Two-body selection distribution of $R_{2\ell 2j}$ in $CR^{2-body}_{VV-SF}$ after the background fits. The contributions from all SM backgrounds are shown as a histogram stack; the bands represent the total statistical and detector-related systematic uncertainty. The rightmost bin of each plot includes overflow events.

Two-body selection distribution of $E_{T,corr}^{miss}$ in $CR_{ttZ}$ after the background fits. The contributions from all SM backgrounds are shown as a histogram stack; the bands represent the total statistical and detector-related systematic uncertainty. The rightmost bin of each plot includes overflow events.

Two-body selection distribution of $E_{T,corr}^{miss}$ in $CR_{VZ}$ after the background fits. The contributions from all SM backgrounds are shown as a histogram stack; the bands represent the total statistical and detector-related systematic uncertainty. The rightmost bin of each plot includes overflow events.

Three-body selection background fit results for the CRs of the SR$^{3-body}_{W}$ and SR$^{3-body}_{t}$ background fit. The nominal expectations from MC simulation are given for comparison for those backgrounds (ttbar, $VV$-DF and $VV$-SF) that are normalised to data in dedicated CRs.Combined statistical and systematic uncertainties are given. Entries marked ``--'' indicate a negligible background contribution. Uncertainties on the predicted background event yields are quoted as symmetric except where the negative uncertainty extends to zero predicted events, in which case the negative uncertainty is truncated.

Three-body selection distributions of $R_{p_{T}}$ in $CR^{3-body}_{t\bar{t}}$ after the background fit. The contributions from all SM backgrounds are shown as a histogram stack; the hatched bands represent the total statistical and detector-related systematic uncertainty. The rightmost bin of each plot includes overflow events.

Three-body selection distributions of $cos\theta_{b}$ in $CR^{3-body}_{VV-DF}$ after the background fit. The contributions from all SM backgrounds are shown as a histogram stack; the hatched bands represent the total statistical and detector-related systematic uncertainty. The rightmost bin of each plot includes overflow events.

Three-body selection distributions of $M_{\Delta}^{R}$ in $CR^{3-body}_{VV-SF}$ after the background fit. The contributions from all SM backgrounds are shown as a histogram stack; the hatched bands represent the total statistical and detector-related systematic uncertainty. The rightmost bin of each plot includes overflow events.

Four-body selection background fit results for the CRs of the SR$^{4-body}$ background fit. The nominal expectations from MC simulation are given for comparison for those backgrounds ($t\bar t$, $VV$ and $Z_{\tau\tau}$) that are normalised to data in dedicated CRs. Combined statistical and systematic uncertainties are given. Uncertainties on the predicted background event yields are quoted as symmetric except where the negative uncertainty extends to zero predicted events, in which case the negative uncertainty is truncated.

Four-body selection distributions of the $p_{T}(j_1)$ in CR$^{4-body}_{t\bar{t}}$ after the background fit. The contributions from all SM backgrounds are shown as a histogram stack; the bands represent the total statistical and detector-related systematic uncertainty. The rightmost bin of each plot includes overflow events.

Four-body selection distributions of the $R_{2\ell}$ in CR$^{4-body}_{VV}$ after the background fit. The contributions from all SM backgrounds are shown as a histogram stack; the bands represent the total statistical and detector-related systematic uncertainty. The rightmost bin of each plot includes overflow events.

Four-body selection distributions of the $E^{miss}_{T}$ in CR$^{4-body}_{Z\tau\tau}$ after the background fit. The contributions from all SM backgrounds are shown as a histogram stack; the bands represent the total statistical and detector-related systematic uncertainty. The rightmost bin of each plot includes overflow events.

Two-body selection background fit results for SRA$^{2-body}_{180}$ and SRB$^{2-body}_{140}$. The nominal expectations from MC simulation are given for comparison for those backgrounds ($t\bar t$, $t\bar t Z$) that are normalised to data in dedicated CRs. The Others category contains the contributions from $t\bar t W$, $t\bar t h$, $t\bar t WW$, $t\bar t t$, $t\bar t t\bar t$, $Wh$, $ggh$ and $Zh$ production. Combined statistical and systematic uncertainties are given. Entries marked $--$ indicate a negligible background contribution. Uncertainties on the predicted background event yields are quoted as symmetric except where the negative uncertainty extends to zero predicted events, in which case the negative uncertainty is truncated.

Two-body selection background fit results for SRC$^{2-body}_{110}$. The nominal expectations from MC simulation are given for comparison for those backgrounds ($t\bar t$, $t\bar t Z$) that are normalised to data in dedicated CRs. The Others category contains the contributions from $t\bar t W$, $t\bar t h$, $t\bar t WW$, $t\bar t t$, $t\bar t t\bar t$, $Wh$, $ggh$ and $Zh$ production. Combined statistical and systematic uncertainties are given. Entries marked $--$ indicate a negligible background contribution. Uncertainties on the predicted background event yields are quoted as symmetric except where the negative uncertainty extends to zero predicted events, in which case the negative uncertainty is truncated.

Two-body selection distributions of $m_{T2}^{ll}$ for events satisfying the selection criteria of the six SRs, except for the one on $m_{T2}^{ll}$, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack; the bands represent the total statistical and systematic uncertainty. The rightmost bin of each plot includes overflow events. Reference top squark pair production signal models are overlayed for comparison. Red arrows indicate the signal region selection criteria.

Two-body selection distributions of $m_{T2}^{ll}$ for events satisfying the selection criteria of the six SRs, except for the one on $m_{T2}^{ll}$, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack; the bands represent the total statistical and systematic uncertainty. The rightmost bin of each plot includes overflow events. Reference top squark pair production signal models are overlayed for comparison. Red arrows indicate the signal region selection criteria.

Two-body selection distributions of $m_{T2}^{ll}$ for events satisfying the selection criteria of the six SRs, except for the one on $m_{T2}^{ll}$, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack; the bands represent the total statistical and systematic uncertainty. The rightmost bin of each plot includes overflow events. Reference top squark pair production signal models are overlayed for comparison. Red arrows indicate the signal region selection criteria.

Two-body selection distributions of $m_{T2}^{ll}$ for events satisfying the selection criteria of the six SRs, except for the one on $m_{T2}^{ll}$, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack; the bands represent the total statistical and systematic uncertainty. The rightmost bin of each plot includes overflow events. Reference top squark pair production signal models are overlayed for comparison. Red arrows indicate the signal region selection criteria.

Two-body selection distributions of $m_{T2}^{ll}$ for events satisfying the selection criteria of the six SRs, except for the one on $m_{T2}^{ll}$, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack; the bands represent the total statistical and systematic uncertainty. The rightmost bin of each plot includes overflow events. Reference top squark pair production signal models are overlayed for comparison. Red arrows indicate the signal region selection criteria.

Two-body selection distributions of $m_{T2}^{ll}$ for events satisfying the selection criteria of the six SRs, except for the one on $m_{T2}^{ll}$, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack; the bands represent the total statistical and systematic uncertainty. The rightmost bin of each plot includes overflow events. Reference top squark pair production signal models are overlayed for comparison. Red arrows indicate the signal region selection criteria.

Two-body selection background fit results for SR(A,B)$^{2-body}_{x,y}$ regions, where x and y denote the low and high edges of the bin. Combined statistical and systematic uncertainties are given. Uncertainties on the predicted background event yields are quoted as symmetric.

Three-body selection background fit results for SR$^{3-body}_{W}$ and SR$^{3-body}_{t}$. Combined statistical and systematic uncertainties are given. Uncertainties on the predicted background event yields are quoted as symmetric.

Three-body selection distributions of $R_{p_{T}}$ in same-flavour events that satisfy all the SR$^{3-body}_{W}$ selection criteria except for the one on $R_{p_{T}}$, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack; the hatched bands represent the total statistical and systematic uncertainty. The rightmost bin of each plot includes overflow events. Reference top squark pair production signal models are overlayed for comparison. Red arrows indicate the signal region selection criteria.

Three-body selection distributions of $R_{p_{T}}$ in different-flavour events that satisfy all the SR$^{3-body}_{W}$ selection criteria except for the one on $R_{p_{T}}$, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack; the hatched bands represent the total statistical and systematic uncertainty. The rightmost bin of each plot includes overflow events. Reference top squark pair production signal models are overlayed for comparison. Red arrows indicate the signal region selection criteria.

Three-body selection distributions of $M_{\Delta}^{R}$ in same-flavour events that satisfy all the SR$^{3-body}_{t}$ selection criteria except for the one on $M_{\Delta}^{R}$, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack; the hatched bands represent the total statistical and systematic uncertainty. The rightmost bin of each plot includes overflow events. Reference top squark pair production signal models are overlayed for comparison. Red arrows indicate the signal region selection criteria.

