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

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

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

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

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

Observed exclusion contour at 95% C.L. for the dark Higgs model in the (m_Z', m_s) plane for g_q=0.25, g_χ=1, m_χ=200 GeV, and sinθ=0.01.

Expected exclusion contour at 95% C.L. for the dark Higgs model in the (m_Z', m_s) plane for g_q=0.25, g_χ=1, m_χ=200 GeV, and sinθ=0.01.

Expected+1σ exclusion contour at 95% C.L. for the dark Higgs model in the (m_Z', m_s) plane for g_q=0.25, g_χ=1, m_χ=200 GeV, and sinθ=0.01.

Expected-1σ exclusion contour at 95% C.L. for the dark Higgs model in the (m_Z', m_s) plane for g_q=0.25, g_χ=1, m_χ=200 GeV, and sinθ=0.01.

Expected+2σ exclusion contour at 95% C.L. for the dark Higgs model in the (m_Z', m_s) plane for g_q=0.25, g_χ=1, m_χ=200 GeV, and sinθ=0.01.

Expected-2σ exclusion contour at 95% C.L. for the dark Higgs model in the (m_Z', m_s) plane for g_q=0.25, g_χ=1, m_χ=200 GeV, and sinθ=0.01.

Observed upper limits at 95% C.L. on σ(pp → s χχ) × B(s → W^± W^∓) for m_Z'=0.5 TeV as a function of m_s. The expected limits, varied up and down by one and two standard deviations, are shown as green and yellow bands, respectively. The observed and expected limits are compared to the theoretical LO cross section for the σ(pp → s χχ) × B(s → W^± W^∓) process for m_Z'=0.5 TeV, shown in dashed blue.

Observed upper limits at 95% C.L. on σ(pp → s χχ) × B(s → W^± W^∓) for m_Z'=1 TeV as a function of m_s. The expected limits, varied up and down by one and two standard deviations, are shown as green and yellow bands, respectively. The observed and expected limits are compared to the theoretical LO cross section for the σ(pp → s χχ) × B(s → W^± W^∓) process for m_Z'=1 TeV, shown in dashed blue.

Observed upper limits at 95% C.L. on σ(pp → s χχ) × B(s → W^± W^∓) for m_Z'=1.7 TeV as a function of m_s. The expected limits, varied up and down by one and two standard deviations, are shown as green and yellow bands, respectively. The observed and expected limits are compared to the theoretical LO cross section for the σ(pp → s χχ) × B(s → W^± W^∓) process for m_Z'=1.7 TeV, shown in dashed blue.

Observed upper limits at 95% C.L. on σ(pp → s χχ) × B(s → W^± W^∓) for m_Z'=2.1 TeV as a function of m_s. The expected limits, varied up and down by one and two standard deviations, are shown as green and yellow bands, respectively. The observed and expected limits are compared to the theoretical LO cross section for the σ(pp → s χχ) × B(s → W^± W^∓) process for m_Z'=2.1 TeV, shown in dashed blue.

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

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

Cumulative efficiencies in the merged category for three representative dark Higgs signal scenarios with g_q=0.25, g_χ=1.0, sinθ=0.01, m_Z' = 1 TeV, and m_χ=200 GeV considering s→W(ℓν)W(qq) decays only.

Cumulative efficiencies in the resolved category for three representative dark Higgs signal scenarios with g_q=0.25, g_χ=1.0, sinθ=0.01, m_Z' = 1 TeV, and m_χ=200 GeV considering s→W(ℓν)W(qq) decays only.

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

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

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

The unfolded differential charge asymmetry as a function of the transverse momentum of the top pair system. The measured values are given with statistical and systematic uncertainties. The SM theory predictions calculated at NNLO in QCD and NLO in EW theory are listed. The scale uncertainty is obtained by varying renormalisation and factorisation scales independently by a factor of 2 or 0.5 around $\mu_0$ to calculate the maximum and minimum value of the asymmetry, respectively. The nominal value $\mu_0$ is chosen as $H_T/4$. The variations in which one scale is multiplied by 2 while the other scale is divided by 2 are excluded. Finally, the scale and MC integration uncertainties are added in quadrature.

The unfolded differential charge asymmetry as a function of the longitudinal boost of the top pair system. The measured values are given with statistical and systematic uncertainties. The SM theory predictions calculated at NNLO in QCD and NLO in EW theory are listed. The scale uncertainty is obtained by varying renormalisation and factorisation scales independently by a factor of 2 or 0.5 around $\mu_0$ to calculate the maximum and minimum value of the asymmetry, respectively. The nominal value $\mu_0$ is chosen as $H_T/4$. The variations in which one scale is multiplied by 2 while the other scale is divided by 2 are excluded. Finally, the scale and MC integration uncertainties are added in quadrature.

The unfolded inclusive leptonic asymmetry. The unfolded $A_C^{\ell\bar{\ell}}$ is obtained in the reduced phase-space defined by the requirement $|\Delta |\eta_{\ell\bar{\ell}}||<2.5$. The measured values are given with statistical and systematic uncertainties. The SM theory predictions calculated at NLO in QCD and NLO in EW theory are listed. The theory uncertainty is obtained by varying both scales by a factor of 0.5 or 2.0 to calculate the minimum and maximum value of the asymmetry, respectively.

The unfolded differential leptonic asymmetry as a function of the invariant mass of the di-lepton pair. The unfolded $A_C^{\ell\bar{\ell}}$ is obtained in the reduced phase-space defined by the requirement $|\Delta |\eta_{\ell\bar{\ell}}||<2.5$. The measured values are given with statistical and systematic uncertainties. The SM theory predictions calculated at NLO in QCD and NLO in EW theory are listed. The theory uncertainty is obtained by varying both scales by a factor of 0.5 or 2.0 to calculate the minimum and maximum value of the asymmetry, respectively.

The unfolded differential leptonic asymmetry as a function of the transverse momentum of the di-lepton pair. The unfolded $A_C^{\ell\bar{\ell}}$ is obtained in the reduced phase-space defined by the requirement $|\Delta |\eta_{\ell\bar{\ell}}||<2.5$. The measured values are given with statistical and systematic uncertainties. The SM theory predictions calculated at NLO in QCD and NLO in EW theory are listed. The theory uncertainty is obtained by varying both scales by a factor of 0.5 or 2.0 to calculate the minimum and maximum value of the asymmetry, respectively.

The unfolded differential leptonic asymmetry as a function of the longitudinal boost of the di-lepton pair. The unfolded $A_C^{\ell\bar{\ell}}$ is obtained in the reduced phase-space defined by the requirement $|\Delta |\eta_{\ell\bar{\ell}}||<2.5$. The measured values are given with statistical and systematic uncertainties. The SM theory predictions calculated at NLO in QCD and NLO in EW theory are listed. The theory uncertainty is obtained by varying both scales by a factor of 0.5 or 2.0 to calculate the minimum and maximum value of the asymmetry, respectively.

Individual 68% and 95% CL bounds on the relevant Wilson coefficients of the SM Effective Field Theory in units of $\text{TeV}^{-2}$. The bounds are derived from the $A_C^{t\bar{t}}$ inclusive measurement. The experimental uncertainties are accounted for, in the form of the complete covariance matrix that keeps track of correlations between bins for the differential measurement. The theory uncertainty from the NNLO QCD + NLO EW calculation is included by explicitly varying the renormalization and factorization scales, or the parton density functions, in the calculation and registering the variations in the intervals.

Individual 68% and 95% CL bounds on the relevant Wilson coefficients of the SM Effective Field Theory in units of $\text{TeV}^{-2}$. The bounds are derived from the $A_C^{t\bar{t}}$ vs $m_{t\bar{t}}$ measurement. The experimental uncertainties are accounted for, in the form of the complete covariance matrix that keeps track of correlations between bins for the differential measurement. The theory uncertainty from the NNLO QCD + NLO EW calculation is included by explicitly varying the renormalization and factorization scales, or the parton density functions, in the calculation and registering the variations in the intervals.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ inclusive measurement. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $\beta_{z,t\bar{t}}$ measurement for $\beta_{z,t\bar{t}}$ $\in$ [0,0.3]. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $\beta_{z,t\bar{t}}$ measurement for $\beta_{z,t\bar{t}}$ $\in$ [0.3,0.6]. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $\beta_{z,t\bar{t}}$ measurement for $\beta_{z,t\bar{t}}$ $\in$ [0.6,0.8]. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $\beta_{z,t\bar{t}}$ measurement for $\beta_{z,t\bar{t}}$ $\in$ [0.8,1]. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $m_{t\bar{t}}$ measurement for $m_{t\bar{t}}$ < 500 GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $m_{t\bar{t}}$ measurement for $m_{t\bar{t}}$ $\in$ [500,750] GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $m_{t\bar{t}}$ measurement for $m_{t\bar{t}}$ $\in$ [750,1000] GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $m_{t\bar{t}}$ measurement for $m_{t\bar{t}}$ $\in$ [1000,1500] GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $m_{t\bar{t}}$ measurement for $m_{t\bar{t}}$ > 1500 GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $p_{T,t\bar{t}}$ measurement for $p_{T,t\bar{t}}$ < 30 GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $p_{T,t\bar{t}}$ measurement for $p_{T,t\bar{t}}$ $\in$ [30,120] GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $p_{T,t\bar{t}}$ measurement for $p_{T,t\bar{t}}$ > 120 GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ inclusive measurement. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ vs $\beta_{z,\ell\bar{\ell}}$ measurement for $\beta_{z,\ell\bar{\ell}}$ $\in$[0,0.3]. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ vs $\beta_{z,\ell\bar{\ell}}$ measurement for $\beta_{z,\ell\bar{\ell}}$ $\in$[0.3,0.6]. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ vs $\beta_{z,\ell\bar{\ell}}$ measurement for $\beta_{z,\ell\bar{\ell}}$ $\in$[0.6,0.8]. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ vs $\beta_{z,\ell\bar{\ell}}$ measurement for $\beta_{z,\ell\bar{\ell}}$ $\in$[0.8,1]. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ vs $m_{\ell\bar{\ell}}$ measurement for $m_{\ell\bar{\ell}}$ < 200 GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ vs $m_{\ell\bar{\ell}}$ measurement for $m_{\ell\bar{\ell}}$ $\in$ [200,300] GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ vs $m_{\ell\bar{\ell}}$ measurement for $m_{\ell\bar{\ell}}$ $\in$ [300,400] GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ vs $m_{\ell\bar{\ell}}$ measurement for $m_{\ell\bar{\ell}}$ > 400 GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ vs $p_{T,\ell\bar{\ell}}$ measurement for $p_{T,\ell\bar{\ell}}$ < 20 GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ vs $p_{T,\ell\bar{\ell}}$ measurement for $p_{T,\ell\bar{\ell}}$ $\in$ [20, 70] GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ vs $p_{T,\ell\bar{\ell}}$ measurement for $p_{T,\ell\bar{\ell}}$ > 70 GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Post-marginalisation correlation coefficients $\rho_{ij}$ of nuisance parameters for the $A_C^{t\bar{t}}$ inclusive measurement. Only $|\rho_{ij}| > 0.05$ values are included.

Post-marginalisation correlation coefficients $\rho_{ij}$ of nuisance parameters for the $A_C^{t\bar{t}}$ vs $m_{t\bar{t}}$ measurement. Only $|\rho_{ij}| > 0.05$ values are included.

Post-marginalisation correlation coefficients $\rho_{ij}$ of nuisance parameters for the $A_C^{t\bar{t}}$ vs $p_{T,t\bar{t}}$ measurement. Only $|\rho_{ij}| > 0.05$ values are included.

Post-marginalisation correlation coefficients $\rho_{ij}$ of nuisance parameters for the $A_C^{t\bar{t}}$ vs $\beta_{z,t\bar{t}}$ measurement. Only $|\rho_{ij}| > 0.05$ values are included.

Post-marginalisation correlation coefficients $\rho_{ij}$ of nuisance parameters for the $A_C^{\ell\ell}$ inclusive measurement. Only $|\rho_{ij}| > 0.05$ values are included.

Post-marginalisation correlation coefficients $\rho_{ij}$ of nuisance parameters for the $A_C^{\ell\ell}$ vs $m_{\ell\bar{\ell}}$ measurement. Only $|\rho_{ij}| > 0.05$ values are included.

Post-marginalisation correlation coefficients $\rho_{ij}$ of nuisance parameters for the $A_C^{\ell\ell}$ vs $p_{T,\ell\bar{\ell}}$ measurement. Only $|\rho_{ij}| > 0.05$ values are included.

Post-marginalisation correlation coefficients $\rho_{ij}$ of nuisance parameters for the $A_C^{\ell\ell}$ vs $\beta_{z,\ell\bar{\ell}}$ measurement. Only $|\rho_{ij}| > 0.05$ values are included.

Covariance matrix for the $A_C^{t\bar{t}}$ vs $m_{t\bar{t}}$ measurement.

Covariance matrix for the $A_C^{t\bar{t}}$ vs $p_{T,t\bar{t}}$ measurement.

Covariance matrix for the $A_C^{t\bar{t}}$ vs $\beta_{z,t\bar{t}}$ measurement.

Covariance matrix for the $A_C^{\ell\ell}$ vs $m_{\ell\bar{\ell}}$ measurement.

Covariance matrix for the $A_C^{\ell\ell}$ vs $p_{T,\ell\bar{\ell}}$ measurement.

Covariance matrix for the $A_C^{\ell\ell}$ vs $\beta_{z,\ell\bar{\ell}}$ measurement.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Breakdown of systematic uncertainties in percent for the measured fiducial cross section times leptonic branching ratio for Z/gamma* production in the Z/gamma* -> mu+mu- final state at 13TeV.

Measured fiducial cross section times leptonic branching ratio for Z/gamma* production in the combined Z/gamma* -> l+l- (l = e, mu) final state.

Measured total cross section times leptonic branching ratio for Z/gamma* production in the combined Z/gamma* -> l+ l- (l = e, mu) final state.

Measured total cross-section for ttbar events using e-mu events with b-tagged jets.

Correlation coefficients amongst the combined (Z/gamma^* -> l+ l-) where (l = e, mu) fiducial cross section and ttbar total cross section at 13, 8, and 7TeV.

Correlation coefficients amongst the combined (Z/gamma^* -> l+ l-) where (l = e, mu) fiducial cross section and ttbar total cross section at 13, 8, and 7TeV, omitting the common normalisation uncertainty due to the luminosity calibration and beam energy.

