HF Fraction at $1.2 < |\eta| < 2.0$ Top Muon Rich Data

HF Fraction at $1.2 < |\eta| < 2.0$ Bottom Ratio

Charged Hadron $v_2$; $1.2 < |\eta| < 2.0$

Charged Hadron; $1.2 < |\eta| < 2.0$

HF -> $\mu$; $1.2 < |\eta| < 2.0$

HF -> $e$; $|\eta| < 0.35$

JPSI v2 in Au+Au collisions as a function of pT (GeV/c) for 10%--40% centrality with pT binned by [0, 2], [2, 5], and [5, 10] GeV/c.

Self-Normalized $J/\psi$ yields in the same arms before and after dimuon subtraction and the comparison with PYTHIA 8 simulations

Self-normalized $\psi(2S)$ to $J/\psi$ yields ratio as a function of Self-normalized $N_{ch}$ in the same arms

Self-normalized $\psi(2S)$ to $J/\psi$ yields ratio as a function of Self-normalized $N_{ch}$ in opposite arms

Distribution of the reconstructed $\tau\tau$ invariant mass ($m_{\tau\tau}$) for all events in the VBF_1 signal region for $p_{\text{T}}^{H}>200$ GeV. The observed Higgs boson signal corresponds to $(\sigma\times B)/(\sigma\times B)_{\text{SM}}\,=\,0.99$. Entries with values above the $x$-axis range are shown in the last bin of each distribution. The prediction for each sample is determined from the likelihood fit performed to measure the total $pp\rightarrow H\rightarrow\tau\tau$ cross-section.

Distribution of the reconstructed $\tau\tau$ invariant mass ($m_{\tau\tau}$) for all events in the VBF_0 signal region for $m_{jj}<1$ TeV. The observed Higgs boson signal corresponds to $(\sigma\times B)/(\sigma\times B)_{\text{SM}}\,=\,0.99$. Entries with values above the $x$-axis range are shown in the last bin of each distribution. The prediction for each sample is determined from the likelihood fit performed to measure the total $pp\rightarrow H\rightarrow \tau\tau$ cross-section.

Distribution of the reconstructed $\tau\tau$ invariant mass ($m_{\tau\tau}$) for all events in the VBF_0 signal region for $m_{jj}>1$ TeV. The observed Higgs boson signal corresponds to $(\sigma\times B)/(\sigma\times B)_{\text{SM}}\,=\,0.99$. Entries with values above the $x$-axis range are shown in the last bin of each distribution. The prediction for each sample is determined from the likelihood fit performed to measure the total $pp\rightarrow H \rightarrow \tau\tau$ cross-section.

Distribution of the reconstructed $\tau\tau$ invariant mass ($m_{\tau\tau}$) for all events in the VBF_1 signal region for $m_{jj}<1$ TeV. The observed Higgs boson signal corresponds to $(\sigma\times B)/(\sigma\times B)_{\text{SM}}\,=\,0.99$. Entries with values above the $x$-axis range are shown in the last bin of each distribution. The prediction for each sample is determined from the likelihood fit performed to measure the total $pp\rightarrow \rightarrow \tau\tau$ cross-section.

Distribution of the reconstructed $\tau\tau$ invariant mass ($m_{\tau\tau}$) for all events in the VBF_1 signal region for $m_{jj}>1$ TeV. The observed Higgs boson signal corresponds to $(\sigma\times B)/(\sigma\times B)_{\text{SM}}\,=\,0.99$. Entries with values above the $x$-axis range are shown in the last bin of each distribution. The prediction for each sample is determined from the likelihood fit performed to measure the total $pp\rightarrow H\rightarrow \tau\tau$ cross-section.

Comparison of the observed and expected event yields in the ttH categories. The window category contains events with $m_{\tau\tau} \in [100, 150]$ GeV, while events outside of this mass region are included in the sideband region. The observed Higgs boson signal corresponds to $(\sigma\times B)/(\sigma\times B)_{\text{SM}}\,=\,0.99$. The prediction for each sample is determined from the likelihood fit performed to measure the total $pp\rightarrow H\rightarrow\tau\tau$ cross-section.

The measured values of $\sigma_{H}\times B(H\rightarrow\tau\tau)$ relative to the SM expectations in the total (labelled as 'Combined') and per-production-mode fit. The total $\pm1\sigma$ uncertainty in each measurement is indicated by the error bar. The total systematic uncertainty in each measurement is also indicated.

The measured values for $\sigma_{H}\times B(H\rightarrow\tau\tau)$ relative to the SM expectations in the simplified template cross-section measurement. The total $\pm1\sigma$ uncertainty in each measurement is indicated by the error bar. The total systematic uncertainty in each measurement is also indicated.

Upper limits at 95% CL on simplified template cross-sections in the individual ttH $p_{\text{T}}^{H}$ bins relative to their SM expectation in the $H\rightarrow\tau\tau$ decay channel, derived using the CL$_\text{s}$ method. The observed upper limits, together with the expected limits both in the background-only hypothesis and in the SM hypothesis (dotted red lines) are included. In the case of the expected limits in the background-only hypothesis, one- and two-standard-deviation uncertainty bands are also shown.

Measured fiducial differential cross-sections as a function of $p_\text{T}(j_0)$. The measurements are compared with particle-level SM predictions from the POWHEG+PYTHIA8, POWHEG+HERWIG7 and MadGraph5_aMC@NLO+Pythia8 generators for the combined VBF, ggF, $VH$, and $t\bar{t}H$ Higgs boson production modes. The shaded box around each data point shows the statistical uncertainty, while the total uncertainty is indicated by the error bar. The contribution from the ggF, $VH$, and $t\bar{t}H$ production modes as predicted by POWHEG+PYTHIA8 is also shown.

Measured fiducial differential cross-sections as a function of $p_\text{T}^{H}$. The measurements are compared with particle-level SM predictions from the POWHEG+PYTHIA8, POWHEG+HERWIG7 and MadGraph5_aMC@NLO+Pythia8 generators for the combined VBF, ggF, $VH$, and $t\bar{t} H$ Higgs boson production modes. The shaded box around each data point shows the statistical uncertainty, while the total uncertainty is indicated by the error bar. The contribution from the ggF, $VH$, and $t\bar{t} H$ production modes as predicted by POWHEG+PYTHIA8 is also shown.