Three-body selection distributions of $M_{\Delta}^{R}$ in different-flavour events that satisfy all the SR$^{3-body}_{t}$ selection criteria except for the one on $M_{\Delta}^{R}$ after the background fit. The contributions from all SM backgrounds are shown as a histogram stack; the hatched bands represent the total statistical and systematic uncertainty. The rightmost bin of each plot includes overflow events. Reference top squark pair production signal models are overlayed for comparison. Red arrows indicate the signal region selection criteria.

Four-body selection distributions of $R_{2\ell 4j}$ for events satisfying all the SR$^{4-body}$ selections but for the one on the variable shown in the figure, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack; the bands represent the total statistical and systematic uncertainty. The rightmost bin of each plot includes overflow events. Reference top squark pair production signal models are overlayed for comparison. Red arrows indicate the signal region selection criteria.

Four-body selection distributions of $R_{2\ell}$ for events satisfying all the SR$^{4-body}$ selections but for the one on the variable shown in the figure, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack; the bands represent the total statistical and systematic uncertainty. The rightmost bin of each plot includes overflow events. Reference top squark pair production signal models are overlayed for comparison. Red arrows indicate the signal region selection criteria.

Four-body selection background fit results for SR$^{4-body}$. The nominal expectations from MC simulation are given for comparison for those backgrounds ($t \bar t$, $VV$ and $Z_{\tau\tau}$) that are normalised to data in dedicated CRs. The Others category contains the contributions from $t\bar t W$, $t\bar t h$, $t\bar t WW$, $t\bar t $, $t\bar t t\bar t$ , $Wh$, $ggh$ and $Zh$ production. Combined statistical and systematic uncertainties are given. Uncertainties on the predicted background event yields are quoted as symmetric except where the negative uncertainty extends to zero predicted events, in which case the negative uncertainty is truncated.

Model-independent 95% CL upper limits on the visible cross-section ($\sigma_{vis}$) of new physics, the visible number of signal events ($S^{95}_{\rm obs}$), the visible number of signal events ($S^{95}_{\rm exp}$) given the expected number of background events (and $\pm1\sigma$ excursions on the expectation), and the discovery $p$-value ($p(s = 0)$), all calculated with pseudo-experiments, are shown for each SR.

Observed exclusion limits at 95% CL for a simplified model assuming $\tilde{t}_{1}$ pair production, decaying via $\tilde{t}_{1}\rightarrow t+\tilde{\chi}_{1}^{0}$ with 100% branching ratio.

Expected exclusion limits at 95% CL for a simplified model assuming $\tilde{t}_{1}$ pair production, decaying via $\tilde{t}_{1}\rightarrow t+\tilde{\chi}_{1}^{0}$ with 100% branching ratio.

Expected exclusion limits at 95% CL from the analysis of $36.1 \; \text{fb}^{-1}$ of 13 TeV $pp$ collision data as a function of the mass of the $\tilde{t}_1$ for a fixed $(\tilde{\chi}^0_1) = 0$ GeV, assuming $\text{BR}(\tilde{\chi}^0_2 \to Z\tilde{\chi}^0_1) = 0.5$ and $\text{BR}(\tilde{\chi}^0_2 \to h\tilde{\chi}^0_1) = 0.5$.

Observed exclusion limits at 95% CL from the analysis of $36.1 \; \text{fb}^{-1}$ of 13 TeV $pp$ collision data as a function of the mass of the $\tilde{t}_1$ for a fixed $(\tilde{\chi}^0_1) = 0$ GeV, assuming $\text{BR}(\tilde{\chi}^0_2 \to Z\tilde{\chi}^0_1) = 0.5$ and $\text{BR}(\tilde{\chi}^0_2 \to h\tilde{\chi}^0_1) = 0.5$.

Expected exclusion contour as a function of $m_{\tilde{t}_1}$ and $m_{\tilde{\chi}^0_1}$ in the pMSSM model described in the text. Pair production of $\tilde{t}_1$ and $\tilde{b}_1$ are considered. Limits are set for both the positive (red in the figure) and negative (blue in the figure) values of $\mu$. The dashed and dotted grey lines indicate constant values of the $\tilde{b}_1$ mass. The signal models included within the shown contours are excluded at 95% CL. The dashed lines and the shaded band are the expected limit and its $\pm1\sigma$ uncertainty. The thick solid line is the observed limit for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section.

Observed exclusion contour as a function of $m_{\tilde{t}_1}$ and $m_{\tilde{\chi}^0_1}$ in the pMSSM model described in the text. Pair production of $\tilde{t}_1$ and $\tilde{b}_1$ are considered. Limits are set for both the positive (red in the figure) and negative (blue in the figure) values of $\mu$. The dashed and dotted grey lines indicate constant values of the $\tilde{b}_1$ mass. The signal models included within the shown contours are excluded at 95% CL. The dashed lines and the shaded band are the expected limit and its $\pm1\sigma$ uncertainty. The thick solid line is the observed limit for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section.

Expected exclusion contour as a function of $m_{\tilde{t}_1}$ and $m_{\tilde{\chi}^0_1}$ in the pMSSM model described in the text. Pair production of $\tilde{t}_1$ and $\tilde{b}_1$ are considered. Limits are set for both the positive (red in the figure) and negative (blue in the figure) values of $\mu$. The dashed and dotted grey lines indicate constant values of the $\tilde{b}_1$ mass. The signal models included within the shown contours are excluded at 95% CL. The dashed lines and the shaded band are the expected limit and its $\pm1\sigma$ uncertainty. The thick solid line is the observed limit for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section.

Observed exclusion contour as a function of $m_{\tilde{t}_1}$ and $m_{\tilde{\chi}^0_1}$ in the pMSSM model described in the text. Pair production of $\tilde{t}_1$ and $\tilde{b}_1$ are considered. Limits are set for both the positive (red in the figure) and negative (blue in the figure) values of $\mu$. The dashed and dotted grey lines indicate constant values of the $\tilde{b}_1$ mass. The signal models included within the shown contours are excluded at 95% CL. The dashed lines and the shaded band are the expected limit and its $\pm1\sigma$ uncertainty. The thick solid line is the observed limit for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section.

Illustration of the best expected signal region per signal grid point for the simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t\tilde{\chi}^0_1$ with 100% branching ratio.

Two-body selection background fit results for the VR in the SRA$^{2-body}$ and SRB$^{2-body}_{140}$ background-only fit. The nominal expectations from MC simulation are given for comparison for those backgrounds ($t\bar t$, $t\bar t Z$) that are normalised to data in dedicated CRs. The Others category contains the contributions from $t\bar t W$, $t\bar t h$, $t\bar t WW$, $t\bar t t$, $t\bar t t\bar t$, $Wh$, $ggh$ and $Zh$ production. Combined statistical and systematic uncertainties are given. Uncertainties on the predicted background event yields are quoted as symmetric except where the negative uncertainty reaches down to zero predicted events, in which case the negative uncertainty is truncated.

Two-body selection background fit results for the VR in the SRC$^{2-body}_{110}$ background-only fit. The nominal expectations from MC simulation are given for comparison for those backgrounds ($t\bar t$, $t\bar t Z$) that are normalised to data in dedicated CRs. The Others category contains the contributions from $t\bar t W$, $t\bar t h$, $t\bar t WW$, $t\bar t t$, $t\bar t t\bar t$, $Wh$, $ggh$ and $Zh$ production. Combined statistical and systematic uncertainties are given. Uncertainties on the predicted background event yields are quoted as symmetric except where the negative uncertainty reaches down to zero predicted events, in which case the negative uncertainty is truncated.

Three-body selection background fit results for the VRs in the SR$^{3-body}_{W}$ and SR$^{3-body}_{t}$ background-only fits. The nominal expectations from MC simulation are given for comparison for those backgrounds ($t\bar t$, $VV$ and $Z_{\tau\tau}$) that are normalised to data in dedicated CRs. The Others category contains the contributions from $t\bar t W$, $t\bar t h$, $t\bar t WW$, $t\bar t $, $t\bar t t\bar t$ , $Wh$, $ggh$ and $Zh$ production. Combined statistical and systematic uncertainties are given. Uncertainties on the predicted background event yields are quoted as symmetric except where the negative uncertainty reaches down to zero predicted events, in which case the negative uncertainty is truncated.

Four-body selection background fit results for the VRs in the SR$^{4-body}$ background-only fit. The nominal expectations from MC simulation are given for comparison for those backgrounds ($t\bar t$, $VV$ and $Z_{\tau\tau}$) that are normalised to data in dedicated CRs. The Others category contains the contributions from $t\bar t W$, $t\bar t h$, $t\bar t WW$, $t\bar t $, $t\bar t t\bar t$ , $Wh$, $ggh$ and $Zh$ production. Combined statistical and systematic uncertainties are given. Uncertainties on the predicted background event yields are quoted as symmetric except where the negative uncertainty reaches down to zero predicted events, in which case the negative uncertainty is truncated.

