$\rho_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{2}$ Standard method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{2}$ Two_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{2}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{3}$ Standard method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{3}$ Two_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{3}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{4}$ Standard method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{4}$ Two_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{4}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{2}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{3}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{3}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{4}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{4}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$

$\rho_{2}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$

$\rho_{3}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$

$\rho_{3}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$

$\rho_{4}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$

$\rho_{4}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$

$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{3}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{3}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{4}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{4}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{2}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{2}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{2}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.3< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{3}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{3}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{3}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.3< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{4}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{4}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{4}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.3< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{3}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{3}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{4}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{4}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$Cov_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$Cov_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$Cov_{3}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$Cov_{3}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$Cov_{4}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$Cov_{4}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality

$\rho_{3}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{3}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality

$\rho_{4}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{4}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality

$\rho_{2}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{2}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality

$\rho_{3}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{3}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality

$\rho_{4}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{4}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality

$\rho_{2}$ for peripheral events, Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality,

$\rho_{2}$ for peripheral events, Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality,

$\rho_{2}$ for peripheral events, Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality,

$\rho_{2}$ for peripheral events, Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality,

$\rho_{2}$ for peripheral events, Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality,

$\rho_{2}$ for peripheral events, Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality,

$\rho_{2}$ for peripheral events, Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality,

$\rho_{2}$ for peripheral events, Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality,

$\rho_{2}$ for peripheral events, Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality,

$\rho_{2}$ for peripheral events, Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality,

$\rho_{2}$ for peripheral events, Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality,

$\rho_{2}$ for peripheral events, Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality,

$\rho_{2}$, Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality,

$\rho_{2}$, Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality,

$\rho_{3}$, Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality,

$\rho_{3}$, Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality,

$\rho_{2}$, Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality,

$\rho_{2}$, Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality,

$\rho_{3}$, Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality,

$\rho_{3}$, Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality,

$\rho_{2}$ for central events, Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality,

$\rho_{2}$ for central events, Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality,

$\rho_{2}$ for central events, Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality,

$\rho_{2}$ for central events, Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality,

$\rho_{2}$ ratio between Xe+Xe 5.44 TeV and Pb+Pb 5.02 TeV for central events, Three_subevent method, for , $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality,

$\rho_{2}$ ratio between Xe+Xe 5.44 TeV and Pb+Pb 5.02 TeV for central events, Three_subevent method, for , $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality,

$\Sigma E_{T}$ vs $N^{rec}_{ch}$ for Pb+Pb 5.02 TeV

$\Sigma E_{T}$ vs $N^{rec}_{ch}$ for Xe+Xe 5.44 TeV

$\rho_{2}$ ratio between Xe+Xe 5.44 TeV and Pb+Pb 5.02 TeV for central events, Standard method, for , $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality,

$\rho_{2}$ ratio between Xe+Xe 5.44 TeV and Pb+Pb 5.02 TeV for central events, Standard method, for , $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality,

$\rho_{2}$ ratio between Xe+Xe 5.44 TeV and Pb+Pb 5.02 TeV for central events, Combined_subevent method, for , $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality,

$\rho_{2}$ ratio between Xe+Xe 5.44 TeV and Pb+Pb 5.02 TeV for central events, Combined_subevent method, for , $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality,

$\rho_{2}$ ratio between Xe+Xe 5.44 TeV and Pb+Pb 5.02 TeV for central events, Three_subevent method, for , $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality,

$\rho_{2}$ ratio between Xe+Xe 5.44 TeV and Pb+Pb 5.02 TeV for central events, Three_subevent method, for , $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality,

$\rho_{2}$ ratio between Xe+Xe 5.44 TeV and Pb+Pb 5.02 TeV for central events, Combined_subevent method, for , $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality,

$\rho_{2}$ ratio between Xe+Xe 5.44 TeV and Pb+Pb 5.02 TeV for central events, Combined_subevent method, for , $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality,

$\rho_{3}$ for central events, Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality,

$\rho_{3}$ for central events, Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality,

$\rho_{3}$ for central events, Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality,

$\rho_{3}$ for central events, Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality,

$\rho_{3}$ ratio between Xe+Xe 5.44 TeV and Pb+Pb 5.02 TeV for central events, Standard method, for , $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality,

$\rho_{3}$ ratio between Xe+Xe 5.44 TeV and Pb+Pb 5.02 TeV for central events, Standard method, for , $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality,

$\rho_{3}$ ratio between Xe+Xe 5.44 TeV and Pb+Pb 5.02 TeV for central events, Combined_subevent method, for , $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality,

$\rho_{3}$ ratio between Xe+Xe 5.44 TeV and Pb+Pb 5.02 TeV for central events, Combined_subevent method, for , $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality,

$\rho_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$

$\rho_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$

$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$

$\rho_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$

$\rho_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$

$\rho_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$

$\rho_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$

$\rho_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$

$\rho_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$

$\rho_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$

$\rho_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$

$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$

$\rho_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$

$\rho_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$

$\rho_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$

$\rho_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$

$\rho_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$

$\rho_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$

$\rho_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$

$\rho_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$

$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$

$\rho_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$

$\rho_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$

$\rho_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$

$\rho_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$

$\rho_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$

$\rho_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$

$\rho_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$

$\rho_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$

$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$

$\rho_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$

$\rho_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$

$\rho_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$

$\rho_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$

$\rho_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$

$\rho_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$

$\rho_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.

$\rho_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.

$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.

$\rho_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.

$\rho_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.

$\rho_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.

$\rho_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.

$\rho_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.

$\rho_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.

$\rho_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$\rho_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$\rho_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$\rho_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$\rho_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$\rho_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$\rho_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$\rho_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$\rho_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.

$\rho_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.

$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.

$\rho_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.

$\rho_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.

$\rho_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.

$\rho_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.

$\rho_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.

$\rho_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.

$\rho_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$\rho_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$\rho_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$\rho_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$\rho_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$\rho_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$\rho_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$\rho_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$\rho_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$

$\rho_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$

$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$

$\rho_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$

$\rho_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$

$\rho_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$

$\rho_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$

$\rho_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$

$\rho_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$

$\rho_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$

$\rho_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$

$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$

$\rho_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$

$\rho_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$

$\rho_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$

$\rho_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$

$\rho_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$

$\rho_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$

$\rho_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$

$\rho_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$

$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$

$\rho_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$

$\rho_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$

$\rho_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$

$\rho_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$

$\rho_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$

$\rho_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$

$\rho_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$

$\rho_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$

$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$

$\rho_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$

$\rho_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$

$\rho_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$

$\rho_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$

$\rho_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$

$\rho_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$

$\rho_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$\rho_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$\rho_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$\rho_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$\rho_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$\rho_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$\rho_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$\rho_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$\rho_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$\rho_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$\rho_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$\rho_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$\rho_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$\rho_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$\rho_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$\rho_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$\rho_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$\rho_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$\rho_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$\rho_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$\rho_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$\rho_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$\rho_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$\rho_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$\rho_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$\rho_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$\rho_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$\rho_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$\rho_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$\rho_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$\rho_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$\rho_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$Cov_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.

$Cov_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.

$Cov_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.

$Cov_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.

$Cov_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.

$Cov_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.

$Cov_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.

$Cov_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.

$Cov_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.

$Cov_{2}$ Standard method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.

$Cov_{2}$ Two_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.

$Cov_{2}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.

$Cov_{3}$ Standard method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.

$Cov_{3}$ Two_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.

$Cov_{3}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.

$Cov_{4}$ Standard method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.

$Cov_{4}$ Two_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.

$Cov_{4}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.

$Cov_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{2}$ Standard method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{2}$ Two_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{2}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{3}$ Standard method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{3}$ Two_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{3}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{4}$ Standard method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{4}$ Two_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{4}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality.

$Cov_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$Cov_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$Cov_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$Cov_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$Cov_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$Cov_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$Cov_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$Cov_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$Cov_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$Cov_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$Cov_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$Cov_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$Cov_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$Cov_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$Cov_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$Cov_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$Cov_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$Cov_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$Cov_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$Cov_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$Cov_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$Cov_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$Cov_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$Cov_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$Cov_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$Cov_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$Cov_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$Cov_{2}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$Cov_{2}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$Cov_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$Cov_{3}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$Cov_{3}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$Cov_{3}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$Cov_{4}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$Cov_{4}$ Two_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$Cov_{4}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$ based Centrality.

$c_{k}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.

$c_{k}$ Standard method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.

$var(v^{2}_{2})$ Combined subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.

$var(v^{2}_{2})$ Combined subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.

$var(v^{2}_{3})$ Combined subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.

$var(v^{2}_{3})$ Combined subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.

$var(v^{2}_{4})$ Combined subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.

$var(v^{2}_{4})$ Combined subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.

$c_{k}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$.

$c_{k}$ Standard method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$.

$var(v^{2}_{2})$ Combined subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$.

$var(v^{2}_{2})$ Combined subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$.

$var(v^{2}_{3})$ Combined subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$.

$var(v^{2}_{3})$ Combined subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$.

$var(v^{2}_{4})$ Combined subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$.

$var(v^{2}_{4})$ Combined subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$.

$c_{k}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.

$c_{k}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.

$var(v^{2}_{2})$ Combined subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.

$var(v^{2}_{2})$ Combined subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.

$var(v^{2}_{3})$ Combined subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.

$var(v^{2}_{3})$ Combined subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.

$var(v^{2}_{4})$ Combined subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.

$var(v^{2}_{4})$ Combined subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$.

$c_{k}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$.

$c_{k}$ Standard method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$.

$var(v^{2}_{2})$ Combined subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$.

$var(v^{2}_{2})$ Combined subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$.

$var(v^{2}_{3})$ Combined subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$.

$var(v^{2}_{3})$ Combined subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$.

$var(v^{2}_{4})$ Combined subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$.

$var(v^{2}_{4})$ Combined subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N^{rec}_{ch}$.

$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N_{ch}^{rec}$ based Centrality

$\rho_{3}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{3}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N_{ch}^{rec}$ based Centrality

$\rho_{4}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{4}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N_{ch}^{rec}$ based Centrality

$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality

$\rho_{3}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{3}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality

$\rho_{4}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{4}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality

$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N_{ch}^{rec}$ based Centrality

$\rho_{3}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{3}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N_{ch}^{rec}$ based Centrality

$\rho_{4}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{4}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N_{ch}^{rec}$ based Centrality

$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{2}$ Three_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality

$\rho_{3}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{3}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality

$\rho_{4}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{4}$ Combined_subevent method, for Pb+Pb 5.02 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality

$\rho_{2}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{2}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N_{ch}^{rec}$ based Centrality

$\rho_{3}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{3}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N_{ch}^{rec}$ based Centrality

$\rho_{4}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{4}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <2.0 GeV vs $N_{ch}^{rec}$ based Centrality

$\rho_{2}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{2}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality

$\rho_{3}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{3}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality

$\rho_{4}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{4}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<2.5, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality

$\rho_{2}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{2}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N_{ch}^{rec}$ based Centrality

$\rho_{3}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{3}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N_{ch}^{rec}$ based Centrality

$\rho_{4}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{4}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <2.0 GeV vs $N_{ch}^{rec}$ based Centrality

$\rho_{2}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{2}$ Three_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality

$\rho_{3}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{3}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality

$\rho_{4}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $\Sigma E_{T}$ based Centrality

$\rho_{4}$ Combined_subevent method, for Xe+Xe 5.44 TeV, $|\eta|$<1.0, 0.5< $p_{T}$ <5.0 GeV vs $N_{ch}^{rec}$ based Centrality

Breakdown of expected and observed yields in the electroweak search Int, Low, and OffShell signal regions after a simultaneous fit to the signal regions and control regions. All statistical and systematic uncertainties are included.

Breakdown of expected and observed yields in the four edge signal regions, integrated over the $m_{\ell\ell}$ distribution after a separate simultaneous fit to each signal region and control region pair. The uncertainties include both the statistical and systematic sources.

Breakdown of expected and observed yields in the three on-$Z$ signal regions after a separate simultaneous fit to each signal region and control region pair. The uncertainties include both the statistical and systematic sources.

Distributions of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in VR-High-Sideband-EWK (top-left), VR-High-R-EWK (top-right), VR-1J-High-EWK (bottom-left), and VR-$\ell\ell bb$-EWK (bottom-right) from the EWK search after a simultaneous fit of the control regions. The hatched band includes both the systematic and statistical uncertainties. The last bin includes the overflow.

Distributions of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in VR-High-Sideband-EWK (top-left), VR-High-R-EWK (top-right), VR-1J-High-EWK (bottom-left), and VR-$\ell\ell bb$-EWK (bottom-right) from the EWK search after a simultaneous fit of the control regions. The hatched band includes both the systematic and statistical uncertainties. The last bin includes the overflow.

Distributions of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in VR-High-Sideband-EWK (top-left), VR-High-R-EWK (top-right), VR-1J-High-EWK (bottom-left), and VR-$\ell\ell bb$-EWK (bottom-right) from the EWK search after a simultaneous fit of the control regions. The hatched band includes both the systematic and statistical uncertainties. The last bin includes the overflow.

Distributions of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in VR-High-Sideband-EWK (top-left), VR-High-R-EWK (top-right), VR-1J-High-EWK (bottom-left), and VR-$\ell\ell bb$-EWK (bottom-right) from the EWK search after a simultaneous fit of the control regions. The hatched band includes both the systematic and statistical uncertainties. The last bin includes the overflow.

Distributions of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in VR-Int-EWK (top-left), VR-Low-EWK (top-right), VR-Low-2-EWK (bottom-left), and VR-OffShell-EWK (bottom-right) from the EWK search after a simultaneous fit of the control regions. The hatched band includes both the systematic and statistical uncertainties. The last bin includes the overflow.

Distributions of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in VR-Int-EWK (top-left), VR-Low-EWK (top-right), VR-Low-2-EWK (bottom-left), and VR-OffShell-EWK (bottom-right) from the EWK search after a simultaneous fit of the control regions. The hatched band includes both the systematic and statistical uncertainties. The last bin includes the overflow.

Distributions of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in VR-Int-EWK (top-left), VR-Low-EWK (top-right), VR-Low-2-EWK (bottom-left), and VR-OffShell-EWK (bottom-right) from the EWK search after a simultaneous fit of the control regions. The hatched band includes both the systematic and statistical uncertainties. The last bin includes the overflow.

Distributions of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in VR-Int-EWK (top-left), VR-Low-EWK (top-right), VR-Low-2-EWK (bottom-left), and VR-OffShell-EWK (bottom-right) from the EWK search after a simultaneous fit of the control regions. The hatched band includes both the systematic and statistical uncertainties. The last bin includes the overflow.

Observed and expected dilepton mass distributions in VRC-STR (top-left), VRLow-STR (top-right), VRMed-STR (bottom-left), and VRHigh-STR (bottom-right). Each validation region is fit separately with the corresponding control region. All statistical and systematic uncertainties are included in the hatched band. The entries are normalized to the bin width, and the last bin is the overflow.

Observed and expected dilepton mass distributions in VRC-STR (top-left), VRLow-STR (top-right), VRMed-STR (bottom-left), and VRHigh-STR (bottom-right). Each validation region is fit separately with the corresponding control region. All statistical and systematic uncertainties are included in the hatched band. The entries are normalized to the bin width, and the last bin is the overflow.

Observed and expected dilepton mass distributions in VRC-STR (top-left), VRLow-STR (top-right), VRMed-STR (bottom-left), and VRHigh-STR (bottom-right). Each validation region is fit separately with the corresponding control region. All statistical and systematic uncertainties are included in the hatched band. The entries are normalized to the bin width, and the last bin is the overflow.

Observed and expected dilepton mass distributions in VRC-STR (top-left), VRLow-STR (top-right), VRMed-STR (bottom-left), and VRHigh-STR (bottom-right). Each validation region is fit separately with the corresponding control region. All statistical and systematic uncertainties are included in the hatched band. The entries are normalized to the bin width, and the last bin is the overflow.

Observed and expected jet multiplicity in VRLow-STR (top-left), VRMed-STR (top-right), and VRHigh-STR (bottom) after a fit performed on the $m_{\ell\ell}$ distribution and corresponding control region. All statistical and systematic uncertainties are included in the hatched band. The last bin contains the overflow.

