Exclusion limits at 95% CL for direct gluino pair production, where the gluinos decay to light-flavor quarks and a $\tilde{\chi}_1^\pm$ that decays to $W^\pm\tilde{\chi}_1^0$. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$, assuming unity branching fraction to $q_i\bar{q}_j W\pm\tilde{\chi}_1^0$.

Exclusion limits at 95% CL for direct gluino pair production, where the gluinos decay to bottom quarks ($\tilde{g}\to b\bar{b}\tilde{\chi}_1^0$). Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$, assuming unity branching fraction for the given decay.

Exclusion limits at 95% CL for direct gluino pair production, where the gluinos decay to top quarks ($\tilde{g}\to t\bar{t}\tilde{\chi}_1^0$). Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$, assuming unity branching fraction for the given decay.

Exclusion limits at 95% CL for light-flavor squark pair production, where the squarks decay to $q\tilde{\chi}_1^0$. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$, assuming unity branching fraction for the given decay and 1-fold degeneracy in the light-flavor squarks (corresponding to the inner set of curves in the limit plot). To get the theory cross section for other N-fold degeneracy assumptions (e.g. 8-fold for the outer curves in the limit plot), just multiply by N.

Exclusion limits at 95% CL for bottom squark pair production, where the squarks decay to $b\tilde{\chi}_1^0$. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$, assuming unity branching fraction for the given decay.

Exclusion limits at 95% CL for top squark pair production, where the squarks decay to $t\tilde{\chi}_1^0$. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$, assuming unity branching fraction for the given decay.

Exclusion limits at 95% CL for top squark pair production, where the squarks decay to $b\tilde{\chi}_1^\pm$ and the $\tilde{\chi}_1^0$ decay to $W^\pm\tilde{\chi}_1^0$. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$, assuming unity branching fraction for the given decay.

Exclusion limits at 95% CL for top squark pair production, where the squarks decay either to $b\tilde{\chi}_1^\pm\to bW^\pm\tilde{\chi}_1^0$ or to $t\tilde{\chi}_1^0$. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$, assuming unity branching fraction for the given decay.

Exclusion limits at 95% CL for top squark pair production, where the squarks decay to $c\tilde{\chi}_1^0$. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$, assuming unity branching fraction for the given decay.

Exclusion limits at 95% CL for the mono-$\phi$ model, in which a resonantly-produced colored scalar decays to a massive Dirac fermion and a quark. Signal cross sections are calculated at leading order in $\alpha_S$, assuming unity branching fraction for the given decay.

Cross section limits for $\mathrm{LQ}\to\mathrm{q}\nu$, where $q=u,\,d,\,s,\,\mathrm{or}\,c$. Limits are at the 95% confidence level. Theory cross sections are LO for vector LQ, and NLO for scalar LQ. Branching ratio is assumed to be 100% to $\mathrm{q}\nu$.

Cross section limits for $\mathrm{LQ}\to\mathrm{b}\nu$. Limits are at the 95% confidence level. Theory cross sections are LO for vector LQ, and NLO for scalar LQ. Branching ratio is assumed to be 100% to $\mathrm{b}\nu$.

Cross section limits for $\mathrm{LQ}\to\mathrm{t}\nu$. Limits are at the 95% confidence level. Theory cross sections are LO for vector LQ, and NLO for scalar LQ. Branching ratios are assumed to be $\mathcal{B}(\mathrm{LQ}\to\mathrm{t}\nu)=1-\beta$, and $\mathcal{B}(\mathrm{LQ}\to\mathrm{b}\tau)=\beta$.

Predictions and observations for monojet signal regions

Predictions and observations for signal regions with $250 \leq H_\mathrm{T} < 450$ GeV

Predictions and observations for signal regions with $450 \leq H_\mathrm{T} < 575$ GeV and $N_\mathrm{j}<7$

Predictions and observations for signal regions with $450 \leq H_\mathrm{T} < 575$ GeV and $N_\mathrm{j}\geq7$

Predictions and observations for signal regions with $575 \leq H_\mathrm{T} < 1200$ GeV and $N_\mathrm{j}^\mathrm{hi}<4$

Predictions and observations for signal regions with $575 \leq H_\mathrm{T} < 1200$ GeV and $4\leq N_\mathrm{j}^\mathrm{hi}<7$

Predictions and observations for signal regions with $575 \leq H_\mathrm{T} < 1200$ GeV and $N_\mathrm{j}\geq7$

Predictions and observations for signal regions with $1200 \leq H_\mathrm{T} < 1500$ GeV and $N_\mathrm{j}^\mathrm{hi}<4$

Predictions and observations for signal regions with $1200 \leq H_\mathrm{T} < 1500$ GeV and $4\leq N_\mathrm{j}^\mathrm{hi}<7$

Predictions and observations for signal regions with $1200 \leq H_\mathrm{T} < 1500$ GeV and $N_\mathrm{j}\geq7$

Predictions and observations for signal regions with $H_\mathrm{T} \geq 1500$ GeV and $N_\mathrm{j}<7$

Predictions and observations for signal regions with $H_\mathrm{T} \geq 1500$ GeV and $N_\mathrm{j}\geq7$

Covariance matrix for the 282 signal regions of the inclusive $M_\mathrm{T2}$ search

Correlation matrix for the 282 signal regions of the inclusive $M_\mathrm{T2}$ search

Bin number definitions for the $M_\mathrm{T2}$ covariance and correlation matrices

Exclusion limits at 95% CL for direct gluino pair production, where the gluinos decay to light-flavor quarks and either the lightest neutralino, or the lightest chargino, and the chargino is long-lived with $c\tau_0 = 10$ cm and mass O(100) MeV greater than the neutralino's mass. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$.

Exclusion limits at 95% CL for direct gluino pair production, where the gluinos decay to light-flavor quarks and either the lightest neutralino, or the lightest chargino, and the chargino is long-lived with $c\tau_0 = 50$ cm and mass O(100) MeV greater than the neutralino's mass. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$.

Exclusion limits at 95% CL for direct gluino pair production, where the gluinos decay to light-flavor quarks and either the lightest neutralino, or the lightest chargino, and the chargino is long-lived with $c\tau_0 = 200$ cm and mass O(100) MeV greater than the neutralino's mass. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$.

Exclusion limits at 95% CL for direct light squark pair production, where the squarks decay to light-flavor quarks and either the lightest neutralino, or the lightest chargino, and the chargino is long-lived with $c\tau_0 = 10$ cm and mass O(100) MeV greater than the neutralino's mass. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$, for a single light squark.

Exclusion limits at 95% CL for direct light squark pair production, where the squarks decay to light-flavor quarks and either the lightest neutralino, or the lightest chargino, and the chargino is long-lived with $c\tau_0 = 50$ cm and mass O(100) MeV greater than the neutralino's mass. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$, for a single light squark.

Exclusion limits at 95% CL for direct light squark pair production, where the squarks decay to light-flavor quarks and either the lightest neutralino, or the lightest chargino, and the chargino is long-lived with $c\tau_0 = 200$ cm and mass O(100) MeV greater than the neutralino's mass. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$, for a single light squark.

Exclusion limits at 95% CL for direct stop pair production, where the stops decay to either a top and the lightest neutralino, or a bottom and the lightest chargino, and the chargino is long-lived with $c\tau_0 = 10$ cm and mass O(100) MeV greater than the neutralino's mass. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$.

Exclusion limits at 95% CL for direct stop pair production, where the stops decay to either a top and the lightest neutralino, or a bottom and the lightest chargino, and the chargino is long-lived with $c\tau_0 = 50$ cm and mass O(100) MeV greater than the neutralino's mass. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$.

Exclusion limits at 95% CL for direct stop pair production, where the stops decay to either a top and the lightest neutralino, or a bottom and the lightest chargino, and the chargino is long-lived with $c\tau_0 = 200$ cm and mass O(100) MeV greater than the neutralino's mass. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$.

The maximum chargino mass excluded at 95% CL for direct gluino pair production, where the gluinos decay to light-flavor quarks and either the lightest neutralino, or the lightest chargino, and the chargino mass is O(100) MeV greater than the neutralino's mass. The chargino's lifetime is varied from $c\tau_{0} = 1$ to 2000 cm while the gluino mass is fixed to 1900 GeV. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$. If all kinematically allowed chargino masses are excluded, the curves, including 68 and 95% expected, tend to overlap. At short decay lengths, horizontal exclusion lines are obtained from the inclusive analysis, as this is not affected by track reconstruction inefficiencies, which may arise when the chargino decays before the CMS tracker, and therefore shows better sensitivity to scenarios with very small lifetime compared to the disappearing track search, based on median expected limits.