Two-body selection distribution of $E_{T}^{miss}$ for events satisfying all the VR$^{2-body}_{VV-DF}$ selections, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack; the bands represent the total statistical and systematic uncertainty. The rightmost bin of each plot includes overflow events.

Two-body selection distribution of $m_{T2}^{ll}$ for events satisfying all the VR$^{2-body}_{t\bar{t}}$ selections, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack; the bands represent the total statistical and systematic uncertainty. The rightmost bin of each plot includes overflow events.

Two-body selection distribution of $m_{T2}^{ll}$ for events satisfying all the VR$^{2-body}_{t\bar{t},3j}$ selections, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack; the bands represent the total statistical and systematic uncertainty. The rightmost bin of each plot includes overflow events.

Three-body selection distributions of $M_{\Delta}^{R}$ in events that satisfy all the $VR^{3-body}_{t\bar{t}}$ selection criteria after the background fit. The contributions from all SM backgrounds are shown as a histogram stack; the hatched bands represent the total statistical and systematic uncertainty. The rightmost bin of each plot includes overflow events.

Three-body selection distributions of $R_{p_{T}}$ in events that satisfy all the $VR^{3-body}_{VV-SF}$ selection criteria after the background fit. The contributions from all SM backgrounds are shown as a histogram stack; the hatched bands represent the total statistical and systematic uncertainty. The rightmost bin of each plot includes overflow events.

Three-body selection distributions of $R_{p_{T}}$ in events that satisfy all the $VR^{3-body}_{VV-DF}$ selection criteria after the background fit. The contributions from all SM backgrounds are shown as a histogram stack; the hatched bands represent the total statistical and systematic uncertainty. The rightmost bin of each plot includes overflow events.

Four-body selection distributions of $R_{2\ell 4j}$ for events with at least 2 jets (with the two leading required not be identified as $b$-jets), a leading jet $p_{T} >150$ GeV and satisfying the SR$^{4-body}$ requirements on the leptons. The contributions from all SM backgrounds are shown as a histogram stack; the bands represent the total statistical and systematic uncertainty. The fake and non-prompt lepton backgrounds are estimated from data, the other backgrounds are estimated from MC simulation with a background fit as described in Section6. The rightmost bin of each plot includes overflow events. In order to enhance the contribution from fake or non-prompt leptons, the lepton pair is required to have the same charge.

Four-body selection distributions of $R_{2\ell}$ for events with at least 2 jets (with the two leading required not be identified as $b$-jets), a leading jet $p_{T} >150$ GeV and satisfying the SR$^{4-body}$ requirements on the leptons. The contributions from all SM backgrounds are shown as a histogram stack; the bands represent the total statistical and systematic uncertainty. The fake and non-prompt lepton backgrounds are estimated from data, the other backgrounds are estimated from MC simulation with a background fit as described in Section6. The rightmost bin of each plot includes overflow events. In order to enhance the contribution from fake or non-prompt leptons, the lepton pair is required to have the same charge.

Four-body selection distributions of $E^{miss}_{T}$ for events satisfying all the VR$^{4-body}_{t\bar{t}}$ selections, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack; the bands represent the total statistical and systematic uncertainty. The fake and non-prompt lepton backgrounds are estimated from data, the other backgrounds are estimated from MC simulation with a background fit as described in Section 6}. The rightmost bin of each plot includes overflow events.

Number of signal events selected at different stages for some scenarios in the $\tilde{t}_1 \rightarrow t\tilde{\chi}^0_1$ model.

Number of signal events selected at different stages for some scenarios in the $\tilde{t}_1 \rightarrow b\tilde{\chi}^{\pm}_1$ model.

Number of signal events selected at different stages for some scenarios in the $\tilde{t}_1 \rightarrow b W \tilde{\chi}^{0}_1$ model.

Number of signal events selected at different stages for some scenarios in the $\tilde{t}_1 \rightarrow b f f \prime \tilde{\chi}^0_1$ model.

Upper limits on cross-sections (in fb) at 95% CL for each signal model, assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t^{}(*)\tilde{\chi}^{0}_1$ with 100% branching ratio.

Upper limits on cross-sections (in fb) at 95% CL for each signal model, assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b\tilde{\chi}^{\pm}_1$ with 100% branching ratio. The lightest chargino mass is assumed to be close to the stop mass, $m_{\tilde{\chi}^{\pm}_1} = m_{\tilde{t}_1}-10$ GeV.

Upper limits on cross-sections (in fb) at 95% CL for each signal model, assuming the pMSSM model described in the text. Pair production of $\tilde{t}_{1}$ and $\tilde{b}_{1}$ are considered. Limits are set for both positive (top) and negative (bottom) values of $\mu$.

Upper limits on cross-sections (in fb) at 95% CL for each signal model, assuming the pMSSM model described in the text. Pair production of $\tilde{t}_{1}$ and $\tilde{b}_{1}$ are considered. Limits are set for both positive (top) and negative (bottom) values of $\mu$.

SRA$^{2-body}_{120,140}$ Different Flavour acceptance for each signal model, assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b \tilde{\chi}^{\pm}_1$ with 100% branching ratio.

SRA$^{2-body}_{120,140}$ Same Flavour acceptance for each signal model, assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b \tilde{\chi}^{\pm}_1$ with 100% branching ratio.

SRA$^{2-body}_{140,160}$ Different Flavour acceptance for each signal model, assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b \tilde{\chi}^{\pm}_1$ with 100% branching ratio.

SRA$^{2-body}_{140,160}$ Same Flavour acceptance for each signal model, assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b \tilde{\chi}^{\pm}_1$ with 100% branching ratio.

SRA$^{2-body}_{160,180}$ Different Flavour acceptance for each signal model, assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b \tilde{\chi}^{\pm}_1$ with 100% branching ratio.

SRA$^{2-body}_{160,180}$ Same Flavour acceptance for each signal model, assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b \tilde{\chi}^{\pm}_1$ with 100% branching ratio.

SRA$^{2-body}_{180}$ Different Flavour acceptance for each signal model, assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b \tilde{\chi}^{\pm}_1$ with 100% branching ratio.

SRA$^{2-body}_{180}$ Same Flavour acceptance for each signal model, assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b \tilde{\chi}^{\pm}_1$ with 100% branching ratio.

SRB$^{2-body}_{120,140}$ Different Flavour acceptance for each signal model, assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t\tilde{\chi}^0_1$ with 100% branching ratio.

SRB$^{2-body}_{120,140}$ SF acceptance for each signal model, assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t\tilde{\chi}^0_1$ with 100% branching ratio.

SRB$^{2-body}_{140}$ Different Flavour acceptance for each signal model, assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t\tilde{\chi}^0_1$ with 100% branching ratio.

SRB$^{2-body}_{140}$ SF acceptance for each signal model, assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t\tilde{\chi}^0_1$ with 100% branching ratio.

SRC$^{2-body}_{110}$ Different Flavour acceptance for each signal model, assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t\tilde{\chi}^0_1$ with 100% branching ratio.

SRC$^{2-body}_{110}$ SF acceptance for each signal model, assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t\tilde{\chi}^0_1$ with 100% branching ratio.

SR$^{3-body}_{W}$ Different Flavour acceptance for each signal model, assuming $\tilde{t}_{1}$ pair production, decaying via $\tilde{t}_{1}\rightarrow t+\tilde{\chi}_{1}^{0}$ with 100% branching ratio.

SR$^{3-body}_{W}$ SF acceptance for each signal model, assuming $\tilde{t}_{1}$ pair production, decaying via $\tilde{t}_{1}\rightarrow t+\tilde{\chi}_{1}^{0}$ with 100% branching ratio.

SR$^{3-body}_{t}$ Different Flavour acceptance for each signal model, assuming $\tilde{t}_{1}$ pair production, decaying via $\tilde{t}_{1}\rightarrow t+\tilde{\chi}_{1}^{0}$ with 100% branching ratio.

SR$^{3-body}_{t}$ SF acceptance for each signal model, assuming $\tilde{t}_{1}$ pair production, decaying via $\tilde{t}_{1}\rightarrow t+\tilde{\chi}_{1}^{0}$ with 100% branching ratio.

SR$^{4-body}$ acceptance for each signal model, assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b f f \prime \tilde{\chi}^0_1$ with 100% branching ratio.

SRA$^{2-body}_{120,140}$ Different Flavour efficiency for each signal model, assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b \tilde{\chi}^{\pm}_1$ with 100% branching ratio.

SRA$^{2-body}_{120,140}$ Same Flavour efficiency for each signal model, assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b \tilde{\chi}^{\pm}_1$ with 100% branching ratio.

