Example of $\Lambda$ signal for 0-40% most central events, over mixed-event background for the bin $-0.05 < y_{cm} < 0.05$ and reduced transverse masses between $100-150 MeV/c^{2}$.

Reduced transverse mass ($m_{t}-m_{0}$) spectra of $K^{0}_{S}$ for the 0-40% most central events.

Reduced transverse mass ($m_{t}-m_{0}$) spectra of $K^{0}_{S}$ for the 0-40% most central events. NOTE: The spectra are not scaled by $1/N_{Events}$! To compare the data, divide by $N_{Events} = 2.1997626 x 10^{9}$

Reduced transverse mass ($m_{t}-m_{0}$) spectra of $\Lambda$ for the 0-40% most central events.

Reduced transverse mass ($m_{t}-m_{0}$) spectra of $\Lambda$ for the 0-40% most central events. NOTE: The spectra are not scaled by $1/N_{Events}$! To compare the data, divide by $N_{Events} = 2.1997626 x 10^{9}$

Rapidity distribution of $K^{0}_{S}$

Rapidity distribution of $K^{0}_{S}$

Rapidity distribution of $\Lambda$

Rapidity distribution of $\Lambda$

Compilation of mid-rapidity yields for central Au+Au collisions as a function of $\sqrt{s_{NN}}$ of $K^{0}_{S}$ and $\Lambda$.

Compilation of mid-rapidity yields for central Au+Au collisions as a function of $\sqrt{s_{NN}}$ of $K^{0}_{S}$ and $\Lambda$.

Multiplicities per mean number of participants $Mult/\langle A_{Part}\rangle$ as a function of $\langle A_{Part}\rangle$

Multiplicities per mean number of participants $Mult/\langle A_{Part}\rangle$ as a function of $\langle A_{Part}\rangle$

Multiplicities per mean number of participants $Mult/\langle A_{Part}\rangle$ as a function of $\langle A_{Part}\rangle$ for $K^{0}_{S}$

Multiplicities per mean number of participants $Mult/\langle A_{Part}\rangle$ as a function of $\langle A_{Part}\rangle$ for $K^{0}_{S}$

Multiplicities per mean number of participants $Mult/\langle A_{Part}\rangle$ as a function of $\langle A_{Part}\rangle$ for $\Lambda$

Multiplicities per mean number of participants $Mult/\langle A_{Part}\rangle$ as a function of $\langle A_{Part}\rangle$ for $\Lambda$

Comparison of the shape of the rapidity distribution of $K^{0}_{S}$ to various transport model versions.

Comparison of the shape of the rapidity distribution of $K^{0}_{S}$ to various transport model versions.

Comparison of the shape of the rapidity distribution of $\Lambda$ to various transport model versions.

Comparison of the shape of the rapidity distribution of $\Lambda$ to various transport model versions.

Comparison of the shape of the $p_{t}$-spectra for $\pm0.15$ rapidity units around mid-rapidity of $K^{0}_{S}$ to various transport model versions.

Comparison of the shape of the $p_{t}$-spectra for $\pm0.15$ rapidity units around mid-rapidity of $K^{0}_{S}$ to various transport model versions.

Comparison of the shape of the $p_{t}$-spectra for $\pm0.15$ rapidity units around mid-rapidity of $\Lambda$ to various transport model versions.

Comparison of the shape of the $p_{t}$-spectra for $\pm0.15$ rapidity units around mid-rapidity of $\Lambda$ to various transport model versions.

Differential yield of $K^{0}_{S}$ as function of rapdidity and reduced transverse mass for the four centrality classes.

Differential yield of $K^{0}_{S}$ as function of rapdidity and reduced transverse mass for the four centrality classes. NOTE: The spectra are not scaled by $1/N_{Events}$! To compare the data, divide by $N_{Events} = 5.64247975 x 10^{8} (0 - 10\%)$, $5.85743394 x 10^{8} (10 - 20\%)$, $5.76369451 x 10^{8} (20 - 30\%)$ or $4.73401752 x 10^{8} (30 - 40\%)$

Differential yield of $\Lambda$ as function of rapdidity and reduced transverse mass for the four centrality classes.