The maximum chargino mass excluded at 95% CL for direct squark pair production, where the squarks decay to light-flavor quarks and either the lightest neutralino, or the lightest chargino, and the chargino mass is O(100) MeV greater than the neutralino's mass. The chargino's lifetime is varied from $c\tau_{0} = 1$ to 2000 cm while the squark mass is fixed to 900 GeV. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$, for a single light squark. If all kinematically allowed chargino masses are excluded, the curves, including 68 and 95% expected, tend to overlap. At short decay lengths, horizontal exclusion lines are obtained from the inclusive analysis, as this is not affected by track reconstruction inefficiencies, which may arise when the chargino decays before the CMS tracker, and therefore shows better sensitivity to scenarios with very small lifetime compared to the disappearing track search, based on median expected limits.

The maximum chargino mass excluded at 95% CL for direct squark pair production, where the squarks decay to light-flavor quarks and either the lightest neutralino, or the lightest chargino, and the chargino mass is O(100) MeV greater than the neutralino's mass. The chargino's lifetime is varied from $c\tau_{0} = 1$ to 2000 cm while the squark mass is fixed to 1500 GeV. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$, and the eight light squarks' masses are assumed to be degenerate. If all kinematically allowed chargino masses are excluded, the curves, including 68 and 95% expected, tend to overlap. At short decay lengths, horizontal exclusion lines are obtained from the inclusive analysis, as this is not affected by track reconstruction inefficiencies, which may arise when the chargino decays before the CMS tracker, and therefore shows better sensitivity to scenarios with very small lifetime compared to the disappearing track search, based on median expected limits.

Exclusion limits at 95% CL for direct stop pair production, where the stops decay to either a top and the lightest neutralino, or a bottom and the lightest chargino, and the chargino mass is O(100) MeV greater than the neutralino's mass. The chargino's lifetime is varied from $c\tau_{0} = 1$ to 2000 cm while the stop mass is fixed to 1000 GeV. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$. If all kinematically allowed chargino masses are excluded, the curves, including 68 and 95% expected, tend to overlap. At short decay lengths, horizontal exclusion lines are obtained from the inclusive analysis, as this is not affected by track reconstruction inefficiencies, which may arise when the chargino decays before the CMS tracker, and therefore shows better sensitivity to scenarios with very small lifetime compared to the disappearing track search, based on median expected limits.

Exclusion limits at 95% CL for direct gluino pair production, where the gluinos decay to light-flavor quarks and either the lightest neutralino, or the lightest chargino, and the chargino mass is O(100) MeV greater than the neutralino's mass. The chargino's lifetime is varied from $c\tau_{0} = 5$ to 1000 cm while the gluino mass is fixed to 1600 GeV and the neutralino's mass is fixed to 1575 GeV. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$.

Exclusion limits at 95% CL for direct squark pair production, where the squarks decay to light-flavor quarks and either the lightest neutralino, or the lightest chargino, and the chargino mass is O(100) MeV greater than the neutralino's mass. The chargino's lifetime is varied from $c\tau_{0} = 5$ to 1000 cm while the squark mass is fixed to 2000 GeV and the neutralino's mass is fixed to 1000 GeV. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$, and the eight light squarks' masses are assumed to be degenerate.

Exclusion limits at 95% CL for direct stop pair production, where the stops decay to either a top and the lightest neutralino, or a bottom and the lightest chargino, and the chargino mass is O(100) MeV greater than the neutralino's mass. The chargino's lifetime is varied from $c\tau_{0} = 5$ to 1000 cm while the stop mass is fixed to 1100 GeV and the neutralino's mass is fixed to 1000 GeV. Signal cross sections are calculated at approximately NNLO+NNLL order in $\alpha_S$.

Predictions and observations for 2016 disappearing track signal regions

Predictions and observations for 2017-2018 pixel track signal regions

Predictions and observations for 2017-2018 medium (M) and long (L) length track signal regions

Covariance matrix for the 68 signal regions of the disappearing tracks $M_\mathrm{T2}$ search

Correlation matrix for the 68 signal regions of the disappearing tracks $M_\mathrm{T2}$ search

The inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ measured in $0.5 < |y| < 1.0$ for jets clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.4$.

The inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ measured in $1.0 < |y| < 1.5$ for jets clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.4$.

The inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ measured in $1.0 < |y| < 1.5$ for jets clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.4$.

The inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ measured in $1.5 < |y| < 2.0$ for jets clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.4$.

The inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ measured in $1.5 < |y| < 2.0$ for jets clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.4$.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $|y| < 0.5$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.4$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $|y| < 0.5$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.4$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $|y| < 0.5$and $0.5 < |y| < 1.0$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.4$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $|y| < 0.5$and $0.5 < |y| < 1.0$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.4$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $|y| < 0.5$and $1.0 < |y| < 1.5$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.4$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $|y| < 0.5$and $1.0 < |y| < 1.5$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.4$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $|y| < 0.5$and $1.5 < |y| < 2.0$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.4$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $|y| < 0.5$and $1.5 < |y| < 2.0$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.4$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $0.5 < |y| < 1.0$and $|y| < 0.5$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.4$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $0.5 < |y| < 1.0$and $|y| < 0.5$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.4$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $0.5 < |y| < 1.0$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.4$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $0.5 < |y| < 1.0$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.4$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $0.5 < |y| < 1.0$and $1.0 < |y| < 1.5$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.4$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $0.5 < |y| < 1.0$and $1.0 < |y| < 1.5$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.4$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $0.5 < |y| < 1.0$and $1.5 < |y| < 2.0$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.4$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $0.5 < |y| < 1.0$and $1.5 < |y| < 2.0$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.4$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $1.0 < |y| < 1.5$and $|y| < 0.5$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.4$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $1.0 < |y| < 1.5$and $|y| < 0.5$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.4$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $1.0 < |y| < 1.5$and $0.5 < |y| < 1.0$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.4$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $1.0 < |y| < 1.5$and $0.5 < |y| < 1.0$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.4$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $1.0 < |y| < 1.5$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.4$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $1.0 < |y| < 1.5$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.4$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $1.0 < |y| < 1.5$and $1.5 < |y| < 2.0$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.4$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $1.0 < |y| < 1.5$and $1.5 < |y| < 2.0$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.4$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $1.5 < |y| < 2.0$and $|y| < 0.5$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.4$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $1.5 < |y| < 2.0$and $|y| < 0.5$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.4$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $1.5 < |y| < 2.0$and $0.5 < |y| < 1.0$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.4$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $1.5 < |y| < 2.0$and $0.5 < |y| < 1.0$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.4$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $1.5 < |y| < 2.0$and $1.0 < |y| < 1.5$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.4$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $1.5 < |y| < 2.0$and $1.0 < |y| < 1.5$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.4$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $1.5 < |y| < 2.0$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.4$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $1.5 < |y| < 2.0$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.4$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ measured in $|y| < 0.5$ for jets clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.7$.

The inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ measured in $|y| < 0.5$ for jets clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.7$.

The inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ measured in $0.5 < |y| < 1.0$ for jets clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.7$.

The inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ measured in $0.5 < |y| < 1.0$ for jets clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.7$.

The inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ measured in $1.0 < |y| < 1.5$ for jets clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.7$.

The inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ measured in $1.0 < |y| < 1.5$ for jets clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.7$.

The inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ measured in $1.5 < |y| < 2.0$ for jets clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.7$.

The inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ measured in $1.5 < |y| < 2.0$ for jets clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.7$.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $|y| < 0.5$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.7$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $|y| < 0.5$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.7$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $|y| < 0.5$and $0.5 < |y| < 1.0$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.7$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $|y| < 0.5$and $0.5 < |y| < 1.0$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.7$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $|y| < 0.5$and $1.0 < |y| < 1.5$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.7$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $|y| < 0.5$and $1.0 < |y| < 1.5$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.7$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $|y| < 0.5$and $1.5 < |y| < 2.0$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.7$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $|y| < 0.5$and $1.5 < |y| < 2.0$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.7$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $0.5 < |y| < 1.0$and $|y| < 0.5$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.7$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $0.5 < |y| < 1.0$and $|y| < 0.5$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.7$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $0.5 < |y| < 1.0$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.7$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $0.5 < |y| < 1.0$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.7$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $0.5 < |y| < 1.0$and $1.0 < |y| < 1.5$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.7$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $0.5 < |y| < 1.0$and $1.0 < |y| < 1.5$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.7$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $0.5 < |y| < 1.0$and $1.5 < |y| < 2.0$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.7$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $0.5 < |y| < 1.0$and $1.5 < |y| < 2.0$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.7$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $1.0 < |y| < 1.5$and $|y| < 0.5$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.7$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $1.0 < |y| < 1.5$and $|y| < 0.5$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.7$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $1.0 < |y| < 1.5$and $0.5 < |y| < 1.0$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.7$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $1.0 < |y| < 1.5$and $0.5 < |y| < 1.0$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.7$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $1.0 < |y| < 1.5$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.7$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $1.0 < |y| < 1.5$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.7$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $1.0 < |y| < 1.5$and $1.5 < |y| < 2.0$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.7$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $1.0 < |y| < 1.5$and $1.5 < |y| < 2.0$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.7$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $1.5 < |y| < 2.0$and $|y| < 0.5$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.7$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $1.5 < |y| < 2.0$and $|y| < 0.5$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.7$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $1.5 < |y| < 2.0$and $0.5 < |y| < 1.0$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.7$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $1.5 < |y| < 2.0$and $0.5 < |y| < 1.0$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.7$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $1.5 < |y| < 2.0$and $1.0 < |y| < 1.5$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.7$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $1.5 < |y| < 2.0$and $1.0 < |y| < 1.5$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.7$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $1.5 < |y| < 2.0$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.7$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The correlation matrix at the particle level of inclusive jet production cross section as a function of the jet transverse momentum~$p_\mathrm{T}$ for jets in $1.5 < |y| < 2.0$ clustered using the anti-$k_\mathrm{t}$ algorithm with $R=0.7$. It contains contributions from the data and from the \textsc{PYTHIA}~8 sample used to perform the unfolding.