Observed and expected jet multiplicity in VRLow-STR (top-left), VRMed-STR (top-right), and VRHigh-STR (bottom) after a fit performed on the $m_{\ell\ell}$ distribution and corresponding control region. All statistical and systematic uncertainties are included in the hatched band. The last bin contains the overflow.

Observed and expected jet multiplicity in VRLow-STR (top-left), VRMed-STR (top-right), and VRHigh-STR (bottom) after a fit performed on the $m_{\ell\ell}$ distribution and corresponding control region. All statistical and systematic uncertainties are included in the hatched band. The last bin contains the overflow.

Observed and expected dilepton mass distributions in VR3L-STR without a fit to the data. The 'Other' category includes the negligible contributions from $t\bar{t}$ and $Z/\gamma^*$+jets processes. The hatched band contains the statistical uncertainty and the theoretical systematic uncertainties of the $WZ$/$ZZ$ prediction, which are the dominant sources of uncertainty. No fit is performed. The last bin contains the overflow.

Observed and expected distributions in five EWK search regions after a simultaneous fit to the SR and CR. In the top row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-High_8-EWK and $m_{bb}$ in SR-$\ell\ell bb$-EWK. In the middle row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Int-EWK and $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Low-EWK. In the bottom row is $m_{\ell\ell}$ in SR-OffShell-EWK. Overlaid are example C1N2 and GMSB signal models, where the numbers in the brackets indicate the masses, in $\mathrm{GeV}$, of the $\tilde{\chi}_1^\pm$ and $\tilde{\chi}_2^0$ or the mass of the $\tilde{\chi}_1^0$ and branching ratio to the Higgs boson respectively. All statistical and systematic uncertainties are included in the hatched bands. The last bin includes the overflow.

Observed and expected distributions in five EWK search regions after a simultaneous fit to the SR and CR. In the top row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-High_8-EWK and $m_{bb}$ in SR-$\ell\ell bb$-EWK. In the middle row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Int-EWK and $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Low-EWK. In the bottom row is $m_{\ell\ell}$ in SR-OffShell-EWK. Overlaid are example C1N2 and GMSB signal models, where the numbers in the brackets indicate the masses, in $\mathrm{GeV}$, of the $\tilde{\chi}_1^\pm$ and $\tilde{\chi}_2^0$ or the mass of the $\tilde{\chi}_1^0$ and branching ratio to the Higgs boson respectively. All statistical and systematic uncertainties are included in the hatched bands. The last bin includes the overflow.

Observed and expected distributions in five EWK search regions after a simultaneous fit to the SR and CR. In the top row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-High_8-EWK and $m_{bb}$ in SR-$\ell\ell bb$-EWK. In the middle row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Int-EWK and $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Low-EWK. In the bottom row is $m_{\ell\ell}$ in SR-OffShell-EWK. Overlaid are example C1N2 and GMSB signal models, where the numbers in the brackets indicate the masses, in $\mathrm{GeV}$, of the $\tilde{\chi}_1^\pm$ and $\tilde{\chi}_2^0$ or the mass of the $\tilde{\chi}_1^0$ and branching ratio to the Higgs boson respectively. All statistical and systematic uncertainties are included in the hatched bands. The last bin includes the overflow.

Observed and expected distributions in five EWK search regions after a simultaneous fit to the SR and CR. In the top row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-High_8-EWK and $m_{bb}$ in SR-$\ell\ell bb$-EWK. In the middle row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Int-EWK and $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Low-EWK. In the bottom row is $m_{\ell\ell}$ in SR-OffShell-EWK. Overlaid are example C1N2 and GMSB signal models, where the numbers in the brackets indicate the masses, in $\mathrm{GeV}$, of the $\tilde{\chi}_1^\pm$ and $\tilde{\chi}_2^0$ or the mass of the $\tilde{\chi}_1^0$ and branching ratio to the Higgs boson respectively. All statistical and systematic uncertainties are included in the hatched bands. The last bin includes the overflow.

Observed and expected distributions in five EWK search regions after a simultaneous fit to the SR and CR. In the top row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-High_8-EWK and $m_{bb}$ in SR-$\ell\ell bb$-EWK. In the middle row, left-to-right, are $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Int-EWK and $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ in SR-Low-EWK. In the bottom row is $m_{\ell\ell}$ in SR-OffShell-EWK. Overlaid are example C1N2 and GMSB signal models, where the numbers in the brackets indicate the masses, in $\mathrm{GeV}$, of the $\tilde{\chi}_1^\pm$ and $\tilde{\chi}_2^0$ or the mass of the $\tilde{\chi}_1^0$ and branching ratio to the Higgs boson respectively. All statistical and systematic uncertainties are included in the hatched bands. The last bin includes the overflow.

Observed and expected dilepton mass distributions in SRC-STR (top-left), SRLow-STR (top-right), SRMed-STR (bottom-left), and SRHigh-STR (bottom-right), with the binning used for interpretations after a separate simultaneous fit to each signal region and control region pair. The red dashed lines are example signal models overlaid on the figure. All statistical and systematic uncertainties are included in the hatched bands. The last bins are the overflow.

Observed and expected dilepton mass distributions in SRC-STR (top-left), SRLow-STR (top-right), SRMed-STR (bottom-left), and SRHigh-STR (bottom-right), with the binning used for interpretations after a separate simultaneous fit to each signal region and control region pair. The red dashed lines are example signal models overlaid on the figure. All statistical and systematic uncertainties are included in the hatched bands. The last bins are the overflow.

Observed and expected dilepton mass distributions in SRC-STR (top-left), SRLow-STR (top-right), SRMed-STR (bottom-left), and SRHigh-STR (bottom-right), with the binning used for interpretations after a separate simultaneous fit to each signal region and control region pair. The red dashed lines are example signal models overlaid on the figure. All statistical and systematic uncertainties are included in the hatched bands. The last bins are the overflow.

Observed and expected dilepton mass distributions in SRC-STR (top-left), SRLow-STR (top-right), SRMed-STR (bottom-left), and SRHigh-STR (bottom-right), with the binning used for interpretations after a separate simultaneous fit to each signal region and control region pair. The red dashed lines are example signal models overlaid on the figure. All statistical and systematic uncertainties are included in the hatched bands. The last bins are the overflow.

Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].

Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].

Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].

Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].

Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].

Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].

Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].

Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].

Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].

Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].

Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].

Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294].

Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294]. The grey numbers indicate the observed 95\% CLs upper limit on the cross section.

Expected and observed exclusion contours from the EWK analysis for the C1N2 model (left) and GMSB model (right). The dashed line indicates the expected limits at 95$\%$ CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties on the background prediction and experimental uncertainties on the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The gray shaded areas indicate observed limits on these models from the two lepton channels of Ref.~[arXiv: 1803.02762] and Ref.~[arXiv: 1403.5294]. The grey numbers indicate the observed 95$\%$ CLs upper limit on the cross section.

Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$ ilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].

Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$ ilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].

Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$ ilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].

Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$ ilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].

Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].

Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].

Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].The grey numbers indicated the observed 95\% CL upper limit on the cross section.

Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].

Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].

Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].

Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].

Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].

Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].

Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].The grey numbers indicated the observed 95\% CL upper limit on the cross section.

Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].

Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].

Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].

Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].

Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].The grey numbers indicated the observed 95\% CL upper limit on the cross section.

Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].

Expected and observed exclusion contours derived from the combination of all of the Strong search SRs for the $\tilde{g}$--$\tilde{\ell}$ (top-left), $\tilde{g}$--$Z$ (top-right), and $\tilde{s}--Z$ (bottom) models. The dashed line indicates the expected limits at 95\% CL and the surrounding band shows the $1\sigma$ variation of the expected limit as a consequence of the uncertainties in the background prediction and experimental uncertainties of the signal ($\pm1\sigma_\mathrm{exp}$). The red dotted lines surrounding the observed limit contours indicate the variation resulting from changing the signal cross-section within its uncertainty ($\pm1\sigma_\mathrm{theory}^\mathrm{SUSY}$). The grey-shaded area indicates the observed limits on these models from Ref. [23].

The combined $E_{\mathrm{T}}^{\mathrm{miss}}$ distribution of VRLow-STR and SRLow-STR (left), and the same region with the $\Delta\phi(\boldsymbol{j}_{1,2},\boldsymbol{\mathit{p}}_{ ext{T}}^{ ext{miss}})<0.4$ requirement, used as a control region to normalize the $Z/\gamma^*+\mathrm{jets}$ process (right). Separate fits for the SR and VR are performed, as for the results in the paper, and the resulting distributions are merged. All statistical and systematic uncertainties are included in the hatched bands. The last bins contain the overflow.

Cutflow of expected events in the four Strong search edge signal regions. `Leptons' refers to electrons and muons only. The gluino-$Z^{(*)}$ model with $m_{ ilde{g}}=800~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for SRC-STR with 60000 Monte Carlo (MC) events generated. The slepton-$Z^{(*)}$ model with $m_{ ilde{\ell}}=1200~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for SRMed-STR with 30000 (MC) events generated. The gluino-slepton model with $m_{ ilde{g}}=2~TeV$ and $m_{ ilde{\ell}}=1.3~TeV$ is used for SRLow-STR and SRHigh-STR with 30000 MC events generated. The Generator Filter requires two 5~GeV leptons and 100~GeV of \met. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~GeV$ or at least one lepton with $p_{\mathrm{T}}>25~GeV$ and a photon with $p_{\mathrm{T}}>40~GeV$, with all objects within $|\eta|=2.6$.

Cutflow of expected events in the four Strong search edge signal regions. `Leptons' refers to electrons and muons only. The gluino-$Z^{(*)}$ model with $m_{ ilde{g}}=800~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for SRC-STR with 60000 Monte Carlo (MC) events generated. The slepton-$Z^{(*)}$ model with $m_{ ilde{\ell}}=1200~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for SRMed-STR with 30000 (MC) events generated. The gluino-slepton model with $m_{ ilde{g}}=2~TeV$ and $m_{ ilde{\ell}}=1.3~TeV$ is used for SRLow-STR and SRHigh-STR with 30000 MC events generated. The Generator Filter requires two 5~GeV leptons and 100~GeV of \met. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~GeV$ or at least one lepton with $p_{\mathrm{T}}>25~GeV$ and a photon with $p_{\mathrm{T}}>40~GeV$, with all objects within $|\eta|=2.6$.

Cutflow of expected events in the four Strong search edge signal regions. `Leptons' refers to electrons and muons only. The gluino-$Z^{(*)}$ model with $m_{ ilde{g}}=800~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for SRC-STR with 60000 Monte Carlo (MC) events generated. The slepton-$Z^{(*)}$ model with $m_{ ilde{\ell}}=1200~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for SRMed-STR with 30000 (MC) events generated. The gluino-slepton model with $m_{ ilde{g}}=2~TeV$ and $m_{ ilde{\ell}}=1.3~TeV$ is used for SRLow-STR and SRHigh-STR with 30000 MC events generated. The Generator Filter requires two 5~GeV leptons and 100~GeV of \met. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~GeV$ or at least one lepton with $p_{\mathrm{T}}>25~GeV$ and a photon with $p_{\mathrm{T}}>40~GeV$, with all objects within $|\eta|=2.6$.

Cutflow of expected events in the four Strong search edge signal regions. `Leptons' refers to electrons and muons only. The gluino-$Z^{(*)}$ model with $m_{ ilde{g}}=800~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for SRC-STR with 60000 Monte Carlo (MC) events generated. The slepton-$Z^{(*)}$ model with $m_{ ilde{\ell}}=1200~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for SRMed-STR with 30000 (MC) events generated. The gluino-slepton model with $m_{ ilde{g}}=2~TeV$ and $m_{ ilde{\ell}}=1.3~TeV$ is used for SRLow-STR and SRHigh-STR with 30000 MC events generated. The Generator Filter requires two 5~GeV leptons and 100~GeV of \met. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~GeV$ or at least one lepton with $p_{\mathrm{T}}>25~GeV$ and a photon with $p_{\mathrm{T}}>40~GeV$, with all objects within $|\eta|=2.6$.

Cutflow of expected events in the three Strong search on-$Z$ signal regions. The cutflow up to the signal region specific requirements is the same as in the Strong search edge cutflow. The slepton-$Z^{(*)}$ model with $m_{ ilde{\ell}}=1200~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for all of the on-$Z$ signal regions with 30000 (MC) events generated.

Cutflow of expected events in the three Strong search on-$Z$ signal regions. The cutflow up to the signal region specific requirements is the same as in the Strong search edge cutflow. The slepton-$Z^{(*)}$ model with $m_{ ilde{\ell}}=1200~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for all of the on-$Z$ signal regions with 30000 (MC) events generated.

Cutflow of expected events in the three Strong search on-$Z$ signal regions. The cutflow up to the signal region specific requirements is the same as in the Strong search edge cutflow. The slepton-$Z^{(*)}$ model with $m_{ ilde{\ell}}=1200~GeV$ and $m_{ ilde{\chi}_1^0}=700~GeV$ is used for all of the on-$Z$ signal regions with 30000 (MC) events generated.

Table 36: Cutflow of expected events in the region SR-OffShell_a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 36: Cutflow of expected events in the region SR-OffShell_a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 37: Cutflow of expected events in the region SR-OffShell_b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 37: Cutflow of expected events in the region SR-OffShell_b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 38: Cutflow of expected events in the region SR-Low_a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 38: Cutflow of expected events in the region SR-Low_a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 39: Cutflow of expected events in the region SR-Low_b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 39: Cutflow of expected events in the region SR-Low_b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 40: Cutflow of expected events in the region SR-Low-2-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 40: Cutflow of expected events in the region SR-Low-2-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 41: Cutflow of expected events in the region SR-Int_a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 41: Cutflow of expected events in the region SR-Int_a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 42: Cutflow of expected events in the region SR-Int_b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 42: Cutflow of expected events in the region SR-Int_b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 43: Cutflow of expected events in the region SR-High_16a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 43: Cutflow of expected events in the region SR-High_16a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 44: Cutflow of expected events in the region SR-High_16b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 44: Cutflow of expected events in the region SR-High_16b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 45: Cutflow of expected events in the region SR-High_8a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 45: Cutflow of expected events in the region SR-High_8a-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 46: Cutflow of expected events in the region SR-High_8b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 46: Cutflow of expected events in the region SR-High_8b-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 47: Cutflow of expected events in the region SR-1J-High-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 47: Cutflow of expected events in the region SR-1J-High-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 48: Cutflow of expected events in the region SR-llbb-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

Table 48: Cutflow of expected events in the region SR-llbb-EWK. Requirements below the line are specific to this region. On the Generator Filter line, the total number of unweighted events simulated is given in brackets. `Leptons' refers to electrons and muons only. For C1N2 models, the Generator Filter requires at least two $7~\mathrm{GeV}$ leptons and for C1N2 models with mass splittings below the Z boson mass it also requires $75~\mathrm{GeV}$ of $E_{\mathrm{T}}^{\mathrm{miss}}$. For GMSB models, the Generator Filter requires at least two $3~\mathrm{GeV}$ leptons. For on-shell C1N2 models, the `Forced Decays' require each Z boson to decay to a charged lepton pair (electron, muon, or tau) and each W boson to decay hadronically. For off-shell C1N2 models, each neutralino is forced to produce a charged lepton pair in its decay, and each chargino can produce any fermion pair. The SUSY2 kernel requires at least two leptons with $p_{\mathrm{T}}>9~\mathrm{GeV}$ or at least one lepton with $p_{\mathrm{T}}>25~\mathrm{GeV}$ and a photon with $p_{\mathrm{T}}>40~\mathrm{GeV}$, with all objects within $|\eta|=2.6$.

The combined $m_{jj}$ distribution of CR-Z-EWK and SR-Low-EWK (left), and the $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ distribution in CR-Z-met-EWK (right), which removes the upper limit of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}}) < 9$ from the definition of CR-Z-EWK. This $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ tail overlaps other control and validation regions, but not signal regions. The arrows indicate the signal region SR-Low-EWK (left), and the $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ phase space which is not included in CR-Z-EWK (right). All EWK search control and signal regions are included in the fit. All statistical and systematic uncertainties are included in the hatched bands. The theoretical uncertainties from CR-Z-EWK are applied to CR-Z-met-EWK. The last bins contain the overflow.

