Two-dimensional distribution of the invariant mass $m_{DV}$ and the track multiplicity in the High-pT jet SR for observed data events

Two-dimensional distribution of the invariant mass $m_{DV}$ and the track multiplicity in the High-pT jet SR for expected signal events in the strong gluino pair pair production model with m(gluino)=1.8 TeV, m(chi0)=0.2 TeV, tau(chi0)=0.1 ns

Two-dimensional distribution of the invariant mass $m_{DV}$ and the track multiplicity in the Trackless jet SR for observed data events

Two-dimensional distribution of the invariant mass $m_{DV}$ and the track multiplicity in the Trackless jet SR for expected signal events in the electroweak pair production model

Expected exclusion limits at 95% CL on the lifetime and mass of the neutralino in electroweakino pair production models

Expected (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in electroweakino pair production models

Expected (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in electroweakino pair production models

Observed exclusion limits at 95% CL on the lifetime and mass of the neutralino in electroweakino pair production models

Observed (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in electroweakino pair production models

Observed (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in electroweakino pair production models

Expected exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.4 TeV

Expected (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.4 TeV

Expected (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.4 TeV

Observed exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.4 TeV

Observed (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.4 TeV

Observed (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.4 TeV

Exclusion limits at 95% CL on the production cross section in the electroweak pair production model.

Exclusion limits at 95% CL on the production cross section in the strong gluino pair production models and m(gluino)=2.4 TeV

Expected exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.0 TeV

Expected (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.0 TeV

Expected (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.0 TeV

Observed exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.0 TeV

Observed (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.0 TeV

Observed (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.0 TeV

Expected exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.2 TeV

Expected (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.2 TeV

Expected (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.2 TeV

Observed exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.2 TeV

Observed (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.2 TeV

Observed (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.2 TeV

Expected exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=50 GeV

Expected (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=50 GeV

Expected (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=50 GeV

Observed exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=50 GeV

Observed (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=50 GeV

Observed (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=50 GeV

Expected exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=450 GeV

Expected (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=450 GeV

Expected (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=450 GeV

Observed exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=450 GeV

Observed (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=450 GeV

Observed (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=450 GeV

Expected exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.01 ns

Expected (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.01 ns

Expected (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.01 ns

Observed exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.01 ns

Observed (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.01 ns

Observed (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.01 ns

Expected exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.1 ns

Expected (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.1 ns

Expected (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.1 ns

Observed exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.1 ns

Observed (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.1 ns

Observed (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.1 ns

Expected exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=1 ns

Expected (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=1 ns

Expected (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=1 ns

Observed exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=1 ns

Observed (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=1 ns

Observed (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=1 ns

Expected exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=10 ns

Expected (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=10 ns

Expected (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=10 ns

Observed exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=10 ns

Observed (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=10 ns

Observed (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=10 ns

Exclusion limits at 95% CL on the production cross section in the strong gluino pair production models and m($ ilde{\chi}^0_1$)=1.25 TeV

Acceptance cutflow for the High-pT SR for representative points in the strong gluino pair production model. See additional resources for more information.

Acceptance cutflow for the Trackless SR for representative points in the electroweak pair production model. See additional resources for more information.

Acceptance cutflow for the Trackless SR for representative points in the electroweak pair production model with heavy-flavor quarks final state. See additional resources for more information.

Acceptance cutflow for the High-pT SR for representative points in the electroweak pair production model with heavy-flavor quarks final state. See additional resources for more information.

Reinterpretation Material: Event-level Efficiency for HighPt SR selections, R < 1150 mm

Reinterpretation Material: Event-level Efficiency for HighPt SR selections, R [1150, 3870] mm

Reinterpretation Material: Event-level Efficiency for HighPt SR selections, R > 3870 mm

Reinterpretation Material: Event-level Efficiency for Trackless SR selections, R < 1150 mm

Reinterpretation Material: Event-level Efficiency for Trackless SR selections, R [1150, 3870] mm

Reinterpretation Material: Event-level Efficiency for Trackless SR selections, R > 3870 mm

Reinterpretation Material: Vertex-level Efficiency for R < 22 mm

Reinterpretation Material: Vertex-level Efficiency for R [22, 25] mm

Reinterpretation Material: Vertex-level Efficiency for R [25, 29] mm

Reinterpretation Material: Vertex-level Efficiency for R [29, 38] mm

Reinterpretation Material: Vertex-level Efficiency for R [38, 46] mm

Reinterpretation Material: Vertex-level Efficiency for R [46, 73] mm

Reinterpretation Material: Vertex-level Efficiency for R [73, 84] mm

Reinterpretation Material: Vertex-level Efficiency for R [84, 111] mm

Reinterpretation Material: Vertex-level Efficiency for R [111, 120] mm

Reinterpretation Material: Vertex-level Efficiency for R [120, 145] mm

Reinterpretation Material: Vertex-level Efficiency for R [145, 180] mm

Reinterpretation Material: Vertex-level Efficiency for R [180, 300] mm

Cutflow (acceptance x efficiency) for the High-pT SR for representative points in the strong gluino pair production model. See additional resources for more information.

Cutflow (acceptance x efficiency) for the Trackless SR for representative points in the electroweak pair production model. See additional resources for more information.

Cutflow (acceptance x efficiency) for the Trackless SR for representative points in the electroweak pair production model with heavy-flavor quarks. See additional resources for more information.

Cutflow (acceptance x efficiency) for the High-pT SR for representative points in the electroweak pair production model with heavy-flavor quarks. See additional resources for more information.

Bayesian upper exclusion limits on the ratio $g_{W'}/g_{W}$ for an SSM-like W$\prime$ boson are shown. The unity coupling ratio (blue dotted curve) corresponds to the SSM common benchmark. The 68 and 95% quantiles of the limits are represented by the green and yellow bands, respectively.

Bayesian lower exclusion limits on the NUGIM G(221) mixing angle $\cot(\theta_{E})$ are shown as a function of the W$\prime$ boson mass. The theoretically excluded region is shaded in grey. The 68 and 95% quantiles of the limits are represented by the green and yellow bands, respectively.

Bayesian upper exclusion limits at 95% CL on the product of the production cross section and branching fraction of a QBH in an associated $ au$ lepton and neutrino final state. Minimum threshold masses $m_{th}$ of up to 6.6 TeV are excluded at 95% CL. The observed limit (solid line) is obtained from the intersection with the LO QBH cross section (blue dotted curve). The 68 and 95% quantiles of the limits are represented by the green and yellow bands, respectively.

Bayesian upper limits at 95% CL on the cross section of the process $pp\rightarrow\tau\nu$ mediated via LQ exchange in the t-channel. The inner (green) band and the outer (yellow) band indicate the regions containing 68 and 95%, respectively, of the distribution of limits expected under the background-only hypothesis. The predicted LQ cross section at LO in the three coupling benchmark scenarios is depicted in different colors for $g_{U}=1$. The uncertainty bandy correspond to the sum in quadrature of PDF and scale variations. The first benchmark scenario considers only couplings to left-handed SM fermions (i.e. $\beta_{\text{R}}^{ij}=0$) and is referred to as "best fit LH". The second benchmark, referred to as "best fit LH+RH", considers $|\beta_{\text{R}}^{\text{b}\tau}|=1$ and all other $\beta_{\text{R}}^{ij}=0$. In the third "democratic" benchmark, equal couplings only to LH fermions are assumed, i.e. $\beta_{\text{L}}^{ij}=1$ and $\beta_{\text{R}}^{ij}=0$ for all $i$ and $j$.

Expected and observed lower limits of the LQ mass as a function of the coupling $g_{U}$ in the LH scenario. The blue band shows the 68% and 95% regions of $g_{U}$ preferred by the fit to the b anomalies data.

Expected and observed lower limits of the LQ mass as a function of the coupling $g_{U}$ in the LH+RH scenario. The blue band shows the 68% and 95% regions of $g_{U}$ preferred by the fit to the b anomalies data.

Expected and observed lower limits of the LQ mass as a function of the coupling $g_{U}$ in the democratic scenario. The blue band shows the 68% and 95% regions of $g_{U}$ preferred by the fit to the b anomalies data.

Bayesian upper exclusion limits at 95% CL on each of the Wilson coefficients described by the EFT model based on 2016-2018 data. The three different coupling types represent a left-handed vector coupling ($\epsilon^{cb}_{L}$), tensor-like coupling ($\epsilon^{cb}_{T}$), and scalar-tensor-like coupling ($\epsilon^{cb}_{S_{L}}$). The 68 and 95% quantiles of the limits are represented by the green and yellow bands, respectively.

Summary of exclusion limits (expected and observed) calculated at 95% CL for full Run-2 CMS data.

Background prediction and observed data yields in the signal region bins. The background yields are obtained from the background-only fit and serve as input to the simplified likelihood reinterpretation scheme. The naming of the bins is "year_binnumber", following the binning from Figure 4.

Matrix of covariance coefficients between signal region bins. The coefficients are obtained from the background-only fit and serve as input to the simplified likelihood reinterpretation scheme. The naming of the bins is "year_binnumber", following the binning used in Figure 4.

Predicted signal yields for the 2017 data-taking period, corresponding to 41.3 fb$^{-1}$, after the application of each search requirement (cumulative) for various signal hypothesis. The requirements listed are presented as total efficiencies w.r.t. the previous selection step.

Covariance matrix for the extrapolation uncertainty for the measurement of the absolute differential cross section as a function of the rho observable at parton level.

Normalized differential cross section as a function of the rho observable at parton level.

Covariance matrix for the total uncertainty (i.e. fit including stat., not extrapolation) for the measurement of the normalized differential cross section as a function of the rho observable at parton level.

Covariance matrix for the statistical uncertainty for the measurement of the normalized differential cross section as a function of the rho observable at parton level.

Covariance matrix for the extrapolation uncertainty for the measurement of the normalized differential cross section as a function of the rho observable at parton level.

Correlation matrix for all nuisance parameters and parameters of interest of the Likelihood fit.

This table is a numerical representation of Fig. 8 for all nuisance parameters.

Centrality dependence of (a) $v_2${2} and (b) $v_2${4}. (a) The red points indicate no pseudorapidity gap whereas the magenta points indicate a pseudorapidity gap of |$\Delta\eta$| > 2.0. (b) The black points indicate $v_2${4} with no pseudorapidity gap, the blue points indicate a two-subevent method with |$\Delta\eta$| > 2.0 but where some short-range pairs are allowed, and the red points indicate a two-subevent method with |$\Delta\eta$| > 2.0 where no short-range pairs are allowed.

Centrality dependence of (a) $v_2${2} and (b) $v_2${4}. (a) The red points indicate no pseudorapidity gap whereas the magenta points indicate a pseudorapidity gap of |$\Delta\eta$| > 2.0. (b) The black points indicate $v_2${4} with no pseudorapidity gap, the blue points indicate a two-subevent method with |$\Delta\eta$| > 2.0 but where some short-range pairs are allowed, and the red points indicate a two-subevent method with |$\Delta\eta$| > 2.0 where no short-range pairs are allowed.

Multi-particle $v_2$ as a function of centrality in Au+Au collisions at $\sqrt{s_{NN}}$ = 200 GeV. The magenta open diamonds indicate the $v_2${SP }, the blue open squares indicate $v_2${4}, the black open circles indicate $v_2${6}, and the green filled diamonds indicate $v_2${8}.

Multi-particle $v_2$ as a function of centrality in Au+Au collisions at $\sqrt{s_{NN}}$ = 200 GeV. The magenta open diamonds indicate the $v_2${SP }, the blue open squares indicate $v_2${4}, the black open circles indicate $v_2${6}, and the green filled diamonds indicate $v_2${8}.

Multi-particle $v_2$ as a function of centrality in Au+Au collisions at $\sqrt{s_{NN}}$ = 200 GeV. The magenta open diamonds indicate the $v_2${SP }, the blue open squares indicate $v_2${4}, the black open circles indicate $v_2${6}, and the green filled diamonds indicate $v_2${8}.

Multi-particle $v_2$ as a function of centrality in Au+Au collisions at $\sqrt{s_{NN}}$ = 200 GeV. The magenta open diamonds indicate the $v_2${SP }, the blue open squares indicate $v_2${4}, the black open circles indicate $v_2${6}, and the green filled diamonds indicate $v_2${8}.

Cumulant method estimate of $\sigma_{v_{2}}$ / $\langle v_{2} \rangle$ as a function of centrality in Au+Au collisions at $\sqrt{s_{NN}}$ = 200 GeV. The data are shown as black open squares. The same calculation as done in data is done in ampt, shown as a solid green line. Calculations of $\sigma_{\epsilon_{2}}$ /$ \langle\epsilon_{2}\rangle$ performed in the Monte Carlo Glauber model are shown as blue lines. The solid blue line is the Monte Carlo Glauber calculation done using the same estimate as the data, the dashed blue line is the direct calculation of the moments of the MC Glauber $\epsilon_{2}$ distribution.

Centrality dependence of $v_3${2, |$\Delta\eta$| > 2} in Au+Au collisions at $\sqrt{s_{NN}}$ = 200 GeV, shown as magenta diamonds. The systematic uncertainty is indicated as a shaded magenta band. Also shown as black squares are $\sqrt{\langle v^{2}_{3}\rangle}$ as determined from the folding analysis, which is shown in the next section.

Centrality dependence of $v_3${2, |$\Delta\eta$| > 2} in Au+Au collisions at $\sqrt{s_{NN}}$ = 200 GeV, shown as magenta diamonds. The systematic uncertainty is indicated as a shaded magenta band. Also shown as black squares are $\sqrt{\langle v^{2}_{3}\rangle}$ as determined from the folding analysis, which is shown in the next section.