The corrections were calculated by Dittmaier, Huss, Speckner.

The corrections were calculated by Dittmaier, Huss, Speckner.

The corrections were calculated by Dittmaier, Huss, Speckner.

The corrections were calculated by Dittmaier, Huss, Speckner.

The corrections were calculated by Dittmaier, Huss, Speckner.

The corrections were calculated by Dittmaier, Huss, Speckner.

The corrections were calculated by Dittmaier, Huss, Speckner.

The corrections were calculated by Dittmaier, Huss, Speckner.

The corrections were calculated by Dittmaier, Huss, Speckner.

The corrections were calculated by Dittmaier, Huss, Speckner.

The corrections were calculated by Dittmaier, Huss, Speckner.

The corrections were calculated by Dittmaier, Huss, Speckner.

The corrections were calculated by Dittmaier, Huss, Speckner.

The corrections were calculated by Dittmaier, Huss, Speckner.

The corrections were calculated by Dittmaier, Huss, Speckner.

The corrections were calculated by Dittmaier, Huss, Speckner.

The values correspond to the average of the corrections obtained with \textsc{{PYTHIA}}~8 and with \textsc{{HERWIG}}++.

The values correspond to the average of the corrections obtained with \textsc{{PYTHIA}}~8 and with \textsc{{HERWIG}}++.

The values correspond to the average of the corrections obtained with \textsc{{PYTHIA}}~8 and with \textsc{{HERWIG}}++.

The values correspond to the average of the corrections obtained with \textsc{{PYTHIA}}~8 and with \textsc{{HERWIG}}++.

The values correspond to the average of the corrections obtained with \textsc{{PYTHIA}}~8 and with \textsc{{HERWIG}}++.

The values correspond to the average of the corrections obtained with \textsc{{PYTHIA}}~8 and with \textsc{{HERWIG}}++.

The values correspond to the average of the corrections obtained with \textsc{{PYTHIA}}~8 and with \textsc{{HERWIG}}++.

The values correspond to the average of the corrections obtained with \textsc{{PYTHIA}}~8 and with \textsc{{HERWIG}}++.

The values correspond to the average of the corrections obtained with \textsc{{PYTHIA}}~8 and with \textsc{{HERWIG}}++.

The values correspond to the average of the corrections obtained with \textsc{{PYTHIA}}~8 and with \textsc{{HERWIG}}++.

The values correspond to the average of the corrections obtained with \textsc{{PYTHIA}}~8 and with \textsc{{HERWIG}}++.

The values correspond to the average of the corrections obtained with \textsc{{PYTHIA}}~8 and with \textsc{{HERWIG}}++.

The values correspond to the average of the corrections obtained with \textsc{{PYTHIA}}~8 and with \textsc{{HERWIG}}++.

The values correspond to the average of the corrections obtained with \textsc{{PYTHIA}}~8 and with \textsc{{HERWIG}}++.

The values correspond to the average of the corrections obtained with \textsc{{PYTHIA}}~8 and with \textsc{{HERWIG}}++.

The values correspond to the average of the corrections obtained with \textsc{{PYTHIA}}~8 and with \textsc{{HERWIG}}++.

Efficiency corrected pT spectra for the different centrality bins and for the various particles. Note that 7 centrality bins have been used for the KS0 and the Λ while only 6 and 3 have been used for the Ξ and Ω, respectively. Errors are statistical only. The Λ spectra are corrected for the feed-down of the Ξ decay.

Efficiency corrected pT spectra for the different centrality bins and for the various particles. Note that 7 centrality bins have been used for the KS0 and the Λ while only 6 and 3 have been used for the Ξ and Ω, respectively. Errors are statistical only. The Λ spectra are corrected for the feed-down of the Ξ decay.

Efficiency corrected pT spectra for the different centrality bins and for the various particles. Note that 7 centrality bins have been used for the KS0 and the Λ while only 6 and 3 have been used for the Ξ and Ω, respectively. Errors are statistical only. The Λ spectra are corrected for the feed-down of the Ξ decay.

Efficiency corrected pT spectra for the different centrality bins and for the various particles. Note that 7 centrality bins have been used for the KS0 and the Λ while only 6 and 3 have been used for the Ξ and Ω, respectively. Errors are statistical only. The Λ spectra are corrected for the feed-down of the Ξ decay.

Efficiency corrected pT spectra for the different centrality bins and for the various particles. Note that 7 centrality bins have been used for the KS0 and the Λ while only 6 and 3 have been used for the Ξ and Ω, respectively. Errors are statistical only. The Λ spectra are corrected for the feed-down of the Ξ decay.

Efficiency corrected pT spectra for the different centrality bins and for the various particles. Note that 7 centrality bins have been used for the KS0 and the Λ while only 6 and 3 have been used for the Ξ and Ω, respectively. Errors are statistical only. The Λ spectra are corrected for the feed-down of the Ξ decay.

Efficiency corrected pT spectra for the different centrality bins and for the various particles. Note that 7 centrality bins have been used for the KS0 and the Λ while only 6 and 3 have been used for the Ξ and Ω, respectively. Errors are statistical only. The Λ spectra are corrected for the feed-down of the Ξ decay.

Efficiency corrected pT spectra for the different centrality bins and for the various particles. Note that 7 centrality bins have been used for the KS0 and the Λ while only 6 and 3 have been used for the Ξ and Ω, respectively. Errors are statistical only. The Λ spectra are corrected for the feed-down of the Ξ decay.

Efficiency corrected pT spectra for the different centrality bins and for the various particles. Note that 7 centrality bins have been used for the KS0 and the Λ while only 6 and 3 have been used for the Ξ and Ω, respectively. Errors are statistical only. The Λ spectra are corrected for the feed-down of the Ξ decay.

Efficiency corrected pT spectra for the different centrality bins and for the various particles. Note that 7 centrality bins have been used for the KS0 and the Λ while only 6 and 3 have been used for the Ξ and Ω, respectively. Errors are statistical only. The Λ spectra are corrected for the feed-down of the Ξ decay.

Efficiency corrected pT spectra for the different centrality bins and for the various particles. Note that 7 centrality bins have been used for the KS0 and the Λ while only 6 and 3 have been used for the Ξ and Ω, respectively. Errors are statistical only. The Λ spectra are corrected for the feed-down of the Ξ decay.

Efficiency corrected pT spectra for the different centrality bins and for the various particles. Note that 7 centrality bins have been used for the KS0 and the Λ while only 6 and 3 have been used for the Ξ and Ω, respectively. Errors are statistical only. The Λ spectra are corrected for the feed-down of the Ξ decay.

Efficiency corrected pT spectra for the different centrality bins and for the various particles. Note that 7 centrality bins have been used for the KS0 and the Λ while only 6 and 3 have been used for the Ξ and Ω, respectively. Errors are statistical only. The Λ spectra are corrected for the feed-down of the Ξ decay.

Extrapolated average transverse momenta ⟨pT ⟩ as a function of dNch/dy for different particle species in Au+Au collisions at 62.4 GeV. Statistical uncertainties are represented by the error bars at the points while the systematic uncertainties are represented by the gray bars. The π, charged K and p data were extracted from Ref. [14].

Extrapolated average transverse momenta ⟨pT ⟩ as a function of dNch/dy for different particle species in Au+Au collisions at 62.4 GeV. Statistical uncertainties are represented by the error bars at the points while the systematic uncertainties are represented by the gray bars. The π, charged K and p data were extracted from Ref. [14].

