Mass dependence of the mid-rapidity $v_1$ slope, $dv_1/dy$, for $\Lambda$, $^{3}_{\Lambda}$H and $^{4}_{\Lambda}$H from the $\sqrt{s_{NN}}$ = 3 GeV 5-40% mid-central Au+Au collisions. The statistical and systematic uncertainties are presented by vertical lines and square brackets, respectively. The slopes of $p$, $d$, $t$, $^3$He and $^4$He from the same collisions are shown as black circles. The blue and dashed green lines are the results of a linear fit to the measured light nuclei and hypernuclei $v_1$ slopes, respectively. For comparison, calculations of transport models plus coalescence afterburner are shown as gold and red bars from JAM model, and blue bars from UrQMD model.

Mass dependence of the mid-rapidity $v_1$ slope, $dv_1/dy$, for $\Lambda$, $^{3}_{\Lambda}$H and $^{4}_{\Lambda}$H from the $\sqrt{s_{NN}}$ = 3 GeV 5-40% mid-central Au+Au collisions. The statistical and systematic uncertainties are presented by vertical lines and square brackets, respectively. The slopes of $p$, $d$, $t$, $^3$He and $^4$He from the same collisions are shown as black circles. The blue and dashed green lines are the results of a linear fit to the measured light nuclei and hypernuclei $v_1$ slopes, respectively. For comparison, calculations of transport models plus coalescence afterburner are shown as gold and red bars from JAM model, and blue bars from UrQMD model.

Mass dependence of the mid-rapidity $v_1$ slope, $dv_1/dy$, for $\Lambda$, $^{3}_{\Lambda}$H and $^{4}_{\Lambda}$H from the $\sqrt{s_{NN}}$ = 3 GeV 5-40% mid-central Au+Au collisions. The statistical and systematic uncertainties are presented by vertical lines and square brackets, respectively. The slopes of $p$, $d$, $t$, $^3$He and $^4$He from the same collisions are shown as black circles. The blue and dashed green lines are the results of a linear fit to the measured light nuclei and hypernuclei $v_1$ slopes, respectively. For comparison, calculations of transport models plus coalescence afterburner are shown as gold and red bars from JAM model, and blue bars from UrQMD model.

Mass dependence of the mid-rapidity $v_1$ slope, $dv_1/dy$, for $\Lambda$, $^{3}_{\Lambda}$H and $^{4}_{\Lambda}$H from the $\sqrt{s_{NN}}$ = 3 GeV 5-40% mid-central Au+Au collisions. The statistical and systematic uncertainties are presented by vertical lines and square brackets, respectively. The slopes of $p$, $d$, $t$, $^3$He and $^4$He from the same collisions are shown as black circles. The blue and dashed green lines are the results of a linear fit to the measured light nuclei and hypernuclei $v_1$ slopes, respectively. For comparison, calculations of transport models plus coalescence afterburner are shown as gold and red bars from JAM model, and blue bars from UrQMD model.

Mass dependence of the mid-rapidity $v_1$ slope, $dv_1/dy$, for $\Lambda$, $^{3}_{\Lambda}$H and $^{4}_{\Lambda}$H from the $\sqrt{s_{NN}}$ = 3 GeV 5-40% mid-central Au+Au collisions. The statistical and systematic uncertainties are presented by vertical lines and square brackets, respectively. The slopes of $p$, $d$, $t$, $^3$He and $^4$He from the same collisions are shown as black circles. The blue and dashed green lines are the results of a linear fit to the measured light nuclei and hypernuclei $v_1$ slopes, respectively. For comparison, calculations of transport models plus coalescence afterburner are shown as gold and red bars from JAM model, and blue bars from UrQMD model.

Reference multiplicity distributions obtained from Au+Au collisions at $\sqrt{s_{\rm NN}}$ = 3 GeV data (black markers), Glauber model (red histogram), and unfolding approach to separate single and pileup contributions. Vertical lines represent statistical uncertainties. Single, pileup, and single+pileup collisions are shown in solid blue markers, dashed green, and dashed pink lines, respectively. The 0–5% central events and 5–60% mid-central to peripheral events are indicated by black arrows. The ratio of the single+pileup to the measured multiplicity distribution is shown in the lower panel.

Reference multiplicity distributions obtained from Au+Au collisions at $\sqrt{s_{\rm NN}}$ = 3 GeV data (black markers), Glauber model (red histogram), and unfolding approach to separate single and pileup contributions. Vertical lines represent statistical uncertainties. Single, pileup, and single+pileup collisions are shown in solid blue markers, dashed green, and dashed pink lines, respectively. The 0–5% central events and 5–60% mid-central to peripheral events are indicated by black arrows. The ratio of the single+pileup to the measured multiplicity distribution is shown in the lower panel.

Proton cumulants as a function of reference multiplicity (black circles) from $\sqrt{s_{\rm NN}}$ = 3 GeV Au+Au collisions. Centrality-binned results with and without centrality bin width corrections are represented by red circles and blue squares, respectively. Vertical dashed lines indicate the centrality classes, from right to left: 0–5%, 5–10%, 10–20%. Data points in this figure are only corrected for detector efficiency but not for the pileup effect, which will be discussed in a later section.

