Three-body selection. Distributions of $M_{\Delta}^R$ in (a,b) $SR_{W}^{3-body}$ and (c,d) $SR_{T}^{3-body}$ for (left) same-flavour and (right) different-flavour events satisfying the selection criteria of the given SR, except the one for the presented variable, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack. ''Others'' includes contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$ processes. 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 in the upper panels indicate the signal region selection criteria. The bottom panels show the ratio of the observed data to the total SM background prediction, with hatched bands representing the total uncertainty in the background prediction; red arrows show data outside the vertical-axis range.

Three-body selection. Distributions of $M_{\Delta}^R$ in (a,b) $SR_{W}^{3-body}$ and (c,d) $SR_{T}^{3-body}$ for (left) same-flavour and (right) different-flavour events satisfying the selection criteria of the given SR, except the one for the presented variable, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack. ''Others'' includes contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$ processes. 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 in the upper panels indicate the signal region selection criteria. The bottom panels show the ratio of the observed data to the total SM background prediction, with hatched bands representing the total uncertainty in the background prediction; red arrows show data outside the vertical-axis range.

Three-body selection. Distributions of $M_{\Delta}^R$ in (a,b) $SR_{W}^{3-body}$ and (c,d) $SR_{T}^{3-body}$ for (left) same-flavour and (right) different-flavour events satisfying the selection criteria of the given SR, except the one for the presented variable, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack. ''Others'' includes contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$ processes. 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 in the upper panels indicate the signal region selection criteria. The bottom panels show the ratio of the observed data to the total SM background prediction, with hatched bands representing the total uncertainty in the background prediction; red arrows show data outside the vertical-axis range.

Four-body selection. (a) distributions of $E_{T}^{miss}$ in $SR^{4-body}_{Small\,\Delta m}$ and (b) distribution of $R_{2\ell 4j}$ in $SR^{4-body}_{Large\,\Delta m}$ for events satisfying the selection criteria of the given SR, except the one for the presented variable, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack. ''Others'' includes contributions from $VVV$, $t\bar{t} t$, $t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$ processes. 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 in the upper panel indicate the signal region selection criteria. The bottom panels show the ratio of the observed data to the total SM background prediction, with hatched bands representing the total uncertainty in the background prediction; red arrows show data outside the vertical-axis range.

Four-body selection. (a) distributions of $E_{T}^{miss}$ in $SR^{4-body}_{Small\,\Delta m}$ and (b) distribution of $R_{2\ell 4j}$ in $SR^{4-body}_{Large\,\Delta m}$ for events satisfying the selection criteria of the given SR, except the one for the presented variable, after the background fit. The contributions from all SM backgrounds are shown as a histogram stack. ''Others'' includes contributions from $VVV$, $t\bar{t} t$, $t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$ processes. 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 in the upper panel indicate the signal region selection criteria. The bottom panels show the ratio of the observed data to the total SM background prediction, with hatched bands representing the total uncertainty in the background prediction; red arrows show data outside the vertical-axis range.

Exclusion limit contour (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, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the expected limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits 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. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.

Exclusion limit contour (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, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the expected limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits 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. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.

Exclusion limit contour (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, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the expected limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits 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. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.

Exclusion limit contour (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, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the Observed limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits 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. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.

Exclusion limit contour (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, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the expected limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits 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. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.

Exclusion limit contour (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, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the expected limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits 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. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.

Exclusion limit contour (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, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the expected limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits 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. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.

Exclusion limit contour (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, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the expected limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits 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. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.

Exclusion limit contour (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, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the expected limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits 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. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.

Exclusion limit contour (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, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the expected limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits 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. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.

Exclusion limit contour (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, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the expected limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits 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. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.

Exclusion limit contour (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, in the (a) $m(\tilde{t}_1)$--$m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{t}_1)$--$\Delta m(\tilde{t}_1,\tilde{\chi}_1^0)$ planes. The dashed lines and the shaded bands are the expected limits and their $\pm1\sigma$ uncertainties. The thick solid lines are the observed limits 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. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty.