Centrality dependence of $c_3${4} for Au+Au collisions at $\sqrt{s_{NN}}$ = 200 GeV. (a) Calculations using both arms: $c_3${4} (black circles), $c_3${4}$_{ab|ab}$ (blue diamonds), $c_3${4}$_{aa|bb}$ (red squares), and comparison to STAR [36] (black stars). (b) Comparison of $c_3${4} determined using both arms (open symbols) and a single arm (closed symbols). Note that the open black circles are the same in (a) and (b).

Centrality dependence of $c_3${4} for Au+Au collisions at $\sqrt{s_{NN}}$ = 200 GeV. (a) Calculations using both arms: $c_3${4} (black circles), $c_3${4}$_{ab|ab}$ (blue diamonds), $c_3${4}$_{aa|bb}$ (red squares), and comparison to STAR [36] (black stars). (b) Comparison of $c_3${4} determined using both arms (open symbols) and a single arm (closed symbols). Note that the open black circles are the same in (a) and (b).

Centrality dependence of $c_3${4} for Au+Au collisions at $\sqrt{s_{NN}}$ = 200 GeV. (a) Calculations using both arms: $c_3${4} (black circles), $c_3${4}$_{ab|ab}$ (blue diamonds), $c_3${4}$_{aa|bb}$ (red squares), and comparison to STAR [36] (black stars). (b) Comparison of $c_3${4} determined using both arms (open symbols) and a single arm (closed symbols). Note that the open black circles are the same in (a) and (b).

Folding results for (a) $v_2$, (b) $\sigma_{v_{2}}$ , and (c) $\sigma_{v_{2}}$ / $\langle v_{2}\rangle$. The black lines above and below the points indicate the systematic uncertainties. The red (green) boxes indicate the statistical uncertainties at the 68.27% (95.45%) confidence level. In the case of $\langle v_{2}\rangle$, the statistical uncertainties at the 68.27% confidence level are too small to be seen, and the uncertainties at the 95.45% confidence level are visible but noticeably smaller than the marker size. Shown as blue squares are the same quantities as determined using the cumulant based calculation—these points are slightly offset in the x-coordinate to improve visibility.

Folding results for (a) $v_2$, (b) $\sigma_{v_{2}}$ , and (c) $\sigma_{v_{2}}$ / $\langle v_{2}\rangle$. The black lines above and below the points indicate the systematic uncertainties. The red (green) boxes indicate the statistical uncertainties at the 68.27% (95.45%) confidence level. In the case of $\langle v_{2}\rangle$, the statistical uncertainties at the 68.27% confidence level are too small to be seen, and the uncertainties at the 95.45% confidence level are visible but noticeably smaller than the marker size. Shown as blue squares are the same quantities as determined using the cumulant based calculation—these points are slightly offset in the x-coordinate to improve visibility.

Folding results for (a) $v_2$, (b) $\sigma_{v_{2}}$ , and (c) $\sigma_{v_{2}}$ / $\langle v_{2}\rangle$. The black lines above and below the points indicate the systematic uncertainties. The red (green) boxes indicate the statistical uncertainties at the 68.27% (95.45%) confidence level. In the case of $\langle v_{2}\rangle$, the statistical uncertainties at the 68.27% confidence level are too small to be seen, and the uncertainties at the 95.45% confidence level are visible but noticeably smaller than the marker size. Shown as blue squares are the same quantities as determined using the cumulant based calculation—these points are slightly offset in the x-coordinate to improve visibility.

Folding results for (a) $\langle v_{3}\rangle$, (b) $\sigma_{v_{3}}$ , and (c) $\sigma_{v_{3}}$ /$\langle v_{3}\rangle$. The black lines above and below the points indicate the systematic uncertainties. The red (green) boxes indicate the statistical uncertainties at the 68.27% (95.45%) confidence level. The $\sigma_{v_{3}}$ /$\langle v_{3}\rangle$ values are all ≈ 0.52, the apparent limiting value of this quantity for the Bessel-Gaussian distribution.

Folding results for (a) $\langle v_{3}\rangle$, (b) $\sigma_{v_{3}}$ , and (c) $\sigma_{v_{3}}$ /$\langle v_{3}\rangle$. The black lines above and below the points indicate the systematic uncertainties. The red (green) boxes indicate the statistical uncertainties at the 68.27% (95.45%) confidence level. The $\sigma_{v_{3}}$ /$\langle v_{3}\rangle$ values are all ≈ 0.52, the apparent limiting value of this quantity for the Bessel-Gaussian distribution.

Folding results for (a) $\langle v_{3}\rangle$, (b) $\sigma_{v_{3}}$ , and (c) $\sigma_{v_{3}}$ /$\langle v_{3}\rangle$. The black lines above and below the points indicate the systematic uncertainties. The red (green) boxes indicate the statistical uncertainties at the 68.27% (95.45%) confidence level. The $\sigma_{v_{3}}$ /$\langle v_{3}\rangle$ values are all ≈ 0.52, the apparent limiting value of this quantity for the Bessel-Gaussian distribution.

The minimum $\chi^2$ and the parameters $T_{fo}$ and $\beta^{max}_T$ for each of the five centrality selections. The best fit parameters are determined by averaging all parameter pairs within the 1$\sigma$ contour. The errors correspond to the standard deviation of the parameter pairs within the 1$\sigma$ $\chi^2$ contour.

Fit parameters for each particle species using Equations $\frac{dN}{dy}$ = $C \cdot$ ($N_{part}$)$^{\alpha_{part}}$ and $\frac{dN}{dy}$ = $C^{\prime} \cdot$ ($N_{coll}$)$^{\alpha_{coll}}$.

Values of the parameters $n_{pp}$ and $x$ from fitting Equation $R \equiv \frac{dN/dy}{N_{part}}$ = (1-$x$) $\cdot n_{pp} \frac{1}{2}$ + $x \cdot n_{pp} \frac{N_{coll}}{N_{part}}$ = $n_{pp}$ [$\frac{1}{2}$ + $x$($\frac{N_{coll}}{N_{part}}$ - $\frac{1}{2})$]to the observed $dN$/$dy$ per $N_{part}$.

Invariant yields for $\pi^{\pm}$ measured in minimum-bias events at midrapidity and normalized to one rapidity unit.

Invariant yields for $K^{\pm}$ measured in minimum-bias events at midrapidity and normalized to one rapidity unit.

Invariant yields for (anti)$p$ measured in minimum-bias events at midrapidity and normalized to one rapidity unit.

Pion invariant yields in each event centrality and $p_T$ bin measured at midrapidity, normalized to one rapidity unit.

Pion invariant yields in each event centrality and $p_T$ bin measured at midrapidity, normalized to one rapidity unit.

Kaon invariant yields in each event centrality and $p_T$ bin measured at midrapidity, normalized to one rapidity unit.

Kaon invariant yields in each event centrality and $p_T$ bin measured at midrapidity, normalized to one rapidity unit.

(Anti)proton invariant yields in each event centrality and $p_T$ bin measured at midrapidity, normalized to one rapidity unit.

(Anti)proton invariant yields in each event centrality and $p_T$ bin measured at midrapidity, normalized to one rapidity unit.

(Anti)proton invariant yields in each event centrality and $p_T$ bin measured at midrapidity, normalized to one rapidity unit.

(Anti)proton invariant yields in each event centrality and $p_T$ bin measured at midrapidity, normalized to one rapidity unit.

(Anti)proton invariant yields in each event centrality and $p_T$ bin measured at midrapidity, normalized to one rapidity unit.

(Anti)proton invariant yields in each event centrality and $p_T$ bin measured at midrapidity, normalized to one rapidity unit.

(Anti)proton invariant yields in each event centrality and $p_T$ bin measured at midrapidity, normalized to one rapidity unit.

Minimum-bias invariant yields for $\pi^{\pm}$ in equal $p_T$ bins.

Minimum-bias invariant yields for $K^{\pm}$ in equal $p_T$ bins.

Minimum-bias invariant yields for (anti)$p$ in equal $p_T$ bins.

Pion invariant yields in each event centrality normalized to one rapidity unit at midrapidity.

Pion invariant yields in each event centrality normalized to one rapidity unit at midrapidity.

Kaon invariant yields in each event centrality normalized to one rapidity unit at midrapidity.

(Anti)proton invariant yields in each event centrality normalized to one rapidity unit at midrapidity.

(Anti)proton invariant yields in each event centrality normalized to one rapidity unit at midrapidity.

The integrated mean $p_T$ for pions, kaons, and (anti)protons produced in the five different classes of event centrality.

The expansion parameters $T_{fo}$ and $\beta^{max}_T$ as a function of the number of participants.

The second-order Fourier coefficients $v_2 (p_T)$ for charge-combined identified hadrons $\pi^{\pm}$, $K^{\pm}$, $ p$, and $\bar{p}$ measured at midrapidity in Cu + Au collisions at $\sqrt{S_{NN}}$ = 200 GeV for the centrality classes marked in each panel.

The second-order Fourier coefficients $v_2 (p_T)$ for charge-combined identified hadrons $\pi^{\pm}$, $K^{\pm}$, $ p$, and $\bar{p}$ measured at midrapidity in Cu + Au collisions at $\sqrt{S_{NN}}$ = 200 GeV for the centrality classes marked in each panel.

The second-order Fourier coefficients $v_2 (p_T)$ for charge-combined identified hadrons $\pi^{\pm}$, $K^{\pm}$, $ p$, and $\bar{p}$ measured at midrapidity in Cu + Au collisions at $\sqrt{S_{NN}}$ = 200 GeV for the centrality classes marked in each panel.

The second-order Fourier coefficients $v_2 (p_T)$ for charge-combined identified hadrons $\pi^{\pm}$, $K^{\pm}$, $ p$, and $\bar{p}$ measured at midrapidity in Cu + Au collisions at $\sqrt{S_{NN}}$ = 200 GeV for the centrality classes marked in each panel.

The second-order Fourier coefficients $v_2 (p_T)$ for charge-combined identified hadrons $\pi^{\pm}$, $K^{\pm}$, $ p$, and $\bar{p}$ measured at midrapidity in Cu + Au collisions at $\sqrt{S_{NN}}$ = 200 GeV for the centrality classes marked in each panel.

The third-order Fourier coefficients $v_3(p_T)$ for charge-combined identified hadrons $\pi^{\pm}$, $K^{\pm}$, $p$, and $\bar{p}$ measured at midrapidity in Cu + Au collisions at $\sqrt{S_{NN}}$ = 200 GeV for 0%-30% centrality.

The third-order Fourier coefficients $v_3(p_T)$ for charge-combined identified hadrons $\pi^{\pm}$, $K^{\pm}$, $p$, and $\bar{p}$ measured at midrapidity in Cu + Au collisions at $\sqrt{S_{NN}}$ = 200 GeV for 0%-30% centrality.

The third-order Fourier coefficients $v_3(p_T)$ for charge-combined identified hadrons $\pi^{\pm}$, $K^{\pm}$, $p$, and $\bar{p}$ measured at midrapidity in Cu + Au collisions at $\sqrt{S_{NN}}$ = 200 GeV for 0%-30% centrality.

The first-order Fourier coefficients $v_1(p_T)$ for charge-combined $\pi^{\pm}$, $K^{\pm}$, $ p$, and $\bar{p}$ identified hadrons measured at midrapidity in Cu + Au collisions at $\sqrt{S_{NN}}$ = 200 GeV for 10%-50% centrality.

The first-order Fourier coefficients $v_1(p_T)$ for charge-combined $\pi^{\pm}$, $K^{\pm}$, $ p$, and $\bar{p}$ identified hadrons measured at midrapidity in Cu + Au collisions at $\sqrt{S_{NN}}$ = 200 GeV for 10%-50% centrality.

Scaled second-order Fourier coefficients $v_2(p_T)/\epsilon_2$ for charged hadrons measured at midrapidity in Cu + Cu collisions at $\sqrt{S_{NN}}$ = 200 GeV.

Scaled second-order Fourier coefficients $v_2(p_T)/\epsilon_2$ for charged hadrons measured at midrapidity in Au + Au collisions at $\sqrt{S_{NN}}$ = 200 GeV.

Scaled second-order Fourier coefficients $v_2(p_T)/\epsilon_2$ for charged hadrons measured at midrapidity in Au + Au collisions at $\sqrt{S_{NN}}$ = 200 GeV.

Scaled second-order Fourier coefficients $v_2(p_T)/\epsilon_2$ for charged hadrons measured at midrapidity in Au + Au collisions at $\sqrt{S_{NN}}$ = 200 GeV.

Scaled second-order Fourier coefficients $v_2(p_T)/\epsilon_2$ for charged hadrons measured at midrapidity in Au + Au collisions at $\sqrt{S_{NN}}$ = 200 GeV.

Scaled second-order Fourier coefficients $v_2(p_T)/\epsilon_2$ for charged hadrons measured at midrapidity in Au + Au collisions at $\sqrt{S_{NN}}$ = 200 GeV.

Scaled second-order Fourier coefficients $v_2(p_T)/\epsilon_2$ for charged hadrons measured at midrapidity in Au + Au collisions at $\sqrt{S_{NN}}$ = 200 GeV.

Scaled second-order Fourier coefficients $v_2(p_T)/\epsilon_2$ for charged hadrons measured at midrapidity in Cu + Au collisions at $\sqrt{S_{NN}}$ = 200 GeV.