Proton cumulants as a function of reference multiplicity (black circles) from $\sqrt{s_{\rm NN}}$ = 3 GeV Au+Au collisions. Centrality-binned results with and without centrality bin width corrections are represented by red circles and blue squares, respectively. Vertical dashed lines indicate the centrality classes, from right to left: 0–5%, 5–10%, 10–20%. Data points in this figure are only corrected for detector efficiency but not for the pileup effect, which will be discussed in a later section.

Proton cumulants as a function of reference multiplicity (black circles) from $\sqrt{s_{\rm NN}}$ = 3 GeV Au+Au collisions. Centrality-binned results with and without centrality bin width corrections are represented by red circles and blue squares, respectively. Vertical dashed lines indicate the centrality classes, from right to left: 0–5%, 5–10%, 10–20%. Data points in this figure are only corrected for detector efficiency but not for the pileup effect, which will be discussed in a later section.

Proton cumulants as a function of reference multiplicity from $\sqrt{s_{\rm NN}}$ = 3 GeV Au+Au collisions. Pileup corrected and uncorrected cumulants as a function of reference multiplicity are represented by black circles and blue open squares, respectively. Red circles and blue-filled squares represent the results of centrality binned data.

Proton cumulants as a function of reference multiplicity from $\sqrt{s_{\rm NN}}$ = 3 GeV Au+Au collisions. Pileup corrected and uncorrected cumulants as a function of reference multiplicity are represented by black circles and blue open squares, respectively. Red circles and blue-filled squares represent the results of centrality binned data.

Ratios of proton cumulants as a function of reference multiplicity from $\sqrt{s_{\rm NN}}$ = 3 GeV Au+Au collisions. Pileup corrected and uncorrected cumulants are represented by black circles and blue open squares, respectively. Red circles and blue-filled squares represent the results of centrality binned data.

Ratios of proton cumulants as a function of reference multiplicity from $\sqrt{s_{\rm NN}}$ = 3 GeV Au+Au collisions. Pileup corrected and uncorrected cumulants are represented by black circles and blue open squares, respectively. Red circles and blue-filled squares represent the results of centrality binned data.

UrQMD results of the proton cumulant ratios up to sixth order in Au+Au collisions at $\sqrt{s_{\rm NN}}$= 3 GeV. The black circles are without VF correction while blue squares and red triangles are results with VFC which used $N_{\rm part}$ distributions from UrQMD and Glauber models, respectively. The blue crosses are calculations using UrQMD events with b $\leq$ 3 fm. The above results are applied CBWC except for the one (blue crosses) using b $\leq$3 fm events.

UrQMD results of the proton cumulant ratios up to sixth order in Au+Au collisions at $\sqrt{s_{\rm NN}}$= 3 GeV. The black circles are without VF correction while blue squares and red triangles are results with VFC which used $N_{\rm part}$ distributions from UrQMD and Glauber models, respectively. The blue crosses are calculations using UrQMD events with b $\leq$ 3 fm. The above results are applied CBWC except for the one (blue crosses) using b $\leq$3 fm events.

Proton cumulants up to sixth order in $\sqrt{s_{\rm NN}}$ = 3 GeV Au+Au collisions. Data without volume fluctuation correction is shown as grey open squares while data with volume fluctuation correction using $N_{\rm part}$ distributions from Glauber and UrQMD models are shown as black circles and black open triangles, respectively. The corresponding centrality binned cumulants are shown in blue squares, red circles, and orange triangles, respectively. Similarly to Fig. 6, the vertical dashed lines indicate the centrality classes.

Proton cumulants up to sixth order in $\sqrt{s_{\rm NN}}$ = 3 GeV Au+Au collisions. Data without volume fluctuation correction is shown as grey open squares while data with volume fluctuation correction using $N_{\rm part}$ distributions from Glauber and UrQMD models are shown as black circles and black open triangles, respectively. The corresponding centrality binned cumulants are shown in blue squares, red circles, and orange triangles, respectively. Similarly to Fig. 6, the vertical dashed lines indicate the centrality classes.

Proton cumulant ratios up to sixth order in $\sqrt{s_{\rm NN}}$ = 3 GeV Au+Au collisions. Data without volume fluctuation correction are shown as grey open squares while data with volume fluctuation correction using $N_{\rm part}$ distributions from Glauber and UrQMD models are shown as black circles and black open triangles, respectively. The corresponding centrality binned cumulants are shown in blue squares, red circles, and orange triangles, respectively. Similarly to Fig. 6, the vertical dashed lines indicate the centrality classes.

Proton cumulant ratios up to sixth order in $\sqrt{s_{\rm NN}}$ = 3 GeV Au+Au collisions. Data without volume fluctuation correction are shown as grey open squares while data with volume fluctuation correction using $N_{\rm part}$ distributions from Glauber and UrQMD models are shown as black circles and black open triangles, respectively. The corresponding centrality binned cumulants are shown in blue squares, red circles, and orange triangles, respectively. Similarly to Fig. 6, the vertical dashed lines indicate the centrality classes.

UrQMD results of proton cumulant ratios up to sixth order in Au+Au collisions at $\sqrt{s_{\rm NN}}$ = 3 GeV. The vertical dashed lines indicate the centrality classes.

Experimental results on centrality dependence of cumulants (left panels) and cumulant ratios (right panels) up to sixth order of the proton multiplicity distributions in Au+Au collisions at $N_{\rm part}$ = 3 GeV. The open squares are data without VF correction while red circles and blue triangles are results with VF correction with $N_{\rm part}$ distributions from Glauber and UrQMD models, respectively.