Z-boson and ttbar production cross-section single ratios at 13, 8, 7TeV. The beam-energy uncertainty, which largely cancels in the ratios, is included in the systematic uncertainty. In the first column, the total (TOT) cross sections are used for both numerator and denominator. In the second column, the total cross section is used for the numerator while the fiducial (FID) cross section is used for the denominator. In the third column, the fiducial cross sections are used for both numerator and denominator. Apart for the MZ requirement, the kinematic fiducial requirements listed below apply only to the fiducial cross sections. The luminosity uncertainty almost entirely cancels in some of the ratio measurements.

Z-boson and ttbar production cross-section double ratios at 13, 8, 7TeV. The beam-energy uncertainty, which largely cancels in the ratios, is included in the systematic uncertainty. In the first column, the total (TOT) cross sections are used for both ttbar and Z processes. In the second column, the total cross section is used for ttbar while the fiducial (FID) cross section is used for Z. In the third column, the fiducial cross sections are used for both ttbar and Z. Apart for the MZ requirement, the kinematic fiducial requirements listed below apply only to the fiducial cross sections.

Measured fiducial cross sections for successive exclusive jet multiplicities in the muon channel. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for successive exclusive jet multiplicities in the combined electron and muon channels. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for successive exclusive jet multiplicities in the combined electron and muon channels. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for successive inclusive jet multiplicities in the electron channel. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for successive inclusive jet multiplicities in the electron channel. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for successive inclusive jet multiplicities in the muon channel. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for successive inclusive jet multiplicities in the muon channel. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for successive inclusive jet multiplicities in the combined electron and muon channels. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for successive inclusive jet multiplicities in the combined electron and muon channels. The statistical, systematic, and luminosity uncertainties are given.

Measured ratios of the fiducial cross sections for successive inclusive jet multiplicities in the electron channel. The statistical, systematic, and luminosity uncertainties are given.

Measured ratios of the fiducial cross sections for successive inclusive jet multiplicities in the electron channel. The statistical, systematic, and luminosity uncertainties are given.

Measured ratios of the fiducial cross sections for successive inclusive jet multiplicities in the muon channel. The statistical, systematic, and luminosity uncertainties are given.

Measured ratios of the fiducial cross sections for successive inclusive jet multiplicities in the muon channel. The statistical, systematic, and luminosity uncertainties are given.

Measured ratios of the fiducial cross sections for successive inclusive jet multiplicities in the combined electron and muons channels. The statistical, systematic, and luminosity uncertainties are given.

Measured ratios of the fiducial cross sections for successive inclusive jet multiplicities in the combined electron and muons channels. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for the jet $p_{\text{T}}$ in exclusive $Z/\gamma^*(\rightarrow ee)$+1 jet events. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for the jet $p_{\text{T}}$ in exclusive $Z/\gamma^*(\rightarrow ee)$+1 jet events. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for the jet $p_{\text{T}}$ in exclusive $Z/\gamma^*(\rightarrow\mu\mu)$+1 jet events. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for the jet $p_{\text{T}}$ in exclusive $Z/\gamma^*(\rightarrow\mu\mu)$+1 jet events. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for the jet $p_{\text{T}}$ in exclusive $Z/\gamma^*(\rightarrow\ell\ell)$+1 jet events. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for the jet $p_{\text{T}}$ in exclusive $Z/\gamma^*(\rightarrow\ell\ell)$+1 jet events. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for the leading jet $p_{\text{T}}$ in $Z/\gamma^*(\rightarrow ee)$+>=1 jet events. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for the leading jet $p_{\text{T}}$ in $Z/\gamma^*(\rightarrow ee)$+>=1 jet events. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for the leading jet $p_{\text{T}}$ in $Z/\gamma^*(\rightarrow\mu\mu)$+>=1 jet events. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for the leading jet $p_{\text{T}}$ in $Z/\gamma^*(\rightarrow\mu\mu)$+>=1 jet events. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for the leading jet $p_{\text{T}}$ in $Z/\gamma^*(\righarrow\ell\ell)$+>=1 jet events. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for the leading jet $p_{\text{T}}$ in $Z/\gamma^*(\rightarrow\ell\ell)$+>=1 jet events. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for the leading jet $p_{\text{T}}$ in $Z/\gamma^*(\rightarrow ee)$+>=2 jet events. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for the leading jet $p_{\text{T}}$ in $Z/\gamma^*(\rightarrow ee)$+>=2 jet events. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for the leading jet $p_{\text{T}}$ in $Z/\gamma^*(\rightarrow\mu\mu)$+>=2 jet events. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for the leading jet $p_{\text{T}}$ in $Z/\gamma^*(\rightarrow\mu\mu)$+>=2 jet events. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for the leading jet $p_{\text{T}}$ in $Z/\gamma^*(\rightarrow\ell\ell)$+>=2 jet events. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for the leading jet $p_{\text{T}}$ in $Z/\gamma^*(\rightarrow\ell\ell)$+>=2 jet events. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for the leading jet $p_{\text{T}}$ in $Z/\gamma^*(\rightarrow ee)$+>=3 jet events. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for the leading jet $p_{\text{T}}$ in $Z/\gamma^*(\rightarrow ee)$+>=3 jet events. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for the leading jet $p_{\text{T}}$ in $Z/\gamma^*(\rightarrow\mu\mu)$+>=3 jet events. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for the leading jet $p_{\text{T}}$ in $Z/\gamma^*(\rightarrow\mu\mu)$+>=3 jet events. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for the leading jet $p_{\text{T}}$ in $Z/\gamma^*(\rightarrow\ell\ell)$+>=3 jet events. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for the leading jet $p_{\text{T}}$ in $Z/\gamma^*(\rightarrow\ell\ell)$+>=3 jet events. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for the leading jet $p_{\text{T}}$ in $Z/\gamma^*(\rightarrow ee)$+>=4 jet events. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for the leading jet $p_{\text{T}}$ in $Z/\gamma^*(\rightarrow ee)$+>=4 jet events. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for the leading jet $p_{\text{T}}$ in $Z/\gamma^*(\rightarrow\mu\mu)$+>=4 jet events. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for the leading jet $p_{\text{T}}$ in $Z/\gamma^*(\rightarrow\mu\mu)$+>=4 jet events. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for the leading jet $p_{\text{T}}$ in $Z/\gamma^*(\rightarrow\ell\ell)$+>=4 jet events. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for the leading jet $p_{\text{T}}$ in $Z/\gamma^*(\rightarrow\ell\ell)$+>=4 jet events. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for the leading jet |y| in the electron channel. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for the leading jet |y| in the electron channel. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for the leading jet |y| in the muon channel. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for the leading jet |y| in the muon channel. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for the leading jet |y| in the combined electron and muon channels. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for the leading jet |y| in the combined electron and muon channels. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for $H_{\text{T}}$ in the electron channel. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for $H_{\text{T}}$ in the electron channel. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for $H_{\text{T}}$ in the muon channel. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for $H_{\text{T}}$ in the muon channel. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for $H_{\text{T}}$ in the combined electron and muon channels. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for $H_{\text{T}}$ in the combined electron and muon channels. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for $\Delta\phi_{jj}$ in the electron channel. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for $\Delta\phi_{jj}$ in the electron channel. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for $\Delta\phi_{jj}$ in the muon channel. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for $\Delta\phi_{jj}$ in the muon channel. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for $\Delta\phi_{jj}$ in the combined electron and muon channels. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for $\Delta\phi_{jj}$ in the combined electron and muon channels. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for $m_{jj}$ in the electron channel. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for $m_{jj}$ in the electron channel. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for $m_{jj}$ in the muon channel. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for $m_{jj}$ in the muon channel. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for $m_{jj}$ in the combined electron and muon channels. The statistical, systematic, and luminosity uncertainties are given.

Measured fiducial cross sections for $m_{jj}$ in the combined electron and muon channels. The statistical, systematic, and luminosity uncertainties are given.

Systematic uncertainties for the exclusive jet multiplicities in the electron channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for the exclusive jet multiplicities in the electron channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for the exclusive jet multiplicities in the muon channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for the exclusive jet multiplicities in the muon channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for the inclusive jet multiplicities in the electron channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for the inclusive jet multiplicities in the electron channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for the inclusive jet multiplicities in the muon channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for the inclusive jet multiplicities in the muon channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for the inclusive jet multiplicity ratio in the electron channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for the inclusive jet multiplicity ratio in the electron channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for the inclusive jet multiplicity ratio in the muon channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for the inclusive jet multiplicity ratio in the muon channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for the jet $p_{\text{T}}$ in exclusive $Z/\gamma^*(\rightarrow ee)$+1 jet events in the electron channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for the jet $p_{\text{T}}$ in exclusive $Z/\gamma^*(\rightarrow ee)$+1 jet events in the electron channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for the jet $p_{\text{T}}$ in exclusive $Z/\gamma^*(\rightarrow\mu\mu)$+1 jet events in the electron channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for the jet $p_{\text{T}}$ in exclusive $Z/\gamma^*(\rightarrow\mu\mu)$+1 jet events in the electron channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for the leading jet $p_{\text{T}}$ in $Z/\gamma^*(\rightarrow ee)$+>=1 jet events in the electron channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for the leading jet $p_{\text{T}}$ in $Z/\gamma^*(\rightarrow ee)$+>=1 jet events in the electron channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for the leading jet $p_{\text{T}}$ in $Z/\gamma^*(\rightarrow\mu\mu)$+>=1 jet events in the electron channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for the leading jet $p_{\text{T}}$ in $Z/\gamma^*(\rightarrow\mu\mu)$+>=1 jet events in the electron channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for the leading jet $p_{\text{T}}$ in $Z/\gamma^*(\rightarrow ee)$+>=2 jet events in the electron channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for the leading jet $p_{\text{T}}$ in $Z/\gamma^*(\rightarrow ee)$+>=2 jet events in the electron channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for the leading jet $p_{\text{T}}$ in $Z/\gamma^*(\rightarrow\mu\mu)$+>=2 jet events in the electron channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for the leading jet $p_{\text{T}}$ in $Z/\gamma^*(\rightarrow\mu\mu)$+>=2 jet events in the electron channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for the leading jet $p_{\text{T}}$ in $Z/\gamma^*(\rightarrow ee)$+>=3 jet events in the electron channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for the leading jet $p_{\text{T}}$ in $Z/\gamma^*(\rightarrow ee)$+>=3 jet events in the electron channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for the leading jet $p_{\text{T}}$ in $Z/\gamma^*(\rightarrow\mu\mu)$+>=3 jet events in the electron channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for the leading jet $p_{\text{T}}$ in $Z/\gamma^*(\rightarrow\mu\mu)$+>=3 jet events in the electron channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for the leading jet $p_{\text{T}}$ in $Z/\gamma^*(\rightarrow ee)$+>=4 jet events in the electron channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for the leading jet $p_{\text{T}}$ in $Z/\gamma^*(\rightarrow ee)$+>=4 jet events in the electron channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for the leading jet $p_{\text{T}}$ in $Z/\gamma^*(\rightarrow\mu\mu)$+>=4 jet events in the electron channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for the leading jet $p_{\text{T}}$ in $Z/\gamma^*(\rightarrow\mu\mu)$+>=4 jet events in the electron channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for |y(jet)| in the electron channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for |y(jet)| in the electron channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for |y(jet)| in the muon channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for |y(jet)| in the muon channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for $H_{\text{T}}$ in the electron channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for $H_{\text{T}}$ in the electron channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for $H_{\text{T}}$ in the muon channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for $H_{\text{T}}$ in the muon channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for $\Delta\phi_{jj}$ in the electron channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for $\Delta\phi_{jj}$ in the electron channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for Deltaphijj in the muon channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for $\Delta\phi_{jj}$ in the muon channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for mjj in the electron channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for $m_{jj}$ in the electron channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for mjj in the muon channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Systematic uncertainties for $m_{jj}$ in the muon channel. The uncertainties are presented as a percentage of the measured cross-section for the upward variation of each source of uncertainty in each bin.

Non-perturbative corrections for successive exclusive jet multiplicities.

Non-perturbative corrections for successive exclusive jet multiplicities.

Non-perturbative corrections for successive inclusive jet multiplicities.

Non-perturbative corrections for successive inclusive jet multiplicities.

Non-perturbative corrections for inclusive jet multiplicity ratios.

Non-perturbative corrections for inclusive jet multiplicity ratios.

Non-perturbative corrections for the jet pT in Z/gamma*(->ll)+1 jet events.

Non-perturbative corrections for the jet $p_{\text{T}}$ in $Z/\gamma^*(\rightarrow\ell\ell)$+1 jet events.

Non-perturbative corrections for the leading jet pT in Z/gamma*(->ll)+>=1 jet events.

Non-perturbative corrections for the leading jet $p_{\text{T}}$ in $Z/\gamma^*(\rightarrow\ell\ell)$+>=1 jet events.

Non-perturbative corrections for the leading jet pT in Z/gamma*(->ll)+>=2 jet events.

Non-perturbative corrections for the leading jet $p_{\text{T}}$ in $Z/\gamma^*(\rightarrow\ell\ell)$+>=2 jet events.

Non-perturbative corrections for the leading jet pT in Z/gamma*(->ll)+>=3 jet events.

Non-perturbative corrections for the leading jet $p_{\text{T}}$ in $Z/\gamma^*(\rightarrow\ell\ell)$+>=3 jet events.

Non-perturbative corrections for the leading jet pT in Z/gamma*(->ll)+>=4 jet events.

Non-perturbative corrections for the leading jet $p_{\text{T}}$ in $Z/\gamma^*(\rightarrow\ell\ell)$+>=4 jet events.

Non-perturbative corrections for |y(jet)|.

Non-perturbative corrections for |y(jet)|.

Non-perturbative corrections for HT.

Non-perturbative corrections for $H_{\text{T}}$.

Non-perturbative corrections for Deltaphijj.

Non-perturbative corrections for $\Delta\phi_{jj}$.

Non-perturbative corrections for mjj.

Non-perturbative corrections for $m_{jj}$.

Correction from the cross section calculated with leptons at the Born level to the cross section calculated with dressed leptons as a function of the exclusive jet multiplicity averaging the electron and muon channels derived with MG5_aMC+Py8 CKKWL. The uncertainty is obtained with Alpgen+Py6.