The combined $m_{jj}$ distribution of CR-Z-EWK and SR-Low-EWK (left), and the $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ distribution in CR-Z-met-EWK (right), which removes the upper limit of $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}}) < 9$ from the definition of CR-Z-EWK. This $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ tail overlaps other control and validation regions, but not signal regions. The arrows indicate the signal region SR-Low-EWK (left), and the $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ phase space which is not included in CR-Z-EWK (right). All EWK search control and signal regions are included in the fit. All statistical and systematic uncertainties are included in the hatched bands. The theoretical uncertainties from CR-Z-EWK are applied to CR-Z-met-EWK. The last bins contain the overflow.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-1J-High-EWK and SR-$\ell\ell bb$-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-1J-High-EWK and SR-$\ell\ell bb$-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-1J-High-EWK and SR-$\ell\ell bb$-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the GMSB model in the regions SR-1J-High-EWK and SR-$\ell\ell bb$-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-OffShell-EWK and SR-Low-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-Low-2-EWK and SR-Int-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-High-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-1J-High-EWK and SR-$\ell\ell bb$-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-1J-High-EWK and SR-$\ell\ell bb$-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-1J-High-EWK and SR-$\ell\ell bb$-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) for the C1N2 model in the regions SR-1J-High-EWK and SR-$\ell\ell bb$-EWK. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. For models with mass splittings below the Z boson mass, this filter also requires $E_{\mathrm{T}}^{\mathrm{miss}} > 75~\mathrm{GeV}$. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_SLN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_SLN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_SLN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_SLN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_SLN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_SLN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_SLN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_SLN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the GG_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Signal region acceptance (left) and efficiency (right) over the full \mll\ range for the SS_N2_ZN1 model in Strong search regions. Acceptance is calculated by applying the signal-region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out.

Expected and observed 95% CL for the 1SFH mu Majorana model.

Expected and observed 95% CL for the 2QDH NH Dirac model.

Expected and observed 95% CL for the 2QDH NH Majorana model.

Expected and observed 95% CL for the 2QDH IH Dirac model.

Expected and observed 95% CL for the 2QDH IH Majorana model.

Cutflow for six simulated signal channels showing the weighted number of expected events based on the single-flavour mixing model in the Majorana limit. Each column uses the generated signal sample with the mass hypothesis $m_N = 10$ GeV and proper decay length $c\tau_N = 10$ mm.

Cutflow for the six channels in data showing the number of events passing each successive signal selection for Majorana HNLs.

The event selection efficiency for each mass-lifetime point in all six studied channels. Shown is the fraction of the produced MC simulation events that pass all signal region selections. An entry of 0 indicates no events were selected.

The dominant signal uncertainty is due to differences in reconstruction of displaced vertices and tracks between data and MC. This is evaluated by comparing $K^{0}_{S} \rightarrow \pi^+\pi^-$ event yields in the VR and in MC produced with Pythia8.186 in bins of $p_\mathrm{T}$ and $r_\mathrm{DV}$. The data/MC ratio is normalized to the bin nearest the IP where the tracking and vertexing reconstruction algorithms are expected to be most robust. The symmetrized difference from 1.0 is applied to each signal vertex as a per-event systematic variation.

Expected and observed yields in the different analysis regions (prefit) for the 1SFH e Dirac model (10 GeV, 10mm).

Expected and observed yields in the different analysis regions (postfit) for the 1SFH e Dirac model (10 GeV, 10mm).

Expected and observed yields in the different analysis regions (prefit) for the 1SFH e Majorana model (10 GeV, 10mm).

Expected and observed yields in the different analysis regions (postfit) for the 1SFH e Majorana model (10 GeV, 10mm).

Expected and observed yields in the different analysis regions (prefit) for the 1SFH u Dirac model (10 GeV, 10mm).

Expected and observed yields in the different analysis regions (postfit) for the 1SFH u Dirac model (10 GeV, 10mm).

Expected and observed yields in the different analysis regions (prefit) for the 1SFH u Majorana model (10 GeV, 10mm).

Expected and observed yields in the different analysis regions (postfit) for the 1SFH u Majorana model (10 GeV, 10mm).

Expected and observed yields in the different analysis regions (prefit) for the 2QDH (NH) Dirac model (10 GeV, 10mm).

Expected and observed yields in the different analysis regions (postfit) for the 2QDH (NH) Dirac model (10 GeV, 10mm).

Expected and observed yields in the different analysis regions (prefit) for the 2QDH (NH) Majorana model (10 GeV, 10mm).

Expected and observed yields in the different analysis regions (postfit) for the 2QDH (NH) Majorana model (10 GeV, 10mm).

Expected and observed yields in the different analysis regions (prefit) for the 2QDH (IH) Dirac model (10 GeV, 10mm).

Expected and observed yields in the different analysis regions (postfit) for the 2QDH (IH) Dirac model (10 GeV, 10mm).

Expected and observed yields in the different analysis regions (prefit) for the 2QDH (IH) Majorana model (10 GeV, 10mm).

Expected and observed yields in the different analysis regions (postfit) for the 2QDH (IH) Majorana model (10 GeV, 10mm).

The total displaced vertexing efficiency as a function of $r_{DV}$ for the custom configuration used in this analysis. The definition of the secondary vertex efficiency can be found in defined in \cite{ATL-PHYS-PUB-2019-013}. The efficiency is shown for $\mu-\mu\mu$, $\mu-\mu e$ and $\mu-ee$ signals with $m_N=10$~GeV and $c\tau_N=10$~mm.

Summary of the total efficiencies. Quoted uncertainties correspond to statistical uncertainties of the simulated samples used. For the $B_c^+\to J/\psi \pi^+$ channel, the efficiency $\epsilon_{B_c^+\to J/\psi \pi^+}$ entering the equations for $R_{D_s^{(*)+}/\pi^+}$ is shown, while the efficiency for the full dataset is not defined.

The Bose-Einstein correlation (BEC) parameter R as a function of n_ch for HMT events using different MC generators in the calculation of R₂(Q). The uncertainties shown are statistical. The lower panel of each plot shows the ratio of the BEC parameters obtained using EPOS LHC (red circles), Pythia 8 Monash (blue squares) and Herwig++ UE-EE-5 (green triangles) compared with the parameters obtained using Pythia 8 A2. The gray band in the lower panels is the MC systematic uncertainty, obtained as explained in the text.

The Bose-Einstein correlation (BEC) parameter R as a function of k_T for MB events using different MC generators in the calculation of R₂(Q). The uncertainties shown are statistical. The lower panel of each plot shows the ratio of the BEC parameters obtained using EPOS LHC (red circles), Pythia 8 Monash (blue squares) and Herwig++ UE-EE-5 (green triangles) compared with the parameters obtained using Pythia 8 A2. The gray band in the lower panels is the MC systematic uncertainty, obtained as explained in the text.

The Bose-Einstein correlation (BEC) parameter &lambda; as a function of k_T for MB events using different MC generators in the calculation of R₂(Q). The uncertainties shown are statistical. The lower panel of each plot shows the ratio of the BEC parameters obtained using EPOS LHC (red circles), Pythia 8 Monash (blue squares) and Herwig++ UE-EE-5 (green triangles) compared with the parameters obtained using Pythia 8 A2. The gray band in the lower panels is the MC systematic uncertainty, obtained as explained in the text.

The two-particle double-ratio correlation function, R₂(Q), for pp collisions for track p_T &gt;100&nbsp;MeV at &radic;s=13&nbsp;TeV in the multiplicity interval 71 &le; n_ch &lt; 80 for the minimum-bias (MB) events. The blue dashed and red solid lines show the results of the exponential and Gaussian fits, respectively. The region excluded from the fits is shown. The statistical uncertainty and the systematic uncertainty for imperfections in the data reconstruction procedure are added in quadrature.

The two-particle double-ratio correlation function, R₂(Q), for pp collisions for track p_T &gt;100&nbsp;MeV at &radic;s=13&nbsp;TeV in the multiplicity interval 231 &le; n_ch &lt; 300 for the high-multiplicity track (HMT) events. The blue dashed and red solid lines show the results of the exponential and Gaussian fits, respectively. The region excluded from the fits is shown. The statistical uncertainty and the systematic uncertainty for imperfections in the data reconstruction procedure are added in quadrature.

The dependence of the correlation strength, &lambda;(m_ch), on rescaled multiplicity, m_ch, obtained from the exponential fit of the R₂(Q) correlation functions for tracks with p_T &gt; 100 &nbsp;MeV and p_T &gt; 500&nbsp;MeV at &radic;s = 13 &nbsp;TeV for the minimum-bias (MB) and high multiplicity track (HMT) data. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the exponential fit of &lambda;(m_ch) for p_T &gt;100&nbsp;MeV and p_T &gt;500&nbsp;MeV, respectively.

The dependence of the correlation strength, &lambda;(m_ch), on rescaled multiplicity, m_ch, obtained from the exponential fit of the R₂(Q) correlation functions for tracks with p_T &gt; 100 &nbsp;MeV and p_T &gt; 500&nbsp;MeV at &radic;s = 13 &nbsp;TeV for the minimum-bias (MB) and high multiplicity track (HMT) data. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the exponential fit of &lambda;(m_ch) for p_T &gt;100&nbsp;MeV and p_T &gt;500&nbsp;MeV, respectively.

The dependence of the correlation strength, &lambda;(m_ch), on rescaled multiplicity, m_ch, obtained from the exponential fit of the R₂(Q) correlation functions for tracks with p_T &gt; 100 &nbsp;MeV and p_T &gt; 500&nbsp;MeV at &radic;s = 13 &nbsp;TeV for the minimum-bias (MB) and high multiplicity track (HMT) data. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the exponential fit of &lambda;(m_ch) for p_T &gt;100&nbsp;MeV and p_T &gt;500&nbsp;MeV, respectively.

The dependence of the correlation strength, &lambda;(m_ch), on rescaled multiplicity, m_ch, obtained from the exponential fit of the R₂(Q) correlation functions for tracks with p_T &gt; 100 &nbsp;MeV and p_T &gt; 500&nbsp;MeV at &radic;s = 13 &nbsp;TeV for the minimum-bias (MB) and high multiplicity track (HMT) data. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the exponential fit of &lambda;(m_ch) for p_T &gt;100&nbsp;MeV and p_T &gt;500&nbsp;MeV, respectively.

The dependence of the source radius, R(m_ch), on m_ch. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the fit of R(m_ch) for &#8731;m_ch &lt; 1.2 for p_T &gt;100&nbsp;MeV and p_T &gt;500&nbsp;MeV, respectively. The black and blue dotted curves are extensions of the black and blue solid curves beyond &#8731;m_ch &gt; 1.2, respectively. The black and brown dashed curves represent the saturation value of R(m_ch) for &#8731;m_ch &gt; 1.45 with p_T &gt;100&nbsp;MeV and for &#8731;m_ch &gt; 1.6 with p_T &gt;500&nbsp;MeV, respectively.

The dependence of the source radius, R(m_ch), on m_ch. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the fit of R(m_ch) for &#8731;m_ch &lt; 1.2 for p_T &gt;100&nbsp;MeV and p_T &gt;500&nbsp;MeV, respectively. The black and blue dotted curves are extensions of the black and blue solid curves beyond &#8731;m_ch &gt; 1.2, respectively. The black and brown dashed curves represent the saturation value of R(m_ch) for &#8731;m_ch &gt; 1.45 with p_T &gt;100&nbsp;MeV and for &#8731;m_ch &gt; 1.6 with p_T &gt;500&nbsp;MeV, respectively.

The dependence of the source radius, R(m_ch), on m_ch. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the fit of R(m_ch) for &#8731;m_ch &lt; 1.2 for p_T &gt;100&nbsp;MeV and p_T &gt;500&nbsp;MeV, respectively. The black and blue dotted curves are extensions of the black and blue solid curves beyond &#8731;m_ch &gt; 1.2, respectively. The black and brown dashed curves represent the saturation value of R(m_ch) for &#8731;m_ch &gt; 1.45 with p_T &gt;100&nbsp;MeV and for &#8731;m_ch &gt; 1.6 with p_T &gt;500&nbsp;MeV, respectively.

The dependence of the source radius, R(m_ch), on m_ch. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the fit of R(m_ch) for &#8731;m_ch &lt; 1.2 for p_T &gt;100&nbsp;MeV and p_T &gt;500&nbsp;MeV, respectively. The black and blue dotted curves are extensions of the black and blue solid curves beyond &#8731;m_ch &gt; 1.2, respectively. The black and brown dashed curves represent the saturation value of R(m_ch) for &#8731;m_ch &gt; 1.45 with p_T &gt;100&nbsp;MeV and for &#8731;m_ch &gt; 1.6 with p_T &gt;500&nbsp;MeV, respectively.

The dependence of the R(m_ch) on &#8731;m_ch. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the fit of R(m_ch) for &#8731;m_ch &lt; 1.2 for p_T &gt;100&nbsp;MeV and p_T &gt;500&nbsp;MeV, respectively. The black and blue dotted curves are extensions of the black and blue solid curves beyond &#8731;m_ch &gt; 1.2, respectively. The black and brown dashed curves represent the saturation value of R(m_ch) for &#8731;m_ch &gt; 1.45 with p_T &gt;100&nbsp;MeV and for &#8731;m_ch &gt; 1.6 with p_T &gt;500&nbsp;MeV, respectively

The dependence of the R(m_ch) on &#8731;m_ch. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the fit of R(m_ch) for &#8731;m_ch &lt; 1.2 for p_T &gt;100&nbsp;MeV and p_T &gt;500&nbsp;MeV, respectively. The black and blue dotted curves are extensions of the black and blue solid curves beyond &#8731;m_ch &gt; 1.2, respectively. The black and brown dashed curves represent the saturation value of R(m_ch) for &#8731;m_ch &gt; 1.45 with p_T &gt;100&nbsp;MeV and for &#8731;m_ch &gt; 1.6 with p_T &gt;500&nbsp;MeV, respectively

The dependence of the R(m_ch) on &#8731;m_ch. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the fit of R(m_ch) for &#8731;m_ch &lt; 1.2 for p_T &gt;100&nbsp;MeV and p_T &gt;500&nbsp;MeV, respectively. The black and blue dotted curves are extensions of the black and blue solid curves beyond &#8731;m_ch &gt; 1.2, respectively. The black and brown dashed curves represent the saturation value of R(m_ch) for &#8731;m_ch &gt; 1.45 with p_T &gt;100&nbsp;MeV and for &#8731;m_ch &gt; 1.6 with p_T &gt;500&nbsp;MeV, respectively

The dependence of the R(m_ch) on &#8731;m_ch. The uncertainties represent the sum in quadrature of the statistical and asymmetric systematic contributions. The black and blue solid curves represent the fit of R(m_ch) for &#8731;m_ch &lt; 1.2 for p_T &gt;100&nbsp;MeV and p_T &gt;500&nbsp;MeV, respectively. The black and blue dotted curves are extensions of the black and blue solid curves beyond &#8731;m_ch &gt; 1.2, respectively. The black and brown dashed curves represent the saturation value of R(m_ch) for &#8731;m_ch &gt; 1.45 with p_T &gt;100&nbsp;MeV and for &#8731;m_ch &gt; 1.6 with p_T &gt;500&nbsp;MeV, respectively

Comparison of single-ratio two-particle correlation functions, using the unlike-charge particle (UCP) pair reference sample, for minimum-bias (MB) events, showing C₂^data(Q) (top panel) at 13&nbsp;TeV (black circles) and 7&nbsp;TeV (open blue circles), and the ratio of C₂^7&nbsp;TeV (Q) to C₂^13&nbsp;TeV (Q) (bottom panel). Comparison of C₂^data (Q) for representative multiplicity region 3.09 &lt; m_ch &le; 3.86. The statistical and systematic uncertainties, combined in quadrature, are presented. The systematic uncertainties include track efficiency, Coulomb correction, non-closure and multiplicity-unfolding uncertainties.

Comparison of single-ratio two-particle correlation functions, using the unlike-charge particle (UCP) pair reference sample, for minimum-bias (MB) events, showing C₂^data(Q) (top panel) at 13 &nbsp;TeV (black circles) and 7 &nbsp;TeV (open blue circles), and the ratio of C₂^7&nbsp;TeV (Q) to C₂^13&nbsp;TeV (Q) (bottom panel). Comparison of C₂^data (Q) for representative k_T region 400 &lt; k_T &le;500 &nbsp;MeV. The statistical and systematic uncertainties, combined in quadrature, are presented. The systematic uncertainties include track efficiency, Coulomb correction, non-closure and multiplicity-unfolding uncertainties.

