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.

The correlation matrix for the Higgs pT measurements, both for the unregularized and regularized fits. The last bin is inclusive.

The correlation matrix for the jet multiplicity measurements, both for the unregularized and regularized fits. The last bin is inclusive.

The correlation matrix for the leading jet pT measurements, both for the unregularized and regularized fits. The last bin is inclusive.

The fiducial integrated signal strength and cross section.

Jet angularity $\lambda_{\alpha}$ for $\alpha = 3$. $20<p_{\mathrm{T}}^{\mathrm{ch jet}}<40$. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Groomed jet angularity $\lambda_{\alpha,g}$ for $\alpha = 1$. $20<p_{\mathrm{T}}^{\mathrm{ch jet}}<40$, Soft Drop $z_{\mathrm{cut}}=0.2, \beta=0$. Note: The first bin corresponds to the Soft Drop untagged fraction. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Groomed jet angularity $\lambda_{\alpha,g}$ for $\alpha = 1.5$. $20<p_{\mathrm{T}}^{\mathrm{ch jet}}<40$, Soft Drop $z_{\mathrm{cut}}=0.2, \beta=0$. Note: The first bin corresponds to the Soft Drop untagged fraction. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Groomed jet angularity $\lambda_{\alpha,g}$ for $\alpha = 2$. $20<p_{\mathrm{T}}^{\mathrm{ch jet}}<40$, Soft Drop $z_{\mathrm{cut}}=0.2, \beta=0$. Note: The first bin corresponds to the Soft Drop untagged fraction. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Groomed jet angularity $\lambda_{\alpha,g}$ for $\alpha = 3$. $20<p_{\mathrm{T}}^{\mathrm{ch jet}}<40$, Soft Drop $z_{\mathrm{cut}}=0.2, \beta=0$. Note: The first bin corresponds to the Soft Drop untagged fraction. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Jet angularity $\lambda_{\alpha}$ for $\alpha = 1$. $40<p_{\mathrm{T}}^{\mathrm{ch jet}}<60$. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Jet angularity $\lambda_{\alpha}$ for $\alpha = 1.5$. $40<p_{\mathrm{T}}^{\mathrm{ch jet}}<60$. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Jet angularity $\lambda_{\alpha}$ for $\alpha = 2$. $40<p_{\mathrm{T}}^{\mathrm{ch jet}}<60$. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Jet angularity $\lambda_{\alpha}$ for $\alpha = 3$. $40<p_{\mathrm{T}}^{\mathrm{ch jet}}<60$. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Groomed jet angularity $\lambda_{\alpha,g}$ for $\alpha = 1$. $40<p_{\mathrm{T}}^{\mathrm{ch jet}}<60$, Soft Drop $z_{\mathrm{cut}}=0.2, \beta=0$. Note: The first bin corresponds to the Soft Drop untagged fraction. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Groomed jet angularity $\lambda_{\alpha,g}$ for $\alpha = 1.5$. $40<p_{\mathrm{T}}^{\mathrm{ch jet}}<60$, Soft Drop $z_{\mathrm{cut}}=0.2, \beta=0$. Note: The first bin corresponds to the Soft Drop untagged fraction. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Groomed jet angularity $\lambda_{\alpha,g}$ for $\alpha = 2$. $40<p_{\mathrm{T}}^{\mathrm{ch jet}}<60$, Soft Drop $z_{\mathrm{cut}}=0.2, \beta=0$. Note: The first bin corresponds to the Soft Drop untagged fraction. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Groomed jet angularity $\lambda_{\alpha,g}$ for $\alpha = 3$. $40<p_{\mathrm{T}}^{\mathrm{ch jet}}<60$, Soft Drop $z_{\mathrm{cut}}=0.2, \beta=0$. Note: The first bin corresponds to the Soft Drop untagged fraction. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Jet angularity $\lambda_{\alpha}$ for $\alpha = 1$. $60<p_{\mathrm{T}}^{\mathrm{ch jet}}<80$. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Jet angularity $\lambda_{\alpha}$ for $\alpha = 1.5$. $60<p_{\mathrm{T}}^{\mathrm{ch jet}}<80$. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Jet angularity $\lambda_{\alpha}$ for $\alpha = 2$. $60<p_{\mathrm{T}}^{\mathrm{ch jet}}<80$. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Jet angularity $\lambda_{\alpha}$ for $\alpha = 3$. $60<p_{\mathrm{T}}^{\mathrm{ch jet}}<80$. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Groomed jet angularity $\lambda_{\alpha,g}$ for $\alpha = 1$. $60<p_{\mathrm{T}}^{\mathrm{ch jet}}<80$, Soft Drop $z_{\mathrm{cut}}=0.2, \beta=0$. Note: The first bin corresponds to the Soft Drop untagged fraction. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Groomed jet angularity $\lambda_{\alpha,g}$ for $\alpha = 1.5$. $60<p_{\mathrm{T}}^{\mathrm{ch jet}}<80$, Soft Drop $z_{\mathrm{cut}}=0.2, \beta=0$. Note: The first bin corresponds to the Soft Drop untagged fraction. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Groomed jet angularity $\lambda_{\alpha,g}$ for $\alpha = 2$. $60<p_{\mathrm{T}}^{\mathrm{ch jet}}<80$, Soft Drop $z_{\mathrm{cut}}=0.2, \beta=0$. Note: The first bin corresponds to the Soft Drop untagged fraction. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Groomed jet angularity $\lambda_{\alpha,g}$ for $\alpha = 3$. $60<p_{\mathrm{T}}^{\mathrm{ch jet}}<80$, Soft Drop $z_{\mathrm{cut}}=0.2, \beta=0$. Note: The first bin corresponds to the Soft Drop untagged fraction. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Jet angularity $\lambda_{\alpha}$ for $\alpha = 1$. $80<p_{\mathrm{T}}^{\mathrm{ch jet}}<100$. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Jet angularity $\lambda_{\alpha}$ for $\alpha = 1.5$. $80<p_{\mathrm{T}}^{\mathrm{ch jet}}<100$. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Jet angularity $\lambda_{\alpha}$ for $\alpha = 2$. $80<p_{\mathrm{T}}^{\mathrm{ch jet}}<100$. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Jet angularity $\lambda_{\alpha}$ for $\alpha = 3$. $80<p_{\mathrm{T}}^{\mathrm{ch jet}}<100$. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Groomed jet angularity $\lambda_{\alpha,g}$ for $\alpha = 1$. $80<p_{\mathrm{T}}^{\mathrm{ch jet}}<100$, Soft Drop $z_{\mathrm{cut}}=0.2, \beta=0$. Note: The first bin corresponds to the Soft Drop untagged fraction. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Groomed jet angularity $\lambda_{\alpha,g}$ for $\alpha = 1.5$. $80<p_{\mathrm{T}}^{\mathrm{ch jet}}<100$, Soft Drop $z_{\mathrm{cut}}=0.2, \beta=0$. Note: The first bin corresponds to the Soft Drop untagged fraction. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Groomed jet angularity $\lambda_{\alpha,g}$ for $\alpha = 2$. $80<p_{\mathrm{T}}^{\mathrm{ch jet}}<100$, Soft Drop $z_{\mathrm{cut}}=0.2, \beta=0$. Note: The first bin corresponds to the Soft Drop untagged fraction. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Groomed jet angularity $\lambda_{\alpha,g}$ for $\alpha = 3$. $80<p_{\mathrm{T}}^{\mathrm{ch jet}}<100$, Soft Drop $z_{\mathrm{cut}}=0.2, \beta=0$. Note: The first bin corresponds to the Soft Drop untagged fraction. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Jet angularity $\lambda_{\alpha}$ for $\alpha = 1$. $20<p_{\mathrm{T}}^{\mathrm{ch jet}}<40$. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Jet angularity $\lambda_{\alpha}$ for $\alpha = 1.5$. $20<p_{\mathrm{T}}^{\mathrm{ch jet}}<40$. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Jet angularity $\lambda_{\alpha}$ for $\alpha = 2$. $20<p_{\mathrm{T}}^{\mathrm{ch jet}}<40$. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Jet angularity $\lambda_{\alpha}$ for $\alpha = 3$. $20<p_{\mathrm{T}}^{\mathrm{ch jet}}<40$. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Groomed jet angularity $\lambda_{\alpha,g}$ for $\alpha = 1$. $20<p_{\mathrm{T}}^{\mathrm{ch jet}}<40$, Soft Drop $z_{\mathrm{cut}}=0.2, \beta=0$. Note: The first bin corresponds to the Soft Drop untagged fraction. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Groomed jet angularity $\lambda_{\alpha,g}$ for $\alpha = 1.5$. $20<p_{\mathrm{T}}^{\mathrm{ch jet}}<40$, Soft Drop $z_{\mathrm{cut}}=0.2, \beta=0$. Note: The first bin corresponds to the Soft Drop untagged fraction. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Groomed jet angularity $\lambda_{\alpha,g}$ for $\alpha = 2$. $20<p_{\mathrm{T}}^{\mathrm{ch jet}}<40$, Soft Drop $z_{\mathrm{cut}}=0.2, \beta=0$. Note: The first bin corresponds to the Soft Drop untagged fraction. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Groomed jet angularity $\lambda_{\alpha,g}$ for $\alpha = 3$. $20<p_{\mathrm{T}}^{\mathrm{ch jet}}<40$, Soft Drop $z_{\mathrm{cut}}=0.2, \beta=0$. Note: The first bin corresponds to the Soft Drop untagged fraction. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Jet angularity $\lambda_{\alpha}$ for $\alpha = 1$. $40<p_{\mathrm{T}}^{\mathrm{ch jet}}<60$. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Jet angularity $\lambda_{\alpha}$ for $\alpha = 1.5$. $40<p_{\mathrm{T}}^{\mathrm{ch jet}}<60$. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Jet angularity $\lambda_{\alpha}$ for $\alpha = 2$. $40<p_{\mathrm{T}}^{\mathrm{ch jet}}<60$. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Jet angularity $\lambda_{\alpha}$ for $\alpha = 3$. $40<p_{\mathrm{T}}^{\mathrm{ch jet}}<60$. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Groomed jet angularity $\lambda_{\alpha,g}$ for $\alpha = 1$. $40<p_{\mathrm{T}}^{\mathrm{ch jet}}<60$, Soft Drop $z_{\mathrm{cut}}=0.2, \beta=0$. Note: The first bin corresponds to the Soft Drop untagged fraction. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Groomed jet angularity $\lambda_{\alpha,g}$ for $\alpha = 1.5$. $40<p_{\mathrm{T}}^{\mathrm{ch jet}}<60$, Soft Drop $z_{\mathrm{cut}}=0.2, \beta=0$. Note: The first bin corresponds to the Soft Drop untagged fraction. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Groomed jet angularity $\lambda_{\alpha,g}$ for $\alpha = 2$. $40<p_{\mathrm{T}}^{\mathrm{ch jet}}<60$, Soft Drop $z_{\mathrm{cut}}=0.2, \beta=0$. Note: The first bin corresponds to the Soft Drop untagged fraction. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Groomed jet angularity $\lambda_{\alpha,g}$ for $\alpha = 3$. $40<p_{\mathrm{T}}^{\mathrm{ch jet}}<60$, Soft Drop $z_{\mathrm{cut}}=0.2, \beta=0$. Note: The first bin corresponds to the Soft Drop untagged fraction. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Jet angularity $\lambda_{\alpha}$ for $\alpha = 1$. $60<p_{\mathrm{T}}^{\mathrm{ch jet}}<80$. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Jet angularity $\lambda_{\alpha}$ for $\alpha = 1.5$. $60<p_{\mathrm{T}}^{\mathrm{ch jet}}<80$. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Jet angularity $\lambda_{\alpha}$ for $\alpha = 2$. $60<p_{\mathrm{T}}^{\mathrm{ch jet}}<80$. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Jet angularity $\lambda_{\alpha}$ for $\alpha = 3$. $60<p_{\mathrm{T}}^{\mathrm{ch jet}}<80$. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Groomed jet angularity $\lambda_{\alpha,g}$ for $\alpha = 1$. $60<p_{\mathrm{T}}^{\mathrm{ch jet}}<80$, Soft Drop $z_{\mathrm{cut}}=0.2, \beta=0$. Note: The first bin corresponds to the Soft Drop untagged fraction. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Groomed jet angularity $\lambda_{\alpha,g}$ for $\alpha = 1.5$. $60<p_{\mathrm{T}}^{\mathrm{ch jet}}<80$, Soft Drop $z_{\mathrm{cut}}=0.2, \beta=0$. Note: The first bin corresponds to the Soft Drop untagged fraction. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Groomed jet angularity $\lambda_{\alpha,g}$ for $\alpha = 2$. $60<p_{\mathrm{T}}^{\mathrm{ch jet}}<80$, Soft Drop $z_{\mathrm{cut}}=0.2, \beta=0$. Note: The first bin corresponds to the Soft Drop untagged fraction. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Groomed jet angularity $\lambda_{\alpha,g}$ for $\alpha = 3$. $60<p_{\mathrm{T}}^{\mathrm{ch jet}}<80$, Soft Drop $z_{\mathrm{cut}}=0.2, \beta=0$. Note: The first bin corresponds to the Soft Drop untagged fraction. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Jet angularity $\lambda_{\alpha}$ for $\alpha = 1$. $80<p_{\mathrm{T}}^{\mathrm{ch jet}}<100$. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Jet angularity $\lambda_{\alpha}$ for $\alpha = 1.5$. $80<p_{\mathrm{T}}^{\mathrm{ch jet}}<100$. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Jet angularity $\lambda_{\alpha}$ for $\alpha = 2$. $80<p_{\mathrm{T}}^{\mathrm{ch jet}}<100$. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Jet angularity $\lambda_{\alpha}$ for $\alpha = 3$. $80<p_{\mathrm{T}}^{\mathrm{ch jet}}<100$. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Groomed jet angularity $\lambda_{\alpha,g}$ for $\alpha = 1$. $80<p_{\mathrm{T}}^{\mathrm{ch jet}}<100$, Soft Drop $z_{\mathrm{cut}}=0.2, \beta=0$. Note: The first bin corresponds to the Soft Drop untagged fraction. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Groomed jet angularity $\lambda_{\alpha,g}$ for $\alpha = 1.5$. $80<p_{\mathrm{T}}^{\mathrm{ch jet}}<100$, Soft Drop $z_{\mathrm{cut}}=0.2, \beta=0$. Note: The first bin corresponds to the Soft Drop untagged fraction. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Groomed jet angularity $\lambda_{\alpha,g}$ for $\alpha = 2$. $80<p_{\mathrm{T}}^{\mathrm{ch jet}}<100$, Soft Drop $z_{\mathrm{cut}}=0.2, \beta=0$. Note: The first bin corresponds to the Soft Drop untagged fraction. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