Measured fiducial differential cross-sections as a function of $\Delta\phi_{jj}^{\text{signed}}$. The measurements are compared with particle-level SM predictions from the POWHEG+PYTHIA8, POWHEG+HERWIG7 and MadGraph5_aMC@NLO+Pythia8 generators for the combined VBF, ggF, $VH$, and $t\bar{t}H$ Higgs boson production modes. The shaded box around each data point shows the statistical uncertainty, while the total uncertainty is indicated by the error bar. The contribution from the ggF, $VH$, and $t\bar{t} H$ production modes as predicted by POWHEG+PYTHIA8 is also shown.

Measured fiducial differential cross-sections as a function of $\Delta\phi_{jj}^{\text{signed}}$ vs $p_\text{T}^\text{H}$. The measurements are compared with particle-level SM predictions from the POWHEG+PYTHIA8, POWHEG+HERWIG7 and MadGraph5_aMC@NLO+Pythia8 generators for the combined VBF, ggF, $VH$, and $t\bar{t}H$ Higgs boson production modes. The shaded box around each data point shows the statistical uncertainty, while the total uncertainty is indicated by the error bar. The contribution from the ggF, $VH$, and $t\bar{t}H$ production modes as predicted by POWHEG+PYTHIA8 is also shown.

The unfolded data compared with the nominal SM predictions from POWHEG+PYTHIA8, as well as the predictions for several values of Wilson coefficients in the SMEFT, for $\Delta\phi_{jj}^{\text{signed}}$.

The unfolded data compared with the nominal SM predictions from POWHEG+PYTHIA8, as well as the predictions for several values of Wilson coefficients in the SMEFT, for $\Delta\phi_{jj}^{\text{signed}}$.

The unfolded data compared with the nominal SM predictions from POWHEG+PYTHIA8, as well as the predictions for several values of Wilson coefficients in the SMEFT, for $\Delta\phi_{jj}^{\text{signed}}$ vs $p_\text{T}^{H}$.

The unfolded data compared with the nominal SM predictions from POWHEG+PYTHIA8, as well as the predictions for several values of Wilson coefficients in the SMEFT, for $p_\text{T}^{H}$.

The 95% expected and observed confidence intervals for each of the six considered Wilson coefficients. Each coefficient is treated individually and both the linear and linear + quadratic models are considered when evaluating the sensitivity to the terms that enter at $\mathcal{O}(\Lambda^{-4})$. For the CP-even operators the $\Delta\phi_{jj}^{\text{signed}}$ distribution is used to extract the confidence interval. The limits are computed at a new-physics scale $\Lambda=1$ TeV.

The 95% expected and observed confidence intervals for each of the six considered Wilson coefficients. Each coefficient is treated individually and both the linear and linear + quadratic models are considered when evaluating the sensitivity to the terms that enter at $\mathcal{O}(\Lambda^{-4})$. For the CP-odd operators the $\Delta\phi_{jj}^{\text{signed}}$ vs $p_\text{T}^{H}$ distribution is used to extract the confidence interval. The limits are computed at a new-physics scale $\Lambda=1$ TeV.

Two-dimensional observed and expected limits at 68% and 95% confidence level obtained from $c_{HW}$ and $c_{HB}$ using only the SM-dimension-6 interference in the SMEFT basis. The limits are computed at a new-physics scale $\Lambda$ = 1 TeV. In this case, the $\Delta\phi_{jj}^{signed}$ distribution is used. IMPORTANT: HEPData requires the same number of rows for each column. However, each curve of on the plot has a different number of points. For that reason, the curves are padded with data of "0.0, 0.0". The "0.0, 0.0" points should be omitted in analysis.

Two-dimensional observed and expected limits at 68% and 95% confidence level obtained from $c_{H\tilde{W}}$ and $c_{H\tilde{B}}$ using only the SM-dimension-6 interference in the SMEFT basis. The limits are computed at a new-physics scale $\Lambda$ = 1 TeV. In this purely CP-odd case, the $\Delta\phi_{jj}^{signed}$ vs $p_{T}^{H}$ distribution is used. IMPORTANT: HEPData requires the same number of rows for each column. However, each curve of on the plot has a different number of points. For that reason, the curves are padded with data of "0.0, 0.0". The "0.0, 0.0" points should be omitted in analysis.

Two-dimensional observed and expected limits at 68% and 95% confidence level obtained from $c_{HW}$ and $c_{H\tilde{W}}$ using only the SM-dimension-6 interference in the SMEFT basis. The limits are computed at a new-physics scale $\Lambda$ = 1 TeV. In this case, the $\Delta\phi_{jj}^{signed}$ distribution is used. IMPORTANT: HEPData requires the same number of rows for each column. However, each curve of on the plot has a different number of points. For that reason, the curves are padded with data of "0.0, 0.0". The "0.0, 0.0" points should be omitted in analysis.

The expected values of $\sigma_{H}\times B(H\rightarrow\tau\tau)$ relative to the SM expectations in the total (labelled as 'Combined') and per-production-mode fit. The total $\pm1\sigma$ uncertainty in each measurement is indicated by the error bar. The total systematic uncertainty in each measurement is also indicated.

The expected values for $\sigma_{H}\times B(H\rightarrow\tau\tau)$ relative to the SM expectations in the simplified template cross-section measurement. The total $\pm1\sigma$ uncertainty in each measurement is indicated by the error bar. The total systematic uncertainty in each measurement is also indicated.

The measured values for $\sigma_{H}\times B(H\rightarrow\tau\tau)$ in the simplified template cross-section measurement. The total $\pm1\sigma$ uncertainty in the measurement is indicated by the black error bars, with the individual contribution from the statistical uncertainty in blue.

The measured correlations between differential fiducial cross-sections, $\sigma$, and the normalisation factors, $\alpha$, for the $Z(\to\tau\tau) + \text{jets}$ and top backgrounds for $p_\text{T}(j_0)$. The bins denoted as $\sigma_{1,2,3,4}$ correspond to the measurements in the four bins listed elsewhere for each observable.

The measured correlations between differential fiducial cross-sections, $\sigma$, and the normalisation factors, $\alpha$, for the $Z(\to\tau\tau) + \text{jets}$ and top backgrounds for $p_\text{T}^{H}}$. The bins denoted as $\sigma_{1,2,3,4}$ correspond to the measurements in the four bins listed elsewhere for each observable.