The k_T dependence of the correlation strength, &lambda;(k_T), obtained from the exponential fit to the R₂(Q) correlation functions for events with multiplicity n_ch &ge; 2 and transfer momentum of tracks with p_T &gt;100&nbsp;MeV and p_T &gt;500&nbsp;MeV at &radic;s=13&nbsp;TeV for the minimum-bias (MB) and high-multiplicity track (HMT) events. The uncertainties represent the sum in quadrature of the statistical and systematic contributions. The curves represent the exponential fits to &lambda;(k_T).

The k_T dependence of the correlation strength, &lambda;(k_T), obtained from the exponential fit to the R₂(Q) correlation functions for events with multiplicity n_ch &ge; 2 and transfer momentum of tracks with p_T &gt;100&nbsp;MeV and p_T &gt;500&nbsp;MeV at &radic;s=13&nbsp;TeV for the minimum-bias (MB) and high-multiplicity track (HMT) events. The uncertainties represent the sum in quadrature of the statistical and systematic contributions. The curves represent the exponential fits to &lambda;(k_T).

The k_T dependence of the correlation strength, &lambda;(k_T), obtained from the exponential fit to the R₂(Q) correlation functions for events with multiplicity n_ch &ge; 2 and transfer momentum of tracks with p_T &gt;100&nbsp;MeV and p_T &gt;500&nbsp;MeV at &radic;s=13&nbsp;TeV for the minimum-bias (MB) and high-multiplicity track (HMT) events. The uncertainties represent the sum in quadrature of the statistical and systematic contributions. The curves represent the exponential fits to &lambda;(k_T).

The k_T dependence of the correlation strength, &lambda;(k_T), obtained from the exponential fit to the R₂(Q) correlation functions for events with multiplicity n_ch &ge; 2 and transfer momentum of tracks with p_T &gt;100&nbsp;MeV and p_T &gt;500&nbsp;MeV at &radic;s=13&nbsp;TeV for the minimum-bias (MB) and high-multiplicity track (HMT) events. The uncertainties represent the sum in quadrature of the statistical and systematic contributions. The curves represent the exponential fits to &lambda;(k_T).

The k_T dependence of the source radius, R(k_T), obtained from the exponential fit to the R₂(Q) correlation functions for events with multiplicity n_ch &ge; 2 and transfer momentum of tracks with p_T &gt;100&nbsp;MeV and p_T &gt;500&nbsp;MeV at &radic;s=13&nbsp;TeV for the minimum-bias (MB) and high-multiplicity track (HMT) events. The uncertainties represent the sum in quadrature of the statistical and systematic contributions. The curves represent the exponential fits to R(k_T).

The k_T dependence of the source radius, R(k_T), obtained from the exponential fit to the R₂(Q) correlation functions for events with multiplicity n_ch &ge; 2 and transfer momentum of tracks with p_T &gt;100&nbsp;MeV and p_T &gt;500&nbsp;MeV at &radic;s=13&nbsp;TeV for the minimum-bias (MB) and high-multiplicity track (HMT) events. The uncertainties represent the sum in quadrature of the statistical and systematic contributions. The curves represent the exponential fits to R(k_T).

The k_T dependence of the source radius, R(k_T), obtained from the exponential fit to the R₂(Q) correlation functions for events with multiplicity n_ch &ge; 2 and transfer momentum of tracks with p_T &gt;100&nbsp;MeV and p_T &gt;500&nbsp;MeV at &radic;s=13&nbsp;TeV for the minimum-bias (MB) and high-multiplicity track (HMT) events. The uncertainties represent the sum in quadrature of the statistical and systematic contributions. The curves represent the exponential fits to R(k_T).

The k_T dependence of the source radius, R(k_T), obtained from the exponential fit to the R₂(Q) correlation functions for events with multiplicity n_ch &ge; 2 and transfer momentum of tracks with p_T &gt;100&nbsp;MeV and p_T &gt;500&nbsp;MeV at &radic;s=13&nbsp;TeV for the minimum-bias (MB) and high-multiplicity track (HMT) events. The uncertainties represent the sum in quadrature of the statistical and systematic contributions. The curves represent the exponential fits to R(k_T).

The two-dimensional dependence on m_ch and k_T for p_T &gt; 100&nbsp;MeV for the correlation strength, &lambda;, obtained from the exponential fit to the R₂(Q) correlation functions using the MB sample for m_ch &le; 3.08 and the HMT sample for m_ch &gt; 3.08.

The two-dimensional dependence on m_ch and k_T for p_T &gt; 100&nbsp;MeV for the source radius, R, obtained from the exponential fit to the R₂(Q) correlation functions using the MB sample for m_ch &le; 3.08 and the HMT sample for m_ch &gt; 3.08.

The parameter &lambda; for p_T &gt; 100&nbsp;MeV as a function of k_T in selected low m_ch intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter &lambda; for p_T &gt; 100&nbsp;MeV as a function of k_T in selected low m_ch intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter &lambda; for p_T &gt; 100&nbsp;MeV as a function of k_T in selected high m_ch intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter &lambda; for p_T &gt; 100&nbsp;MeV as a function of k_T in selected high m_ch intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter &lambda; for p_T &gt; 100&nbsp;MeV as a function of m_ch in k_T intervals between 0.1 and 0.5&nbsp;GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter &lambda; for p_T &gt; 100&nbsp;MeV as a function of m_ch in k_T intervals between 0.1 and 0.5&nbsp;GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter &lambda; for p_T &gt; 100&nbsp;MeV as a function of m_ch in k_T intervals between 0.5 and 1.5&nbsp;GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter &lambda; for p_T &gt; 100&nbsp;MeV as a function of m_ch in k_T intervals between 0.5 and 1.5&nbsp;GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter R for p_T &gt; 100&nbsp;MeV as a function of k_T in selected low m_ch intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter R for p_T &gt; 100&nbsp;MeV as a function of k_T in selected low m_ch intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter R for p_T &gt; 100&nbsp;MeV as a function of k_T in selected high m_ch intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter R for p_T &gt; 100&nbsp;MeV as a function of k_T in selected high m_ch intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter R for p_T &gt; 100&nbsp;MeV as a function of m_ch in k_T intervals between 0.1 and 0.5&nbsp;GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter R for p_T &gt; 100&nbsp;MeV as a function of m_ch in k_T intervals between 0.1 and 0.5&nbsp;GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter R for p_T &gt; 100&nbsp;MeV as a function of m_ch in k_T intervals between 0.5 and 1.5&nbsp;GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter R for p_T &gt; 100&nbsp;MeV as a function of m_ch in k_T intervals between 0.5 and 1.5&nbsp;GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.

The fit parameter &mu; describing the dependence of the correlation strength, &lambda;, on charged-particle scaled multiplicity, for track p_T&gt;100&nbsp;MeV and track p_T&gt;500&nbsp;MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at &radic;s = 13&nbsp;TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid (blue dashed) curve represents the exponential fit of the dependence of parameter &mu; on m_ch for tracks with p_T &gt;100&nbsp;MeV (p_T &gt;500&nbsp;MeV).

The fit parameter &mu; describing the dependence of the correlation strength, &lambda;, on charged-particle scaled multiplicity, for track p_T&gt;100&nbsp;MeV and track p_T&gt;500&nbsp;MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at &radic;s = 13&nbsp;TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid (blue dashed) curve represents the exponential fit of the dependence of parameter &mu; on m_ch for tracks with p_T &gt;100&nbsp;MeV (p_T &gt;500&nbsp;MeV).

The fit parameter &mu; describing the dependence of the correlation strength, &lambda;, on charged-particle scaled multiplicity, for track p_T&gt;100&nbsp;MeV and track p_T&gt;500&nbsp;MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at &radic;s = 13&nbsp;TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid (blue dashed) curve represents the exponential fit of the dependence of parameter &mu; on m_ch for tracks with p_T &gt;100&nbsp;MeV (p_T &gt;500&nbsp;MeV).

The fit parameter &mu; describing the dependence of the correlation strength, &lambda;, on charged-particle scaled multiplicity, for track p_T&gt;100&nbsp;MeV and track p_T&gt;500&nbsp;MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at &radic;s = 13&nbsp;TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid (blue dashed) curve represents the exponential fit of the dependence of parameter &mu; on m_ch for tracks with p_T &gt;100&nbsp;MeV (p_T &gt;500&nbsp;MeV).

The fit parameter &nu; describing the dependence of the correlation strength, &lambda;, on charged-particle scaled multiplicity, for track p_T&gt;100&nbsp;MeV and track p_T&gt;500&nbsp;MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at &radic;s = 13&nbsp;TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid (blue dashed) curve represents the exponential fit of the dependence of parameter &nu; on m_ch for tracks with p_T &gt;100&nbsp;MeV (p_T &gt;500&nbsp;MeV).

The fit parameter &nu; describing the dependence of the correlation strength, &lambda;, on charged-particle scaled multiplicity, for track p_T&gt;100&nbsp;MeV and track p_T&gt;500&nbsp;MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at &radic;s = 13&nbsp;TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid (blue dashed) curve represents the exponential fit of the dependence of parameter &nu; on m_ch for tracks with p_T &gt;100&nbsp;MeV (p_T &gt;500&nbsp;MeV).

The fit parameter &nu; describing the dependence of the correlation strength, &lambda;, on charged-particle scaled multiplicity, for track p_T&gt;100&nbsp;MeV and track p_T&gt;500&nbsp;MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at &radic;s = 13&nbsp;TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid (blue dashed) curve represents the exponential fit of the dependence of parameter &nu; on m_ch for tracks with p_T &gt;100&nbsp;MeV (p_T &gt;500&nbsp;MeV).

The fit parameter &nu; describing the dependence of the correlation strength, &lambda;, on charged-particle scaled multiplicity, for track p_T&gt;100&nbsp;MeV and track p_T&gt;500&nbsp;MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at &radic;s = 13&nbsp;TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid (blue dashed) curve represents the exponential fit of the dependence of parameter &nu; on m_ch for tracks with p_T &gt;100&nbsp;MeV (p_T &gt;500&nbsp;MeV).

The parameter &xi; describing the dependence of the source radius, R, on charged-particle scaled multiplicity, m_ch, for track p_T&gt;100&nbsp;MeV and track p_T&gt;500&nbsp;MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at &radic;s = 13&nbsp;TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid and blue dashed curves represent the saturated value of the parameter &xi; for m_ch &gt; 3.0 for tracks with p_T &gt;100&nbsp;MeV and for m_ch &gt; 2.8 for tracks with p_T &gt;500&nbsp;MeV, respectively.

The parameter &xi; describing the dependence of the source radius, R, on charged-particle scaled multiplicity, m_ch, for track p_T&gt;100&nbsp;MeV and track p_T&gt;500&nbsp;MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at &radic;s = 13&nbsp;TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid and blue dashed curves represent the saturated value of the parameter &xi; for m_ch &gt; 3.0 for tracks with p_T &gt;100&nbsp;MeV and for m_ch &gt; 2.8 for tracks with p_T &gt;500&nbsp;MeV, respectively.

The parameter &xi; describing the dependence of the source radius, R, on charged-particle scaled multiplicity, m_ch, for track p_T&gt;100&nbsp;MeV and track p_T&gt;500&nbsp;MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at &radic;s = 13&nbsp;TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid and blue dashed curves represent the saturated value of the parameter &xi; for m_ch &gt; 3.0 for tracks with p_T &gt;100&nbsp;MeV and for m_ch &gt; 2.8 for tracks with p_T &gt;500&nbsp;MeV, respectively.

The parameter &xi; describing the dependence of the source radius, R, on charged-particle scaled multiplicity, m_ch, for track p_T&gt;100&nbsp;MeV and track p_T&gt;500&nbsp;MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at &radic;s = 13&nbsp;TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid and blue dashed curves represent the saturated value of the parameter &xi; for m_ch &gt; 3.0 for tracks with p_T &gt;100&nbsp;MeV and for m_ch &gt; 2.8 for tracks with p_T &gt;500&nbsp;MeV, respectively.

The parameter &kappa; describing the dependence of the source radius, R, on charged-particle scaled multiplicity, m_ch, for track p_T&gt;100&nbsp;MeV and track p_T&gt;500&nbsp;MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at &radic;s = 13&nbsp;TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid and blue dashed curves represent the exponential fit to the parameter &kappa; for tracks with p_T &gt;100&nbsp;MeV and for tracks with p_T &gt;500&nbsp;MeV, respectively.

The parameter &kappa; describing the dependence of the source radius, R, on charged-particle scaled multiplicity, m_ch, for track p_T&gt;100&nbsp;MeV and track p_T&gt;500&nbsp;MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at &radic;s = 13&nbsp;TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid and blue dashed curves represent the exponential fit to the parameter &kappa; for tracks with p_T &gt;100&nbsp;MeV and for tracks with p_T &gt;500&nbsp;MeV, respectively.

The parameter &kappa; describing the dependence of the source radius, R, on charged-particle scaled multiplicity, m_ch, for track p_T&gt;100&nbsp;MeV and track p_T&gt;500&nbsp;MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at &radic;s = 13&nbsp;TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid and blue dashed curves represent the exponential fit to the parameter &kappa; for tracks with p_T &gt;100&nbsp;MeV and for tracks with p_T &gt;500&nbsp;MeV, respectively.

The parameter &kappa; describing the dependence of the source radius, R, on charged-particle scaled multiplicity, m_ch, for track p_T&gt;100&nbsp;MeV and track p_T&gt;500&nbsp;MeV in the minimum-bias (MB) and high-multiplicity track (HMT) samples at &radic;s = 13&nbsp;TeV. The error bars and boxes represent the statistical and systematic contributions, respectively. The black solid and blue dashed curves represent the exponential fit to the parameter &kappa; for tracks with p_T &gt;100&nbsp;MeV and for tracks with p_T &gt;500&nbsp;MeV, respectively.

The two-dimensional dependence on m_ch and k_T for p_T &gt; 500&nbsp;MeV for the correlation strength, &lambda;, obtained from the exponential fit to the R₂(Q) correlation functions using the MB sample for m_ch &le; 3.08 and the HMT sample for m_ch &gt; 3.08.

The two-dimensional dependence on m_ch and k_T for p_T &gt; 500&nbsp;MeV for the source radius, R, obtained from the exponential fit to the R₂(Q) correlation functions using the MB sample for m_ch &le; 3.08 and the HMT sample for m_ch &gt; 3.08.

The parameter &lambda; for p_T &gt; 500&nbsp;MeV as a function of k_T in selected low m_ch intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter &lambda; for p_T &gt; 500&nbsp;MeV as a function of k_T in selected low m_ch intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter &lambda; for p_T &gt; 500&nbsp;MeV as a function of k_T in selected high m_ch intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter &lambda; for p_T &gt; 500&nbsp;MeV as a function of k_T in selected high m_ch intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter &lambda; for p_T &gt; 500&nbsp;MeV as a function of m_ch in k_T intervals between 0.5 and 1.5&nbsp;GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter &lambda; for p_T &gt; 500&nbsp;MeV as a function of m_ch in k_T intervals between 0.5 and 1.5&nbsp;GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter R for p_T &gt; 500&nbsp;MeV as a function of k_T in selected low m_ch intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter R for p_T &gt; 500&nbsp;MeV as a function of k_T in selected low m_ch intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter R for p_T &gt; 500&nbsp;MeV as a function of k_T in selected high m_ch intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter R for p_T &gt; 500&nbsp;MeV as a function of k_T in selected high m_ch intervals. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter R for p_T &gt; 500&nbsp;MeV as a function of m_ch in k_T intervals between 0.5 and 1.5&nbsp;GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.

The parameter R for p_T &gt; 500&nbsp;MeV as a function of m_ch in k_T intervals between 0.5 and 1.5&nbsp;GeV. The error bars and boxes represent the statistical and systematic contributions, respectively.

