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FIG. 2: a) left side: The correlation data for the ratio of the histograms of same-event-pairs to mixed-event-pairs for unlike-sign charged pairs, shown in a two-dimensional (2-D) perspective plot $\Delta\phi$ - $\Delta\eta$. The plot was normalized to a mean of 1. b) right side: The similar correlation data for like-sign charge pairs.

FIG. 3: a) left side: Folded correlation data for unlike-sign charge pairs on $\Delta\phi$ and $\Delta\eta$ based on demonstrated symmetries in the data. This increases the statistics in a typical bin by a factor of four. Henceforth we will be dealing with folded data only. b) right side: Similar folded data for like-sign charge pairs.

FIG. 3: a) left side: Folded correlation data for unlike-sign charge pairs on $\Delta\phi$ and $\Delta\eta$ based on demonstrated symmetries in the data. This increases the statistics in a typical bin by a factor of four. Henceforth we will be dealing with folded data only. b) right side: Similar folded data for like-sign charge pairs.

FIG. 4: “(Color online)”a) left side: The 2 dimensional (2-D) approximately gaussian signal shape equation (4) from the fit to the normalized and folded unlike-sign charge pairs signal data. b) right side: The unlike-sign charge pairs signal data corresponding to the adjoining signal function on the left side.

FIG. 4: “(Color online)”a) left side: The 2 dimensional (2-D) approximately gaussian signal shape equation (4) from the fit to the normalized and folded unlike-sign charge pairs signal data. b) right side: The unlike-sign charge pairs signal data corresponding to the adjoining signal function on the left side.

FIG. 5 :“(Color online)”a) left side: A perspective plot of the fit to the 2-D like-sign charge pairs signal shape of equation (5). b) right side: Like-sign charge pairs signal data corresponding to the adjacent signal fit on the left side.

FIG. 5: “(Color online)”a) left side: A perspective plot of the fit to the 2-D like-sign charge pairs signal shape of equation (5). b) right side: Like-sign charge pairs signal data corresponding to the adjacent signal fit on the left side.

FIG. 6: “(Color online)”a) left side: The charge dependent (CD) signal shape is a 2 dimensional (2-D) approximate gaussian which is symmetrical. The average gaussian width is 27.5$^{\circ}$ $\pm$ 3.2$^{\circ}$ (0.48 $\pm$ 0.056 rad) both in $\Delta\phi$ and $\Delta\eta$. Thus we are observing a greater probability for unlike-sign charge pairs of particles than for like-sign charge pairs emitted randomly on 2-D $\eta\phi$ directions. b) right side: The CD signal data corresponding to the adjacent signal fit on the left.

FIG. 6: “(Color online)”a) left side: The charge dependent (CD) signal shape is a 2 dimensional (2-D) approximate gaussian which is symmetrical. The average gaussian width is 27.5$^{\circ}$ $\pm$ 3.2$^{\circ}$ (0.48 $\pm$ 0.056 rad) both in $\Delta\phi$ and $\Delta\eta$. Thus we are observing a greater probability for unlike-sign charge pairs of particles than for like-sign charge pairs emitted randomly on 2-D $\eta\phi$ directions. b) right side: The CD signal data corresponding to the adjacent signal fit on the left.

FIG. 7: “(Color online)”a) left side: The fit to the charge independent (CI) signal shape which is the sum of the fits of like-sign plus unlike-sign charge pairs signals. The 2-D gaussian equivalent RMS signal has a $\Delta\phi$ width of about 32$^{\circ}$ (0.52 rad), and $\Delta\eta$ width of about 66$^{\circ}$ (1.15 rad) which is about double the $\Delta\phi$ width. b) right side: The CI signal data corresponding to the adjacent fit on the left.

FIG. 7: “(Color online)”a) left side: The fit to the charge independent (CI) signal shape which is the sum of the fits of like-sign plus unlike-sign charge pairs signals. The 2-D gaussian equivalent RMS signal has a $\Delta\phi$ width of about 32$^{\circ}$ (0.52 rad), and $\Delta\eta$ width of about 66$^{\circ}$ (1.15 rad) which is about double the $\Delta\phi$ width. b) right side: The CI signal data corresponding to the adjacent fit on the left.

FIG. 8: a) left side: The charge independent (CI) signal data with the lower range of elliptic flow amplitude and the best $\chi^2$ (the same as Figure 7b) plotted as a 2-D perspective plot on $\Delta\phi$ vs. $\Delta\eta$. b) right side: The charge independent (CI) signal data with our maximum elliptic flow amplitude used in our analysis ($\chi^2$ was worse by 1$\sigma$).