SRA$^{2-body}_{140,160}$ Different Flavour efficiency for each signal model, assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b \tilde{\chi}^{\pm}_1$ with 100% branching ratio.

SRA$^{2-body}_{140,160}$ Same Flavour efficiency for each signal model, assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b \tilde{\chi}^{\pm}_1$ with 100% branching ratio.

SRA$^{2-body}_{160,180}$ Different Flavour efficiency for each signal model, assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b \tilde{\chi}^{\pm}_1$ with 100% branching ratio.

SRA$^{2-body}_{160,180}$ Same Flavour efficiency for each signal model, assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b \tilde{\chi}^{\pm}_1$ with 100% branching ratio.

SRA$^{2-body}_{180}$ Different Flavour efficiency for each signal model, assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b \tilde{\chi}^{\pm}_1$ with 100% branching ratio.

SRA$^{2-body}_{180}$ Same Flavour efficiency for each signal model, assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b \tilde{\chi}^{\pm}_1$ with 100% branching ratio.

SRB$^{2-body}_{120,140}$ Different Flavour efficiency for each signal model, assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t\tilde{\chi}^0_1$ with 100% branching ratio.

SRB$^{2-body}_{120,140}$ Same Flavour efficiency for each signal model, assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t\tilde{\chi}^0_1$ with 100% branching ratio.

SRB$^{2-body}_{140}$ Different Flavour efficiency for each signal model, assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t\tilde{\chi}^0_1$ with 100% branching ratio.

SRB$^{2-body}_{140}$ Same Flavour efficiency for each signal model, assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t\tilde{\chi}^0_1$ with 100% branching ratio.

SRC$^{2-body}_{110}$ Different Flavour efficiency for each signal model, assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t\tilde{\chi}^0_1$ with 100% branching ratio.

SRC$^{2-body}_{110}$ Same Flavour efficiency for each signal model, assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t\tilde{\chi}^0_1$ with 100% branching ratio.

SR$^{3-body}_{W}$ Different Flavour efficiency for each signal model, assuming $\tilde{t}_{1}$ pair production, decaying via $\tilde{t}_{1}\rightarrow t+\tilde{\chi}_{1}^{0}$ with 100% branching ratio.

SR$^{3-body}_{W}$ Same Flavour efficiency for each signal model, assuming $\tilde{t}_{1}$ pair production, decaying via $\tilde{t}_{1}\rightarrow t+\tilde{\chi}_{1}^{0}$ with 100% branching ratio.

SR$^{3-body}_{t}$ Different Flavour efficiency for each signal model, assuming $\tilde{t}_{1}$ pair production, decaying via $\tilde{t}_{1}\rightarrow t+\tilde{\chi}_{1}^{0}$ with 100% branching ratio.

SR$^{3-body}_{t}$ Same Flavour efficiency for each signal model, assuming $\tilde{t}_{1}$ pair production, decaying via $\tilde{t}_{1}\rightarrow t+\tilde{\chi}_{1}^{0}$ with 100% branching ratio.

SR$^{4-body}$ efficiency for each signal model, assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b f f \prime \tilde{\chi}^0_1$ with 100% branching ratio.

Observed 95% CL limit for the pMSSM grid.

Observed 95% CL limit for the pMSSM grid when the signal cross section is increased by one standard deviation.

Observed 95% CL limit for the pMSSM grid when the signal cross section is increased by one standard deviation.

Observed 95% CL limit for the pMSSM grid when the signal cross section is decreased by one standard deviation.

Observed 95% CL limit for the pMSSM grid when the signal cross section is decreased by one standard deviation.

Expected 95% CL limit for the pMSSM grid.

Expected 95% CL limit for the pMSSM grid.

Expected 95% CL limit for the pMSSM grid with an up variation of the uncertainties.

Expected 95% CL limit for the pMSSM grid with an up variation of the uncertainties.

Expected 95% CL limit for the pMSSM grid with a down variation of the uncertainties.

Expected 95% CL limit for the pMSSM grid with a down variation of the uncertainties.

Observed 95% CL limit for the 2Step grid.

Observed 95% CL limit for the 2Step grid.

Observed 95% CL limit for the 2Step grid when the signal cross section is increased by one standard deviation.

Observed 95% CL limit for the 2Step grid when the signal cross section is increased by one standard deviation.

Observed 95% CL limit for the 2Step grid when the signal cross section is decreased by one standard deviation.

Observed 95% CL limit for the 2Step grid when the signal cross section is decreased by one standard deviation.

Expected 95% CL limit for the 2Step grid.

Expected 95% CL limit for the 2Step grid.

Expected 95% CL limit for the 2Step grid with an up variation of the uncertainties.

Expected 95% CL limit for the 2Step grid with an up variation of the uncertainties.

Expected 95% CL limit for the 2Step grid with a down variation of the uncertainties.

Expected 95% CL limit for the 2Step grid with a down variation of the uncertainties.

Observed 95% CL limit for the gtt off-shell grid.

Observed 95% CL limit for the gtt off-shell grid.

Observed 95% CL limit for the gtt off-shell grid when the signal cross section is increased by one standard deviation.

Observed 95% CL limit for the gtt off-shell grid when the signal cross section is increased by one standard deviation.

Observed 95% CL limit for the gtt off-shell grid when the signal cross section is decreased by one standard deviation.

Observed 95% CL limit for the gtt off-shell grid when the signal cross section is decreased by one standard deviation.

Expected 95% CL limit for the gtt off-shell grid.

Expected 95% CL limit for the gtt off-shell grid.

Expected 95% CL limit for the gtt off-shell grid with an up variation of the uncertainties.

Expected 95% CL limit for the gtt off-shell grid with an up variation of the uncertainties.

Expected 95% CL limit for the gtt off-shell grid with a down variation of the uncertainties.

Expected 95% CL limit for the gtt off-shell grid with a down variation of the uncertainties.

Observed 95% CL limit for the RPV grid.

Observed 95% CL limit for the RPV grid.

Observed 95% CL limit for the RPV grid when the signal cross section is increased by one standard deviation.

Observed 95% CL limit for the RPV grid when the signal cross section is increased by one standard deviation.

Observed 95% CL limit for the RPV grid when the signal cross section is decreased by one standard deviation.

Observed 95% CL limit for the RPV grid when the signal cross section is decreased by one standard deviation.

Expected 95% CL limit for the RPV grid.

Expected 95% CL limit for the RPV grid.

Expected 95% CL limit for the RPV grid with an up variation of the uncertainties.

Expected 95% CL limit for the RPV grid with an up variation of the uncertainties.

Expected 95% CL limit for the RPV grid with a down variation of the uncertainties.

Expected 95% CL limit for the RPV grid with a down variation of the uncertainties.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-7j80-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-7j80-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-7j80-1b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-7j80-1b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-7j80-2b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-7j80-2b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-8j80-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-8j80-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-8j80-1b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-8j80-1b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-8j80-2b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-8j80-2b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-9j80-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-9j80-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-9j80-1b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-9j80-1b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-9j80-2b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-9j80-2b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-8j50-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-8j50-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-8j50-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-8j50-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-8j50-1b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-8j50-1b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-8j50-2b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-8j50-2b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-9j50-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-9j50-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-9j50-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-9j50-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-9j50-1b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-9j50-1b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-9j50-2b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-9j50-2b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-10j50-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-10j50-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-10j50-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-10j50-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-10j50-1b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-10j50-1b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-10j50-2b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-10j50-2b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-11j50-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-11j50-0b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-11j50-1b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-11j50-1b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-11j50-2b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

Number of signal events expected for 36.1 fb$^{-1}$ at different stages of the event selection for the signal region SR-11j50-2b in a pMSSM inspired model where m($\tilde{g}$) = 1400 GeV and m($\tilde{\chi}_{0}^{1}$) = 200 GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-8j50-0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-8j50-0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-8j50-1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-8j50-1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-8j50-2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-8j50-2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-9j50-0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-9j50-0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-9j50-1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-9j50-1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-9j50-2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-9j50-2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-10j50-0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-10j50-0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-10j50-1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-10j50-1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-10j50-2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-10j50-2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-11j50-0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-11j50-0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-11j50-1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-11j50-1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-11j50-2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-11j50-2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-7j80-0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-7j80-0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-7j80-1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-7j80-1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-7j80-2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-7j80-2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-8j80-0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-8j80-0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-8j80-1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-8j80-1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-8j80-2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-8j80-2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-9j80-0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-9j80-0b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-9j80-1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-9j80-1b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-9j80-2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-9j80-2b. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-8j50-0b-MJ340. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-8j50-0b-MJ340. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-8j50-0b-MJ500. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-8j50-0b-MJ500. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-9j50-0b-MJ340. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-9j50-0b-MJ340. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-9j50-0b-MJ500. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-9j50-0b-MJ500. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-10j50-0b-MJ340. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-10j50-0b-MJ340. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-10j50-0b-MJ500. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

$E_{\mathrm{T}}^{\mathrm{miss}} / \sqrt{H_{\mathrm{T}}}$ distribution in signal region SR-10j50-0b-MJ500. Two benchmark signal models are overlaid on the plot for comparison. Labelled `pMSSM' and `2-step', they show signal distributions from the example SUSY models (as described in the paper): a pMSSM slice model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{\pm}}$) = (1300, 200) GeV and a cascade decay model with ($m \tilde{g}$, $m \tilde{\chi_{1}^{0}}$) = (1300, 200) GeV.

