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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Signal region detector-level distribution for the observable $p_{\mathrm{T}}^{\mathrm{lead}\, \ell}$.

Signal region detector-level distribution for the observable $m_{e\mu}$.

Signal region detector-level distribution for the observable $p_{\mathrm{T}}^{e\mu}$.

Measured fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $|y_{e\mu}|$

Relative systematic uncertainties for the fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $|y_{e\mu}|$

Measured fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $|\Delta \phi(e \mu)|$

Relative systematic uncertainties for the fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $|\Delta \phi(e \mu)|$

Measured fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $ \cos\theta^{\ast}$

Relative systematic uncertainties for the fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $ \cos\theta^{\ast}$

Measured fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $p_{\mathrm{T}}^{\mathrm{lead}\, \ell}$

Relative systematic uncertainties for the fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $p_{\mathrm{T}}^{\mathrm{lead}\, \ell}$

Measured fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $m_{e\mu}$

Relative systematic uncertainties for the fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $m_{e\mu}$

Measured fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $p_{\mathrm{T}}^{e\mu}$

Relative systematic uncertainties for the fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $p_{\mathrm{T}}^{e\mu}$

The statistical correlation coefficients (in percentage) between bins for the measured fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $|y_{e\mu}|$

The total correlation coefficients (in percentage) between bins for the measured fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $|y_{e\mu}|$

The statistical correlation coefficients (in percentage) between bins for the measured fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $|\Delta \phi(e \mu)|$

The total correlation coefficients (in percentage) between bins for the measured fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $|\Delta \phi(e \mu)|$

The statistical correlation coefficients (in percentage) between bins for the measured fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $ \cos\theta^{\ast}$

The total correlation coefficients (in percentage) between bins for the measured fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $ \cos\theta^{\ast}$

The statistical correlation coefficients (in percentage) between bins for the measured fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $p_{\mathrm{T}}^{\mathrm{lead}\, \ell}$

The total correlation coefficients (in percentage) between bins for the measured fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $p_{\mathrm{T}}^{\mathrm{lead}\, \ell}$

The statistical correlation coefficients (in percentage) between bins for the measured fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $m_{e\mu}$

The total correlation coefficients (in percentage) between bins for the measured fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $m_{e\mu}$

The statistical correlation coefficients (in percentage) between bins for the measured fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $p_{\mathrm{T}}^{e\mu}$

The total correlation coefficients (in percentage) between bins for the measured fiducial differential cross-section of $WW \rightarrow e^{\pm}\nu\mu^{\mp}\nu$ production for the observable $p_{\mathrm{T}}^{e\mu}$

The $v_{dyn}$ and the three terms of $v_{dyn}$ vs $\sqrt{\langle N_{ch}\rangle \langle N_{\gamma}\rangle }$ for mixed events. $Corr_{\gamma\,-ch}^{real}$ is plotted.

The $v_{dyn}$ and the three terms of $v_{dyn}$ vs $\sqrt{\langle N_{ch}\rangle \langle N_{\gamma}\rangle }$ for mixed events. $Corr_{\gamma\,-ch}^{mixed}$ is plotted.

The $v_{dyn}$ and the three terms of $v_{dyn}$ vs $\sqrt{\langle N_{ch}\rangle \langle N_{\gamma}\rangle }$ for mixed events. $\omega_{\gamma}^{real}$ is plotted.

The $v_{dyn}$ and the three terms of $v_{dyn}$ vs $\sqrt{\langle N_{ch}\rangle \langle N_{\gamma}\rangle }$ for mixed events. $\omega_{\gamma}^{mixed}$ is plotted.

The $v_{dyn}$ and the three terms of $v_{dyn}$ vs $\sqrt{\langle N_{ch}\rangle \langle N_{\gamma}\rangle }$ for mixed events. $v_{dyn}^{real}$ is plotted.

The $v_{dyn}$ and the three terms of $v_{dyn}$ vs $\sqrt{\langle N_{ch}\rangle \langle N_{\gamma}\rangle }$ for mixed events. $v_{dyn}^{mixed}$ is plotted.

The values of the observable $v_{dyn}^{ch-\gamma}$ for the same side.

The values of the observable $v_{dyn}^{ch-\gamma}$ for the same side.

The values of the observable $v_{dyn}^{ch-\gamma}$ for the away-side.

The values of the observable $v_{dyn}^{ch-\gamma}$ for the away-side.

The correlation between positive and negative charged particles measured by the FTPC and photons measured by the PMD using $v_{dyn}$ for real events.

$r_{m,1}$ vs multiplicity for first order of m.

$r_{m,1}$ vs multiplicity for first order of m.

$r_{m,1}$ vs multiplicity for second order of m.

$r_{m,1}$ vs multiplicity for second order of m.

$r_{m,1}$ vs multiplicity for third order of m.

$r_{m,1}$ vs multiplicity for third order of m.

The moments $r_{m,1}$(m=1-3) for real and mixed events as a function of order m in a fixed multiplicity bin of 47$\langle \sqrt{\langle N_{ch}\rangle \langle N_{\gamma}\rangle }\langle 54$.

The $\Lambda\Lambda$ interaction parameters from this experiment.

The three-point correlator, $\gamma$, as a function of centrality for Au+Au collisions at 19.6 GeV.

The three-point correlator, $\gamma$, as a function of centrality for Au+Au collisions at 11.5 GeV.

The three-point correlator, $\gamma$, as a function of centrality for Au+Au collisions at 7.7.

The two-particle correlation as a function of centrality for Au+Au collisions at 62.4 GeV.

The two-particle correlation as a function of centrality for Au+Au collisions at 39 GeV.