Experimental results on centrality dependence of cumulants (left panels) and cumulant ratios (right panels) up to sixth order of the proton multiplicity distributions in Au+Au collisions at $N_{\rm part}$ = 3 GeV. The open squares are data without VF correction while red circles and blue triangles are results with VF correction with $N_{\rm part}$ distributions from Glauber and UrQMD models, respectively.

Same as Fig. 14 but for correlation function (left panels) and their normalized ratios (right panels).

Same as Fig. 14 but for correlation function (left panels) and their normalized ratios (right panels).

Cumulants and cumulant ratios of proton multiplicity distributions for Au+Au collisions at $\sqrt{s_{\rm NN}}$ = 3 GeV. The transverse momentum window is $p_{\rm T}$ from $0.4<p_{\rm T}<2.0$ GeV/$c$ and the rapidity window is $−0.5<y<0$. Statistical and systematic uncertainties are represented by black and gray bars, respectively. UrQMD predictions are depicted by gold bands.

Cumulants and cumulant ratios of proton multiplicity distributions for Au+Au collisions at $\sqrt{s_{\rm NN}}$ = 3 GeV. The transverse momentum window is $p_{\rm T}$ from $0.4<p_{\rm T}<2.0$ GeV/$c$ and the rapidity window is $−0.5<y<0$. Statistical and systematic uncertainties are represented by black and gray bars, respectively. UrQMD predictions are depicted by gold bands.

Same as Fig. 16 but for correlation functions and correlation function ratios of proton multiplicity distributions for Au+Au collisions at $\sqrt{s_{\rm NN}}$ = 3 GeV.

Same as Fig. 16 but for correlation functions and correlation function ratios of proton multiplicity distributions for Au+Au collisions at $\sqrt{s_{\rm NN}}$ = 3 GeV.

The transverse-momentum and rapidity dependence of cumulant ratios of proton multiplicity distributions for Au+Au collisions at $\sqrt{s_{\rm NN}}$ = 3 GeV. In the left column, the $p_{\rm T}$ analysis window is $0.4<p_{\rm T}<2.0$ GeV/$c$ while the rapidity window is varied in the range $y_{\rm min}<y<0$. In the right column, the rapidit$y$ analysis window is $−0.5<y<0$ while the $p_{\rm T}$ is varied in the range $0.4<p_{\rm T}<p_{\rm T}^{\rm max}$ GeV/$c$. The most central (0–5%) and peripheral (50–60%) events are depicted by black squares and blue triangles, respectively. Statistical and systematic uncertainties are represented by black and gray bars, respectively. UrQMD simulations for the top 0–5% and 50–60% are shown by gold and blue bands, respectively.

The transverse-momentum and rapidity dependence of cumulant ratios of proton multiplicity distributions for Au+Au collisions at $\sqrt{s_{\rm NN}}$ = 3 GeV. In the left column, the $p_{\rm T}$ analysis window is $0.4<p_{\rm T}<2.0$ GeV/$c$ while the rapidity window is varied in the range $y_{\rm min}<y<0$. In the right column, the rapidit$y$ analysis window is $−0.5<y<0$ while the $p_{\rm T}$ is varied in the range $0.4<p_{\rm T}<p_{\rm T}^{\rm max}$ GeV/$c$. The most central (0–5%) and peripheral (50–60%) events are depicted by black squares and blue triangles, respectively. Statistical and systematic uncertainties are represented by black and gray bars, respectively. UrQMD simulations for the top 0–5% and 50–60% are shown by gold and blue bands, respectively.

The transverse-momentum and rapidity dependence of cumulant ratios of proton multiplicity distributions for Au+Au collisions at $\sqrt{s_{\rm NN}}$ = 3 GeV. In the left column, the $p_{\rm T}$ analysis window is $0.4<p_{\rm T}<2.0$ GeV/$c$ while the rapidity window is varied in the range $y_{\rm min}<y<0$. In the right column, the rapidit$y$ analysis window is $−0.5<y<0$ while the $p_{\rm T}$ is varied in the range $0.4<p_{\rm T}<p_{\rm T}^{\rm max}$ GeV/$c$. The most central (0–5%) and peripheral (50–60%) events are depicted by black squares and blue triangles, respectively. Statistical and systematic uncertainties are represented by black and gray bars, respectively. UrQMD simulations for the top 0–5% and 50–60% are shown by gold and blue bands, respectively.

The transverse-momentum and rapidity dependence of cumulant ratios of proton multiplicity distributions for Au+Au collisions at $\sqrt{s_{\rm NN}}$ = 3 GeV. In the left column, the $p_{\rm T}$ analysis window is $0.4<p_{\rm T}<2.0$ GeV/$c$ while the rapidity window is varied in the range $y_{\rm min}<y<0$. In the right column, the rapidit$y$ analysis window is $−0.5<y<0$ while the $p_{\rm T}$ is varied in the range $0.4<p_{\rm T}<p_{\rm T}^{\rm max}$ GeV/$c$. The most central (0–5%) and peripheral (50–60%) events are depicted by black squares and blue triangles, respectively. Statistical and systematic uncertainties are represented by black and gray bars, respectively. UrQMD simulations for the top 0–5% and 50–60% are shown by gold and blue bands, respectively.