Groomed jet angularity $\lambda_{\alpha,g}$ for $\alpha = 3$. $80<p_{\mathrm{T}}^{\mathrm{ch jet}}<100$, Soft Drop $z_{\mathrm{cut}}=0.2, \beta=0$. Note: The first bin corresponds to the Soft Drop untagged fraction. For the "trkeff" and "generator" systematic uncertainty sources, the signed systematic uncertainty breakdowns ($\pm$ vs. $\mp$), denote correlation across bins (both within this table, and across tables). For the remaining sources ("unfolding", "random_mass") no correlation information is specified ($\pm$ is always used).

$\Delta\varphi$ projection of h-h correlation function with $3<p_{\mathrm{T}}^{\mathrm{trigg}}< 4 \mathrm{GeV}/c$ and $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

$\Delta\varphi$ projection of $K_S^0$-h correlation function with $3<p_{\mathrm{T}}^{\mathrm{trigg}}< 4 \mathrm{GeV}/c$ and $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

$\Delta\varphi$ projection of $K_S^0$-h correlation function with $3<p_{\mathrm{T}}^{\mathrm{trigg}}< 4 \mathrm{GeV}/c$ and $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

$\Delta\varphi$ projection of ($\Lambda+\overline{\Lambda}$)-h correlation function with $3<p_{\mathrm{T}}^{\mathrm{trigg}}< 4 \mathrm{GeV}/c$ and $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

$\Delta\varphi$ projection of ($\Lambda+\overline{\Lambda}$)-h correlation function with $3<p_{\mathrm{T}}^{\mathrm{trigg}}< 4 \mathrm{GeV}/c$ and $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

$\Delta\varphi$ projection of h-h correlation function with $9<p_{\mathrm{T}}^{\mathrm{trigg}}< 11 \mathrm{GeV}/c$ and $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

$\Delta\varphi$ projection of h-h correlation function with $9<p_{\mathrm{T}}^{\mathrm{trigg}}< 11 \mathrm{GeV}/c$ and $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

$\Delta\varphi$ projection of $K_S^0$-h correlation function with $9<p_{\mathrm{T}}^{\mathrm{trigg}}< 11 \mathrm{GeV}/c$ and $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

$\Delta\varphi$ projection of $K_S^0$-h correlation function with $9<p_{\mathrm{T}}^{\mathrm{trigg}}< 11 \mathrm{GeV}/c$ and $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

$\Delta\varphi$ projection of ($\Lambda+\overline{\Lambda}$)-h correlation function with $9<p_{\mathrm{T}}^{\mathrm{trigg}}< 11 \mathrm{GeV}/c$ and $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

$\Delta\varphi$ projection of ($\Lambda+\overline{\Lambda}$)-h correlation function with $9<p_{\mathrm{T}}^{\mathrm{trigg}}< 11 \mathrm{GeV}/c$ and $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

Per-trigger yields of h-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side with $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

Per-trigger yields of h-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side with $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

Per-trigger yields of $K_S^0$-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side with $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

Per-trigger yields of $K_S^0$-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side with $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

Per-trigger yields of ($\Lambda+\overline{\Lambda}$)-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side with $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

Per-trigger yields of ($\Lambda+\overline{\Lambda}$)-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side with $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

Per-trigger yields of h-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side with $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

Per-trigger yields of h-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side with $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

Per-trigger yields of $K_S^0$-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side with $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

Per-trigger yields of $K_S^0$-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side with $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

Per-trigger yields of ($\Lambda+\overline{\Lambda}$)-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side with $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

Per-trigger yields of ($\Lambda+\overline{\Lambda}$)-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side with $1 \mathrm{GeV}/c<p_{\mathrm{T}}^{\mathrm{assoc}}< p_{\mathrm{T}}^{\mathrm{trigg}} $

Ratio of the per-trigger yields in different multiplicity classes to the corresponding minimum bias yield for h-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side

Ratio of the per-trigger yields in different multiplicity classes to the corresponding minimum bias yield for h-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side

Ratio of the per-trigger yields in different multiplicity classes to the corresponding minimum bias yield for $K_S^0$-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side

Ratio of the per-trigger yields in different multiplicity classes to the corresponding minimum bias yield for $K_S^0$-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side

Ratio of the per-trigger yields in different multiplicity classes to the corresponding minimum bias yield for ($\Lambda+\overline{\Lambda}$)-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side

Ratio of the per-trigger yields in different multiplicity classes to the corresponding minimum bias yield for ($\Lambda+\overline{\Lambda}$)-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side

Ratio of the per-trigger yields in different multiplicity classes to the corresponding minimum bias yield for h-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side