Correction from the cross section calculated with leptons at the Born level to the cross section calculated with dressed leptons as a function of the exclusive jet multiplicity averaging the electron and muon channels derived with MG5_aMC+Py8 CKKWL. The uncertainty is obtained with Alpgen+Py6.

Correction from the cross section calculated with leptons at the Born level to the cross section calculated with dressed leptons as a function of the inclusive jet multiplicity averaging the electron and muon channels derived with MG5_aMC+Py8 CKKWL. The uncertainty is obtained with Alpgen+Py6.

Correction from the cross section calculated with leptons at the Born level to the cross section calculated with dressed leptons as a function of the inclusive jet multiplicity averaging the electron and muon channels derived with MG5_aMC+Py8 CKKWL. The uncertainty is obtained with Alpgen+Py6.

Correction from the cross section calculated with leptons at the Born level to the cross section calculated with dressed leptons as a function of the inclusive jet multiplicity ratio averaging the electron and muon channels derived with MG5_aMC+Py8 CKKWL. The uncertainty is obtained with Alpgen+Py6.

Correction from the cross section calculated with leptons at the Born level to the cross section calculated with dressed leptons as a function of the inclusive jet multiplicity ratio averaging the electron and muon channels derived with MG5_aMC+Py8 CKKWL. The uncertainty is obtained with Alpgen+Py6.

Correction from the cross section calculated with leptons at the Born level to the cross section calculated with dressed leptons as a function of the jet pT for exclusive Z+1 jet events averaging the electron and muon channels derived with MG5_aMC+Py8 CKKWL. The uncertainty is obtained with Alpgen+Py6.

Correction from the cross section calculated with leptons at the Born level to the cross section calculated with dressed leptons as a function of the jet $p_{\text{T}}$ for exclusive Z+1 jet events averaging the electron and muon channels derived with MG5_aMC+Py8 CKKWL. The uncertainty is obtained with Alpgen+Py6.

Correction from the cross section calculated with leptons at the Born level to the cross section calculated with dressed leptons as a function of the leading jet pT for Z+>=1 jet events averaging the electron and muon channels derived with MG5_aMC+Py8 CKKWL. The uncertainty is obtained with Alpgen+Py6.

Correction from the cross section calculated with leptons at the Born level to the cross section calculated with dressed leptons as a function of the leading jet $p_{\text{T}}$ for Z+>=1 jet events averaging the electron and muon channels derived with MG5_aMC+Py8 CKKWL. The uncertainty is obtained with Alpgen+Py6.

Correction from the cross section calculated with leptons at the Born level to the cross section calculated with dressed leptons as a function of the leading jet pT for Z+>=2 jet events averaging the electron and muon channels derived with MG5_aMC+Py8 CKKWL. The uncertainty is obtained with Alpgen+Py6.

Correction from the cross section calculated with leptons at the Born level to the cross section calculated with dressed leptons as a function of the leading jet $p_{\text{T}}$ for Z+>=2 jet events averaging the electron and muon channels derived with MG5_aMC+Py8 CKKWL. The uncertainty is obtained with Alpgen+Py6.

Correction from the cross section calculated with leptons at the Born level to the cross section calculated with dressed leptons as a function of the leading jet pT for Z+>=3 jet events averaging the electron and muon channels derived with MG5_aMC+Py8 CKKWL. The uncertainty is obtained with Alpgen+Py6.

Correction from the cross section calculated with leptons at the Born level to the cross section calculated with dressed leptons as a function of the leading jet $p_{\text{T}}$ for Z+>=3 jet events averaging the electron and muon channels derived with MG5_aMC+Py8 CKKWL. The uncertainty is obtained with Alpgen+Py6.

Correction from the cross section calculated with leptons at the Born level to the cross section calculated with dressed leptons as a function of the leading jet pT for Z+>=4 jet events averaging the electron and muon channels derived with MG5_aMC+Py8 CKKWL. The uncertainty is obtained with Alpgen+Py6.

Correction from the cross section calculated with leptons at the Born level to the cross section calculated with dressed leptons as a function of the leading jet $p_{\text{T}}$ for Z+>=4 jet events averaging the electron and muon channels derived with MG5_aMC+Py8 CKKWL. The uncertainty is obtained with Alpgen+Py6.

Correction from the cross section calculated with leptons at the Born level to the cross section calculated with dressed leptons as a function of the leading jet |y| for Z+>=1 jet events averaging the electron and muon channels derived with MG5_aMC+Py8 CKKWL. The uncertainty is obtained with Alpgen+Py6.

Correction from the cross section calculated with leptons at the Born level to the cross section calculated with dressed leptons as a function of the leading jet |y| for Z+>=1 jet events averaging the electron and muon channels derived with MG5_aMC+Py8 CKKWL. The uncertainty is obtained with Alpgen+Py6.

Correction from the cross section calculated with leptons at the Born level to the cross section calculated with dressed leptons as a function of HT averaging the electron and muon channels derived with MG5_aMC+Py8 CKKWL. The uncertainty is obtained with Alpgen+Py6.

Correction from the cross section calculated with leptons at the Born level to the cross section calculated with dressed leptons as a function of $H_{\text{T}}$ averaging the electron and muon channels derived with MG5_aMC+Py8 CKKWL. The uncertainty is obtained with Alpgen+Py6.

Correction from the cross section calculated with leptons at the Born level to the cross section calculated with dressed leptons as a function of Deltaphijj for Z+>=2 jet events averaging the electron and muon channels derived with MG5_aMC+Py8 CKKWL. The uncertainty is obtained with Alpgen+Py6.

Correction from the cross section calculated with leptons at the Born level to the cross section calculated with dressed leptons as a function of $\Delta\phi_{jj}$ for Z+>=2 jet events averaging the electron and muon channels derived with MG5_aMC+Py8 CKKWL. The uncertainty is obtained with Alpgen+Py6.

Correction from the cross section calculated with leptons at the Born level to the cross section calculated with dressed leptons as a function of the mjj for Z+>=2 jet events averaging the electron and muon channels derived with MG5_aMC+Py8 CKKWL. The uncertainty is obtained with Alpgen+Py6.

Correction from the cross section calculated with leptons at the Born level to the cross section calculated with dressed leptons as a function of the $m_{jj}$ for Z+>=2 jet events averaging the electron and muon channels derived with MG5_aMC+Py8 CKKWL. The uncertainty is obtained with Alpgen+Py6.

Multiplicity of additional jets with pt>80GeV

Transverse momentum of leading b-jet

Transverse momentum of sub-leading b-jet

Transverse momentum of leading (highest pt) additional jet

Measured Gap fraction within |y|<0.8 as a function of Q0

Measured Gap fraction within 0.8<|y|<1.5 as a function of Q0

Measured Gap fraction within 1.5<|y|<2.1 as a function of Q0

Measured Gap fraction within |y|<2.1 as a function of Q0

Measured Gap fraction within |y|<2.1 as a function of Q0 for invariant mass region m_{emubb} < 300GeV

Measured Gap fraction within |y|<2.1 as a function of Q0 for invariant mass region 300 GeV < m_{emubb} < 425GeV

Measured Gap fraction within |y|<2.1 as a function of Q0 for invariant mass region 425 GeV< m_{emubb} < 600GeV

Measured Gap fraction within |y|<2.1 as a function of Q0 for invariant mass region m_{emubb} > 600GeV

Measured Gap fraction within |y|<0.8 as a function of QSUM

Measured Gap fraction within 0.8<|y|<1.5 as a function of QSUM

Measured Gap fraction within 1.5<|y|<2.1 as a function of QSUM

Measured Gap fraction within |y|<2.1 as a function of QSUM

Measured Gap fraction within |y|<2.1 as a function of QSUM for invariant mass region m_{emubb} < 300GeV

Measured Gap fraction within |y|<2.1 as a function of QSUM for invariant mass region 300 GeV < m_{emubb} < 425 GeV

Measured Gap fraction within |y|<2.1 as a function of QSUM for invariant mass region 425GeV< m_{emubb} < 600GeV

Measured Gap fraction within |y|<2.1 as a function of QSUM for invariant mass region m_{emubb} > 600GeV

Extrapolation factors AWW -- used to extrapolate from the fiducial particle level to the total phase space.

Cross sections and ratios (13/8 TeV) -- experimental and PDF uncertainties are treated as uncorrelated, scale uncertainties are correlated between the different centre-of-mass energies.

DM exclusion limit in the two-dimensional phase space of WIMP mass m_&chi; vs mediator mass m_med determined using the combined ee+&mu;&mu; channel. Both the observed and expected limits are presented, and the 1&sigma; uncertainty band for the expected limits is also provided. Regions bounded by the limit curves are excluded at the 95% CL. The grey line labelled with "m_med = 2m_&chi;'' indicates the kinematic threshold where the mediator can decay on-shell into WIMPs, and the other grey line gives the perturbative limit (arXiv 1603.04156). The relic density line (arXiv 1603.04156) illustrates the combination of m_&chi; and m_med that would explain the observed DM relic density.

DM exclusion limit in the two-dimensional phase space of WIMP mass m_&chi; vs mediator mass m_med determined using the combined ee+&mu;&mu; channel. Both the observed and expected limits are presented, and the 1&sigma; uncertainty band for the expected limits is also provided. Regions bounded by the limit curves are excluded at the 95% CL. The grey line labelled with "m_med = 2m_&chi;'' indicates the kinematic threshold where the mediator can decay on-shell into WIMPs, and the other grey line gives the perturbative limit (arXiv 1603.04156). The relic density line (arXiv 1603.04156) illustrates the combination of m_&chi; and m_med that would explain the observed DM relic density.

DM exclusion limit in the two-dimensional phase space of WIMP mass m_&chi; vs mediator mass m_med determined using the combined ee+&mu;&mu; channel. Both the observed and expected limits are presented, and the 1&sigma; uncertainty band for the expected limits is also provided. Regions bounded by the limit curves are excluded at the 95% CL. The grey line labelled with "m_med = 2m_&chi;'' indicates the kinematic threshold where the mediator can decay on-shell into WIMPs, and the other grey line gives the perturbative limit (arXiv 1603.04156). The relic density line (arXiv 1603.04156) illustrates the combination of m_&chi; and m_med that would explain the observed DM relic density.

The 95% CL upper limits on the production cross-section of the ZH process with the prompt Z&rarr; ee and Z&rarr; &mu;&mu; decays and the invisible Higgs boson decays as a function of m_H, obtained from the combined ee+&mu;&mu; channel. The observed and expected limits are given, as well as the &pm;1&sigma; and &pm;2&sigma; error bands on the expected limits. The signal process is only modelled for the qq initial state, and the theory uncertainties on the signal prediction are not considered.

DM exclusion limit in the two-dimensional phase space of m_&chi; vs m_med set using the combined ee+&mu;&mu; channel. The DM model assumes a vector mediator, a fermionic WIMP, and the coupling parameters g_q = 0.25 and g_&chi; = 1. Both the observed and expected limits are presented, and the 1&sigma; uncertainty band for the expected limits is also provided. Regions bounded by the limit curves are excluded at the 95% CL. The grey line labelled with "m_med = 2m_&chi;'' indicates the kinematic threshold where the mediator can decay on-shell into WIMPs. The relic density line [arXiv 1603.04156] illustrates the combination of m_&chi; and m_med that would explain the observed DM relic density.

DM exclusion limit in the two-dimensional phase space of m_&chi; vs m_med set using the combined ee+&mu;&mu; channel. The DM model assumes a vector mediator, a fermionic WIMP, and the coupling parameters g_q = 0.25 and g_&chi; = 1. Both the observed and expected limits are presented, and the 1&sigma; uncertainty band for the expected limits is also provided. Regions bounded by the limit curves are excluded at the 95% CL. The grey line labelled with "m_med = 2m_&chi;'' indicates the kinematic threshold where the mediator can decay on-shell into WIMPs. The relic density line [arXiv 1603.04156] illustrates the combination of m_&chi; and m_med that would explain the observed DM relic density.

DM exclusion limit in the two-dimensional phase space of m_&chi; vs m_med set using the combined ee+&mu;&mu; channel. The DM model assumes a vector mediator, a fermionic WIMP, and the coupling parameters g_q = 0.25 and g_&chi; = 1. Both the observed and expected limits are presented, and the 1&sigma; uncertainty band for the expected limits is also provided. Regions bounded by the limit curves are excluded at the 95% CL. The grey line labelled with "m_med = 2m_&chi;'' indicates the kinematic threshold where the mediator can decay on-shell into WIMPs. The relic density line [arXiv 1603.04156] illustrates the combination of m_&chi; and m_med that would explain the observed DM relic density.

DM exclusion limit in the two-dimensional phase space of m_&chi; vs m_med set using the combined ee+&mu;&mu; channel. The DM model assumes a vector mediator, a fermionic WIMP, and the coupling parameters g_q = 0.25 and g_&chi; = 1. Both the observed and expected limits are presented, and the 1&sigma; uncertainty band for the expected limits is also provided. Regions bounded by the limit curves are excluded at the 95% CL. The grey line labelled with "m_med = 2m_&chi;'' indicates the kinematic threshold where the mediator can decay on-shell into WIMPs. The relic density line [arXiv 1603.04156] illustrates the combination of m_&chi; and m_med that would explain the observed DM relic density.

Limits on the WIMP and proton scattering cross section as a function of WIMP mass, obtained for simplified dark matter models with an axial-vector mediator (left) and a vector mediator (right). The solid black line shows the observed limit at the 90% confidence level from this search. The left plot incorporates the latest results from these competitive direct-search experiments, LUX [arXiv 1705.03380], PICO-2L [Phys. Rev. Lett. 114 (2015) 231302], and PICO-60 [arXiv 1702.07666]. The right plot incorporates the latest results from the following experiments, CRESST-II [Eur. Phys. J. C76 (2016) 25], CDMSlite [Phys. Rev. Lett. 116 (2016) 071301], PandaX-II [Phys. Rev. Lett. 117 (2016) 121303], LUX [Phys. Rev. Lett. 118 (2017) 021303], and XENON1T [arXiv 1705.06655].