FIG. 8: a) left side: The charge independent (CI) signal data with the lower range of elliptic flow amplitude and the best $\chi^2$ (the same as Figure 7b) plotted as a 2-D perspective plot on $\Delta\phi$ vs. $\Delta\eta$. b) right side: The charge independent (CI) signal data with our maximum elliptic flow amplitude used in our analysis ($\chi^2$ was worse by 1$\sigma$).

The dependence of the jet shapes on the transverse jet energy ET in the pseudorapidity range < 1.5 and the ET range > 8 GeV using the inclusive KT jet finding algorithm.

The dependence of the jet shapes on the transverse jet energy ET in the pseudorapidity range 1.5 TO 2.2 and the ET range > 8 GeV using the inclusive KT jet finding algorithm.

The dependence of the jet shapes on the transverse jet energy ET in the pseudorapidity range > 2.2 and the ET range > 8 GeV using the inclusive KT jet finding algorithm.

The dependence of the jet shapes on the transverse jet energy ET in the pseudorapidity range < 1.5 and the ET range 5 TO 8 GeV using the cone jet finding algorthm with cone radius = 1.0.

The dependence of the jet shapes on the transverse jet energy ET in the pseudorapidity range 1.5 TO 2.2 and the ET range 5 TO 8 GeV using the cone jet finding algorthm with cone radius = 1.0.

The dependence of the jet shapes on the transverse jet energy ET in the pseudorapidity range > 2.2 and the ET range 5 TO 8 GeV using the cone jet finding algorthm with cone radius = 1.0.

The dependence of the jet shapes on the transverse jet energy ET in the pseudorapidity range < 1.5 and the ET range > 8 GeV using the cone jet finding algorthm with cone radius = 1.0.

The dependence of the jet shapes on the transverse jet energy ET in the pseudorapidity range 1.5 TO 2.2 and the ET range > 8 GeV using the cone jet finding algorthm with cone radius = 1.0.

The dependence of the jet shapes on the transverse jet energy ET in the pseudorapidity range > 2.2 and the ET range > 8 GeV using the cone jet finding algorthm with cone radius = 1.0.

The dependence of the jet shapes on the transverse jet energy ET in the pseudorapidity range < 1.5 and the ET range 5 TO 8 GeV using the cone jet finding algorthm with cone radius = 0.7.

The dependence of the jet shapes on the transverse jet energy ET in the pseudorapidity range 1.5 TO 2.2 and the ET range 5 TO 8 GeV using the cone jet finding algorthm with cone radius = 0.7.

The dependence of the jet shapes on the transverse jet energy ET in the pseudorapidity range > 2.2 and the ET range 5 TO 8 GeV using the cone jet finding algorthm with cone radius = 0.7.

The dependence of the jet shapes on the transverse jet energy ET in the pseudorapidity range < 1.5 and the ET range > 8 GeV using the cone jet finding algorthm with cone radius = 0.7.

The dependence of the jet shapes on the transverse jet energy ET in the pseudorapidity range 1.5 TO 2.2 and the ET range > 8 GeV using the cone jet finding algorthm with cone radius = 0.7.

The dependence of the jet shapes on the transverse jet energy ET in the pseudorapidity range > 2.2 and the ET range > 8 GeV using the cone jet finding algorthm with cone radius = 0.7.

The average number of subjets as a function of the resolution parameter YCUT using the inclusive KT jet finding algorithm in the pseudorapidity range < 1.5 and the ET range 5 TO 8 GeV YCUT using the inclusive KT jet finding algorithm.

The average number of subjets as a function of the resolution parameter YCUT using the inclusive KT jet finding algorithm in the pseudorapidity range 1.5 TO 2.2 and the ET range 5 TO 8 GeV YCUT using the inclusive KT jet finding algorithm.

The average number of subjets as a function of the resolution parameter YCUT using the inclusive KT jet finding algorithm in the pseudorapidity range > 2.2 and the ET range 5 TO 8 GeV YCUT using the inclusive KT jet finding algorithm.

The average number of subjets as a function of the resolution parameter YCUT using the inclusive KT jet finding algorithm in the pseudorapidity range < 1.5 and the ET range > 8 GeV YCUT using the inclusive KT jet finding algorithm.

The average number of subjets as a function of the resolution parameter YCUT using the inclusive KT jet finding algorithm in the pseudorapidity range 1.5 TO 2.2 and the ET range > 8 GeV YCUT using the inclusive KT jet finding algorithm.

The average number of subjets as a function of the resolution parameter YCUT using the inclusive KT jet finding algorithm in the pseudorapidity range > 2.2 and the ET range > 8 GeV YCUT using the inclusive KT jet finding algorithm.