Differential yield of $\Lambda$ as function of rapdidity and reduced transverse mass for the four centrality classes. NOTE: The spectra are not scaled by $1/N_{Events}$! To compare the data, divide by $N_{Events} = 5.64247975 x 10^{8} (0 - 10\%)$, $5.85743394 x 10^{8} (10 - 20\%)$, $5.76369451 x 10^{8} (20 - 30\%)$ or $4.73401752 x 10^{8} (30 - 40\%)$

Normalised differential cross-section as a function of $\sum_{n_{\text{ch}}} p_{\text{T}}$.

Normalised double-differential cross-section as a function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} < 20$.

Normalised double-differential cross-section as a function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$.

Normalised double-differential cross-section as a function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 40 \leq n_\text{ch} < 60$.

Normalised double-differential cross-section as a function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 60 \leq n_\text{ch} < 80$.

Normalised double-differential cross-section as a function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n\text{ch}$ in $ n_\text{ch} \geq 80$.

The $\chi^2$ and NDF for measured absolute differential cross-sections obtained by comparing the different predictions with the unfolded data. Global($n_\text{ch},\Sigma_{n_{\text{ch}}} p_{\text{T}}$) denotes the scenario in which the covariance matrix is built including the correlations of systematic uncertainties between the two observables $n_{\text{ch}}$ and $\Sigma_{n_{\text{ch}}} p_{\text{T}}$

Absolute differential cross-section as a function of $n_\text{ch}$.

Absolute differential cross-section as a function of $\sum_{n_{\text{ch}}} p_{\text{T}}$.

Absolute double-differential cross-section as a function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $n_\text{ch} < 20$.

Absolute double-differential cross-section as a function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 20 \leq n_\text{ch} < 40$.

Absolute double-differential cross-section as a function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 40 \leq n_\text{ch} < 60$.

Absolute double-differential cross-section as a function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n_\text{ch}$ in $ 60 \leq n_\text{ch} < 80$.

Absolute double-differential cross-section as a function of $\sum_{n_{\text{ch}}} p_{\text{T}}$ vs. $n\text{ch}$ in $ n_\text{ch} \geq 80$.

Measured beam asymmetry I_S as a function of the angle between the reaction plane and the plane of the two final state particles with the the pi0 as the recoiling particle for the cm energy range 1642 to 1770 MeV.

Measured beam asymmetry I_S as a function of the angle between the reaction plane and the plane of the two final state particles with the the pi0 as the recoiling particle for the cm energy range 1770 to 1898 MeV.

Measured beam asymmetry I_S as a function of the angle between the reaction plane and the plane of the two final state particles with the the pi0 as the recoiling particle for the cm energy range 1898 to 1994 MeV.

Measured beam asymmetry I_S as a function of the angle between the reaction plane and the plane of the two final state particles with the the eta as the recoiling particle for the cm energy range 1642 to 1770 MeV.

Measured beam asymmetry I_S as a function of the angle between the reaction plane and the plane of the two final state particles with the the eta as the recoiling particle for the cm energy range 1770 to 1898 MeV.

Measured beam asymmetry I_S as a function of the angle between the reaction plane and the plane of the two final state particles with the the eta as the recoiling particle for the cm energy range 1898 to 1994 MeV.

Measured beam asymmetry I_C as a function of the angle between the reaction plane and the plane of the two final state particles with the the proton as the recoiling particle for the cm energy range 1642 to 1770 MeV.

Measured beam asymmetry I_C as a function of the angle between the reaction plane and the plane of the two final state particles with the the proton as the recoiling particle for the cm energy range 1770 to 1898 MeV.

Measured beam asymmetry I_C as a function of the angle between the reaction plane and the plane of the two final state particles with the the proton as the recoiling particle for the cm energy range 1898 to 1994 MeV.

Measured beam asymmetry I_C as a function of the angle between the reaction plane and the plane of the two final state particles with the the pi0 as the recoiling particle for the cm energy range 1642 to 1770 MeV.

Measured beam asymmetry I_C as a function of the angle between the reaction plane and the plane of the two final state particles with the the pi0 as the recoiling particle for the cm energy range 1770 to 1898 MeV.

Measured beam asymmetry I_C as a function of the angle between the reaction plane and the plane of the two final state particles with the the pi0 as the recoiling particle for the cm energy range 1898 to 1994 MeV.