The two-particle correlation as a function of centrality for Au+Au collisions at 27 GeV.

The two-particle correlation as a function of centrality for Au+Au collisions at 19.6 GeV.

The two-particle correlation as a function of centrality for Au+Au collisions at 11.5 GeV.

The two-particle correlation as a function of centrality for Au+Au collisions at 7.7 GeV.

$H_{SS}-H{OS}$, as a function of beam energy for 60-80% centrality in Au+Au collisions.

$H_{SS}-H{OS}$, as a function of beam energy for 30-60% centrality in Au+Au collisions.

$H_{SS}-H{OS}$, as a function of beam energy for 10-30% centrality in Au+Au collisions.

Sample correlations in $\Delta\phi$ ($|\Delta\eta|<$ 1.78) for 3 $<$ $p_T^{trigger}$ $<$ 6 GeV/$c$ and 1.5 GeV/$c$ $<$ $p_T^{associated}$ $<$ $p_T^{trigger}$ for 0-60% Cu+Cu at $\sqrt{s_{NN}}$ = 62.4 GeV, 0-80% Au+Au at $\sqrt{s_{NN}}$ = 62.4 GeV, 0-95% $d$+Au at $\sqrt{s_{NN}}$ = 200 GeV, 0-60% Cu+Cu at $\sqrt{s_{NN}}$ = 200 GeV, 40-80% Au+Au at $\sqrt{s_{NN}}$ = 200 GeV, and 0-12% central Au+Au at $\sqrt{s_{NN}}$ = 200 GeV. The data are averaged between positive and negative $\Delta\phi$ and reflected in the plot.

Background subtracted sample correlations for 3 $<$ $p_T^{trigger}$ $<$ 6 GeV/$c$ and 1.5 GeV/$c$ $<$ $p_T^{associated}$ $<$ $p_T^{trigger}$ on the near-side for 0-60% Cu+Cu at $\sqrt{s_{NN}}$ = 62.4 GeV, 0-80% Au+Au at $\sqrt{s_{NN}}$ = 62.4 GeV, 0-95% $d$+Au collisions at $\sqrt{s_{NN}}$ = 200 GeV, 0-60% Cu+Cu at $\sqrt{s_{NN}}$ = 200 GeV, 40-80% Au+Au at $\sqrt{s_{NN}}$ = 200 GeV and 0-12% central Au+Au at $\sqrt{s_{NN}}$ = 200 GeV. The dependence of the jet-like correlation is shown as a function of $\Delta\eta$ ($|\Delta\phi|<$ 0.78). The data are averaged between positive and negative $\Delta\eta$.

Background subtracted sample correlations for 3 $<$ $p_T^{trigger}$ $<$ 6 GeV/$c$ and 1.5 GeV/$c$ $<$ $p_T^{associated}$ $<$ $p_T^{trigger}$ on the near-side for 0-60% Cu+Cu at $\sqrt{s_{NN}}$ = 62.4 GeV, 0-80% Au+Au at $\sqrt{s_{NN}}$ = 62.4 GeV, 0-95% $d$+Au collisions at $\sqrt{s_{NN}}$ = 200 GeV, 0-60% Cu+Cu at $\sqrt{s_{NN}}$ = 200 GeV, 40-80% Au+Au at $\sqrt{s_{NN}}$ = 200 GeV and 0-12% central Au+Au at $\sqrt{s_{NN}}$ = 200 GeV. The dependence of the jet-like correlation is shown as a function of $\Delta\phi$ ($|\Delta\eta|<$ 1.78). The data are averaged between positive and negative $\Delta\phi$.

Dependence of jet-like yield on $N_{part}$ for 3 $<$ $p_T^{trigger}$ $<$ 6 GeV/$c$ and 1.5 GeV/$c$ $<$ $p_T^{associated}$ $<$ $p_T^{trigger}$ for Cu+Cu at $\sqrt{s_{NN}}$ = 62.4 GeV. 5% systematic error due to the uncertainty on the associated particle's efficiency is not shown.

Dependence of jet-like yield on $N_{part}$ for 3 $<$ $p_T^{trigger}$ $<$ 6 GeV/$c$ and 1.5 GeV/$c$ $<$ $p_T^{associated}$ $<$ $p_T^{trigger}$ for Au+Au at $\sqrt{s_{NN}}$ = 62.4 GeV. 5% systematic error due to the uncertainty on the associated particle's efficiency is not shown.

Dependence of jet-like yield on $N_{part}$ for 3 $<$ $p_T^{trigger}$ $<$ 6 GeV/$c$ and 1.5 GeV/$c$ $<$ $p_T^{associated}$ $<$ $p_T^{trigger}$ for $d$+Au at $\sqrt{s_{NN}}$ = 200 GeV. 5% systematic error due to the uncertainty on the associated particle's efficiency is not shown.

Dependence of jet-like yield on $N_{part}$ for 3 $<$ $p_T^{trigger}$ $<$ 6 GeV/$c$ and 1.5 GeV/$c$ $<$ $p_T^{associated}$ $<$ $p_T^{trigger}$ for Cu+Cu at $\sqrt{s_{NN}}$ = 200 GeV. 5% systematic error due to the uncertainty on the associated particle's efficiency is not shown.

Dependence of jet-like yield on $N_{part}$ for 3 $<$ $p_T^{trigger}$ $<$ 6 GeV/$c$ and 1.5 GeV/$c$ $<$ $p_T^{associated}$ $<$ $p_T^{trigger}$ for Au+Au at $\sqrt{s_{NN}}$ = 200 GeV. 5% systematic error due to the uncertainty on the associated particle's efficiency is not shown.

