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.

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.

Prompt D0 meson v3 in 0-10 centrality percentile in midrapidity (|y| < 1.0) in PbPb collisions at 5.02 TeV. The second sys is the systematic uncertainty from the nonprompt D0. The first sys is the systematic uncertainty from other sources.

Prompt D0 meson v3 in 10-30 centrality percentile in midrapidity (|y| < 1.0) in PbPb collisions at 5.02 TeV. The second sys is the systematic uncertainty from the nonprompt D0. The first sys is the systematic uncertainty from other sources.

Prompt D0 meson v3 in 30-50 centrality percentile in midrapidity (|y| < 1.0) in PbPb collisions at 5.02 TeV. The second sys is the systematic uncertainty from the nonprompt D0. The first sys is the systematic uncertainty from other sources.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

The mjj distribution in data and simulated events after requiring all selection criteria in the e+e- channel. The various signal hypotheses displayed have been scaled to a cross section of 5 pb for display purposes.

The mjj distribution in data and simulated events after requiring all selection criteria in the e^{+/-}mu^{-/+} channel. The various signal hypotheses displayed have been scaled to a cross section of 5 pb for display purposes.

The mjj distribution in data and simulated events after requiring all selection criteria in the mu+mu- channel. The various signal hypotheses displayed have been scaled to a cross section of 5 pb for display purposes.

The DNN output distributions in data and simulated events after requiring all selection criteria, in the e+e− channel. Output values towards 0 are background-like, while output values towards 1 are signal-like. The parameterised resonant DNN output is evaluated at mX=400GeV. The signal hypothesis has been scaled to a cross section of 5 pb for display purposes.

The DNN output distributions in data and simulated events after requiring all selection criteria, in the e+e− channel. Output values towards 0 are background-like, while output values towards 1 are signal-like. The parameterised nonresonant DNN output is evaluated at \kappa_\lambda=1, \kappa_t=1. The signal hypothesis has been scaled to a cross section of 5 pb for display purposes.

The DNN output distributions in data and simulated events after requiring all selection criteria, in the e^{+/-}mu^{-/+} channel. Output values towards 0 are background-like, while output values towards 1 are signal-like. The parameterised resonant DNN output is evaluated at mX=400GeV. The signal hypothesis has been scaled to a cross section of 5 pb for display purposes.

The DNN output distributions in data and simulated events after requiring all selection criteria, in the e^{+/-}mu^{-/+} channel. Output values towards 0 are background-like, while output values towards 1 are signal-like. The parameterised nonresonant DNN output is evaluated at \kappa_\lambda=1, \kappa_t=1. The signal hypothesis has been scaled to a cross section of 5 pb for display purposes.

The DNN output distributions in data and simulated events after requiring all selection criteria, in the mu+mu− channel. Output values towards 0 are background-like, while output values towards 1 are signal-like. The parameterised resonant DNN output is evaluated at mX=400GeV. The signal hypothesis has been scaled to a cross section of 5 pb for display purposes.

The DNN output distributions in data and simulated events after requiring all selection criteria, in the mu+mu− channel. Output values towards 0 are background-like, while output values towards 1 are signal-like. The parameterised nonresonant DNN output is evaluated at \kappa_\lambda=1, \kappa_t=1. The signal hypothesis has been scaled to a cross section of 5 pb for display purposes.

The DNN output distributions in data and simulated events, for the e+e- channel, in three different mjj regions. The parameterised resonant DNN output is evaluated at mX=400GeV. The signal hypothesis has been scaled to a cross section of 5 pb for display purposes.

The DNN output distributions in data and simulated events, for the e+e- channel, in three different mjj regions. Output values towards 0 are background-like, while output values towards 1 are signal-like. The parameterised nonresonant DNN output is evaluated at \kappa_\lambda=1, \kappa_t=1. The signal hypothesis has been scaled to a cross section of 5 pb for display purposes.