Exclusion limits for (a) $t\bar{t} + \phi $ scalar and (b) $t\bar{t} + a $ pseudoscalar models as a function of the mediator mass for a DM particle mass of $m(\chi)=1$ GeV. The limits are calculated at 95% CL and are expressed in terms of the ratio of the excluded cross-section to the nominal cross-section for a coupling assumption of $g = g_q = g_{\chi} = 1$. The solid (dashed) lines shows the observed (expected) exclusion limits.

Exclusion limits for (a) $t\bar{t} + \phi $ scalar and (b) $t\bar{t} + a $ pseudoscalar models as a function of the mediator mass for a DM particle mass of $m(\chi)=1$ GeV. The limits are calculated at 95% CL and are expressed in terms of the ratio of the excluded cross-section to the nominal cross-section for a coupling assumption of $g = g_q = g_{\chi} = 1$. The solid (dashed) lines shows the observed (expected) exclusion limits.

Exclusion limits for (a) $t\bar{t} + \phi $ scalar and (b) $t\bar{t} + a $ pseudoscalar models as a function of the mediator mass for a DM particle mass of $m(\chi)=1$ GeV. The limits are calculated at 95% CL and are expressed in terms of the ratio of the excluded cross-section to the nominal cross-section for a coupling assumption of $g = g_q = g_{\chi} = 1$. The solid (dashed) lines shows the observed (expected) exclusion limits.

Exclusion limits for (a) $t\bar{t} + \phi $ scalar and (b) $t\bar{t} + a $ pseudoscalar models as a function of the mediator mass for a DM particle mass of $m(\chi)=1$ GeV. The limits are calculated at 95% CL and are expressed in terms of the ratio of the excluded cross-section to the nominal cross-section for a coupling assumption of $g = g_q = g_{\chi} = 1$. The solid (dashed) lines shows the observed (expected) exclusion limits.

Two-body selection. Background fit results for $\mathrm{CR}^{\mathrm{2-body}}_{t\bar{t}}$, $\mathrm{CR}^{\mathrm{2-body}}_{t\bar{t}Z}$, $\mathrm{VR}^{\mathrm{2-body}}_{t\bar{t}, DF}$, $\mathrm{VR}^{\mathrm{2-body}}_{t\bar{t}, SF}$ and $\mathrm{VR}^{\mathrm{2-body}}_{t\bar{t} Z}$. ''Others'' includes contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$ processes. Combined statistical and systematic uncertainties are given. Entries marked `--' indicate a negligible background contribution (less than 0.001 events). The individual uncertainties can be correlated, and do not necessarily add up in quadrature to the total background uncertainty.

Three-body selection. Background fit results for $\mathrm{CR}^{\mathrm{3-body}}_{t\bar{t}}$, $\mathrm{CR}^{\mathrm{3-body}}_{VV}$, $\mathrm{CR}^{\mathrm{2-body}}_{t\bar{t}Z}$, $\mathrm{VR}^{\mathrm{3-body}}_{VV}$, $\mathrm{VR(1)}^{\mathrm{3-body}}_{t\bar{t}}$ and $\mathrm{VR(2)}^{\mathrm{3-body}}_{t\bar{t}}$. ''Others'' includes contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$ processes. Combined statistical and systematic uncertainties are given. Entries marked `--' indicate a negligible background contribution (less than 0.001 events). The individual uncertainties can be correlated, and do not necessarily add up in quadrature to the total background uncertainty.

Four-body selection. Background fit results for $\mathrm{CR}^{\mathrm{4-body}}_{t\bar{t}}$,$\mathrm{CR}^{\mathrm{4-body}}_{VV}$, $\mathrm{VR}^{\mathrm{4-body}}_{t\bar{t}}$, $VR^{4-body}_{VV}$ and $\mathrm{VR}^{\mathrm{4-body}}_{VV,lll}$. The ''Others'' category contains the contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$. Combined statistical and systematic uncertainties are given. Entries marked `--' indicate a negligible background contribution (less than 0.001 events). The individual uncertainties can be correlated, and do not necessarily add up in quadrature to the total background uncertainty.

Two-body selection. Background fit results for the different-flavour leptons binned SRs. The ''Others'' category contains the contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$. Combined statistical and systematic uncertainties are given. Entries marked `--' indicate a negligible background contribution (less than 0.001 events). The individual uncertainties can be correlated, and do not necessarily add up in quadrature to the total background uncertainty.