The measured correlations between differential fiducial cross-sections, $\sigma$, and the normalisation factors, $\alpha$, for the $Z(\to\tau\tau) + \text{jets}$ and top backgrounds for $\Delta\phi_{jj}^{\text{signed}}$. The bins denoted as $\sigma_{1,2,3,4}$ correspond to the measurements in the four bins listed elsewhere for each observable.

The measured correlations between differential fiducial cross-sections, $\sigma$, and the normalisation factors, $\alpha$, for the $Z(\to\tau\tau) + \text{jets}$ and top backgrounds for $\Delta\phi_{jj}^{\text{signed}}$ vs $p_\text{T}^{H}$. The bins denoted as $\sigma_{1,2,3,4}$ correspond to the measurements in the four bins listed elsewhere for each observable.

95&percnt; CL expected and observed exclusion limits on the branching ratio of the Higgs boson to dark photons as a function of the &gamma;_d mass for the HAHM model.

95&percnt; CL expected and observed exclusion limits on the branching ratio of the Higgs boson to dark photons as a function of the &gamma;_d mass for the FRVZ model.

90&percnt; CL exclusion limit contours on the branching ratio of the Higgs boson to dark photons as functions of the &gamma;_d mass and kinetic mixing parameter &epsilon; for the HAHM model. These exclusions assume Higgs boson branching fractions to dark photons within a 0.01&percnt; and 10&percnt; range.

90&percnt; CL exclusion limit contours on the branching ratio of the Higgs boson to dark photons as functions of the &gamma;_d mass and kinetic mixing parameter &epsilon; for the FRVZ model. These exclusions assume Higgs boson branching fractions to dark photons within a 0.01&percnt; and 10&percnt; range.

The reconstruction efficiency for &mu;LJ objects produced in the decay of a &gamma;_d into a muon pair. The reconstruction efficiency is shown for different dark photon mass hypotheses generated according to the HAHM signal model. The efficiency is shown as a function of the dark photon p_T.

The reconstruction efficiency for &mu;LJ objects produced in the decay of a &gamma;_d into a muon pair. The reconstruction efficiency is shown for different dark photon mass hypotheses generated according to the FRVZ signal model. The efficiency is shown as a function of the dark photon p_T.

The reconstruction efficiency for &mu;LJ objects produced in the decay of a &gamma;_d into a muon pair. The reconstruction efficiency is shown for different dark photon mass hypotheses generated according to the HAHM signal model. The efficiency is shown as a function of the &Delta;R opening between the decay products of a dark photon.

The reconstruction efficiency for &mu;LJ objects produced in the decay of a &gamma;_d into a muon pair. The reconstruction efficiency is shown for different dark photon mass hypotheses generated according to the FRVZ signal model. The efficiency is shown as a function of the &Delta;R opening between the decay products of a dark photon.

The reconstruction efficiency for &mu;LJ objects produced in the decay of a &gamma;_d into a muon pair. The reconstruction efficiency is shown for a dark photon mass of 0.4 GeV, generated according to the HAHM and FRVZ signal models. The efficiency is shown as a function of the &gamma;_d p_T.

The reconstruction efficiency for &mu;LJ objects produced in the decay of a &gamma;_d into a muon pair. The reconstruction efficiency is shown for a dark photon mass of 0.4 GeV, generated according to the HAHM and FRVZ signal models. The efficiency is shown as a function of the &Delta;R opening between the decay products of a dark photon.

The reconstruction efficiency for eLJ objects produced in the decay of a &gamma;_d into an electron pair. The reconstruction efficiency is shown for different dark photon mass hypotheses generated according to the HAHM signal model. The efficiency is shown as a function of the dark photon p_T.

The reconstruction efficiency for eLJ objects produced in the decay of a &gamma;_d into an electron pair. The reconstruction efficiency is shown for different dark photon mass hypotheses generated according to the FRVZ signal model. The efficiency is shown as a function of the dark photon p_T.

The reconstruction efficiency for eLJ objects produced in the decay of a &gamma;_d into a pair of electrons. The reconstruction efficiency is shown for different dark photon mass hypotheses generated according to the HAHM signal model. The efficiency is shown as a function of the &Delta;R opening between the decay products of a dark photon. The decrease in efficiency, visible at 0.1, is due to the transition between the region of the phase space where eLJs are identified from merged EM showers with two tracks, to the one where eLJs are obtained by the clustering of two resolved electrons.

The reconstruction efficiency for eLJ objects produced in the decay of a &gamma;_d into a pair of electrons. The reconstruction efficiency is shown for different dark photon mass hypotheses generated according to the FRVZ signal model. The efficiency is shown as a function of the &Delta;R opening between the decay products of a dark photon. The decrease in efficiency, visible at 0.1, is due to the transition between the region of the phase space where eLJs are identified from merged EM showers with two tracks, to the one where eLJs are obtained by the clustering of two resolved electrons.

The reconstruction efficiency for eLJ objects produced in the decay of a &gamma;_d into a pair of electrons. The reconstruction efficiency is shown for a dark photon mass of 0.1 GeV, generated according to the HAHM and FRVZ signal models. The efficiency is shown as a function of the &gamma;_d p_T.

The reconstruction efficiency for eLJ objects produced in the decay of a &gamma;_d into a pair of electrons. The reconstruction efficiency is shown for a dark photon mass of 0.1 GeV, generated according to the HAHM and FRVZ signal models. The efficiency is shown as a function of the &Delta;R opening between the decay products of a dark photon.

95&percnt; CL expected and observed exclusion limits on the branching ratio of the Higgs boson to dark photons as a function of the &gamma;_d mass for the HAHM model, obtained from the &mu;LJ&ndash;&mu;LJ signal region.

95&percnt; CL expected and observed exclusion limits on the branching ratio of the Higgs boson to dark photons as a function of the &gamma;_d mass for the FRVZ model, obtained from the &mu;LJ&ndash;&mu;LJ signal region.

95&percnt; CL expected and observed exclusion limits on the branching ratio of the Higgs boson to dark photons as a function of the &gamma;_d mass for the HAHM model, obtained from the &mu;LJ&ndash;eLJ signal region.

95&percnt; CL expected and observed exclusion limits on the branching ratio of the Higgs boson to dark photons as a function of the &gamma;_d mass for the FRVZ model, obtained from the &mu;LJ&ndash;eLJ signal region.