Measured beam asymmetry I_C as a function of the angle between the reaction plane and the plane of the two final state particles with the the eta as the recoiling particle for the cm energy range 1642 to 1770 MeV.

Measured beam asymmetry I_C as a function of the angle between the reaction plane and the plane of the two final state particles with the the eta as the recoiling particle for the cm energy range 1770 to 1898 MeV.

Measured beam asymmetry I_C as a function of the angle between the reaction plane and the plane of the two final state particles with the the eta as the recoiling particle for the cm energy range 1898 to 1994 MeV.

Measured beam asymmetry as a function of the invariant mass of the PI0-ETA system for beam energies 0.970 to 1.200 GeV.

Measured beam asymmetry as a function of the invariant mass of the PI0-ETA system for beam energies 1.200 to 1.450 GeV.

Measured beam asymmetry as a function of the invariant mass of the PI0-ETA system for beam energies 1.450 to 1.650 GeV.

Measured beam asymmetry as a function of the invariant mass of the P-PI0 system for beam energies 0.970 to 1.200 GeV.

Measured beam asymmetry as a function of the invariant mass of the P-PI0 system for beam energies 1.200 to 1.450 GeV.

Measured beam asymmetry as a function of the invariant mass of the P-PI0 system for beam energies 1.450 to 1.650 GeV.

Measured beam asymmetry as a function of the invariant mass of the P-ETA system for beam energies 0.970 to 1.200 GeV.

Measured beam asymmetry as a function of the invariant mass of the P-ETA system for beam energies 1.200 to 1.450 GeV.

Measured beam asymmetry as a function of the invariant mass of the P-ETA system for beam energies 1.450 to 1.650 GeV.

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$\sigma$).

Jet fractions using the JADE algorithm as a function of the jet resolution parameter YCUT at c.m. energy 172.3 GeV.

Jet fractions using the JADE algorithm as a function of the jet resolution parameter YCUT at c.m. energy 182.8 GeV.

Jet fractions using the JADE algorithm as a function of the jet resolution parameter YCUT at c.m. energy 188.6 GeV.

Jet fractions using the JADE algorithm as a function of the jet resolution parameter YCUT at c.m. energy 194.4 GeV.

Jet fractions using the JADE algorithm as a function of the jet resolution parameter YCUT at c.m. energy 200.2 GeV.

Jet fractions using the JADE algorithm as a function of the jet resolution parameter YCUT at c.m. energy 206.2 GeV.

Jet fractions using the KT(Durham) algorithm as a function of the jet resolution parameter YCUT at c.m. energy 130.1 GeV.

Jet fractions using the KT(Durham) algorithm as a function of the jet resolution parameter YCUT at c.m. energy 136.1 GeV.

Jet fractions using the KT(Durham) algorithm as a function of the jet resolution parameter YCUT at c.m. energy 161.3 GeV.

Jet fractions using the KT(Durham) algorithm as a function of the jet resolution parameter YCUT at c.m. energy 172.3 GeV.

Jet fractions using the KT(Durham) algorithm as a function of the jet resolution parameter YCUT at c.m. energy 182.8 GeV.

Jet fractions using the KT(Durham) algorithm as a function of the jet resolution parameter YCUT at c.m. energy 188.6 GeV.

Jet fractions using the KT(Durham) algorithm as a function of the jet resolution parameter YCUT at c.m. energy 194.4 GeV.

Jet fractions using the KT(Durham) algorithm as a function of the jet resolution parameter YCUT at c.m. energy 200.2 GeV.

Jet fractions using the KT(Durham) algorithm as a function of the jet resolution parameter YCUT at c.m. energy 206.2 GeV.

Jet fractions using the Cambridge algorithm as a function of the jet resolution parameter YCUT at c.m. energy 202.2 GeV.

Jet fractions using the Cambridge algorithm as a function of the jet resolution parameter YCUT at c.m. energy 206.2 GeV.

Differential distributions for event thrust.

Differential distributions for event thrust.

Differential distributions for event thrust.

Differential distributions for event thrust.

Differential distributions for event thrust.

Differential distributions for the scaled heavy jet mass (RHO(C=HEAVY)).

Differential distributions for the scaled heavy jet mass (RHO(C=HEAVY)).

Differential distributions for the scaled heavy jet mass (RHO(C=HEAVY)).