Limits on the WIMP and proton scattering cross section as a function of WIMP mass, obtained for simplified dark matter models with an axial-vector mediator (left) and a vector mediator (right). The solid black line shows the observed limit at the 90% confidence level from this search. The left plot incorporates the latest results from these competitive direct-search experiments, LUX [arXiv 1705.03380], PICO-2L [Phys. Rev. Lett. 114 (2015) 231302], and PICO-60 [arXiv 1702.07666]. The right plot incorporates the latest results from the following experiments, CRESST-II [Eur. Phys. J. C76 (2016) 25], CDMSlite [Phys. Rev. Lett. 116 (2016) 071301], PandaX-II [Phys. Rev. Lett. 117 (2016) 121303], LUX [Phys. Rev. Lett. 118 (2017) 021303], and XENON1T [arXiv 1705.06655].

The c_2{4} values calculated for charged particles with 0.3 < pT < 3 GeV with the standard cumulant method from the 13 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for pT > 0.6 GeV.

The c_2{4} values calculated for charged particles with 0.5 < pT < 5 GeV with the standard cumulant method from the 13 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.5 < pT < 5 GeV.

The c_2{4} values calculated for charged particles with 0.5 < pT < 5 GeV with the standard cumulant method from the 13 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for pT > 0.2 GeV.

The c_2{4} values calculated for charged particles with 0.5 < pT < 5 GeV with the standard cumulant method from the 13 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for pT > 0.4 GeV.

The c_2{4} values calculated for charged particles with 0.5 < pT < 5 GeV with the standard cumulant method from the 13 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for pT > 0.6 GeV.

The c_2{4} values calculated for charged particles with 0.3 < pT < 3 GeV with the 2-subevent cumulant method from the 13 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.3 < pT < 3 GeV.

The c_2{4} values calculated for charged particles with 0.3 < pT < 3 GeV with the 2-subevent cumulant method from the 13 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for pT > 0.2 GeV.

The c_2{4} values calculated for charged particles with 0.3 < pT < 3 GeV with the 2-subevent cumulant method from the 13 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for pT > 0.4 GeV.

The c_2{4} values calculated for charged particles with 0.3 < pT < 3 GeV with the 2-subevent cumulant method from the 13 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for pT > 0.6 GeV.

The c_2{4} values calculated for charged particles with 0.5 < pT < 5 GeV with the 2-subevent cumulant method from the 13 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.5 < pT < 5 GeV.

The c_2{4} values calculated for charged particles with 0.5 < pT < 5 GeV with the 2-subevent cumulant method from the 13 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for pT > 0.2 GeV.

The c_2{4} values calculated for charged particles with 0.5 < pT < 5 GeV with the 2-subevent cumulant method from the 13 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for pT > 0.4 GeV.

The c_2{4} values calculated for charged particles with 0.5 < pT < 5 GeV with the 2-subevent cumulant method from the 13 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for pT > 0.6 GeV.

The c_2{4} values calculated for charged particles with 0.3 < pT < 3 GeV with the 3-subevent cumulant method from the 13 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.3 < pT < 3 GeV.

The c_2{4} values calculated for charged particles with 0.3 < pT < 3 GeV with the 3-subevent cumulant method from the 13 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for pT > 0.2 GeV.

The c_2{4} values calculated for charged particles with 0.3 < pT < 3 GeV with the 3-subevent cumulant method from the 13 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for pT > 0.4 GeV.

The c_2{4} values calculated for charged particles with 0.3 < pT < 3 GeV with the 3-subevent cumulant method from the 13 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for pT > 0.6 GeV.

The c_2{4} values calculated for charged particles with 0.5 < pT < 5 GeV with the 3-subevent cumulant method from the 13 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.5 < pT < 5 GeV.

The c_2{4} values calculated for charged particles with 0.5 < pT < 5 GeV with the 3-subevent cumulant method from the 13 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for pT > 0.2 GeV.

The c_2{4} values calculated for charged particles with 0.5 < pT < 5 GeV with the 3-subevent cumulant method from the 13 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for pT > 0.4 GeV.

The c_2{4} values calculated for charged particles with 0.5 < pT < 5 GeV with the 3-subevent cumulant method from the 13 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for pT > 0.6 GeV.

The c_2{4} values calculated for charged particles with 0.3 < pT < 3 GeV with the standard cumulant method from the 13 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.3 < pT < 3 GeV.

The c_2{4} values calculated for charged particles with 0.3 < pT < 3 GeV with the 2-subevent cumulant method from the 13 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.3 < pT < 3 GeV.

The c_2{4} values calculated for charged particles with 0.3 < pT < 3 GeV with the 3-subevent cumulant method from the 13 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.3 < pT < 3 GeV.

The c_2{4} values calculated for charged particles with 0.5 < pT < 5 GeV with the standard cumulant method from the 13 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.5 < pT < 5 GeV.

The c_2{4} values calculated for charged particles with 0.5 < pT < 5 GeV with the 2-subevent cumulant method from the 13 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.5 < pT < 5 GeV.

The c_2{4} values calculated for charged particles with 0.5 < pT < 5 GeV with the 3-subevent cumulant method from the 13 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.5 < pT < 5 GeV.

The c_2{4} values calculated for charged particles with 0.3 < pT < 3 GeV with the standard cumulant method from the 5.02 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.3 < pT < 3 GeV.

The c_2{4} values calculated for charged particles with 0.3 < pT < 3 GeV with the 2-subevent cumulant method from the 5.02 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.3 < pT < 3 GeV.

The c_2{4} values calculated for charged particles with 0.3 < pT < 3 GeV with the 3-subevent cumulant method from the 5.02 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.3 < pT < 3 GeV.

The c_2{4} values calculated for charged particles with 0.5 < pT < 5 GeV with the standard cumulant method from the 5.02 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.5 < pT < 5 GeV.

The c_2{4} values calculated for charged particles with 0.5 < pT < 5 GeV with the 2-subevent cumulant method from the 5.02 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.5 < pT < 5 GeV.

The c_2{4} values calculated for charged particles with 0.5 < pT < 5 GeV with the 3-subevent cumulant method from the 5.02 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.5 < pT < 5 GeV.

The c_2{4} values calculated for charged particles with 0.3 < pT < 3 GeV with the standard cumulant method from the 5.02 TeV p+Pb data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.3 < pT < 3 GeV.

The c_2{4} values calculated for charged particles with 0.3 < pT < 3 GeV with the 2-subevent cumulant method from the 5.02 TeV p+Pb data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.3 < pT < 3 GeV.

The c_2{4} values calculated for charged particles with 0.3 < pT < 3 GeV with the 3-subevent cumulant method from the 5.02 TeV p+Pb data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.3 < pT < 3 GeV.

The c_2{4} values calculated for charged particles with 0.5 < pT < 5 GeV with the standard cumulant method from the 5.02 TeV p+Pb data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.5 < pT < 5 GeV.

The c_2{4} values calculated for charged particles with 0.5 < pT < 5 GeV with the 2-subevent cumulant method from the 5.02 TeV p+Pb data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.5 < pT < 5 GeV.

The c_2{4} values calculated for charged particles with 0.5 < pT < 5 GeV with the 3-subevent cumulant method from the 5.02 TeV p+Pb data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.5 < pT < 5 GeV.

The c_3{4} values calculated for charged particles with 0.3 < pT < 3 GeV with the standard cumulant method from the 5.02 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.3 < pT < 3 GeV.

The c_3{4} values calculated for charged particles with 0.3 < pT < 3 GeV with the standard cumulant method from the 13 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.3 < pT < 3 GeV.

The c_3{4} values calculated for charged particles with 0.3 < pT < 3 GeV with the standard cumulant method from the 5.02 TeV p+Pb data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.3 < pT < 3 GeV.

The c_3{4} values calculated for charged particles with 0.3 < pT < 3 GeV with the 3-subevent cumulant method from the 5.02 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.3 < pT < 3 GeV.

The c_3{4} values calculated for charged particles with 0.3 < pT < 3 GeV with the 3-subevent cumulant method from the 13 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.3 < pT < 3 GeV.

The c_3{4} values calculated for charged particles with 0.3 < pT < 3 GeV with the 3-subevent cumulant method from the 5.02 TeV p+Pb data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.3 < pT < 3 GeV.

The c_3{4} values calculated for charged particles with 0.5 < pT < 5 GeV with the standard cumulant method from the 5.02 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.5 < pT < 5 GeV.

The c_3{4} values calculated for charged particles with 0.5 < pT < 5 GeV with the standard cumulant method from the 13 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.5 < pT < 5 GeV.

The c_3{4} values calculated for charged particles with 0.5 < pT < 5 GeV with the standard cumulant method from the 5.02 TeV p+Pb data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.5 < pT < 5 GeV.

The c_3{4} values calculated for charged particles with 0.5 < pT < 5 GeV with the 3-subevent cumulant method from the 5.02 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.5 < pT < 5 GeV.

The c_3{4} values calculated for charged particles with 0.5 < pT < 5 GeV with the 3-subevent cumulant method from the 13 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.5 < pT < 5 GeV.

The c_3{4} values calculated for charged particles with 0.5 < pT < 5 GeV with the 3-subevent cumulant method from the 5.02 TeV p+Pb data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.5 < pT < 5 GeV.

The c_3{4} values calculated for charged particles with 0.3 < pT < 3 GeV with the 3-subevent cumulant method from the 5.02 TeV p+Pb data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.3 < pT < 3 GeV.

The c_3{4} values calculated for charged particles with 0.3 < pT < 3 GeV with the 3-subevent cumulant method from the 5.02 TeV p+Pb data. The event averaging is performed for N_{ch}^{Sel} calculated for pT > 0.2 GeV.

The c_3{4} values calculated for charged particles with 0.3 < pT < 3 GeV with the 3-subevent cumulant method from the 5.02 TeV p+Pb data. The event averaging is performed for N_{ch}^{Sel} calculated for pT > 0.4 GeV.

The c_3{4} values calculated for charged particles with 0.3 < pT < 3 GeV with the 3-subevent cumulant method from the 5.02 TeV p+Pb data. The event averaging is performed for N_{ch}^{Sel} calculated for pT > 0.6 GeV.

The c_3{4} values calculated for charged particles with 0.5 < pT < 5 GeV with the 3-subevent cumulant method from the 5.02 TeV p+Pb data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.5 < pT < 5 GeV.

The c_3{4} values calculated for charged particles with 0.5 < pT < 5 GeV with the 3-subevent cumulant method from the 5.02 TeV p+Pb data. The event averaging is performed for N_{ch}^{Sel} calculated for pT > 0.2 GeV.

The c_3{4} values calculated for charged particles with 0.5 < pT < 5 GeV with the 3-subevent cumulant method from the 5.02 TeV p+Pb data. The event averaging is performed for N_{ch}^{Sel} calculated for pT > 0.4 GeV.

The c_3{4} values calculated for charged particles with 0.5 < pT < 5 GeV with the 3-subevent cumulant method from the 5.02 TeV p+Pb data. The event averaging is performed for N_{ch}^{Sel} calculated for pT > 0.6 GeV.

The v_2{4} values calculated for charged particles with 0.3 < pT < 3 GeV with the 3-subevent cumulant method from the 5.02 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.3 < pT < 3 GeV.

The v_2{4} values calculated for charged particles with 0.3 < pT < 3 GeV with the 3-subevent cumulant method from the 13 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.3 < pT < 3 GeV.

The v_2{4} values calculated for charged particles with 0.3 < pT < 3 GeV with the 3-subevent cumulant method from the 5.02 TeV p+Pb data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.3 < pT < 3 GeV.

The v_2{4} values calculated for charged particles with 0.5 < pT < 5 GeV with the 3-subevent cumulant method from the 5.02 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.5 < pT < 5 GeV.

The v_2{4} values calculated for charged particles with 0.5 < pT < 5 GeV with the 3-subevent cumulant method from the 13 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.5 < pT < 5 GeV.

The v_2{4} values calculated for charged particles with 0.5 < pT < 5 GeV with the 3-subevent cumulant method from the 5.02 TeV p+Pb data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.5 < pT < 5 GeV.

The N_s calculated for charged particles with 0.3 < pT < 3 GeV with the 3-subevent cumulant method from the 13 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.3 < pT < 3 GeV.

The N_s values calculated for charged particles with 0.3 < pT < 3 GeV with the 3-subevent cumulant method from the 5.02 TeV p+Pb data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.3 < pT < 3 GeV.

The N_s values calculated for charged particles with 0.5 < pT < 5 GeV with the 3-subevent cumulant method from the 13 TeV pp data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.5 < pT < 5 GeV.

The N_s values calculated for charged particles with 0.5 < pT < 5 GeV with the 3-subevent cumulant method from the 5.02 TeV p+Pb data. The event averaging is performed for N_{ch}^{Sel} calculated for 0.5 < pT < 5 GeV.

Selection acceptance times efficiency for VBF H -> ZZ -> vvqq as a function of the Higgs boson mass, combining the HP and LP signal regions.

Selection acceptance times efficiency for DY W' -> ZW -> llqq as a function of the W' mass, combining the HP and LP signal regions of the ZV -> llJ selection and the b-tagged and untagged regions of the ZV -> lljj selection.

Selection acceptance times efficiency for VBF W' -> ZW -> llqq as a function of the W' mass, combining the HP and LP signal regions of the ZV -> llJ selection and the b-tagged and untagged regions of the ZV -> lljj selection.

Selection acceptance times efficiency for DY W' -> ZW -> vvqq as a function of the W' mass, combining the HP and LP signal regions.

Selection acceptance times efficiency for VBF W' -> ZW -> vvqq as a function of the W' mass, combining the HP and LP signal regions.

Selection acceptance times efficiency for G* -> ZZ -> llqq as a function of the W' mass, combining the HP and LP signal regions of the ZV -> llJ selection and the b-tagged and untagged regions of the ZV -> lljj selection.

Selection acceptance times efficiency for G* -> ZZ -> vvqq as a function of the W' mass, combining the HP and LP signal regions.

Observed and expected 95% CL upper limits on $\sigma\times$BR($H\to ZZ$) at $\sqrt{s} = 13$ TeV for ggF production of a heavy Higgs boson as a function of its mass, combining $\ell\ell qq$ and $\nu\nu qq$ searches.

Observed and expected 95% CL upper limits on $\sigma\times$BR($H\to ZZ$) at $\sqrt{s} = 13$ TeV for VBF production of a heavy Higgs boson as a function of its mass, combining $\ell\ell qq$ and $\nu\nu qq$ searches.

Observed and expected 95% CL upper limits on $\sigma\times$BR($W'\to ZW$) at $\sqrt{s} = 13$ TeV for Drell-Yan production of a $W'$ boson in the HVT model as a function of its mass, combining $\ell\ell qq$ and $\nu\nu qq$ searches.