Dependence of jet-like yield on $p_T^{\mathrm{trigger}}$ for 0-60% Cu+Cu at $\sqrt{s_{NN}}$ = 62.4 GeV, 0-80% Au+Au at $\sqrt{s_{NN}}$ = 62.4 GeV, 0-95% $d$+Au collisions at $\sqrt{s_{NN}}$ = 200 GeV, 0-60% Cu+Cu at $\sqrt{s_{NN}}$ = 200 GeV, 40-80% Au+Au at $\sqrt{s_{NN}}$ = 200 GeV and 0-12% central Au+Au at $\sqrt{s_{NN}}$ = 200 GeV. The 5% systematic error due to the uncertainty on the associated particle's efficiency is not shown.

Dependence of jet-like yield on $p_T^{\mathrm{associated}}$ for 3 $<$ $p_T^{trigger}$ $<$ 6 GeV/$c$ for 0-60% Cu+Cu and 0-80% Au+Au collisions at $\sqrt{s_{NN}}$ = 62.4 GeV and 0-95% $d$+Au, 0-60% Cu+Cu, 0-12% Au+Au and 40-80% Au+Au collisions at $\sqrt{s_{NN}}$ = 200 GeV. The 5% systematic error due to the uncertainty on the associated particle's efficiency is not shown.

Dependence of the widths in $\Delta\phi$ on $p_T^{\mathrm{trigger}}$ for 1.5 GeV/$c$ $<$ $p_T^{associated}$ $<$ $p_T^{trigger}$ for 0-95% $d$+Au, 0-60% Cu+Cu at $\sqrt{s_{NN}}$ = 62.4 GeV and $\sqrt{s_{NN}}$ = 200 GeV, 0-80% Au+Au at $\sqrt{s_{NN}}$ = 62.4 GeV, and 0-12% and 40-80% Au+Au at $\sqrt{s_{NN}}$ = 200 GeV.

Dependence of the widths in $\Delta\phi$ on $p_T^{\mathrm{associated}}$ for 3 $<$ $p_T^{trigger}$ $<$ 6 GeV/$c$ for 0-95% $d$+Au, 0-60% Cu+Cu at $\sqrt{s_{NN}}$ = 62.4 GeV and $\sqrt{s_{NN}}$ = 200 GeV, 0-80% Au+Au at $\sqrt{s_{NN}}$ = 62.4 GeV, and 0-12% and 40-80% Au+Au at $\sqrt{s_{NN}}$ = 200 GeV.

Dependence of the widths in $\Delta\phi$ on $N_{part}$ for 3 $<$ $p_T^{trigger}$ $<$ 6 GeV/$c$ and 1.5 GeV/$c$ $<$ $p_T^{associated}$ $<$ $p_T^{trigger}$ for 0-60% Cu+Cu at $\sqrt{s_{NN}}$ = 62.4 GeV.

Dependence of the widths in $\Delta\phi$ on $N_{part}$ for 3 $<$ $p_T^{trigger}$ $<$ 6 GeV/$c$ and 1.5 GeV/$c$ $<$ $p_T^{associated}$ $<$ $p_T^{trigger}$ for 0-80% Au+Au at $\sqrt{s_{NN}}$ = 62.4 GeV.

Dependence of the widths in $\Delta\phi$ on $N_{part}$ for 3 $<$ $p_T^{trigger}$ $<$ 6 GeV/$c$ and 1.5 GeV/$c$ $<$ $p_T^{associated}$ $<$ $p_T^{trigger}$ for 0-95% $d$+Au at $\sqrt{s_{NN}}$ = 200 GeV.

Dependence of the widths in $\Delta\phi$ on $N_{part}$ for 3 $<$ $p_T^{trigger}$ $<$ 6 GeV/$c$ and 1.5 GeV/$c$ $<$ $p_T^{associated}$ $<$ $p_T^{trigger}$ for 0-60% Cu+Cu at $\sqrt{s_{NN}}$ = 200 GeV.

Dependence of the widths in $\Delta\phi$ on $N_{part}$ for 3 $<$ $p_T^{trigger}$ $<$ 6 GeV/$c$ and 1.5 GeV/$c$ $<$ $p_T^{associated}$ $<$ $p_T^{trigger}$ for Au+Au at $\sqrt{s_{NN}}$ = 200 GeV.

Dependence of the widths in $\Delta\eta$ on $p_T^{\mathrm{trigger}}$ for 1.5 GeV/$c$ $<$ $p_T^{associated}$ $<$ $p_T^{trigger}$ for 0-95% $d$+Au, 0-60% Cu+Cu at $\sqrt{s_{NN}}$ = 62.4 GeV and $\sqrt{s_{NN}}$ = 200 GeV, 0-80% Au+Au at $\sqrt{s_{NN}}$ = 62.4 GeV, and 0-12% and 40-80% Au+Au at $\sqrt{s_{NN}}$ = 200 GeV.

Dependence of the widths in $\Delta\eta$ on $p_T^{\mathrm{associated}}$ for 3 $<$ $p_T^{trigger}$ $<$ 6 GeV/$c$ for 0-95% $d$+Au, 0-60% Cu+Cu at $\sqrt{s_{NN}}$ = 62.4 GeV and $\sqrt{s_{NN}}$ = 200 GeV, 0-80% Au+Au at $\sqrt{s_{NN}}$ = 62.4 GeV, and 0-12% and 40-80% Au+Au at $\sqrt{s_{NN}}$ = 200 GeV.