Ratio of the per-trigger yields in different multiplicity classes to the corresponding minimum bias yield for h-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side

Ratio of the per-trigger yields in different multiplicity classes to the corresponding minimum bias yield for $K_S^0$-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side

Ratio of the per-trigger yields in different multiplicity classes to the corresponding minimum bias yield for $K_S^0$-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side

Ratio of the per-trigger yields in different multiplicity classes to the corresponding minimum bias yield for ($\Lambda+\overline{\Lambda}$)-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side

Ratio of the per-trigger yields in different multiplicity classes to the corresponding minimum bias yield for ($\Lambda+\overline{\Lambda}$)-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side

Per-trigger yields of h-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side from minimum bias

Per-trigger yields of h-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side from minimum bias

Per-trigger yields of $K_S^0$-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side from minimum bias

Per-trigger yields of $K_S^0$-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side from minimum bias

Per-trigger yields of ($\Lambda+\overline{\Lambda}$)-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side from minimum bias

Per-trigger yields of ($\Lambda+\overline{\Lambda}$)-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side from minimum bias

Per-trigger yields of h-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side from minimum bias

Per-trigger yields of h-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side from minimum bias

Per-trigger yields of $K_S^0$-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side from minimum bias

Per-trigger yields of $K_S^0$-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side from minimum bias

Per-trigger yields of ($\Lambda+\overline{\Lambda}$)-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side from minimum bias

Per-trigger yields of ($\Lambda+\overline{\Lambda}$)-h correlation functions as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side from minimum bias

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for minimum bias

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for minimum bias

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 0-1% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 0-1% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 1-3% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 1-3% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 3-7% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 3-7% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 7-15% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 7-15% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 15-50% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 15-50% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 50-100% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 50-100% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for minimum bias

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for minimum bias

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 0-1% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 0-1% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 1-3% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 1-3% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 3-7% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 3-7% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 7-15% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 7-15% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 15-50% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 15-50% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 50-100% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the near-side for 50-100% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for minimum bias

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for minimum bias

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 0-1% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 0-1% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 1-3% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 1-3% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 3-7% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 3-7% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 7-15% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 7-15% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 15-50% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 15-50% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 50-100% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 50-100% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for minimum bias

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for minimum bias

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 0-1% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 0-1% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 1-3% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 1-3% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 3-7% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 3-7% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 7-15% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 7-15% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 15-50% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 15-50% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 50-100% multiplicity class

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{trigg}}$ on the away-side for 50-100% multiplicity class

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $3 < p_{\mathrm{T}}^{\mathrm{trigg}} < 4 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $3 < p_{\mathrm{T}}^{\mathrm{trigg}} < 4 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $4 < p_{\mathrm{T}}^{\mathrm{trigg}} < 5 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $4 < p_{\mathrm{T}}^{\mathrm{trigg}} < 5 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $5 < p_{\mathrm{T}}^{\mathrm{trigg}} < 6 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $5 < p_{\mathrm{T}}^{\mathrm{trigg}} < 6 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $6 < p_{\mathrm{T}}^{\mathrm{trigg}} < 7 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $6 < p_{\mathrm{T}}^{\mathrm{trigg}} < 7 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $7 < p_{\mathrm{T}}^{\mathrm{trigg}} < 9 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $7 < p_{\mathrm{T}}^{\mathrm{trigg}} < 9 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $9 < p_{\mathrm{T}}^{\mathrm{trigg}} < 11 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $9 < p_{\mathrm{T}}^{\mathrm{trigg}} < 11 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $11 < p_{\mathrm{T}}^{\mathrm{trigg}} < 15 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $11 < p_{\mathrm{T}}^{\mathrm{trigg}} < 15 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $3 < p_{\mathrm{T}}^{\mathrm{trigg}} < 4 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $3 < p_{\mathrm{T}}^{\mathrm{trigg}} < 4 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $4 < p_{\mathrm{T}}^{\mathrm{trigg}} < 5 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $4 < p_{\mathrm{T}}^{\mathrm{trigg}} < 5 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $5 < p_{\mathrm{T}}^{\mathrm{trigg}} < 6 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $5 < p_{\mathrm{T}}^{\mathrm{trigg}} < 6 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $6 < p_{\mathrm{T}}^{\mathrm{trigg}} < 7 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $6 < p_{\mathrm{T}}^{\mathrm{trigg}} < 7 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $7 < p_{\mathrm{T}}^{\mathrm{trigg}} < 9 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $7 < p_{\mathrm{T}}^{\mathrm{trigg}} < 9 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $9 < p_{\mathrm{T}}^{\mathrm{trigg}} < 11 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $9 < p_{\mathrm{T}}^{\mathrm{trigg}} < 11 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $11 < p_{\mathrm{T}}^{\mathrm{trigg}} < 15 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the near-side for $11 < p_{\mathrm{T}}^{\mathrm{trigg}} < 15 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $3 < p_{\mathrm{T}}^{\mathrm{trigg}} < 4 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $3 < p_{\mathrm{T}}^{\mathrm{trigg}} < 4 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $4 < p_{\mathrm{T}}^{\mathrm{trigg}} < 5 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $4 < p_{\mathrm{T}}^{\mathrm{trigg}} < 5 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $5 < p_{\mathrm{T}}^{\mathrm{trigg}} < 6 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $5 < p_{\mathrm{T}}^{\mathrm{trigg}} < 6 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $6 < p_{\mathrm{T}}^{\mathrm{trigg}} < 7 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $6 < p_{\mathrm{T}}^{\mathrm{trigg}} < 7 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $7 < p_{\mathrm{T}}^{\mathrm{trigg}} < 9 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $7 < p_{\mathrm{T}}^{\mathrm{trigg}} < 9 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $9 < p_{\mathrm{T}}^{\mathrm{trigg}} < 11 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $9 < p_{\mathrm{T}}^{\mathrm{trigg}} < 11 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $11 < p_{\mathrm{T}}^{\mathrm{trigg}} < 15 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of $K_S^0$-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $11 < p_{\mathrm{T}}^{\mathrm{trigg}} < 15 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $3 < p_{\mathrm{T}}^{\mathrm{trigg}} < 4 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $3 < p_{\mathrm{T}}^{\mathrm{trigg}} < 4 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $4 < p_{\mathrm{T}}^{\mathrm{trigg}} < 5 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $4 < p_{\mathrm{T}}^{\mathrm{trigg}} < 5 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $5 < p_{\mathrm{T}}^{\mathrm{trigg}} < 6 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $5 < p_{\mathrm{T}}^{\mathrm{trigg}} < 6 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $6 < p_{\mathrm{T}}^{\mathrm{trigg}} < 7 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $6 < p_{\mathrm{T}}^{\mathrm{trigg}} < 7 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $7 < p_{\mathrm{T}}^{\mathrm{trigg}} < 9 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $7 < p_{\mathrm{T}}^{\mathrm{trigg}} < 9 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $9 < p_{\mathrm{T}}^{\mathrm{trigg}} < 11 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $9 < p_{\mathrm{T}}^{\mathrm{trigg}} < 11 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $11 < p_{\mathrm{T}}^{\mathrm{trigg}} < 15 \mathrm{GeV}/c$

