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

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

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

self normalized dijets from pp collisions

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

$\rho_{3}$ 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.

Example of combinatorial background subtracted invariant mass distributions and the extracted yields as a function of $\cos \theta^*$ for $\phi$ and $K^{*0}$ mesons. \textbf{a)} example of $\phi \rightarrow K^+ + K^-$ invariant mass distributions, with combinatorial background subtracted, integrated over $\cos \theta^*$; \textbf{b)} example of $K^{*0} (\overline{K^{*0}}) \rightarrow K^{-} \pi^{+} (K^{+} \pi^{-})$ invariant mass distributions, with combinatorial background subtracted, integrated over $\cos \theta^*$; \textbf{c)} extracted yields of $\phi$ as a function of $\cos \theta^*$; \textbf{d)} extracted yields of $K^{*0}$ as a function of $\cos \theta^*$.

Example of combinatorial background subtracted invariant mass distributions and the extracted yields as a function of $\cos \theta^*$ for $\phi$ and $K^{*0}$ mesons. \textbf{a)} example of $\phi \rightarrow K^+ + K^-$ invariant mass distributions, with combinatorial background subtracted, integrated over $\cos \theta^*$; \textbf{b)} example of $K^{*0} (\overline{K^{*0}}) \rightarrow K^{-} \pi^{+} (K^{+} \pi^{-})$ invariant mass distributions, with combinatorial background subtracted, integrated over $\cos \theta^*$; \textbf{c)} extracted yields of $\phi$ as a function of $\cos \theta^*$; \textbf{d)} extracted yields of $K^{*0}$ as a function of $\cos \theta^*$.

Example of combinatorial background subtracted invariant mass distributions and the extracted yields as a function of $\cos \theta^*$ for $\phi$ and $K^{*0}$ mesons. \textbf{a)} example of $\phi \rightarrow K^+ + K^-$ invariant mass distributions, with combinatorial background subtracted, integrated over $\cos \theta^*$; \textbf{b)} example of $K^{*0} (\overline{K^{*0}}) \rightarrow K^{-} \pi^{+} (K^{+} \pi^{-})$ invariant mass distributions, with combinatorial background subtracted, integrated over $\cos \theta^*$; \textbf{c)} extracted yields of $\phi$ as a function of $\cos \theta^*$; \textbf{d)} extracted yields of $K^{*0}$ as a function of $\cos \theta^*$.

Efficiency corrected $\phi$-meson yields as a function of cos$\theta$* and corresponding fits with Eq.1 in the method section.

Efficiency and acceptance corrected $K^{*0}$-meson yields as a function of cos$\theta$* and corresponding fits with Eq.4 in the method section.

$\phi$-meson $\rho_{00}$ obtained from 1st- and 2nd-order event planes. The red stars (gray squares) show the $\phi$-meson $\rho_{00}$ as a function of beam energy, obtained with the 2nd-order (1st-order) EP.

$\phi$-meson $\rho_{00}$ with respect to different quantization axes. $\phi$-meson $\rho_{00}$ as a function of beam energy, for the out-of-plane direction (stars) and the in-plane direction (diamonds). Curves are fits based on theoretical calculations with a $\phi$-meson field. The corresponding $G_s^{(y)}$ values obtained from the fits are shown in the legend.

$\rho_{00}$ as a function of transverse momentum for $\phi$ for different collision energies. The gray squares and red stars are results obtained with the 1st- and 2nd-order EP, respectively.

$\rho_{00}$ as a function of transverse momentum for $\phi$ for different collision energies. The gray squares and red stars are results obtained with the 1st- and 2nd-order EP, respectively.

$\rho_{00}$ as a function of transverse momentum for $\phi$ for different collision energies. The gray squares and red stars are results obtained with the 1st- and 2nd-order EP, respectively.

$\rho_{00}$ as a function of transverse momentum for $\phi$ for different collision energies. The gray squares and red stars are results obtained with the 1st- and 2nd-order EP, respectively.

$\rho_{00}$ as a function of transverse momentum for $\phi$ for different collision energies. The gray squares and red stars are results obtained with the 1st- and 2nd-order EP, respectively.

$\rho_{00}$ as a function of transverse momentum for $\phi$ for different collision energies. The gray squares and red stars are results obtained with the 1st- and 2nd-order EP, respectively.