Two-body selection. Background fit results for the same-flavour leptons binned SRs. The ''Others'' category contains the contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$. Combined statistical and systematic uncertainties are given. The individual uncertainties can be correlated, and do not necessarily add up in quadrature to the total background uncertainty.

Three-body selection. Observed event yields and background fit results for the three-body selection SRs. The ''Others'' category contains contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$. Combined statistical and systematic uncertainties are given. Entries marked `--' indicate a negligible background contribution (less than 0.001 events). The individual uncertainties can be correlated, and do not necessarily add up in quadrature to the total background uncertainty.

Four-body selection. Observed event yields and background fit results for SR$^{\mathrm{4-body}}_{\mathrm{Small}\,\Delta m}$ and SR$^{\mathrm{4-body}}_{\mathrm{Large}\,\Delta m}$. The ''Others'' category contains the contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$. Combined statistical and systematic uncertainties are given. The individual uncertainties can be correlated, and do not necessarily add up in quadrature to the total background uncertainty.

Exclusion limits contours (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}^0_1$ with 100% branching ratio in $\tilde{t}_1--\tilde{\chi}^0_1$ masses planes. The dashed lines and the shaded bands are the expected limit and its $\pm 1\sigma$ uncertainty. The thick solid lines are the observed limits 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. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The exclusion limits contours for the two-body, three-body and four-body selections are respectively shown in blue, green and red.

Exclusion limits contours (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}^0_1$ with 100% branching ratio in $\tilde{t}_1--\tilde{\chi}^0_1$ masses planes. The dashed lines and the shaded bands are the expected limit and its $\pm 1\sigma$ uncertainty. The thick solid lines are the observed limits 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. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The exclusion limits contours for the two-body, three-body and four-body selections are respectively shown in blue, green and red.

Exclusion limit contour (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, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty. The thick solid lines are the observed limits 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. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.

Exclusion limit contour (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, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty. The thick solid lines are the observed limits 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. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.

Exclusion limit contour (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, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty. The thick solid lines are the observed limits 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. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.

Exclusion limit contour (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, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty. The thick solid lines are the observed limits 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. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.

Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b W \tilde{\chi}_1^0$ with 100% branching ratio, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty. The thick solid lines are the observed limits 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. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.

Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b W \tilde{\chi}_1^0$ with 100% branching ratio, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty. The thick solid lines are the observed limits 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. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.

Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b W \tilde{\chi}_1^0$ with 100% branching ratio, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty. The thick solid lines are the observed limits 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. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm 1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.

Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b W \tilde{\chi}_1^0$ with 100% branching ratio, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty. The thick solid lines are the observed limits 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. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.

Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b l \nu \tilde{\chi}_1^0$ with 100% branching ratio, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty. The thick solid lines are the observed limits 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. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.

Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b l \nu \tilde{\chi}_1^0$ with 100% branching ratio, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty. The thick solid lines are the observed limits 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. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.

Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b l \nu \tilde{\chi}_1^0$ with 100% branching ratio, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty.The thick solid lines are the observed limits 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. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.

Exclusion limit contour (95% CL) for a simplified model assuming $\tilde{t}_1$ pair production, decaying via $\tilde{t}_1 \rightarrow b l \nu \tilde{\chi}_1^0$ with 100% branching ratio, in $\tilde{t}_1$--$\tilde{\chi}_1^0$ masses plane. The dashed lines and the shaded bands are the expected limit and its $\pm1\sigma$ uncertainty.The thick solid lines are the observed limits 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. The dotted lines show the effect on the observed limit when varying the signal cross-section by $\pm1\sigma$ of the theoretical uncertainty. The observed (a) and expected (b) CLs values are respectively shown.

Exclusion limits for (a) $t\bar{t} + \phi $ scalar and (b) $t\bar{t} + a $ pseudoscalar models as a function of the DM particle mass for a mediator mass of 10 GeV. The limits are calculated at 95% CL and are expressed in terms of the ratio of the excluded cross-section to the nominal cross-section for a coupling assumption of $g = g_q = g_{\chi} = 1$. The solid (dashed) lines shows the observed (expected) exclusion limits.