Ratios of integrated per-trigger yield of ($\Lambda+\overline{\Lambda}$)-h to h-h as a function of $p_{\mathrm{T}}^{\mathrm{assoc}}$ on the away-side for $11 < p_{\mathrm{T}}^{\mathrm{trigg}} < 15 \mathrm{GeV}/c$

$v_2\{2, |\Delta\eta| > 2.0\}$ of $\pi^{\pm}$ as a function of $p_{\rm T}$ for the 20-30% centrality interval.

$v_2\{2, |\Delta\eta| > 2.0\}$ of $\pi^{\pm}$ as a function of $p_{\rm T}$ for the 30-40% centrality interval.

$v_2\{2, |\Delta\eta| > 2.0\}$ of $\pi^{\pm}$ as a function of $p_{\rm T}$ for the 40-50% centrality interval.

$v_2\{2, |\Delta\eta| > 2.0\}$ of $\pi^{\pm}$ as a function of $p_{\rm T}$ for the 50-60% centrality interval.

$v_2\{2, |\Delta\eta| > 2.0\}$ of $\rm{K}^{\pm}$ as a function of $p_{\rm T}$ for the 0-5% centrality interval.

$v_2\{2, |\Delta\eta| > 2.0\}$ of $\rm{K}^{\pm}$ as a function of $p_{\rm T}$ for the 5-10% centrality interval.

$v_2\{2, |\Delta\eta| > 2.0\}$ of $\rm{K}^{\pm}$ as a function of $p_{\rm T}$ for the 10-20% centrality interval.

$v_2\{2, |\Delta\eta| > 2.0\}$ of $\rm{K}^{\pm}$ as a function of $p_{\rm T}$ for the 20-30% centrality interval.

$v_2\{2, |\Delta\eta| > 2.0\}$ of $\rm{K}^{\pm}$ as a function of $p_{\rm T}$ for the 30-40% centrality interval.

$v_2\{2, |\Delta\eta| > 2.0\}$ of $\rm{K}^{\pm}$ as a function of $p_{\rm T}$ for the 40-50% centrality interval.

$v_2\{2, |\Delta\eta| > 2.0\}$ of $\rm{K}^{\pm}$ as a function of $p_{\rm T}$ for the 50-60% centrality interval.

$v_2\{2, |\Delta\eta| > 2.0\}$ of p+$\rm\overline{p}$ as a function of $p_{\rm T}$ for the 0-5% centrality interval.

$v_2\{2, |\Delta\eta| > 2.0\}$ of p+$\rm\overline{p}$ as a function of $p_{\rm T}$ for the 5-10% centrality interval.

$v_2\{2, |\Delta\eta| > 2.0\}$ of p+$\rm\overline{p}$ as a function of $p_{\rm T}$ for the 10-20% centrality interval.

$v_2\{2, |\Delta\eta| > 2.0\}$ of p+$\rm\overline{p}$ as a function of $p_{\rm T}$ for the 20-30% centrality interval.

$v_2\{2, |\Delta\eta| > 2.0\}$ of p+$\rm\overline{p}$ as a function of $p_{\rm T}$ for the 30-40% centrality interval.

$v_2\{2, |\Delta\eta| > 2.0\}$ of p+$\rm\overline{p}$ as a function of $p_{\rm T}$ for the 40-50% centrality interval.

$v_2\{2, |\Delta\eta| > 2.0\}$ of p+$\rm\overline{p}$ as a function of $p_{\rm T}$ for the 50-60% centrality interval.

$v_2\{2, |\Delta\eta| > 2.0\}$ of ${\rm K}^{0}_{\rm{S}}$ as a function of $p_{\rm T}$ for the 0-5% centrality interval.

$v_2\{2, |\Delta\eta| > 2.0\}$ of ${\rm K}^{0}_{\rm{S}}$ as a function of $p_{\rm T}$ for the 5-10% centrality interval.

$v_2\{2, |\Delta\eta| > 2.0\}$ of ${\rm K}^{0}_{\rm{S}}$ as a function of $p_{\rm T}$ for the 10-20% centrality interval.

$v_2\{2, |\Delta\eta| > 2.0\}$ of ${\rm K}^{0}_{\rm{S}}$ as a function of $p_{\rm T}$ for the 20-30% centrality interval.

$v_2\{2, |\Delta\eta| > 2.0\}$ of ${\rm K}^{0}_{\rm{S}}$ as a function of $p_{\rm T}$ for the 30-40% centrality interval.

$v_2\{2, |\Delta\eta| > 2.0\}$ of ${\rm K}^{0}_{\rm{S}}$ as a function of $p_{\rm T}$ for the 40-50% centrality interval.

$v_2\{2, |\Delta\eta| > 2.0\}$ of ${\rm K}^{0}_{\rm{S}}$ as a function of $p_{\rm T}$ for the 50-60% centrality interval.

$v_2\{2, |\Delta\eta| > 2.0\}$ of $\Lambda$+$\overline{\Lambda}$ as a function of $p_{\rm T}$ for the 0-5% centrality interval.

$v_2\{2, |\Delta\eta| > 2.0\}$ of $\Lambda$+$\overline{\Lambda}$ as a function of $p_{\rm T}$ for the 5-10% centrality interval.

$v_2\{2, |\Delta\eta| > 2.0\}$ of $\Lambda$+$\overline{\Lambda}$ as a function of $p_{\rm T}$ for the 10-20% centrality interval.

$v_2\{2, |\Delta\eta| > 2.0\}$ of $\Lambda$+$\overline{\Lambda}$ as a function of $p_{\rm T}$ for the 20-30% centrality interval.

$v_2\{2, |\Delta\eta| > 2.0\}$ of $\Lambda$+$\overline{\Lambda}$ as a function of $p_{\rm T}$ for the 30-40% centrality interval.

$v_2\{2, |\Delta\eta| > 2.0\}$ of $\Lambda$+$\overline{\Lambda}$ as a function of $p_{\rm T}$ for the 40-50% centrality interval.