Degree of multijet closure for signal and vaidation regions (prior to the leptonic background fit) for the flavour stream with no b-jet requirement and a minimum transverse momentum of 50 GeV. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).

Degree of multijet closure for signal and vaidation regions (prior to the leptonic background fit) for the flavour stream with no b-jet requirement and a minimum transverse momentum of 50 GeV. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).

Degree of multijet closure for signal and vaidation regions (prior to the leptonic background fit) for the flavour stream with one inclusive b-jet required and a minimum transverse momentum of 50 GeV. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).

Degree of multijet closure for signal and vaidation regions (prior to the leptonic background fit) for the flavour stream with one inclusive b-jet required and a minimum transverse momentum of 50 GeV. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).

Degree of multijet closure for signal and vaidation regions (prior to the leptonic background fit) for the flavour stream with two inclusive b-jets required and a minimum transverse momentum of 50 GeV. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).

Degree of multijet closure for signal and vaidation regions (prior to the leptonic background fit) for the flavour stream with two inclusive b-jets required and a minimum transverse momentum of 50 GeV. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).

Degree of multijet closure for signal and vaidation regions (prior to the leptonic background fit) for the flavour stream with no b-jet requirement and a minimum transverse momentum of 80 GeV. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).

Degree of multijet closure for signal and vaidation regions (prior to the leptonic background fit) for the flavour stream with no b-jet requirement and a minimum transverse momentum of 80 GeV. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).

Degree of multijet closure for signal and vaidation regions (prior to the leptonic background fit) for the flavour stream with one inclusive b-jet required and a minimum transverse momentum of 80 GeV. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).

Degree of multijet closure for signal and vaidation regions (prior to the leptonic background fit) for the flavour stream with one inclusive b-jet required and a minimum transverse momentum of 80 GeV. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).

Degree of multijet closure for signal and vaidation regions (prior to the leptonic background fit) for the flavour stream with two inclusive b-jets required and a minimum transverse momentum of 80 GeV. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).

Degree of multijet closure for signal and vaidation regions (prior to the leptonic background fit) for the flavour stream with two inclusive b-jets required and a minimum transverse momentum of 80 GeV. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).

Degree of multijet closure for signal and vaidation regions (prior to the leptonic background fit) for the fat-jet stream with MJSigma above 340 GeV. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).

Degree of multijet closure for signal and vaidation regions (prior to the leptonic background fit) for the fat-jet stream with MJSigma above 340 GeV. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).

Degree of multijet closure for signal and vaidation regions (prior to the leptonic background fit) for the fat-jet stream with MJSigma above 500 GeV. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).

Degree of multijet closure for signal and vaidation regions (prior to the leptonic background fit) for the fat-jet stream with MJSigma above 500 GeV. The solid lines are the pre-fit predicted numbers of events and the points are the observed numbers. The blue hatched band shows only the statistical (MC and data) uncertainty on the background estimate. The template closure uncertainty for each SR bin is given by the maximal deviation of data from prediction in any non-SR bin to its left on this plot (although those for 80 GeV regions are independent of deviations in 50 GeV regions).

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the 2Step grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the 2Step grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the 2Step grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the 2Step grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the 2Step grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the 2Step grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the pMSSM grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the pMSSM grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the pMSSM grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the pMSSM grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the pMSSM grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the pMSSM grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the RPV grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the RPV grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the RPV grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the RPV grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the RPV grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the RPV grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the gtt off-shell grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the gtt off-shell grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the gtt off-shell grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the gtt off-shell grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the gtt off-shell grid.

The best-expected signal region and the corresponding best-observed and best-expected CLs values for the gtt off-shell grid.

95% CLs observed upper limit on model cross-section (in fb) for 2Step signal points for the best-expected signal region.

95% CLs observed upper limit on model cross-section (in fb) for 2Step signal points for the best-expected signal region.

95% CLs observed upper limit on model cross-section (in fb) for RPV signal points for the best-expected signal region.

95% CLs observed upper limit on model cross-section (in fb) for RPV signal points for the best-expected signal region.

95% CLs observed upper limit on model cross-section (in fb) for gtt off-shell signal points for the best-expected signal region.

95% CLs observed upper limit on model cross-section (in fb) for gtt off-shell signal points for the best-expected signal region.

Performance of the SR-8j50-0b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-8j50-0b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-8j50-0b-MJ340 for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-8j50-0b-MJ340 for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-8j50-0b-MJ500 for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-8j50-0b-MJ500 for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-8j50-1b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-8j50-1b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-8j50-2b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-8j50-2b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-9j50-0b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-9j50-0b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-9j50-0b-MJ340 for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-9j50-0b-MJ340 for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-9j50-0b-MJ500 for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-9j50-0b-MJ500 for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-9j50-1b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-9j50-1b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-9j50-2b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-9j50-2b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-10j50-0b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-10j50-0b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-10j50-0b-MJ340 for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-10j50-0b-MJ340 for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-10j50-0b-MJ500 for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-10j50-0b-MJ500 for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-10j50-1b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-10j50-1b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-10j50-2b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-10j50-2b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-11j50-0b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-11j50-0b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-11j50-1b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-11j50-1b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-11j50-2b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-11j50-2b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-7j80-0b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-7j80-0b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-7j80-1b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-7j80-1b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-7j80-2b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-7j80-2b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-8j80-0b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-8j80-0b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-8j80-1b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-8j80-1b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-8j80-2b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-8j80-2b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-9j80-0b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-9j80-0b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-9j80-1b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-9j80-1b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-9j80-2b for the 2Step grid: fractional acceptance; fractional efficiency.

Performance of the SR-9j80-2b for the 2Step grid: fractional acceptance; fractional efficiency.

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.

Data from Table 2. Observed and expected exclusion limits for the aQGC parameters at 95% CL, without any form factors.

Data from Fig.4. Observed yields of four lepton invariant mass distribution. The last bin includes overflow.

Data from Fig.4. Expected yields of four lepton invariant mass distribution for the EW ZZjj signal process. The last bin includes overflow.

Data from Fig.4. Expected yields of four lepton invariant mass distribution for the mixed EW-QCD qqZZjj background. The last bin includes overflow.

Data from Fig.4. Expected yields of four lepton invariant mass distribution for the mixed EW-QCD ggZZjj background. The last bin includes overflow.

Data from Fig.4. Expected yields of four lepton invariant mass distribution for the WWZ background. The last bin includes overflow.

Data from Fig.4. Expected yields of four lepton invariant mass distribution for the ttZ background. The last bin includes overflow.

Data from Fig.4. Expected yields of four lepton invariant mass distribution for the Z+X reducible background. The last bin includes overflow.

Multiplicity distribution in the pseudorapidity region -3.4 to 3.4 for NSD collisions at a centre-of-mass energy of 900 GeV.

Multiplicity distribution in the pseudorapidity region -3.4 to 5.0 for NSD collisions at a centre-of-mass energy of 900 GeV.

Multiplicity distribution in the pseudorapidity region -2.0 to 2.0 for NSD collisions at a centre-of-mass energy of 7000 GeV.

Multiplicity distribution in the pseudorapidity region -2.4 to 2.4 for NSD collisions at a centre-of-mass energy of 7000 GeV.

Multiplicity distribution in the pseudorapidity region -3.0 to 3.0 for NSD collisions at a centre-of-mass energy of 7000 GeV.

Multiplicity distribution in the pseudorapidity region -3.4 to 3.4 for NSD collisions at a centre-of-mass energy of 7000 GeV.

Multiplicity distribution in the pseudorapidity region -3.4 to 5.0 for NSD collisions at a centre-of-mass energy of 7000 GeV.

Multiplicity distribution in the pseudorapidity region -2.0 to 2.0 for NSD collisions at a centre-of-mass energy of 8000 GeV.

Multiplicity distribution in the pseudorapidity region -2.4 to 2.4 for NSD collisions at a centre-of-mass energy of 8000 GeV.

Multiplicity distribution in the pseudorapidity region -3.0 to 3.0 for NSD collisions at a centre-of-mass energy of 8000 GeV.