ATLAS and CMS results for the source radius R as a function of n_ch in pp interactions at 13&nbsp;TeV. The CMS results (open circles) have been adjusted (by the CMS collaboration) to the ATLAS kinematic region&#8758; p_T &gt; 100&nbsp;MeV and |&eta;|&lt;2.5. The ATLAS uncertainties are the sum in quadrature of the statistical and asymmetric systematic uncertainties. For CMS, only the systematic uncertainties are shown since the statistical uncertainties are smaller than the marker size. The dashed blue (ATLAS) and black (CMS) lines represent the fit to &#8731;n_ch at low multiplicity, continued as dotted lines beyond the fit range. The solid green (ATLAS) and broken black (CMS) lines indicate the plateau level at high multiplicity.

ATLAS and CMS results for the source radius R as a function of n_ch in pp interactions at 13&nbsp;TeV. The CMS results (open circles) have been adjusted (by the CMS collaboration) to the ATLAS kinematic region&#8758; p_T &gt; 100&nbsp;MeV and |&eta;|&lt;2.5. The ATLAS uncertainties are the sum in quadrature of the statistical and asymmetric systematic uncertainties. For CMS, only the systematic uncertainties are shown since the statistical uncertainties are smaller than the marker size. The dashed blue (ATLAS) and black (CMS) lines represent the fit to &#8731;n_ch at low multiplicity, continued as dotted lines beyond the fit range. The solid green (ATLAS) and broken black (CMS) lines indicate the plateau level at high multiplicity.

ATLAS and CMS results for the source radius R as a function of n_ch in pp interactions at 13&nbsp;TeV. The CMS results (open circles) have been adjusted (by the CMS collaboration) to the ATLAS kinematic region&#8758; p_T &gt; 100&nbsp;MeV and |&eta;|&lt;2.5. The ATLAS uncertainties are the sum in quadrature of the statistical and asymmetric systematic uncertainties. For CMS, only the systematic uncertainties are shown since the statistical uncertainties are smaller than the marker size. The dashed blue (ATLAS) and black (CMS) lines represent the fit to &#8731;n_ch at low multiplicity, continued as dotted lines beyond the fit range. The solid green (ATLAS) and broken black (CMS) lines indicate the plateau level at high multiplicity.

ATLAS and CMS results for the source radius R as a function of &#8731;n_ch in pp interactions at 13&nbsp;TeV. The CMS results (open circles) have been adjusted (by the CMS collaboration) to the ATLAS kinematic region&#8758; p_T &gt; 100&nbsp;MeV and |&eta;|&lt;2.5. The ATLAS uncertainties are the sum in quadrature of the statistical and asymmetric systematic uncertainties. For CMS, only the systematic uncertainties are shown since the statistical uncertainties are smaller than the marker size. The dashed blue (ATLAS) and black (CMS) lines represent the fit to &#8731;n_ch at low multiplicity, continued as dotted lines beyond the fit range. The solid green (ATLAS) and broken black (CMS) lines indicate the plateau level at high multiplicity.

ATLAS and CMS results for the source radius R as a function of &#8731;n_ch in pp interactions at 13&nbsp;TeV. The CMS results (open circles) have been adjusted (by the CMS collaboration) to the ATLAS kinematic region&#8758; p_T &gt; 100&nbsp;MeV and |&eta;|&lt;2.5. The ATLAS uncertainties are the sum in quadrature of the statistical and asymmetric systematic uncertainties. For CMS, only the systematic uncertainties are shown since the statistical uncertainties are smaller than the marker size. The dashed blue (ATLAS) and black (CMS) lines represent the fit to &#8731;n_ch at low multiplicity, continued as dotted lines beyond the fit range. The solid green (ATLAS) and broken black (CMS) lines indicate the plateau level at high multiplicity.

ATLAS and CMS results for the source radius R as a function of &#8731;n_ch in pp interactions at 13&nbsp;TeV. The CMS results (open circles) have been adjusted (by the CMS collaboration) to the ATLAS kinematic region&#8758; p_T &gt; 100&nbsp;MeV and |&eta;|&lt;2.5. The ATLAS uncertainties are the sum in quadrature of the statistical and asymmetric systematic uncertainties. For CMS, only the systematic uncertainties are shown since the statistical uncertainties are smaller than the marker size. The dashed blue (ATLAS) and black (CMS) lines represent the fit to &#8731;n_ch at low multiplicity, continued as dotted lines beyond the fit range. The solid green (ATLAS) and broken black (CMS) lines indicate the plateau level at high multiplicity.

Systematic uncertainties (in percent) in the correlation strength, &lambda;, and source radius, R, for the exponential fit of the two-particle double-ratio correlation functions, R₂(Q), for p_T &gt; 100&nbsp;MeV at &radic;s= 13&nbsp;TeV for the MB and HMT events. The choice of MC generator gives rise to asymmetric uncertainties, denoted by uparrow and downarrow. This asymmetry propagates through to the cumulative uncertainty. The columns under ‘Uncertainty range’ show the range of systematic uncertainty from the fits in the various n_ch intervals.

The results of the fits to the dependencies of the correlation strength, &lambda;, and source radius, R, on the average rescaled charged-particle multiplicity, m_ch, for |&eta;| &lt; 2.5 and both p_T &gt; 100&nbsp;MeV and p_T &gt; 500&nbsp;MeV at &radic;s = 13&nbsp;TeV for the minimum-bias (MB) and the high-multiplicity track (HMT) events. The parameters &gamma; and &delta; resulting from a joint fit to the MB and HMT data are presented. The total uncertainties are shown.

The results of the fits to the dependencies of the correlation strength, &lambda;, and source radius, R, on the pair average transverse momentum, k_T, for various functional forms and for minimum-bias (MB) and high-multiplicity track (HMT) events for p_T &gt; 100&nbsp;MeV and p_T &gt; 500&nbsp;MeV at &radic;s = 13&nbsp;TeV. The total uncertainties are shown.

The Bose-Einstein correlation (BEC) parameters &lambda; and R as a function of n_ch and k_T using different MC generators in the calculation of R₂(Q). (a) &lambda; versus n_ch for MB events, (b) &lambda; versus n_ch for HMT events, (c) &lambda; versus k_T and (d) R versus k_T for MB events. The uncertainties shown are statistical. The lower panel of each plot shows the ratio of the BEC parameters obtained using EPOS LHC (red circles), Pythia 8 Monash (blue squares) and Herwig++ UE-EE-5 (green triangles) compared with the parameters obtained using Pythia 8 A2. The gray band in the lower panels is the MC systematic uncertainty, obtained as explained in the text.

The Bose-Einstein correlation (BEC) parameters &lambda; and R as a function of n_ch and k_T using different MC generators in the calculation of R₂(Q). (a) &lambda; versus n_ch for MB events, (b) &lambda; versus n_ch for HMT events, (c) &lambda; versus k_T and (d) R versus k_T for MB events. The uncertainties shown are statistical. The lower panel of each plot shows the ratio of the BEC parameters obtained using EPOS LHC (red circles), Pythia 8 Monash (blue squares) and Herwig++ UE-EE-5 (green triangles) compared with the parameters obtained using Pythia 8 A2. The gray band in the lower panels is the MC systematic uncertainty, obtained as explained in the text.

The Bose-Einstein correlation (BEC) parameters &lambda; and R as a function of n_ch and k_T using different MC generators in the calculation of R₂(Q). (a) &lambda; versus n_ch for MB events, (b) &lambda; versus n_ch for HMT events, (c) &lambda; versus k_T and (d) R versus k_T for MB events. The uncertainties shown are statistical. The lower panel of each plot shows the ratio of the BEC parameters obtained using EPOS LHC (red circles), Pythia 8 Monash (blue squares) and Herwig++ UE-EE-5 (green triangles) compared with the parameters obtained using Pythia 8 A2. The gray band in the lower panels is the MC systematic uncertainty, obtained as explained in the text.

The Bose-Einstein correlation (BEC) parameters &lambda; and R as a function of n_ch and k_T using different MC generators in the calculation of R₂(Q). (a) &lambda; versus n_ch for MB events, (b) &lambda; versus n_ch for HMT events, (c) &lambda; versus k_T and (d) R versus k_T for MB events. The uncertainties shown are statistical. The lower panel of each plot shows the ratio of the BEC parameters obtained using EPOS LHC (red circles), Pythia 8 Monash (blue squares) and Herwig++ UE-EE-5 (green triangles) compared with the parameters obtained using Pythia 8 A2. The gray band in the lower panels is the MC systematic uncertainty, obtained as explained in the text.