$v_2\{2, |\Delta\eta| > 2.0\}$ of $\Lambda$+$\overline{\Lambda}$ as a function of $p_{\rm T}$ for the 50-60% centrality interval.

$v_3\{2, |\Delta\eta| > 2.0\}$ of $\pi^{\pm}$ as a function of $p_{\rm T}$ for the 0-10% centrality interval.

$v_3\{2, |\Delta\eta| > 2.0\}$ of $\pi^{\pm}$ as a function of $p_{\rm T}$ for the 10-30% centrality interval.

$v_3\{2, |\Delta\eta| > 2.0\}$ of $\pi^{\pm}$ as a function of $p_{\rm T}$ for the 30-50% centrality interval.

$v_3\{2, |\Delta\eta| > 2.0\}$ of $\rm{K}^{\pm}$ as a function of $p_{\rm T}$ for the 0-10% centrality interval.

$v_3\{2, |\Delta\eta| > 2.0\}$ of $\rm{K}^{\pm}$ as a function of $p_{\rm T}$ for the 10-30% centrality interval.

$v_3\{2, |\Delta\eta| > 2.0\}$ of $\rm{K}^{\pm}$ as a function of $p_{\rm T}$ for the 30-50% centrality interval.

$v_3\{2, |\Delta\eta| > 2.0\}$ of p+$\rm\overline{p}$ as a function of $p_{\rm T}$ for the 0-10% centrality interval.

$v_3\{2, |\Delta\eta| > 2.0\}$ of p+$\rm\overline{p}$ as a function of $p_{\rm T}$ for the 10-30% centrality interval.

$v_3\{2, |\Delta\eta| > 2.0\}$ of p+$\rm\overline{p}$ as a function of $p_{\rm T}$ for the 30-50% centrality interval.

The $p_{\rm T}$ of $v_2^{\mathrm{max}}$ for $\pi^{\pm}$ as a function of centrality.

The $p_{\rm T}$ of $v_2^{\mathrm{max}}$ for p+$\rm\overline{p}$ as a function of centrality.

${p}_{T}^{miss}$ distribution of data and MC events in the signal region with the signal stacked on top of the background prediction for a mass hypothesis of ${m}_{stop} = 225GeV$ and ${m}_{LSP} = 50 GeV$. Events from ttW, ttZ, DY, non-prompt leptons, and diboson processes are grouped into the 'Other' category. The lower panel contains the data-to-prediction ratio. The uncertainty band includes statistical, background normalization and all systematic uncertainties.

${p}_{T}^{miss}$ normalized distribution for signal points with different top squark and neutralino masses and SM ttbar events are compared.

${m}_{T2} (e\mu)$ normalized distribution for signal points with different top squark and neutralino masses and SM ttbar events are compared.

$\Delta\eta (e\mu)$ normalized distribution for signal points with different top squark and neutralino masses and SM ttbar events are compared.

$\Delta\phi (e\mu)$ normalized distribution for signal points with different top squark and neutralino masses and SM ttbar events are compared.

Normalized DNN score distribution in the signal region for two mass hypotheses to compare signal and ttbar background: $m_{LSP}=$ 50 (100) GeV and $m_{stop}=$ 225 (275) GeV.

Post-fit DNN score distributions in the signal region with the signal superimposed and scaled by a factor of 20 for different mass hypotheses of $({m}_{stop}, {m}_{LSP})=$ (225, 50) GeV. The uncertainty band includes statistical, background normalization, and all systematic uncertainties. Events from ttW, ttZ, DY, non-prompt leptons, and diboson processes are grouped into the 'Other' category. The lower panel contains the data-to-prediction ratio before the fit (line) and after (dots), each of them with their corresponding band of uncertainties, and the ratio between the sum of the signal and background predictions and the background prediction. The masses of the signal model correspond to the values of the DNN mass parameters in each distribution.

Post-fit DNN score distributions in the signal region with the signal superimposed and scaled by a factor of 20 for different mass hypotheses of $({m}_{stop}, {m}_{LSP})=$ (275, 100) GeV. The uncertainty band includes statistical, background normalization, and all systematic uncertainties. Events from ttW, ttZ, DY, non-prompt leptons, and diboson processes are grouped into the 'Other' category. The lower panel contains the data-to-prediction ratio before the fit (line) and after (dots), each of them with their corresponding band of uncertainties, and the ratio between the sum of the signal and background predictions and the background prediction. The masses of the signal model correspond to the values of the DNN mass parameters in each distribution.

Post-fit DNN score distributions in the signal region with the signal superimposed and scaled by a factor of 20 for different mass hypotheses of $({m}_{stop}, {m}_{LSP})=$ (275, 70) GeV. The uncertainty band includes statistical, background normalization, and all systematic uncertainties. Events from ttW, ttZ, DY, non-prompt leptons, and diboson processes are grouped into the 'Other' category. The lower panel contains the data-to-prediction ratio before the fit (line) and after (dots), each of them with their corresponding band of uncertainties, and the ratio between the sum of the signal and background predictions and the background prediction. The masses of the signal model correspond to the values of the DNN mass parameters in each distribution.

Post-fit DNN score distributions in the signal region with the signal superimposed and scaled by a factor of 20 for different mass hypotheses of $({m}_{stop}, {m}_{LSP})=$ (245, 100) GeV. The uncertainty band includes statistical, background normalization, and all systematic uncertainties. Events from ttW, ttZ, DY, non-prompt leptons, and diboson processes are grouped into the 'Other' category. The lower panel contains the data-to-prediction ratio before the fit (line) and after (dots), each of them with their corresponding band of uncertainties, and the ratio between the sum of the signal and background predictions and the background prediction. The masses of the signal model correspond to the values of the DNN mass parameters in each distribution.

Upper limit at 95% CL on the signal cross section as a function of the top squark and neutralino masses. The model is excluded for all of the colored region inside the black boundary.

Upper limit at 95% CL on the signal cross section as a function of the top squark mass for mass difference of 175 GeV. The green and yellow bands represent the regions containing 68 and 95%, respectively, of the distribution of limits expected under the background-only hypothesis. The purple dotted line indicates the approximate NNLO + NNLL productioncross section.

Upper limit at 95% CL on the signal cross section as a function of the top squark mass for mass difference of 185 GeV. The green and yellow bands represent the regions containing 68 and 95%, respectively, of the distribution of limits expected under the background-only hypothesis. The purple dotted line indicates the approximate NNLO + NNLL productioncross section.