Dependence of the widths in $\Delta\eta$ on $N_{part}$ for 3 $<$ $p_T^{trigger}$ $<$ 6 GeV/$c$ and 1.5 GeV/$c$ $<$ $p_T^{associated}$ $<$ $p_T^{trigger}$ for 0-60% Cu+Cu at $\sqrt{s_{NN}}$ = 62.4 GeV.

Dependence of the widths in $\Delta\eta$ on $N_{part}$ for 3 $<$ $p_T^{trigger}$ $<$ 6 GeV/$c$ and 1.5 GeV/$c$ $<$ $p_T^{associated}$ $<$ $p_T^{trigger}$ for 0-80% Au+Au at $\sqrt{s_{NN}}$ = 62.4 GeV.

Dependence of the widths in $\Delta\eta$ on $N_{part}$ for 3 $<$ $p_T^{trigger}$ $<$ 6 GeV/$c$ and 1.5 GeV/$c$ $<$ $p_T^{associated}$ $<$ $p_T^{trigger}$ for 0-95% $d$+Au at $\sqrt{s_{NN}}$ = 200 GeV.

Dependence of the widths in $\Delta\eta$ on $N_{part}$ for 3 $<$ $p_T^{trigger}$ $<$ 6 GeV/$c$ and 1.5 GeV/$c$ $<$ $p_T^{associated}$ $<$ $p_T^{trigger}$ for 0-60% Cu+Cu at $\sqrt{s_{NN}}$ = 200 GeV.

Dependence of the widths in $\Delta\eta$ on $N_{part}$ for 3 $<$ $p_T^{trigger}$ $<$ 6 GeV/$c$ and 1.5 GeV/$c$ $<$ $p_T^{associated}$ $<$ $p_T^{trigger}$ for Au+Au at $\sqrt{s_{NN}}$ = 200 GeV.

Dependence of ridge yield on $N_{part}$ for 3 $<$ $p_T^{trigger}$ $<$ 6 GeV/$c$ and 1.5 GeV/$c$ $<$ $p_T^{associated}$ $<$ $p_T^{trigger}$ for Cu+Cu at $\sqrt{s_{NN}}$ = 62.4 GeV.

Dependence of ridge yield on $N_{part}$ for 3 $<$ $p_T^{trigger}$ $<$ 6 GeV/$c$ and 1.5 GeV/$c$ $<$ $p_T^{associated}$ $<$ $p_T^{trigger}$ for Au+Au at $\sqrt{s_{NN}}$ = 62.4 GeV.

Dependence of ridge yield on $N_{part}$ for 3 $<$ $p_T^{trigger}$ $<$ 6 GeV/$c$ and 1.5 GeV/$c$ $<$ $p_T^{associated}$ $<$ $p_T^{trigger}$ for Cu+Cu at $\sqrt{s_{NN}}$ = 200 GeV.

Dependence of ridge yield on $N_{part}$ for 3 $<$ $p_T^{trigger}$ $<$ 6 GeV/$c$ and 1.5 GeV/$c$ $<$ $p_T^{associated}$ $<$ $p_T^{trigger}$ for Au+Au at $\sqrt{s_{NN}}$ = 200 GeV.

Ratio of the ridge and jet-like yields on $N_{part}$ for 3 $<$ $p_T^{trigger}$ $<$ 6 GeV/$c$ and 1.5 GeV/$c$ $<$ $p_T^{associated}$ $<$ $p_T^{trigger}$ for Cu+Cu at $\sqrt{s_{NN}}$ = 62.4 GeV.

Ratio of the ridge and jet-like yields on $N_{part}$ for 3 $<$ $p_T^{trigger}$ $<$ 6 GeV/$c$ and 1.5 GeV/$c$ $<$ $p_T^{associated}$ $<$ $p_T^{trigger}$ for Au+Au at $\sqrt{s_{NN}}$ = 62.4 GeV.

Ratio of the ridge and jet-like yields on $N_{part}$ for 3 $<$ $p_T^{trigger}$ $<$ 6 GeV/$c$ and 1.5 GeV/$c$ $<$ $p_T^{associated}$ $<$ $p_T^{trigger}$ for Cu+Cu at $\sqrt{s_{NN}}$ = 200 GeV.

Ratio of the ridge and jet-like yields on $N_{part}$ for 3 $<$ $p_T^{trigger}$ $<$ 6 GeV/$c$ and 1.5 GeV/$c$ $<$ $p_T^{associated}$ $<$ $p_T^{trigger}$ for Au+Au at $\sqrt{s_{NN}}$ = 200 GeV.

Dependence of $V_{3\Delta}/V_{2\Delta}$ on $N_{part}$ for 3 $<$ $p_T^{trigger}$ $<$ 6 GeV/$c$ and 1.5 GeV/$c$ $<$ $p_T^{associated}$ $<$ $p_T^{trigger}$ for Cu+Cu at $\sqrt{s_{NN}}$ = 62.4 GeV.

Dependence of $V_{3\Delta}/V_{2\Delta}$ on $N_{part}$ for 3 $<$ $p_T^{trigger}$ $<$ 6 GeV/$c$ and 1.5 GeV/$c$ $<$ $p_T^{associated}$ $<$ $p_T^{trigger}$ for Au+Au at $\sqrt{s_{NN}}$ = 62.4 GeV.

Dependence of $V_{3\Delta}/V_{2\Delta}$ on $N_{part}$ for 3 $<$ $p_T^{trigger}$ $<$ 6 GeV/$c$ and 1.5 GeV/$c$ $<$ $p_T^{associated}$ $<$ $p_T^{trigger}$ for $d$+Au at $\sqrt{s_{NN}}$ = 200 GeV.