The single-ratio two-particle correlation functions, C₂^data(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals&#8758; (a) 2 &lt; n_ch &le; 10, (b) 11 &lt; n_ch &le; 20, (c) 21 &lt; n_ch &le; 30, (d) 31 &lt; n_ch &le; 40, (e) 41 &lt; n_ch &le; 50, (f) 51 &lt; n_ch &le; 60, (g) 61 &lt; n_ch &le; 70, (h) 71 &lt; n_ch &le; 80 and (i) 81 &lt; n_ch &le; 90. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals&#8758; (a) 2 &lt; n_ch &le; 10, (b) 11 &lt; n_ch &le; 20, (c) 21 &lt; n_ch &le; 30, (d) 31 &lt; n_ch &le; 40, (e) 41 &lt; n_ch &le; 50, (f) 51 &lt; n_ch &le; 60, (g) 61 &lt; n_ch &le; 70, (h) 71 &lt; n_ch &le; 80 and (i) 81 &lt; n_ch &le; 90. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals&#8758; (a) 2 &lt; n_ch &le; 10, (b) 11 &lt; n_ch &le; 20, (c) 21 &lt; n_ch &le; 30, (d) 31 &lt; n_ch &le; 40, (e) 41 &lt; n_ch &le; 50, (f) 51 &lt; n_ch &le; 60, (g) 61 &lt; n_ch &le; 70, (h) 71 &lt; n_ch &le; 80 and (i) 81 &lt; n_ch &le; 90. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals&#8758; (a) 2 &lt; n_ch &le; 10, (b) 11 &lt; n_ch &le; 20, (c) 21 &lt; n_ch &le; 30, (d) 31 &lt; n_ch &le; 40, (e) 41 &lt; n_ch &le; 50, (f) 51 &lt; n_ch &le; 60, (g) 61 &lt; n_ch &le; 70, (h) 71 &lt; n_ch &le; 80 and (i) 81 &lt; n_ch &le; 90. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals&#8758; (a) 2 &lt; n_ch &le; 10, (b) 11 &lt; n_ch &le; 20, (c) 21 &lt; n_ch &le; 30, (d) 31 &lt; n_ch &le; 40, (e) 41 &lt; n_ch &le; 50, (f) 51 &lt; n_ch &le; 60, (g) 61 &lt; n_ch &le; 70, (h) 71 &lt; n_ch &le; 80 and (i) 81 &lt; n_ch &le; 90. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals&#8758; (a) 2 &lt; n_ch &le; 10, (b) 11 &lt; n_ch &le; 20, (c) 21 &lt; n_ch &le; 30, (d) 31 &lt; n_ch &le; 40, (e) 41 &lt; n_ch &le; 50, (f) 51 &lt; n_ch &le; 60, (g) 61 &lt; n_ch &le; 70, (h) 71 &lt; n_ch &le; 80 and (i) 81 &lt; n_ch &le; 90. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals&#8758; (a) 2 &lt; n_ch &le; 10, (b) 11 &lt; n_ch &le; 20, (c) 21 &lt; n_ch &le; 30, (d) 31 &lt; n_ch &le; 40, (e) 41 &lt; n_ch &le; 50, (f) 51 &lt; n_ch &le; 60, (g) 61 &lt; n_ch &le; 70, (h) 71 &lt; n_ch &le; 80 and (i) 81 &lt; n_ch &le; 90. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals&#8758; (a) 2 &lt; n_ch &le; 10, (b) 11 &lt; n_ch &le; 20, (c) 21 &lt; n_ch &le; 30, (d) 31 &lt; n_ch &le; 40, (e) 41 &lt; n_ch &le; 50, (f) 51 &lt; n_ch &le; 60, (g) 61 &lt; n_ch &le; 70, (h) 71 &lt; n_ch &le; 80 and (i) 81 &lt; n_ch &le; 90. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals&#8758; (a) 2 &lt; n_ch &le; 10, (b) 11 &lt; n_ch &le; 20, (c) 21 &lt; n_ch &le; 30, (d) 31 &lt; n_ch &le; 40, (e) 41 &lt; n_ch &le; 50, (f) 51 &lt; n_ch &le; 60, (g) 61 &lt; n_ch &le; 70, (h) 71 &lt; n_ch &le; 80 and (i) 81 &lt; n_ch &le; 90. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals&#8758; (a) 91 &lt; n_ch &le; 100, (b) 101 &lt; n_ch &le; 125, (c) 126 &lt; n_ch &le; 150, (d) 151 &lt; n_ch &le; 200, (e) 201 &lt; n_ch &le; 250. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals&#8758; (a) 91 &lt; n_ch &le; 100, (b) 101 &lt; n_ch &le; 125, (c) 126 &lt; n_ch &le; 150, (d) 151 &lt; n_ch &le; 200, (e) 201 &lt; n_ch &le; 250. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals&#8758; (a) 91 &lt; n_ch &le; 100, (b) 101 &lt; n_ch &le; 125, (c) 126 &lt; n_ch &le; 150, (d) 151 &lt; n_ch &le; 200, (e) 201 &lt; n_ch &le; 250. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals&#8758; (a) 91 &lt; n_ch &le; 100, (b) 101 &lt; n_ch &le; 125, (c) 126 &lt; n_ch &le; 150, (d) 151 &lt; n_ch &le; 200, (e) 201 &lt; n_ch &le; 250. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals&#8758; (a) 91 &lt; n_ch &le; 100, (b) 101 &lt; n_ch &le; 125, (c) 126 &lt; n_ch &le; 150, (d) 151 &lt; n_ch &le; 200, (e) 201 &lt; n_ch &le; 250. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals&#8758; (a) 101 &lt; n_ch &le; 110, (b) 111 &lt; n_ch &le; 120, (c) 121 &lt; n_ch &le; 130, (d) 131 &lt; n_ch &le; 140, (e) 141 &lt; n_ch &le; 155, (f) 156 &lt; n_ch &le; 175, (g) 176 &lt; n_ch &le; 200, (h) 201 &lt; n_ch &le; 230 and (i) 231 &lt; n_ch &le; 300. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals&#8758; (a) 101 &lt; n_ch &le; 110, (b) 111 &lt; n_ch &le; 120, (c) 121 &lt; n_ch &le; 130, (d) 131 &lt; n_ch &le; 140, (e) 141 &lt; n_ch &le; 155, (f) 156 &lt; n_ch &le; 175, (g) 176 &lt; n_ch &le; 200, (h) 201 &lt; n_ch &le; 230 and (i) 231 &lt; n_ch &le; 300. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals&#8758; (a) 101 &lt; n_ch &le; 110, (b) 111 &lt; n_ch &le; 120, (c) 121 &lt; n_ch &le; 130, (d) 131 &lt; n_ch &le; 140, (e) 141 &lt; n_ch &le; 155, (f) 156 &lt; n_ch &le; 175, (g) 176 &lt; n_ch &le; 200, (h) 201 &lt; n_ch &le; 230 and (i) 231 &lt; n_ch &le; 300. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals&#8758; (a) 101 &lt; n_ch &le; 110, (b) 111 &lt; n_ch &le; 120, (c) 121 &lt; n_ch &le; 130, (d) 131 &lt; n_ch &le; 140, (e) 141 &lt; n_ch &le; 155, (f) 156 &lt; n_ch &le; 175, (g) 176 &lt; n_ch &le; 200, (h) 201 &lt; n_ch &le; 230 and (i) 231 &lt; n_ch &le; 300. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals&#8758; (a) 101 &lt; n_ch &le; 110, (b) 111 &lt; n_ch &le; 120, (c) 121 &lt; n_ch &le; 130, (d) 131 &lt; n_ch &le; 140, (e) 141 &lt; n_ch &le; 155, (f) 156 &lt; n_ch &le; 175, (g) 176 &lt; n_ch &le; 200, (h) 201 &lt; n_ch &le; 230 and (i) 231 &lt; n_ch &le; 300. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals&#8758; (a) 101 &lt; n_ch &le; 110, (b) 111 &lt; n_ch &le; 120, (c) 121 &lt; n_ch &le; 130, (d) 131 &lt; n_ch &le; 140, (e) 141 &lt; n_ch &le; 155, (f) 156 &lt; n_ch &le; 175, (g) 176 &lt; n_ch &le; 200, (h) 201 &lt; n_ch &le; 230 and (i) 231 &lt; n_ch &le; 300. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals&#8758; (a) 101 &lt; n_ch &le; 110, (b) 111 &lt; n_ch &le; 120, (c) 121 &lt; n_ch &le; 130, (d) 131 &lt; n_ch &le; 140, (e) 141 &lt; n_ch &le; 155, (f) 156 &lt; n_ch &le; 175, (g) 176 &lt; n_ch &le; 200, (h) 201 &lt; n_ch &le; 230 and (i) 231 &lt; n_ch &le; 300. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals&#8758; (a) 101 &lt; n_ch &le; 110, (b) 111 &lt; n_ch &le; 120, (c) 121 &lt; n_ch &le; 130, (d) 131 &lt; n_ch &le; 140, (e) 141 &lt; n_ch &le; 155, (f) 156 &lt; n_ch &le; 175, (g) 176 &lt; n_ch &le; 200, (h) 201 &lt; n_ch &le; 230 and (i) 231 &lt; n_ch &le; 300. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals&#8758; (a) 101 &lt; n_ch &le; 110, (b) 111 &lt; n_ch &le; 120, (c) 121 &lt; n_ch &le; 130, (d) 131 &lt; n_ch &le; 140, (e) 141 &lt; n_ch &le; 155, (f) 156 &lt; n_ch &le; 175, (g) 176 &lt; n_ch &le; 200, (h) 201 &lt; n_ch &le; 230 and (i) 231 &lt; n_ch &le; 300. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k_T - intervals&#8758; (a) 100 &lt; k_T &le; 200&nbsp;MeV, (b) 200 &lt; k_T &le; 300&nbsp;MeV, (c) 300 &lt; k_T &le; 400&nbsp;MeV, (d) 400 &lt; k_T &le; 500&nbsp;MeV, (e) 500 &lt; k_T &le; 600&nbsp;MeV, (f) 600 &lt; k_T &le; 700&nbsp;MeV, (g) 700 &lt; k_T &le; 1000&nbsp;MeV, and (h) 1000 &lt; k_T &le; 1500&nbsp;MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k_T - intervals&#8758; (a) 100 &lt; k_T &le; 200&nbsp;MeV, (b) 200 &lt; k_T &le; 300&nbsp;MeV, (c) 300 &lt; k_T &le; 400&nbsp;MeV, (d) 400 &lt; k_T &le; 500&nbsp;MeV, (e) 500 &lt; k_T &le; 600&nbsp;MeV, (f) 600 &lt; k_T &le; 700&nbsp;MeV, (g) 700 &lt; k_T &le; 1000&nbsp;MeV, and (h) 1000 &lt; k_T &le; 1500&nbsp;MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k_T - intervals&#8758; (a) 100 &lt; k_T &le; 200&nbsp;MeV, (b) 200 &lt; k_T &le; 300&nbsp;MeV, (c) 300 &lt; k_T &le; 400&nbsp;MeV, (d) 400 &lt; k_T &le; 500&nbsp;MeV, (e) 500 &lt; k_T &le; 600&nbsp;MeV, (f) 600 &lt; k_T &le; 700&nbsp;MeV, (g) 700 &lt; k_T &le; 1000&nbsp;MeV, and (h) 1000 &lt; k_T &le; 1500&nbsp;MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k_T - intervals&#8758; (a) 100 &lt; k_T &le; 200&nbsp;MeV, (b) 200 &lt; k_T &le; 300&nbsp;MeV, (c) 300 &lt; k_T &le; 400&nbsp;MeV, (d) 400 &lt; k_T &le; 500&nbsp;MeV, (e) 500 &lt; k_T &le; 600&nbsp;MeV, (f) 600 &lt; k_T &le; 700&nbsp;MeV, (g) 700 &lt; k_T &le; 1000&nbsp;MeV, and (h) 1000 &lt; k_T &le; 1500&nbsp;MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k_T - intervals&#8758; (a) 100 &lt; k_T &le; 200&nbsp;MeV, (b) 200 &lt; k_T &le; 300&nbsp;MeV, (c) 300 &lt; k_T &le; 400&nbsp;MeV, (d) 400 &lt; k_T &le; 500&nbsp;MeV, (e) 500 &lt; k_T &le; 600&nbsp;MeV, (f) 600 &lt; k_T &le; 700&nbsp;MeV, (g) 700 &lt; k_T &le; 1000&nbsp;MeV, and (h) 1000 &lt; k_T &le; 1500&nbsp;MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k_T - intervals&#8758; (a) 100 &lt; k_T &le; 200&nbsp;MeV, (b) 200 &lt; k_T &le; 300&nbsp;MeV, (c) 300 &lt; k_T &le; 400&nbsp;MeV, (d) 400 &lt; k_T &le; 500&nbsp;MeV, (e) 500 &lt; k_T &le; 600&nbsp;MeV, (f) 600 &lt; k_T &le; 700&nbsp;MeV, (g) 700 &lt; k_T &le; 1000&nbsp;MeV, and (h) 1000 &lt; k_T &le; 1500&nbsp;MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k_T - intervals&#8758; (a) 100 &lt; k_T &le; 200&nbsp;MeV, (b) 200 &lt; k_T &le; 300&nbsp;MeV, (c) 300 &lt; k_T &le; 400&nbsp;MeV, (d) 400 &lt; k_T &le; 500&nbsp;MeV, (e) 500 &lt; k_T &le; 600&nbsp;MeV, (f) 600 &lt; k_T &le; 700&nbsp;MeV, (g) 700 &lt; k_T &le; 1000&nbsp;MeV, and (h) 1000 &lt; k_T &le; 1500&nbsp;MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k_T - intervals&#8758; (a) 100 &lt; k_T &le; 200&nbsp;MeV, (b) 200 &lt; k_T &le; 300&nbsp;MeV, (c) 300 &lt; k_T &le; 400&nbsp;MeV, (d) 400 &lt; k_T &le; 500&nbsp;MeV, (e) 500 &lt; k_T &le; 600&nbsp;MeV, (f) 600 &lt; k_T &le; 700&nbsp;MeV, (g) 700 &lt; k_T &le; 1000&nbsp;MeV, and (h) 1000 &lt; k_T &le; 1500&nbsp;MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for k_T - intervals&#8758; (a) 100 &lt; k_T &le; 200&nbsp;MeV, (b) 200 &lt; k_T &le; 300&nbsp;MeV, (c) 300 &lt; k_T &le; 400&nbsp;MeV, (d) 400 &lt; k_T &le; 500&nbsp;MeV, (e) 500 &lt; k_T &le; 600&nbsp;MeV, (f) 600 &lt; k_T &le; 700&nbsp;MeV, (g) 700 &lt; k_T &le; 1000&nbsp;MeV, and (h) 1000 &lt; k_T &le; 1500&nbsp;MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for k_T - intervals&#8758; (a) 100 &lt; k_T &le; 200&nbsp;MeV, (b) 200 &lt; k_T &le; 300&nbsp;MeV, (c) 300 &lt; k_T &le; 400&nbsp;MeV, (d) 400 &lt; k_T &le; 500&nbsp;MeV, (e) 500 &lt; k_T &le; 600&nbsp;MeV, (f) 600 &lt; k_T &le; 700&nbsp;MeV, (g) 700 &lt; k_T &le; 1000&nbsp;MeV, and (h) 1000 &lt; k_T &le; 1500&nbsp;MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for k_T - intervals&#8758; (a) 100 &lt; k_T &le; 200&nbsp;MeV, (b) 200 &lt; k_T &le; 300&nbsp;MeV, (c) 300 &lt; k_T &le; 400&nbsp;MeV, (d) 400 &lt; k_T &le; 500&nbsp;MeV, (e) 500 &lt; k_T &le; 600&nbsp;MeV, (f) 600 &lt; k_T &le; 700&nbsp;MeV, (g) 700 &lt; k_T &le; 1000&nbsp;MeV, and (h) 1000 &lt; k_T &le; 1500&nbsp;MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for k_T - intervals&#8758; (a) 100 &lt; k_T &le; 200&nbsp;MeV, (b) 200 &lt; k_T &le; 300&nbsp;MeV, (c) 300 &lt; k_T &le; 400&nbsp;MeV, (d) 400 &lt; k_T &le; 500&nbsp;MeV, (e) 500 &lt; k_T &le; 600&nbsp;MeV, (f) 600 &lt; k_T &le; 700&nbsp;MeV, (g) 700 &lt; k_T &le; 1000&nbsp;MeV, and (h) 1000 &lt; k_T &le; 1500&nbsp;MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for k_T - intervals&#8758; (a) 100 &lt; k_T &le; 200&nbsp;MeV, (b) 200 &lt; k_T &le; 300&nbsp;MeV, (c) 300 &lt; k_T &le; 400&nbsp;MeV, (d) 400 &lt; k_T &le; 500&nbsp;MeV, (e) 500 &lt; k_T &le; 600&nbsp;MeV, (f) 600 &lt; k_T &le; 700&nbsp;MeV, (g) 700 &lt; k_T &le; 1000&nbsp;MeV, and (h) 1000 &lt; k_T &le; 1500&nbsp;MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for k_T - intervals&#8758; (a) 100 &lt; k_T &le; 200&nbsp;MeV, (b) 200 &lt; k_T &le; 300&nbsp;MeV, (c) 300 &lt; k_T &le; 400&nbsp;MeV, (d) 400 &lt; k_T &le; 500&nbsp;MeV, (e) 500 &lt; k_T &le; 600&nbsp;MeV, (f) 600 &lt; k_T &le; 700&nbsp;MeV, (g) 700 &lt; k_T &le; 1000&nbsp;MeV, and (h) 1000 &lt; k_T &le; 1500&nbsp;MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for k_T - intervals&#8758; (a) 100 &lt; k_T &le; 200&nbsp;MeV, (b) 200 &lt; k_T &le; 300&nbsp;MeV, (c) 300 &lt; k_T &le; 400&nbsp;MeV, (d) 400 &lt; k_T &le; 500&nbsp;MeV, (e) 500 &lt; k_T &le; 600&nbsp;MeV, (f) 600 &lt; k_T &le; 700&nbsp;MeV, (g) 700 &lt; k_T &le; 1000&nbsp;MeV, and (h) 1000 &lt; k_T &le; 1500&nbsp;MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), for the high-multiplicity track (HMT) events using the unlike-charge particle (UCP) pairs reference sample for k_T - intervals&#8758; (a) 100 &lt; k_T &le; 200&nbsp;MeV, (b) 200 &lt; k_T &le; 300&nbsp;MeV, (c) 300 &lt; k_T &le; 400&nbsp;MeV, (d) 400 &lt; k_T &le; 500&nbsp;MeV, (e) 500 &lt; k_T &le; 600&nbsp;MeV, (f) 600 &lt; k_T &le; 700&nbsp;MeV, (g) 700 &lt; k_T &le; 1000&nbsp;MeV, and (h) 1000 &lt; k_T &le; 1500&nbsp;MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals&#8758; (a) 2 &lt; n_ch &le; 9, (b) 10 &lt; n_ch &le; 18, (c) 19 &lt; n_ch &le; 27, (d) 28 &lt; n_ch &le; 36, (e) 37 &lt; n_ch &le; 45, (f) 46 &lt; n_ch &le; 54, (g) 55 &lt; n_ch &le; 63, (h) 64 &lt; n_ch &le; 72, (i) 73 &lt; n_ch &le; 81, (j) 82 &lt; n_ch &le; 90, (k) 91 &lt; n_ch &le; 113, and (l) 114 &lt; n_ch &le; 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals&#8758; (a) 2 &lt; n_ch &le; 9, (b) 10 &lt; n_ch &le; 18, (c) 19 &lt; n_ch &le; 27, (d) 28 &lt; n_ch &le; 36, (e) 37 &lt; n_ch &le; 45, (f) 46 &lt; n_ch &le; 54, (g) 55 &lt; n_ch &le; 63, (h) 64 &lt; n_ch &le; 72, (i) 73 &lt; n_ch &le; 81, (j) 82 &lt; n_ch &le; 90, (k) 91 &lt; n_ch &le; 113, and (l) 114 &lt; n_ch &le; 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals&#8758; (a) 2 &lt; n_ch &le; 9, (b) 10 &lt; n_ch &le; 18, (c) 19 &lt; n_ch &le; 27, (d) 28 &lt; n_ch &le; 36, (e) 37 &lt; n_ch &le; 45, (f) 46 &lt; n_ch &le; 54, (g) 55 &lt; n_ch &le; 63, (h) 64 &lt; n_ch &le; 72, (i) 73 &lt; n_ch &le; 81, (j) 82 &lt; n_ch &le; 90, (k) 91 &lt; n_ch &le; 113, and (l) 114 &lt; n_ch &le; 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals&#8758; (a) 2 &lt; n_ch &le; 9, (b) 10 &lt; n_ch &le; 18, (c) 19 &lt; n_ch &le; 27, (d) 28 &lt; n_ch &le; 36, (e) 37 &lt; n_ch &le; 45, (f) 46 &lt; n_ch &le; 54, (g) 55 &lt; n_ch &le; 63, (h) 64 &lt; n_ch &le; 72, (i) 73 &lt; n_ch &le; 81, (j) 82 &lt; n_ch &le; 90, (k) 91 &lt; n_ch &le; 113, and (l) 114 &lt; n_ch &le; 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals&#8758; (a) 2 &lt; n_ch &le; 9, (b) 10 &lt; n_ch &le; 18, (c) 19 &lt; n_ch &le; 27, (d) 28 &lt; n_ch &le; 36, (e) 37 &lt; n_ch &le; 45, (f) 46 &lt; n_ch &le; 54, (g) 55 &lt; n_ch &le; 63, (h) 64 &lt; n_ch &le; 72, (i) 73 &lt; n_ch &le; 81, (j) 82 &lt; n_ch &le; 90, (k) 91 &lt; n_ch &le; 113, and (l) 114 &lt; n_ch &le; 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals&#8758; (a) 2 &lt; n_ch &le; 9, (b) 10 &lt; n_ch &le; 18, (c) 19 &lt; n_ch &le; 27, (d) 28 &lt; n_ch &le; 36, (e) 37 &lt; n_ch &le; 45, (f) 46 &lt; n_ch &le; 54, (g) 55 &lt; n_ch &le; 63, (h) 64 &lt; n_ch &le; 72, (i) 73 &lt; n_ch &le; 81, (j) 82 &lt; n_ch &le; 90, (k) 91 &lt; n_ch &le; 113, and (l) 114 &lt; n_ch &le; 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals&#8758; (a) 2 &lt; n_ch &le; 9, (b) 10 &lt; n_ch &le; 18, (c) 19 &lt; n_ch &le; 27, (d) 28 &lt; n_ch &le; 36, (e) 37 &lt; n_ch &le; 45, (f) 46 &lt; n_ch &le; 54, (g) 55 &lt; n_ch &le; 63, (h) 64 &lt; n_ch &le; 72, (i) 73 &lt; n_ch &le; 81, (j) 82 &lt; n_ch &le; 90, (k) 91 &lt; n_ch &le; 113, and (l) 114 &lt; n_ch &le; 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals&#8758; (a) 2 &lt; n_ch &le; 9, (b) 10 &lt; n_ch &le; 18, (c) 19 &lt; n_ch &le; 27, (d) 28 &lt; n_ch &le; 36, (e) 37 &lt; n_ch &le; 45, (f) 46 &lt; n_ch &le; 54, (g) 55 &lt; n_ch &le; 63, (h) 64 &lt; n_ch &le; 72, (i) 73 &lt; n_ch &le; 81, (j) 82 &lt; n_ch &le; 90, (k) 91 &lt; n_ch &le; 113, and (l) 114 &lt; n_ch &le; 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals&#8758; (a) 2 &lt; n_ch &le; 9, (b) 10 &lt; n_ch &le; 18, (c) 19 &lt; n_ch &le; 27, (d) 28 &lt; n_ch &le; 36, (e) 37 &lt; n_ch &le; 45, (f) 46 &lt; n_ch &le; 54, (g) 55 &lt; n_ch &le; 63, (h) 64 &lt; n_ch &le; 72, (i) 73 &lt; n_ch &le; 81, (j) 82 &lt; n_ch &le; 90, (k) 91 &lt; n_ch &le; 113, and (l) 114 &lt; n_ch &le; 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals&#8758; (a) 2 &lt; n_ch &le; 9, (b) 10 &lt; n_ch &le; 18, (c) 19 &lt; n_ch &le; 27, (d) 28 &lt; n_ch &le; 36, (e) 37 &lt; n_ch &le; 45, (f) 46 &lt; n_ch &le; 54, (g) 55 &lt; n_ch &le; 63, (h) 64 &lt; n_ch &le; 72, (i) 73 &lt; n_ch &le; 81, (j) 82 &lt; n_ch &le; 90, (k) 91 &lt; n_ch &le; 113, and (l) 114 &lt; n_ch &le; 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals&#8758; (a) 2 &lt; n_ch &le; 9, (b) 10 &lt; n_ch &le; 18, (c) 19 &lt; n_ch &le; 27, (d) 28 &lt; n_ch &le; 36, (e) 37 &lt; n_ch &le; 45, (f) 46 &lt; n_ch &le; 54, (g) 55 &lt; n_ch &le; 63, (h) 64 &lt; n_ch &le; 72, (i) 73 &lt; n_ch &le; 81, (j) 82 &lt; n_ch &le; 90, (k) 91 &lt; n_ch &le; 113, and (l) 114 &lt; n_ch &le; 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample for n_ch - intervals&#8758; (a) 2 &lt; n_ch &le; 9, (b) 10 &lt; n_ch &le; 18, (c) 19 &lt; n_ch &le; 27, (d) 28 &lt; n_ch &le; 36, (e) 37 &lt; n_ch &le; 45, (f) 46 &lt; n_ch &le; 54, (g) 55 &lt; n_ch &le; 63, (h) 64 &lt; n_ch &le; 72, (i) 73 &lt; n_ch &le; 81, (j) 82 &lt; n_ch &le; 90, (k) 91 &lt; n_ch &le; 113, and (l) 114 &lt; n_ch &le; 136. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k_T - intervals&#8758; (a) 100 &lt; k_T &le; 200&nbsp;MeV, (b) 200 &lt; k_T &le; 300&nbsp;MeV, (c) 300 &lt; k_T &le; 400&nbsp;MeV, (d) 400 &lt; k_T &le; 500&nbsp;MeV, (e) 500 &lt; k_T &le; 600&nbsp;MeV, (f) 600 &lt; k_T &le; 700&nbsp;MeV, (g) 700 &lt; k_T &le; 1000&nbsp;MeV, and (h) 1000 &lt; k_T &le; 1500&nbsp;MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k_T - intervals&#8758; (a) 100 &lt; k_T &le; 200&nbsp;MeV, (b) 200 &lt; k_T &le; 300&nbsp;MeV, (c) 300 &lt; k_T &le; 400&nbsp;MeV, (d) 400 &lt; k_T &le; 500&nbsp;MeV, (e) 500 &lt; k_T &le; 600&nbsp;MeV, (f) 600 &lt; k_T &le; 700&nbsp;MeV, (g) 700 &lt; k_T &le; 1000&nbsp;MeV, and (h) 1000 &lt; k_T &le; 1500&nbsp;MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k_T - intervals&#8758; (a) 100 &lt; k_T &le; 200&nbsp;MeV, (b) 200 &lt; k_T &le; 300&nbsp;MeV, (c) 300 &lt; k_T &le; 400&nbsp;MeV, (d) 400 &lt; k_T &le; 500&nbsp;MeV, (e) 500 &lt; k_T &le; 600&nbsp;MeV, (f) 600 &lt; k_T &le; 700&nbsp;MeV, (g) 700 &lt; k_T &le; 1000&nbsp;MeV, and (h) 1000 &lt; k_T &le; 1500&nbsp;MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k_T - intervals&#8758; (a) 100 &lt; k_T &le; 200&nbsp;MeV, (b) 200 &lt; k_T &le; 300&nbsp;MeV, (c) 300 &lt; k_T &le; 400&nbsp;MeV, (d) 400 &lt; k_T &le; 500&nbsp;MeV, (e) 500 &lt; k_T &le; 600&nbsp;MeV, (f) 600 &lt; k_T &le; 700&nbsp;MeV, (g) 700 &lt; k_T &le; 1000&nbsp;MeV, and (h) 1000 &lt; k_T &le; 1500&nbsp;MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k_T - intervals&#8758; (a) 100 &lt; k_T &le; 200&nbsp;MeV, (b) 200 &lt; k_T &le; 300&nbsp;MeV, (c) 300 &lt; k_T &le; 400&nbsp;MeV, (d) 400 &lt; k_T &le; 500&nbsp;MeV, (e) 500 &lt; k_T &le; 600&nbsp;MeV, (f) 600 &lt; k_T &le; 700&nbsp;MeV, (g) 700 &lt; k_T &le; 1000&nbsp;MeV, and (h) 1000 &lt; k_T &le; 1500&nbsp;MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k_T - intervals&#8758; (a) 100 &lt; k_T &le; 200&nbsp;MeV, (b) 200 &lt; k_T &le; 300&nbsp;MeV, (c) 300 &lt; k_T &le; 400&nbsp;MeV, (d) 400 &lt; k_T &le; 500&nbsp;MeV, (e) 500 &lt; k_T &le; 600&nbsp;MeV, (f) 600 &lt; k_T &le; 700&nbsp;MeV, (g) 700 &lt; k_T &le; 1000&nbsp;MeV, and (h) 1000 &lt; k_T &le; 1500&nbsp;MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k_T - intervals&#8758; (a) 100 &lt; k_T &le; 200&nbsp;MeV, (b) 200 &lt; k_T &le; 300&nbsp;MeV, (c) 300 &lt; k_T &le; 400&nbsp;MeV, (d) 400 &lt; k_T &le; 500&nbsp;MeV, (e) 500 &lt; k_T &le; 600&nbsp;MeV, (f) 600 &lt; k_T &le; 700&nbsp;MeV, (g) 700 &lt; k_T &le; 1000&nbsp;MeV, and (h) 1000 &lt; k_T &le; 1500&nbsp;MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The single-ratio two-particle correlation functions, C₂^data(Q), at 7 TeV for the minimum-bias (MB) events using the unlike-charge particle (UCP) pairs reference sample k_T - intervals&#8758; (a) 100 &lt; k_T &le; 200&nbsp;MeV, (b) 200 &lt; k_T &le; 300&nbsp;MeV, (c) 300 &lt; k_T &le; 400&nbsp;MeV, (d) 400 &lt; k_T &le; 500&nbsp;MeV, (e) 500 &lt; k_T &le; 600&nbsp;MeV, (f) 600 &lt; k_T &le; 700&nbsp;MeV, (g) 700 &lt; k_T &le; 1000&nbsp;MeV, and (h) 1000 &lt; k_T &le; 1500&nbsp;MeV. The error bars represent the statistical uncertainties. The boxes represent the systematic uncertainties, which are the sum in quadrature of a variation of the Coulomb correction, the track reconstruction efficiency and the unfolding matrix.