Scaled second-order Fourier coefficients $v_2(p_T)/(\epsilon_2 N^{1/3}_{part})$ for charged hadrons measured at midrapidity in Cu + Cu collisions at $\sqrt{S_{NN}}$ = 200 GeV.

Scaled second-order Fourier coefficients $v_2(p_T)/(\epsilon_2 N^{1/3}_{part})$ for charged hadrons measured at midrapidity in Au + Au collisions at $\sqrt{S_{NN}}$ = 200 GeV.

Scaled second-order Fourier coefficients $v_2(p_T)/(\epsilon_2 N^{1/3}_{part})$ for charged hadrons measured at midrapidity in Au + Au collisions at $\sqrt{S_{NN}}$ = 200 GeV.

Scaled second-order Fourier coefficients $v_2(p_T)/(\epsilon_2 N^{1/3}_{part})$ for charged hadrons measured at midrapidity in Au + Au collisions at $\sqrt{S_{NN}}$ = 200 GeV.

Scaled second-order Fourier coefficients $v_2(p_T)/(\epsilon_2 N^{1/3}_{part})$ for charged hadrons measured at midrapidity in Au + Au collisions at $\sqrt{S_{NN}}$ = 200 GeV.

Scaled second-order Fourier coefficients $v_2(p_T)/(\epsilon_2 N^{1/3}_{part})$ for charged hadrons measured at midrapidity in Au + Au collisions at $\sqrt{S_{NN}}$ = 200 GeV.

Scaled second-order Fourier coefficients $v_2(p_T)/(\epsilon_2 N^{1/3}_{part})$ for charged hadrons measured at midrapidity in Au + Au collisions at $\sqrt{S_{NN}}$ = 200 GeV.

Scaled second-order Fourier coefficients $v_2(p_T)/(\epsilon_2 N^{1/3}_{part})$ for charged hadrons measured at midrapidity in Cu + Au collisions at $\sqrt{S_{NN}}$ = 200 GeV.

Scaled third-order Fourier coefficients $v_3(p_T)/\epsilon_3$ for charged hadrons measured at midrapidity in Au + Au collisions at $\sqrt{S_{NN}}$ = 200 GeV.

Scaled third-order Fourier coefficients $v_3(p_T)/\epsilon_3$ for charged hadrons measured at midrapidity in Au + Au collisions at $\sqrt{S_{NN}}$ = 200 GeV.

Scaled third-order Fourier coefficients $v_3(p_T)/\epsilon_3$ for charged hadrons measured at midrapidity in Cu + Au collisions at $\sqrt{S_{NN}}$ = 200 GeV.

Scaled third-order Fourier coefficients $\frac{v_3}{($_3 N_{part}^{1/3})}$ for charged hadrons measured at midrapidity in Au + Au collisions at $\sqrt{S_{NN}}$ = 200 GeV.

Scaled third-order Fourier coefficients $\frac{v_3}{(e_3 N_{part}^{1/3})}$ for charged hadrons measured at midrapidity in Au + Au collisions at $\sqrt{S_{NN}}$ = 200 GeV.

Scaled third-order Fourier coefficients $\frac{v_3}{(e_3 N_{part}^{1/3})}$ for charged hadrons measured at midrapidity in Cu + Au collisions at $\sqrt{S_{NN}}$ = 200 GeV.

The second-order Fourier coefficients $v_2$($p_T$ ) for charged hadrons measured at midrapidity in Cu + Au collisions at $\sqrt{S_{NN}}$ = 200 GeV in comparison with hydrodynamics calculations for the centrality classes marked in each panel.

The third-order Fourier coefficients $v_3(p_T)$ for charged hadrons measured at midrapidity in Cu + Au collisions at $\sqrt{S_{NN}}$ = 200 GeV in comparison with hydrodynamics calculations for the centrality classes marked in each panel.

The ratio of $\psi(2S)$ to $J/\psi(1S)$ cross sections, as measured in the dimuon decay channel in pp collisions at 200 GeV over the rapidity interval $1.2<|y|<2.2$, as a function of transverse momentum $p_{T}$.

The double ratios $[\sigma_{\psi(2S)}/\sigma_{\psi(1S)}]_{pA}/[\sigma_{\psi(2S)}/\sigma_{\psi(1S)}]_{pp}$. The global systematic uncertainty is $\pm 14\%$.

The charged-particle multiplicity $dN_{ch}/d\eta$ determined from AMPT simulations and the nuclear overlap $S_T$ from Glauber simulations for the data shown in Fig. 5. Here we assume $dN/d\eta$ = $\frac{3}{2}dN_{ch}/d\eta$.

The charged-particle multiplicity $dN_{ch}/d\eta$ determined from AMPT simulations and the nuclear overlap $S_T$ from Glauber simulations for the data shown in Fig. 5. Here we assume $dN/d\eta$ = $\frac{3}{2}dN_{ch}/d\eta$.

The charged-particle multiplicity $dN_{ch}/d\eta$ determined from AMPT simulations and the nuclear overlap $S_T$ from Glauber simulations for the data shown in Fig. 5. Here we assume $dN/d\eta$ = $\frac{3}{2}dN_{ch}/d\eta$.

Data table for $\sigma_{\psi(2S)}/\sigma_{\psi(1S)}$ ratios, measured in the dimuon decay channel. Here "fwd" refers to the forward rapidity interval $1.2<y<2.2$, "bwd" refers to the backward rapidity interval $-2.2<y<-1.2$, and "comb" refers to the rapidity interval $1.2<|y|<2.2$.

Efficiency corrected cumulants of net-charge distributions as a function of $\langle N_{part} \rangle$ from Au+Au collisions at different collision energies.

$\langle N_{part} \rangle$ dependence of efficiency corrected $\mu / \sigma^2$ of net-charge distributions for Au+Au collisions at different collision energies.

$\langle N_{part} \rangle$ dependence of efficiency corrected $S \sigma$ of net-charge distributions for Au+Au collisions at different collision energies.

$\langle N_{part} \rangle$ dependence of efficiency corrected $\kappa \sigma^2$ of net-charge distributions for Au+Au collisions at different collision energies.

$\langle N_{part} \rangle$ dependence of efficiency corrected $S \sigma^3 / \mu$ of net-charge distributions for Au+Au collisions at different collision energies.

The energy dependence of efficiency corrected $\mu / \sigma^2$, $S \sigma$, $\kappa \sigma^2$, and $S \sigma^3 / \mu$ of netcharge distributions for central (0%–5%) Au+Au collisions.

The energy dependence of the chemical freeze-out parameter $\mu_B$.

$z_{g}$ for Matched Trigger jets in pp$+$AuAu Data anti-kT R$=$0.4

$z_{g}$ for HardCore Recoil jets in AuAu Data anti-kT R$=$0.4

$z_{g}$ for HardCore Recoil jets in pp$+$AuAu Data anti-kT R$=$0.4

$z_{g}$ for Matched Recoil jets in AuAu Data anti-kT R$=$0.4

$z_{g}$ for Matched Recoil jets in pp$+$AuAu Data anti-kT R$=$0.4

$R_{g}$ for HardCore Trigger jets in AuAu Data anti-kT R$=$0.4

$R_{g}$ for HardCore Trigger jets in pp$+$AuAu Data anti-kT R$=$0.4

$R_{g}$ for Matched Trigger jets in AuAu Data anti-kT R$=$0.4

$R_{g}$ for Matched Trigger jets in pp$+$AuAu Data anti-kT R$=$0.4

$R_{g}$ for HardCore Recoil jets in AuAu Data anti-kT R$=$0.4

$R_{g}$ for HardCore Recoil jets in pp$+$AuAu Data anti-kT R$=$0.4

$R_{g}$ for Matched Recoil jets in AuAu Data anti-kT R$=$0.4

$R_{g}$ for Matched Recoil jets in pp$+$AuAu Data anti-kT R$=$0.4

Fully corrected two subjet $z_{sj}$ for $15 < p_{\rm{T, jet}} < 20$ GeV/c, R$=$0.4 anti-kT and R$=$0.1 subjets

Fully corrected two subjet $z_{sj}$ for $20 < p_{\rm{T, jet}} < 25$ GeV/c, R$=$0.4 anti-kT and R$=$0.1 subjets

Fully corrected two subjet $z_{sj}$ for $25 < p_{\rm{T, jet}} < 30$ GeV/c, R$=$0.4 anti-kT and R$=$0.1 subjets

Fully corrected two subjet $z_{sj}$ for $30 < p_{\rm{T, jet}} < 40$ GeV/c, R$=$0.4 anti-kT and R$=$0.1 subjets

Fully corrected two subjet $\theta_{sj}$ for $15 < p_{\rm{T, jet}} < 20$ GeV/c, R$=$0.4 anti-kT and R$=$0.1 subjets

Fully corrected two subjet $\theta_{sj}$ for $20 < p_{\rm{T, jet}} < 25$ GeV/c, R$=$0.4 anti-kT and R$=$0.1 subjets

Fully corrected two subjet $\theta_{sj}$ for $25 < p_{\rm{T, jet}} < 30$ GeV/c, R$=$0.4 anti-kT and R$=$0.1 subjets

Fully corrected two subjet $\theta_{sj}$ for $30 < p_{\rm{T, jet}} < 40$ GeV/c, R$=$0.4 anti-kT and R$=$0.1 subjets

$z_{sj}$ for HardCore Trigger jets in AuAu Data anti-kT R$=$0.4

$z_{sj}$ for HardCore Trigger jets in pp$+$AuAu Data anti-kT R$=$0.4

$z_{sj}$ for Matched Trigger jets in AuAu Data anti-kT R$=$0.4

$z_{sj}$ for Matched Trigger jets in pp$+$AuAu Data anti-kT R$=$0.4

$z_{sj}$ for HardCore Recoil jets in AuAu Data anti-kT R$=$0.4

$z_{sj}$ for HardCore Recoil jets in pp$+$AuAu Data anti-kT R$=$0.4

$z_{sj}$ for Matched Recoil jets in AuAu Data anti-kT R$=$0.4

$z_{sj}$ for Matched Recoil jets in pp$+$AuAu Data anti-kT R$=$0.4

$\theta_{sj}$ for HardCore Trigger jets in AuAu Data anti-kT R$=$0.4

$\theta_{sj}$ for HardCore Trigger jets in pp$+$AuAu Data anti-kT R$=$0.4

$\theta_{sj}$ for Matched Trigger jets in AuAu Data anti-kT R$=$0.4

$\theta_{sj}$ for Matched Trigger jets in pp$+$AuAu Data anti-kT R$=$0.4

$\theta_{sj}$ for HardCore Recoil jets in AuAu Data anti-kT R$=$0.4

$\theta_{sj}$ for HardCore Recoil jets in pp$+$AuAu Data anti-kT R$=$0.4

$\theta_{sj}$ for Matched Recoil jets in AuAu Data anti-kT R$=$0.4

$\theta_{sj}$ for Matched Recoil jets in pp$+$AuAu Data anti-kT R$=$0.4

$A_{J}$ for HardCore R=0.4 anti-kT jets with $\theta_{sj} > 0.1$ in Au$+$Au collisions

$A_{J}$ for HardCore R=0.4 anti-kT jets with $\theta_{sj} > 0.1$ in pp$+$AuAu reference

$A_{J}$ for HardCore R=0.4 anti-kT jets with $0.1 < \theta_{sj} < 0.2$ in Au$+$Au collisions

$A_{J}$ for HardCore R=0.4 anti-kT jets with $0.1 < \theta_{sj} < 0.2$ in pp$+$AuAu reference

$A_{J}$ for HardCore R=0.4 anti-kT jets with $0.2 < \theta_{sj} < 0.3$ in Au$+$Au collisions

$A_{J}$ for HardCore R=0.4 anti-kT jets with $0.2 < \theta_{sj} < 0.3$ in pp$+$AuAu reference

$A_{J}$ for Matched R=0.4 anti-kT jets with $\theta_{sj} > 0.1$ in Au$+$Au collisions

$A_{J}$ for Matched R=0.4 anti-kT jets with $\theta_{sj} > 0.1$ in pp$+$AuAu reference

$A_{J}$ for Matched R=0.4 anti-kT jets with $0.1 < \theta_{sj} < 0.2$ in Au$+$Au collisions

$A_{J}$ for Matched R=0.4 anti-kT jets with $0.1 < \theta_{sj} < 0.2$ in pp$+$AuAu reference

$A_{J}$ for Matched R=0.4 anti-kT jets with $0.2 < \theta_{sj} < 0.3$ in Au$+$Au collisions

$A_{J}$ for Matched R=0.4 anti-kT jets with $0.2 < \theta_{sj} < 0.3$ in pp$+$AuAu reference

tracking efficiency in pp collisions as a function of track momentum

tracking efficiency in AuAu collisions as a function of track momentum

absolutely normalized dijet yields scaled by 1/<TAA> in 20-40% central PbPb collisions

absolutely normalized dijet yields scaled by 1/<TAA> in 40-60% central PbPb collisions

absolutely normalized dijet yields scaled by 1/<TAA> in 60-80% central PbPb collisions

self normalized dijets from pp collisions

self normalized dijet distributions in 0-10% central PbPb collisions

self normalized dijet distributions in 10-20% central PbPb collisions

self normalized dijet distributions in 20-40% central PbPb collisions

self normalized dijet distributions in 40-60% central PbPb collisions

self normalized dijet distributions in 60-80% central PbPb collisions

leading jet RAA^pair in 0-10% central PbPb collisions

subleading jet RAA^pair in 0-10% central PbPb collisions

leading jet RAA^pair in 10-20% central PbPb collisions

subleading jet RAA^pair in 10-20% central PbPb collisions

leading jet RAA^pair in 20-40% central PbPb collisions

subleading jet RAA^pair in 20-40% central PbPb collisions

leading jet RAA^pair in 40-60% central PbPb collisions

subleading jet RAA^pair in 40-60% central PbPb collisions

leading jet RAA^pair in 60-80% central PbPb collisions

subleading jet RAA^pair in 60-80% central PbPb collisions

ratio of subleading jet RAA^pair to leading jet RAA^pair in PbPb collisions

The Au+Au 200 GeV measurements of the two-, four- and six-particle elliptic flow and the elliptic flow fluctuations.