Multiplicity distribution in the pseudorapidity region -3.4 to 3.4 for NSD collisions at a centre-of-mass energy of 8000 GeV.

Multiplicity distribution in the pseudorapidity region -3.4 to 5.0 for NSD collisions at a centre-of-mass energy of 8000 GeV.

Multiplicity distribution in the pseudorapidity region -2.0 to 2.0 for INEL collisions at a centre-of-mass energy of 900 GeV.

Multiplicity distribution in the pseudorapidity region -2.4 to 2.4 for INEL collisions at a centre-of-mass energy of 900 GeV.

Multiplicity distribution in the pseudorapidity region -3.0 to 3.0 for INEL collisions at a centre-of-mass energy of 900 GeV.

Multiplicity distribution in the pseudorapidity region -3.4 to 3.4 for INEL collisions at a centre-of-mass energy of 900 GeV.

Multiplicity distribution in the pseudorapidity region -3.4 to 5.0 for INEL collisions at a centre-of-mass energy of 900 GeV.

Multiplicity distribution in the pseudorapidity region -2.0 to 2.0 for INEL collisions at a centre-of-mass energy of 7000 GeV.

Multiplicity distribution in the pseudorapidity region -2.4 to 2.4 for INEL collisions at a centre-of-mass energy of 7000 GeV.

Multiplicity distribution in the pseudorapidity region -3.0 to 3.0 for INEL collisions at a centre-of-mass energy of 7000 GeV.

Multiplicity distribution in the pseudorapidity region -3.4 to 3.4 for INEL collisions at a centre-of-mass energy of 7000 GeV.

Multiplicity distribution in the pseudorapidity region -3.4 to 5.0 for INEL collisions at a centre-of-mass energy of 7000 GeV.

Multiplicity distribution in the pseudorapidity region -2.0 to 2.0 for INEL collisions at a centre-of-mass energy of 8000 GeV.

Multiplicity distribution in the pseudorapidity region -2.4 to 2.4 for INEL collisions at a centre-of-mass energy of 8000 GeV.

Multiplicity distribution in the pseudorapidity region -3.0 to 3.0 for INEL collisions at a centre-of-mass energy of 8000 GeV.

Multiplicity distribution in the pseudorapidity region -3.4 to 3.4 for INEL collisions at a centre-of-mass energy of 8000 GeV.

Multiplicity distribution in the pseudorapidity region -3.4 to 5.0 for INEL collisions at a centre-of-mass energy of 8000 GeV.

Multiplicity distribution in the pseudorapidity region -2.0 to 2.0 for INEL>0 collisions at a centre-of-mass energy of 900 GeV.

Multiplicity distribution in the pseudorapidity region -2.4 to 2.4 for INEL>0 collisions at a centre-of-mass energy of 900 GeV.

Multiplicity distribution in the pseudorapidity region -3.0 to 3.0 for INEL>0 collisions at a centre-of-mass energy of 900 GeV.

Multiplicity distribution in the pseudorapidity region -3.4 to 3.4 for INEL>0 collisions at a centre-of-mass energy of 900 GeV.

Multiplicity distribution in the pseudorapidity region -3.4 to 5.0 for INEL>0 collisions at a centre-of-mass energy of 900 GeV.

Multiplicity distribution in the pseudorapidity region -2.0 to 2.0 for INEL>0 collisions at a centre-of-mass energy of 7000 GeV.

Multiplicity distribution in the pseudorapidity region -2.4 to 2.4 for INEL>0 collisions at a centre-of-mass energy of 7000 GeV.

Multiplicity distribution in the pseudorapidity region -3.0 to 3.0 for INEL>0 collisions at a centre-of-mass energy of 7000 GeV.

Multiplicity distribution in the pseudorapidity region -3.4 to 3.4 for INEL>0 collisions at a centre-of-mass energy of 7000 GeV.

Multiplicity distribution in the pseudorapidity region -3.4 to 5.0 for INEL>0 collisions at a centre-of-mass energy of 7000 GeV.

Multiplicity distribution in the pseudorapidity region -2.0 to 2.0 for INEL>0 collisions at a centre-of-mass energy of 8000 GeV.

Multiplicity distribution in the pseudorapidity region -2.4 to 2.4 for INEL>0 collisions at a centre-of-mass energy of 8000 GeV.

Multiplicity distribution in the pseudorapidity region -3.0 to 3.0 for INEL>0 collisions at a centre-of-mass energy of 8000 GeV.

Multiplicity distribution in the pseudorapidity region -3.4 to 3.4 for INEL>0 collisions at a centre-of-mass energy of 8000 GeV.

Multiplicity distribution in the pseudorapidity region -3.4 to 5.0 for INEL>0 collisions at a centre-of-mass energy of 8000 GeV.

Set of fit parameters for the multiplicity distribution in pseudorapidity range -2.0 to 2.0 in NSD collisions at center-of-mass energy 900 GeV.

Set of fit parameters for the multiplicity distribution in pseudorapidity range -2.4 to 2.4 in NSD collisions at center-of-mass energy 900 GeV.

Set of fit parameters for the multiplicity distribution in pseudorapidity range -3.0 to 3.0 in NSD collisions at center-of-mass energy 900 GeV.

Set of fit parameters for the multiplicity distribution in pseudorapidity range -3.4 to 3.4 in NSD collisions at center-of-mass energy 900 GeV.

Set of fit parameters for the multiplicity distribution in pseudorapidity range -3.4 to 5.0 in NSD collisions at center-of-mass energy 900 GeV.

Set of fit parameters for the multiplicity distribution in pseudorapidity range -2.0 to 2.0 in NSD collisions at center-of-mass energy 7000 GeV.

Set of fit parameters for the multiplicity distribution in pseudorapidity range -2.4 to 2.4 in NSD collisions at center-of-mass energy 7000 GeV.

Set of fit parameters for the multiplicity distribution in pseudorapidity range -3.0 to 3.0 in NSD collisions at center-of-mass energy 7000 GeV.

Set of fit parameters for the multiplicity distribution in pseudorapidity range -3.4 to 3.4 in NSD collisions at center-of-mass energy 7000 GeV.

Set of fit parameters for the multiplicity distribution in pseudorapidity range -3.4 to 5.0 in NSD collisions at center-of-mass energy 7000 GeV.

Set of fit parameters for the multiplicity distribution in pseudorapidity range -2.0 to 2.0 in NSD collisions at center-of-mass energy 8000 GeV.

Set of fit parameters for the multiplicity distribution in pseudorapidity range -2.4 to 2.4 in NSD collisions at center-of-mass energy 8000 GeV.

Set of fit parameters for the multiplicity distribution in pseudorapidity range -3.0 to 3.0 in NSD collisions at center-of-mass energy 8000 GeV.

Set of fit parameters for the multiplicity distribution in pseudorapidity range -3.4 to 3.4 in NSD collisions at center-of-mass energy 8000 GeV.

Set of fit parameters for the multiplicity distribution in pseudorapidity range -3.4 to 5.0 in NSD collisions at center-of-mass energy 8000 GeV.

Set of fit parameters for the multiplicity distribution in pseudorapidity range -2.0 to 2.0 in INEL collisions at center-of-mass energy 900 GeV.

Set of fit parameters for the multiplicity distribution in pseudorapidity range -2.4 to 2.4 in INEL collisions at center-of-mass energy 900 GeV.

Set of fit parameters for the multiplicity distribution in pseudorapidity range -3.0 to 3.0 in INEL collisions at center-of-mass energy 900 GeV.

Set of fit parameters for the multiplicity distribution in pseudorapidity range -3.4 to 3.4 in INEL collisions at center-of-mass energy 900 GeV.

Set of fit parameters for the multiplicity distribution in pseudorapidity range -3.4 to 5.0 in INEL collisions at center-of-mass energy 900 GeV.

Set of fit parameters for the multiplicity distribution in pseudorapidity range -2.0 to 2.0 in INEL collisions at center-of-mass energy 7000 GeV.

Set of fit parameters for the multiplicity distribution in pseudorapidity range -2.4 to 2.4 in INEL collisions at center-of-mass energy 7000 GeV.

Set of fit parameters for the multiplicity distribution in pseudorapidity range -3.0 to 3.0 in INEL collisions at center-of-mass energy 7000 GeV.

Set of fit parameters for the multiplicity distribution in pseudorapidity range -3.4 to 3.4 in INEL collisions at center-of-mass energy 7000 GeV.

Set of fit parameters for the multiplicity distribution in pseudorapidity range -3.4 to 5.0 in INEL collisions at center-of-mass energy 7000 GeV.

Set of fit parameters for the multiplicity distribution in pseudorapidity range -2.0 to 2.0 in INEL collisions at center-of-mass energy 8000 GeV.

Set of fit parameters for the multiplicity distribution in pseudorapidity range -2.4 to 2.4 in INEL collisions at center-of-mass energy 8000 GeV.