$\rho_{00}$ as a function of transverse momentum for $\phi$ for different collision energies. The gray squares and red stars are results obtained with the 1st- and 2nd-order EP, respectively.

$\rho_{00}$ as a function of transverse momentum for $\phi$ for different collision energies. The gray squares and red stars are results obtained with the 1st- and 2nd-order EP, respectively.

$\rho_{00}$ as a function of transverse momentum for $\phi$ for different collision energies. The gray squares and red stars are results obtained with the 1st- and 2nd-order EP, respectively.

$\rho_{00}$ as a function of transverse momentum for $\phi$ for different collision energies. The gray squares and red stars are results obtained with the 1st- and 2nd-order EP, respectively.

$\rho_{00}$ as a function of transverse momentum for $\phi$ for different collision energies. The gray squares and red stars are results obtained with the 1st- and 2nd-order EP, respectively.

$\rho_{00}$ as a function of transverse momentum for $\phi$ for different collision energies. The gray squares and red stars are results obtained with the 1st- and 2nd-order EP, respectively.

$\rho_{00}$ as a function of transverse momentum for $K^{*0}$ for different collision energies.

$\rho_{00}$ as a function of transverse momentum for $K^{*0}$ for different collision energies.

$\rho_{00}$ as a function of transverse momentum for $K^{*0}$ for different collision energies.

$\rho_{00}$ as a function of transverse momentum for $K^{*0}$ for different collision energies.

$\rho_{00}$ as a function of transverse momentum for $K^{*0}$ for different collision energies.

$\rho_{00}$ as a function of transverse momentum for $K^{*0}$ for different collision energies.

$\rho_{00}$ as a function of transverse momentum for $K^{*0}$ for different collision energies.

$\rho_{00}$ as a function of centrality for $\phi$ (upper panels) and $K^{*0}$ (lower panels). The solid squares and stars are results for the $\phi$ meson, obtained with the 1st- and 2nd-order EP, respectively. The solid circles are results for the $K^{*0}$ meson, obtained with the 2nd-order EP.}

$\rho_{00}$ as a function of centrality for $\phi$ (upper panels) and $K^{*0}$ (lower panels). The solid squares and stars are results for the $\phi$ meson, obtained with the 1st- and 2nd-order EP, respectively. The solid circles are results for the $K^{*0}$ meson, obtained with the 2nd-order EP.}

$\rho_{00}$ as a function of centrality for $\phi$ (upper panels) and $K^{*0}$ (lower panels). The solid squares and stars are results for the $\phi$ meson, obtained with the 1st- and 2nd-order EP, respectively. The solid circles are results for the $K^{*0}$ meson, obtained with the 2nd-order EP.}

$\rho_{00}$ as a function of centrality for $\phi$ (upper panels) and $K^{*0}$ (lower panels). The solid squares and stars are results for the $\phi$ meson, obtained with the 1st- and 2nd-order EP, respectively. The solid circles are results for the $K^{*0}$ meson, obtained with the 2nd-order EP.}

$\rho_{00}$ as a function of centrality for $\phi$ (upper panels) and $K^{*0}$ (lower panels). The solid squares and stars are results for the $\phi$ meson, obtained with the 1st- and 2nd-order EP, respectively. The solid circles are results for the $K^{*0}$ meson, obtained with the 2nd-order EP.}

$\rho_{00}$ as a function of centrality for $\phi$ (upper panels) and $K^{*0}$ (lower panels). The solid squares and stars are results for the $\phi$ meson, obtained with the 1st- and 2nd-order EP, respectively. The solid circles are results for the $K^{*0}$ meson, obtained with the 2nd-order EP.}

$\rho_{00}$ as a function of centrality for $\phi$ (upper panels) and $K^{*0}$ (lower panels). The solid squares and stars are results for the $\phi$ meson, obtained with the 1st- and 2nd-order EP, respectively. The solid circles are results for the $K^{*0}$ meson, obtained with the 2nd-order EP.}

Global spin alignment measurement of $\phi$ and $K^{*0}$ vector mesons in Au+Au collisions at 0-20\% centrality. The solid squares and stars are results for the $\phi$ meson, obtained with the 1st- and 2nd-order EP, respectively. The solid circles are results for $K^{*0}$-meson, obtained with the 2nd-order EP.