Exclusion limits for (a) $t\bar{t} + \phi $ scalar and (b) $t\bar{t} + a $ pseudoscalar models as a function of the DM particle mass for a mediator mass of 10 GeV. The limits are calculated at 95% CL and are expressed in terms of the ratio of the excluded cross-section to the nominal cross-section for a coupling assumption of $g = g_q = g_{\chi} = 1$. The solid (dashed) lines shows the observed (expected) exclusion limits.

Exclusion limits for (a) $t\bar{t} + \phi $ scalar and (b) $t\bar{t} + a $ pseudoscalar models as a function of the DM particle mass for a mediator mass of 10 GeV. The limits are calculated at 95% CL and are expressed in terms of the ratio of the excluded cross-section to the nominal cross-section for a coupling assumption of $g = g_q = g_{\chi} = 1$. The solid (dashed) lines shows the observed (expected) exclusion limits.

Exclusion limits for (a) $t\bar{t} + \phi $ scalar and (b) $t\bar{t} + a $ pseudoscalar models as a function of the DM particle mass for a mediator mass of 10 GeV. The limits are calculated at 95% CL and are expressed in terms of the ratio of the excluded cross-section to the nominal cross-section for a coupling assumption of $g = g_q = g_{\chi} = 1$. The solid (dashed) lines shows the observed (expected) exclusion limits.

Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.

Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.

Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.

Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.

Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.

Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.

Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.

Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.

Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.

Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.

Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.

Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.

Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.

Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.

Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.

Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.

Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.

Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.

Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.

Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.

Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.

Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.

Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.

Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.

Two-body selection efficiency (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.

Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.

Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.

Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.

Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.

Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.

Two-body selection efficiency (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.

Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.

Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.

Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.

Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.

Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.

Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.

Two-body selection efficiency (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.

Three-body selection efficiency (a) SR-DF$^{3-body}_{t}$, (b) SR-SF$^{3-body}_{t}$, (c) SR-DF$^{3-body}_{W}$, (d) SR-SF$^{3-body}_{W}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Three-body selection efficiency (a) SR-DF$^{3-body}_{t}$, (b) SR-SF$^{3-body}_{t}$, (c) SR-DF$^{3-body}_{W}$, (d) SR-SF$^{3-body}_{W}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Three-body selection efficiency (a) SR-DF$^{3-body}_{t}$, (b) SR-SF$^{3-body}_{t}$, (c) SR-DF$^{3-body}_{W}$, (d) SR-SF$^{3-body}_{W}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Three-body selection efficiency (a) SR-DF$^{3-body}_{t}$, (b) SR-SF$^{3-body}_{t}$, (c) SR-DF$^{3-body}_{W}$, (d) SR-SF$^{3-body}_{W}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Four-body selection Efficiency (a) SR$^{4-body}_{Small \Delta m}$ , (b) $SR^{4-body}_{Large \Delta m}$ for a simplified model assuming $\tilde{t}_1$ pair production.

Four-body selection Efficiency (a) SR$^{4-body}_{Small \Delta m}$ , (b) $SR^{4-body}_{Large \Delta\ m}$ for a simplified model assuming $\tilde{t}_1$ pair production.

Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.

Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.

Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.

Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.

Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.

Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.

Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} +\phi$ pair production.

Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ t \tilde{t} +\phi$ pair production.

Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ t \tilde{t} +\phi$ pair production.

Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ t \tilde{t} +\phi$ pair production.

Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ t \tilde{t} +\phi$ pair production.

Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $ t \tilde{t} +\phi$ pair production.

Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.

Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.

Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.

Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.

Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.

Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.

Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + \phi$ pair production.

Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.

Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.

Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.

Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.

Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.

Two-body selection acceptance (a) SR-DF$^{2-body}_{[110,120)}$, (b) SR-DF1$^{2-body}_{[120,140)}$, (c) SR-DF2$^{2-body}_{[140,160)}$, (d) SR-DF3$^{2-body}_{[160,180)}$, (e) SR-DF4$^{2-body}_{[180,220)}$, (f) SR-DF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.

Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming t \tilde{t} + a$ pair production.

Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.

Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.

Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.

Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.