The Au+Au 54.4 GeV measurements of the two-, four- and six-particle elliptic flow and the elliptic flow fluctuations.

The Au+Au 39 GeV measurements of the two-, four- and six-particle elliptic flow and the elliptic flow fluctuations.

The Au+Au 27 GeV measurements of the two-, four- and six-particle elliptic flow and the elliptic flow fluctuations.

The Au+Au 19.6 GeV measurements of the two- and four-particle elliptic flow and the elliptic flow fluctuations.

The Au+Au 11.5 GeV measurements of the two- and four-particle elliptic flow and the elliptic flow fluctuations.

The U+U 193 GeV measurements of the two-, four- and six-particle elliptic flow and the elliptic flow fluctuations.

The Cu+Au 200 GeV measurements of the two-, four- and six-particle elliptic flow and the elliptic flow fluctuations.

Parametrization of the $A_{X}$ factor, defined as the fraction of diphoton resonances satisfying the fiducial acceptance at the particle level, as function of $m_{X}$ obtained from the narrow width simulated signal samples produced in gluon fusion.

The correction factor, $C_{X}$, defined as the ratio between the number of reconstructed signal events passing the analysis cuts and the number of signal events at the particle level generated within the fiducial volume, and acceptance correction factor, $A_{X}$, defined as the fraction of diphoton resonances satisfying the fiducial acceptance at the particle level. Both are computed for NWA spin-0 models as a function of $m_{X}$.

Effect of event selections on a scalar MC signal sample generated for $m_{X}$ = 15 GeV and on the data. For the MC sample, the efficiencies are shown after applying event weights and a truth level filter that requires two photons with $p^{\gamma\gamma}_{T}>40$ GeV; for the data, the absolute yields are shown. The initial yields for data include a trigger preselection that is the OR of a list of single photon and diphoton triggers. The "2 $loose$ photons" step includes the kinematic acceptance cuts.

Parameterization of the Double Sided Crystal Ball function parameters describing the scalar mass resolution model as a function of $m_{X}$ [GeV].

The reconstruction efficiency for caloDPJs produced by the decay of &gamma;_d into e⁺e^- or qq&#772;. The reconstruction efficiency is shown for &gamma;_d with 0&lt;|&eta;|&lt;1.1 as a function of their transverse momentum in events where the &gamma;_d L_xy is between 2&nbsp;m and 4&nbsp;m.

Observed 95% CL upper limits on the branching ratio (B) for the decay H&rarr;&nbsp;2&gamma;_d+X and ggF selection, for different &gamma;_d masses and a 125&nbsp;GeV Higgs boson. The limits are shown for the SR_2&mu;^ggF, assuming an FRVZ signal model. The hatched band denotes the region in which the branching ratio of H&rarr;&nbsp;2&gamma;_d+X is larger than unity.

Observed 95% CL upper limits on the branching ratio (B) for the decay H&rarr;&nbsp;2&gamma;_d+X and ggF selection, for different &gamma;_d masses and a 125&nbsp;GeV Higgs boson. The limits are shown for the SR_c+&mu;^ggF, assuming an FRVZ signal model. The hatched band denotes the region in which the branching ratio of H&rarr;&nbsp;2&gamma;_d+X is larger than unity.

Observed 95% CL upper limits on the branching ratio (B) for the decay H&rarr;&nbsp;2&gamma;_d+X and ggF selection, for different &gamma;_d masses and a 125&nbsp;GeV Higgs boson. The limits are shown for the SR_2c^ggF, assuming an FRVZ signal model. The hatched band denotes the region in which the branching ratio of H&rarr;&nbsp;2&gamma;_d+X is larger than unity.

Observed 95% CL upper limits on the branching ratio (B) for the decay H&rarr;&nbsp;2&gamma;_d+X and WH selection, for different &gamma;_d masses and a 125&nbsp;GeV Higgs boson. The limits are shown for the SR_c^WH, assuming an FRVZ signal model. The hatched band denotes the region in which the branching ratio of H&rarr;&nbsp;2&gamma;_d+X is larger than unity.

Observed 95% CL upper limits on the branching ratio (B) for the decay H&rarr;&nbsp;2&gamma;_d+X and WH selection, for different &gamma;_d masses and a 125&nbsp;GeV Higgs boson. The limits are shown for the SR_c+&mu;^WH, assuming an FRVZ signal model. The hatched band denotes the region in which the branching ratio of H&rarr;&nbsp;2&gamma;_d+X is larger than unity.

Observed 95% CL upper limits on the branching ratio (B) for the decay H&rarr;&nbsp;2&gamma;_d+X and WH selection, for different &gamma;_d masses and a 125&nbsp;GeV Higgs boson. The limits are shown for the SR_2c^WH, assuming an FRVZ signal model. The hatched band denotes the region in which the branching ratio of H&rarr;&nbsp;2&gamma;_d+X is larger than unity.

Observed 95% CL upper limits on the branching ratio (B) for the decay H&rarr;&nbsp;2&gamma;_d and ggF selection, for different &gamma;_d masses and a 125&nbsp;GeV Higgs boson. The limits are shown for the SR_2&mu;^ggF, assuming a HAHM signal model. The hatched band denotes the region in which the branching ratio of H&rarr;&nbsp;2&gamma;_d is larger than unity.

Observed 95% CL upper limits on the branching ratio (B) for the decay H&rarr;&nbsp;2&gamma;_d and ggF selection, for different &gamma;_d masses and a 125&nbsp;GeV Higgs boson. The limits are shown for the SR_c+&mu;^ggF, assuming a HAHM signal model. The hatched band denotes the region in which the branching ratio of H&rarr;&nbsp;2&gamma;_d is larger than unity.

Observed 95% CL upper limits on the branching ratio (B) for the decay H&rarr;&nbsp;2&gamma;_d and ggF selection, for different &gamma;_d masses and a 125&nbsp;GeV Higgs boson. The limits are shown for the SR_2c^ggF, assuming a HAHM signal model. The hatched band denotes the region in which the branching ratio of H&rarr;&nbsp;2&gamma;_d is larger than unity.

The CalRatio 2015--2016 trigger efficiency for the decay of &gamma;_d in e⁺e^- or qq&#772;. The trigger efficiency is shown for &gamma;_d with 0&lt;|&eta;|&lt;1.1 as function of the transverse decay length L_xy.

The CalRatio 2015--2016 trigger efficiency for the decay of &gamma;_d in e⁺e^- or qq&#772;. The trigger efficiency is shown for &gamma;_d with 0&lt;|&eta;|&lt;1.1 as function of the transverse momentum, in events where the &gamma;_d L_xy is between 2&nbsp;m and 4&nbsp;m.

The CalRatio 2017--2018 trigger efficiency for the decay of &gamma;_d in e⁺e^- or qq&#772;. The trigger efficiency is shown for &gamma;_d with 0&lt;|&eta;|&lt;1.1 as function of the transverse decay length L_xy.

The CalRatio 2017--2018 trigger efficiency for the decay of &gamma;_d in e⁺e^- or qq&#772;. The trigger efficiency is shown for &gamma;_d with 0&lt;|&eta;|&lt;1.1 as function of the transverse momentum, in events where the &gamma;_d L_xy is between 2&nbsp;m and 4&nbsp;m.

The narrow-scan 2015--2016 trigger efficiency for the decay of &gamma;_d in &mu;⁺&mu;^-. The trigger efficiency is shown for &gamma;_d with 0&lt;|&eta;|&lt;1.1 as function of the transverse decay length L_xy.

The narrow-scan 2015--2016 trigger efficiency for the decay of &gamma;_d in &mu;⁺&mu;^-. The trigger efficiency is shown for &gamma;_d with 0&lt;|&eta;|&lt;1.1 as function of the transverse momentum, in events where the &gamma;_d L_xy is below 6&nbsp;m.

The narrow-scan 2017--2018 trigger efficiency for the decay of &gamma;_d in &mu;⁺&mu;^-. The trigger efficiency is shown for &gamma;_d with 0&lt;|&eta;|&lt;1.1 as function of the transverse decay length L_xy.

The narrow-scan 2017--2018 trigger efficiency for the decay of &gamma;_d in &mu;⁺&mu;^-. The trigger efficiency is shown for &gamma;_d with 0&lt;|&eta;|&lt;1.1 as function of the transverse momentum, in events where the &gamma;_d L_xy is below 6&nbsp;m.

Efficiency of the cosmic-ray tagger as function of the &gamma;_d transverse decay length. The efficiency is calculated accepting the &mu;DPJs for which the cosmic-ray tagger score is &gt; 0.2 for each associated MS-only track.

Efficiency of the cosmic-ray tagger as function of the &gamma;_d transverse momentum. The efficiency is calculated accepting the &mu;DPJs for which the cosmic-ray tagger score is &gt; 0.2 for each associated MS-only track.

Efficiency of the QCD tagger as function of the &gamma;_d transverse decay length. The efficiency is calculated accepting the caloDPJs for which the QCD tagger score is &gt; 0.5.

Efficiency of the QCD tagger as function of the &gamma;_d transverse momentum. The efficiency is calculated accepting the caloDPJs for which the QCD tagger score is &gt; 0.5.

The extrapolated acceptance times efficiencies as a function of the &gamma;_d mean proper lifetime c&tau; for the FRVZ pp &rarr; H&rarr;&nbsp;2&gamma;_d+X process and a SM Higgs boson for the SR_2&mu;^ggF.

The extrapolated acceptance times efficiencies as a function of the &gamma;_d mean proper lifetime c&tau; for the FRVZ pp &rarr; H&rarr;&nbsp;2&gamma;_d+X process and a SM Higgs boson for the SR_c+&mu;^ggF.

The extrapolated acceptance times efficiencies as a function of the &gamma;_d mean proper lifetime c&tau; for the FRVZ pp &rarr; H&rarr;&nbsp;2&gamma;_d+X process and a SM Higgs boson for the SR_2c^ggF.

The extrapolated acceptance times efficiencies as a function of the &gamma;_d mean proper lifetime c&tau; for the FRVZ pp &rarr; H&rarr;&nbsp;2&gamma;_d+X process and a SM Higgs boson for the SR_c^WH.

The extrapolated acceptance times efficiencies as a function of the &gamma;_d mean proper lifetime c&tau; for the FRVZ pp &rarr; H&rarr;&nbsp;2&gamma;_d+X process and a SM Higgs boson for the SR_2c^WH.

The extrapolated acceptance times efficiencies as a function of the &gamma;_d mean proper lifetime c&tau; for the FRVZ pp &rarr; H&rarr;&nbsp;2&gamma;_d+X process and a SM Higgs boson for the SR_c+&mu;^WH.

The extrapolated acceptance times efficiencies for SR_2&mu;^ggF, as a function of the &gamma;_d mean proper lifetime c&tau; for the FRVZ pp &rarr; H&rarr;&nbsp;2&gamma;_d+X process and a Higgs-like scalar with a mass of 800&nbsp;GeV. The coloured bands represent the MC statistical uncertainties.

The extrapolated acceptance times efficiencies for SR_c+&mu;^ggF, as a function of the &gamma;_d mean proper lifetime c&tau; for the FRVZ pp &rarr; H&rarr;&nbsp;2&gamma;_d+X process and a Higgs-like scalar with a mass of 800&nbsp;GeV. The coloured bands represent the MC statistical uncertainties.

The extrapolated acceptance times efficiencies for SR_2c;^ggF, as a function of the &gamma;_d mean proper lifetime c&tau; for the FRVZ pp &rarr; H&rarr;&nbsp;2&gamma;_d+X process and a Higgs-like scalar with a mass of 800&nbsp;GeV. The coloured bands represent the MC statistical uncertainties.

The extrapolated acceptance times efficiencies for SR_2&mu;^ggF, as a function of the &gamma;_d mean proper lifetime c&tau; for the HAHM H&rarr;&nbsp;2&gamma;_d+X process and a SM Higgs boson for the ggF channel.

The extrapolated acceptance times efficiencies for SR_c+&mu;^ggF, as a function of the &gamma;_d mean proper lifetime c&tau; for the HAHM H&rarr;&nbsp;2&gamma;_d+X process and a SM Higgs boson for the ggF channel.

The extrapolated acceptance times efficiencies for SR_2c;^ggF, as a function of the &gamma;_d mean proper lifetime c&tau; for the HAHM H&rarr;&nbsp;2&gamma;_d+X process and a SM Higgs boson for the ggF channel.

The extrapolated acceptance times efficiencies for SR_2&mu;^ggF, as a function of the &gamma;_d mean proper lifetime c&tau; for the FRVZ pp &rarr; H&rarr;&nbsp;4&gamma;_d+X process and a Higgs-like scalar with a mass of 800&nbsp;GeV. The coloured bands represent the MC statistical uncertainties.

The extrapolated acceptance times efficiencies for SR_c+&mu;^ggF, as a function of the &gamma;_d mean proper lifetime c&tau; for the FRVZ pp &rarr; H&rarr;&nbsp;4&gamma;_d+X process and a Higgs-like scalar with a mass of 800&nbsp;GeV. The coloured bands represent the MC statistical uncertainties.