KS0 dN/dpT spectra compared to the charged Kaon spectra for the event centrality of 0-5% and 30-40%. The charged Kaons data points are for rapidity range of |y| < 0.1 and were extracted from Ref. [14].

KS0 dN/dpT spectra compared to the charged Kaon spectra for the event centrality of 0-5% and 30-40%. The charged Kaons data points are for rapidity range of |y| < 0.1 and were extracted from Ref. [14].

KS0 dN/dpT spectra compared to the charged Kaon spectra for the event centrality of 0-5% and 30-40%. The charged Kaons data points are for rapidity range of |y| < 0.1 and were extracted from Ref. [14].

KS0 dN/dpT spectra compared to the charged Kaon spectra for the event centrality of 0-5% and 30-40%. The charged Kaons data points are for rapidity range of |y| < 0.1 and were extracted from Ref. [14].

Strange particle production yields at mid-rapidity in central Au+Au and Pb+Pb collisions versus the center of mass energy √sNN. The top panel shows results for K0S and Λ. The AGS values are from E896 [1] (centrality 0 − 5 %). The SPS values are from NA49 [20] (centrality 0 − 7 %) and the RHIC values are from STAR [4, 15] (centrality 0 − 5 %). For the multi-strange baryons Ξ and Ω (bottom panel), the SPS results are from NA57 [2] (centrality 0 − 11 %) and the RHIC values are from STAR [15, 21] (centrality 0 − 20 %).

Strange particle production yields at mid-rapidity in central Au+Au and Pb+Pb collisions versus the center of mass energy √sNN. The top panel shows results for K0S and Λ. The AGS values are from E896 [1] (centrality 0 − 5 %). The SPS values are from NA49 [20] (centrality 0 − 7 %) and the RHIC values are from STAR [4, 15] (centrality 0 − 5 %). For the multi-strange baryons Ξ and Ω (bottom panel), the SPS results are from NA57 [2] (centrality 0 − 11 %) and the RHIC values are from STAR [15, 21] (centrality 0 − 20 %).

Strange particle production yields at mid-rapidity in central Au+Au and Pb+Pb collisions versus the center of mass energy √sNN. The top panel shows results for K0S and Λ. The AGS values are from E896 [1] (centrality 0 − 5 %). The SPS values are from NA49 [20] (centrality 0 − 7 %) and the RHIC values are from STAR [4, 15] (centrality 0 − 5 %). For the multi-strange baryons Ξ and Ω (bottom panel), the SPS results are from NA57 [2] (centrality 0 − 11 %) and the RHIC values are from STAR [15, 21] (centrality 0 − 20 %).

Strange particle production yields at mid-rapidity in central Au+Au and Pb+Pb collisions versus the center of mass energy √sNN. The top panel shows results for K0S and Λ. The AGS values are from E896 [1] (centrality 0 − 5 %). The SPS values are from NA49 [20] (centrality 0 − 7 %) and the RHIC values are from STAR [4, 15] (centrality 0 − 5 %). For the multi-strange baryons Ξ and Ω (bottom panel), the SPS results are from NA57 [2] (centrality 0 − 11 %) and the RHIC values are from STAR [15, 21] (centrality 0 − 20 %).

Anti-baryon to baryon yield ratios for strange baryons versus the center of mass energy √sNN. Λ/Λ is shown in the top panel while the multi-strange baryons are on the bottom panel. The data from AGS are not corrected for the weak decay feed-down from the multistrange baryons while the data from SPS and RHIC are corrected. The lines are the results of a thermal model calculation (see text section IV A). The AGS values are from E896 [1] (centrality 0 − 5 %). The SPS values are from NA49 [20] (centrality 0 − 7 %) and the RHIC values are from STAR [4, 15] (centrality 0 − 5 %). For the multi- strange baryons Ξ and Ω (bottom panel), the SPS results are from NA57 [2] (centrality 0 − 11 %) and the RHIC values are from STAR [15, 21] (centrality 0 − 20 %).

Anti-baryon to baryon yield ratios for strange baryons versus the center of mass energy √sNN. Λ/Λ is shown in the top panel while the multi-strange baryons are on the bottom panel. The data from AGS are not corrected for the weak decay feed-down from the multistrange baryons while the data from SPS and RHIC are corrected. The lines are the results of a thermal model calculation (see text section IV A). The AGS values are from E896 [1] (centrality 0 − 5 %). The SPS values are from NA49 [20] (centrality 0 − 7 %) and the RHIC values are from STAR [4, 15] (centrality 0 − 5 %). For the multi- strange baryons Ξ and Ω (bottom panel), the SPS results are from NA57 [2] (centrality 0 − 11 %) and the RHIC values are from STAR [15, 21] (centrality 0 − 20 %).

Antibaryon-to-baryon yield ratios for strange particles and protons as a function of dNch/dy at √sNN=62.4 and 200 GeV. The p data were extracted from Ref. [14]. The √sNN=200 GeV strange hadron data were extracted from Ref. [15].

Antibaryon-to-baryon yield ratios for strange particles and protons as a function of dNch/dy at √sNN=62.4 and 200 GeV. The p data were extracted from Ref. [14]. The √sNN=200 GeV strange hadron data were extracted from Ref. [15].

Particle-yield ratios as obtained by measurements (black dots) for the most central (0–5%) Au+Au collisions at 62.4 GeV and statistical model predictions (lines). The ratios indicated by the dashed lines (blue) were obtained by using only π, K, and protons, whereas the ratios indicated by the full lines (green) were obtained by also using the hyperons in the fit.

Particle-yield ratios as obtained by measurements (black dots) for the most central (0–5%) Au+Au collisions at 62.4 GeV and statistical model predictions (lines). The ratios indicated by the dashed lines (blue) were obtained by using only π, K, and protons, whereas the ratios indicated by the full lines (green) were obtained by also using the hyperons in the fit.

Chemical freeze-out temperature Tch (a) and strangeness saturation factor γs (b) as a function of the mean number of participants.

Chemical freeze-out temperature Tch (a) and strangeness saturation factor γs (b) as a function of the mean number of participants.

Chemical freeze-out temperature Tch (a) and strangeness saturation factor γs (b) as a function of the mean number of participants.

Chemical freeze-out temperature Tch (a) and strangeness saturation factor γs (b) as a function of the mean number of participants.

Temperature and baryon chemical potential obtained from thermal model fits as a function of √sNN (see Ref. [22]). The dashed lines correspond to the parametrizations given in Ref. [22]. The solid stars show the result for √sNN=62.4 and 200 GeV.

Temperature and baryon chemical potential obtained from thermal model fits as a function of √sNN (see Ref. [22]). The dashed lines correspond to the parametrizations given in Ref. [22]. The solid stars show the result for √sNN=62.4 and 200 GeV.

Temperature and baryon chemical potential obtained from thermal model fits as a function of √sNN (see Ref. [22]). The dashed lines correspond to the parametrizations given in Ref. [22]. The solid stars show the result for √sNN=62.4 and 200 GeV.

Temperature and baryon chemical potential obtained from thermal model fits as a function of √sNN (see Ref. [22]). The dashed lines correspond to the parametrizations given in Ref. [22]. The solid stars show the result for √sNN=62.4 and 200 GeV.

Ratio of baryon (solid symbols) and antibaryon (open symbols) to π+ as a function of dNch/dy for √sNN=62.4 GeV (left) and √sNN=200 GeV (right). The π and p data were extracted from Ref. [14].

Ratio of baryon (solid symbols) and antibaryon (open symbols) to π- as a function of dNch/dy for √sNN=62.4 GeV (left) and √sNN=200 GeV (right). The π and p data were extracted from Ref. [14].

Ratio of baryon (solid symbols) and antibaryon (open symbols) to π+ as a function of dNch/dy for √sNN=62.4 GeV (left) and √sNN=200 GeV (right). The π and p data were extracted from Ref. [14].

Ratio of baryon (solid symbols) and antibaryon (open symbols) to π- as a function of dNch/dy for √sNN=62.4 GeV (left) and √sNN=200 GeV (right). The π and p data were extracted from Ref. [14].

Ratio of baryon (solid symbols) and antibaryon (open symbols) to π+ as a function of dNch/dy for √sNN=62.4 GeV (left) and √sNN=200 GeV (right). The π and p data were extracted from Ref. [14].

Ratio of baryon (solid symbols) and antibaryon (open symbols) to π- as a function of dNch/dy for √sNN=62.4 GeV (left) and √sNN=200 GeV (right). The π and p data were extracted from Ref. [14].

Ratio of baryon (solid symbols) and antibaryon (open symbols) to π+ as a function of dNch/dy for √sNN=62.4 GeV (left) and √sNN=200 GeV (right). The π and p data were extracted from Ref. [14].