Two-body selection acceptance (a) SR-SF$^{2-body}_{[110,120)}$, (b) SR-SF1$^{2-body}_{[120,140)}$, (c) SR-SF2$^{2-body}_{[140,160)}$, (d) SR-SF3$^{2-body}_{[160,180)}$, (e) SR-SF4$^{2-body}_{[180,220)}$, (f) SR-SF5$^{2-body}_{[220,\infty)}$ for a simplified model assuming $t \tilde{t} + a$ pair production.

Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Two-body selection acceptance (a) $SR^{2-body}_{[110,\infty)}$ , (b) $SR^{2-body}_{[120,\infty)}$ , (c) $SR^{2-body}_{[140,\infty)}$ , (d) $SR^{2-body}_{[160,\infty)}$ , (e) $SR^{2-body}_{[180,\infty)}$ , (f) $SR^{2-body}_{[200,\infty)}$ , (g) $SR^{2-body}_{[220,\infty)}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Three-body selection acceptance (a) SR-DF$^{3-body}_{t}$, (b) SR-SF$^{3-body}_{t}$, (c) SR-DF$^{3-body}_{W}$, (d) SR-SF$^{3-body}_{W}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Three-body selection acceptance (a) SR-DF$^{3-body}_{t}$, (b) SR-SF$^{3-body}_{t}$, (c) SR-DF$^{3-body}_{W}$, (d) SR-SF$^{3-body}_{W}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Three-body selection acceptance (a) SR-DF$^{3-body}_{t}$, (b) SR-SF$^{3-body}_{t}$, (c) SR-DF$^{3-body}_{W}$, (d) SR-SF$^{3-body}_{W}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Three-body selection acceptance (a) SR-DF$^{3-body}_{t}$, (b) SR-SF$^{3-body}_{t}$, (c) SR-DF$^{3-body}_{W}$, (d) SR-SF$^{3-body}_{W}$ for a simplified model assuming $ \tilde{t}_1$ pair production.

Four-body selection acceptance (a) SR$^{4-body}_{Small \Delta m}$ , (b) $SR^{4-body}_{Large \Delta m}$ for a simplified model assuming $\tilde{t}_1$ pair production.

Four-body selection acceptance (a) SR$^{4-body}_{Small \Delta m}$ , (b) $SR^{4-body}_{Large \Delta m}$ for a simplified model assuming $\tilde{t}_1$ pair production.

Two-body selection The numbers indicate the observed upper limits on the signal strenght for (a) a simplified model assuming $\tilde{t}_1$ pair production, (b) for $t\tilde{t} + a $ pseudoscalar models, (c) for $t\tilde{t} + \phi $ scalar models. In Figure (a), the red line corresponds to the observed limit.

Two-body selection The numbers indicate the observed upper limits on the signal strenght for (a) a simplified model assuming $\tilde{t}_1$ pair production, (b) for $t\tilde{t} + a $ pseudoscalar models, (c) for $t\tilde{t} + \phi $ scalar models. In Figure (a), the red line corresponds to the observed limit.

Two-body selection The numbers indicate the observed upper limits on the signal strenght for (a) a simplified model assuming $\tilde{t}_1$ pair production, (b) for $t\tilde{t} + a $ pseudoscalar models, (c) for $t\tilde{t} + \phi $ scalar models. In Figure (a), the red line corresponds to the observed limit.

Three-body selection The numbers indicate the upper limits on the signal strenght for a simplified model assuming $\tilde{t}_1$ pair production. For comparison, the red line corresponds to the observed limit.

Four-body selection The numbers indicate the upper limits on the signal strenght for a simplified model assuming $\tilde{t}_1$ pair production. For comparison, the red line corresponds to the observed limit.

Two-body selection The numbers indicate the upper limits on the signal cross-section for (a) a simplified model assuming $\tilde{t}_1$ pair production, (b) for $t\tilde{t} + a $ pseudoscalar models, (c) for $t\tilde{t} + \phi $ scalar models. In Figure (a), the red line corresponds to the observed limit.

Two-body selection The numbers indicate the upper limits on the signal cross-section for (a) a simplified model assuming $\tilde{t}_1$ pair production, (b) for $t\tilde{t} + a $ pseudoscalar models, (c) for $t\tilde{t} + \phi $ scalar models. In Figure (a), the red line corresponds to the observed limit.