Observed and expected 95% CL upper limits on $\sigma\times$BR($W'\to ZW$) at $\sqrt{s} = 13$ TeV for VBF production of a $W'$ boson in the HVT model as a function of its mass, combining $\ell\ell qq$ and $\nu\nu qq$ searches.

Observed and expected 95% CL upper limits on $\sigma\times$BR($G_{\mathrm{KK}}\to ZZ$) at $\sqrt{s} = 13$ TeV for the production of a bulk RS graviton with couplings of $k/\overline{M}_{\mathrm{Pl}}=1$.

Observed and expected 95% CL upper limits on $\sigma\times$BR($G_{\mathrm{KK}}\to ZZ$) at $\sqrt{s} = 13$ TeV for the production of a bulk RS graviton with couplings of $k/\overline{M}_{\mathrm{Pl}}=0.5$.

Observed 95% CL upper limits on the production cross section times branching ratio to a photon and a quark or gluon for the ADD model. The limits are placed as a function of M_th. The calculation is performed using ensemble tests for masses in the search range every 500 GeV.

Fiducial acceptance and selection efficiency for the ADD model as a function of M_th.

Fiducial acceptance and selection efficiency for the RS1 model as a function of M_th.

Signal acceptance (in %) in the (BRe,BRtau) plane for a 800 GeV stop, for the SR1100 signal region.

Observed exclusion limit contour in the (BRe,BRtau) plane for a 600 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit contour in the (BRe,BRtau) plane for a 600 GeV stop. All limits are computed at 95% CL.

Signal efficiency (in %) in the (BRe,BRtau) plane for a 800 GeV stop, for the SR800 signal region.

Expected exclusion limit contour in the (BRe,BRtau) plane for a 700 GeV stop. All limits are computed at 95% CL.

Expected exclusion limit contour in the (BRe,BRtau) plane for a 700 GeV stop. All limits are computed at 95% CL.

Signal efficiency (in %) in the (BRe,BRtau) plane for a 800 GeV stop, for the SR1100 signal region.

Observed exclusion limit contour in the (BRe,BRtau) plane for a 700 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit contour in the (BRe,BRtau) plane for a 700 GeV stop. All limits are computed at 95% CL.

Signal acceptance (in %) in the (BRe,BRtau) plane for a 1200 GeV stop, for the SR800 signal region.

Expected exclusion limit contour in the (BRe,BRtau) plane for a 800 GeV stop. All limits are computed at 95% CL.

Expected exclusion limit contour in the (BRe,BRtau) plane for a 800 GeV stop. All limits are computed at 95% CL.

Signal acceptance (in %) in the (BRe,BRtau) plane for a 1200 GeV stop, for the SR1100 signal region.

Observed exclusion limit contour in the (BRe,BRtau) plane for a 800 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit contour in the (BRe,BRtau) plane for a 800 GeV stop. All limits are computed at 95% CL.

Signal efficiency (in %) in the (BRe,BRtau) plane for a 1200 GeV stop, for the SR800 signal region.

Expected exclusion limit contour in the (BRe,BRtau) plane for a 900 GeV stop. All limits are computed at 95% CL.

Expected exclusion limit contour in the (BRe,BRtau) plane for a 900 GeV stop. All limits are computed at 95% CL.

Signal efficiency (in %) in the (BRe,BRtau) plane for a 1200 GeV stop, for the SR1100 signal region.

Observed exclusion limit contour in the (BRe,BRtau) plane for a 900 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit contour in the (BRe,BRtau) plane for a 900 GeV stop. All limits are computed at 95% CL.

Signal acceptance (in %) in the (BRe,BRtau) plane for a 1500 GeV stop, for the SR800 signal region.

Expected exclusion limit contour in the (BRe,BRtau) plane for a 1000 GeV stop. All limits are computed at 95% CL.

Expected exclusion limit contour in the (BRe,BRtau) plane for a 1000 GeV stop. All limits are computed at 95% CL.

Signal acceptance (in %) in the (BRe,BRtau) plane for a 1500 GeV stop, for the SR1100 signal region.

Observed exclusion limit contour in the (BRe,BRtau) plane for a 1000 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit contour in the (BRe,BRtau) plane for a 1000 GeV stop. All limits are computed at 95% CL.

Signal efficiency (in %) in the (BRe,BRtau) plane for a 1500 GeV stop, for the SR800 signal region.

Expected exclusion limit contour in the (BRe,BRtau) plane for a 1050 GeV stop. All limits are computed at 95% CL.

Expected exclusion limit contour in the (BRe,BRtau) plane for a 1050 GeV stop. All limits are computed at 95% CL.

Signal efficiency (in %) in the (BRe,BRtau) plane for a 1500 GeV stop, for the SR1100 signal region.

Observed exclusion limit contour in the (BRe,BRtau) plane for a 1050 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit contour in the (BRe,BRtau) plane for a 1050 GeV stop. All limits are computed at 95% CL.

Expected exclusion limit contour in the (BRe,BRtau) plane for a 600 GeV stop. All limits are computed at 95% CL.

Expected exclusion limit contour in the (BRe,BRtau) plane for a 1100 GeV stop. All limits are computed at 95% CL.

Expected exclusion limit contour in the (BRe,BRtau) plane for a 1100 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit contour in the (BRe,BRtau) plane for a 600 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit contour in the (BRe,BRtau) plane for a 1100 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit contour in the (BRe,BRtau) plane for a 1100 GeV stop. All limits are computed at 95% CL.

Expected exclusion limit contour in the (BRe,BRtau) plane for a 700 GeV stop. All limits are computed at 95% CL.

Expected exclusion limit contour in the (BRe,BRtau) plane for a 1150 GeV stop. All limits are computed at 95% CL.

Expected exclusion limit contour in the (BRe,BRtau) plane for a 1150 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit contour in the (BRe,BRtau) plane for a 700 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit contour in the (BRe,BRtau) plane for a 1150 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit contour in the (BRe,BRtau) plane for a 1150 GeV stop. All limits are computed at 95% CL.

Expected exclusion limit contour in the (BRe,BRtau) plane for a 800 GeV stop. All limits are computed at 95% CL.

Expected exclusion limit contour in the (BRe,BRtau) plane for a 1200 GeV stop. All limits are computed at 95% CL.

Expected exclusion limit contour in the (BRe,BRtau) plane for a 1200 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit contour in the (BRe,BRtau) plane for a 800 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit contour in the (BRe,BRtau) plane for a 1200 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit contour in the (BRe,BRtau) plane for a 1200 GeV stop. All limits are computed at 95% CL.

Expected exclusion limit contour in the (BRe,BRtau) plane for a 900 GeV stop. All limits are computed at 95% CL.

Expected exclusion limit contour in the (BRe,BRtau) plane for a 1250 GeV stop. All limits are computed at 95% CL.

Expected exclusion limit contour in the (BRe,BRtau) plane for a 1250 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit contour in the (BRe,BRtau) plane for a 900 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit contour in the (BRe,BRtau) plane for a 1250 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit contour in the (BRe,BRtau) plane for a 1250 GeV stop. All limits are computed at 95% CL.

Expected exclusion limit contour in the (BRe,BRtau) plane for a 1000 GeV stop. All limits are computed at 95% CL.

Expected exclusion limit contour in the (BRe,BRtau) plane for a 1300 GeV stop. All limits are computed at 95% CL.

Expected exclusion limit contour in the (BRe,BRtau) plane for a 1300 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit contour in the (BRe,BRtau) plane for a 1000 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit contour in the (BRe,BRtau) plane for a 1300 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit contour in the (BRe,BRtau) plane for a 1300 GeV stop. All limits are computed at 95% CL.

Expected exclusion limit contour in the (BRe,BRtau) plane for a 1050 GeV stop. All limits are computed at 95% CL.

Expected exclusion limit contour in the (BRe,BRtau) plane for a 1350 GeV stop. All limits are computed at 95% CL.

Expected exclusion limit contour in the (BRe,BRtau) plane for a 1350 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit contour in the (BRe,BRtau) plane for a 1050 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit contour in the (BRe,BRtau) plane for a 1350 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit contour in the (BRe,BRtau) plane for a 1350 GeV stop. All limits are computed at 95% CL.

Expected exclusion limit contour in the (BRe,BRtau) plane for a 1100 GeV stop. All limits are computed at 95% CL.

Expected exclusion limit contour in the (BRe,BRtau) plane for a 1400 GeV stop. All limits are computed at 95% CL.

Expected exclusion limit contour in the (BRe,BRtau) plane for a 1400 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit contour in the (BRe,BRtau) plane for a 1100 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit contour in the (BRe,BRtau) plane for a 1400 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit contour in the (BRe,BRtau) plane for a 1400 GeV stop. All limits are computed at 95% CL.

Expected exclusion limit contour in the (BRe,BRtau) plane for a 1150 GeV stop. All limits are computed at 95% CL.

Expected exclusion limit contour in the (BRe,BRtau) plane for a 1450 GeV stop. All limits are computed at 95% CL.

Expected exclusion limit contour in the (BRe,BRtau) plane for a 1450 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit contour in the (BRe,BRtau) plane for a 1150 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit contour in the (BRe,BRtau) plane for a 1450 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit contour in the (BRe,BRtau) plane for a 1450 GeV stop. All limits are computed at 95% CL.

Expected exclusion limit contour in the (BRe,BRtau) plane for a 1200 GeV stop. All limits are computed at 95% CL.

Expected exclusion limit contour in the (BRe,BRtau) plane for a 1500 GeV stop. All limits are computed at 95% CL.

Expected exclusion limit contour in the (BRe,BRtau) plane for a 1500 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit contour in the (BRe,BRtau) plane for a 1200 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit contour in the (BRe,BRtau) plane for a 1500 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit contour in the (BRe,BRtau) plane for a 1500 GeV stop. All limits are computed at 95% CL.

Expected exclusion limit contour in the (BRe,BRtau) plane for a 1250 GeV stop. All limits are computed at 95% CL.

Signal acceptance (in %) in the (BRe,BRtau) plane for a 800 GeV stop, for the SR800 signal region.

Signal acceptance (in %) in the (BRe,BRtau) plane for a 800 GeV stop, for the SR800 signal region.

Observed exclusion limit contour in the (BRe,BRtau) plane for a 1250 GeV stop. All limits are computed at 95% CL.

Signal acceptance (in %) in the (BRe,BRtau) plane for a 800 GeV stop, for the SR1100 signal region.

Signal acceptance (in %) in the (BRe,BRtau) plane for a 800 GeV stop, for the SR1100 signal region.

Expected exclusion limit contour in the (BRe,BRtau) plane for a 1300 GeV stop. All limits are computed at 95% CL.

Signal efficiency (in %) in the (BRe,BRtau) plane for a 800 GeV stop, for the SR800 signal region.

Signal efficiency (in %) in the (BRe,BRtau) plane for a 800 GeV stop, for the SR800 signal region.

Observed exclusion limit contour in the (BRe,BRtau) plane for a 1300 GeV stop. All limits are computed at 95% CL.

Signal efficiency (in %) in the (BRe,BRtau) plane for a 800 GeV stop, for the SR1100 signal region.

Signal efficiency (in %) in the (BRe,BRtau) plane for a 800 GeV stop, for the SR1100 signal region.

Expected exclusion limit contour in the (BRe,BRtau) plane for a 1350 GeV stop. All limits are computed at 95% CL.

Signal acceptance (in %) in the (BRe,BRtau) plane for a 1200 GeV stop, for the SR800 signal region.

Signal acceptance (in %) in the (BRe,BRtau) plane for a 1200 GeV stop, for the SR800 signal region.

Observed exclusion limit contour in the (BRe,BRtau) plane for a 1350 GeV stop. All limits are computed at 95% CL.

Signal acceptance (in %) in the (BRe,BRtau) plane for a 1200 GeV stop, for the SR1100 signal region.

Signal acceptance (in %) in the (BRe,BRtau) plane for a 1200 GeV stop, for the SR1100 signal region.

Expected exclusion limit contour in the (BRe,BRtau) plane for a 1400 GeV stop. All limits are computed at 95% CL.

Signal efficiency (in %) in the (BRe,BRtau) plane for a 1200 GeV stop, for the SR800 signal region.

Signal efficiency (in %) in the (BRe,BRtau) plane for a 1200 GeV stop, for the SR800 signal region.

Observed exclusion limit contour in the (BRe,BRtau) plane for a 1400 GeV stop. All limits are computed at 95% CL.

Signal efficiency (in %) in the (BRe,BRtau) plane for a 1200 GeV stop, for the SR1100 signal region.

Signal efficiency (in %) in the (BRe,BRtau) plane for a 1200 GeV stop, for the SR1100 signal region.

Expected exclusion limit contour in the (BRe,BRtau) plane for a 1450 GeV stop. All limits are computed at 95% CL.

Signal acceptance (in %) in the (BRe,BRtau) plane for a 1500 GeV stop, for the SR800 signal region.

Signal acceptance (in %) in the (BRe,BRtau) plane for a 1500 GeV stop, for the SR800 signal region.

Observed exclusion limit contour in the (BRe,BRtau) plane for a 1450 GeV stop. All limits are computed at 95% CL.

Signal acceptance (in %) in the (BRe,BRtau) plane for a 1500 GeV stop, for the SR1100 signal region.

Signal acceptance (in %) in the (BRe,BRtau) plane for a 1500 GeV stop, for the SR1100 signal region.

Expected exclusion limit contour in the (BRe,BRtau) plane for a 1500 GeV stop. All limits are computed at 95% CL.

Signal efficiency (in %) in the (BRe,BRtau) plane for a 1500 GeV stop, for the SR800 signal region.

Signal efficiency (in %) in the (BRe,BRtau) plane for a 1500 GeV stop, for the SR800 signal region.

Observed exclusion limit contour in the (BRe,BRtau) plane for a 1500 GeV stop. All limits are computed at 95% CL.

Signal efficiency (in %) in the (BRe,BRtau) plane for a 1500 GeV stop, for the SR1100 signal region.

Signal efficiency (in %) in the (BRe,BRtau) plane for a 1500 GeV stop, for the SR1100 signal region.

$m_{bl}^{0}$ distribution in SR800. All selection criteria are applied, except the selection on the variable that is displayed in the plot. The SM backgrounds are normalized to the values determined in the background-only fit. The last bin includes overflows.