Ratio of baryon (solid symbols) and antibaryon (open symbols) to π- as a function of dNch/dy for √sNN=62.4 GeV (left) and √sNN=200 GeV (right). The π and p data were extracted from Ref. [14].

Ratio of baryon (solid symbols) and antibaryon (open symbols) to π− as a function of √sNN. The lines are the results of the thermal model calculation (see text Sec. 4a). The SPS values are from NA49 [20] (centrality 0–7%) and the RHIC values are from STAR [4, 15] (centrality 0–5%). For the multistrange baryons Ξ and Ω (bottom), the SPS results are from NA57 [2] (centrality 0–11%) and the RHIC values are from STAR [15, 21] (centrality 0–20%).

Ratio of baryon (solid symbols) and antibaryon (open symbols) to π− as a function of √sNN. The lines are the results of the thermal model calculation (see text Sec. 4a). The SPS values are from NA49 [20] (centrality 0–7%) and the RHIC values are from STAR [4, 15] (centrality 0–5%). For the multistrange baryons Ξ and Ω (bottom), the SPS results are from NA57 [2] (centrality 0–11%) and the RHIC values are from STAR [15, 21] (centrality 0–20%).

Nuclear modification factor RCP, calculated as the ratio between 0–10% central spectra and 40–80% peripheral spectra, for π, K0S, Λ, and Ξ particles in Au+Au collisions at 62.4 GeV. The π RCP values were extracted from Ref. [10]. The gray band on the right side of the plot shows the uncertainties on the estimation of the number of binary collisions and the gray band on the lower left side indicates the uncertainties on the number of participants.

Nuclear modification factor RCP, calculated as the ratio between 0–10% central spectra and 40–80% peripheral spectra, for π, K0S, Λ, and Ξ particles in Au+Au collisions at 62.4 GeV. The π RCP values were extracted from Ref. [10]. The gray band on the right side of the plot shows the uncertainties on the estimation of the number of binary collisions and the gray band on the lower left side indicates the uncertainties on the number of participants.

Nuclear modification factor RCP, calculated as the ratio between 0–5% central spectra and 40–60% peripheral spectra, for Λ and Ξ particles measured in Au + Au collisions at 62.4 GeV. The gray band corresponds to the equivalent RCP curve for the Λ particles measured in Au+Au collisions at 200 GeV [15].

Nuclear modification factor RCP, calculated as the ratio between 0–5% central spectra and 40–60% peripheral spectra, for Λ and Ξ particles measured in Au + Au collisions at 62.4 GeV. The gray band corresponds to the equivalent RCP curve for the Λ particles measured in Au+Au collisions at 200 GeV [15].

Λ/K0S ratio as a function of transverse momentum for different centrality classes. 0–5% (solid circles), 40–60% (open squares), and 60–80% (solid triangles) in Au+Au collisions at 62.4 GeV.

Λ/K0S ratio as a function of transverse momentum for different centrality classes. 0–5% (solid circles), 40–60% (open squares), and 60–80% (solid triangles) in Au+Au collisions at 62.4 GeV.

Maximum value of the Λ/K0S ratio from Au+Au collisions at 62.4 GeV (solid circles) and 200 GeV (open circles) [11] as a function of ⟨Npart⟩ for different centrality classes. The lowest ⟨Npart⟩ point corresponds to p+p collisions at 200 GeV [44]. The maximum of the Λ––/K0S from Au+Au collisions at 62.4 GeV is shown as solid triangles.

Maximum value of the Λ/K0S ratio from Au+Au collisions at 62.4 GeV (solid circles) and 200 GeV (open circles) [11] as a function of ⟨Npart⟩ for different centrality classes. The lowest ⟨Npart⟩ point corresponds to p+p collisions at 200 GeV [44]. The maximum of the Λ––/K0S from Au+Au collisions at 62.4 GeV is shown as solid triangles.

Experimental Xi values and FJF predictions for the four NRQCD terms using BK LDME parameters

Experimental Xi values and FJF predictions for the four NRQCD terms using BCKL LDME parameters

Experimental Xi values and FJF predictions for the four NRQCD terms using BK LDME parameters

Electron $p_{T}$ distribution using 2016-2018 data sets. The complete set of selection criteria were applied. Two examples of SSM WPRIME boson signal samples with masses of 3.8 and 5.6 TeV are shown. The lower panel shows the ratio of data to SM prediction, and the shaded band represents the systematic uncertainties.

$p_{T}^{miss}$ distribution in the electron channel using 2016-2018 data sets. The complete set of selection criteria were applied. Two examples of SSM WPRIME boson signal samples with masses of 3.8 and 5.6 TeV are shown. The lower panel shows the ratio of data to SM prediction, and the shaded band represents the systematic uncertainties.

Muon $p_T$ distribution using 2016-2018 data sets. The complete set of selection criteria were applied. Two examples of SSM WPRIME boson signal samples with masses of 3.8 and 5.6 TeV are shown. The lower panel shows the ratio of data to SM prediction, and the shaded band represents the systematic uncertainties.

$p_T^{miss}$ distribution in the muon channel using 2016-2018 data sets. The complete set of selection criteria were applied. Two examples of SSM WPRIME boson signal samples with masses of 3.8 and 5.6 TeV are shown. The lower panel shows the ratio of data to SM prediction, and the shaded band represents the systematic uncertainties.

$M_T$ distribution for the E+INVISIBLE system using 2016-2018 data sets. The complete set of selection criteria were applied. Two examples of SSM WPRIME boson signal samples with masses of 3.8 and 5.6 TeV are shown. The lower panel shows the ratio of data to SM prediction, and the shaded band represents the systematic uncertainties.

$M_T$ distribution for the MU+INVISIBLE system using 2016-2018 data sets. The complete set of selection criteria were applied. Two examples of SSM WPRIME boson signal samples with masses of 3.8 and 5.6 TeV are shown. The lower panel shows the ratio of data to SM prediction, and the shaded band represents the systematic uncertainties.

Theoretical prediction for the production and decay cross-section of SSM WPRIME bosons (W --> LEPTON + NU) as a function of the WPRIME mass, for the range 200-6400 GeV and inclusive in phase-space (no cuts). The uncertainty shown covers PDF and ALPHAS uncertainties. These theoretical predictions are obtained with PYTHIA (LO) and corrected to NNLO in QCD using FEWZ program.

Observed (solid line) and expected (dashed line) upper limits at 95% CL on the product of WPRIME cross-section production and BF(WPRIME --> LEPTON + NU) for an SSM WPRIME boson, as a function of the boson mass, for the electron decay channel. The shaded bands represent the one (green) and two (yellow) standard deviation uncertainty bands for the expected limits. The theoretical predictions for the SSM at NNLO precision in QCD are shown with narrow gray bands corresponding to the PDF and ALPHAS uncertainties.

Observed (solid line) and expected (dashed line) upper limits at 95% CL on the product of WPRIME cross-section production and BF(WPRIME --> LEPTON + NU) for an SSM WPRIME boson, as a function of the boson mass, for the muon decay channel. The shaded bands represent the one (green) and two (yellow) standard deviation uncertainty bands for the expected limits. The theoretical predictions for the SSM at NNLO precision in QCD are shown with narrow gray bands corresponding to the PDF and ALPHAS uncertainties.

Observed (solid line) and expected (dashed line) upper limits at 95% CL on the product of WPRIME cross-section production and BF(WPRIME --> LEPTON + NU) for an SSM WPRIME boson, as a function of the boson mass, for the combined electron and muon decay channels. The shaded bands represent the one (green) and two (yellow) standard deviation uncertainty bands for the expected limits. The theoretical predictions for the SSM at NNLO precision in QCD are shown with narrow gray bands corresponding to the PDF and ALPHAS uncertainties.

The 95% CL observed (solid line) and expected (dashed line) model independent cross section upper limits as function of the $MT_{min}$ threshold, for the electron decay channel. The shaded bands represent the one (green) and two (yellow) standard deviation uncertainty bands for the expected limits.

The 95% CL observed (solid line) and expected (dashed line) model independent cross section upper limits as function of the $MT_{min}$ threshold, for the muon decay channel. The shaded bands represent the one (green) and two (yellow) standard deviation uncertainty bands for the expected limits.

The 95% CL observed (solid line) and expected (dashed line) model independent cross section upper limits as function of the $MT_{min}$ threshold, for the combined electron and muon decay channels. The shaded bands represent the one (green) and two (yellow) standard deviation uncertainty bands for the expected limits.

Observed (solid line) and expected (dashed line) upper limits at 95% CL on the coupling strength ratio, gWprime/gW as a function of the mass of the WPRIME boson, for the electron channel. The one (green) and two (yellow) standard deviation uncertainty bands for the expected limits are shown. The area above the limit curve is excluded. The dotted line represents the case of SSM coupling, gWprime, being equal to gW, the SM coupling.