Two-body selection The numbers indicate the upper limits on the signal cross-section for (a) a simplified model assuming $\tilde{t}_1$ pair production, (b) for $t\tilde{t} + a $ pseudoscalar models, (c) for $t\tilde{t} + \phi $ scalar models. In Figure (a), the red line corresponds to the observed limit.

Three-body selection The numbers indicate the upper limits on the signal cross-section for a simplified model assuming $\tilde{t}_1$ pair production. For comparison, the red line corresponds to the observed limit.

Four-body selection The numbers indicate the upper limits on the signal cross-section for a simplified model assuming $\tilde{t}_1$ pair production. For comparison, the red line corresponds to the observed limit.

Two-body selection. Background fit results for the $inclusive$ SRs. The Others category contains the contributions from $VVV$, $t\bar{t} t$, $t\bar{t}t\bar{t}$, $t\bar{t} W$, $t\bar{t} WW$, $t\bar{t} WZ$, $t\bar{t} H$, and $tZ$. Combined statistical and systematic uncertainties are given. Note that the individual uncertainties can be correlated, and do not necessarily add up quadratically to the total background uncertainty.

Cut flow for the simplified signal model $\tilde{t}_1 \rightarrow t^{(*)}\tilde{\chi}^0_1$ with $m(\tilde{t}_1)=600~ GeV$ and $m(\tilde{\chi}^0_1)=400~ GeV$ in the SRs for the two-body selection. The number of events is normalized to the cross-section and to an integrated luminosity of $139~fb^{-1}$.

Cut flow for the scalar signal model $t\bar{t} + \phi $ with $m(\phi)=150~ GeV$ and $m(\chi)=1~ GeV$ in the SRs for the two-body selection. The number of events is normalized to the cross-section and to an integrated luminosity of $139~fb^{-1}$.

Cut flow for the pseudoscalar signal model $t\bar{t} + a $ with $m(a)=150~ GeV$ and $m(\chi)=1~ GeV$ in the SRs for the two-body selection. The number of events is normalized to the cross-section and to an integrated luminosity of $139~fb^{-1}$.

Cut flow for the simplified signal model $\tilde{t}_1 \rightarrow bW\tilde{\chi}^0_1$ with $m(\tilde{t}_1)=550~ GeV$ and $m(\tilde{\chi}^0_1)=385~ GeV$ in the SRs for the three-body selection. The number of events is normalized to the cross-section and to an integrated luminosity of $139~fb^{-1}$.

Cut flow for the simplified signal model $\tilde{t}_1 \rightarrow bW\tilde{\chi}^0_1$ with $m(\tilde{t}_1)=550~ GeV$ and $m(\tilde{\chi}^0_1)=400~ GeV$ in the SRs for the three-body selection. The number of events is normalized to the cross-section and to an integrated luminosity of $139~fb^{-1}$.

Cut flow for the simplified signal model $\tilde{t}_1 \rightarrow bW\tilde{\chi}^0_1$ with $m(\tilde{t}_1)=550~ GeV$ and $m(\tilde{\chi}^0_1)=430~ GeV$ in the SRs for the three-body selection. The number of events is normalized to the cross-section and to an integrated luminosity of $139~fb^{-1}$.

Cut flow for the simplified signal model $\tilde{t}_1 \rightarrow bW\tilde{\chi}^0_1$ with $m(\tilde{t}_1)=550~ GeV$ and $m(\tilde{\chi}^0_1)=460~ GeV$ in the SRs for the three-body selection. The number of events is normalized to the cross-section and to an integrated luminosity of $139~fb^{-1}$.

Cut flow for the simplified signal model $\tilde{t}_1 \rightarrow b l \nu \tilde{\chi}^0_1$ with $m(\tilde{t}_1)=400~ GeV$ and $m(\tilde{\chi}^0_1)=380~ GeV$ in the SRs for the four-body selection. The number of events is normalized to the cross-section and to an integrated luminosity of $139~fb^{-1}$.

Cut flow for the simplified signal model $\tilde{t}_1 \rightarrow b l \nu \tilde{\chi}^0_1$ with $m(\tilde{t}_1)=460~ GeV$ and $m(\tilde{\chi}^0_1)=415~ GeV$ in the SRs for the four-body selection. The number of events is normalized to the cross-section and to an integrated luminosity of $139~fb^{-1}$.