Global spin alignment measurement of $\phi$ and $K^{*0}$ vector mesons in Au+Au collisions at 0-20\% centrality. The solid squares and stars are results for the $\phi$ meson, obtained with the 1st- and 2nd-order EP, respectively. The solid circles are results for $K^{*0}$-meson, obtained with the 2nd-order EP.

The $p_{T}$ dependencies of $v_{1}$ within $-0.4<y<-0.1$ for $t$ in 10-40% mid-central Au+Au collisions at 3 GeV.

The rapidity and $p_{T}$ dependencies of $v_{1}$ for $^{3}$He in 10-40% mid-central Au+Au collisions at 3 GeV.

The $p_{T}$ dependencies of $v_{1}$ within $-0.1<y<0$ for $^4$He in 10-40% mid-central Au+Au collisions at 3 GeV.

The $p_{T}$ dependencies of $v_{1}$ within $-0.4<y<-0.1$ for $^{4}$He in 10-40% mid-central Au+Au collisions at 3 GeV.

The rapidity and $p_{T}$ dependencies of $v_{2}$ for $p$ in 10-40% mid-central Au+Au collisions at 3 GeV.

The rapidity and $p_{T}$ dependencies of $v_{2}$ for $d$ in 10-40% mid-central Au+Au collisions at 3 GeV.

The $p_{T}$ dependencies of $v_{2}$ within $-0.1<y<0$ for $t$ in 10-40% mid-central Au+Au collisions at 3 GeV.

The $p_{T}$ dependencies of $v_{2}$ within $-0.4<y<-0.1$ for $t$ in 10-40% mid-central Au+Au collisions at 3 GeV.

The rapidity and $p_{T}$ dependencies of $v_{2}$ for $^{3}$He in 10-40% mid-central Au+Au collisions at 3 GeV.

The $p_{T}$ dependencies of $v_{2}$ within $-0.1<y<0$ for $^4$He in 10-40% mid-central Au+Au collisions at 3 GeV.

The $p_{T}$ dependencies of $v_{2}$ within $-0.4<y<-0.1$ for $^{4}$He in 10-40% mid-central Au+Au collisions at 3 GeV.

The rapidity dependencies of $v_{1}$ for $p$, $d$, and $^{3}$He in 10-40% mid-central Au+Au collisions at 3 GeV.

The rapidity dependencies of $v_{1}$ for $t$ and $^{4}$He in 10-40% mid-central Au+Au collisions at 3 GeV.

The rapidity dependencies of $v_{1}$ from JAM plus coalescence calculations in 10-40% mid-central Au+Au collisions at 3 GeV.

The rapidity dependencies of $v_{2}$ for $p$, $d$, and $^{3}$He in 10-40% mid-central Au+Au collisions at 3 GeV.

The rapidity dependencies of $v_{2}$ for $t$ and $^{4}$He in 10-40% mid-central Au+Au collisions at 3 GeV.

The rapidity dependencies of $v_{2}$ from JAM plus coalescence calculations in 10-40% mid-central Au+Au collisions at 3 GeV.

Light nucleus scaled $v_{1}$ slopes as a function os collision energy in 10-40 mid-cantral Au+Au collisions.

Light nucleus scaled $v_{1}$ slopes from JAM plus coalescence in 10-40 mid-cantral Au+Au collisions at 3 GeV.

Centrality dependence of the proton cumulant ratios for Au+Au collisions at $\sqrt{s_{NN}}$ = 3.0 GeV. Protons are from $-0.5 < y < 0$ and $0.4 < p_{T} < 2.0$ GeV/$c$. Systematic uncertainties are represented by gray bars. Statistical uncertainties are smaller than marker size. CBWC is applied to all cumulant ratios. While open squares represent the data without the VFC correction, blue triangles and red circles are the results with VFC using the $\langle N_{\rm{part}} \rangle$ distributions from the UrQMD and Glauber models, respectively. UrQMD model results are represented as gold dashed line.