Observed (solid line) and expected (dashed line) upper limits at 95% CL on the coupling strength ratio, gWprime/gW, as a function of the mass of the WPRIME boson, for the muon channel. The one (green) and two (yellow) standard deviation uncertainty bands for the expected limits are shown. The area above the limit curve is excluded. The dotted line represents the case of SSM coupling, gWprime , being equal to gW, the SM coupling.

Exclusion limits in the 2D plane (1/R, $\mu$) for the split-UED interpretation for the n = 2 case, for the electron channel for the 2016-2018 data sets. R is the radius of the additional spatial dimension and $\mu$ the bulk mass for the fermion field in five dimensions. The expected limit is depicted as a black dashed line. The one (green) and two (yellow) standard deviation uncertainty bands for the expected limits are shown. The experimentally excluded region is the entire area to the left of the solid black line.

Exclusion limits in the 2D plane (1/R, $\mu$) for the split-UED interpretation for the n = 2 case, for the muon channel for the 2016-2018 data sets. R is the radius of the additional spatial dimension and $\mu$ the bulk mass for the fermion field in five dimensions. The expected limit is depicted as a black dashed line. The one (green) and two (yellow) standard deviation uncertainty bands for the expected limits are shown. The experimentally excluded region is the entire area to the left of the solid black line.

Exclusion limits in the 2D plane (1/R, $\mu$) for the split-UED interpretation for the n = 2 case, for the combined electron and muon channels for the 2016-2018 data sets. R is the radius of the additional spatial dimension and $\mu$ the bulk mass for the fermion field in five dimensions. The expected limit is depicted as a black dashed line. The one (green) and two (yellow) standard deviation uncertainty bands for the expected limits are shown. The experimentally excluded region is the entire area to the left of the solid black line.

Observed (solid line) and expected (dashed line) upper limits at 95% CL on the ${\lambda}_{231}$ coupling in the RPV SUSY model with a STAU mediator, as a function of the mass of STAU, for the electron channel and for the production coupling, ${\lambda}^{'}_{3ij}$=0.5 . The couplings ${\lambda}^{'}_{3ij}$, ${\lambda}_{231}$, and ${\lambda}_{132}$ are defined in Fig. 1. The one (green) and two (yellow) standard deviation uncertainty bands for the expected limits are shown. The area above the limit curve is excluded. Limits for other values of ${\lambda}^{'}_{3ij}$ are obtained multiplying the ones shown by the ratio ${\lambda}^{'}_{3ij}$/0.5

Observed (solid line) and expected (dashed line) upper limits at 95% CL on the ${\lambda}_{132}$ coupling in the RPV SUSY model with a stau mediator, as a function of the mass of the stau, for the muon channel and for the production coupling, ${\lambda}^{'}_{3ij}$ = 0.5 . The couplings ${\lambda}^{'}_{3ij}$, ${\lambda}_{231}$, and ${\lambda}_{132}$ are defined in Fig. 1. The one (green) and two (yellow) standard deviation uncertainty bands for the expected limits are shown. The area above the limit curve is excluded. Limits for other values of ${\lambda}^{'}_{3ij}$ are obtained multiplying these ones by the ratio ${\lambda}^{'}_{3ij}$/0.5

Region in the oblique (W,Y) parameter phase space allowed by the current analysis at 95% CL. The combination of the electron and muon channel distributions from the 2017 and 2018 data sets at sqrt(s) = 13 TeV is used, having 101 fb-1 of luminosity.

Negative Log-Likelihood for the determination of the oblique W parameter, for the combination of the electron and muon channel and for 2017 and 2018 data sets (L=101 fb-1) at sqrt(s) = 13 TeV.

Total background estimate and observed data in all bins used in the limit calculation for the SSM WPRIME limits. The total event sample is split into the three years of data taking and the two lepton flavors.The distributions being shown are $M_T$ ones. The associated integrated luminosities for each year are of 35.9, 41.5, and 59.4 fb$̣^{-1}. The mass bins are numbered in ascending order.

Differential polarized inclusive jet cross sections as a function of jet transverse energy.

Differential polarized inclusive jet cross sections as a function of photon virtuality, Q**2.

Differential polarized inclusive jet cross sections as a function of photon virtuality, Q**2.

Differential polarized inclusive jet cross sections as a function of X. Update: contrary to the publication, this is D(SIG)/DLOG10(X) not D(SIG)/DX.

Differential polarized inclusive jet cross sections as a function of X. Update: contrary to the publication, this is D(SIG)/DLOG10(X) not D(SIG)/DX.

Integrated polarized inclusive-jet cross section in the given kinematical range for the E- beam.

Integrated polarized inclusive-jet cross section in the given kinematical range for the E+ beam.

Differential unpolarized cross section for single jet production as a function of the jet pseudorapidity.

Differential unpolarized cross section for two jet production as a function of the mean jet pseudorapidity.

Differential unpolarized cross section for three jet production as a function of the mean jet pseudorapidity.

Differential unpolarized cross section for single jet production as a function of the jet transverse energy.

Differential unpolarized cross section for two jet production as a function of the mean jet transverse energy.

Differential unpolarized cross section for three jet production as a function of the mean jet transverse energy.

Differential unpolarized cross section for single jet production as a function of photon virtuality, Q**2.

Differential unpolarized cross section for two jet production as a function of photon virtuality, Q**2.

Differential unpolarized cross section for three jet production as a function of photon virtuality, Q**2.

Differential unpolarized inclusive-jet cross section as a function of X. Update: contrary to the publication, this is D(SIG)/DLOG10(X) not D(SIG)/DX.

Integrated unpolarized jet cross section in the given kinemetical region.

Differential unpolarized dijet cross section as a function of the dijet mass.

Differential unpolarized three-jet cross section as a function of the three-jet mass.

The Z boson differential cross section as a function of |yZ|.

The Z boson differential cross section as a function of |yZ|.

The Z boson differential cross section as a function of |yZ|.

The Z boson differential cross section as a function of pTZ.

The Z boson differential cross section as a function of pTZ.

The Z boson differential cross section as a function of pTZ.

The TAA-normalized yields of Z bosons as a function of centrality.

The TAA-normalized yields of Z bosons as a function of centrality.

The TAA-normalized yields of Z bosons as a function of centrality.

The relative statistical and systematic uncertainties in % from various sources for the absolute cross section measurements in bins of Z pt on dimuons.

The relative statistical and systematic uncertainties in % from various sources for the absolute cross section measurements in bins of Z pt on dielectrons.

The relative statistical and systematic uncertainties in % from various sources for the absolute cross section measurements in bins of |y(Z)| on dimuons.

The relative statistical and systematic uncertainties in % from various sources for the absolute cross section measurements in bins of |y(Z)| on dielectrons.

The relative statistical and systematic uncertainties in % from various sources for the absolute cross section measurements in bins of $\phi^{\scriptscriptstyle *}_\eta$ on dimuons.

The relative statistical and systematic uncertainties in % from various sources for the absolute cross section measurements in bins of $\phi^{\scriptscriptstyle *}_\eta$ on dielectrons.

The relative statistical and systematic uncertainties in % from various sources for the normalized cross section measurements in bins of Z pt on dimuons.

The relative statistical and systematic uncertainties in % from various sources for the normalized cross section measurements in bins of Z pt on dielectrons.

The relative statistical and systematic uncertainties in % from various sources for the normalized cross section measurements in bins of |y(Z)| on dimuons.

The relative statistical and systematic uncertainties in % from various sources for the normalized cross section measurements in bins of |y(Z)| on dielectrons.

The relative statistical and systematic uncertainties in % from various sources for the normalized cross section measurements in bins of $\phi^{\scriptscriptstyle *}_\eta$ on dimuons.

The relative statistical and systematic uncertainties in % from various sources for the normalized cross section measurements in bins of $\phi^{\scriptscriptstyle *}_\eta$ on dielectrons.

The relative statistical and systematic uncertainties in % from various sources for the absolute double-differential cross section measurements in bins of Z pt for the 0 < |y(Z)| < 0.4 bin in the dimuon final state.

The relative statistical and systematic uncertainties in % from various sources for the absolute double-differential cross section measurements in bins of Z pt for the 0.4 < |y(Z)| < 0.8 bin in the dimuon final state.

The relative statistical and systematic uncertainties in % from various sources for the absolute double-differential cross section measurements in bins of Z pt for the 0.8 < |y(Z)| < 1.2 bin in the dimuon final state.

The relative statistical and systematic uncertainties in % from various sources for the absolute double-differential cross section measurements in bins of Z pt for the 1.2 < |y(Z)| < 1.6 bin in the dimuon final state.

The relative statistical and systematic uncertainties in % from various sources for the absolute double-differential cross section measurements in bins of Z pt for the 1.6 < |y(Z)| < 2.4 bin in the dimuon final state.