Upper limit at 95% CL on the signal cross section as a function of the top squark mass for mass difference of 165 GeV. The green and yellow bands represent the regions containing 68 and 95%, respectively, of the distribution of limits expected under the background-only hypothesis. The purple dotted line indicates the approximate NNLO + NNLL productioncross section.

Summary of the contributions of the experimental uncertainties in the DNN score distribution for signal and the ttbar background. The values represent the relative variation in the number of expected events across different signal models in the signal region.

Summary of the contribution of each modeling uncertainty source to the DNN score distribution for the ttbar background.

95% CL expected upper limit on top squark cross section for the direct decay model.

95% CL observed upper limit on top squark cross section for the direct decay model.

Contour of the region excluded with 95% CL (expected).

Contour of the region excluded with 95% CL (observed).

95% CL expected upper limit on top squark cross section for the cascade decay model.

95% CL observed upper limit on top squark cross section for the cascade decay model.

Contour of the region excluded with 95% CL (expected).

Contour of the region excluded with 95% CL (observed).

95% CL expected upper limit on top squark cross section for the mixed decay model.

95% CL observed upper limit on top squark cross section for the mixed decay model.

Contour of the region excluded with 95% CL (expected).

Contour of the region excluded with 95% CL (observed).

95% CL expected limit on $\sigma/\sigma_{theory}$ for a fermionic DM particle with m = 1 GeV, as a function of the mediator mass for a scalar.

95% CL observed limit on $\sigma/\sigma_{theory}$ for a fermionic DM particle with m = 1 GeV, as a function of the mediator mass for a scalar.

95% CL expected limit on $\sigma/\sigma_{theory}$ for a fermionic DM particle with m = 1 GeV, as a function of the mediator mass for a pseudoscalar.

95% CL observed limit on $\sigma/\sigma_{theory}$ for a fermionic DM particle with m = 1 GeV, as a function of the mediator mass for a pseudoscalar.

Pb-remnant side ZN signal normalized to MB value vs. ZN centrality percentile in p-Pb collisions at 8.16 TeV

p-remnant side ZN signal normalized to MB value vs. ZN centrality percentile in p-Pb collisions at 5.02 TeV

p-remnant side ZN signal normalized to MB value vs. ZN centrality percentile in p-Pb collisions at 8.16 TeV

Pb-remnant side ZN signal normalized to MB value vs. average Ncoll in p-Pb collisions at 5.02 TeV

Pb-remnant side ZN signal normalized to MB value vs. average Ncoll in p-Pb collisions at 8.16 TeV

p-remnant side ZN signal normalized to MB value vs. average Ncoll in p-Pb collisions at 5.02 TeV

p-remnant side ZN signal normalized to MB value vs. average Ncoll in p-Pb collisions at 8.16 TeV

ZN signal normalized to MB value vs. normalized charged-particle multiplicity in p-p collisions at 13 TeV

p-remnant side ZN signal normalized to MB value vs. normalized charged-particle multiplicity in p-Pb collisions at 8.16 TeV

ZP signal normalized to MB value vs. normalized charged-particle multiplicity in p-p collisions at 13 TeV

p-remnant side ZP signal normalized to MB value vs. average charged-particle multiplicity in p-Pb collisions at 8.16 TeV

ZN signal normalized to MB value vs. leading transverse momentum in |eta|<0.8 in p-p collisions at 13 TeV

ZP signal normalized to MB value vs. leading transverse momentum in |eta|<0.8 in p-p collisions at 13 TeV

Differential cross section as a function of $m_{\gamma\gamma}$. The table contains the values measured in data and theory predictions from SHERPA, DIPHOX and NNLOJET.

Differential cross section as a function of $p_{T,\gamma\gamma}$. The table contains the values measured in data and theory predictions from SHERPA, DIPHOX and NNLOJET.

Differential cross section as a function of $a_{T,\gamma\gamma}$. The table contains the values measured in data and theory predictions from SHERPA, DIPHOX and NNLOJET.

Differential cross section as a function of $\phi_{\eta}*$. The table contains the values measured in data and theory predictions from SHERPA, DIPHOX and NNLOJET.

Differential cross section as a function of $\pi-\Delta\phi_{\gamma\gamma}$. The table contains the values measured in data and theory predictions from SHERPA, DIPHOX and NNLOJET.

Differential cross section as a function of $|cos\theta*|^{(CS)}$. The table contains the values measured in data and theory predictions from SHERPA, DIPHOX and NNLOJET.

$\Lambda_{b}^{0}$ production asymmetry in bins of $\Lambda_{b}^{0}$ $p_T$ for proton-proton collisions with $\sqrt{s} = 8$ TeV. The first uncertainty is statistical and the second represents the systematic uncertainty. The results in neighbouring intervals are correlated.

Covariance matrix of the statistical uncertainty on $\Lambda_{b}^{0}$ production asymmetry in bins of $\Lambda_{b}^{0}$ rapidity for proton-proton collisions with $\sqrt{s} = 7$ TeV.

Covariance matrix of the statistical uncertainty on $\Lambda_{b}^{0}$ production asymmetry in bins of $\Lambda_{b}^{0}$ rapidity for proton-proton collisions with $\sqrt{s} = 8$ TeV.

Covariance matrix of the systematic uncertainty on $\Lambda_{b}^{0}$ production asymmetry in bins of $\Lambda_{b}^{0}$ rapidity for proton-proton collisions with $\sqrt{s} = 7$ TeV.

Covariance matrix of the systematic uncertainty on $\Lambda_{b}^{0}$ production asymmetry in bins of $\Lambda_{b}^{0}$ rapidity for proton-proton collisions with $\sqrt{s} = 8$ TeV.

Measured, normalised distribution of $p_T, y$ from background-subtracted $\Lambda_{b}^{0}$ candidates for $\sqrt{s} = 7$ TeV. Distribution is not corrected for the detector efficiency. Darker areas correspond tp mpre densely populated regions.

Measured, normalised distribution of $p_T, y$ from background-subtracted $\Lambda_{b}^{0}$ candidates for $\sqrt{s} = 8$ TeV. Distribution is not corrected for the detector efficiency. Darker areas correspond tp mpre densely populated regions.