As in Fig. 18 but for transverse-momentum and rapidity dependence of correlation function ratios of proton multiplicity distributions for Au+Au collisions at $\sqrt{s_{\rm NN}}$ = 3 GeV.

As in Fig. 18 but for transverse-momentum and rapidity dependence of correlation function ratios of proton multiplicity distributions for Au+Au collisions at $\sqrt{s_{\rm NN}}$ = 3 GeV.

As in Fig. 18 but for transverse-momentum and rapidity dependence of correlation function ratios of proton multiplicity distributions for Au+Au collisions at $\sqrt{s_{\rm NN}}$ = 3 GeV.

As in Fig. 18 but for transverse-momentum and rapidity dependence of correlation function ratios of proton multiplicity distributions for Au+Au collisions at $\sqrt{s_{\rm NN}}$ = 3 GeV.

Collision energy dependence of the cumulant ratios: $C_2/C_1=\sigma/M$, $C_3/C_2=S\sigma$, and $C_4/C_2=\kappa\sigma^2$, for protons (open squares) and net protons (red circles) from top 0–5% (top panels) and 50–60% (bottom panels) Au+Au collisions at RHIC. The points for protons are shifted horizontally for clarity. The new result for protons from $\sqrt{s_{\rm NN}}$ = 3 GeV Au+Au collisions is shown as a filled square. UrQMD results with $|y|<0.5$ for protons are shown as gold bands while those for net protons are shown as green dashed lines or green bands. At 3GeV, the model results for protons (−0.5) are shown as blue crosses. UrQMD results of proton and net-proton $C_4/C_2$, see right panels, are almost totally overlapped. The open cross is the result of the model with a fixed impact parameter $b < 3$ fm. The hydrodynamic calculations, for 5% central Au+Au collisions, for protons from $|y|<0.5$ are shown as dashed red linea and the result of the 3 GeV protons from $−0.5<y<0$ is shown as an open red star.

Collision energy dependence of the cumulant ratios: $C_2/C_1=\sigma/M$, $C_3/C_2=S\sigma$, and $C_4/C_2=\kappa\sigma^2$, for protons (open squares) and net protons (red circles) from top 0–5% (top panels) and 50–60% (bottom panels) Au+Au collisions at RHIC. The points for protons are shifted horizontally for clarity. The new result for protons from $\sqrt{s_{\rm NN}}$ = 3 GeV Au+Au collisions is shown as a filled square. UrQMD results with $|y|<0.5$ for protons are shown as gold bands while those for net protons are shown as green dashed lines or green bands. At 3GeV, the model results for protons (−0.5) are shown as blue crosses. UrQMD results of proton and net-proton $C_4/C_2$, see right panels, are almost totally overlapped. The open cross is the result of the model with a fixed impact parameter $b < 3$ fm. The hydrodynamic calculations, for 5% central Au+Au collisions, for protons from $|y|<0.5$ are shown as dashed red linea and the result of the 3 GeV protons from $−0.5<y<0$ is shown as an open red star.

Collision energy dependence of the cumulant ratios: $C_2/C_1=\sigma/M$, $C_3/C_2=S\sigma$, and $C_4/C_2=\kappa\sigma^2$, for protons (open squares) and net protons (red circles) from top 0–5% (top panels) and 50–60% (bottom panels) Au+Au collisions at RHIC. The points for protons are shifted horizontally for clarity. The new result for protons from $\sqrt{s_{\rm NN}}$ = 3 GeV Au+Au collisions is shown as a filled square. UrQMD results with $|y|<0.5$ for protons are shown as gold bands while those for net protons are shown as green dashed lines or green bands. At 3GeV, the model results for protons (−0.5) are shown as blue crosses. UrQMD results of proton and net-proton $C_4/C_2$, see right panels, are almost totally overlapped. The open cross is the result of the model with a fixed impact parameter $b < 3$ fm. The hydrodynamic calculations, for 5% central Au+Au collisions, for protons from $|y|<0.5$ are shown as dashed red linea and the result of the 3 GeV protons from $−0.5<y<0$ is shown as an open red star.

Collision energy dependence of the cumulant ratios: $C_2/C_1=\sigma/M$, $C_3/C_2=S\sigma$, and $C_4/C_2=\kappa\sigma^2$, for protons (open squares) and net protons (red circles) from top 0–5% (top panels) and 50–60% (bottom panels) Au+Au collisions at RHIC. The points for protons are shifted horizontally for clarity. The new result for protons from $\sqrt{s_{\rm NN}}$ = 3 GeV Au+Au collisions is shown as a filled square. UrQMD results with $|y|<0.5$ for protons are shown as gold bands while those for net protons are shown as green dashed lines or green bands. At 3GeV, the model results for protons (−0.5) are shown as blue crosses. UrQMD results of proton and net-proton $C_4/C_2$, see right panels, are almost totally overlapped. The open cross is the result of the model with a fixed impact parameter $b < 3$ fm. The hydrodynamic calculations, for 5% central Au+Au collisions, for protons from $|y|<0.5$ are shown as dashed red linea and the result of the 3 GeV protons from $−0.5<y<0$ is shown as an open red star.