Acceptance times efficiencies (A&times;&varepsilon;) as a function of the &gamma;_d mass for the HAHM process for the three signal regions of the analysis, eLJ-eLJ, eLJ-&mu;LJ and &mu;LJ-&mu;LJ. The decrease of the A&times;&varepsilon; is expected for increasing masses of the &gamma;_d, as its decay products become resolved and are no longer reconstructed as LJs. The local minimum around m_{&gamma;_d}=2 GeV observed for the eLJ-&mu;LJ distribution is expected, as the reconstruction efficiency for eLJs with merged EM showers decreases before the reconstruction of eLJ with two resolved electrons becomes efficient.

Acceptance times efficiencies (A&times;&varepsilon;) as a function of the &gamma;_d mass for the FRVZ process for the three signal regions of the analysis, eLJ-eLJ, eLJ-&mu;LJ and &mu;LJ-&mu;LJ. The decrease of the A&times;&varepsilon; is expected for increasing masses of the &gamma;_d, as its decay products become resolved and are no longer reconstructed as LJs. The local minimum around m_{&gamma;_d}=2 GeV observed for the eLJ-&mu;LJ distribution is expected, as the reconstruction efficiency for eLJs with merged EM showers decreases before the reconstruction of eLJ with two resolved electrons becomes efficient.

The transverse-mass dependence of the correlation-strength parameter $\lambda$ in 30-40% centrality bin obtained from Lévy fits with Eq. (9).

The transverse-mass dependence of the correlation-strength parameter $\lambda$ in 40-50% centrality bin obtained from Lévy fits with Eq. (9).

The transverse-mass dependence of the correlation-strength parameter $\lambda$ in 50-60% centrality bin obtained from Lévy fits with Eq. (9).

The transverse-mass dependence of the Lévy-scale parameter $R$ in 0-10% centrality bin obtained from Lévy fits with Eq. (9).

The transverse-mass dependence of the Lévy-scale parameter $R$ in 10-20% centrality bin obtained from Lévy fits with Eq. (9).

The transverse-mass dependence of the Lévy-scale parameter $R$ in 20-30% centrality bin obtained from Lévy fits with Eq. (9).

The transverse-mass dependence of the Lévy-scale parameter $R$ in 30-40% centrality bin obtained from Lévy fits with Eq. (9).

The transverse-mass dependence of the Lévy-scale parameter $R$ in 40-50% centrality bin obtained from Lévy fits with Eq. (9).

The transverse-mass dependence of the Lévy-scale parameter $R$ in 50-60% centrality bin obtained from Lévy fits with Eq. (9).

The transverse-mass dependence of the Lévy-index of stability parameter $\alpha$ in 0-10% centrality bin obtained from Lévy fits with Eq. (9).

The transverse-mass dependence of the Lévy-index of stability parameter $\alpha$ in 10-20% centrality bin obtained from Lévy fits with Eq. (9).

The transverse-mass dependence of the Lévy-index of stability parameter $\alpha$ in 20-30% centrality bin obtained from Lévy fits with Eq. (9).

The transverse-mass dependence of the Lévy-index of stability parameter $\alpha$ in 30-40% centrality bin obtained from Lévy fits with Eq. (9).

The transverse-mass dependence of the Lévy-index of stability parameter $\alpha$ in 40-50% centrality bin obtained from Lévy fits with Eq. (9).

The transverse-mass dependence of the Lévy-index of stability parameter $\alpha$ in 50-60% centrality bin obtained from Lévy fits with Eq. (9).

The transverse-mass dependence of the normalized correlation-strength parameter $\lambda/\lambda_{\rm max}$ for 0-10% centrality intervals. For each centrality bin the data are fitted with the Gaussian function of Eq. (15). This parameterization can describe the data and is discussed in detail in Section VI B. The fit parameters with the statistic and systematic uncertainties are shown in Fig. 7.

The transverse-mass dependence of the normalized correlation-strength parameter $\lambda/\lambda_{\rm max}$ for 10-20% centrality intervals. For each centrality bin the data are fitted with the Gaussian function of Eq. (15). This parameterization can describe the data and is discussed in detail in Section VI B. The fit parameters with the statistic and systematic uncertainties are shown in Fig. 7.

The transverse-mass dependence of the normalized correlation-strength parameter $\lambda/\lambda_{\rm max}$ for 20-30% centrality intervals. For each centrality bin the data are fitted with the Gaussian function of Eq. (15). This parameterization can describe the data and is discussed in detail in Section VI B. The fit parameters with the statistic and systematic uncertainties are shown in Fig. 7.

The transverse-mass dependence of the normalized correlation-strength parameter $\lambda/\lambda_{\rm max}$ for 30-40% centrality intervals. For each centrality bin the data are fitted with the Gaussian function of Eq. (15). This parameterization can describe the data and is discussed in detail in Section VI B. The fit parameters with the statistic and systematic uncertainties are shown in Fig. 7.

The transverse-mass dependence of the normalized correlation-strength parameter $\lambda/\lambda_{\rm max}$ for 40-50% centrality interval. For each centrality bin the data are fitted with the Gaussian function of Eq. (15). This parameterization can describe the data and is discussed in detail in Section VI B. The fit parameters with the statistic and systematic uncertainties are shown in Fig. 7.

The transverse-mass dependence of the normalized correlation-strength parameter $\lambda/\lambda_{\rm max}$ for 50-60% centrality interval. For each centrality bin the data are fitted with the Gaussian function of Eq. (15). This parameterization can describe the data and is discussed in detail in Section VI B. The fit parameters with the statistic and systematic uncertainties are shown in Fig. 7.

The transverse-mass dependence of the inverse square of the Lévy-scale parameter $R$, shown in 0-10% centrality bin. The values and uncertainties of the A and B linear fit parameters with the statistic and systematic uncertainties are shown in Fig. 8.

The transverse-mass dependence of the inverse square of the Lévy-scale parameter $R$, shown in 10-20% centrality bin. The values and uncertainties of the A and B linear fit parameters with the statistic and systematic uncertainties are shown in Fig. 8.

The transverse-mass dependence of the inverse square of the Lévy-scale parameter $R$, shown in 20-30% centrality bin. The values and uncertainties of the A and B linear fit parameters with the statistic and systematic uncertainties are shown in Fig. 8.

The transverse-mass dependence of the inverse square of the Lévy-scale parameter $R$, shown in 30-40% centrality bin. The values and uncertainties of the A and B linear fit parameters with the statistic and systematic uncertainties are shown in Fig. 8.