The DNN output distributions in data and simulated events, for the e^{+/-}mu^{-/+} channel, in three different mjj regions. Output values towards 0 are background-like, while output values towards 1 are signal-like. The parameterised resonant DNN output is evaluated at mX=400GeV. The signal hypothesis has been scaled to a cross section of 5 pb for display purposes.

The DNN output distributions in data and simulated events, for the e^{+/-}mu^{-/+} channel, in three different mjj regions. Output values towards 0 are background-like, while output values towards 1 are signal-like. The parameterised nonresonant DNN output is evaluated at \kappa_\lambda=1, \kappa_t=1. The signal hypothesis has been scaled to a cross section of 5 pb for display purposes.

The DNN output distributions in data and simulated events, for the mu+mu- channel, in three different mjj regions. Output values towards 0 are background-like, while output values towards 1 are signal-like. The parameterised resonant DNN output is evaluated at mX=400GeV. The signal hypothesis has been scaled to a cross section of 5 pb for display purposes.

The DNN output distributions in data and simulated events, for the mu+mu- channel, in three different mjj regions. Output values towards 0 are background-like, while output values towards 1 are signal-like. The parameterised nonresonant DNN output is evaluated at \kappa_\lambda=1, \kappa_t=1. The signal hypothesis has been scaled to a cross section of 5 pb for display purposes.

Expected and observed 95% CL upper limits on the product of the production cross section for X and branching fraction for X -> HH -> bbVV -> bblnulnu, as a function of mX. These limits are computed using the asymptotic CLs method, combining all channels, for the spin-0 hypothesis.

Expected and observed 95% CL upper limits on the product of the production cross section for X and branching fraction for X -> HH -> bbVV -> bblnulnu, as a function of mX. These limits are computed using the asymptotic CLs method, combining all channels, for the spin-2 hypothesis.

expected and observed 95% CL upper limits on the product of the Higgs boson pair production cross section and branching fraction for HH -> bbVV -> bblnulnu as a function of kappa_top/kappa_lambda.

Exclusions in the (\kappa_top, \kappa_\lambda) plane. Parameters excluded at 95% CL with the observed data, and expected exclusions and the 68 and 95% bands.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Leading ($\alpha$ = 1) and subleading ($\alpha$ = 2) elliptic flow, $v^{(\alpha)}_2$, as a function of $p_T$ in 10-20% centrality PbPb collisions.

Leading ($\alpha$ = 1) and subleading ($\alpha$ = 2) elliptic flow, $v^{(\alpha)}_2$, as a function of $p_T$ in 20-30% centrality PbPb collisions.

Leading ($\alpha$ = 1) and subleading ($\alpha$ = 2) elliptic flow, $v^{(\alpha)}_2$, as a function of $p_T$ in 30-40% centrality PbPb collisions.

Leading ($\alpha$ = 1) and subleading ($\alpha$ = 2) elliptic flow, $v^{(\alpha)}_2$, as a function of $p_T$ in 40-50% centrality PbPb collisions.

Leading ($\alpha$ = 1) and subleading ($\alpha$ = 2) elliptic flow, $v^{(\alpha)}_2$, as a function of $p_T$ in 50-60% centrality PbPb collisions.

Leading ($\alpha$ = 1) and subleading ($\alpha$ = 2) triangular flow, $v^{(\alpha)}_3$, as a function of $p_T$ in 0-0.2% centrality PbPb collisions.

Leading ($\alpha$ = 1) and subleading ($\alpha$ = 2) triangular flow, $v^{(\alpha)}_3$, as a function of $p_T$ in 0-5% centrality PbPb collisions.

Leading ($\alpha$ = 1) and subleading ($\alpha$ = 2) triangular flow, $v^{(\alpha)}_3$, as a function of $p_T$ in 0-10% centrality PbPb collisions.

Leading ($\alpha$ = 1) and subleading ($\alpha$ = 2) triangular flow, $v^{(\alpha)}_3$, as a function of $p_T$ in 10-20% centrality PbPb collisions.

