kT parameters ShowerHandler:IntrinsicPtGaussian in Herwig with the underlying-event tune CH2 at proton-proton center-of-mass energy 13000 GeV versus the dilepton mass range of the process.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters among various generator settings at proton-proton center-of-mass energy 38.8 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters among various generator settings at proton-proton center-of-mass energy 62 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters among various generator settings at proton-proton center-of-mass energy 200 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters among various generator settings at proton-anti-proton center-of-mass energy 1800 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters among various generator settings at proton-anti-proton center-of-mass energy 1960 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters among various generator settings at proton-proton center-of-mass energy 2760 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters among various generator settings at proton-proton center-of-mass energy 8000 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters among various generator settings at proton-nucleon center-of-mass energy 8160 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters among various generator settings at proton-proton center-of-mass energy 13000 GeV when fitting to the CMS measurement.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters among various generator settings at proton-proton center-of-mass energy 13000 GeV when fitting to the LHCb measurement.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters between the two generator settings of Pythia at proton-proton center-of-mass energy 38.8 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters between the two generator settings of Pythia at proton-proton center-of-mass energy 62 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters between the two generator settings of Pythia at proton-proton center-of-mass energy 200 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters between the two generator settings of Pythia at proton-anti-proton center-of-mass energy 1800 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters between the two generator settings of Pythia at proton-anti-proton center-of-mass energy 1960 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters between the two generator settings of Pythia at proton-proton center-of-mass energy 2760 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters between the two generator settings of Pythia at proton-proton center-of-mass energy 8000 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters between the two generator settings of Pythia at proton-nucleon center-of-mass energy 8160 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters between the two generator settings of Pythia at proton-proton center-of-mass energy 13000 GeV when fitting to the CMS measurement.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters between the two generator settings of Pythia at proton-proton center-of-mass energy 13000 GeV when fitting to the LHCb measurement.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters between the two generator settings of Herwig at proton-proton center-of-mass energy 38.8 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters between the two generator settings of Herwig at proton-proton center-of-mass energy 62 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters between the two generator settings of Herwig at proton-proton center-of-mass energy 200 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters between the two generator settings of Herwig at proton-anti-proton center-of-mass energy 1800 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters between the two generator settings of Herwig at proton-anti-proton center-of-mass energy 1960 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters between the two generator settings of Herwig at proton-proton center-of-mass energy 2760 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters between the two generator settings of Herwig at proton-proton center-of-mass energy 8000 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters between the two generator settings of Herwig at proton-nucleon center-of-mass energy 8160 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters between the two generator settings of Herwig at proton-proton center-of-mass energy 13000 GeV when fitting to the CMS measurement.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters between the two generator settings of Herwig at proton-proton center-of-mass energy 13000 GeV when fitting to the LHCb measurement.