The extrapolated acceptance times efficiencies for SR_2c;^ggF, as a function of the &gamma;_d mean proper lifetime c&tau; for the FRVZ pp &rarr; H&rarr;&nbsp;4&gamma;_d+X process and a Higgs-like scalar with a mass of 800&nbsp;GeV. The coloured bands represent the MC statistical uncertainties.

The extrapolated acceptance times efficiencies for SR_2&mu;^ggF, as a function of the &gamma;_d mean proper lifetime c&tau; for the FRVZ pp &rarr; H&rarr;&nbsp;4&gamma;_d+X process and a SM Higgs boson. The coloured bands represent the MC statistical uncertainties.

The extrapolated acceptance times efficiencies for SR_c+&mu;^ggF, as a function of the &gamma;_d mean proper lifetime c&tau; for the FRVZ pp &rarr; H&rarr;&nbsp;4&gamma;_d+X process and a SM Higgs boson. The coloured bands represent the MC statistical uncertainties.

The extrapolated acceptance times efficiencies for SR_2c;^ggF, as a function of the &gamma;_d mean proper lifetime c&tau; for the FRVZ pp &rarr; H&rarr;&nbsp;4&gamma;_d+X process and a SM Higgs boson. The coloured bands represent the MC statistical uncertainties.

Observed limits at the 95% CL on the branching ratio (B), obtained from the SR_2&mu;^ggF, for the process pp &rarr; H&rarr;&nbsp;4&gamma;_d+X, for different &gamma;_d masses and a 125 GeV Higgs boson. The limits are shown assuming an FRVZ signal model.

Observed limits at the 95% CL on the branching ratio (B), obtained from the SR_c+&mu;^ggF, for the process pp &rarr; H&rarr;&nbsp;4&gamma;_d+X, for different &gamma;_d masses and a 125 GeV Higgs boson. The limits are shown assuming an FRVZ signal model.

Observed limits at the 95% CL on the branching ratio (B), obtained from the SR_2c^ggF, for the process pp &rarr; H&rarr;&nbsp;4&gamma;_d+X, for different &gamma;_d masses and a 125 GeV Higgs boson. The limits are shown assuming an FRVZ signal model.

Observed limits at the 95% CL on the cross section, obtained from the SR_2&mu;^ggF, for the process pp &rarr; H&rarr;&nbsp;2&gamma;_d+X, for different &gamma;_d masses and a Higgs-like scalar with a mass of 800&nbsp;GeV. The limits are shown assuming an FRVZ signal model.

Observed limits at the 95% CL on the cross section, obtained from the SR_c+&mu;^ggF, for the process pp &rarr; H&rarr;&nbsp;2&gamma;_d+X, for different &gamma;_d masses and a Higgs-like scalar with a mass of 800&nbsp;GeV. The limits are shown assuming an FRVZ signal model.

Observed limits at the 95% CL on the cross section, obtained from the SR_2c^ggF, for the process pp &rarr; H&rarr;&nbsp;2&gamma;_d+X and ggF selection, for different &gamma;_d masses and a Higgs-like scalar with a mass of 800&nbsp;GeV. The limits are shown assuming an FRVZ signal model.

Observed limits at the 95% CL on the cross section for the process pp &rarr; H&rarr;&nbsp;4&gamma;_d+X and ggF selection, for different &gamma;_d masses and a Higgs-like scalar with a mass of 800&nbsp;GeV. The limits are shown for the 2&mu; search channel, assuming an FRVZ signal model.

Observed limits at the 95% CL on the cross section for the process pp &rarr; H&rarr;&nbsp;4&gamma;_d+X and ggF selection, for different &gamma;_d masses and a Higgs-like scalar with a mass of 800&nbsp;GeV. The limits are shown for the c+&mu; search channel, assuming an FRVZ signal model.

Observed limits at the 95% CL on the cross section for the process pp &rarr; H&rarr;&nbsp;4&gamma;_d+X and ggF selection, for different &gamma;_d masses and a Higgs-like scalar with a mass of 800&nbsp;GeV. The limits are shown for the 2c search channel, assuming an FRVZ signal model.

Comparison between data and background prediction before the fit (Pre-Fit) for the mass of the FCNC top-quark candidate in SR1. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The four FCNC LH signals are also shown separately, normalized to five times the cross-section corresponding to the most stringent observed branching ratio limits. The first (last) bin in all distributions includes the underflow (overflow). The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction before the fit (Pre-Fit) for the mass of the SM top-quark candidate in SR2. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The four FCNC LH signals are also shown separately, normalized to five times the cross-section corresponding to the most stringent observed branching ratio limits. The first (last) bin in all distributions includes the underflow (overflow). The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction before the fit (Pre-Fit) for the transverse momentum of the Z boson candidate in SR2. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The four FCNC LH signals are also shown separately, normalized to five times the cross-section corresponding to the most stringent observed branching ratio limits. The first (last) bin in all distributions includes the underflow (overflow). The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZu LH coupling extraction. The distribution is for the $D_{1}$ discriminant in the mass sideband CR1. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZu LH signals are also separately shown, normalized to 500 times the best fit of the signal yield. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZu LH coupling extraction. The distribution is for the $D_{2}^{u}$ discriminant in the mass sideband CR2. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZu LH signals are also separately shown, normalized to 500 times the best fit of the signal yield. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZu LH coupling extraction. The distribution is for the $D_{1}$ discriminant in SR1. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZu LH signals are also separately shown, normalized to 50 times the best fit of the signal yield. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZu LH coupling extraction. The distribution is for the $D_{2}^{u}$ discriminant in SR2. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZu LH signals are also separately shown, normalized to 50 times the best fit of the signal yield. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZc LH coupling extraction. The distribution is for the $D_{1}$ discriminant in the mass sideband CR1. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZc LH signals are also separately shown, normalized to 500 times the best fit of the signal yield. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZc LH coupling extraction. The distribution is for the $D_{2}^{c}$ discriminant in the mass sideband CR2. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZc LH signals are also separately shown, normalized to 500 times the best fit of the signal yield. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZc LH coupling extraction. The distribution is for the $D_{1}$ discriminant in SR1. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZc LH signals are also separately shown, normalized to 50 times the best fit of the signal yield. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZc LH coupling extraction. The distribution is for the $D_{2}^{c}$ discriminant in SR2. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZc LH signals are also separately shown, normalized to 50 times the best fit of the signal yield. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZu LH coupling extraction. The distribution is for the leading lepton $p_{T}$ in the $t\bar{t}$ CR. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZu LH signals are also shown separately, normalized to $10^{3}$ times the best fit of the signal yield. The last bin includes the overflow. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZu LH coupling extraction. The distribution is for the third lepton $p_{T}$ in the $t\bar{t}$ CR. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZu LH signals are also shown separately, normalized to $10^{3}$ times the best fit of the signal yield. The last bin includes the overflow. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZu LH coupling extraction. The distribution is for the leading lepton $p_{T}$ in the $t\bar{t}Z$ CR. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZu LH signals are also shown separately, normalized to $10^{3}$ times the best fit of the signal yield. The last bin includes the overflow. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZu LH coupling extraction. The distribution is for the $D_{1}$ discriminant in the $t\bar{t}Z$ CR. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZu LH signals are also shown separately, normalized to $10^{3}$ times the best fit of the signal yield. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Measured differential cross section as a function of observable $ p_{T}^{ll} - p_{T}^{\gamma}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll} + p_{T}^{\gamma}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll} + p_{T}^{\gamma}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ \Delta R (l,l)$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ \Delta R (l,l)$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ N_{jets}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ N_{jets}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{Jet1}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{Jet1}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{Jet2}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{Jet2}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{Jet2}/p_{T}^{Jet1}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{Jet2}/p_{T}^{Jet1}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ m_{jj}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ m_{jj}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ m_{ll\gamma j}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ m_{ll\gamma j}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ H_{T}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ H_{T}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{\gamma} / \sqrt{H_{T}}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{\gamma} / \sqrt{H_{T}}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ \Delta \phi (Jet,\gamma)$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ \Delta \phi (Jet,\gamma)$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll\gamma j}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll\gamma j}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ \phi_{CS}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ \phi_{CS}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ \cos \theta_{CS}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ \cos \theta_{CS}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll\gamma} / m_{ll\gamma}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll\gamma} / m_{ll\gamma}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll\gamma} / m_{ll\gamma}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll\gamma} / m_{ll\gamma}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll\gamma} / m_{ll\gamma}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll\gamma} / m_{ll\gamma}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll} - p_{T}^{\gamma}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll} - p_{T}^{\gamma}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll} - p_{T}^{\gamma}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll} - p_{T}^{\gamma}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll} - p_{T}^{\gamma}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll} - p_{T}^{\gamma}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll\gamma j}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll\gamma j}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll\gamma j}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll\gamma j}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll\gamma j}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Measured differential cross section as a function of observable $ p_{T}^{ll\gamma j}$. Error on the measured cross-section include all the systematic uncertainties. SM predictions are produced with the event generators at particle level: Sherpa 2.2.4, Sherpa 2.2.11, MadGraph5_aMC@NLO, and MiNNLO$_{PS}$. Fixed order calculations results use MATRIX NNLO. Error represent statistical uncertainty and theoretical uncertainty (PDF and Scale variations).

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{\gamma} / \sqrt{H_{T}}$ (Fig. 8 (b))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{\gamma} / \sqrt{H_{T}}$ (Fig. 8 (b))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ H_{T}$ (Fig. 8 (a))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ H_{T}$ (Fig. 8 (a))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ \Delta \phi (Jet,\gamma)$ (Fig. 8 (c))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ \Delta \phi (Jet,\gamma)$ (Fig. 8 (c))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ \Delta R (l,l)$ (Fig. 5 (d))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ \Delta R (l,l)$ (Fig. 5 (d))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll} - p_{T}^{\gamma}$ (Fig. 5 (b))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll} - p_{T}^{\gamma}$ (Fig. 5 (b))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll} - p_{T}^{\gamma} \textrm{ in bin } p_{T}^{ll} + p_{T}^{\gamma} < 200 GeV$ (Fig. 11 (a))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll} - p_{T}^{\gamma} \textrm{ in bin } p_{T}^{ll} + p_{T}^{\gamma} < 200 GeV$ (Fig. 11 (a))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll} - p_{T}^{\gamma} \textrm{ in bin } 200 GeV < p_{T}^{ll} + p_{T}^{\gamma} < 300 GeV$ (Fig. 11 (b))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll} - p_{T}^{\gamma} \textrm{ in bin } 200 GeV < p_{T}^{ll} + p_{T}^{\gamma} < 300 GeV$ (Fig. 11 (b))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll} - p_{T}^{\gamma} \textrm{ in bin } p_{T}^{ll} + p_{T}^{\gamma} > 300 GeV$ (Fig. 11 (c))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll} - p_{T}^{\gamma} \textrm{ in bin } p_{T}^{ll} + p_{T}^{\gamma} > 300 GeV$ (Fig. 11 (c))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ m_{jj}$ (Fig. 7 (a))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ m_{jj}$ (Fig. 7 (a))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ m_{ll\gamma j}$ (Fig. 7 (b))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ m_{ll\gamma j}$ (Fig. 7 (b))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ N_{jets}$ (Fig. 6 (a))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ N_{jets}$ (Fig. 6 (a))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{Jet1}$ (Fig. 6 (b))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{Jet1}$ (Fig. 6 (b))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{Jet2}$ (Fig. 6 (c))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{Jet2}$ (Fig. 6 (c))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{Jet2}/p_{T}^{Jet1}$ (Fig. 6 (d))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{Jet2}/p_{T}^{Jet1}$ (Fig. 6 (d))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll}$ (Fig. 5 (a))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll}$ (Fig. 5 (a))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll\gamma j}$ (Fig. 8 (d))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll\gamma j}$ (Fig. 8 (d))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll\gamma j} \textrm{ in bin } p_{T}^{ll\gamma} < 50 GeV$ (Fig. 12 (a))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll\gamma j} \textrm{ in bin } p_{T}^{ll\gamma} < 50 GeV$ (Fig. 12 (a))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll\gamma j} \textrm{ in bin } 50 GeV < p_{T}^{ll\gamma} < 75 GeV$ (Fig. 12 (b))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll\gamma j} \textrm{ in bin } 50 GeV < p_{T}^{ll\gamma} < 75 GeV$ (Fig. 12 (b))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll\gamma j} \textrm{ in bin } p_{T}^{ll\gamma} > 75 GeV$ (Fig. 12 (c))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll\gamma j} \textrm{ in bin } p_{T}^{ll\gamma} > 75 GeV$ (Fig. 12 (c))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll\gamma} / m_{ll\gamma} \textrm{ in bin } 125 GeV < m_{ll\gamma} < 200 GeV$ (Fig. 10 (a))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll\gamma} / m_{ll\gamma} \textrm{ in bin } 125 GeV < m_{ll\gamma} < 200 GeV$ (Fig. 10 (a))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll\gamma} / m_{ll\gamma} \textrm{ in bin } 200 GeV < m_{ll\gamma} < 300 GeV$ (Fig. 10 (b))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll\gamma} / m_{ll\gamma} \textrm{ in bin } 200 GeV < m_{ll\gamma} < 300 GeV$ (Fig. 10 (b))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll\gamma} / m_{ll\gamma} \textrm{ in bin } m_{ll\gamma} > 300 GeV$ (Fig. 10 (c))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll\gamma} / m_{ll\gamma} \textrm{ in bin } m_{ll\gamma} > 300 GeV$ (Fig. 10 (c))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll} + p_{T}^{\gamma}$ (Fig. 5 (c))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ p_{T}^{ll} + p_{T}^{\gamma}$ (Fig. 5 (c))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ \cos \theta_{CS}$ (Fig. 9 (b))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ \cos \theta_{CS}$ (Fig. 9 (b))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ \phi_{CS}$ (Fig. 9 (a))

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $ \phi_{CS}$ (Fig. 9 (a))

The observed and expected 95% CL upper limits on the minimal coupling vector LQ pair production cross-sections assuming B = 1 as a function of m$_\text{LQ}$.