Leading ($\alpha$ = 1) and subleading ($\alpha$ = 2) triangular flow, $v^{(\alpha)}_3$, as a function of $p_T$ in 20-30% centrality PbPb collisions.

Leading ($\alpha$ = 1) and subleading ($\alpha$ = 2) triangular flow, $v^{(\alpha)}_3$, as a function of $p_T$ in 30-40% centrality PbPb collisions.

Leading ($\alpha$ = 1) and subleading ($\alpha$ = 2) triangular flow, $v^{(\alpha)}_3$, as a function of $p_T$ in 40-50% centrality PbPb collisions.

Leading ($\alpha$ = 1) and subleading ($\alpha$ = 2) triangular flow, $v^{(\alpha)}_3$, as a function of $p_T$ in 50-60% centrality PbPb collisions.

Leading ($\alpha$ = 1) and subleading ($\alpha$ = 2) elliptic flow, $v^{(\alpha)}_2$, as a function of $p_T$ for multiplicity class $220 \leq N^{offline}_{trk}<260$ in pPb collisions.

Leading ($\alpha$ = 1) and subleading ($\alpha$ = 2) elliptic flow, $v^{(\alpha)}_2$, as a function of $p_T$ for multiplicity class $185 \leq N^{offline}_{trk}<220$ in pPb collisions.

Leading ($\alpha$ = 1) and subleading ($\alpha$ = 2) elliptic flow, $v^{(\alpha)}_2$, as a function of $p_T$ for multiplicity class $150 \leq N^{offline}_{trk}<185$ in pPb collisions.

Leading ($\alpha$ = 1) and subleading ($\alpha$ = 2) elliptic flow, $v^{(\alpha)}_2$, as a function of $p_T$ $120 \leq N^{offline}_{trk}<150$ in pPb collisions.

Leading ($\alpha$ = 1) and subleading ($\alpha$ = 2) triangular flow, $v^{(\alpha)}_3$, as a function of $p_T$ for multiplicity class $220 \leq N^{offline}_{trk}<260$ in pPb collisions.

Leading ($\alpha$ = 1) and subleading ($\alpha$ = 2) triangular flow, $v^{(\alpha)}_3$, as a function of $p_T$ for multiplicity class $185 \leq N^{offline}_{trk}<220$ in pPb collisions.

Leading ($\alpha$ = 1) and subleading ($\alpha$ = 2) triangular flow, $v^{(\alpha)}_3$, as a function of $p_T$ for multiplicity class $150 \leq N^{offline}_{trk}<185$ in pPb collisions.

Leading ($\alpha$ = 1) and subleading ($\alpha$ = 2) triangular flow, $v^{(\alpha)}_3$, as a function of $p_T$ for multiplicity class $120 \leq N^{offline}_{trk}<150$ in pPb collisions.

Pearson correlation coefficients $r_2$ and $r_3$ reconstructed using the leading and subleading flows as a function of $p^{a}_{T} - p^{b}_{T}$ in bin $p^{a}_{T}$ for centrality class 0-0.2% in PbPb collisions.

Pearson correlation coefficients $r_2$ and $r_3$ reconstructed using the leading and subleading flows as a function of $p^{a}_{T} - p^{b}_{T}$ in bin $p^{a}_{T}$ for centrality class 0-5% in PbPb collisions.

Pearson correlation coefficients $r_2$ and $r_3$ reconstructed using the leading and subleading flows as a function of $p^{a}_{T} - p^{b}_{T}$ in bin $p^{a}_{T}$ for centrality class 10-20% in PbPb collisions.

Pearson correlation coefficients $r_2$ and $r_3$ reconstructed using the leading and subleading flows as a function of $p^{a}_{T} - p^{b}_{T}$ in bin $p^{a}_{T}$ for centrality class 20-30% in PbPb collisions.

Pearson correlation coefficients $r_2$ and $r_3$ reconstructed using the leading and subleading flows as a function of $p^{a}_{T} - p^{b}_{T}$ in bin $p^{a}_{T}$ for centrality class 30-40% in PbPb collisions.