Dependence of $V_{3\Delta}/V_{2\Delta}$ on $N_{part}$ for 3 $<$ $p_T^{trigger}$ $<$ 6 GeV/$c$ and 1.5 GeV/$c$ $<$ $p_T^{associated}$ $<$ $p_T^{trigger}$ for Cu+Cu at $\sqrt{s_{NN}}$ = 200 GeV.

Dependence of $V_{3\Delta}/V_{2\Delta}$ on $N_{part}$ for 3 $<$ $p_T^{trigger}$ $<$ 6 GeV/$c$ and 1.5 GeV/$c$ $<$ $p_T^{associated}$ $<$ $p_T^{trigger}$ for Au+Au at $\sqrt{s_{NN}}$ = 200 GeV.

FIG. 1. (Color online) Perspective views of $2 \mathrm{D}$ charge-independent angular correlations $\Delta \rho / \sqrt{\rho_{\mathrm{ref}}}$ on $\left(\eta_{\Delta}, \phi_{\Delta}\right)$ for Au-Au collisions at $\sqrt{s_{N N}}=200$ and $62 \mathrm{GeV}$ (top and bottom rows, respectively). Centrality increases left to right from most peripheral to most central. Corrected total cross-section fractions are (left to right) $84 \%-93 \%, 55 \%-64 \%, 18 \%-28 \%,$ and $0 \%-5 \%$ for the $200-\mathrm{GeV}$ data and $84 \%-95 \%, 56 \%-65 \%$ $18 \%-28 \%,$ and $0 \%-5 \%$ for the $62 \mathrm{GeV}$ data (see Tables III and IV).

FIG. 1. (Color online) Perspective views of $2 \mathrm{D}$ charge-independent angular correlations $\Delta \rho / \sqrt{\rho_{\mathrm{ref}}}$ on $\left(\eta_{\Delta}, \phi_{\Delta}\right)$ for Au-Au collisions at $\sqrt{s_{N N}}=200$ and $62 \mathrm{GeV}$ (top and bottom rows, respectively). Centrality increases left to right from most peripheral to most central. Corrected total cross-section fractions are (left to right) $84 \%-93 \%, 55 \%-64 \%, 18 \%-28 \%,$ and $0 \%-5 \%$ for the $200-\mathrm{GeV}$ data and $84 \%-95 \%, 56 \%-65 \%$ $18 \%-28 \%,$ and $0 \%-5 \%$ for the $62 \mathrm{GeV}$ data (see Tables III and IV).

FIG. 1. (Color online) Perspective views of $2 \mathrm{D}$ charge-independent angular correlations $\Delta \rho / \sqrt{\rho_{\mathrm{ref}}}$ on $\left(\eta_{\Delta}, \phi_{\Delta}\right)$ for Au-Au collisions at $\sqrt{s_{N N}}=200$ and $62 \mathrm{GeV}$ (top and bottom rows, respectively). Centrality increases left to right from most peripheral to most central. Corrected total cross-section fractions are (left to right) $84 \%-93 \%, 55 \%-64 \%, 18 \%-28 \%,$ and $0 \%-5 \%$ for the $200-\mathrm{GeV}$ data and $84 \%-95 \%, 56 \%-65 \%$ $18 \%-28 \%,$ and $0 \%-5 \%$ for the $62 \mathrm{GeV}$ data (see Tables III and IV).

FIG. 1. (Color online) Perspective views of $2 \mathrm{D}$ charge-independent angular correlations $\Delta \rho / \sqrt{\rho_{\mathrm{ref}}}$ on $\left(\eta_{\Delta}, \phi_{\Delta}\right)$ for Au-Au collisions at $\sqrt{s_{N N}}=200$ and $62 \mathrm{GeV}$ (top and bottom rows, respectively). Centrality increases left to right from most peripheral to most central. Corrected total cross-section fractions are (left to right) $84 \%-93 \%, 55 \%-64 \%, 18 \%-28 \%,$ and $0 \%-5 \%$ for the $200-\mathrm{GeV}$ data and $84 \%-95 \%, 56 \%-65 \%$ $18 \%-28 \%,$ and $0 \%-5 \%$ for the $62 \mathrm{GeV}$ data (see Tables III and IV).

FIG. 1. (Color online) Perspective views of $2 \mathrm{D}$ charge-independent angular correlations $\Delta \rho / \sqrt{\rho_{\mathrm{ref}}}$ on $\left(\eta_{\Delta}, \phi_{\Delta}\right)$ for Au-Au collisions at $\sqrt{s_{N N}}=200$ and $62 \mathrm{GeV}$ (top and bottom rows, respectively). Centrality increases left to right from most peripheral to most central. Corrected total cross-section fractions are (left to right) $84 \%-93 \%, 55 \%-64 \%, 18 \%-28 \%,$ and $0 \%-5 \%$ for the $200-\mathrm{GeV}$ data and $84 \%-95 \%, 56 \%-65 \%$ $18 \%-28 \%,$ and $0 \%-5 \%$ for the $62 \mathrm{GeV}$ data (see Tables III and IV).

FIG. 2. (Color online) Fit decomposition of the $46 \%-56 \%$ centrality data for 62 -GeV Au-Au collisions. The top panels show from left to right the corrected data, model fit, fit residuals (data - model), and same-side 2D Gaussian. The bottom panels similarly show the away-side azimuth dipole, the nonjet azimuth quadrupole, the 1D $\eta_{\Delta}$ Gaussian, and the 2D exponential. This centrality is just below the sharp transition at $v_{\text {trans }}=3$. Fit residuals (c) are scaled up eightfold relative to the data.