Collision energy dependence of the cumulant ratios: $C_2/C_1=\sigma/M$, $C_3/C_2=S\sigma$, and $C_4/C_2=\kappa\sigma^2$, for protons (open squares) and net protons (red circles) from top 0–5% (top panels) and 50–60% (bottom panels) Au+Au collisions at RHIC. The points for protons are shifted horizontally for clarity. The new result for protons from $\sqrt{s_{\rm NN}}$ = 3 GeV Au+Au collisions is shown as a filled square. UrQMD results with $|y|<0.5$ for protons are shown as gold bands while those for net protons are shown as green dashed lines or green bands. At 3GeV, the model results for protons (−0.5) are shown as blue crosses. UrQMD results of proton and net-proton $C_4/C_2$, see right panels, are almost totally overlapped. The open cross is the result of the model with a fixed impact parameter $b < 3$ fm. The hydrodynamic calculations, for 5% central Au+Au collisions, for protons from $|y|<0.5$ are shown as dashed red linea and the result of the 3 GeV protons from $−0.5<y<0$ is shown as an open red star.

Collision energy dependence of the cumulant ratios: $C_2/C_1=\sigma/M$, $C_3/C_2=S\sigma$, and $C_4/C_2=\kappa\sigma^2$, for protons (open squares) and net protons (red circles) from top 0–5% (top panels) and 50–60% (bottom panels) Au+Au collisions at RHIC. The points for protons are shifted horizontally for clarity. The new result for protons from $\sqrt{s_{\rm NN}}$ = 3 GeV Au+Au collisions is shown as a filled square. UrQMD results with $|y|<0.5$ for protons are shown as gold bands while those for net protons are shown as green dashed lines or green bands. At 3GeV, the model results for protons (−0.5) are shown as blue crosses. UrQMD results of proton and net-proton $C_4/C_2$, see right panels, are almost totally overlapped. The open cross is the result of the model with a fixed impact parameter $b < 3$ fm. The hydrodynamic calculations, for 5% central Au+Au collisions, for protons from $|y|<0.5$ are shown as dashed red linea and the result of the 3 GeV protons from $−0.5<y<0$ is shown as an open red star.

B.R. times dN/dy of $^{3}_{\Lambda}$H vs y in 3 GeV 10-50% Au+Au collisions

B.R. times dN/dy of $^{4}_{\Lambda}$H vs y in 3 GeV 10-50% Au+Au collisions

B.R. times dN/dy at |y|<0.5 of $^{3}_{\Lambda}$H vs B.R in 3 GeV 0-10% Au+Au collisions

B.R. times dN/dy at |y|<0.5 of $^{4}_{\Lambda}$H vs B.R in 3 GeV 0-10% Au+Au collisions

$^{3}_{\Lambda}$H $p_T$ spectra times B.R., -0.25<y<0, Au+Au 3 GeV, 0-10%

$^{3}_{\Lambda}$H $p_T$ spectra times B.R., -0.5<y<-0.25, Au+Au 3 GeV, 0-10%

$^{3}_{\Lambda}$H $p_T$ spectra times B.R., -0.25<y<0, Au+Au 3 GeV, 10-50%

$^{3}_{\Lambda}$H $p_T$ spectra times B.R., -0.5<y<-0.25, Au+Au 3 GeV, 10-50%

$^{4}_{\Lambda}$H $p_T$ spectra times B.R., -0.25<y<0, Au+Au 3 GeV, 0-10%

$^{4}_{\Lambda}$H $p_T$ spectra times B.R., -0.5<y<-0.25, Au+Au 3 GeV, 0-10%

$^{4}_{\Lambda}$H $p_T$ spectra times B.R., -0.75<y<-0.5, Au+Au 3 GeV, 0-10%

$^{4}_{\Lambda}$H $p_T$ spectra times B.R., -0.25<y<0, Au+Au 3 GeV, 10-50%

$^{4}_{\Lambda}$H $p_T$ spectra times B.R., -0.5<y<-0.25, Au+Au 3 GeV, 10-50%

$^{4}_{\Lambda}$H $p_T$ spectra times B.R., -0.75<y<-0.5, Au+Au 3 GeV, 10-50%

This table contains thinned out samples of the Markov chains used in the parameter estimation of the SDME measurements for $-(t-t_\text{0}) = 0.400\pm0.056~\text{GeV}^2/c^2$, reported in the main article. One in about 250 steps in the chain, which results in 200 different sets of SDMEs, is provided. These values should be used instead of bootstrapping of the results, in order to estimate uncertainties of physics models fitted to this data. To assess how the uncertainties propagate to the model uncertainties, one should evaluate the model under scrutiny for each of the 200 different sets of SDMEs. Plotting all resulting lines in a single plot will create bands which reflect the influence of the uncertainties in the data on the model. This method has the great advantage that all correlations are accurately taken into account.

This table contains thinned out samples of the Markov chains used in the parameter estimation of the SDME measurements for $-(t-t_\text{0}) = 0.597\pm0.057~\text{GeV}^2/c^2$, reported in the main article. One in about 250 steps in the chain, which results in 200 different sets of SDMEs, is provided. These values should be used instead of bootstrapping of the results, in order to estimate uncertainties of physics models fitted to this data. To assess how the uncertainties propagate to the model uncertainties, one should evaluate the model under scrutiny for each of the 200 different sets of SDMEs. Plotting all resulting lines in a single plot will create bands which reflect the influence of the uncertainties in the data on the model. This method has the great advantage that all correlations are accurately taken into account.