The transverse-mass dependence of the inverse square of the Lévy-scale parameter $R$, shown in 40-50% centrality bin. The values and uncertainties of the A and B linear fit parameters with the statistic and systematic uncertainties are shown in Fig. 8.

The transverse-mass dependence of the inverse square of the Lévy-scale parameter $R$, shown in 50-60% centrality bin. The values and uncertainties of the A and B linear fit parameters with the statistic and systematic uncertainties are shown in Fig. 8.

The transverse-mass dependence of the $\widehat{R}$ parameter, shown in 0-10% centrality bin. The values and uncertainties of the linear fit parameters $\widehat{A}$ and $\widehat{B}$ with the statistic and systematic uncertainties are shown in Fig. 9

The transverse-mass dependence of the $\widehat{R}$ parameter, shown in 10-20% centrality bin. The values and uncertainties of the linear fit parameters $\widehat{A}$ and $\widehat{B}$ with the statistic and systematic uncertainties are shown in Fig. 9

The transverse-mass dependence of the $\widehat{R}$ parameter, shown in 20-30% centrality bin. The values and uncertainties of the linear fit parameters $\widehat{A}$ and $\widehat{B}$ with the statistic and systematic uncertainties are shown in Fig. 9

The transverse-mass dependence of the $\widehat{R}$ parameter, shown in 30-40% centrality bin. The values and uncertainties of the linear fit parameters $\widehat{A}$ and $\widehat{B}$ with the statistic and systematic uncertainties are shown in Fig. 9

The transverse-mass dependence of the $\widehat{R}$ parameter, shown in 40-50% centrality bin. The values and uncertainties of the linear fit parameters $\widehat{A}$ and $\widehat{B}$ with the statistic and systematic uncertainties are shown in Fig. 9

The transverse-mass dependence of the $\widehat{R}$ parameter, shown in 50-60% centrality bin. The values and uncertainties of the linear fit parameters $\widehat{A}$ and $\widehat{B}$ with the statistic and systematic uncertainties are shown in Fig. 9

The $H$ parameter that characterize the magnitude of the $\lambda/\lambda_{max}(m_T)$ and is defined in Eq. (15)., shown as functions of $N_{part}$.

The $\sigma$ parameter that characterize the width of the $\lambda/\lambda_{max}(m_T)$ and is defined in Eq. (15)., shown as functions of $N_{part}$.

The parameter $A$ of the affine linear fit to the inverse square of the Lévy-scale parameter that are defined in Eq.(12) as function of $N_{part}$

The parameter $B$ of the affine linear fit to the inverse square of the Lévy-scale parameter that are defined in Eq.(12) as function of $N_{part}$

The parameter $\widehat{A}$ of the affine linear fit to the inverse of the $\widehat{R}$ parameter that are defined in Eq.(14) as function of $N_{part}$.

The parameter $\widehat{B}$ of the affine linear fit to the inverse of the $\widehat{R}$ parameter that are defined in Eq.(14) as function of $N_{part}$.

The centrality dependence of $\alpha_0$, the $m_T$-averaged value of $\alpha$ as a function of $N_{part}$.

The Lévy scale parameter $R$ as a function of $N^{1/3}_{part}$ at $m_T=0.326$ GeV.

The Lévy scale parameter $R$ as a function of $N^{1/3}_{part}$ at $m_T=0.438$ GeV.

The Lévy scale parameter $R$ as a function of $N^{1/3}_{part}$ at $m_T=0.553$ GeV.

The Lévy scale parameter $R$ as a function of $N^{1/3}_{part}$ at $m_T=0.670$ GeV.

The Lévy scale parameter $R$ as a function of $N^{1/3}_{part}$ at $m_T=0.787$ GeV.

Monte Carlo calcuations with no mass drop assumed in 0-10%.

Monte Carlo calcuations with no mass drop assumed in 10-20%.

Monte Carlo calcuations with no mass drop assumed in 20-30%.

Monte Carlo calcuations with no mass drop assumed in 30-40%.

Monte Carlo calcuations with no mass drop assumed in 40-50%.

Monte Carlo calcuations with no mass drop assumed in 50-60%.

Monte Carlo calcuations with the best mass drop assumed in 0-10%.

Monte Carlo calcuations with the best mass drop assumed in 10-20%.

Monte Carlo calcuations with the best mass drop assumed in 20-30%.

Monte Carlo calcuations with the best mass drop assumed in 30-40%.

Monte Carlo calcuations with the best mass drop assumed in 40-50%.

Monte Carlo calcuations with the best mass drop assumed in 50-60%.

The best values of $B^{-1}_{\eta\prime}$ spectrum of the $\eta\prime$ condensate in the six centrality classes.

The centrality dependence of the best values of the in-medium mass of the $m^{*}_{\eta\prime}$.

The CL maps of the comparison of the MC to data in 0-10% (see Fig. 11).

The CL maps of the comparison of the MC to data in 10-20% (see Fig. 11).

The CL maps of the comparison of the MC to data in 20-30% (see Fig. 11).

The CL maps of the comparison of the MC to data in 30-40% (see Fig. 11).

The CL maps of the comparison of the MC to data in 40-50% (see Fig. 11).

The CL maps of the comparison of the MC to data in 50-60% (see Fig. 11).

Differential away-side a function of Deltaphi 0%-20% collisions. Systematic uncertainties for background subtraction and global scale uncertainties are given.

Differential away-side a function of Deltaphi 0%-20% collisions. Systematic uncertainties for background subtraction and global scale uncertainties are given.

Differential away-side a function of Deltaphi 0%-20% collisions. Systematic uncertainties for background subtraction and global scale uncertainties are given.

Differential away-side a function of Deltaphi 0%-20% collisions. Systematic uncertainties for background subtraction and global scale uncertainties are given.

Differential away-side a function of Deltaphi 0%-20% collisions. Systematic uncertainties for background subtraction and global scale uncertainties are given.

Differential away-side a function of Deltaphi 0%-20% collisions. Systematic uncertainties for background subtraction and global scale uncertainties are given.

Differential away-side a function of Deltaphi 0%-20% collisions. Systematic uncertainties for background subtraction and global scale uncertainties are given.

Differential away-side a function of Deltaphi 0%-20% collisions. Systematic uncertainties for background subtraction and global scale uncertainties are given.