FIG. 3. Fit parameters for $\left(\eta_{\Delta}, \phi_{\Delta}\right)$ correlation data from Au-Au collisions at $\sqrt{s_{N N}}=62$ (open symbols) and 200 GeV (solid symbols) versus centrality measure $\nu$ computed at fixed energy $(200 \mathrm{GeV})$. The SS $2 \mathrm{D}$ Gaussian amplitudes, $\eta_{\Delta}$ widths, and $\phi_{\Delta}$ widths are shown in the left, center, and right panels, respectively of the top row. The bottom row shows from left to right the amplitudes for the dipole, quadrupole, and SS peak width aspect ratio $\sigma_{\eta_{\Delta}} / \sigma_{\phi_{\Delta}} .$ Fitting errors are indicated by error bars where larger than the symbols. Solid lines connect the points for clarity. The dotted and dashed curves indicate Glauber linear superposition estimates for 62 - and 200 -GeV peak amplitudes respectively, as discussed in the text. The quadrupole data are consistent with Ref. [60]. The hatched regions indicate the full range of systematic uncertainties listed in Appendix F. The vertical dark bands indicate estimated $v$ equivalents for $N-N$ collisions and $b=0$ Au-Au collisions.

FIG. 3. Fit parameters for $\left(\eta_{\Delta}, \phi_{\Delta}\right)$ correlation data from Au-Au collisions at $\sqrt{s_{N N}}=62$ (open symbols) and 200 GeV (solid symbols) versus centrality measure $\nu$ computed at fixed energy $(200 \mathrm{GeV})$. The SS $2 \mathrm{D}$ Gaussian amplitudes, $\eta_{\Delta}$ widths, and $\phi_{\Delta}$ widths are shown in the left, center, and right panels, respectively of the top row. The bottom row shows from left to right the amplitudes for the dipole, quadrupole, and SS peak width aspect ratio $\sigma_{\eta_{\Delta}} / \sigma_{\phi_{\Delta}} .$ Fitting errors are indicated by error bars where larger than the symbols. Solid lines connect the points for clarity. The dotted and dashed curves indicate Glauber linear superposition estimates for 62 - and 200 -GeV peak amplitudes respectively, as discussed in the text. The quadrupole data are consistent with Ref. [60]. The hatched regions indicate the full range of systematic uncertainties listed in Appendix F. The vertical dark bands indicate estimated $v$ equivalents for $N-N$ collisions and $b=0$ Au-Au collisions.

FIG. 3. Fit parameters for $\left(\eta_{\Delta}, \phi_{\Delta}\right)$ correlation data from Au-Au collisions at $\sqrt{s_{N N}}=62$ (open symbols) and 200 GeV (solid symbols) versus centrality measure $\nu$ computed at fixed energy $(200 \mathrm{GeV})$. The SS $2 \mathrm{D}$ Gaussian amplitudes, $\eta_{\Delta}$ widths, and $\phi_{\Delta}$ widths are shown in the left, center, and right panels, respectively of the top row. The bottom row shows from left to right the amplitudes for the dipole, quadrupole, and SS peak width aspect ratio $\sigma_{\eta_{\Delta}} / \sigma_{\phi_{\Delta}} .$ Fitting errors are indicated by error bars where larger than the symbols. Solid lines connect the points for clarity. The dotted and dashed curves indicate Glauber linear superposition estimates for 62 - and 200 -GeV peak amplitudes respectively, as discussed in the text. The quadrupole data are consistent with Ref. [60]. The hatched regions indicate the full range of systematic uncertainties listed in Appendix F. The vertical dark bands indicate estimated $v$ equivalents for $N-N$ collisions and $b=0$ Au-Au collisions.

FIG. 3. Fit parameters for $\left(\eta_{\Delta}, \phi_{\Delta}\right)$ correlation data from Au-Au collisions at $\sqrt{s_{N N}}=62$ (open symbols) and 200 GeV (solid symbols) versus centrality measure $\nu$ computed at fixed energy $(200 \mathrm{GeV})$. The SS $2 \mathrm{D}$ Gaussian amplitudes, $\eta_{\Delta}$ widths, and $\phi_{\Delta}$ widths are shown in the left, center, and right panels, respectively of the top row. The bottom row shows from left to right the amplitudes for the dipole, quadrupole, and SS peak width aspect ratio $\sigma_{\eta_{\Delta}} / \sigma_{\phi_{\Delta}} .$ Fitting errors are indicated by error bars where larger than the symbols. Solid lines connect the points for clarity. The dotted and dashed curves indicate Glauber linear superposition estimates for 62 - and 200 -GeV peak amplitudes respectively, as discussed in the text. The quadrupole data are consistent with Ref. [60]. The hatched regions indicate the full range of systematic uncertainties listed in Appendix F. The vertical dark bands indicate estimated $v$ equivalents for $N-N$ collisions and $b=0$ Au-Au collisions.

FIG. 3. Fit parameters for $\left(\eta_{\Delta}, \phi_{\Delta}\right)$ correlation data from Au-Au collisions at $\sqrt{s_{N N}}=62$ (open symbols) and 200 GeV (solid symbols) versus centrality measure $\nu$ computed at fixed energy $(200 \mathrm{GeV})$. The SS $2 \mathrm{D}$ Gaussian amplitudes, $\eta_{\Delta}$ widths, and $\phi_{\Delta}$ widths are shown in the left, center, and right panels, respectively of the top row. The bottom row shows from left to right the amplitudes for the dipole, quadrupole, and SS peak width aspect ratio $\sigma_{\eta_{\Delta}} / \sigma_{\phi_{\Delta}} .$ Fitting errors are indicated by error bars where larger than the symbols. Solid lines connect the points for clarity. The dotted and dashed curves indicate Glauber linear superposition estimates for 62 - and 200 -GeV peak amplitudes respectively, as discussed in the text. The quadrupole data are consistent with Ref. [60]. The hatched regions indicate the full range of systematic uncertainties listed in Appendix F. The vertical dark bands indicate estimated $v$ equivalents for $N-N$ collisions and $b=0$ Au-Au collisions.