Pearson correlation coefficients $r_2$ and $r_3$ reconstructed using the leading and subleading flows as a function of $p^{a}_{T} - p^{b}_{T}$ in bin $p^{a}_{T}$ for centrality class 40-50% in PbPb collisions.

Elliptic and triangular ratios of subleading and leading flow as a function of multiplicity for the highest bin 2.5 < $p_T$ < 3.0 GeV in PbPb collisions.

Elliptic and triangular ratios of subleading and leading flow as a function of multiplicity for the highest bin 2.5 < $p_T$ < 3.0 GeV in pPb collisions.

Leading ($\alpha$ = 1) and subleading ($\alpha$ = 2) multiplicity modes, $v^{(\alpha)}_0$, as a function of $p_T$ in 0-0.2% centrality PbPb collisions.

Leading ($\alpha$ = 1) and subleading ($\alpha$ = 2) multiplicity modes, $v^{(\alpha)}_0$, as a function of $p_T$ in 0-5% centrality PbPb collisions.

Leading ($\alpha$ = 1) and subleading ($\alpha$ = 2) multiplicity modes, $v^{(\alpha)}_0$, as a function of $p_T$ in 0-10% centrality PbPb collisions.

Leading ($\alpha$ = 1) and subleading ($\alpha$ = 2) multiplicity modes, $v^{(\alpha)}_0$, as a function of $p_T$ in 10-20% centrality PbPb collisions.

Leading ($\alpha$ = 1) and subleading ($\alpha$ = 2) multiplicity modes, $v^{(\alpha)}_0$, as a function of $p_T$ in 20-30% centrality PbPb collisions.

Leading ($\alpha$ = 1) and subleading ($\alpha$ = 2) multiplicity modes, $v^{(\alpha)}_0$, as a function of $p_T$ in 30-40% centrality PbPb collisions.

Leading ($\alpha$ = 1) and subleading ($\alpha$ = 2) multiplicity modes, $v^{(\alpha)}_0$, as a function of $p_T$ in 40-50% centrality PbPb collisions.

Leading ($\alpha$ = 1) and subleading ($\alpha$ = 2) multiplicity modes, $v^{(\alpha)}_0$, as a function of $p_T$ in 50-60% centrality PbPb collisions.

The $m_{\mathrm{T2}}$ distribution in the multi-jet background VR-F for SR-lowMass. The stacked histograms show the contribution of the non-multi-jet SM backgrounds from MC simulation. The multi-jet contribution is estimated from data using the ABCD method. The hatched bands represent the combined statistical and systematic uncertainties in the sum of the SM backgrounds shown. For illustration, the distributions of the SUSY reference points are also shown as dashed lines. The last bin in the left panels includes the overflow events.

The $E_{\mathrm T}^{\mathrm{miss}}$ distribution in the multi-jet background VR-F for SR-highMass. The stacked histograms show the contribution of the non-multi-jet SM backgrounds from MC simulation. The multi-jet contribution is estimated from data using the ABCD method. The hatched bands represent the combined statistical and systematic uncertainties in the sum of the SM backgrounds shown. For illustration, the distributions of the SUSY reference points are also shown as dashed lines. The last bin in the left panels includes the overflow events.

The $m_{\mathrm{T2}}$ distribution in the multi-jet background VR-F for SR-highMass. The stacked histograms show the contribution of the non-multi-jet SM backgrounds from MC simulation. The multi-jet contribution is estimated from data using the ABCD method. The hatched bands represent the combined statistical and systematic uncertainties in the sum of the SM backgrounds shown. For illustration, the distributions of the SUSY reference points are also shown as dashed lines. The last bin in the left panels includes the overflow events.

The $E_{\mathrm T}^{\mathrm{miss}}$ distribution in the $W$-VR region. The SM backgrounds other than multi-jet production are estimated from MC simulation. The contribution of $W$+jets events is scaled to the fit result. The multi-jet contribution is estimated from data using the $OS--SS$ method. The hatched bands represent the combined statistical and systematic uncertainties of the total SM background. For illustration, the distributions of the SUSY reference points are also shown as dashed lines. The lower panels show the ratio of data to the SM background estimate. The last bin includes the overflow events.