The observed and expected 95% CL upper limits on the Yang-Mills coupling vector LQ pair production cross-sections assuming B = 1 as a function of m$_\text{LQ}$.

The observed and expected 95% CL upper limits on the branching ratio into charged leptons as a function of m$_\text{LQ}$ for the scalar LQ.

The observed and expected 95% CL upper limits on the branching ratio into charged leptons as a function of m$_\text{LQ}$ for the vector LQ minimal coupling scenario.

The observed and expected 95% CL upper limits on the branching ratio into charged leptons as a function of m$_\text{LQ}$ for the vector LQ Yang-Mills coupling scenario.

Data selection efficiency as a function of nuclear recoil energy

Data points used in analysis in log_10(S2)-S1 space

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Inclusive unlike-sign $\mu \mu$ pair yield from $p$+$p$ collisions at $\sqrt{s}$ = 200 GeV as a function of mass in different $p_T$ slices for the south and north muon arms and the ratio of data to expected sources.

Inclusive unlike-sign $\mu \mu$ pair yield from $p$+$p$ collisions at $\sqrt{s}$ = 200 GeV as a function of mass in different $p_T$ slices for the south and north muon arms and the ratio of data to expected sources.

Inclusive like-sign $\mu \mu$ pair yield from $p$+$p$ collisions at $\sqrt{s}$ = 200 GeV as a function of mass in different $p_T$ slices for the south and north muon arms and the ratio of data to expected sources.

Inclusive like-sign $\mu \mu$ pair yield from $p$+$p$ collisions at $\sqrt{s}$ = 200 GeV as a function of mass in different $p_T$ slices for the south and north muon arms and the ratio of data to expected sources.

Inclusive like-sign $\mu \mu$ pair yield from $p$+$p$ collisions at $\sqrt{s}$ = 200 GeV as a function of mass in different $p_T$ slices for the south and north muon arms and the ratio of data to expected sources.

The $\mu \mu$ pair data in the charm mass region as a function of $\Delta \phi$.

The $\mu \mu$ pair data in the charm mass region as a function of $\Delta \phi.$

The $\mu \mu$ pair data in the charm mass region as a function of pair $p_T$.

The $\mu \mu$ pair data in the charm mass region as a function of pair $p_T$

The like-sign $\mu \mu$ pair data in the bottom mass region as a function of $\Delta \phi$.

The like-sign $\mu \mu$ pair data in the bottom mass region as a function of $\Delta \phi$.

The like-sign $\mu \mu$ pair data in the bottom mass region as a function of pair $p_T$.

The like-sign $\mu \mu$ pair data in the bottom mass region as a function of pair $p_T$.

The unlike-sign $\mu \mu$ pair data used to determine the Drell-Yan contribution as a function of mass.

The unlike-sign $\mu \mu$ pair data used to determine the Drell-Yan contribution as a function of mass.

The unlike-sign $\mu \mu$ pair data used to determine the Drell-Yan contribution as a function of pair $p_T$.

The unlike-sign $\mu \mu$ pair data used to determine the Drell-Yan contribution as a function of pair $p_T$.

Summary of arm-averaged relative systematic uncertainties for the total bottom cross section $\sigma _{b\bar{b}}$, the differential Drell-Yan cross section $d^{2}\sigma _{DY\implies \mu\mu}/dmdy$, and the $b\bar{b}$ ($c\bar{c}$) differential yields $dN_{b\bar{b}(c\bar{c})\implies \mu\mu}/d\Delta\phi$. The systematic uncertainty type is indicated in the second column and is applicable only to the differential measurements. The uncertainties for the differential measurements vary with azimuthal opening angle, pair $p_{T}$ , or mass. Asymmetric uncertainties are quoted in bracketed values. For the $c\bar{c}$ measurement, the regions $\Delta\phi$ < $\pi$/2, $p_{T}$ < 0.5 GeV/$c$ and $p_{T}$ > 2.0 GeV/$c$ are excluded because the yield approaches zero and relative systematic uncertainties diverge. With these regions excluded, the difference between the systematic uncertainties of all measurements for the south and north muon arms differs by no greater than 2% for all systematic uncertainties sources.

The differential yield $dN/d\phi$ of unlike-sign muon pairs from charm with mass 1.5-2.5 GeV/$c^2$ in the ideal muon arm acceptance, as a function of the pair azimuthal opening angle. Statistical (stat.) and types B and C systematic errors (sys. B & sys. C) are all $10^{-9}\times$[rad$^{-1}$].

The differential yield $dN/d\phi$ of like-sign muon pairs from bottom with mass 3.5-10.0 GeV/$c^2$ in the ideal muon arm acceptance, as a function of the pair azimuthal opening angle. Statistical (stat.) and types B and C systematic errors (sys. B & sys. C) are all $10^{-9}\times$[rad$^{-1}$].

The differential yield $dN/dp_{T}$ of unlike-sign muon pairs from bottom with mass 1.5-2.5 GeV/$c^2$ in the ideal muon arm acceptance, as a function of the pair transverse momentum. Statistical (stat.) and types B and C systematic errors (sys. B & sys. C) are all $10^{-9}\times$[$c$/GeV].

The differential yield $dN/dp_{T}$ of like-sign muon pairs from bottom with mass 3.5-10.0 GeV/$c^2$ in the ideal muon arm acceptance, as a function of the pair transverse momentum. Statistical (stat.) and types B and C systematic errors (sys. B & sys. C) are all $10^{-9}\times$[$c$/GeV].

$\sigma_{b\bar{b}}$ from fit using different models. Only statistical uncertainties are shown.

The differential Drell-Yan cross section $\frac{d^{2}\sigma}{dmdy}$ as a function of the muon pair mass, where the muon pair rapidity |$y\mu\mu$| is between 1.2 and 2.2. Statistical (stat.) and types B and C systematic errors (sys. B & sys. C) are all $10^{-9}\times$[pb $c^2$/GeV]. In the data table below, the value of mass correspond to the center of the stated range.

The differential Drell-Yan cross section $\frac{1}{2\pi p_{T}} \frac{d^{2}\sigma}{dydp_{T}}$ as a function of the muon pair transverse momentum, where the muon pair mass $m_{\mu\mu}$ is between 4.8 and 8.2 GeV/$c^2$ and the muon pair rapidity |$y\mu\mu$| is between 1.2 and 2.2. Statistical (stat.) and types B and C systematic errors (sys. B & sys. C) are all $10^{-9}\times$[pb $c^2$/GeV]. In the data table below, the value of p_T correspond to the center of the stated range.

The relative nuclear-modification factor for U+U and Au+Au as a function of collision centrality.

The ratio of the invariant yield for U+U to that for Au+Au, as a function of collision centrality.

Probability of finding at least one TAR jet, where the p_T-leading TAR jet passes the m_Wcand and D₂^&beta;=1 requirements, as a function of m_s. The probability is determined in a sample of signal events with m_Z'=2100 GeV, with the preselections applied.

Probability of finding a W_had candidate reconstructed as a pair of R=0.4 PFlow jets, as a function of m_s. The probability is determined in a sample of signal events with m_Z'=500 GeV, with the preselections applied that do not pass the requirements of the merged category.

Probability of finding a W_had candidate reconstructed as a pair of R=0.4 PFlow jets, as a function of m_s. The probability is determined in a sample of signal events with m_Z'=1000 GeV, with the preselections applied that do not pass the requirements of the merged category.

Probability of finding a W_had candidate reconstructed as a pair of R=0.4 PFlow jets, as a function of m_s. The probability is determined in a sample of signal events with m_Z'=1700 GeV, with the preselections applied that do not pass the requirements of the merged category.

Probability of finding a W_had candidate reconstructed as a pair of R=0.4 PFlow jets, as a function of m_s. The probability is determined in a sample of signal events with m_Z'=2100 GeV, with the preselections applied that do not pass the requirements of the merged category.

Observed exclusion contour at 95&#37; C.L. for the dark Higgs model in the (m_Z', m_s) plane for g_q=0.25, g_&chi;=1, m_&chi;=200 GeV, and sin&theta;=0.01.

Expected exclusion contour at 95&#37; C.L. for the dark Higgs model in the (m_Z', m_s) plane for g_q=0.25, g_&chi;=1, m_&chi;=200 GeV, and sin&theta;=0.01.

Expected+1&sigma; exclusion contour at 95&#37; C.L. for the dark Higgs model in the (m_Z', m_s) plane for g_q=0.25, g_&chi;=1, m_&chi;=200 GeV, and sin&theta;=0.01.

Expected-1&sigma; exclusion contour at 95&#37; C.L. for the dark Higgs model in the (m_Z', m_s) plane for g_q=0.25, g_&chi;=1, m_&chi;=200 GeV, and sin&theta;=0.01.

Expected+2&sigma; exclusion contour at 95&#37; C.L. for the dark Higgs model in the (m_Z', m_s) plane for g_q=0.25, g_&chi;=1, m_&chi;=200 GeV, and sin&theta;=0.01.

Expected-2&sigma; exclusion contour at 95&#37; C.L. for the dark Higgs model in the (m_Z', m_s) plane for g_q=0.25, g_&chi;=1, m_&chi;=200 GeV, and sin&theta;=0.01.

Observed upper limits at 95&#37; C.L. on &sigma;(pp &rarr; s &chi;&chi;) &times; B(s &rarr; W^&pm; W^&mp;) for m_Z'=0.5 TeV as a function of m_s. The expected limits, varied up and down by one and two standard deviations, are shown as green and yellow bands, respectively. The observed and expected limits are compared to the theoretical LO cross section for the &sigma;(pp &rarr; s &chi;&chi;) &times; B(s &rarr; W^&pm; W^&mp;) process for m_Z'=0.5 TeV, shown in dashed blue.

Observed upper limits at 95&#37; C.L. on &sigma;(pp &rarr; s &chi;&chi;) &times; B(s &rarr; W^&pm; W^&mp;) for m_Z'=1 TeV as a function of m_s. The expected limits, varied up and down by one and two standard deviations, are shown as green and yellow bands, respectively. The observed and expected limits are compared to the theoretical LO cross section for the &sigma;(pp &rarr; s &chi;&chi;) &times; B(s &rarr; W^&pm; W^&mp;) process for m_Z'=1 TeV, shown in dashed blue.

Observed upper limits at 95&#37; C.L. on &sigma;(pp &rarr; s &chi;&chi;) &times; B(s &rarr; W^&pm; W^&mp;) for m_Z'=1.7 TeV as a function of m_s. The expected limits, varied up and down by one and two standard deviations, are shown as green and yellow bands, respectively. The observed and expected limits are compared to the theoretical LO cross section for the &sigma;(pp &rarr; s &chi;&chi;) &times; B(s &rarr; W^&pm; W^&mp;) process for m_Z'=1.7 TeV, shown in dashed blue.

Observed upper limits at 95&#37; C.L. on &sigma;(pp &rarr; s &chi;&chi;) &times; B(s &rarr; W^&pm; W^&mp;) for m_Z'=2.1 TeV as a function of m_s. The expected limits, varied up and down by one and two standard deviations, are shown as green and yellow bands, respectively. The observed and expected limits are compared to the theoretical LO cross section for the &sigma;(pp &rarr; s &chi;&chi;) &times; B(s &rarr; W^&pm; W^&mp;) process for m_Z'=2.1 TeV, shown in dashed blue.

Data overlaid on SM background yields stacked in each SR and CR category after the fit to data ('Post-fit'). The yields in the SR are broken down into their contributions to the individual bins. The maximum-likelihood estimators are set to the conditional values of the CR-only fit, and propagated to SR and CRs.

Dominant sources of uncertainty for three dark Higgs scenarios after the fit to data. The uncertainties are quantified in terms of their contribution to the fitted signal uncertainty that is expressed relative to the theory prediction. Three representative dark Higgs signal scenarios with g_q=0.25, g_&chi;=1.0, sin&theta;=0.01 and m_&chi;=200 GeV are considered, which are indicated using the (m_Z', m_s) format in units of GeV in the table columns.

Cumulative efficiencies in the merged category for three representative dark Higgs signal scenarios with g_q=0.25, g_&chi;=1.0, sin&theta;=0.01, m_Z' = 1 TeV, and m_&chi;=200 GeV considering s&rarr;W(&ell;&nu;)W(qq) decays only.

Cumulative efficiencies in the resolved category for three representative dark Higgs signal scenarios with g_q=0.25, g_&chi;=1.0, sin&theta;=0.01, m_Z' = 1 TeV, and m_&chi;=200 GeV considering s&rarr;W(&ell;&nu;)W(qq) decays only.