Set of fit parameters for the multiplicity distribution in pseudorapidity range -3.0 to 3.0 in INEL collisions at center-of-mass energy 8000 GeV.

Set of fit parameters for the multiplicity distribution in pseudorapidity range -3.4 to 3.4 in INEL collisions at center-of-mass energy 8000 GeV.

Set of fit parameters for the multiplicity distribution in pseudorapidity range -3.4 to 5.0 in INEL collisions at center-of-mass energy 8000 GeV.

Set of fit parameters for the multiplicity distribution in pseudorapidity range -2.0 to 2.0 in INEL>0 collisions at center-of-mass energy 900 GeV.

Set of fit parameters for the multiplicity distribution in pseudorapidity range -2.4 to 2.4 in INEL>0 collisions at center-of-mass energy 900 GeV.

Set of fit parameters for the multiplicity distribution in pseudorapidity range -3.0 to 3.0 in INEL>0 collisions at center-of-mass energy 900 GeV.

Set of fit parameters for the multiplicity distribution in pseudorapidity range -3.4 to 3.4 in INEL>0 collisions at center-of-mass energy 900 GeV.

Set of fit parameters for the multiplicity distribution in pseudorapidity range -3.4 to 5.0 in INEL>0 collisions at center-of-mass energy 900 GeV.

Set of fit parameters for the multiplicity distribution in pseudorapidity range -2.0 to 2.0 in INEL>0 collisions at center-of-mass energy 7000 GeV.

Set of fit parameters for the multiplicity distribution in pseudorapidity range -2.4 to 2.4 in INEL>0 collisions at center-of-mass energy 7000 GeV.

Set of fit parameters for the multiplicity distribution in pseudorapidity range -3.0 to 3.0 in INEL>0 collisions at center-of-mass energy 7000 GeV.

Set of fit parameters for the multiplicity distribution in pseudorapidity range -3.4 to 3.4 in INEL>0 collisions at center-of-mass energy 7000 GeV.

Set of fit parameters for the multiplicity distribution in pseudorapidity range -3.4 to 5.0 in INEL>0 collisions at center-of-mass energy 7000 GeV.

Set of fit parameters for the multiplicity distribution in pseudorapidity range -2.0 to 2.0 in INEL>0 collisions at center-of-mass energy 8000 GeV.

Set of fit parameters for the multiplicity distribution in pseudorapidity range -2.4 to 2.4 in INEL>0 collisions at center-of-mass energy 8000 GeV.

Set of fit parameters for the multiplicity distribution in pseudorapidity range -3.0 to 3.0 in INEL>0 collisions at center-of-mass energy 8000 GeV.

Set of fit parameters for the multiplicity distribution in pseudorapidity range -3.4 to 3.4 in INEL>0 collisions at center-of-mass energy 8000 GeV.

Set of fit parameters for the multiplicity distribution in pseudorapidity range -3.4 to 5.0 in INEL>0 collisions at center-of-mass energy 8000 GeV.

Three-particle correlation with respect to the 3rd order event plane from Pb-going side in pPb collisions.

Three-particle correlation with respect to the 3rd order event plane from p-going side in pPb collisions.

Three-particle correlation with respect to the 3rd order event plane in PbPb collisions.

Two-particle correlation in pPb collisions.

Two-particle correlation in PbPb collisions.

Three-particle correlation with respect to the 2nd order event plane from Pb-going side in pPb collisions.

Three-particle correlation with respect to the 2nd order event plane from p-going side in pPb collisions.

Three-particle correlation with respect to the 2nd order event plane in PbPb collisions.

Three-particle correlation with respect to the 3rd order event plane from Pb-going side in pPb collisions.

Three-particle correlation with respect to the 3rd order event plane from p-going side in pPb collisions.

Three-particle correlation with respect to the 3rd order event plane in PbPb collisions.

Two-particle correlation in pPb collisions.

Two-particle correlation in PbPb collisions.

Three-particle correlation with respect to the 2nd order event plane from Pb-going side in pPb collisions.

Three-particle correlation with respect to the 2nd order event plane from p-going side in pPb collisions.

Three-particle correlation with respect to the 2nd order event plane in PbPb collisions.

Three-particle correlation with respect to the 3rd order event plane from Pb-going side in pPb collisions.

Three-particle correlation with respect to the 3rd order event plane from p-going side in pPb collisions.

Three-particle correlation with respect to the 3rd order event plane in PbPb collisions.

Two-particle correlation in pPb collisions.

Two-particle correlation in PbPb collisions.

Three-particle correlation with respect to the 2nd order event plane from Pb-going side in pPb collisions.

Three-particle correlation with respect to the 2nd order event plane in PbPb collisions.

Three-particle correlation with respect to the 2nd order event plane in PbPb collisions.

Three-particle correlation with respect to the 2nd order event plane from Pb-going side in pPb collisions.

Three-particle correlation with respect to the 2nd order event plane in PbPb collisions.

Three-particle correlation with respect to the 2nd order event plane in PbPb collisions.

Three-particle correlation with respect to the 3rd order event plane from Pb-going side in pPb collisions.

Three-particle correlation with respect to the 3rd order event plane in PbPb collisions.

Three-particle correlation with respect to the 2nd order event plane in PbPb collisions.

Two-particle correlation in pPb collisions.

Two-particle correlation in PbPb collisions.

Two-particle correlation in PbPb collisions.

Three-particle correlation with respect to the 2nd order event plane from Pb-going side in pPb collisions.

Three-particle correlation with respect to the 2nd order event plane from p-going side in pPb collisions.

Three-particle correlation with respect to the 2nd order event plane in PbPb collisions.

Three-particle correlation with respect to the 2nd order event plane from Pb-going side in pPb collisions.

Three-particle correlation with respect to the 2nd order event plane from p-going side in pPb collisions.

Three-particle correlation with respect to the 2nd order event plane in PbPb collisions.

Three-particle correlation with respect to the 2nd order event plane from Pb-going side in pPb collisions.

Three-particle correlation with respect to the 2nd order event plane from p-going side in pPb collisions.

Three-particle correlation with respect to the 2nd order event plane in PbPb collisions.

Three-particle correlation with respect to the 3rd order event plane from Pb-going side in pPb collisions.

Three-particle correlation with respect to the 3rd order event plane from p-going side in pPb collisions.

Three-particle correlation with respect to the 3rd order event plane in PbPb collisions.

Three-particle correlation with respect to the 3rd order event plane from Pb-going side in pPb collisions.

Three-particle correlation with respect to the 3rd order event plane from p-going side in pPb collisions.

Three-particle correlation with respect to the 3rd order event plane in PbPb collisions.

Three-particle correlation with respect to the 3rd order event plane from Pb-going side in pPb collisions.

Three-particle correlation with respect to the 3rd order event plane from p-going side in pPb collisions.

Three-particle correlation with respect to the 3rd order event plane in PbPb collisions.

Two-particle correlation in pPb collisions.

Two-particle correlation in PbPb collisions.

Two-particle correlation in pPb collisions.

Two-particle correlation in PbPb collisions.

Two-particle correlation in pPb collisions.

Two-particle correlation in PbPb collisions.

Three-particle correlation with respect to the 2nd order event plane in Pb-going direction in pPb collisions.

Three-particle correlation with respect to the 2nd order event plane in p-going direction in pPb collisions.

Three-particle correlation with respect to the 2nd order event plane in PbPb collisions.

Three-particle correlation with respect to the 2nd order event plane in PbPb collisions.

Three-particle correlation with respect to the 3rd order event plane in Pb-going direction in pPb collisions.

Three-particle correlation with respect to the 3rd order event plane in PbPb collisions.

Three-particle correlation with respect to the 3rd order event plane in PbPb collisions.

Two-particle correlation in pPb collisions.

Two-particle correlation in PbPb collisions.

Two-particle correlation in PbPb collisions.

Three-particle to two-particle correlation ratio from Pb-going side in pPb collisions.

Three-particle to two-particle correlation ratio in PbPb collisions.

Three-particle to two-particle correlation ratio in PbPb collisions.

Three-particle to two-particle correlation ratio in pPb (Pb- and p-going direction) collisions.

Three-particle to two-particle correlation ratio in pPb (Pb- and p-going direction) collisions.

Three-particle to two-particle correlation ratio in pPb (Pb- and p-going direction) collisions.

Three-particle to two-particle correlation ratio in PbPb collisions.

Three-particle to two-particle correlation ratio in PbPb collisions.

Three-particle to two-particle correlation ratio in PbPb collisions.

Three-particle correlation with respect to the 2nd order event plane from Pb-going side as a function of v2 in pPb collisions.

Three-particle correlation with respect to the 2nd order event plane from p-going side as a function of v2 in pPb collisions.