The $m_{\mathrm{T2}}$ distribution in the $W$-VR region. The SM backgrounds other than multi-jet production are estimated from MC simulation. The contribution of $W$+jets events is scaled to the fit result. The multi-jet contribution is estimated from data using the $OS--SS$ method. The hatched bands represent the combined statistical and systematic uncertainties of the total SM background. For illustration, the distributions of the SUSY reference points are also shown as dashed lines. The lower panels show the ratio of data to the SM background estimate. The last bin includes the overflow events.

The $m_{\mathrm{T2}}$ distribution in the $Z$-VR region. The SM backgrounds other than multi-jet production are estimated from MC simulation. The multi-jet contribution is estimated from data using the ABCD method, using CRs obtained with the same technique used for the SRs. The hatched bands represent the combined statistical and systematic uncertainties of the total SM background. For illustration, the distributions of the SUSY reference points are also shown as dashed lines. The lower panels show the ratio of data to the SM background estimate. The last bin includes the overflow events except for the upper left panel.

The $m_{\mathrm{T2}}$ distribution in the Top-VR region. The SM backgrounds other than multi-jet production are estimated from MC simulation. The multi-jet contribution is estimated from data using the ABCD method, using CRs obtained with the same technique used for the SRs. The hatched bands represent the combined statistical and systematic uncertainties of the total SM background. For illustration, the distributions of the SUSY reference points are also shown as dashed lines. The lower panels show the ratio of data to the SM background estimate. The last bin includes the overflow events except for the upper left panel.

The $m_{\mathrm{T2}}$ distribution in the $WW$-VR region. The SM backgrounds other than multi-jet production are estimated from MC simulation. The multi-jet contribution is negligible and not considered. The hatched bands represent the combined statistical and systematic uncertainties of the total SM background. For illustration, the distributions of the SUSY reference points are also shown as dashed lines. The lower panels show the ratio of data to the SM background estimate. The last bin includes the overflow events except for the upper left panel.

The $m_{\mathrm{T2}}$ distribution in the $ZZ$-VR region. The SM backgrounds other than multi-jet production are estimated from MC simulation. The multi-jet contribution is negligible and not considered. The hatched bands represent the combined statistical and systematic uncertainties of the total SM background. For illustration, the distributions of the SUSY reference points are also shown as dashed lines. The lower panels show the ratio of data to the SM background estimate. The last bin includes the overflow events except for the upper left panel.

The $m_{\mathrm{T2}}$ distribution before the $m_{\mathrm{T2}}$ requirement is applied for SR-lowMass region, where the arrow indicates the position of the cut in the signal region. The stacked histograms show the expected SM backgrounds. The multi-jet contribution is estimated from data using the ABCD method. The contributions of multi-jet and $W$+jets events are scaled with the corresponding normalisation factors. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distributions of the SUSY reference points are also shown as dashed lines. The lower panels show the ratio of data to the total SM background estimate. The last bin includes the overflow events.

The $m_{\mathrm{T2}}$ distribution before the $m_{\mathrm{T2}}$ requirement is applied for SR-highMass region, where the arrow indicates the position of the cut in the signal region. The stacked histograms show the expected SM backgrounds. The multi-jet contribution is estimated from data using the ABCD method. The contributions of multi-jet and $W$+jets events are scaled with the corresponding normalisation factors. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distributions of the SUSY reference points are also shown as dashed lines. The lower panels show the ratio of data to the total SM background estimate. The last bin includes the overflow events.

Observed exclusion contours in chargino pair production model.

Expected exclusion contours in chargino pair production model.

Observed exclusion contours in chargino chargino and chargino neutralino production model.

Expected exclusion contours in chargino chargino and chargino neutralino production model.

Observed upper limits on the model cross-section in units of pb as a function of the chargino and neutralino masses in chargino chargino pair production.