The relative statistical and systematic uncertainties in % from various sources for the absolute double-differential cross section measurements in bins of Z pt for the 0 < |y(Z)| < 0.4 bin in the dielectron final state.

The relative statistical and systematic uncertainties in % from various sources for the absolute double-differential cross section measurements in bins of Z pt for the 0.4 < |y(Z)| < 0.8 bin in the dielectron final state.

The relative statistical and systematic uncertainties in % from various sources for the absolute double-differential cross section measurements in bins of Z pt for the 0.8 < |y(Z)| < 1.2 bin in the dielectron final state.

The relative statistical and systematic uncertainties in % from various sources for the absolute double-differential cross section measurements in bins of Z pt for the 1.2 < |y(Z)| < 1.6 bin in the dielectron final state.

The relative statistical and systematic uncertainties in % from various sources for the absolute double-differential cross section measurements in bins of Z pt for the 1.6 < |y(Z)| < 2.4 bin in the dielectron final state.

The measured absolute cross sections in bins of |y(Z)|, using dressed level leptons. The cross sections are normalized by the bin width.

The measured absolute cross sections in bins of Z pt, using dressed level leptons. The cross sections are normalized by the bin width.

The measured absolute cross sections in bins of $\phi^{\scriptscriptstyle *}_\eta$, using dressed level leptons. The cross sections are normalized by the bin width.

The measured absolute cross sections in bins of Z pt different |y(Z)| bins, using dressed level leptons. The cross sections are normalized by the bin width.

The measured normalized cross sections in bins of Z pt, using dressed level leptons. The cross sections are divided by the bin width and then the distributions are normalized to 1.

The measured normalized cross sections in bins of $\phi^{\scriptscriptstyle *}_\eta$, using dressed level leptons. The cross sections are divided by the bin width and then the distributions are normalized to 1.

The measured normalized cross sections in bins of |y(Z)|, using dressed level leptons. The cross sections are divided by the bin width and then the distributions are normalized to 1.

The measured normalized cross sections in bins of Z pt in |y(Z)| bins, using dressed level leptons. The cross sections are divided by the bin width and then the distributions are normalized to 1.

Covariance matrix using dressed level leptons for all bins used in bins of Z pt in the dimuon final state.

Covariance matrix using dressed level leptons for all bins used in bins of |y(Z)| in the dimuon final state.

Covariance matrix using dressed level leptons for all bins used in bins of $\phi^{\scriptscriptstyle *}_\eta$ in the dimuon final state.

Covariance matrix using dressed level leptons for all bins used in bins of Z pt for the 0 < |y(Z)| < 0.4 bin in the dimuon final state.

Covariance matrix using dressed level leptons for all bins used in bins of Z pt for the 0.4 < |y(Z)| < 0.8 bin in the dimuon final state.

Covariance matrix using dressed level leptons for all bins used in bins of Z pt for the 0.8 < |y(Z)| < 1.2 bin in the dimuon final state.

Covariance matrix using dressed level leptons for all bins used in bins of Z pt for the 1.2 < |y(Z)| < 1.6 bin in the dimuon final state.

Covariance matrix using dressed level leptons for all bins used in bins of Z pt for the 1.6 < |y(Z)| < 2.4 bin in the dimuon final state.

Covariance matrix using dressed level leptons for all bins used in bins of Z pt in the dielectron final state.

Covariance matrix using dressed level leptons for all bins used in bins of |y(Z)| in the dielectron final state.

Covariance matrix using dressed level leptons for all bins used in bins of $\phi^{\scriptscriptstyle *}_\eta$ in the dielectron final state.

Covariance matrix using dressed level leptons for all bins used in bins of Z pt for the 0 < |y(Z)| < 0.4 bin in the dielectron final state.

Covariance matrix using dressed level leptons for all bins used in bins of Z pt for the 0.4 < |y(Z)| < 0.8 bin in the dielectron final state.

Covariance matrix using dressed level leptons for all bins used in bins of Z pt for the 0.8 < |y(Z)| < 1.2 bin in the dielectron final state.

Covariance matrix using dressed level leptons for all bins used in bins of Z pt for the 1.2 < |y(Z)| < 1.6 bin in the dielectron final state.

Covariance matrix using dressed level leptons for all bins used in bins of Z pt for the 1.6 < |y(Z)| < 2.4 bin in the dielectron final state.

Covariance matrix using born level leptons for all bins used in bins of Z pt in the dimuon final state.

Covariance matrix using born level leptons for all bins used in bins of |y(Z)| in the dimuon final state.

Covariance matrix using born level leptons for all bins used in bins of $\phi^{\scriptscriptstyle *}_\eta$ in the dimuon final state.

Covariance matrix using born level leptons for all bins used in bins of Z pt for the 0 < |y(Z)| < 0.4 bin in the dimuon final state.

Covariance matrix using born level leptons for all bins used in bins of Z pt for the 0.4 < |y(Z)| < 0.8 bin in the dimuon final state.

Covariance matrix using born level leptons for all bins used in bins of Z pt for the 0.8 < |y(Z)| < 1.2 bin in the dimuon final state.

Covariance matrix using born level leptons for all bins used in bins of Z pt for the 1.2 < |y(Z)| < 1.6 bin in the dimuon final state.

Covariance matrix using born level leptons for all bins used in bins of Z pt for the 1.6 < |y(Z)| < 2.4 bin in the dimuon final state.

Covariance matrix using born level leptons for all bins used in bins of Z pt in the dielectron final state.

Covariance matrix using born level leptons for all bins used in bins of |y(Z)| in the dielectron final state.

Covariance matrix using born level leptons for all bins used in bins of $\phi^{\scriptscriptstyle *}_\eta$ in the dielectron final state.

Covariance matrix using born level leptons for all bins used in bins of Z pt for the 0 < |y(Z)| < 0.4 bin in the dielectron final state.

Covariance matrix using born level leptons for all bins used in bins of Z pt for the 0.4 < |y(Z)| < 0.8 bin in the dielectron final state.

Covariance matrix using born level leptons for all bins used in bins of Z pt for the 0.8 < |y(Z)| < 1.2 bin in the dielectron final state.

Covariance matrix using born level leptons for all bins used in bins of Z pt for the 1.2 < |y(Z)| < 1.6 bin in the dielectron final state.

Covariance matrix using born level leptons for all bins used in bins of Z pt for the 1.6 < |y(Z)| < 2.4 bin in the dielectron final state.

Covariance matrix for normalized cross sections using dressed level leptons for all bins used in bins of Z pt in the dimuon final state.

Covariance matrix for normalized cross sections using dressed level leptons for all bins used in bins of |y(Z)| in the dimuon final state.

Covariance matrix for normalized cross sections using dressed level leptons for all bins used in bins of $\phi^{\scriptscriptstyle *}_\eta$ in the dimuon final state.

Covariance matrix for normalized cross sections using dressed level leptons for all bins used in bins of Z pt for the 0 < |y(Z)| < 0.4 bin in the dimuon final state.

Covariance matrix for normalized cross sections using dressed level leptons for all bins used in bins of Z pt for the 0.4 < |y(Z)| < 0.8 bin in the dimuon final state.

Covariance matrix for normalized cross sections using dressed level leptons for all bins used in bins of Z pt for the 0.8 < |y(Z)| < 1.2 bin in the dimuon final state.

Covariance matrix for normalized cross sections using dressed level leptons for all bins used in bins of Z pt for the 1.2 < |y(Z)| < 1.6 bin in the dimuon final state.

Covariance matrix for normalized cross sections using dressed level leptons for all bins used in bins of Z pt for the 1.6 < |y(Z)| < 2.4 bin in the dimuon final state.

Covariance matrix for normalized cross sections using dressed level leptons for all bins used in bins of Z pt in the dielectron final state.

Covariance matrix for normalized cross sections using dressed level leptons for all bins used in bins of |y(Z)| in the dielectron final state.

Covariance matrix for normalized cross sections using dressed level leptons for all bins used in bins of $\phi^{\scriptscriptstyle *}_\eta$ in the dielectron final state.

Covariance matrix for normalized cross sections using dressed level leptons for all bins used in bins of Z pt for the 0 < |y(Z)| < 0.4 bin in the dielectron final state.

Covariance matrix for normalized cross sections using dressed level leptons for all bins used in bins of Z pt for the 0.4 < |y(Z)| < 0.8 bin in the dielectron final state.

Covariance matrix for normalized cross sections using dressed level leptons for all bins used in bins of Z pt for the 0.8 < |y(Z)| < 1.2 bin in the dielectron final state.

Covariance matrix for normalized cross sections using dressed level leptons for all bins used in bins of Z pt for the 1.2 < |y(Z)| < 1.6 bin in the dielectron final state.