$m_{bl}^{0}$ distribution in SR800. All selection criteria are applied, except the selection on the variable that is displayed in the plot. The SM backgrounds are normalized to the values determined in the background-only fit. The last bin includes overflows.

$m_{bl}^{0}$ distribution in SR800. All selection criteria are applied, except the selection on the variable that is displayed in the plot. The SM backgrounds are normalized to the values determined in the background-only fit. The last bin includes overflows.

$m_{bl}^\mathrm{asym}$ distribution in SR800. All selection criteria are applied, except the selection on the variable that is displayed in the plot. The SM backgrounds are normalized to the values determined in the background-only fit. The last bin includes overflows.

$m_{bl}^\mathrm{asym}$ distribution in SR800. All selection criteria are applied, except the selection on the variable that is displayed in the plot. The SM backgrounds are normalized to the values determined in the background-only fit. The last bin includes overflows.

$m_{bl}^\mathrm{asym}$ distribution in SR800. All selection criteria are applied, except the selection on the variable that is displayed in the plot. The SM backgrounds are normalized to the values determined in the background-only fit. The last bin includes overflows.

$H_\mathrm{T}$ distribution in SR800. All selection criteria are applied, except the selection on the variable that is displayed in the plot. The SM backgrounds are normalized to the values determined in the background-only fit. The last bin includes overflows.

$H_\mathrm{T}$ distribution in SR800. All selection criteria are applied, except the selection on the variable that is displayed in the plot. The SM backgrounds are normalized to the values determined in the background-only fit. The last bin includes overflows.

$H_\mathrm{T}$ distribution in SR800. All selection criteria are applied, except the selection on the variable that is displayed in the plot. The SM backgrounds are normalized to the values determined in the background-only fit. The last bin includes overflows.

$m_{ll}$ distribution in SR800. All selection criteria are applied, except the selection on the variable that is displayed in the plot. The SM backgrounds are normalized to the values determined in the background-only fit. The last bin includes overflows.

$m_{ll}$ distribution in SR800. All selection criteria are applied, except the selection on the variable that is displayed in the plot. The SM backgrounds are normalized to the values determined in the background-only fit. The last bin includes overflows.

$m_{ll}$ distribution in SR800. All selection criteria are applied, except the selection on the variable that is displayed in the plot. The SM backgrounds are normalized to the values determined in the background-only fit. The last bin includes overflows.

$m_{bl}^{1}$(rej) distribution in SR800. All selection criteria are applied, except the selection on the variable that is displayed in the plot. The SM backgrounds are normalized to the values determined in the background-only fit. The last bin includes overflows.

$m_{bl}^{1}$(rej) distribution in SR800. All selection criteria are applied, except the selection on the variable that is displayed in the plot. The SM backgrounds are normalized to the values determined in the background-only fit. The last bin includes overflows.

$m_{bl}^{1}$(rej) distribution in SR800. All selection criteria are applied, except the selection on the variable that is displayed in the plot. The SM backgrounds are normalized to the values determined in the background-only fit. The last bin includes overflows.

Full list of event selections and MC generator-weighted yields and efficiencies in the inclusive SR800 and SR1100 signal regions for several signal samples of varying stop mass with decay into b-electron, b-muon or b-tau at 1/3 branching ratio.

Full list of event selections and MC generator-weighted yields and efficiencies in the inclusive SR800 and SR1100 signal regions for several signal samples of varying stop mass with decay into b-electron, b-muon or b-tau at 1/3 branching ratio.

Full list of event selections and MC generator-weighted yields and efficiencies in the inclusive SR800 and SR1100 signal regions for several signal samples of varying stop mass with decay into b-electron, b-muon or b-tau at 1/3 branching ratio.

Observed exclusion limit in the (BRe,BRtau) plane on the cross section for a 600 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit in the (BRe,BRtau) plane on the cross section for a 600 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit in the (BRe,BRtau) plane on the cross section for a 700 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit in the (BRe,BRtau) plane on the cross section for a 700 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit in the (BRe,BRtau) plane on the cross section for a 800 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit in the (BRe,BRtau) plane on the cross section for a 800 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit in the (BRe,BRtau) plane on the cross section for a 900 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit in the (BRe,BRtau) plane on the cross section for a 900 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit in the (BRe,BRtau) plane on the cross section for a 1000 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit in the (BRe,BRtau) plane on the cross section for a 1000 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit in the (BRe,BRtau) plane on the cross section for a 1050 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit in the (BRe,BRtau) plane on the cross section for a 1050 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit in the (BRe,BRtau) plane on the cross section for a 1100 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit in the (BRe,BRtau) plane on the cross section for a 1100 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit in the (BRe,BRtau) plane on the cross section for a 1150 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit in the (BRe,BRtau) plane on the cross section for a 1150 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit in the (BRe,BRtau) plane on the cross section for a 1200 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit in the (BRe,BRtau) plane on the cross section for a 1200 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit in the (BRe,BRtau) plane on the cross section for a 1250 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit in the (BRe,BRtau) plane on the cross section for a 1250 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit in the (BRe,BRtau) plane on the cross section for a 1300 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit in the (BRe,BRtau) plane on the cross section for a 1300 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit in the (BRe,BRtau) plane on the cross section for a 1350 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit in the (BRe,BRtau) plane on the cross section for a 1350 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit in the (BRe,BRtau) plane on the cross section for a 1400 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit in the (BRe,BRtau) plane on the cross section for a 1400 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit in the (BRe,BRtau) plane on the cross section for a 1450 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit in the (BRe,BRtau) plane on the cross section for a 1450 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit in the (BRe,BRtau) plane on the cross section for a 1500 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit in the (BRe,BRtau) plane on the cross section for a 1500 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit in the (BRe,BRtau) plane on the cross section for a 1550 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit in the (BRe,BRtau) plane on the cross section for a 1550 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit in the (BRe,BRtau) plane on the cross section for a 1600 GeV stop. All limits are computed at 95% CL.

Observed exclusion limit in the (BRe,BRtau) plane on the cross section for a 1600 GeV stop. All limits are computed at 95% CL.

The chosen signal region in the (BRe,BRtau) plane with the best expected exclusion on the cross section for a 1350 GeV stop. All limits are computed at 95% CL.

The chosen signal region in the (BRe,BRtau) plane with the best expected exclusion on the cross section for a 1350 GeV stop. All limits are computed at 95% CL.

The chosen signal region in the (BRe,BRtau) plane with the best expected exclusion on the cross section for a 1400 GeV stop. All limits are computed at 95% CL.

The chosen signal region in the (BRe,BRtau) plane with the best expected exclusion on the cross section for a 1400 GeV stop. All limits are computed at 95% CL.

The chosen signal region in the (BRe,BRtau) plane with the best expected exclusion on the cross section for a 1450 GeV stop. All limits are computed at 95% CL.

The chosen signal region in the (BRe,BRtau) plane with the best expected exclusion on the cross section for a 1450 GeV stop. All limits are computed at 95% CL.

The chosen signal region in the (BRe,BRtau) plane with the best expected exclusion on the cross section for a 1500 GeV stop. All limits are computed at 95% CL.

The chosen signal region in the (BRe,BRtau) plane with the best expected exclusion on the cross section for a 1500 GeV stop. All limits are computed at 95% CL.

The chosen signal region in the (BRe,BRtau) plane with the best expected exclusion on the cross section for a 1550 GeV stop. All limits are computed at 95% CL.

The chosen signal region in the (BRe,BRtau) plane with the best expected exclusion on the cross section for a 1550 GeV stop. All limits are computed at 95% CL.

The chosen signal region in the (BRe,BRtau) plane with the best expected exclusion on the cross section for a 1600 GeV stop. All limits are computed at 95% CL.

The chosen signal region in the (BRe,BRtau) plane with the best expected exclusion on the cross section for a 1600 GeV stop. All limits are computed at 95% CL.

The chosen signal region in the (BRe,BRtau) plane with the best expected exclusion on the cross section for a 600 GeV stop. All limits are computed at 95% CL.

The chosen signal region in the (BRe,BRtau) plane with the best expected exclusion on the cross section for a 600 GeV stop. All limits are computed at 95% CL.

The chosen signal region in the (BRe,BRtau) plane with the best expected exclusion on the cross section for a 700 GeV stop. All limits are computed at 95% CL.

The chosen signal region in the (BRe,BRtau) plane with the best expected exclusion on the cross section for a 700 GeV stop. All limits are computed at 95% CL.

The chosen signal region in the (BRe,BRtau) plane with the best expected exclusion on the cross section for a 800 GeV stop. All limits are computed at 95% CL.

The chosen signal region in the (BRe,BRtau) plane with the best expected exclusion on the cross section for a 800 GeV stop. All limits are computed at 95% CL.

The chosen signal region in the (BRe,BRtau) plane with the best expected exclusion on the cross section for a 900 GeV stop. All limits are computed at 95% CL.

The chosen signal region in the (BRe,BRtau) plane with the best expected exclusion on the cross section for a 900 GeV stop. All limits are computed at 95% CL.

The chosen signal region in the (BRe,BRtau) plane with the best expected exclusion on the cross section for a 1000 GeV stop. All limits are computed at 95% CL.

The chosen signal region in the (BRe,BRtau) plane with the best expected exclusion on the cross section for a 1000 GeV stop. All limits are computed at 95% CL.

The chosen signal region in the (BRe,BRtau) plane with the best expected exclusion on the cross section for a 1050 GeV stop. All limits are computed at 95% CL.

The chosen signal region in the (BRe,BRtau) plane with the best expected exclusion on the cross section for a 1050 GeV stop. All limits are computed at 95% CL.

The chosen signal region in the (BRe,BRtau) plane with the best expected exclusion on the cross section for a 1100 GeV stop. All limits are computed at 95% CL.

The chosen signal region in the (BRe,BRtau) plane with the best expected exclusion on the cross section for a 1100 GeV stop. All limits are computed at 95% CL.

The chosen signal region in the (BRe,BRtau) plane with the best expected exclusion on the cross section for a 1150 GeV stop. All limits are computed at 95% CL.

The chosen signal region in the (BRe,BRtau) plane with the best expected exclusion on the cross section for a 1150 GeV stop. All limits are computed at 95% CL.

The chosen signal region in the (BRe,BRtau) plane with the best expected exclusion on the cross section for a 1200 GeV stop. All limits are computed at 95% CL.

The chosen signal region in the (BRe,BRtau) plane with the best expected exclusion on the cross section for a 1200 GeV stop. All limits are computed at 95% CL.

The chosen signal region in the (BRe,BRtau) plane with the best expected exclusion on the cross section for a 1250 GeV stop. All limits are computed at 95% CL.

The chosen signal region in the (BRe,BRtau) plane with the best expected exclusion on the cross section for a 1250 GeV stop. All limits are computed at 95% CL.

The chosen signal region in the (BRe,BRtau) plane with the best expected exclusion on the cross section for a 1300 GeV stop. All limits are computed at 95% CL.

The chosen signal region in the (BRe,BRtau) plane with the best expected exclusion on the cross section for a 1300 GeV stop. All limits are computed at 95% CL.

Upper limits on the fiducial cross section times branching ratio to two photons at centre-of-mass energy of 13 TeV of a narrow-width (Γ_X = 4 MeV) spin-0 resonance as a function of its mass m_X.

Upper limits on the production cross section times branching ratio to two photons at centre-of-mass energy of 13 TeV of the lightest KK graviton as a function of its mass m_G* for k/MPl=0.01.

Upper limits on the production cross section times branching ratio to two photons at centre-of-mass energy of 13 TeV of the lightest KK graviton as a function of its mass m_G* for k/MPl=0.10. Only the limits derived with the asymptotic formulae are quoted here.

Upper limits on the production cross section times branching ratio to two photons at centre-of-mass energy of 13 TeV of the lightest KK graviton as a function of its mass m_G* for k/MPl=0.20.

Upper limits on the production cross section times branching ratio to two photons at centre-of-mass energy of 13 TeV of the lightest KK graviton as a function of its mass m_G* for k/MPl=0.30.

Distribution of the diphoton invariant mass for data events passing the spin-0 selection. The data points are plotted at the centre of each bin. The error bars indicate statistical uncertainties. The distribution consists of not only genuine diphoton events, but also events where at least one photon is faked by a jet. There is no data event above 2700 GeV.

Distribution of the diphoton invariant mass for data events passing the spin-2 selection. The data points are plotted at the centre of each bin. The error bars indicate statistical uncertainties. The distribution consists of not only genuine diphoton events, but also events where at least one photon is faked by a jet. There is no data event above 2700 GeV.

Fiducial acceptance and product of the fiducial acceptance times the combined reconstruction and identification efficiency as a function of the mass for a spin-0 resonant signal with narrow width under the spin-0 selection. Only MC statistical uncertainties are included.

Fiducial acceptance and product of the fiducial acceptance times the combined reconstruction and identification efficiency as a function of the mass for a spin-2 resonant signal with k/MPl=0.1 under the spin-2 selection. The definition of fiducial region is provided in JHEP 09 (2016) 001. Only MC statistical uncertainties are included.

Fiducial acceptance and product of the fiducial acceptance times the combined reconstruction and identification efficiency as a function of the mass for an ADD excess (GRW formalism), calculated as the difference between the sum of ADD and SM contributions (including their interference) and the SM contribution, under the spin-2 selection in the signal region M(gamma gamma)>2240 GeV. The definition of fiducial region is provided in JHEP 09 (2016) 001, and M(gamma gamma)>2240 GeV is required in addition. Only MC statistical uncertainties are included.

Measured differential fiducial cross sections in cos(theta*) (second column). The given uncertainty is split into statistical (first) and systematic components (second). Values without uncertainties are 95% CL limits in the absence of signal events. The third column gives the theoretical prediction of Higgs production in the fiducial volume using Powheg NNLOPS for the ggF process, Powheg for the VBF and the VH processes, and Madgraph5_aMC@NLO for the ttH and bbH processes. The uncertainty includes PDF, scale, and branching fraction uncertainty. All predictions were normalized to the best available inclusive Higgs production cross sections at the time of the publication.

Measured differential fiducial cross sections in number of jets (second column). The given uncertainty is split into statistical (first) and systematic components (second). Values without uncertainties are 95% CL limits in the absence of signal events. The third column gives the theoretical prediction of Higgs production in the fiducial volume using Powheg NNLOPS for the ggF process, Powheg for the VBF and the VH processes, and Madgraph5_aMC@NLO for the ttH and bbH processes. The uncertainty includes PDF, scale, and branching fraction uncertainty. All predictions were normalized to the best available inclusive Higgs production cross sections at the time of the publication.