FIG. 3. Fit parameters for $\left(\eta_{\Delta}, \phi_{\Delta}\right)$ correlation data from Au-Au collisions at $\sqrt{s_{N N}}=62$ (open symbols) and 200 GeV (solid symbols) versus centrality measure $\nu$ computed at fixed energy $(200 \mathrm{GeV})$. The SS $2 \mathrm{D}$ Gaussian amplitudes, $\eta_{\Delta}$ widths, and $\phi_{\Delta}$ widths are shown in the left, center, and right panels, respectively of the top row. The bottom row shows from left to right the amplitudes for the dipole, quadrupole, and SS peak width aspect ratio $\sigma_{\eta_{\Delta}} / \sigma_{\phi_{\Delta}} .$ Fitting errors are indicated by error bars where larger than the symbols. Solid lines connect the points for clarity. The dotted and dashed curves indicate Glauber linear superposition estimates for 62 - and 200 -GeV peak amplitudes respectively, as discussed in the text. The quadrupole data are consistent with Ref. [60]. The hatched regions indicate the full range of systematic uncertainties listed in Appendix F. The vertical dark bands indicate estimated $v$ equivalents for $N-N$ collisions and $b=0$ Au-Au collisions.

FIG. 4. (Color online) (a) 2D data histogram from $0 \%-5 \%$ central 200 GeV Au-Au collisions $[(0,0)$ bin suppressed]. (b) Additional model component fitted to the $2 \mathrm{D}$ histogram and consisting of an AS azimuth dipole modulated by function $F\left(\eta_{\Delta}\right)$ described in the text. (c) Fit residuals including the new model component. (d) Data histogram in the first panel minus the additional model component and fitted offset. Remaining structure is described accurately by an AS dipole and SS 2D Gaussian.

FIG. 9. (a) Amplitude of SS 2D peak (jet-correlated pairs per final-state hadron) for data (solid points), GLS extrapolation from $p$ - $p$ data (dashed curve) and from the HIJING Monte Carlo (open points, dotted curve). (b) Single-particle production extrapolated from $p-p$ data (dashed curve, GLS), and from more-central Au-Au data (solid line) and HIJING (dash-dotted line, open points). (c) Single-particle hard-component production per $N-N$ binary collision from $p-p$ data, from more-central Au-Au data and from HIJING (open points). (d) Jet-correlated pair production (SS 2D peak) per $N-N$ binary collision extrapolated from $p-p$ data (GLS), and from Au-Au data (solid points) and HIJING (open points).

FIG. 9. (a) Amplitude of SS 2D peak (jet-correlated pairs per final-state hadron) for data (solid points), GLS extrapolation from $p$ - $p$ data (dashed curve) and from the HIJING Monte Carlo (open points, dotted curve). (b) Single-particle production extrapolated from $p-p$ data (dashed curve, GLS), and from more-central Au-Au data (solid line) and HIJING (dash-dotted line, open points). (c) Single-particle hard-component production per $N-N$ binary collision from $p-p$ data, from more-central Au-Au data and from HIJING (open points). (d) Jet-correlated pair production (SS 2D peak) per $N-N$ binary collision extrapolated from $p-p$ data (GLS), and from Au-Au data (solid points) and HIJING (open points).

FIG. 9. (a) Amplitude of SS 2D peak (jet-correlated pairs per final-state hadron) for data (solid points), GLS extrapolation from $p$ - $p$ data (dashed curve) and from the HIJING Monte Carlo (open points, dotted curve). (b) Single-particle production extrapolated from $p-p$ data (dashed curve, GLS), and from more-central Au-Au data (solid line) and HIJING (dash-dotted line, open points). (c) Single-particle hard-component production per $N-N$ binary collision from $p-p$ data, from more-central Au-Au data and from HIJING (open points). (d) Jet-correlated pair production (SS 2D peak) per $N-N$ binary collision extrapolated from $p-p$ data (GLS), and from Au-Au data (solid points) and HIJING (open points).

FIG. 9. (a) Amplitude of SS 2D peak (jet-correlated pairs per final-state hadron) for data (solid points), GLS extrapolation from $p$ - $p$ data (dashed curve) and from the HIJING Monte Carlo (open points, dotted curve). (b) Single-particle production extrapolated from $p-p$ data (dashed curve, GLS), and from more-central Au-Au data (solid line) and HIJING (dash-dotted line, open points). (c) Single-particle hard-component production per $N-N$ binary collision from $p-p$ data, from more-central Au-Au data and from HIJING (open points). (d) Jet-correlated pair production (SS 2D peak) per $N-N$ binary collision extrapolated from $p-p$ data (GLS), and from Au-Au data (solid points) and HIJING (open points).

FIG. 11. (Color online) (Left) Uncorrected angular correlations from 62-GeV $37 \%-46 \%$ central Au-Au collisions showing pileup distortions, especially evident as the W-shaped nonuniformity of the AS ridge on $\eta_{\Delta}$. (Right) The same data with pileup correction applied.