Differential distributions for the scaled heavy jet mass (RHO(C=HEAVY)).

Differential distributions for the scaled heavy jet mass (RHO(C=HEAVY)).

Differential distributions for total jet broadening (BT).

Differential distributions for total jet broadening (BT).

Differential distributions for total jet broadening (BT).

Differential distributions for total jet broadening (BT).

Differential distributions for total jet broadening (BT).

Differential distributions for wide jet broadening (BW).

Differential distributions for wide jet broadening (BW).

Differential distributions for wide jet broadening (BW).

Differential distributions for wide jet broadening (BW).

Differential distributions for wide jet broadening (BW).

Differential distributions for the C-Parameter.

Differential distributions for the C-Parameter.

Differential distributions for the C-Parameter.

Differential distributions for the D-Parameter.

Differential distributions for the D-Parameter.

Differential distributions for the D-Parameter.

Differential distributions for the THRUST at c.m. energy 91.2 GeV for light quark (udsc) and b quark events.

Differential distributions for the RHO(C=HEAVY) at c.m. energy 91.2 GeV forlight quark (udsc) and b quark events.

Differential distributions for the BT at c.m. energy 91.2 GeV for light quark (udsc) and b quark events.

Differential distributions for the BW at c.m. energy 91.2 GeV for light quark (udsc) and b quark events.

Differential distributions for the C-PARAM at c.m. energy 91.2 GeV for light quark (udsc) and b quark events.

Differential distributions for the D-PARAM at c.m. energy 91.2 GeV for light quark (udsc) and b quark events.

Mean values (first moment) and dispersion (second moment) of the THRUST distribution as a function of c.m. energy.

Mean values (first moment) and dispersion (second moment) of the scaled heavy jet mass (RHO(C=HEAVY)) as a function of c.m. energy.

Mean values (first moment) and dispersion (second moment) of the total jet broadening (BT) as a function of c.m. energy.

Mean values (first moment) and dispersion (second moment) of the wide jet broadening (BW) as a function of c.m. energy.

Mean values (first moment) and dispersion (second moment) of the C-PARAM as a function of c.m. energy.

Mean values (first moment) and dispersion (second moment) of the D-PARAM as a function of c.m. energy.

Charged particle multiplicities at c.m. energy 91.2 GeV for all flavour, light quark (udsc) and bottom (b) flavour events.

Charged particle multiplicity.

Charged particle multiplicity.

Charged particle multiplicity.

First and second moment of the charged particle multiplicity distribution at c.m. energy 91.2 GeV for all flavours and for udsc an b flavours.

First and second moment of the charged particle multiplicity distribution at c.m. energy.

Distribution of LN(1/X) at c.m. energy 91.2 GeV.

Distribution of LN(1/X) at higher c.m. energies.

Distribution of LN(1/X) at higher c.m. energies.

Distribution of LN(1/X) at higher c.m. energies.

Spherical tensor analysing powers t20 and t22 for EPP 0.1 to 1.0 MeV and cos(theta) < 0.5.

Spherical tensor analysing powers t20 and t22 for EPP 1 to 3 MeV and cos(theta) > 0.5.

Spherical tensor analysing powers t20 and t22 for EPP 1 to 3 MeV and cos(theta) < 0.5.

Differential ep cross section for dijet production as a function of the average pseudorapidity the two jets in two transverse energy regions and in the Y region 0.1 to 0.5.

Differential ep cross section for dijet production as a function of the average pseudorapidity the two jets in two transverse energy regions and in the Y region 0.5 to 0.9.

Differential ep cross section for dijet production as a function of the photon momentum fraction X(C=GAMMA) in two regions of proton fractional momentum XP.

Differential ep cross section for dijet production as a function of the proton momentum fraction XP in two regions of photon fractional momentum X(C=GAMMA).

Differential ep cross section for dijet production as a function of the photon momentum fraction X(C=GAMMA) in two regions maximum jet transverseenergy.

Differential ep cross section for dijet production as a function of COS(THETA*) in two regions of fractional photon momentum fraction X(C=GAMMA).

Differential ep cross section for dijet production as a function of COS(THETA*) for dijet masses > 65 GeV in two regions of fractional photon momentum fraction X(C=GAMMA).