Measured differential fiducial cross sections in transverse momentum of the leading jet (second column). The given uncertainty is split into statistical (first) and systematic components (second). Values without uncertainties are 95% CL limits in the absence of signal events. The third column gives the theoretical prediction of Higgs production in the fiducial volume using Powheg NNLOPS for the ggF process, Powheg for the VBF and the VH processes, and Madgraph5_aMC@NLO for the ttH and bbH processes. The uncertainty includes PDF, scale, and branching fraction uncertainty. All predictions were normalized to the best available inclusive Higgs production cross sections at the time of the publication.

Measured differential fiducial cross sections in dijet invariant mass (second column). The given uncertainty is split into statistical (first) and systematic components (second). Values without uncertainties are 95% CL limits in the absence of signal events. The third column gives the theoretical prediction of Higgs production in the fiducial volume using Powheg NNLOPS for the ggF process, Powheg for the VBF and the VH processes, and Madgraph5_aMC@NLO for the ttH and bbH processes. The uncertainty includes PDF, scale, and branching fraction uncertainty. All predictions were normalized to the best available inclusive Higgs production cross sections at the time of the publication.

Measured differential fiducial cross sections in dijet angle phi (second column). The given uncertainty is split into statistical (first) and systematic components (second). Values without uncertainties are 95% CL limits in the absence of signal events. The third column gives the theoretical prediction of Higgs production in the fiducial volume using Powheg NNLOPS for the ggF process, Powheg for the VBF and the VH processes, and Madgraph5_aMC@NLO for the ttH and bbH processes. The uncertainty includes PDF, scale, and branching fraction uncertainty. All predictions were normalized to the best available inclusive Higgs production cross sections at the time of the publication.

Measured differential fiducial cross sections in m12 vs m34 (second column). The given uncertainty is split into statistical (first) and systematic components (second). Values without uncertainties are 95% CL limits in the absence of signal events. The third column gives the theoretical prediction of Higgs production in the fiducial volume using Powheg NNLOPS for the ggF process, Powheg for the VBF and the VH processes, and Madgraph5_aMC@NLO for the ttH and bbH processes. The uncertainty includes PDF, scale, and branching fraction uncertainty. All predictions were normalized to the best available inclusive Higgs production cross sections at the time of the publication.

Measured differential fiducial cross sections in Higgs transverse momentum for 0 jet events (second column). The given uncertainty is split into statistical (first) and systematic components (second). Values without uncertainties are 95% CL limits in the absence of signal events. The third column gives the theoretical prediction of Higgs production in the fiducial volume using Powheg NNLOPS for the ggF process, Powheg for the VBF and the VH processes, and Madgraph5_aMC@NLO for the ttH and bbH processes. The uncertainty includes PDF, scale, and branching fraction uncertainty. All predictions were normalized to the best available inclusive Higgs production cross sections at the time of the publication.

Measured differential fiducial cross sections in Higgs transverse momentum for 1-jet events (second column). The given uncertainty is split into statistical (first) and systematic components (second). Values without uncertainties are 95% CL limits in the absence of signal events. The third column gives the theoretical prediction of Higgs production in the fiducial volume using Powheg NNLOPS for the ggF process, Powheg for the VBF and the VH processes, and Madgraph5_aMC@NLO for the ttH and bbH processes. The uncertainty includes PDF, scale, and branching fraction uncertainty. All predictions were normalized to the best available inclusive Higgs production cross sections at the time of the publication.

Measured differential fiducial cross sections in Higgs transverse momentum for events with 2 or more jets (second column). The given uncertainty is split into statistical (first) and systematic components (second). Values without uncertainties are 95% CL limits in the absence of signal events. The third column gives the theoretical prediction of Higgs production in the fiducial volume using Powheg NNLOPS for the ggF process, Powheg for the VBF and the VH processes, and Madgraph5_aMC@NLO for the ttH and bbH processes. The uncertainty includes PDF, scale, and branching fraction uncertainty. All predictions were normalized to the best available inclusive Higgs production cross sections at the time of the publication.

Measured differential fiducial cross sections in dijet angle eta (second column). The given uncertainty is split into statistical (first) and systematic components (second). Values without uncertainties are 95% CL limits in the absence of signal events. The third column gives the theoretical prediction of Higgs production in the fiducial volume using Powheg NNLOPS for the ggF process, Powheg for the VBF and the VH processes, and Madgraph5_aMC@NLO for the ttH and bbH processes. The uncertainty includes PDF, scale, and branching fraction uncertainty. All predictions were normalized to the best available inclusive Higgs production cross sections at the time of the publication.

Measured differential fiducial cross sections in invariant mass of the leading lepton pair (second column). The given uncertainty is split into statistical (first) and systematic components (second). Values without uncertainties are 95% CL limits in the absence of signal events. The third column gives the theoretical prediction of Higgs production in the fiducial volume using Powheg NNLOPS for the ggF process, Powheg for the VBF and the VH processes, and Madgraph5_aMC@NLO for the ttH and bbH processes. The uncertainty includes PDF, scale, and branching fraction uncertainty. All predictions were normalized to the best available inclusive Higgs production cross sections at the time of the publication.

Measured differential fiducial cross sections in number of bjets (second column). The given uncertainty is split into statistical (first) and systematic components (second). Values without uncertainties are 95% CL limits in the absence of signal events. The third column gives the theoretical prediction of Higgs production in the fiducial volume using Powheg NNLOPS for the ggF process, Powheg for the VBF and the VH processes, and Madgraph5_aMC@NLO for the ttH and bbH processes. The uncertainty includes PDF, scale, and branching fraction uncertainty. All predictions were normalized to the best available inclusive Higgs production cross sections at the time of the publication.

Measured fiducial cross sections (second column). The given uncertainty is split into statistical (first) and systematic components (second). The third column gives the theoretical prediction of Higgs production in the fiducial volume using the best available inclusive Higgs production cross sections at the time of the publication. The acceptance to estimate the cross section in the fiducial volume is calculated using Powheg NNLOPS for the ggF process, Powheg for the VBF and the VH processes, and Madgraph5_aMC@NLO for the ttH and bbH processes. The uncertainty includes PDF, scale, and branching fraction uncertainty.

Signal acceptance times efficiency as a function of mass for Z' → WW in the HVT model

Upper limits at the 95% CL on the cross section times branching ratio for (c) WW+ZZ production as a function of scalar mass.

Signal acceptance times efficiency as a function of mass for GKK → WW in the bulk RS model

Dijet mass distributions for data in the (a) WW signal region.

Dijet mass distributions for data in the (a) WW signal region.

Dijet mass distributions for data in the (b) WZ signal region.

Dijet mass distributions for data in the (b) WZ signal region.

Dijet mass distributions for data in the (c) ZZ signal region.

Dijet mass distributions for data in the (c) ZZ signal region.

Dijet mass distributions for data in the (d) WZ+WW signal region.

Dijet mass distributions for data in the (d) WZ+WW signal region.

Dijet mass distributions for data in the (e) WW+ZZ signal region.

Dijet mass distributions for data in the (e) WW+ZZ signal region.

Signal acceptance times efficiency as a function of mass for Scalar → WW in the heavy scalar model

Upper limits at the 95% CL on the cross section times branching ratio for WW+WZ production as a function of V' mass

Signal acceptance times efficiency as a function of mass for Z' → WW in the HVT model

Upper limits at the 95% CL on the cross section times branching ratio for WW+ZZ production as a function of GKK mass for the bulk RS model with k/M̄Pl=1.

Signal acceptance times efficiency as a function of mass for GKK → WW in the bulk RS model

Upper limits at the 95% CL on the cross section times branching ratio for (c) WW+ZZ production as a function of scalar mass.

Upper limits at the 95% CL on the cross section times branching ratio for WW+ZZ production as a function of GKK mass for the bulk RS model with k/M̄Pl=0.5.

Upper limits at the 95% CL on the cross section times branching ratio for WW production as a function of V' mass

Upper limits at the 95% CL on the cross section times branching ratio for WW production as a function of V' mass

Upper limits at the 95% CL on the cross section times branching ratio for WZ production as a function of V' mass

Upper limits at the 95% CL on the cross section times branching ratio for WZ production as a function of V' mass

Upper limits at the 95% CL on the cross section times branching ratio for WW production as a function of GKK mass for the bulk RS model with k/M̄Pl=0.5.

Upper limits at the 95% CL on the cross section times branching ratio for WW production as a function of GKK mass for the bulk RS model with k/M̄Pl=0.5.

Upper limits at the 95% CL on the cross section times branching ratio for ZZ production as a function of GKK mass for the bulk RS model with k/M̄Pl=0.5.

Upper limits at the 95% CL on the cross section times branching ratio for ZZ production as a function of GKK mass for the bulk RS model with k/M̄Pl=0.5.

Upper limits at the 95% CL on the cross section times branching ratio for WW production as a function of GKK mass for the bulk RS model with k/M̄Pl=1.

Upper limits at the 95% CL on the cross section times branching ratio for WW production as a function of GKK mass for the bulk RS model with k/M̄Pl=1.

Upper limits at the 95% CL on the cross section times branching ratio for ZZ production as a function of GKK mass for the bulk RS model with k/M̄Pl=1.

Upper limits at the 95% CL on the cross section times branching ratio for ZZ production as a function of GKK mass for the bulk RS model with k/M̄Pl=1.

Upper limits at the 95% CL on the cross section times branching ratio for WW+ZZ production as a function of GKK mass for the bulk RS model with k/M̄Pl=0.5.

Upper limits at the 95% CL on the cross section times branching ratio for WW production as a function of scalar mass.

Upper limits at the 95% CL on the cross section times branching ratio for WW production as a function of scalar mass.

Upper limits at the 95% CL on the cross section times branching ratio for ZZ production as a function of scalar mass.

Upper limits at the 95% CL on the cross section times branching ratio for ZZ production as a function of scalar mass.

Measured cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $1.81<|\eta^{\gamma}|<2.37$.

Predicted cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $|\eta^{\gamma}|<0.6$.

Predicted cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $0.6<|\eta^{\gamma}|<1.37$.

Predicted cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $1.56<|\eta^{\gamma}|<1.81$.

Predicted cross sections for inclusive isolated-photon production as a function of $E_{\rm T}^{\gamma}$ for $1.81<|\eta^{\gamma}|<2.37$.

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.

Trigger efficiency for simulated signal events as a function of the LLP decay position in the x&ndash;y plane (L_xy) for LLPs decaying in the barrel (|&eta;|&lt;1.4) for one of the low-E_T signal samples for HLT CalRatio triggers seeded by the high-E_T L1 triggers with E_T thresholds of 60 GeV and 100 GeV and by the two versions of the low-E_T L1 triggers. Only statistical uncertainties are shown.

Trigger efficiency for simulated signal events as a function of the LLP decay position in the x&ndash;y plane (L_xy) for LLPs decaying in the barrel (|&eta;|&lt;1.4) for one of the high-E_T signal samples for HLT CalRatio triggers seeded by the high-E_T L1 triggers with E_T thresholds of 60 GeV and 100 GeV and by the two versions of the low-E_T L1 triggers. Only statistical uncertainties are shown.

The NN output scores in the dijet control region for the low-E_T training with no adversary network. Statistical uncertainties are shown in all plots. In cases where training with adversary networks is considered, the systematic uncertainty related to modelling discrepancies is included as well.

The NN output scores in the dijet control region for the low-E_T training with an adversary network included. Statistical uncertainties are shown in all plots. In cases where training with adversary networks is considered, the systematic uncertainty related to modelling discrepancies is included as well.

The NN output scores in the dijet control region for the high-E_T training with no adversary network. Statistical uncertainties are shown in all plots. In cases where training with adversary networks is considered, the systematic uncertainty related to modelling discrepancies is included as well.

The NN output scores in the dijet control region for the high-E_T training with an adversary network included. Statistical uncertainties are shown in all plots. In cases where training with adversary networks is considered, the systematic uncertainty related to modelling discrepancies is included as well.

Distribution of the low-E_T per-event BDT in main data, BIB data and some of the benchmark signal samples after preselection. Only statistical uncertainties are shown.

Distribution of the high-E_T per-event BDT outputs in main data, BIB data and some of the benchmark signal samples after preselection. Only statistical uncertainties are shown.

Sequential impact of each requirement on the number of events passing the selection for the high-E_T selections. The signal columns represent the cumulative fraction of events passing the selection than the number of events.

Sequential impact of each requirement on the number of events passing the selection for the low-E_T selections. The signal columns represent the cumulative fraction of events passing the selection than the number of events.

Application of the modified ABCD method to the final high-E_T selections. The a priori estimate refers to the "pre-unblinding" case, where the data in region A are ignored by removing the Poisson constraint in that region and the signal strength is fixed to zero. This matches the simple N^bkg_A=(N^bkg_B&middot; N^bkg_C)/N^bkg_D relation. The a posteriori estimate refers to the "post-unblinding" case, including the observed data in region A in the background-only global fit, obtained by fixing the signal strength to 0 (background-only fit) or allowing it to float (signal-plus-background fit). The table also shows one set of representative signal yields in each selection for the signal-plus-background fit. Only statistical uncertainties are included in the quoted error of the background, while the uncertainties in the signal include those from both statistical and experimental sources.

Application of the modified ABCD method to the final low-E_T selections. The a priori estimate refers to the "pre-unblinding" case, where the data in region A are ignored by removing the Poisson constraint in that region and the signal strength is fixed to zero. This matches the simple N^bkg_A=(N^bkg_B&middot; N^bkg_C)/N^bkg_D relation. The a posteriori estimate refers to the "post-unblinding" case, including the observed data in region A in the background-only global fit, obtained by fixing the signal strength to 0 (background-only fit) or allowing it to float (signal-plus-background fit). The table also shows one set of representative signal yields in each selection for the signal-plus-background fit. Only statistical uncertainties are included in the quoted error of the background, while the uncertainties in the signal include those from both statistical and experimental sources.

95% CL expected and observed limits on the BR of SM Higgs bosons to pairs of neutral LLPs (B_{H&rarr; ss}), showing the &plusmn; 1 &sigma; (green) and &plusmn; 2 &sigma; (yellow) expected limit bands, as well as a comparison with the results from previous ATLAS searches [36,78]. The cross-section for SM Higgs boson gluon--gluon fusion production is assumed to be 48.6 pb.