Centrality dependence of the proton cumulant ratios for Au+Au collisions at $\sqrt{s_{NN}}$ = 3.0 GeV. Protons are from $-0.5 < y < 0$ and $0.4 < p_{T} < 2.0$ GeV/$c$. Systematic uncertainties are represented by gray bars. Statistical uncertainties are smaller than marker size. CBWC is applied to all cumulant ratios. While open squares represent the data without the VFC correction, blue triangles and red circles are the results with VFC using the $\langle N_{\rm{part}} \rangle$ distributions from the UrQMD and Glauber models, respectively. UrQMD model results are represented as gold dashed line.

Rapidity and transverse momentum dependence of the proton cumulant ratios for 0–5% central collisions. Black-squares, red-dots and blue-triangles stand for data without and with the VFC using Glauber and UrQMD, respectively.

Rapidity and transverse momentum dependence of the proton cumulant ratios for 0–5% central collisions. Black-squares, red-dots and blue-triangles stand for data without and with the VFC using Glauber and UrQMD, respectively.

Rapidity and transverse momentum dependence of the proton cumulant ratios for 0–5% central collisions. Black-squares, red-dots and blue-triangles stand for data without and with the VFC using Glauber and UrQMD, respectively.

Rapidity and transverse momentum dependence of the proton cumulant ratios for 0–5% central collisions. Black-squares, red-dots and blue-triangles stand for data without and with the VFC using Glauber and UrQMD, respectively.

Collision energy dependence of the ratios of cumulants, $C_4/C_2$, for proton (squares) and net-proton (red circles) from top 0-5% Au+Au collisions at RHIC. The points for protons are shifted horizontally for clarity. The new result for proton from $\sqrt{s_{NN}}$ = 3.0 GeV collisions is shown as a filled square. HADES data of $\sqrt{s_{NN}}$ = 2.4 GeV 0-10% collisions is also shown. The vertical black and gray bars are the statistical and systematic uncertainties, respectively. In addition, results from the HRG model, based on both Canonical Ensemble (CE) and Grand-Canonical Ensemble (GCE), and transport model UrQMD are presented.

Fraction of bottom hadron decayed electrons in 0-80% Au+Au collisions at $\sqrt{s_{\rm NN}}$ = 200 GeV.

Fraction of bottom hadron decayed electrons in 0-20% and 20-40% Au+Au collisions at $\sqrt{s_{\rm NN}}$ = 200 GeV.

Fraction of bottom hadron decayed electrons in 40-80% Au+Au collisions at $\sqrt{s_{\rm NN}}$ = 200 GeV.

Nuclear modification factor $R_{\rm AA}$ of inclusive heavy flavor decayed electrons in 0-80% Au+Au collisions at $\sqrt{s_{\rm NN}}$ = 200 GeV. The 8% global uncertainty from the $p$+$p$ reference and a 8% gloabl uncertainty from $N_{\rm coll.}$ are not included in the table values.

Nuclear modification factor $R_{\rm AA}$ of bottom- and charm-decay electrons in 0-80% Au+Au collisions at $\sqrt{s_{\rm NN}}$ = 200 GeV. The 8% global uncertainty from the $p$+$p$ reference and a 8% gloabl uncertainty from $N_{\rm coll.}$ are not included in the table values.

Nuclear modification factor $R_{\rm AA}$ ratio of bottom- to charm-decay electrons in 0-80% Au+Au collisions at $\sqrt{s_{\rm NN}}$ = 200 GeV.

Null hypothesis for the nuclear modification factor $R_{\rm AA}$ ratio of bottom- to charm-decay electrons in 0-80% Au+Au collisions at $\sqrt{s_{\rm NN}}$ = 200 GeV.

Nuclear modification factor $R_{\rm CP}$ ratio of bottom- and charm-decay electrons in 0-80% Au+Au collisions at $\sqrt{s_{\rm NN}}$ = 200 GeV.

Null hypotheses for the nuclear modification factor $R_{\rm CP}$ ratio of bottom- and charm-decay electrons in 0-80% Au+Au collisions at $\sqrt{s_{\rm NN}}$ = 200 GeV.

Upper limits on the production cross section times branching fraction of the b* RH hypothesis at a 95% CL. Dashed colored lines show the expected limits from the l+jets and all-hadronic channels, where the latter start at resonance masses of 1.4 TeV. The observed and expected limits from the combination are shown as solid and dashed black lines, respectively. The green and yellow bands show the 68 and 95% confidence intervals on the combined expected limits.