The correlation strength, &lambda;, and source radius, R, of the exponential fits to the two-particle double-ratio correlation functions, R₂(Q), in dependence on the multiplicity, m_ch, intervals for the minimum-bias (MB) and the high-multiplicity track (HMT) events for p_T &gt; 100&nbsp;MeV at &radic;s = 13&nbsp;TeV. Statistical uncertainties for &radic;&chi;²/ndf&gt;1 are corrected by the &radic;&chi;²/ndf. The total uncertainties are shown.

The correlation strength, &lambda;, and source radius, R, of the exponential fits to the two-particle double-ratio correlation functions, R₂(Q), in dependence on the multiplicity, m_ch, intervals for the minimum-bias (MB) and the high-multiplicity track (HMT) events for p_T &gt; 500&nbsp;MeV at &radic;s = 13&nbsp;TeV. Statistical uncertainties for &radic;&chi;²/ndf&gt;1 are corrected by the &radic;&chi;²/ndf. The total uncertainties are shown.

The correlation strength, &lambda;, and source radius, R, of the exponential fits to the two-particle double-ratio correlation functions, R₂(Q), in dependence on the pair transverse momentum, k_T, intervals for the minimum-bias (MB) and the high-multiplicity track (HMT) events for p_T &gt; 100&nbsp;MeV at &radic;s = 13&nbsp;TeV. Statistical uncertainties for &radic;&chi;²/ndf&gt;1 are corrected by the &radic;&chi;²/ndf. The total uncertainties are shown.

The correlation strength, &lambda;, and source radius, R, of the exponential fits to the two-particle double-ratio correlation functions, R₂(Q), in dependence on the pair transverse momentum, k_T, intervals for the minimum-bias (MB) and the high-multiplicity track (HMT) events for p_T &gt; 500&nbsp;MeV at &radic;s = 13&nbsp;TeV. Statistical uncertainties for &radic;&chi;²/ndf&gt;1 are corrected by the &radic;&chi;²/ndf. The total uncertainties are shown.

The $1\sigma_{\text{exp}}$ variation of the expected exclusion contour at 95% CL as a function of the smuon and neutralino masses, for $\lambda_{231}^{'}=1.0$.

The observed exclusion contour at 95% CL as a function of the smuon and neutralino masses, for $\lambda_{231}^{'}=0.1$.

The expected exclusion contour at 95% CL as a function of the smuon and neutralino masses, for $\lambda_{231}^{'}=0.1$.

The observed exclusion contour at 95% CL as a function of the smuon and neutralino masses, for $\lambda_{231}^{'}=0.15$.

The expected exclusion contour at 95% CL as a function of the smuon and neutralino masses, for $\lambda_{231}^{'}=0.15$.

The observed exclusion contour at 95% CL as a function of the smuon and neutralino masses, for $\lambda_{231}^{'}=0.2$.

The expected exclusion contour at 95% CL as a function of the smuon and neutralino masses, for $\lambda_{231}^{'}=0.2$.

The observed exclusion contour at 95% CL as a function of the smuon and neutralino masses, for $\lambda_{231}^{'}=0.4$.

The expected exclusion contour at 95% CL as a function of the smuon and neutralino masses, for $\lambda_{231}^{'}=0.4$.

The observed exclusion contour at 95% CL as a function of the smuon and neutralino masses, for $\lambda_{231}^{'}=0.6$.

The expected exclusion contour at 95% CL as a function of the smuon and neutralino masses, for $\lambda_{231}^{'}=0p6$.

The observed exclusion contour at 95% CL as a function of the smuon and neutralino masses, for $\lambda_{231}^{'}=1.5$.

The expected exclusion contour at 95% CL as a function of the smuon and neutralino masses, for $\lambda_{231}^{'}=1.5$.

The observed exclusion contour at 95% CL as a function of the leptoquark mass and coupling strength.

The expected exclusion contour at 95% CL as a function of the leptoquark mass and coupling strength.

The minus $1\sigma_{\text{theory}}$ variation of the observed exclusion contour at 95% CL as a function of the leptoquark mass and coupling strength.

The plus $1\sigma_{\text{theory}}$ variation of the observed exclusion contour at 95% CL as a function of the leptoquark mass and coupling strength.

The $1\sigma_{\text{exp}}$ variation of the expected exclusion contour at 95% CL as a function of the leptoquark mass and coupling strength.

Observed yields, and fake lepton background yields in the $e^{+}\mu^{-}$ and $e^{-}\mu^{+}$ channels of SR-MET, along with the results of the $e^{+}\mu^{-}/e^{-}\mu^{+}$ ratio measurement and 1-sided p-value in SR-MET, binned in $M_{T2}$.

Observed yields, and fake lepton background yields in the $e^{+}\mu^{-}$ and $e^{-}\mu^{+}$ channels of SR-JET, along with the results of the $e^{+}\mu^{-}/e^{-}\mu^{+}$ ratio measurement and 1-sided p-value in SR-JET, binned in $H_{\text{P}}$.

Observed and expected 95% CL upper limits on the total number of signal events entering the $e^{+}\mu^{-}$ and $e^{-}\mu^{+}$ channels of each bin of SR-MET. The regions are binned in the same way as the ratio $\rho$ measurement. The limits are shown for a selection of 'z' values, where 'z' is the fraction of the total signal events entering the $e^{+}\mu^{-}$ channel.

Observed and expected 95% CL upper limits on the total number of signal events entering the $e^{+}\mu^{-}$ and $e^{-}\mu^{+}$ channels of each bin of SR-JET. The regions are binned in the same way as the ratio $\rho$ measurement. The limits are shown for a selection of 'z' values, where 'z' is the fraction of the total signal events entering the $e^{+}\mu^{-}$ channel.

Signal yields following each cut in the analysis, for representative $R$-parity-violating supersymmetry and leptoquark signals. All yields are MC generator-weighted and normalised to $139~\text{fb}^{-1}$. The cut labelled `Preselection' includes trigger requirements, and requires exactly one Baseline electron and one Baseline muon. At this point, the muon charge-bias correction weights are also applied. The $R$-parity-violating supersymmetry models were generated by specifying a top-quark in the final state and applying a two-lepton filter, hence the first row also includes events where the top quark decays to an electron.

The observed exclusion contours as a function of (m(med), m($\chi$)), with Vector mediator)

The expected exclusion contours as a function of (m(a), tan($\beta$)), with sin($\theta$) = 0.35)

The observed exclusion contours as a function of (m(a), tan($\beta$)), with sin($\theta$) = 0.35)

The expected exclusion contours as a function of (m(a), tan($\beta$)), with sin($\theta$) = 0.7)

The observed exclusion contours as a function of (m(a), tan($\beta$)), with sin($\theta$) = 0.7)

The expected exclusion contours as a function of (m(H), tan($\beta$)), with sin($\theta$) = 0.35)

The observed exclusion contours as a function of (m(H), tan($\beta$)), with sin($\theta$) = 0.35)

The expected exclusion contours as a function of (m(H), tan($\beta$)), with sin($\theta$) = 0.7)

The observed exclusion contours as a function of (m(H), tan($\beta$)), with sin($\theta$) = 0.7)

The expected exclusion contours as a function of (m(a), m(H)), with sin($\theta$) = 0.35)

The observed exclusion contours as a function of (m(a), m(H)), with sin($\theta$) = 0.35)

The expected exclusion contours as a function of (m(a), m(H)), with sin($\theta$) = 0.7)

The observed exclusion contours as a function of (m(a), m(H)), with sin($\theta$) = 0.7)

Expected lower limit on signal strength at 95% CL as a function of sin($\theta$), with m(a) = 200 GeV, m(H) = 600 GeV.

Observed lower limit on signal strength at 95% CL as a function of sin($\theta$), with m(a) = 200 GeV, m(H) = 600 GeV.

Expected lower limit on signal strength at 95% CL as a function of sin($\theta$), with m(a) = 350 GeV, m(H) = 1000 GeV.

Observed lower limit on signal strength at 95% CL as a function of sin($\theta$), with m(a) = 350 GeV, m(H) = 1000 GeV.

Observed lower limit on WIMP-nucleon cross section at 90% CL as a function of m(WIMP), assuming Higgs-portal scenario with Scalar WIMP.

Observed lower limit on WIMP-nucleon cross section at 90% CL as a function of m(WIMP), assuming Higgs-portal scenario with Majorana WIMP.

Observed lower limit on the spin-dependent WIMP–proton scattering cross-section.

Observed lower limit on the spin-independent WIMP–nucleon scattering cross-section.

Cutflow of unweighted and weighted events of $ZH$ signals in the electron channel.

Cutflow of unweighted and weighted events of $ZH$ signals in the muon channel.

Cutflow of unweighted and weighted events of DM signals (simplified DM axial-vector with m(med) = 900 GeV and m($\chi$) = 40 GeV, 2HDM+$a$ signal with m(A) = 600 GeV, m(a) = 400 GeV, tan($\beta$) = 1.0 and m($\chi$) = 10 GeV) in the electron channel.

Cutflow of unweighted and weighted events of DM signals (simplified DM axial-vector with m(med) = 900 GeV and m($\chi$) = 40 GeV, 2HDM+$a$ signal with m(A) = 600 GeV, m(a) = 400 GeV, tan($\beta$) = 1.0 and m($\chi$) = 10 GeV) in the muon channel.

Upper limits on $\mathcal{B}(H\rightarrow aa\rightarrow bb\mu\mu)$ at 95% CL including the BDT cut as a function of the signal mass.