This table contains thinned out samples of the Markov chains used in the parameter estimation of the SDME measurements for $-(t-t_\text{0}) = 0.793\pm0.057~\text{GeV}^2/c^2$, reported in the main article. One in about 250 steps in the chain, which results in 200 different sets of SDMEs, is provided. These values should be used instead of bootstrapping of the results, in order to estimate uncertainties of physics models fitted to this data. To assess how the uncertainties propagate to the model uncertainties, one should evaluate the model under scrutiny for each of the 200 different sets of SDMEs. Plotting all resulting lines in a single plot will create bands which reflect the influence of the uncertainties in the data on the model. This method has the great advantage that all correlations are accurately taken into account.

This table contains thinned out samples of the Markov chains used in the parameter estimation of the SDME measurements for $-(t-t_\text{0}) = 0.992\pm0.058~\text{GeV}^2/c^2$, reported in the main article. One in about 250 steps in the chain, which results in 200 different sets of SDMEs, is provided. These values should be used instead of bootstrapping of the results, in order to estimate uncertainties of physics models fitted to this data. To assess how the uncertainties propagate to the model uncertainties, one should evaluate the model under scrutiny for each of the 200 different sets of SDMEs. Plotting all resulting lines in a single plot will create bands which reflect the influence of the uncertainties in the data on the model. This method has the great advantage that all correlations are accurately taken into account.

This table contains thinned out samples of the Markov chains used in the parameter estimation of the SDME measurements for $-(t-t_\text{0}) = 1.189\pm0.058~\text{GeV}^2/c^2$, reported in the main article. One in about 250 steps in the chain, which results in 200 different sets of SDMEs, is provided. These values should be used instead of bootstrapping of the results, in order to estimate uncertainties of physics models fitted to this data. To assess how the uncertainties propagate to the model uncertainties, one should evaluate the model under scrutiny for each of the 200 different sets of SDMEs. Plotting all resulting lines in a single plot will create bands which reflect the influence of the uncertainties in the data on the model. This method has the great advantage that all correlations are accurately taken into account.

This table contains thinned out samples of the Markov chains used in the parameter estimation of the SDME measurements for $-(t-t_\text{0}) = 1.435\pm0.086~\text{GeV}^2/c^2$, reported in the main article. One in about 250 steps in the chain, which results in 200 different sets of SDMEs, is provided. These values should be used instead of bootstrapping of the results, in order to estimate uncertainties of physics models fitted to this data. To assess how the uncertainties propagate to the model uncertainties, one should evaluate the model under scrutiny for each of the 200 different sets of SDMEs. Plotting all resulting lines in a single plot will create bands which reflect the influence of the uncertainties in the data on the model. This method has the great advantage that all correlations are accurately taken into account.

This table contains thinned out samples of the Markov chains used in the parameter estimation of the SDME measurements for $-(t-t_\text{0}) = 1.761\pm0.111~\text{GeV}^2/c^2$, reported in the main article. One in about 250 steps in the chain, which results in 200 different sets of SDMEs, is provided. These values should be used instead of bootstrapping of the results, in order to estimate uncertainties of physics models fitted to this data. To assess how the uncertainties propagate to the model uncertainties, one should evaluate the model under scrutiny for each of the 200 different sets of SDMEs. Plotting all resulting lines in a single plot will create bands which reflect the influence of the uncertainties in the data on the model. This method has the great advantage that all correlations are accurately taken into account.

Mixed higher-order flow harmonic $v_6\{\Psi_{33}\}$ from the scalar-product method at 5.02 TeV as a function of PT in the 0-20% centrality range.

Mixed higher-order flow harmonic $v_7\{\Psi_{223}\}$ from the scalar-product method at 5.02 TeV as a function of PT in the 0-20% centrality range.

Mixed higher-order flow harmonic $v_4\{\Psi_{22}\}$ from the scalar-product method at 5.02 TeV as a function of PT in the 20-60% centrality range.

Mixed higher-order flow harmonic $v_5\{\Psi_{23}\}$ from the scalar-product method at 5.02 TeV as a function of PT in the 20-60% centrality range.

Mixed higher-order flow harmonic $v_6\{\Psi_{222}\}$ from the scalar-product method at 5.02 TeV as a function of PT in the 20-60% centrality range.

Mixed higher-order flow harmonic $v_6\{\Psi_{33}\}$ from the scalar-product method at 5.02 TeV as a function of PT in the 20-60% centrality range.

Mixed higher-order flow harmonic $v_7\{\Psi_{223}\}$ from the scalar-product method at 5.02 TeV as a function of PT in the 20-60% centrality range.

Mixed higher-order flow harmonic $v_4\{\Psi_{22}\}$ from the scalar-product method at 2.76 TeV as a function of PT in the 0-20% centrality range.

Mixed higher-order flow harmonic $v_5\{\Psi_{23}\}$ from the scalar-product method at 2.76 TeV as a function of PT in the 0-20% centrality range.

Mixed higher-order flow harmonic $v_6\{\Psi_{222}\}$ from the scalar-product method at 2.76 TeV as a function of PT in the 0-20% centrality range.

Mixed higher-order flow harmonic $v_6\{\Psi_{33}\}$ from the scalar-product method at 2.76 TeV as a function of PT in the 0-20% centrality range.

Mixed higher-order flow harmonic $v_7\{\Psi_{223}\}$ from the scalar-product method at 2.76 TeV as a function of PT in the 0-20% centrality range.

Mixed higher-order flow harmonic $v_4\{\Psi_{22}\}$ from the scalar-product method at 2.76 TeV as a function of PT in the 20-60% centrality range.