Trigger efficiency of simulated signal events as a function of the LLP decay position in the z direction for LLPs decaying in the calorimeter endcaps (1.4 &le; |&eta;| &lt; 2.5) for one of the low-E_T signal samples for HLT CalRatio triggers seeded by the 60 GeV-high-E_T trigger and by the two versions of the low-E_T triggers.

Trigger efficiency of simulated signal events as a function of the LLP decay position in the z direction for LLPs decaying in the calorimeter endcaps (1.4 &le; |&eta;| &lt; 2.5) for one of the high-E_T signal samples for HLT CalRatio triggers seeded by the 60 GeV-high-E_T trigger and by the two versions of the low-E_T triggers.

The simulated efficiencies as a function of c times the mean proper lifetime (c&tau;) of s for several different MC samples. A weight-based extrapolation procedure is used to determine the efficiency at a given mean proper lifetime.

The simulated efficiencies as a function of c times the mean proper lifetime (c&tau;) of s for several different MC samples. A weight-based extrapolation procedure is used to determine the efficiency at a given mean proper lifetime.

The simulated efficiencies as a function of c times the mean proper lifetime (c&tau;) of s for several different MC samples. A weight-based extrapolation procedure is used to determine the efficiency at a given mean proper lifetime.

The simulated efficiencies as a function of c times the mean proper lifetime (c&tau;) of s for several different MC samples. A weight-based extrapolation procedure is used to determine the efficiency at a given mean proper lifetime.

The simulated efficiencies as a function of c times the mean proper lifetime (c&tau;) of s for several different MC samples. A weight-based extrapolation procedure is used to determine the efficiency at a given mean proper lifetime.

The simulated efficiencies as a function of c times the mean proper lifetime (c&tau;) of s for several different MC samples. A weight-based extrapolation procedure is used to determine the efficiency at a given mean proper lifetime.

The simulated efficiencies as a function of c times the mean proper lifetime (c&tau;) of s for several different MC samples. A weight-based extrapolation procedure is used to determine the efficiency at a given mean proper lifetime.

The simulated efficiencies as a function of c times the mean proper lifetime (c&tau;) of s for several different MC samples. A weight-based extrapolation procedure is used to determine the efficiency at a given mean proper lifetime.

The simulated efficiencies as a function of c times the mean proper lifetime (c&tau;) of s for several different MC samples. A weight-based extrapolation procedure is used to determine the efficiency at a given mean proper lifetime.

The simulated efficiencies as a function of c times the mean proper lifetime (c&tau;) of s for several different MC samples. A weight-based extrapolation procedure is used to determine the efficiency at a given mean proper lifetime.

The simulated efficiencies as a function of c times the mean proper lifetime (c&tau;) of s for several different MC samples. A weight-based extrapolation procedure is used to determine the efficiency at a given mean proper lifetime.

The simulated efficiencies as a function of c times the mean proper lifetime (c&tau;) of s for several different MC samples. A weight-based extrapolation procedure is used to determine the efficiency at a given mean proper lifetime.

The simulated efficiencies as a function of c times the mean proper lifetime (c&tau;) of s for several different MC samples. A weight-based extrapolation procedure is used to determine the efficiency at a given mean proper lifetime.

The simulated efficiencies as a function of c times the mean proper lifetime (c&tau;) of s for several different MC samples. A weight-based extrapolation procedure is used to determine the efficiency at a given mean proper lifetime.

The event BDT in the dijet control region for the low-E_T training training. The uncertainties are combined statistical and ML modelling systematic uncertainty.

The event BDT in the dijet control region for the high-E_T training. The uncertainties are combined statistical and ML modelling systematic uncertainty.

The 95% CL observed limits, expected limits and &plusmn; 1 &sigma; and 2 &sigma; bands for the &Phi; mass of 60 GeV compared to the results from the 2016-data analysis and subsequent combinations, where available.

The 95% CL observed limits, expected limits and &plusmn; 1 &sigma; and 2 &sigma; bands for the &Phi; mass of 60 GeV compared to the results from the 2016-data analysis and subsequent combinations, where available.

The 95% CL observed limits, expected limits and &plusmn; 1 &sigma; and 2 &sigma; bands for the &Phi; mass 125 GeV, compared to the results from the 2016-data analysis and subsequent combinations, where available.

The 95% CL observed limits, expected limits and &plusmn; 1 &sigma; and 2 &sigma; bands for the &Phi; mass 125 GeV, compared to the results from the 2016-data analysis and subsequent combinations, where available. The 125 GeV mediator is assumed to be the SM Higgs boson.

The 95% CL observed limits, expected limits and &plusmn; 1 &sigma; and 2 &sigma; bands for the &Phi; mass 125 GeV, compared to the results from the 2016-data analysis and subsequent combinations, where available. The 125 GeV mediator is assumed to be the SM Higgs boson.

The 95% CL observed limits, expected limits and &plusmn; 1 &sigma; and 2 &sigma; bands for the &Phi; mass of 200 GeV, compared to the results from the 2016-data analysis and subsequent combinations, where available.

The 95% CL observed limits, expected limits and &plusmn; 1 &sigma; and 2 &sigma; bands for the &Phi; mass of 400 GeV, compared to the results from the 2016-data analysis and subsequent combinations, where available.

The 95% CL observed limits, expected limits and &plusmn; 1 &sigma; and 2 &sigma; bands for the &Phi; mass 600 GeV, compared to the results from the 2016-data analysis and subsequent combinations, where available.

The 95% CL observed limits, expected limits and &plusmn; 1 &sigma; and 2 &sigma; bands for the &Phi; mass of 600 GeV, compared to the results from the 2016-data analysis and subsequent combinations, where available.

The 95% CL observed limits, expected limits and &plusmn; 1 &sigma; and 2 &sigma; bands for the &Phi; masses of of 1000 GeV, compared to the results from the 2016-data analysis and subsequent combinations, where available.

The 95% CL observed limits, expected limits and &plusmn; 1 &sigma; and 2 &sigma; bands for the &Phi; masses of of 1000 GeV, compared to the results from the 2016-data analysis and subsequent combinations, where available.

The 95% CL observed limits, expected limits and &plusmn; 1 &sigma; and 2 &sigma; bands for the &Phi; masses of of 1000 GeV, compared to the results from the 2016-data analysis and subsequent combinations, where available.

The 95% CL observed limits, expected limits and &plusmn; 1 &sigma; and 2 &sigma; bands for the &Phi; masses of of 1000 GeV, compared to the results from the 2016-data analysis and subsequent combinations, where available.

Efficiency for an event to enter Region A of the high-E_T selection, as a function of the two LLP kinematics, decay type and decay position. LLP p_T is binned in the ranges of [0, 50 , 100, 200 , 400, 1600] GeV (5 bins), the LLP decay position is binned in decay position in L_xy in [0, 1.5, 2, 2.5, 3, 3.5, 3.9, &infin;] m for LLPs with |&eta;| &lt; 1.5 and L_z in [0, 3.6, 4.2, 4.8, 5.5, 6, &infin; ] m for LLPs with |&eta;|geq1.5, 13 bins in all. Finally, four decay types are considered: LLPs decaying to pairs of c, b, t, or &tau; in bins 0, 1, 2, 3 respectively. The efficiency is presented as a function of "Bin Index", which is calculated as follows: Bin Index = (decay position bin index ) &times; (number of p_T bins &times; number of decay type bins) + p_T bin index * (number of decay type bin) + decay type bin index. The efficiency for a given pair-produced LLP sample can be obtained by summing the efficiency values for each event as extracted from this map, and dividing it by the total number of events in the sample. The efficiency map is symmetric between the LLPs, so the choice of LLP1 and LLP2 is arbitrary. For the high-E_T selections, for overall efficiencies above 0.5%, the results are typically accurate to around 25%, but below this the efficiency can be overestimated and therefore should not be used for re-interpration.

Efficiency for an event to enter Region A of the low-E_T selection, as a function of the two LLP kinematics, decay type and decay position. LLP p_T is binned in the ranges of [0, 50 , 100, 200 , 400, 1600] GeV (5 bins), the LLP decay position is binned in L_xy in [0, 1.5, 2, 2.5, 3, 3.5, 3.9, &infin;] m for LLPs with |&eta;| &lt; 1.5 and L_z in [0, 3.6, 4.2, 4.8, 5.5, 6, &infin; ] m for LLPs with |&eta;|geq1.5, 13 bins in all. Finally, four decay types are considered: LLPs decaying to pairs of c, b, t, or &tau; in bins 0, 1, 2, 3 respectively. The efficiency is presented as a function of "Bin Index", which is calculated as follows: Bin Index = (decay position bin index ) &times; (number of p_T bins &times; number of decay type bins) + p_T bin index * (number of decay type bin) + decay type bin index. The efficiency for a given pair-produced LLP sample can be obtained by summing the efficiency values for each event as extracted from this map, and dividing it by the total number of events in the sample. The efficiency map is symmetric between the LLPs, so the choice of LLP1 and LLP2 is arbitrary. For the low-E_T selections, for overall efficiencies above 0.15%, the results are typically accurate to around 33%, and below this the efficiency is typically accurate up to a factor of 3.

Covariance matrix of the Absolute differential cross-section as function of $p_T^{t,h}$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $p_T^{t,h}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $p_T^{t,l}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $p_T^{t,l}$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $p_T^{t,l}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $m^{t\bar{t}}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $m^{t\bar{t}}$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $m^{t\bar{t}}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $y^{t,h}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $y^{t,h}$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $y^{t,h}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $y^{t,l}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $y^{t,l}$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $y^{t,l}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $y^{t\bar{t}}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $y^{t\bar{t}}$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $y^{t\bar{t}}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $H_T^{t\bar{t}}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $H_T^{t\bar{t}}$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $H_T^{t\bar{t}}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $\frac{\Delta\phi}{\pi}(b_{l},t_{h})$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(b_{l},t_{h})$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $\frac{\Delta\phi}{\pi}(b_{l},t_{h})$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $p_T^{t\bar{t}}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $p_T^{t\bar{t}}$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $p_T^{t\bar{t}}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $\frac{\Delta\phi}{\pi}(t_{h},t_{l})$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(t_{h},t_{l})$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $\frac{\Delta\phi}{\pi}(t_{h},t_{l})$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $H_T^{t\bar{t}+jets}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $H_T^{t\bar{t}+jets}$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $H_T^{t\bar{t}+jets}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $N^j$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $N^j$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $N^j$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $p_T^{j,1}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $p_T^{j,1}$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $p_T^{j,1}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $m(j_1, t_h)$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $m(j_1, t_h)$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $m(j_1, t_h)$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $\frac{\Delta\phi}{\pi}(j_1, t_h)$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $\frac{\Delta\phi}{\pi}(j_{2}, t_{h})$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{2}, t_{h})$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $\frac{\Delta\phi}{\pi}(j_{2}, t_{h})$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $\frac{\Delta\phi}{\pi}(j_{1}, j_{2})$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $\frac{\Delta\phi}{\pi}(j_{1}, j_{2})$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $\frac{\Delta\phi}{\pi}(j_{1}, j_{2})$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of $p_T^{j,2}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of $p_T^{j,2}$ at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative differential cross-section as a function of $p_T^{j,2}$ at particle level in the boosted topology. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Relative double-differential cross-section as a function of $p_T^{j,1}$ vs $N^j$ at particle level in the boosted topology in $N^j$ = 1. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Relative double-differential cross-section as a function of $p_T^{j,1}$ vs $N^j$ at particle level in the boosted topology in $N^j$ = 2. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Relative double-differential cross-section as a function of $p_T^{j,1}$ vs $N^j$ at particle level in the boosted topology in $N^j$ $\geq$ 3. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of $p_T^{j,1}$ vs $N^j$ at particle level in the boosted topology in $N^j$ = 1. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of $p_T^{j,1}$ vs $N^j$ at particle level in the boosted topology in $N^j$ = 2. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of $p_T^{j,1}$ vs $N^j$ at particle level in the boosted topology in $N^j$ $\geq$ 3. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix between the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $N^j$ in $N^j$ = 1 and the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $N^j$ in $N^j$ = 1 at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $N^j$ in $N^j$ = 2 and the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $N^j$ in $N^j$ = 1 at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $N^j$ in $N^j$ = 2 and the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $N^j$ in $N^j$ = 2 at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $N^j$ in $N^j$ $\geq$ 3 and the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $N^j$ in $N^j$ = 1 at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $N^j$ in $N^j$ $\geq$ 3 and the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $N^j$ in $N^j$ = 2 at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $N^j$ in $N^j$ $\geq$ 3 and the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $N^j$ in $N^j$ $\geq$ 3 at particle level in the boosted topology, accounting for the statistical uncertainties.

Relative double-differential cross-section as a function of $p_T^{j,1}$ vs $p_T^{t,h}$ at particle level in the boosted topology in 355.0 GeV < $p_T^{t,h}$ < 398.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Relative double-differential cross-section as a function of $p_T^{j,1}$ vs $p_T^{t,h}$ at particle level in the boosted topology in 398.0 GeV < $p_T^{t,h}$ < 496.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Relative double-differential cross-section as a function of $p_T^{j,1}$ vs $p_T^{t,h}$ at particle level in the boosted topology in 496.0 GeV < $p_T^{t,h}$ < 2000.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of $p_T^{j,1}$ vs $p_T^{t,h}$ at particle level in the boosted topology in 355.0 GeV < $p_T^{t,h}$ < 398.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of $p_T^{j,1}$ vs $p_T^{t,h}$ at particle level in the boosted topology in 398.0 GeV < $p_T^{t,h}$ < 496.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of $p_T^{j,1}$ vs $p_T^{t,h}$ at particle level in the boosted topology in 496.0 GeV < $p_T^{t,h}$ < 2000.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix between the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $p_T^{t,h}$ in 355.0 GeV < $p_T^{t,h}$ < 398.0 GeV and the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $p_T^{t,h}$ in 355.0 GeV < $p_T^{t,h}$ < 398.0 GeV at particle level in the boosted topology, accounting for the statistical uncertainties.

Covariance matrix between the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $p_T^{t,h}$ in 398.0 GeV < $p_T^{t,h}$ < 496.0 GeV and the Absolute double-differential cross-section as function of $p_T^{j,1}$ vs $p_T^{t,h}$ in 355.0 GeV < $p_T^{t,h}$ < 398.0 GeV at particle level in the boosted topology, accounting for the statistical uncertainties.