Covariance matrix for normalized cross sections using dressed level leptons for all bins used in bins of Z pt for the 1.6 < |y(Z)| < 2.4 bin in the dielectron final state.

Covariance matrix for normalized cross sections using born level leptons for all bins used in bins of Z pt in the dimuon final state.

Covariance matrix for normalized cross sections using born level leptons for all bins used in bins of |y(Z)| in the dimuon final state.

Covariance matrix for normalized cross sections using born level leptons for all bins used in bins of $\phi^{\scriptscriptstyle *}_\eta$ in the dimuon final state.

Covariance matrix for normalized cross sections using born level leptons for all bins used in bins of Z pt for the 0 < |y(Z)| < 0.4 bin in the dimuon final state.

Covariance matrix for normalized cross sections using born level leptons for all bins used in bins of Z pt for the 0.4 < |y(Z)| < 0.8 bin in the dimuon final state.

Covariance matrix for normalized cross sections using born level leptons for all bins used in bins of Z pt for the 0.8 < |y(Z)| < 1.2 bin in the dimuon final state.

Covariance matrix for normalized cross sections using born level leptons for all bins used in bins of Z pt for the 1.2 < |y(Z)| < 1.6 bin in the dimuon final state.

Covariance matrix for normalized cross sections using born level leptons for all bins used in bins of Z pt for the 1.6 < |y(Z)| < 2.4 bin in the dimuon final state.

Covariance matrix for normalized cross sections using born level leptons for all bins used in bins of Z pt in the dielectron final state.

Covariance matrix for normalized cross sections using born level leptons for all bins used in bins of |y(Z)| in the dielectron final state.

Covariance matrix for normalized cross sections using born level leptons for all bins used in bins of $\phi^{\scriptscriptstyle *}_\eta$ in the dielectron final state.

Covariance matrix for normalized cross sections using born level leptons for all bins used in bins of Z pt for the 0 < |y(Z)| < 0.4 bin in the dielectron final state.

Covariance matrix for normalized cross sections using born level leptons for all bins used in bins of Z pt for the 0.4 < |y(Z)| < 0.8 bin in the dielectron final state.

Covariance matrix for normalized cross sections using born level leptons for all bins used in bins of Z pt for the 0.8 < |y(Z)| < 1.2 bin in the dielectron final state.

Covariance matrix for normalized cross sections using born level leptons for all bins used in bins of Z pt for the 1.2 < |y(Z)| < 1.6 bin in the dielectron final state.

Covariance matrix for normalized cross sections using born level leptons for all bins used in bins of Z pt for the 1.6 < |y(Z)| < 2.4 bin in the dielectron final state.

The measured absolute cross sections in bins of |y(Z)|, using born level leptons. The cross sections are normalized by the bin width.

The measured absolute cross sections in bins of Z pt, using born level leptons. The cross sections are normalized by the bin width. The first bin (0-1 GeV) is not shown as large differences were observed in aMC@NLO and POWHEG predictions at Born level.

The measured absolute cross sections in bins of $\phi^{\scriptscriptstyle *}_\eta$, using born level leptons. The cross sections are normalized by the bin width.

The measured absolute cross sections in bins of Z pt different |y(Z)| bins, using born level leptons. The cross sections are normalized by the bin width. The first bin (0-1 GeV) is not shown as large differences were observed in aMC@NLO and POWHEG predictions at Born level.

The measured normalized cross sections in bins of Z pt, using born level leptons. The first bin (0-1 GeV) is not shown as large differences were observed in aMC@NLO and POWHEG predictions at Born level. The cross sections are divided by the bin width and then the distributions are normalized to 1.

The measured normalized cross sections in bins of $\phi^{\scriptscriptstyle *}_\eta$, using born level leptons. The cross sections are divided by the bin width and then the distributions are normalized to 1.

The measured normalized cross sections in bins of |y(Z)|, using born level leptons.

The measured normalized cross sections (left) in bins of Z pt in |y(Z)| bins, using born level leptons. The first bin (0-1 GeV) is not shown as large differences were observed in aMC@NLO and POWHEG predictions at Born level. The cross sections are divided by the bin width and then the distributions are normalized to 1.

Covariance matrix using dressed level leptons for all bins used in bins of Z pt in the dilepton final state.

Covariance matrix using dressed level leptons for all bins used in bins of |y(Z)| in the dilepton final state.

Covariance matrix using dressed level leptons for all bins used in bins of $\phi^{\scriptscriptstyle *}_\eta$ in the dilepton final state.

Covariance matrix using dressed level leptons for all bins used in bins of Z pt for the 0 < |y(Z)| < 0.4 bin in the dilepton final state.

Covariance matrix using dressed level leptons for all bins used in bins of Z pt for the 0.4 < |y(Z)| < 0.8 bin in the dilepton final state.

Covariance matrix using dressed level leptons for all bins used in bins of Z pt for the 0.8 < |y(Z)| < 1.2 bin in the dilepton final state.

Covariance matrix using dressed level leptons for all bins used in bins of Z pt for the 1.2 < |y(Z)| < 1.6 bin in the dilepton final state.

Covariance matrix using dressed level leptons for all bins used in bins of Z pt for the 1.6 < |y(Z)| < 2.4 bin in the dilepton final state.

Covariance matrix using born level leptons for all bins used in bins of Z pt in the dilepton final state.

Covariance matrix using born level leptons for all bins used in bins of |y(Z)| in the dilepton final state.

Covariance matrix using born level leptons for all bins used in bins of $\phi^{\scriptscriptstyle *}_\eta$ in the dilepton final state.

Covariance matrix using born level leptons for all bins used in bins of Z pt for the 0 < |y(Z)| < 0.4 bin in the dilepton final state.

Covariance matrix using born level leptons for all bins used in bins of Z pt for the 0.4 < |y(Z)| < 0.8 bin in the dilepton final state.

Covariance matrix using born level leptons for all bins used in bins of Z pt for the 0.8 < |y(Z)| < 1.2 bin in the dilepton final state.

Covariance matrix using born level leptons for all bins used in bins of Z pt for the 1.2 < |y(Z)| < 1.6 bin in the dilepton final state.

Covariance matrix using born level leptons for all bins used in bins of Z pt for the 1.6 < |y(Z)| < 2.4 bin in the dilepton final state.

Covariance matrix for normalized cross sections using dressed level leptons for all bins used in bins of Z pt in the dilepton final state.

Covariance matrix for normalized cross sections using dressed level leptons for all bins used in bins of |y(Z)| in the dilepton final state.

Covariance matrix for normalized cross sections using dressed level leptons for all bins used in bins of $\phi^{\scriptscriptstyle *}_\eta$ in the dilepton final state.

Covariance matrix for normalized cross sections using dressed level leptons for all bins used in bins of Z pt for the 0 < |y(Z)| < 0.4 bin in the dilepton final state.

Covariance matrix for normalized cross sections using dressed level leptons for all bins used in bins of Z pt for the 0.4 < |y(Z)| < 0.8 bin in the dilepton final state.

Covariance matrix for normalized cross sections using dressed level leptons for all bins used in bins of Z pt for the 0.8 < |y(Z)| < 1.2 bin in the dilepton final state.

Covariance matrix for normalized cross sections using dressed level leptons for all bins used in bins of Z pt for the 1.2 < |y(Z)| < 1.6 bin in the dilepton final state.

Covariance matrix for normalized cross sections using dressed level leptons for all bins used in bins of Z pt for the 1.6 < |y(Z)| < 2.4 bin in the dilepton final state.

Covariance matrix for normalized cross sections using born level leptons for all bins used in bins of Z pt in the dilepton final state.

Covariance matrix for normalized cross sections using born level leptons for all bins used in bins of |y(Z)| in the dilepton final state.

Covariance matrix for normalized cross sections using born level leptons for all bins used in bins of $\phi^{\scriptscriptstyle *}_\eta$ in the dilepton final state.

Covariance matrix for normalized cross sections using born level leptons for all bins used in bins of Z pt for the 0 < |y(Z)| < 0.4 bin in the dilepton final state.

Covariance matrix for normalized cross sections using born level leptons for all bins used in bins of Z pt for the 0.4 < |y(Z)| < 0.8 bin in the dilepton final state.

Covariance matrix for normalized cross sections using born level leptons for all bins used in bins of Z pt for the 0.8 < |y(Z)| < 1.2 bin in the dilepton final state.

Covariance matrix for normalized cross sections using born level leptons for all bins used in bins of Z pt for the 1.2 < |y(Z)| < 1.6 bin in the dilepton final state.

Covariance matrix for normalized cross sections using born level leptons for all bins used in bins of Z pt for the 1.6 < |y(Z)| < 2.4 bin in the dilepton final state.