Observed upper limits on the model cross-section in units of pb as a function of the chargino and neutralino masses in chargino chargino and chargino neutralino pair production.

Best signal region used in chargino chargino and chargino neutralino pair production, H is corresponding to SR-highMass and L is SR-lowMass.

Observed CLs significance in variable-x model of chargino chargino pair production for compressed mass scenario.

Expected CLs significance in variable-x model of chargino chargino pair production for compressed mass scenario.

Observed CLs significance in variable-x model of chargino chargino pair production for large mass splitting scenario.

Expected CLs significance in variable-x model of chargino chargino pair production for large mass splitting scenario.

Observed CLs significance in variable-x model of chargino chargino and chargino neutralino pair production for compressed mass scenario.

Expected CLs significance in variable-x model of chargino chargino and chargino neutralino pair production for compressed mass scenario.

Observed CLs significance in variable-x model of chargino chargino and chargino neutralino pair production for large mass splitting scenario.

Expected CLs significance in variable-x model of chargino chargino and chargino neutralino pair production for large mass splitting scenario.

Acceptance in SR-lowMass for CHARGINO1 NEUTRALINO2 production.

Acceptance in SR-highMass for CHARGINO1 NEUTRALINO2 production.

Acceptance in SR-highMass for CHARGINO1 CHARGINO1 production.

Efficiency in SR-lowMass for CHARGINO1 NEUTRALINO2 production.

Efficiency in SR-highMass for CHARGINO1 NEUTRALINO2 production.

Efficiency in SR-highMass for CHARGINO1 CHARGINO1 production.

Cut flow for the reference point 1 (CHARGINO1 NEUTRALINO2 production) in SR-lowMass. The column labelled $N_{raw}$ shows the results for the generated number of events, while $N_{weighted}$ includes all correction factors applied to simulation, and is normalised to 36.1 fb$^{-1}$. The quoted uncertainties are statistical only. At the step ``at least two medium tau candidates, matched to trigger objects' the following requirements are applied: the event is recorded using either the asymmetric di-tau trigger or the di-tau+$E_{\mathrm T}^{\mathrm{miss}}$ trigger, and the two matched tau candidates must be of medium quality. If the event has been selected by the asymmetric di-tau trigger, the two tau candidates are required to have ${p}_{\mathrm{T}, \tau_1}>$ 95 GeV and ${p}_{\mathrm{T}, \tau_2}>$ 65 GeV. If the event has been selected by the di-tau+$E_{\mathrm T}^{\mathrm{miss}}$ trigger, the two tau candidates are required to have ${p}_{\mathrm{T}, \tau_1}>$ 50 GeV, ${p}_{\mathrm{T}, \tau_2}>$ 40 GeV, and $E_{\mathrm T}^{\mathrm{miss}}$ > 150 GeV is required.}

Cut flow for the reference point 2 (CHARGINO1 CHARGINO1 production) in SR-highMass. The column labelled $N_{raw}$ shows the results for the generated number of events, while $N_{weighted}$ includes all correction factors applied to simulation, and is normalised to 36.1 fb$^{-1}$. The quoted uncertainties are statistical only. At the step ``at least two medium tau candidates, matched to trigger objects' the following requirements are applied: the event is recorded using either the asymmetric di-tau trigger or the di-tau+$E_{\mathrm T}^{\mathrm{miss}}$ trigger, and the two matched tau candidates must be of medium quality. If the event has been selected by the asymmetric di-tau trigger, the two tau candidates are required to have ${p}_{\mathrm{T}, \tau_1}>$ 95 GeV and ${p}_{\mathrm{T}, \tau_2}>$ 65 GeV. If the event has been selected by the di-tau+$E_{\mathrm T}^{\mathrm{miss}}$ trigger, the two tau candidates are required to have ${p}_{\mathrm{T}, \tau_1}>$ 50 GeV, ${p}_{\mathrm{T}, \tau_2}>$ 40 GeV, and $E_{\mathrm T}^{\mathrm{miss}}$ > 150 GeV is required.}