Mixed higher-order flow harmonic $v_5\{\Psi_{23}\}$ from the scalar-product method at 2.76 TeV as a function of PT in the 20-60% centrality range.

Mixed higher-order flow harmonic $v_6\{\Psi_{222}\}$ from the scalar-product method at 2.76 TeV as a function of PT in the 20-60% centrality range.

Mixed higher-order flow harmonic $v_6\{\Psi_{33}\}$ from the scalar-product method at 2.76 TeV as a function of PT in the 20-60% centrality range.

Mixed higher-order flow harmonic $v_7\{\Psi_{223}\}$ from the scalar-product method at 2.76 TeV as a function of PT in the 20-60% centrality range.

The overall flow harmonic $v_4\{\Psi_{4}\}$ from the scalar-product method at 5.02 TeV as a function of PT in the 0-20% centrality range.

The overall flow harmonic $v_5\{\Psi_{5}\}$ from the scalar-product method at 5.02 TeV as a function of PT in the 0-20% centrality range.

The overall flow harmonic $v_6\{\Psi_{6}\}$ from the scalar-product method at 5.02 TeV as a function of PT in the 0-20% centrality range.

The overall flow harmonic $v_6\{\Psi_{6}\}$ from the scalar-product method at 5.02 TeV as a function of PT in the 0-20% centrality range.

The overall flow harmonic $v_7\{\Psi_{7}\}$ from the scalar-product method at 5.02 TeV as a function of PT in the 0-20% centrality range.

The overall flow harmonic $v_4\{\Psi_{4}\}$ from the scalar-product method at 5.02 TeV as a function of PT in the 20-60% centrality range.

The overall flow harmonic $v_5\{\Psi_{5}\}$ from the scalar-product method at 5.02 TeV as a function of PT in the 20-60% centrality range.

The overall flow harmonic $v_6\{\Psi_{6}\}$ from the scalar-product method at 5.02 TeV as a function of PT in the 20-60% centrality range.

The overall flow harmonic $v_6\{\Psi_{6}\}$ from the scalar-product method at 5.02 TeV as a function of PT in the 20-60% centrality range.

The overall flow harmonic $v_7\{\Psi_{7}\}$ from the scalar-product method at 5.02 TeV as a function of PT in the 20-60% centrality range.

Mixed higher-order flow harmonic $v_4\{\Psi_{22}\}$ from the scalar-product method at 5.02 TeV as a function of PT in the 0-20% centrality range.

Mixed higher-order flow harmonic $v_5\{\Psi_{23}\}$ from the scalar-product method at 5.02 TeV as a function of PT in the 0-20% centrality range.

Mixed higher-order flow harmonic $v_6\{\Psi_{222}\}$ from the scalar-product method at 5.02 TeV as a function of PT in the 0-20% centrality range.

Mixed higher-order flow harmonic $v_6\{\Psi_{33}\}$ from the scalar-product method at 5.02 TeV as a function of PT in the 0-20% centrality range.

Mixed higher-order flow harmonic $v_7\{\Psi_{223}\}$ from the scalar-product method at 5.02 TeV as a function of PT in the 0-20% centrality range.

Mixed higher-order flow harmonic $v_4\{\Psi_{22}\}$ from the scalar-product method at 5.02 TeV as a function of PT in the 20-60% centrality range.

Mixed higher-order flow harmonic $v_5\{\Psi_{23}\}$ from the scalar-product method at 5.02 TeV as a function of PT in the 20-60% centrality range.

Mixed higher-order flow harmonic $v_6\{\Psi_{222}\}$ from the scalar-product method at 5.02 TeV as a function of PT in the 20-60% centrality range.

Mixed higher-order flow harmonic $v_6\{\Psi_{33}\}$ from the scalar-product method at 5.02 TeV as a function of PT in the 20-60% centrality range.

Mixed higher-order flow harmonic $v_7\{\Psi_{223}\}$ from the scalar-product method at 5.02 TeV as a function of PT in the 20-60% centrality range.

Nonlinear response coefficient $\chi_{422}$ from the scalar-product method at 5.02 TeV as a function of PT in the 0-20% centrality range.

Nonlinear response coefficient $\chi_{523}$ from the scalar-product method at 5.02 TeV as a function of PT in the 0-20% centrality range.

Nonlinear response coefficient $\chi_{6222}$ from the scalar-product method at 5.02 TeV as a function of PT in the 0-20% centrality range.

Nonlinear response coefficient $\chi_{633}$ from the scalar-product method at 5.02 TeV as a function of PT in the 0-20% centrality range.

Nonlinear response coefficient $\chi_{7223}$ from the scalar-product method at 5.02 TeV as a function of PT in the 0-20% centrality range.

Nonlinear response coefficient $\chi_{422}$ from the scalar-product method at 5.02 TeV as a function of PT in the 20-60% centrality range.

Nonlinear response coefficient $\chi_{523}$ from the scalar-product method at 5.02 TeV as a function of PT in the 20-60% centrality range.

Nonlinear response coefficient $\chi_{6222}$ from the scalar-product method at 5.02 TeV as a function of PT in the 20-60% centrality range.

Nonlinear response coefficient $\chi_{633}$ from the scalar-product method at 5.02 TeV as a function of PT in the 20-60% centrality range.