Differential away-side a function of Deltaphi 0%-20% collisions. Systematic uncertainties for background subtraction and global scale uncertainties are given.

Differential away-side a function of Deltaphi 0%-20% collisions. Systematic uncertainties for background subtraction and global scale uncertainties are given.

Differential away-side a function of Deltaphi 0%-20% collisions. Systematic uncertainties for background subtraction and global scale uncertainties are given.

Differential away-side a function of Deltaphi 20%-40% collisions. Systematic uncertainties for background subtraction and global scale uncertainties are given.

Differential away-side a function of Deltaphi 20%-40% collisions. Systematic uncertainties for background subtraction and global scale uncertainties are given.

Differential away-side a function of Deltaphi 20%-40% collisions. Systematic uncertainties for background subtraction and global scale uncertainties are given.

Differential away-side a function of Deltaphi 20%-40% collisions. Systematic uncertainties for background subtraction and global scale uncertainties are given.

Differential away-side a function of Deltaphi 20%-40% collisions. Systematic uncertainties for background subtraction and global scale uncertainties are given.

Differential away-side a function of Deltaphi 20%-40% collisions. Systematic uncertainties for background subtraction and global scale uncertainties are given.

Differential away-side a function of Deltaphi 20%-40% collisions. Systematic uncertainties for background subtraction and global scale uncertainties are given.

Differential away-side a function of Deltaphi 20%-40% collisions. Systematic uncertainties for background subtraction and global scale uncertainties are given.

Differential away-side a function of Deltaphi 20%-40% collisions. Systematic uncertainties for background subtraction and global scale uncertainties are given.

Differential away-side a function of Deltaphi 20%-40% collisions. Systematic uncertainties for background subtraction and global scale uncertainties are given.

Differential away-side a function of Deltaphi 20%-40% collisions. Systematic uncertainties for background subtraction and global scale uncertainties are given.

Differential away-side a function of Deltaphi 20%-40% collisions. Systematic uncertainties for background subtraction and global scale uncertainties are given.

Differential away-side $\Delta_{AA}$ for ${\pi/2<\Delta\phi<\pi}$

Differential away-side $\Delta_{AA}$ for ${\pi/2<\Delta\phi<\pi}$

Differential away-side $\Delta_{AA}$ for ${\pi/2<\Delta\phi<\pi}$

<b>Note: in the paper, uncertainties are given in relative terms. The HEPData table contains absolute numbers. The original data file, containing relative uncertainties as in the paper, is available via the 'Resources' button above.</b> Differential cross sections, $d\sigma/d\Delta\phi$, in the $p_{T,jet}^{lead}$ region of $2.5 \;\mathrm{GeV} < p_{T,jet}^{lead} < 7 \;\mathrm{GeV}$ for $N_{jet} \geq 3$, as obtained from the data, ARIADNE MC simulations, and perturbative calculations at $\mathcal{O}(\alpha_{s})$ and $\mathcal{O}(\alpha_{s}^{2})$ accuracy. Other details are as in the caption to Table 1.

<b>Note: in the paper, uncertainties are given in relative terms. The HEPData table contains absolute numbers. The original data file, containing relative uncertainties as in the paper, is available via the 'Resources' button above.</b> Differential cross sections, $d\sigma/d\Delta\phi$, in the $p_{T,jet}^{lead}$ region of $7 \;\mathrm{GeV} < p_{T,jet}^{lead} < 12 \;\mathrm{GeV}$ for $N_{jet} \geq 1$, as obtained from the data, ARIADNE MC simulations, and perturbative calculations at $\mathcal{O}(\alpha_{s})$ and $\mathcal{O}(\alpha_{s}^{2})$ accuracy. Other details are as in the caption to Table 1.

<b>Note: in the paper, uncertainties are given in relative terms. The HEPData table contains absolute numbers. The original data file, containing relative uncertainties as in the paper, is available via the 'Resources' button above.</b> Differential cross sections, $d\sigma/d\Delta\phi$, in the $p_{T,jet}^{lead}$ region of $7 \;\mathrm{GeV} < p_{T,jet}^{lead} < 12 \;\mathrm{GeV}$ for $N_{jet} \geq 2$, as obtained from the data, ARIADNE MC simulations, and perturbative calculations at $\mathcal{O}(\alpha_{s})$ and $\mathcal{O}(\alpha_{s}^{2})$ accuracy. Other details are as in the caption to Table 1.

<b>Note: in the paper, uncertainties are given in relative terms. The HEPData table contains absolute numbers. The original data file, containing relative uncertainties as in the paper, is available via the 'Resources' button above.</b> Differential cross sections, $d\sigma/d\Delta\phi$, in the $p_{T,jet}^{lead}$ region of $7 \;\mathrm{GeV} < p_{T,jet}^{lead} < 12 \;\mathrm{GeV}$ for $N_{jet} \geq 3$, as obtained from the data, ARIADNE MC simulations, and perturbative calculations at $\mathcal{O}(\alpha_{s})$ and $\mathcal{O}(\alpha_{s}^{2})$ accuracy. Other details are as in the caption to Table 1.

<b>Note: in the paper, uncertainties are given in relative terms. The HEPData table contains absolute numbers. The original data file, containing relative uncertainties as in the paper, is available via the 'Resources' button above.</b> Differential cross sections, $d\sigma/d\Delta\phi$, in the $p_{T,jet}^{lead}$ region of $12 \;\mathrm{GeV} < p_{T,jet}^{lead} < 30 \;\mathrm{GeV}$ for $N_{jet} \geq 1$, as obtained from the data, ARIADNE MC simulations, and perturbative calculations at $\mathcal{O}(\alpha_{s})$ and $\mathcal{O}(\alpha_{s}^{2})$ accuracy. Other details are as in the caption to Table 1.

<b>Note: in the paper, uncertainties are given in relative terms. The HEPData table contains absolute numbers. The original data file, containing relative uncertainties as in the paper, is available via the 'Resources' button above.</b> Differential cross sections, $d\sigma/d\Delta\phi$, in the $p_{T,jet}^{lead}$ region of $12 \;\mathrm{GeV} < p_{T,jet}^{lead} < 30 \;\mathrm{GeV}$ for $N_{jet} \geq 2$, as obtained from the data, ARIADNE MC simulations, and perturbative calculations at $\mathcal{O}(\alpha_{s})$ and $\mathcal{O}(\alpha_{s}^{2})$ accuracy. Other details are as in the caption to Table 1.