$v_3$ vs $p_T$, p+Au at 200 GeV, 0-5% central, BBCS-FVTXS-CNT detector combination

$v_3$ vs $p_T$, d+Au at 200 GeV, 0-5% central, BBCS-FVTXS-CNT detector combination

$v_3$ vs $p_T$, 3He+Au at 200 GeV, 0-5% central, BBCS-FVTXS-CNT detector combination

$v_2$ vs $p_T$, p+Au at 200 GeV, 0-5% central, FVTXS-CNT-FVTXN detector combination

$v_2$ vs $p_T$, d+Au at 200 GeV, 0-5% central, FVTXS-CNT-FVTXN detector combination

$v_2$ vs $p_T$, 3He+Au at 200 GeV, 0-5% central, FVTXS-CNT-FVTXN detector combination

$v_2$ ratio vs $p_T$, p/d/3He+Au at 200 GeV, 0-5% central

$v_3$ vs $p_T$, p+Au at 200 GeV, 0-5% central, FVTXS-CNT-FVTXN detector combination

$v_3$ vs $p_T$, d+Au at 200 GeV, 0-5% central, FVTXS-CNT-FVTXN detector combination

$v_3$ vs $p_T$, 3He+Au at 200 GeV, 0-5% central, FVTXS-CNT-FVTXN detector combination

$c_2$ vs $\eta$, p+Au at 200 GeV, 0-5% central

$c_2$ vs $\eta$, d+Au at 200 GeV, 0-5% central

$c_2$ vs $\eta$, 3He+Au at 200 GeV, 0-5% central

$c_3$ vs $\eta$, p+Au at 200 GeV, 0-5% central

$c_3$ vs $\eta$, d+Au at 200 GeV, 0-5% central

$c_3$ vs $\eta$, 3He+Au at 200 GeV, 0-5% central

$C(\Delta\phi)$ vs $\Delta\phi$, p+p at 200 GeV, minimum bias, BBCS-FVTXS correlation

$C(\Delta\phi)$ vs $\Delta\phi$, p+Au at 200 GeV, 0-5% central, BBCS-FVTXS correlation

$C(\Delta\phi)$ vs $\Delta\phi$, d+Au at 200 GeV, 0-5% central, BBCS-FVTXS correlation

$C(\Delta\phi)$ vs $\Delta\phi$, 3He+Au at 200 GeV, 0-5% central, BBCS-FVTXS correlation

$C(\Delta\phi)$ vs $\Delta\phi$, p+p at 200 GeV, minimum bias, BBCS-FVTXN correlation

$C(\Delta\phi)$ vs $\Delta\phi$, p+Au at 200 GeV, 0-5% central, BBCS-FVTXN correlation

$C(\Delta\phi)$ vs $\Delta\phi$, d+Au at 200 GeV, 0-5% central, BBCS-FVTXN correlation

$C(\Delta\phi)$ vs $\Delta\phi$, 3He+Au at 200 GeV, 0-5% central, BBCS-FVTXN correlation

$C(\Delta\phi)$ vs $\Delta\phi$, p+p at 200 GeV, minimum bias, FVTXS-FVTXN correlation

$C(\Delta\phi)$ vs $\Delta\phi$, p+Au at 200 GeV, 0-5% central, FVTXS-FVTXN correlation

$C(\Delta\phi)$ vs $\Delta\phi$, d+Au at 200 GeV, 0-5% central, FVTXS-FVTXN correlation

$C(\Delta\phi)$ vs $\Delta\phi$, 3He+Au at 200 GeV, 0-5% central, FVTXS-FVTXN correlation

$C(\Delta\phi)$ vs $\Delta\phi$, p+p at 200 GeV, minimum bias, CNT-BBCS correlation

$C(\Delta\phi)$ vs $\Delta\phi$, p+Au at 200 GeV, 0-5% central, CNT-BBCS correlation

$C(\Delta\phi)$ vs $\Delta\phi$, d+Au at 200 GeV, 0-5% central, CNT-BBCS correlation

$C(\Delta\phi)$ vs $\Delta\phi$, 3He+Au at 200 GeV, 0-5% central, CNT-BBCS correlation

$C(\Delta\phi)$ vs $\Delta\phi$, p+p at 200 GeV, minimum bias, CNT-FVTXS correlation

$C(\Delta\phi)$ vs $\Delta\phi$, p+Au at 200 GeV, 0-5% central, CNT-FVTXS correlation

$C(\Delta\phi)$ vs $\Delta\phi$, d+Au at 200 GeV, 0-5% central, CNT-FVTXS correlation

$C(\Delta\phi)$ vs $\Delta\phi$, 3He+Au at 200 GeV, 0-5% central, CNT-FVTXS correlation

$C(\Delta\phi)$ vs $\Delta\phi$, p+p at 200 GeV, minimum bias, CNT-FVTXN correlation

$C(\Delta\phi)$ vs $\Delta\phi$, p+Au at 200 GeV, 0-5% central, CNT-FVTXN correlation

$C(\Delta\phi)$ vs $\Delta\phi$, d+Au at 200 GeV, 0-5% central, CNT-FVTXN correlation

$C(\Delta\phi)$ vs $\Delta\phi$, 3He+Au at 200 GeV, 0-5% central, CNT-FVTXN correlation

$c_n$ vs detector combination, p+p at 200 GeV, Minimum Bias

$c_n$ vs $p_T$, p+p at 200 GeV, Minimum Bias, BBCS-CNT detector combination

$c_n$ vs $p_T$, p+p at 200 GeV, Minimum Bias, FVTXS-CNT detector combination

$c_n$ vs $p_T$, p+p at 200 GeV, Minimum Bias, FVTXN-CNT detector combination

$c_n$ vs detector combination, p+Au at 200 GeV, 0-5% central

$c_n$ vs $p_T$, p+Au at 200 GeV, 0-5% central, BBCS-CNT detector combination

$c_n$ vs $p_T$, p+Au at 200 GeV, 0-5% central, FVTXS-CNT detector combination

$c_n$ vs $p_T$, p+Au at 200 GeV, 0-5% central, FVTXN-CNT detector combination

$c_n$ vs detector combination, p+Au at 200 GeV, 0-5% central

$c_n$ vs $p_T$, p+Au at 200 GeV, 0-5% central, BBCS-CNT detector combination

$c_n$ vs $p_T$, p+Au at 200 GeV, 0-5% central, FVTXS-CNT detector combination

$c_n$ vs $p_T$, p+Au at 200 GeV, 0-5% central, FVTXN-CNT detector combination

$c_n$ vs detector combination, p+Au at 200 GeV, 0-5% central

$c_n$ vs $p_T$, 3He+Au at 200 GeV, 0-5% central, BBCS-CNT detector combination

$c_n$ vs $p_T$, 3He+Au at 200 GeV, 0-5% central, FVTXS-CNT detector combination

$c_n$ vs $p_T$, 3He+Au at 200 GeV, 0-5% central, FVTXN-CNT detector combination