Three-particle correlation with respect to the 2nd order event plane as a function of v2 in PbPb collisions.

Three-particle correlation (OS-SS) with respect to the 2nd order event plane as a function of v2 in pPb collisions.

Three-particle correlation (OS-SS) with respect to the 2nd order event plane as a function of v2 in PbPb collisions.

Three-particle correlation (OS-SS) with respect to the 2nd order event plane as a function of v2 in PbPb collisions.

Two-particle correlation (OS-SS) as a function of v2 in pPb collisions.

Two-particle correlation (OS-SS) as a function of v2 in PbPb collisions.

Ratio of three-particle and two-particle correlation (OS-SS) as a function of v2 in pPb collisions.

Ratio of three-particle and two-particle correlation (OS-SS) as a function of v2 in PbPb collisions.

Extracted intercept parameter b_norm in PbPb collisions.

Extracted intercept parameter b_norm in pPb collisions.

Upper limit on v2-independent gamma_112 correlator component in PbPb collisions.

Upper limit on v2-independent gamma_112 correlator component in pPb collisions.

Covariance matrix of the relative cross-section as function of the top quark pT, accounting for the statistical and systematic uncertainties in the resolved topology.

Covariance matrix for the absolute cross-section as function of the hadronic top-quark top quark pT, accounting for the statistic and systematic uncertainties in the boosted topology.

Covariance matrix for the absolute cross-section as function of the hadronic top-quark top quark pT, accounting for the statistic and systematic uncertainties in the boosted topology.

Covariance matrix for the relative cross-section as function of the hadronic top-quark top quark pT, accounting for the statistic and systematic uncertainties in the boosted topology.

Covariance matrix for the relative cross-section as function of the hadronic top-quark top quark pT, accounting for the statistic and systematic uncertainties in the boosted topology.

Covariance matrix of the absolute cross-section as function of the absolute value of the rapidity of the top quark, accounting for the statistical and systematic uncertainties in the resolved topology.

Covariance matrix of the absolute cross-section as function of the absolute value of the rapidity of the top quark, accounting for the statistical and systematic uncertainties in the resolved topology.

Covariance matrix of the relative cross-section as function of the absolute value of the rapidity of the top quark, accounting for the statistical and systematic uncertainties in the resolved topology.

Covariance matrix of the relative cross-section as function of the absolute value of the rapidity of the top quark, accounting for the statistical and systematic uncertainties in the resolved topology.

Covariance matrix for the absolute cross-section as function of the absolute value of the rapidity of the top quark, accounting for the statistic and systematic uncertainties in the boosted topology.

Covariance matrix for the absolute cross-section as function of the absolute value of the rapidity of the top quark, accounting for the statistic and systematic uncertainties in the boosted topology.

Covariance matrix for the relative cross-section as function of the absolute value of the rapidity of the top quark, accounting for the statistic and systematic uncertainties in the boosted topology.

Covariance matrix for the relative cross-section as function of the absolute value of the rapidity of the top quark, accounting for the statistic and systematic uncertainties in the boosted topology.

Covariance matrix of the absolute cross-section as function of the mass of the tt̄ system, accounting for the statistical and systematic uncertainties in the resolved topology.

Covariance matrix of the absolute cross-section as function of the mass of the tt̄ system, accounting for the statistical and systematic uncertainties in the resolved topology.

Covariance matrix of the relative cross-section as function of the mass of the tt̄ system, accounting for the statistical and systematic uncertainties in the resolved topology.

Covariance matrix of the relative cross-section as function of the mass of the tt̄ system, accounting for the statistical and systematic uncertainties in the resolved topology.

Covariance matrix of the absolute cross-section as function of the tt̄ system pT, accounting for the statistical and systematic uncertainties in the resolved topology.

Covariance matrix of the absolute cross-section as function of the tt̄ system pT, accounting for the statistical and systematic uncertainties in the resolved topology.

Covariance matrix of the relative cross-section as function of the tt̄ system pT, accounting for the statistical and systematic uncertainties in the resolved topology.

Covariance matrix of the relative cross-section as function of the tt̄ system pT, accounting for the statistical and systematic uncertainties in the resolved topology.

Covariance matrix of the absolute cross-section as function of the absolute value of the rapidity of the tt̄ system, accounting for the statistical and systematic uncertainties in the resolved topology.

Covariance matrix of the absolute cross-section as function of the absolute value of the rapidity of the tt̄ system, accounting for the statistical and systematic uncertainties in the resolved topology.

Covariance matrix of the absolute cross-section as function of the absolute value of the rapidity of the tt̄ system, accounting for the statistical and systematic uncertainties in the resolved topology.

Covariance matrix of the absolute cross-section as function of the absolute value of the rapidity of the tt̄ system, accounting for the statistical and systematic uncertainties in the resolved topology.

Table of systematic uncertainties for the absolute differential cross-section at particle level for the top quark transverse momentum in the resolved regime. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Table of systematic uncertainties for the absolute differential cross-section at particle level for the top quark transverse momentum in the resolved regime. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Table of systematic uncertainties for the relative differential cross-section at particle level for the top quark transverse momentum in the resolved regime. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Table of systematic uncertainties for the relative differential cross-section at particle level for the top quark transverse momentum in the resolved regime. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Table of systematic uncertainties for the absolute differential cross-section at particle level for the absolute value of the top quark rapidity in the resolved regime. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Table of systematic uncertainties for the absolute differential cross-section at particle level for the absolute value of the top quark rapidity in the resolved regime. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Table of systematic uncertainties for the relative differential cross-section at particle level for the absolute value of the top quark rapidity in the resolved regime. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Table of systematic uncertainties for the relative differential cross-section at particle level for the absolute value of the top quark rapidity in the resolved regime. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Table of systematic uncertainties for the absolute differential cross-section at particle level for the tt̄ system transverse momentum in the resolved regime. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Table of systematic uncertainties for the absolute differential cross-section at particle level for the tt̄ system transverse momentum in the resolved regime. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Table of systematic uncertainties for the relative differential cross-section at particle level for the tt̄ system transverse momentum in the resolved regime. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Table of systematic uncertainties for the relative differential cross-section at particle level for the tt̄ system transverse momentum in the resolved regime. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Table of systematic uncertainties for the absolute differential cross-section at particle level for the absolute value of the tt̄ system rapidity in the resolved regime. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Table of systematic uncertainties for the absolute differential cross-section at particle level for the absolute value of the tt̄ system rapidity in the resolved regime. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Table of systematic uncertainties for the relative differential cross-section at particle level for the absolute value of the tt̄ system rapidity in the resolved regime. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Table of systematic uncertainties for the relative differential cross-section at particle level for the absolute value of the tt̄ system rapidity in the resolved regime. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Table of systematic uncertainties for the absolute differential cross-section at particle level for the mass of the tt̄ system in the resolved regime. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Table of systematic uncertainties for the absolute differential cross-section at particle level for the mass of the tt̄ system in the resolved regime. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Table of systematic uncertainties for the relative differential cross-section at particle level for the mass of the tt̄ system in the resolved regime. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Table of systematic uncertainties for the relative differential cross-section at particle level for the mass of the tt̄ system in the resolved regime. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Table of systematic uncertainties for the absolute differential cross-section at particle level for the top quark transverse momentum in the boosted regime. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Table of systematic uncertainties for the absolute differential cross-section at particle level for the top quark transverse momentum in the boosted regime. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Table of systematic uncertainties for the relative differential cross-section at particle level for the top quark transverse momentum in the boosted regime. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Table of systematic uncertainties for the relative differential cross-section at particle level for the top quark transverse momentum in the boosted regime. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Table of systematic uncertainties for the absolute differential cross-section at particle level for the absolute value of the top quark rapidity in the boosted regime. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Table of systematic uncertainties for the absolute differential cross-section at particle level for the absolute value of the top quark rapidity in the boosted regime. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Table of systematic uncertainties for the relative differential cross-section at particle level for the absolute value of the top quark rapidity in the boosted regime. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Table of systematic uncertainties for the relative differential cross-section at particle level for the absolute value of the top quark rapidity in the boosted regime. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text.

Best fit signal strength per category, for mH = 125.09 GeV. The constraints from the global fit are used to extract each of the individual best fit signal strengths. The combined best fit signal strength is μ = 1.09+0.27

Best fit signal strength per channel, for mH = 125.09 GeV. The constraints from the global fit are used to extract each of the individual best fit signal strengths. The combined best fit signal strength is μ = 1.09+0.27

v2 of anti-deuterons and deuterons vs $p_{\mathrm T}$ for different centrality intervals

$B_2$ vs $p_{\mathrm T/A}$ for $p_{\mathrm T/A} > $ 2.2 GeV/$c$. Low $p_{\mathrm T/A}$ points can be found here 'http://hepdata.cedar.ac.uk/view/ins1380491'