<b>Note: in the paper, uncertainties are given in relative terms. The HEPData table contains absolute numbers. The original data file, containing relative uncertainties as in the paper, is available via the 'Resources' button above.</b> Differential cross sections, $d\sigma/d\Delta\phi$, in the $p_{T,jet}^{lead}$ region of $12 \;\mathrm{GeV} < p_{T,jet}^{lead} < 30 \;\mathrm{GeV}$ for $N_{jet} \geq 3$, as obtained from the data, ARIADNE MC simulations, and perturbative calculations at $\mathcal{O}(\alpha_{s})$ and $\mathcal{O}(\alpha_{s}^{2})$ accuracy. Other details are as in the caption to Table 1.

<b>Note: in the paper, uncertainties are given in relative terms. The HEPData table contains absolute numbers. The original data file, containing relative uncertainties as in the paper, is available via the 'Resources' button above.</b> Differential cross sections, $d\sigma/d\Delta\phi$, in the $Q^{2}$ region of $10 \;\mathrm{GeV}^{2} < Q^{2} < 50 \;\mathrm{GeV}^{2}$ for $N_{jet} \geq 1$, as obtained from the data, ARIADNE MC simulations, and perturbative calculations at $\mathcal{O}(\alpha_{s})$ and $\mathcal{O}(\alpha_{s}^{2})$ accuracy. Other details are as in the caption to Table 1.

<b>Note: in the paper, uncertainties are given in relative terms. The HEPData table contains absolute numbers. The original data file, containing relative uncertainties as in the paper, is available via the 'Resources' button above.</b> Differential cross sections, $d\sigma/d\Delta\phi$, in the $Q^{2}$ region of $10 \;\mathrm{GeV}^{2} < Q^{2} < 50 \;\mathrm{GeV}^{2}$ for $N_{jet} \geq 2$, as obtained from the data, ARIADNE MC simulations, and perturbative calculations at $\mathcal{O}(\alpha_{s})$ and $\mathcal{O}(\alpha_{s}^{2})$ accuracy. Other details are as in the caption to Table 1.

<b>Note: in the paper, uncertainties are given in relative terms. The HEPData table contains absolute numbers. The original data file, containing relative uncertainties as in the paper, is available via the 'Resources' button above.</b> Differential cross sections, $d\sigma/d\Delta\phi$, in the $Q^{2}$ region of $10 \;\mathrm{GeV}^{2} < Q^{2} < 50 \;\mathrm{GeV}^{2}$ for $N_{jet} \geq 3$, as obtained from the data, ARIADNE MC simulations, and perturbative calculations at $\mathcal{O}(\alpha_{s})$ and $\mathcal{O}(\alpha_{s}^{2})$ accuracy. Other details are as in the caption to Table 1.

<b>Note: in the paper, uncertainties are given in relative terms. The HEPData table contains absolute numbers. The original data file, containing relative uncertainties as in the paper, is available via the 'Resources' button above.</b> Differential cross sections, $d\sigma/d\Delta\phi$, in the $Q^{2}$ region of $50 \;\mathrm{GeV}^{2} < Q^{2} < 100 \;\mathrm{GeV}^{2}$ for $N_{jet} \geq 1$, as obtained from the data, ARIADNE MC simulations, and perturbative calculations at $\mathcal{O}(\alpha_{s})$ and $\mathcal{O}(\alpha_{s}^{2})$ accuracy. Other details are as in the caption to Table 1.

<b>Note: in the paper, uncertainties are given in relative terms. The HEPData table contains absolute numbers. The original data file, containing relative uncertainties as in the paper, is available via the 'Resources' button above.</b> Differential cross sections, $d\sigma/d\Delta\phi$, in the $Q^{2}$ region of $50 \;\mathrm{GeV}^{2} < Q^{2} < 100 \;\mathrm{GeV}^{2}$ for $N_{jet} \geq 2$, as obtained from the data, ARIADNE MC simulations, and perturbative calculations at $\mathcal{O}(\alpha_{s})$ and $\mathcal{O}(\alpha_{s}^{2})$ accuracy. Other details are as in the caption to Table 1.

<b>Note: in the paper, uncertainties are given in relative terms. The HEPData table contains absolute numbers. The original data file, containing relative uncertainties as in the paper, is available via the 'Resources' button above.</b> Differential cross sections, $d\sigma/d\Delta\phi$, in the $Q^{2}$ region of $50 \;\mathrm{GeV}^{2} < Q^{2} < 100 \;\mathrm{GeV}^{2}$ for $N_{jet} \geq 3$, as obtained from the data, ARIADNE MC simulations, and perturbative calculations at $\mathcal{O}(\alpha_{s})$ and $\mathcal{O}(\alpha_{s}^{2})$ accuracy. Other details are as in the caption to Table 1.

<b>Note: in the paper, uncertainties are given in relative terms. The HEPData table contains absolute numbers. The original data file, containing relative uncertainties as in the paper, is available via the 'Resources' button above.</b> Differential cross sections, $d\sigma/d\Delta\phi$, in the $Q^{2}$ region of $100 \;\mathrm{GeV}^{2} < Q^{2} < 350 \;\mathrm{GeV}^{2}$ for $N_{jet} \geq 1$, as obtained from the data, ARIADNE MC simulations, and perturbative calculations at $\mathcal{O}(\alpha_{s})$ and $\mathcal{O}(\alpha_{s}^{2})$ accuracy. Other details are as in the caption to Table 1.

<b>Note: in the paper, uncertainties are given in relative terms. The HEPData table contains absolute numbers. The original data file, containing relative uncertainties as in the paper, is available via the 'Resources' button above.</b> Differential cross sections, $d\sigma/d\Delta\phi$, in the $Q^{2}$ region of $100 \;\mathrm{GeV}^{2} < Q^{2} < 350 \;\mathrm{GeV}^{2}$ for $N_{jet} \geq 2$, as obtained from the data, ARIADNE MC simulations, and perturbative calculations at $\mathcal{O}(\alpha_{s})$ and $\mathcal{O}(\alpha_{s}^{2})$ accuracy. Other details are as in the caption to Table 1.