FIG. 1: (a) Raw two-particle correlation signal $Y_2$ (red), background $aB_{inc}F_2$ (solid histogram), and background systematic uncertainty from a (dashed histograms). (b) Background-subtracted two-particle correlation $\hat{Y}_2$ (red), and systematic uncertainties due to a (dashed histograms) and flow (blue histograms). (c) Raw three-particle correlation $Y_3$. (d) $ba^2Y_{inc}^2$ . (e) Sum of trig-corr-bkgd and trigger flow. Data are from 12% central Au+Au collisions. Statistical errors in (a,b) are smaller than the point size.

FIG. 1: (a) Raw two-particle correlation signal $Y_2$ (red), background $aB_{inc}F_2$ (solid histogram), and background systematic uncertainty from a (dashed histograms). (b) Background-subtracted two-particle correlation $\hat{Y}_2$ (red), and systematic uncertainties due to a (dashed histograms) and flow (blue histograms). (c) Raw three-particle correlation $Y_3$. (d) $ba^2Y_{inc}^2$ . (e) Sum of trig-corr-bkgd and trigger flow. Data are from 12% central Au+Au collisions. Statistical errors in (a,b) are smaller than the point size.

FIG. 2: Background subtracted three-particle correlations, $\hat{Y}_3$, for (a) pp, (b) d+Au, (c) 80-50% Au+Au, (d) 50-30% Au+Au, (e) 30-10% Au+Au, and (f) 12% central Au+Au. Statistical errors per bin are approximately $\pm$0.012 in (a) and $\pm$0.006 in (b), both at ($\pi$, $\pi$), and are $\pm$0.022, $\pm$0.049, $\pm$0.099 and $\pm$0.077 from (c) to (f), similar for all bins.

FIG. 2: Background subtracted three-particle correlations, $\hat{Y}_3$, for (a) pp, (b) d+Au, (c) 80-50% Au+Au, (d) 50-30% Au+Au, (e) 30-10% Au+Au, and (f) 12% central Au+Au. Statistical errors per bin are approximately $\pm$0.012 in (a) and $\pm$0.006 in (b), both at ($\pi$, $\pi$), and are $\pm$0.022, $\pm$0.049, $\pm$0.099 and $\pm$0.077 from (c) to (f), similar for all bins.

FIG. 2: Background subtracted three-particle correlations, $\hat{Y}_3$, for (a) pp, (b) d+Au, (c) 80-50% Au+Au, (d) 50-30% Au+Au, (e) 30-10% Au+Au, and (f) 12% central Au+Au. Statistical errors per bin are approximately $\pm$0.012 in (a) and $\pm$0.006 in (b), both at ($\pi$, $\pi$), and are $\pm$0.022, $\pm$0.049, $\pm$0.099 and $\pm$0.077 from (c) to (f), similar for all bins.

FIG. 2: Background subtracted three-particle correlations, $\hat{Y}_3$, for (a) pp, (b) d+Au, (c) 80-50% Au+Au, (d) 50-30% Au+Au, (e) 30-10% Au+Au, and (f) 12% central Au+Au. Statistical errors per bin are approximately $\pm$0.012 in (a) and $\pm$0.006 in (b), both at ($\pi$, $\pi$), and are $\pm$0.022, $\pm$0.049, $\pm$0.099 and $\pm$0.077 from (c) to (f), similar for all bins.

FIG. 2: Background subtracted three-particle correlations, $\hat{Y}_3$, for (a) pp, (b) d+Au, (c) 80-50% Au+Au, (d) 50-30% Au+Au, (e) 30-10% Au+Au, and (f) 12% central Au+Au. Statistical errors per bin are approximately $\pm$0.012 in (a) and $\pm$0.006 in (b), both at ($\pi$, $\pi$), and are $\pm$0.022, $\pm$0.049, $\pm$0.099 and $\pm$0.077 from (c) to (f), similar for all bins.

FIG. 2: Background subtracted three-particle correlations, $\hat{Y}_3$, for (a) pp, (b) d+Au, (c) 80-50% Au+Au, (d) 50-30% Au+Au, (e) 30-10% Au+Au, and (f) 12% central Au+Au. Statistical errors per bin are approximately $\pm$0.012 in (a) and $\pm$0.006 in (b), both at ($\pi$, $\pi$), and are $\pm$0.022, $\pm$0.049, $\pm$0.099 and $\pm$0.077 from (c) to (f), similar for all bins.

Projections of away-side three-particle correlations along the diagonal $\Sigma$ within 0 < $\Delta$ < 0.35 (squares) and along the off-diagonal $\Delta$ within |$\Sigma$| < 0.35 (points) in (a) d+Au and (b) 12% central Au+Au collisions. The shaded areas indicate systematic uncertainties on the off-diagonal projections. The histogram in (a) is the near-side off-diagonal projection. The histogram in (b) is the away-side off-diagonal projection of our result with a = b = 1. NOTE: For points with invisible error bars, the point size was considered as an absolute upper limit for the uncertainty.

Projections of away-side three-particle correlations along the diagonal $\Sigma$ within 0 < $\Delta$ < 0.35 (squares) and along the off-diagonal $\Delta$ within |$\Sigma$| < 0.35 (points) in (a) d+Au and (b) 12% central Au+Au collisions. The shaded areas indicate systematic uncertainties on the off-diagonal projections. The histogram in (a) is the near-side off-diagonal projection. The histogram in (b) is the away-side off-diagonal projection of our result with a = b = 1. NOTE: For points with invisible error bars, the point size was considered as an absolute upper limit for the uncertainty.

Three-particle correlation strength per radian$^2$ versus ($N_{part}$/2)$^{1/3}$ where $N_{part}$ is the number of participants. Some of the data points have been displaced in $N_{part}$ for clarity.

Correlation matrix of negative systematic uncertainties.