Theoretical cross section for &sigma;(pp &rarr; s&chi;&chi;) &times; B(s &rarr; W^&plusmn;W^&#8723;) for each of the dark Higgs signal points at m_Z′ ={300, 350, 400, 500, 750} GeV, with g_q = 0.25, g<sub>&chi; = 1.0, sin&theta; = 0.01, m_Z′ = 1 TeV , and m_&chi; = 200 GeV. Also shown are experimentally excluded cross sections of &sigma;(pp &rarr; s&chi;&chi;) &times; B(s &rarr; W^&plusmn;W^&#8723;) (Obs.) together with the expectations (Exp.) varied up and down by one standard deviation (&plusmn;1&sigma;).

Theoretical cross section for &sigma;(pp &rarr; s&chi;&chi;) &times; B(s &rarr; W^&plusmn;W^&#8723;) for each of the dark Higgs signal points at m_Z′ ={1000, 1700} GeV, with g_q = 0.25, g<sub>&chi; = 1.0, sin&theta; = 0.01, m_Z′ = 1 TeV , and m_&chi; = 200 GeV. Also shown are experimentally excluded cross sections of &sigma;(pp &rarr; s&chi;&chi;) &times; B(s &rarr; W^&plusmn;W^&#8723;) (Obs.) together with the expectations (Exp.) varied up and down by one standard deviation (&plusmn;1&sigma;).

Theoretical cross section for &sigma;(pp &rarr; s&chi;&chi;) &times; B(s &rarr; W^&plusmn;W^&#8723;) for each of the dark Higgs signal points at m_Z′ ={2100, 2500, 2900, 3300} GeV, with g_q = 0.25, g<sub>&chi; = 1.0, sin&theta; = 0.01, m_Z′ = 1 TeV , and m_&chi; = 200 GeV. Also shown are experimentally excluded cross sections of &sigma;(pp &rarr; s&chi;&chi;) &times; B(s &rarr; W^&plusmn;W^&#8723;) (Obs.) together with the expectations (Exp.) varied up and down by one standard deviation (&plusmn;1&sigma;).

Lévy scale parameter $R$ versus average $m_T$ of the pair. The graphical representation of statistical and systematic uncertainties is the same as in Fig. 4.

Lévy index parameter $\alpha$ versus average $m_T$ of the pair. Statistical and systematic uncertainties are indicated similarly to Fig. 4. The horizontal line, %\aplha$ = 1.207, represents the 0%-30% centrality average value of %\aplha$.

Inverse square of the Lévy scale parameter 1/$R^2$ versus average $m_T$ of the pair. Statistical and systematic uncertainties shown as bars and boxes, respectively.

New scale parameter $\hat{R}$ versus average $m_T$ of the pair, with a linear fit. Statistical and systematic uncertainties shown as bars and boxes, respectively.

Normalized correlation strength parameter $\lambda/\lambda_{max}$ versus average $m_T$ of the pair. The data are compared with parameter scans from Refs. [58, 59] using different values of in-medium $\eta^{\prime}$ mass $m^{*}_{\eta^{\prime}}$ and slope parameter $B^{-1}_{\eta^{\prime}}$ . A best fit with Eq. (63) and the resulting $H$ and $\sigma$ parameters are also shown.

Normalized correlation strength parameter $\lambda/\lambda_{max}$ versus average $m_T$ of the pair. The data are compared with parameter scans from Refs. [58, 59] using different values of in-medium $\eta^{\prime}$ mass $m^{*}_{\eta^{\prime}}$ and slope parameter $B^{-1}_{\eta^{\prime}}$ . A best fit with Eq. (63) and the resulting $H$ and $\sigma$ parameters are also shown.

Normalized correlation strength parameter $\lambda/\lambda_{max}$ versus average $m_T$ of the pair. The data are compared with parameter scans from Refs. [58, 59] using different values of in-medium $\eta^{\prime}$ mass $m^{*}_{\eta^{\prime}}$ and slope parameter $B^{-1}_{\eta^{\prime}}$ . A best fit with Eq. (63) and the resulting $H$ and $\sigma$ parameters are also shown.

Normalized correlation strength parameter $\lambda/\lambda_{max}$ versus average $m_T$ of the pair. The data are compared with parameter scans from Refs. [58, 59] using different values of in-medium $\eta^{\prime}$ mass $m^{*}_{\eta^{\prime}}$ and slope parameter $B^{-1}_{\eta^{\prime}}$ . A best fit with Eq. (63) and the resulting $H$ and $\sigma$ parameters are also shown.

Normalized correlation strength parameter $\lambda/\lambda_{max}$ versus average $m_T$ of the pair. The data are compared with parameter scans from Refs. [58, 59] using different values of in-medium $\eta^{\prime}$ mass $m^{*}_{\eta^{\prime}}$ and slope parameter $B^{-1}_{\eta^{\prime}}$ . A best fit with Eq. (63) and the resulting $H$ and $\sigma$ parameters are also shown.

Dependence of $\overline{p}$-$\overline{d}$ correlation on pseudorapidity acceptance of $\overline{p}$ and $\overline{d}$ selection in Pb-Pb collisions at $\sqrt{s_\mathrm{NN}}$ = 5.02 TeV. Results are for 20.0--30.0$\%$ collision centrality.

Dependence of $\overline{p}$-$\overline{d}$ correlation on pseudorapidity acceptance of $\overline{p}$ and $\overline{d}$ selection in Pb-Pb collisions at $\sqrt{s_\mathrm{NN}}$ = 5.02 TeV. Results are for 50.0--60.0$\%$ collision centrality.

HBT parameters of charge-combined kaon pairs, shown as value $\pm$ statistical uncertainty [absolute value] $\pm$ systematic uncertainty [%] for the centrality bins shown in Fig. 3.

$R_o/R_s$ of positive pion pairs shown as value $\pm$ statistical uncertainty [absolute value] $\pm$ systematic uncertainty [%] for the centrality bins shown in Fig. 4.

$R_o/R_s$ of negative pion pairs shown as value $\pm$ statistical uncertainty [absolute value] $\pm$ systematic uncertainty [%] for the centrality bins shown in Fig. 4.

$R_o/R_s$ of charge-combined kaon pairs shown as value $\pm$ statistical uncertainty [absolute value] $\pm$ systematic uncertainty [%] for the centrality bins shown in Fig. 4.

Azimuthal angle dependence of HBT radii of charged kaons, shown as value $\pm$ statistical uncertainty $\pm$ systematic uncertainty for the centrality bins shown in Fig. 8.

Azimuthal angle dependence of HBT radii of charged pions, shown as value $\pm$ statistical uncertainty $\pm$ systematic uncertainty for the 0%–20% and 20%–60% centrality bins.

Oscillation amplitudes relative to the event plane for charged pions, shown as value $\pm$ statistical uncertainty $\pm$ systematic uncertainty for the 0%–20% and 20%–60% centrality bins.

Oscillation amplitudes relative to the event plane for charged kaons, shown as value $\pm$ statistical uncertainty $\pm$ systematic uncertainty for the 0%–20% and 20%–60% centrality bins.

Summary of extracted parameters in the blast-wave model fit for two fitting conditions. The $T_f$ and $\rho_0$ parameters were obtained by fits to $p_T$ spectra, and the other parameters were obtained by a simultaneous fit to $v_2$ and the HBT radii.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Expected, with the corresponding $\pm 1\sigma$ intervals, and observed 95% CL branching fraction upper limits for the Higgs and $Z$ boson decays into a quarkonium state and a photon. Standard Model production of the Higgs boson is assumed. The corresponding upper limits on the production cross section times branching fraction $\sigma\times\mathcal{B}$ are also shown.

$v(Q)$, for central events, as a function of the azimuthal coverage of the detector for data. (Angles in degrees.)

The effect on $v(Q)$ of varying the acceptance in $\varphi_r$. The solid curve shows the expectation from global charge conservation. The 10% most central events are used for data and RQMD. (Angles in degrees.)

$J/\psi$ $R_{CP}$ for 0-20%, 20-40%, and 40-60% (central) relative to 60-86% (peripheral) Au+Au collisions at 62.4 GeV. Type A errors are point-to-point uncorrelated, Type B errors are point-to-point correlated, and Type C are global systematic from the uncertainty in the peripheral $<N_{coll}>$ value.

$J/\psi$ $R_{CP}$ for 0-40% (central) relative to 40-86% (peripheral) Au+Au collisions at 39 GeV. Type A errors are point-to-point uncorrelated, Type B errors are point-to-point correlated, and Type C are global systematic from the uncertainty in the peripheral $<N_{coll}>$ value.

$J/\psi$ $R_{AA}$ at $\sqrt{s_{NN}}$ = 39 and 62.4 GeV. Type A errors are point-to-point uncorrelated, Type B errors are point-to-point correlated, and Type C are global systematic from the uncertainty in the peripheral $<N_{coll}>$ value.

$J/\psi$ $R_{AA}$ at $\sqrt{s_{NN}}$ = 39 and 62.4 GeV.

The $M_{e_T}$ distributions for four different centrality classes. The curves are the random baseline mixed event distributions. The source of differences in the data and mixed event distributions are addressed in the text.

The residual distribution between the data and mixed event $M_{e_T}$ spectra as a function of $M_{e_T}$ in units of standard deviation. The total ${\chi}^2$ and the number of degrees of freedom for the $0-5\%$, $0-10\%$, $10-20\%$, $20-30\%$ centrality classes are 310.0/32, 896.4/36, 678.7/47, and 553.9/53, respectively. A large fraction of the residual contributions are due to the effects of cluster merging.

The experimental sensitivity and observed limit on the number of dark photon candidates as a function of the assumed dark photon mass.

Limits on the $U-\gamma$ mixing parameters from PHENIX at 90%, 85% and 80% confidence levels.

$\pi^0$-h$^{\pm}$ $\sqrt{\langle p^2_{out} \rangle}$ values from fits to the $\Delta \phi$ correlations.

$\pi^0$ per trigger yields as a function of $p_{out}$.

$\pi^0$ per trigger yields as a function of $p_{out}$.

$\pi^0$ per trigger yields as a function of $p_{out}$.

Direct photon per trigger yields as a function of $p_{out}$.

$\pi^0$ per-trigger yields as a function of $\Delta \phi$.

Direct photon per-trigger yields as a function of $\Delta \phi$.

Gaussian widths from fits to the $p_{out}$ distributions.

Gaussian widths from fits to the $p_{out}$ distributions.

Frame-independent angular decay coefficient $\tilde{\lambda}$ as a function of transverse momentum for the four reference frames and three $p_T$ bins. The numbers in the CS frame for the $p_T$ = 2-3 GeV/$c$ bin are 90% confidence level upper limits.

The per-trigger yields are shown as a function of $\Delta\phi$ in several $p_T^{trig}$ $\otimes$ $p_T^{assoc}$ bins.

The per-trigger yields are shown as a function of $\Delta\phi$ in several $p_T^{trig}$ $\otimes$ $p_T^{assoc}$ bins.

The per-trigger yields are shown as a function of $\Delta\phi$ in several $p_T^{trig}$ $\otimes$ $p_T^{assoc}$ bins.

The per-trigger yields are shown as a function of $\Delta\phi$ in several $p_T^{trig}$ $\otimes$ $p_T^{assoc}$ bins.

The per-trigger yields are shown as a function of $\Delta\phi$ in several $p_T^{trig}$ $\otimes$ $p_T^{assoc}$ bins.

The per-trigger yields are shown as a function of $\Delta\phi$ in several $p_T^{trig}$ $\otimes$ $p_T^{assoc}$ bins.

The per-trigger yields are shown as a function of $\Delta\phi$ in several $p_T^{trig}$ $\otimes$ $p_T^{assoc}$ bins.

The per-trigger yields are shown as a function of $\Delta\phi$ in several $p_T^{trig}$ $\otimes$ $p_T^{assoc}$ bins.

The per-trigger yields are shown as a function of $\Delta\phi$ in several $p_T^{trig}$ $\otimes$ $p_T^{assoc}$ bins.

The per-trigger yields are shown as a function of $\Delta\phi$ in several $p_T^{trig}$ $\otimes$ $p_T^{assoc}$ bins.

The per-trigger yields are shown as a function of $\Delta\phi$ in several $p_T^{trig}$ $\otimes$ $p_T^{assoc}$ bins.

The $p_{out}$ distributions are shown for dihadron and direct photon-hadron correlations, binned in $p^{trig}_T$ in $x_E$.

The $p_{out}$ distributions are shown for dihadron and direct photon-hadron correlations, binned in $p^{trig}_T$ in $x_E$.

The $p_{out}$ distributions are shown for dihadron and direct photon-hadron correlations, binned in $p^{trig}_T$ in $x_E$.

The $p_{out}$ distributions are shown for dihadron and direct photon-hadron correlations, binned in $p^{trig}_T$ in $x_E$.

The $p_{out}$ distributions are shown for dihadron and direct photon-hadron correlations, binned in $p^{trig}_T$ in $x_E$.

The $p_{out}$ distributions are shown for dihadron and direct photon-hadron correlations, binned in $p^{trig}_T$ in $x_E$.

The $p_{out}$ distributions are shown for dihadron and direct photon-hadron correlations, binned in $p^{trig}_T$ in $x_E$.

The $p_{out}$ distributions are shown for dihadron and direct photon-hadron correlations, binned in $p^{trig}_T$ in $x_E$.

The $p_{out}$ distributions are shown for dihadron and direct photon-hadron correlations, binned in $p^{trig}_T$ in $x_E$.

The nonperturbative away-side jet widths as a function of $p^{trig}_T$ at $\sqrt{s}$ = 200 GeV for both direct photon-hadron and dihadron correlations.