<b>Note: in the paper, uncertainties are given in relative terms. The HEPData table contains absolute numbers. The original data file, containing relative uncertainties as in the paper, is available via the 'Resources' button above.</b> Differential cross sections, $d\sigma/d\Delta\phi$, in the $Q^{2}$ region of $100 \;\mathrm{GeV}^{2} < Q^{2} < 350 \;\mathrm{GeV}^{2}$ for $N_{jet} \geq 3$, as obtained from the data, ARIADNE MC simulations, and perturbative calculations at $\mathcal{O}(\alpha_{s})$ and $\mathcal{O}(\alpha_{s}^{2})$ accuracy. Other details are as in the caption to Table 1.

QED correction factors for inclusive measurement, as estimated with RAPGAP.

QED correction factors for $2.5 \;\mathrm{GeV} < p_{T,jet}^{lead} < 7 \;\mathrm{GeV}$ and $N_{jet} \geq 1$, as estimated with RAPGAP.

QED correction factors for $2.5 \;\mathrm{GeV} < p_{T,jet}^{lead} < 7 \;\mathrm{GeV}$ and $N_{jet} \geq 2$, as estimated with RAPGAP.

QED correction factors for $2.5 \;\mathrm{GeV} < p_{T,jet}^{lead} < 7 \;\mathrm{GeV}$ and $N_{jet} \geq 3$, as estimated with RAPGAP.

QED correction factors for $7 \;\mathrm{GeV} < p_{T,jet}^{lead} < 12 \;\mathrm{GeV}$ and $N_{jet} \geq 1$, as estimated with RAPGAP.

QED correction factors for $7 \;\mathrm{GeV} < p_{T,jet}^{lead} < 12 \;\mathrm{GeV}$ and $N_{jet} \geq 2$, as estimated with RAPGAP.

QED correction factors for $7 \;\mathrm{GeV} < p_{T,jet}^{lead} < 12 \;\mathrm{GeV}$ and $N_{jet} \geq 3$, as estimated with RAPGAP.

QED correction factors for $12 \;\mathrm{GeV} < p_{T,jet}^{lead} < 30 \;\mathrm{GeV}$ and $N_{jet} \geq 1$, as estimated with RAPGAP.

QED correction factors for $12 \;\mathrm{GeV} < p_{T,jet}^{lead} < 30 \;\mathrm{GeV}$ and $N_{jet} \geq 2$, as estimated with RAPGAP.

QED correction factors for $12 \;\mathrm{GeV} < p_{T,jet}^{lead} < 30 \;\mathrm{GeV}$ and $N_{jet} \geq 3$, as estimated with RAPGAP.

QED correction factors for $10 \;\mathrm{GeV}^{2} < Q^{2} < 50 \;\mathrm{GeV}^{2}$ and $N_{jet} \geq 1$, as estimated with RAPGAP.

QED correction factors for $10 \;\mathrm{GeV}^{2} < Q^{2} < 50 \;\mathrm{GeV}^{2}$ and $N_{jet} \geq 2$, as estimated with RAPGAP.

QED correction factors for $10 \;\mathrm{GeV}^{2} < Q^{2} < 50 \;\mathrm{GeV}^{2}$ and $N_{jet} \geq 3$, as estimated with RAPGAP.

QED correction factors for $50 \;\mathrm{GeV}^{2} < Q^{2} < 100 \;\mathrm{GeV}^{2}$ and $N_{jet} \geq 1$, as estimated with RAPGAP.

QED correction factors for $50 \;\mathrm{GeV}^{2} < Q^{2} < 100 \;\mathrm{GeV}^{2}$ and $N_{jet} \geq 2$, as estimated with RAPGAP.

QED correction factors for $50 \;\mathrm{GeV}^{2} < Q^{2} < 100 \;\mathrm{GeV}^{2}$ and $N_{jet} \geq 3$, as estimated with RAPGAP.

QED correction factors for $100 \;\mathrm{GeV}^{2} < Q^{2} < 350 \;\mathrm{GeV}^{2}$ and $N_{jet} \geq 1$, as estimated with RAPGAP.

QED correction factors for $100 \;\mathrm{GeV}^{2} < Q^{2} < 350 \;\mathrm{GeV}^{2}$ and $N_{jet} \geq 2$, as estimated with RAPGAP.

QED correction factors for $100 \;\mathrm{GeV}^{2} < Q^{2} < 350 \;\mathrm{GeV}^{2}$ and $N_{jet} \geq 3$, as estimated with RAPGAP.

The correlation matrix for the inclusive measurement. The azimuthal correlation angle $\Delta\phi$ of each lepton--leading-jet pair was assigned a bin ID between 0 to 59 segmented uniformly from 0 to $\pi$. This bin ID was offset by multiples of 60 based on the jet multiplicity so that the pair from a single jet event, as suggested by the MC simulation, was assigned a value between 0 to 59, dijet events were given 60 to 119, trijet 120 to 179, and four or more jets 180 to 239.

The correlation matrix for $2.5 \;\mathrm{GeV} < p_{T,jet}^{lead} < 7 \;\mathrm{GeV}$. Other details are as in the caption to Fig. 13.

The correlation matrix for $7 \;\mathrm{GeV} < p_{T,jet}^{lead} < 12 \;\mathrm{GeV}$. Other details are as in the caption to Fig. 13.

The correlation matrix for $12 \;\mathrm{GeV} < p_{T,jet}^{lead} < 30 \;\mathrm{GeV}$. Other details are as in the caption to Fig. 13.

The correlation matrix for $10 \;\mathrm{GeV}^{2} < Q^{2} < 50 \;\mathrm{GeV}^{2}$. Other details are as in the caption to Fig. 13.

The correlation matrix for $50 \;\mathrm{GeV}^{2} < Q^{2} < 100 \;\mathrm{GeV}^{2}$. Other details are as in the caption to Fig. 13.

The correlation matrix for $100 \;\mathrm{GeV}^{2} < Q^{2} < 350 \;\mathrm{GeV}^{2}$. Other details are as in the caption to Fig. 13.

The systematic covariance matrix for the $e^+e^- \to \pi^+ \pi^- \pi^0$ cross section measurement at the Belle II. The 212 x 212 matrix of the energy ranges from 0.62 to 3.50 GeV. This covariance matrix includes all systematic uncertainty given in Table I. The total covariance matrix for the measured cross section can be obtained by adding statistical and systematic covariance matrices.

This table provides the ``inverse'' of the total (stat.+ sys.) covariance matrix. This matrix can be used for a chi-square fit of the mass spectrum. We provide this inverse matrix since special care is needed to take the inverse of the given covariance matrix.