Upper limits on the production cross section times branching fraction of the b* VL hypothesis at a 95% CL. Dashed colored lines show the expected limits from the l+jets and all-hadronic channels, where the latter start at resonance masses of 1.4 TeV. The observed and expected limits from the combination are shown as solid and dashed black lines, respectively. The green and yellow bands show the 68 and 95% confidence intervals on the combined expected limits.

Upper limits on the production cross section times branching fraction of the B+b hypothesis at a 95% CL. Dashed colored lines show the expected limits from the l+jets and all-hadronic channels, where the latter start at resonance masses of 1.4 TeV. The observed and expected limits from the combination are shown as solid and dashed black lines, respectively. The green and yellow bands show the 68 and 95% confidence intervals on the combined expected limits.

Upper limits on the production cross section times branching fraction of the B+t hypothesis at a 95% CL. Dashed colored lines show the expected limits from the l+jets and all-hadronic channels, where the latter start at resonance masses of 1.4 TeV. The observed and expected limits from the combination are shown as solid and dashed black lines, respectively. The green and yellow bands show the 68 and 95% confidence intervals on the combined expected limits.

The correlation functions (corrected for nonuniform detector efficiency in $\phi$; not corrected for the absolute detection efficiency) vs. azimuthal angle difference between forward ($2.6<\eta<4.0$) $\pi^{0}$s in $p$+$p$ collisions at $\sqrt{s_{\mathrm{_{NN}}}}=200$ GeV at high $p_{T}$ ($p^{trig}_{T}$=2.5-3 GeV/c, $p^{asso}_{T}$=2-2.5 GeV/c)

The correlation functions (corrected for nonuniform detector efficiency in $\phi$; not corrected for the absolute detection efficiency) vs. azimuthal angle difference between forward ($2.6<\eta<4.0$) $\pi^{0}$s in $p$+Al collisions at $\sqrt{s_{\mathrm{_{NN}}}}=200$ GeV at high $p_{T}$ ($p^{trig}_{T}$=2.5-3 GeV/c, $p^{asso}_{T}$=2-2.5 GeV/c)

The correlation functions (corrected for nonuniform detector efficiency in $\phi$; not corrected for the absolute detection efficiency) vs. azimuthal angle difference between forward ($2.6<\eta<4.0$) $\pi^{0}$s in $p$+$Au collisions at $\sqrt{s_{\mathrm{_{NN}}}}=200$ GeV at high $p_{T}$ ($p^{trig}_{T}$=2.5-3 GeV/c, $p^{asso}_{T}$=2-2.5 GeV/c)

Relative area of MinBias $pAu/pp$ of back-to-back di-$\pi^0$ correlations at forward pseudorapidities ($2.6<\eta<4.0$) from data

Relative area of MinBias $pAl/pp$ of back-to-back di-$\pi^0$ correlations at forward pseudorapidities ($2.6<\eta<4.0$) from data

Relative area of $pAu/pp$ at b=0 of back-to-back di-$\pi^0$ correlations at forward pseudorapidities ($2.6<\eta<4.0$) from prediction

Relative width of MinBias $pAu/pp$ of back-to-back di-$\pi^0$ correlations at forward pseudorapidities ($2.6<\eta<4.0$) from data

Relative width of MinBias $pAl/pp$ of back-to-back di-$\pi^0$ correlations at forward pseudorapidities ($2.6<\eta<4.0$) from data

Relative pedestal of MinBias $pAu/pp$ of back-to-back di-$\pi^0$ correlations at forward pseudorapidities ($2.6<\eta<4.0$) from data

Relative pedestal of MinBias $pAl/pp$ of back-to-back di-$\pi^0$ correlations at forward pseudorapidities ($2.6<\eta<4.0$) from data

Relative area of MinBias $pp/pp$ of back-to-back di-$\pi^0$ correlations at forward pseudorapidities ($2.6<\eta<4.0$), the ratio is unity, error is zero

Relative area of MinBias $pA/pp$ of back-to-back di-$\pi^0$ correlations at forward pseudorapidities ($2.6<\eta<4.0$) from data