Upper limits on $\mathcal{B}(H\rightarrow aa\rightarrow bb\mu\mu)$ at 95% CL without the BDT cut as a function of the signal mass.

The number of events when applying each cut in the analysis for $m_a$ = 16 GeV. The first row shows the approximate total number of events scaled to the theoretical signal cross-section and luminosity of the full Run 2 dataset, assuming $ \mathcal{B}(H\rightarrow aa\rightarrow bb\mu\mu)$ = 0.16%.

The number of events when applying each cut in the analysis for $m_a$ = 20 GeV. The first row shows the approximate total number of events scaled to the theoretical signal cross-section and luminosity of the full Run 2 dataset, assuming $ \mathcal{B}(H\rightarrow aa\rightarrow bb\mu\mu)$ = 0.16%.

The number of events when applying each cut in the analysis for $m_a$ = 30 GeV. The first row shows the approximate total number of events scaled to the theoretical signal cross-section and luminosity of the full Run 2 dataset, assuming $ \mathcal{B}(H\rightarrow aa\rightarrow bb\mu\mu)$ = 0.16%.

The number of events when applying each cut in the analysis for $m_a$ = 40 GeV. The first row shows the approximate total number of events scaled to the theoretical signal cross-section and luminosity of the full Run 2 dataset, assuming $ \mathcal{B}(H\rightarrow aa\rightarrow bb\mu\mu)$ = 0.16%.

The number of events when applying each cut in the analysis for $m_a$ = 50 GeV. The first row shows the approximate total number of events scaled to the theoretical signal cross-section and luminosity of the full Run 2 dataset, assuming $ \mathcal{B}(H\rightarrow aa\rightarrow bb\mu\mu)$ = 0.16%.

The number of events when applying each cut in the analysis for $m_a$ = 60 GeV. The first row shows the approximate total number of events scaled to the theoretical signal cross-section and luminosity of the full Run 2 dataset, assuming $ \mathcal{B}(H\rightarrow aa\rightarrow bb\mu\mu)$ = 0.16%.

Distribution of the missing transverse energy in CRTop. The Z+HF and $t\bar{t}$ scale factors, described in the text, have been applied to the simulated samples. The distribution labeled "Signal" is for the model with ($m_a$, $m_{\tilde{\chi}_{1}^{0}}$, $m_{\tilde{\chi}_{2}^{0}}$) = (45 GeV, 10 GeV, 80 GeV).

Distribution of the dijet invariant mass in the signal region, shown together with the parameterized background model (labelled "Bkg Model"). For reference, the MC prediction for the SM background is also shown (labelled "SM MC"). The Z+HF and $t\bar{t}$ scale factors, described in the text, have been applied to the simulated samples. The signal region is defined to have dijet invariant mass > 20 GeV. The distribution labeled "Signal" is for the model with ($m_a$, $m_{\tilde{\chi}_{1}^{0}}$, $m_{\tilde{\chi}_{2}^{0}}$) = (45 GeV, 10 GeV, 80 GeV).

Upper limits at 95% CL on the $pp \rightarrow ZH$ cross section times the branching ratio for $Z \rightarrow \ell^{+}\ell^{-}$ (where $\ell = e, \mu \;\mathrm{or}\; \tau$) and $H \rightarrow \tilde{\chi}_{2}^{0}\tilde{\chi}_{1}^{0} \rightarrow a \tilde{\chi}_{1}^{0}\tilde{\chi}_{1}^{0} \rightarrow b\bar{b} \tilde{\chi}_{1}^{0}\tilde{\chi}_{1}^{0}$ as a function of $m_{a}$ for $m_{\tilde{\chi}_{1}^{0}} = 10$ GeV and $m_{\tilde{\chi}_{2}^{0}} = 65$ GeV in the NMSSM scenario described in the text. All branching ratios in the Higgs boson decay chain after the decay $H \rightarrow \tilde{\chi}_{2}^{0}\tilde{\chi}_{1}^{0}$ are set to 100%.

Upper limits at 95% CL on the $pp \rightarrow ZH$ cross section times the branching ratio for $Z \rightarrow \ell^{+}\ell^{-}$ (where $\ell = e, \mu \;\mathrm{or}\; \tau$) and $H \rightarrow \tilde{\chi}_{2}^{0}\tilde{\chi}_{1}^{0} \rightarrow a \tilde{\chi}_{1}^{0}\tilde{\chi}_{1}^{0} \rightarrow b\bar{b} \tilde{\chi}_{1}^{0}\tilde{\chi}_{1}^{0}$ as a function of $m_{a}$ for $m_{\tilde{\chi}_{1}^{0}} = 10$ GeV and $m_{\tilde{\chi}_{2}^{0}} = 80$ GeV in the NMSSM scenario described in the text. All branching ratios in the Higgs boson decay chain after the decay $H \rightarrow \tilde{\chi}_{2}^{0}\tilde{\chi}_{1}^{0}$ are set to 100%.

Upper limits at 95% CL on the $pp \rightarrow ZH$ cross section times the branching ratio for $Z \rightarrow \ell^{+}\ell^{-}$ (where $\ell = e, \mu\; \mathrm{or}\; \tau$) and $H \rightarrow \tilde{\chi}_{2}^{0}\tilde{\chi}_{1}^{0} \rightarrow a \tilde{\chi}_{1}^{0}\tilde{\chi}_{1}^{0} \rightarrow b\bar{b} \tilde{\chi}_{1}^{0}\tilde{\chi}_{1}^{0}$ as a function of $m_{a}$ for $m_{\tilde{\chi}_{1}^{0}} = 10$ GeV and $m_{\tilde{\chi}_{2}^{0}} = 95$ GeV in the NMSSM scenario described in the text. All branching ratios in the Higgs boson decay chain after the decay $H \rightarrow \tilde{\chi}_{2}^{0}\tilde{\chi}_{1}^{0}$ are set to 100%.

Upper limits at 95% CL on the $pp \rightarrow ZH$ cross section times the branching ratio for $Z \rightarrow \ell^{+}\ell^{-}$ (where $\ell = e, \mu\; \mathrm{or}\; \tau$) and $H \rightarrow \tilde{\chi}_{2}^{0}\tilde{\chi}_{1}^{0} \rightarrow a \tilde{\chi}_{1}^{0}\tilde{\chi}_{1}^{0} \rightarrow b\bar{b} \tilde{\chi}_{1}^{0}\tilde{\chi}_{1}^{0}$ as a function of $m_{a}$ for $m_{\tilde{\chi}_{1}^{0}} = 10$ GeV and $m_{\tilde{\chi}_{2}^{0}} = 110$ GeV in the NMSSM scenario described in the text. All branching ratios in the Higgs boson decay chain after the decay $H \rightarrow \tilde{\chi}_{2}^{0}\tilde{\chi}_{1}^{0}$ are set to 100%.

Upper limits at 95% CL on the $pp \rightarrow ZH$ cross section times the branching ratio for $Z \rightarrow \ell^{+}\ell^{-}$ (where $\ell = e, \mu\; \mathrm{or}\; \tau$) and $H \rightarrow \tilde{\chi}_{2}^{0}\tilde{\chi}_{1}^{0} \rightarrow a \tilde{\chi}_{1}^{0}\tilde{\chi}_{1}^{0} \rightarrow b\bar{b} \tilde{\chi}_{1}^{0}\tilde{\chi}_{1}^{0}$ as a function of $m_{a}$ for $m_{\tilde{\chi}_{1}^{0}} = 20$ GeV and $m_{\tilde{\chi}_{2}^{0}} = 80$ GeV in the NMSSM scenario described in the text. All branching ratios in the Higgs boson decay chain after the decay $H \rightarrow \tilde{\chi}_{2}^{0}\tilde{\chi}_{1}^{0}$ are set to 100%.

Upper limits at 95% CL on the $pp \rightarrow ZH$ cross section times the branching ratio for $Z \rightarrow \ell^{+}\ell^{-}$ (where $\ell = e, \mu \;\mathrm{or}\; \tau$) and $H \rightarrow \tilde{\chi}_{2}^{0}\tilde{\chi}_{1}^{0} \rightarrow a \tilde{\chi}_{1}^{0}\tilde{\chi}_{1}^{0} \rightarrow b\bar{b} \tilde{\chi}_{1}^{0}\tilde{\chi}_{1}^{0}$ as a function of $m_{a}$ for $m_{\tilde{\chi}_{1}^{0}} = 30$ GeV and $m_{\tilde{\chi}_{2}^{0}} = 80$ GeV in the NMSSM scenario described in the text. All branching ratios in the Higgs boson decay chain after the decay $H \rightarrow \tilde{\chi}_{2}^{0}\tilde{\chi}_{1}^{0}$ are set to 100%.

Upper limits at 95% CL on the branching ratio $H \rightarrow \tilde{\chi}_{2}^{0}\tilde{\chi}_{1}^{0} \rightarrow a \tilde{\chi}_{1}^{0}\tilde{\chi}_{1}^{0} \rightarrow b\bar{b} \tilde{\chi}_{1}^{0}\tilde{\chi}_{1}^{0}$ as a function of $m_{a}$ for $m_{\tilde{\chi}_{1}^{0}} = 10$ GeV and $m_{\tilde{\chi}_{2}^{0}} = 65$ GeV in the NMSSM scenario described in the text. The SM $ZH$ cross section is assumed.

Upper limits at 95% CL on the branching ratio $H \rightarrow \tilde{\chi}_{2}^{0}\tilde{\chi}_{1}^{0} \rightarrow a \tilde{\chi}_{1}^{0}\tilde{\chi}_{1}^{0} \rightarrow b\bar{b} \tilde{\chi}_{1}^{0}\tilde{\chi}_{1}^{0}$ as a function of $m_{a}$ for $m_{\tilde{\chi}_{1}^{0}} = 10$ GeV and $m_{\tilde{\chi}_{2}^{0}} = 80$ GeV in the NMSSM scenario described in the text. The SM $ZH$ cross section is assumed.

Upper limits at 95% CL on the branching ratio $H \rightarrow \tilde{\chi}_{2}^{0}\tilde{\chi}_{1}^{0} \rightarrow a \tilde{\chi}_{1}^{0}\tilde{\chi}_{1}^{0} \rightarrow b\bar{b} \tilde{\chi}_{1}^{0}\tilde{\chi}_{1}^{0}$ as a function of $m_{a}$ for $m_{\tilde{\chi}_{1}^{0}} = 10$ GeV and $m_{\tilde{\chi}_{2}^{0}} = 95$ GeV in the NMSSM scenario described in the text. The SM $ZH$ cross section is assumed.

Upper limits at 95% CL on the branching ratio $H \rightarrow \tilde{\chi}_{2}^{0}\tilde{\chi}_{1}^{0} \rightarrow a \tilde{\chi}_{1}^{0}\tilde{\chi}_{1}^{0} \rightarrow b\bar{b} \tilde{\chi}_{1}^{0}\tilde{\chi}_{1}^{0}$ as a function of $m_{a}$ for $m_{\tilde{\chi}_{1}^{0}} = 10$ GeV and $m_{\tilde{\chi}_{2}^{0}} = 110$ GeV in the NMSSM scenario described in the text. The SM $ZH$ cross section is assumed.

Upper limits at 95% CL on the branching ratio $H \rightarrow \tilde{\chi}_{2}^{0}\tilde{\chi}_{1}^{0} \rightarrow a \tilde{\chi}_{1}^{0}\tilde{\chi}_{1}^{0} \rightarrow b\bar{b} \tilde{\chi}_{1}^{0}\tilde{\chi}_{1}^{0}$ as a function of $m_{a}$ for $m_{\tilde{\chi}_{1}^{0}} = 20$ GeV and $m_{\tilde{\chi}_{2}^{0}} = 80$ GeV in the NMSSM scenario described in the text. The SM $ZH$ cross section is assumed.

Upper limits at 95% CL on the branching ratio $H \rightarrow \tilde{\chi}_{2}^{0}\tilde{\chi}_{1}^{0} \rightarrow a \tilde{\chi}_{1}^{0}\tilde{\chi}_{1}^{0} \rightarrow b\bar{b} \tilde{\chi}_{1}^{0}\tilde{\chi}_{1}^{0}$ as a function of $m_{a}$ for $m_{\tilde{\chi}_{1}^{0}} = 30$ GeV and $m_{\tilde{\chi}_{2}^{0}} = 80$ GeV in the NMSSM scenario described in the text. The SM $ZH$ cross section is assumed.

Unweighted and weighted number of events after each stage of selection for the NMSSM scenario with $pp \rightarrow ZH$, $Z \rightarrow \ell^{+}\ell^{-}$, $H \rightarrow \tilde{\chi}_{2}^{0}\tilde{\chi}_{1}^{0} \rightarrow a \tilde{\chi}_{1}^{0}\tilde{\chi}_{1}^{0} \rightarrow b\bar{b} \tilde{\chi}_{1}^{0}\tilde{\chi}_{1}^{0}$ where $(m_{a}, m_{\tilde{\chi}_{1}^{0}}, m_{\tilde{\chi}_{2}^{0}}) = (45,10,80)$ GeV and the Z boson decaying to $e^{+}e^{-}, \;\mu^{+}\mu^{-} \;\mathrm{or}\; \tau^{+}\tau^{-}$. All branching ratios in the Higgs boson decay chain are set to 100%. The weighted number of events corresponds to an integrated luminosity of $139 \;\mathrm{fb}^{-1}$. The "skimming selection" required either a single electron or muon with $p_{T} > 100\;$ GeV or a pair of electrons or muons each with $p_{T} > 20\;$ GeV. The preselection requirements include the trigger, absence of a bad jet or bad muon, and two leptons, where a lepton is either an electron or a muon.

Acceptance and efficiency of this analysis for the signal models considered in this paper. The signal is an NMSSM scenario with $pp \rightarrow ZH$, $Z \rightarrow \ell^{+}\ell^{-}$, $H \rightarrow \tilde{\chi}_{2}^{0}\tilde{\chi}_{1}^{0} \rightarrow a \tilde{\chi}_{1}^{0}\tilde{\chi}_{1}^{0} \rightarrow b\bar{b} \tilde{\chi}_{1}^{0}\tilde{\chi}_{1}^{0}$ where the values of $(m_{a}, m_{\tilde{\chi}_{1}^{0}}, m_{\tilde{\chi}_{2}^{0}})$ are varied. The Z boson decays to $e^{+}e^{-}, \mu^{+}\mu^{-} \;\mathrm{or}\; \tau^{+}\tau^{-}$. All branching ratios in the Higgs boson decay chain are set to 100%. The product of acceptance times efficiency is defined by the fraction of simulated events that pass all the selection criteria of this analysis. The acceptance is defined by the fraction of simulated events that pass all the selection criteria as applied to Monte Carlo truth-level quantities. The efficiency is then defined as the acceptance times efficiency, divided by the acceptance.

Acceptance and efficiency of this analysis for the signal models considered in this paper. The signal is an NMSSM scenario with $pp \rightarrow ZH$, $Z \rightarrow \ell^{+}\ell^{-}$, $H \rightarrow \tilde{\chi}_{2}^{0}\tilde{\chi}_{1}^{0} \rightarrow a \tilde{\chi}_{1}^{0}\tilde{\chi}_{1}^{0} \rightarrow b\bar{b} \tilde{\chi}_{1}^{0}\tilde{\chi}_{1}^{0}$ where the values of $(m_{a}, m_{\tilde{\chi}_{1}^{0}}, m_{\tilde{\chi}_{2}^{0}})$ are varied. The Z boson decays to $e^{+}e^{-}, \mu^{+}\mu^{-} \;\mathrm{or}\; \tau^{+}\tau^{-}$. All branching ratios in the Higgs boson decay chain are set to 100%. The product of acceptance times efficiency is defined by the fraction of simulated events that pass all the selection criteria of this analysis. The acceptance is defined by the fraction of simulated events that pass all the selection criteria as applied to Monte Carlo truth-level quantities. The efficiency is then defined as the acceptance times efficiency, divided by the acceptance.

Summary of results for charm muon RAA as a function of pT for five different centrality. Uncertainties are statistical and systematic, respectively.

Summary of results for bottom muon RAA as a function of pT for five different centrality. Uncertainties are statistical and systematic, respectively.

Summary of results for charm muon RAA to bottom muon RAA ratio as a function of pT for five different centrality. Uncertainties are statistical and systematic, respectively.