The nonperturbative away-side jet widths as a function of $p^{trig}_T$ at $\sqrt{s}$ = 200 GeV for both direct photon-hadron and dihadron correlations.

The $p_{out}$ distributions are shown in several bins of $x_E$, integrated over a range of $p_T^{trig}$.

The $p_{out}$ distributions are shown in several bins of $x_E$, integrated over a range of $p_T^{trig}$.

The $p_{out}$ distributions are shown in several bins of $x_E$, integrated over a range of $p_T^{trig}$.

The $p_{out}$ distributions are shown in several bins of $x_E$, integrated over a range of $p_T^{trig}$.

The $p_{out}$ distributions are shown in several bins of $x_E$, integrated over a range of $p_T^{trig}$.

The $p_{out}$ distributions are shown in several bins of $x_E$, integrated over a range of $p_T^{trig}$.

The $p_{out}$ distributions are shown in several bins of $x_E$, integrated over a range of $p_T^{trig}$.

The $p_{out}$ distributions are shown in several bins of $x_E$, integrated over a range of $p_T^{trig}$.

The Gaussian widths of $p_{out}$ as a function of $x_E$ are shown for both $\pi^0$ and direct photon triggered correlations.

The nonperturbative Gaussian widths are shown as a function of $x_E$ for $\sqrt{s}$ = 510 GeV. The points for $\sqrt{s}$ = 200 GeV are given in figure 8 and its associated table.

The nonperturbative Gaussian widths are shown as a function of $x_E$ for $\sqrt{s}$ = 510 GeV. The points for $\sqrt{s}$ = 200 GeV are given in figure 8 and its associated table.

Ratio of the electron data to the calculated background as a function of $p_T$ in minimum bias collisions (upper panel) and relative contributions to the background from various sources (lower panel). The curves for $\omega$ and $\phi$ show the sum of the Dalitz and the di-electron decay modes.

The background-subtracted electron spectra for central (0-10%) collisions compared with the expected contributions from open charm decays. Also shown, for central collisions only, are the expected contribution from bottom decays (dashed) and the conversion electron spectrum from a direct phonon prediction (dotted).

The background-subtracted electron spectra for minimum bias (0-92%) collisions compared with the expected contributions from open charm decays. Also shown, for central collisions only, are the expected contribution from bottom decays (dashed) and the conversion electron spectrum from a direct phonon prediction (dotted).

Single electron cross sections $\frac{d\sigma_e}{dy}|_{y=0}$ of this measurement and ISR experiments [9,11,31] are displayed (bottom of figure, right-hand scale) with charm decay contributions calculated with PYTHIA. Open and filled symbols for 1.0 < $p_T$ < 1.4 GeV/$c$ and $p_T$ > 1.4 GeV/$c$, respectively. The derived charm cross section of this measurement is compared with charm cross sections from SPS/FNAL experiments (top of figure, left-hand scale). The thick curve and the shaded band represent the charm cross section in the PYTHIA model and in a NLO pQCD calculation [30], respectively.

Single electron cross sections $\frac{d\sigma_e}{dy}|_{y=0}$ of this measurement and ISR experiments [9,11,31] are displayed (bottom of figure, right-hand scale) with charm decay contributions calculated with PYTHIA. Open and filled symbols for 1.0 < $p_T$ < 1.4 GeV/$c$ and $p_T$ > 1.4 GeV/$c$, respectively. The derived charm cross section of this measurement is compared with charm cross sections from SPS/FNAL experiments (top of figure, left-hand scale). The thick curve and the shaded band represent the charm cross section in the PYTHIA model and in a NLO pQCD calculation [30], respectively.

Invariant cross section of heavy-flavor electrons in $p$$+$$p$ collisions at $\sqrt{s_{_{NN}}}$ = 62.4 GeV. Candidate (inclusive), photonic, and heavy-flavor electron $v_{2}$ in Au+Au collisions at $\sqrt{s_{NN}}$ = 62.4 GeV for 20%-40% centrality. Fit parameters to p+p data in Fig 13.

Integrated invariant yield per binary collision vs $N_{coll}$ for heavy-flavor electrons in Au$+$Au collisions at $\sqrt{s_{_{NN}}}$ = 62.4 GeV for the indicated $p_{T}^{e}$ ranges. The data point at $N_{coll}$ =1 is for $p$$+$$p$ collisions.

Integrated invariant yield per binary collision vs $N_{coll}$ for heavy-flavor electrons in Au$+$Au collisions at $\sqrt{s_{_{NN}}}$ = 62.4 GeV for the indicated $p_{T}^{e}$ ranges. The data point at $N_{coll}$ =1 is for $p$$+$$p$ collisions.

The $R_{AA}$ for electrons from heavy-flavor decays in Au+Au collisions at $\sqrt{s_{NN}}$ = 62.4 GeV for the indicated centralities. The error bars (boxes) represent the statistical (systematic) uncertainties. The global uncertainty due to the uncertainty in Ncoll for each centrality is given by the box on the right side of each plot.

The $R_{AA}$ for electrons from heavy-flavor decays in Au+Au collisions at $\sqrt{s_{NN}}$ = 62.4 GeV for the indicated centralities. The error bars (boxes) represent the statistical (systematic) uncertainties. The global uncertainty due to the uncertainty in Ncoll for each centrality is given by the box on the right side of each plot.

The $R_{AA}$ for electrons from heavy-flavor decays in Au+Au collisions at $\sqrt{s_{NN}}$ = 62.4 GeV for the indicated centralities. The error bars (boxes) represent the statistical (systematic) uncertainties. The global uncertainty due to the uncertainty in Ncoll for each centrality is given by the box on the right side of each plot.

The $R_{AA}$ for electrons from heavy-flavor decays in Au+Au collisions at $\sqrt{s_{NN}}$ = 62.4 GeV for the indicated centralities. The error bars (boxes) represent the statistical (systematic) uncertainties. The global uncertainty due to the uncertainty in Ncoll for each centrality is given by the box on the right side of each plot.

The $R_{AA}$ values for electrons from heavy-flavor decay in Au+Au collisions at 62.4 GeV with the $R_{AA}$ results from $d$+Au, Cu+Cu, and Au+Au collisions at $\sqrt{s_{NN}}$ = 200 GeV (data from [9, 21]). The error bars (boxes) represent the statistical (systematic) uncertainties. The $p_T$ ranges are as indicated: (a) 1 < $p_T$ < 3 GeV/c and (b) 3 < $p_T$ < 5 GeV/$c$.

The $R_{AA}$ values for electrons from heavy-flavor decay in Au+Au collisions at 62.4 GeV with the $R_{AA}$ results from $d$+Au, Cu+Cu, and Au+Au collisions at $\sqrt{s_{NN}}$ = 200 GeV (data from [9, 21]). The error bars (boxes) represent the statistical (systematic) uncertainties. The $p_T$ ranges are as indicated: (a) 1 < $p_T$ < 3 GeV/c and (b) 3 < $p_T$ < 5 GeV/$c$.

Heavy-flavor electron RCP between centrality 0\%–20\% and 40\%–60\% in Au$+$Au collisions at $\sqrt{s_{_{NN}}}$ = 62.4 GeV. The error bars (boxes) show the statistical (systematic) uncertainties.

Candidate (inclusive), photonic, and heavy-flavor electron $v_{2}$ in Au+Au collisions at $\sqrt{s_{NN}}$ = 62.4 GeV for 20%-40% centrality.

Direct photon $p_T$ spectra in different centrality bins.

Direct photon $p_T$ spectra after subtraction of the $N_{coll}$ scaled $p$+$p$ contribution in different centrality bins.

Integrated thermal photon yields as a function of $N_{part}$ for different lower $p_T$ integration limits.

Charge-combined, invariant cross section of muons from open heavy-flavor decays as a function of $p_T$ in $p$+$p$ collisions at $\sqrt{s}$ = 200 GeV at forward rapidity.

Global variables for Pb+Pb collisions at the LHC from ALICE.

$p^{pp}_T$ dependence of $S_{loss}$ for $\pi^0$ in 200 GeV Au+Au collisions from 2007 data from the PHENIX experiment at RHIC.

$p^{pp}_T$ dependence of $S_{loss}$ for $\pi^0$ in 200 GeV Au+Au collisions from 2004 data from the PHENIX experiment at RHIC for $p_T$ <10 GeV/$c$.

$p^{pp}_T$ dependence of $S_{loss}$ for $\pi^0$ in 200 GeV Cu+Cu collisions using the spectra measured by PHENIX at RHIC in 2005.

$p^{pp}_T$ dependence of $S_{loss}$ for $\pi^0$ in 62 GeV Au+Au collisions using the spectra measured by PHENIX in 2010.

$p^{pp}_T$ dependence of $S_{loss}$ for $\pi^0$ in 62.4 GeV Cu+Cu collisions using the spectra measured by PHENIX in 2005.

$p^{pp}_T$ dependence of $S_{loss}$ for $\pi^0$ in 2.76 TeV Pb+Pb collisions using the result from the ALICE experiment.

Parameters from fitting the indicated power-law functions for $\delta p_T/p_T$ to the data as a function of $p^{pp}_T$ for Au+Au collisions from 2004 data at $\sqrt{s_{NN}}$ = 200 GeV.

Parameters from fitting the indicated power-law functions for $\delta p_T/p_T$ to the data as a function of $p^{pp}_T$ for Au+Au collisions from 2007 data at $\sqrt{s_{NN}}$ = 200 GeV.

Parameters from fitting the indicated power-law functions for $\delta p_T/p_T$ to the data as a function of $p^{pp}_T$ for Cu+Cu collisions from 2005 data at $\sqrt{s_{NN}}$ = 200 GeV.

Parameters from fitting the indicated power-law functions for $\delta p_T/p_T$ to the data as a function of $p^{pp}_T$ for Pb+Pb collisions at $\sqrt{s_{NN}}$ = 2.76 TeV.

The nuclear modification factor $R_{CuAu}$ as a function of the number of participating nucleons for 1.2 < $|y|$ < 2.2 and 1 < $p_T$ < 5 GeV/$c$. Type A represents uncertainties that are uncorrelated from point to point, Type B represents uncertainties that are correlated from point to point, and Type C represents uncertainties in the overall normalization.

The nuclear modification factor $R_{CuAu}$ as a function of the number of participating nucleons for 1.2 < $|y|$ < 2.2 and 1 < $p_T$ < 5 GeV/$c$. Type A represents uncertainties that are uncorrelated from point to point, Type B represents uncertainties that are correlated from point to point, and Type C represents uncertainties in the overall normalization.

The nuclear modification factor $R_{CuAu}$ as a function of rapidity for 1 < $p_T$ < 5 GeV/$c$ and 0%– 93% centrality. Type A represents uncertainties that are uncorrelated from point to point, Type B represents uncertainties that are correlated from point to point, and Type C represents uncertainties in the overall normalization.

The forward/backward ratio as a function of the number of participating nucleons for 1 < $p_T$ < 5 GeV/$c$ and 1.2 < $|y|$ < 2.2. Type A represents uncertainties that are uncorrelated from point to point and Type B represents uncertainties that are correlated from point to point. For the B sys. error for centrality 0-20% forward/backward ratio 0.20, the value is $\pm$ < 0.10.

Backward [$x_F$ < 0] $A^{J/\psi}_N$ vs high $p_T$ for $p$+$p$, $p$+Al, and $p$+Au collisions.

$A^{J/\psi}_N$ vs $x_F$ for $p$+$p$, $p$+Al, and $p$+Au collisions.

$A^{J/\psi}_N$ vs $x_F$ for $p$+$p$, $p$+Al, and $p$+Au collisions.

$A^{J/\psi}_N$ vs $x_F$ for $p$+$p$, $p$+Al, and $p$+Au collisions.

$A^{J/\psi}_N$ vs $x_F$ for $p$+$p$, $p$+Al, and $p$+Au collisions.

$v_2$ vs Fixed $p_T$ for several centrality selections. [F] and [A] follow the notation Fig. 2. Systematic errors are estimated to be $\sim 5$%.

$v_2$ vs Assorted $p_T$ for several centrality selections. [F] and [A] follow the notation Fig. 2. Systematic errors are estimated to be $\sim 5$%.

$v_2$ vs Assorted $p_T$ for several centrality selections. [F] and [A] follow the notation Fig. 2. Systematic errors are estimated to be $\sim 5$%.

The centrality dependence of $A_2$ for two different $p_T$ selections. [F] and [A] follow the notation in Fig. 2. Systematic errors are estimated to be $\sim 10$%, dominated by the normalization of the correction function and the model determination of$ \varepsilon$.

The centrality dependence of $A_2$ for two different $p_T$ selections. [F] and [A] follow the notation in Fig. 2. Systematic errors are estimated to be $\sim 10$%, dominated by the normalization of the correction function and the model determination of$ \varepsilon$.

$R_{dAu}$ as a function of rapidity of $\phi$ meson summed over the $p_T$ range, 1 < $p_T$ < 7 GeV/$c$ for 0%–100% centrality. Type B represents uncertainties that are correlated from point to point.

$R_{dAu}$ vs $N_{coll}$ of $\phi$ meson at 1 < $p_T$ < 7 GeV/$c$. Type B represents uncertainties that are correlated from point to point, and Type C represents uncertainties in the overall normalization.

$R_{dAu}$ and $p_T$ at different $d$+Au centrality classes. Type B represents uncertainties that are correlated from point to point.

$R_{dAu}$ and $p_T$ at different $d$+Au centrality classes. Type B represents uncertainties that are correlated from point to point.

$R_{dAu}$ and $p_T$ at different $d$+Au centrality classes. Type B represents uncertainties that are correlated from point to point.