Nonlinear response coefficient $\chi_{7223}$ from the scalar-product method at 5.02 TeV as a function of PT in the 20-60% centrality range.

Nonlinear response coefficient $\chi_{422}$ from the scalar-product method at 2.76 TeV as a function of PT in the 0-20% centrality range.

Nonlinear response coefficient $\chi_{523}$ from the scalar-product method at 2.76 TeV as a function of PT in the 0-20% centrality range.

Nonlinear response coefficient $\chi_{6222}$ from the scalar-product method at 2.76 TeV as a function of PT in the 0-20% centrality range.

Nonlinear response coefficient $\chi_{633}$ from the scalar-product method at 2.76 TeV as a function of PT in the 0-20% centrality range.

Nonlinear response coefficient $\chi_{7223}$ from the scalar-product method at 2.76 TeV as a function of PT in the 0-20% centrality range.

Nonlinear response coefficient $\chi_{422}$ from the scalar-product method at 2.76 TeV as a function of PT in the 20-60% centrality range.

Nonlinear response coefficient $\chi_{523}$ from the scalar-product method at 2.76 TeV as a function of PT in the 20-60% centrality range.

Nonlinear response coefficient $\chi_{6222}$ from the scalar-product method at 2.76 TeV as a function of PT in the 20-60% centrality range.

Nonlinear response coefficient $\chi_{633}$ from the scalar-product method at 2.76 TeV as a function of PT in the 20-60% centrality range.

Nonlinear response coefficient $\chi_{7223}$ from the scalar-product method at 2.76 TeV as a function of PT in the 20-60% centrality range.

Mixed higher-order flow harmonic $v_4\{\Psi_{22}\}$ from the scalar-product method at 5.02 TeV as a function of centrality.

Mixed higher-order flow harmonic $v_5\{\Psi_{23}\}$ from the scalar-product method at 5.02 TeV as a function of centrality.

Mixed higher-order flow harmonic $v_6\{\Psi_{222}\}$ from the scalar-product method at 5.02 TeV as a function of centrality.

Mixed higher-order flow harmonic $v_6\{\Psi_{33}\}$ from the scalar-product method at 5.02 TeV as a function of centrality.

Mixed higher-order flow harmonic $v_7\{\Psi_{223}\}$ from the scalar-product method at 5.02 TeV as a function of centrality.

Mixed higher-order flow harmonic $v_4\{\Psi_{22}\}$ from the scalar-product method at 2.76 TeV as a function of centrality.

Mixed higher-order flow harmonic $v_5\{\Psi_{23}\}$ from the scalar-product method at 2.76 TeV as a function of centrality.

Mixed higher-order flow harmonic $v_6\{\Psi_{222}\}$ from the scalar-product method at 2.76 TeV as a function of centrality.

Mixed higher-order flow harmonic $v_6\{\Psi_{33}\}$ from the scalar-product method at 2.76 TeV as a function of centrality.

Mixed higher-order flow harmonic $v_7\{\Psi_{223}\}$ from the scalar-product method at 2.76 TeV as a function of centrality.

Nonlinear response coefficient $\chi_{422}$ from the scalar-product method at 5.02 TeV as a function of centrality.

Nonlinear response coefficient $\chi_{523}$ from the scalar-product method at 5.02 TeV as a function of centrality.

Nonlinear response coefficient $\chi_{6222}$ from the scalar-product method at 5.02 TeV as a function of centrality.

Nonlinear response coefficient $\chi_{633}$ from the scalar-product method at 5.02 TeV as a function of centrality.

Nonlinear response coefficient $\chi_{7223}$ from the scalar-product method at 5.02 TeV as a function of centrality.

Nonlinear response coefficient $\chi_{422}$ from the scalar-product method at 2.76 TeV as a function of centrality.

Nonlinear response coefficient $\chi_{523}$ from the scalar-product method at 2.76 TeV as a function of centrality.

Nonlinear response coefficient $\chi_{6222}$ from the scalar-product method at 2.76 TeV as a function of centrality.

Nonlinear response coefficient $\chi_{633}$ from the scalar-product method at 2.76 TeV as a function of centrality.

Nonlinear response coefficient $\chi_{7223}$ from the scalar-product method at 2.76 TeV as a function of centrality.

Nonlinear response coefficient $\chi_{422}$ from the scalar-product method at 5.02 TeV as a function of centrality.

Nonlinear response coefficient $\chi_{523}$ from the scalar-product method at 5.02 TeV as a function of centrality.

Nonlinear response coefficient $\chi_{6222}$ from the scalar-product method at 5.02 TeV as a function of centrality.

Nonlinear response coefficient $\chi_{633}$ from the scalar-product method at 5.02 TeV as a function of centrality.

Nonlinear response coefficient $\chi_{7223}$ from the scalar-product method at 5.02 TeV as a function of centrality.

Nonlinear response coefficient $\chi_{422}$ from the scalar-product method at 2.76 TeV as a function of centrality.

Nonlinear response coefficient $\chi_{523}$ from the scalar-product method at 2.76 TeV as a function of centrality.

Nonlinear response coefficient $\chi_{6222}$ from the scalar-product method at 2.76 TeV as a function of centrality.

Nonlinear response coefficient $\chi_{633}$ from the scalar-product method at 2.76 TeV as a function of centrality.

Nonlinear response coefficient $\chi_{7223}$ from the scalar-product method at 2.76 TeV as a function of centrality.