Cut flow for the simplified signal model $\tilde{t}_1 \rightarrow b l \nu \tilde{\chi}^0_1$ with $m(\tilde{t}_1)=400~ GeV$ and $m(\tilde{\chi}^0_1)=320~ GeV$ in the SRs for the four-body selection. The number of events is normalized to the cross-section and to an integrated luminosity of $139~fb^{-1}$.

Distribution of $S$, which is one of the discriminating variables used to define the $2\ell^{sc}$ SRs. The events are selected with the preselection requirements listed in Table 4 in the paper. The data (dots) are compared with the expected contributions from the relevant background sources (histograms). The expected signal distributions for $m_{H^{\pm\pm}} = 300~GeV$ are also shown, scaled to the observed number of events. The last bin includes overflows.

Distribution of $E_{T}^{miss}$, which is one of the discriminating variables used to define the $3\ell$ SRs. The events are selected with the preselection requirements listed in Table 4 in the paper. The data (dots) are compared with the expected contributions from the relevant background sources (histograms). The expected signal distributions for $m_{H^{\pm\pm}} = 300~GeV$ are also shown, scaled to the observed number of events. The last bin includes overflows.

Distribution of $\Delta R_{\ell^{\pm}\ell^{\pm}}$, which is one of the discriminating variables used to define the $3\ell$ SRs. The events are selected with the preselection requirements listed in Table 4 in the paper. The data (dots) are compared with the expected contributions from the relevant background sources (histograms). The expected signal distributions for $m_{H^{\pm\pm}} = 300~GeV$ are also shown, scaled to the observed number of events. The last bin includes overflows.

Distribution of $m_{x\ell}$ ($x$=3), which is one of the discriminating variables used to define the $3\ell$ SRs. The events are selected with the preselection requirements listed in Table 4 in the paper. The data (dots) are compared with the expected contributions from the relevant background sources (histograms). The expected signal distributions for $m_{H^{\pm\pm}} = 300~GeV$ are also shown, scaled to the observed number of events. The last bin includes overflows.

Distribution of $p_{T}^{leading jet}$, which is one of the discriminating variables used to define the $3\ell$ SRs. The events are selected with the preselection requirements listed in Table 4 in the paper. The data (dots) are compared with the expected contributions from the relevant background sources (histograms). The expected signal distributions for $m_{H^{\pm\pm}} = 300~GeV$ are also shown, scaled to the observed number of events. The last bin includes overflows.

Distribution of $E_{T}^{miss}$, which is one of the discriminating variables used to define the $4\ell$ SRs. The events are selected with the preselection requirements listed in Table 4 in the paper. The data (dots) are compared with the expected contributions from the relevant background sources (histograms). The expected signal distributions for $m_{H^{\pm\pm}} = 300~GeV$ are also shown, scaled to the observed number of events. The last bin includes overflows.

Distribution of $\Delta R_{\ell^{\pm}\ell^{\pm}}^{min}$, which is one of the discriminating variables used to define the $4\ell$ SRs. The events are selected with the preselection requirements listed in Table 4 in the paper. The data (dots) are compared with the expected contributions from the relevant background sources (histograms). The expected signal distributions for $m_{H^{\pm\pm}} = 300~GeV$ are also shown, scaled to the observed number of events. The last bin includes overflows.

Distribution of $m_{x\ell}$ ($x$=4), which is one of the discriminating variables used to define the $4\ell$ SRs. The events are selected with the preselection requirements listed in Table 4 in the paper. The data (dots) are compared with the expected contributions from the relevant background sources (histograms). The expected signal distributions for $m_{H^{\pm\pm}} = 300~GeV$ are also shown, scaled to the observed number of events. The last bin includes overflows.

Distribution of $p_{T}^{\ell_{1}}$, which is one of the discriminating variables used to define the $4\ell$ SRs. The events are selected with the preselection requirements listed in Table 4 in the paper. The data (dots) are compared with the expected contributions from the relevant background sources (histograms). The expected signal distributions for $m_{H^{\pm\pm}} = 300~GeV$ are also shown, scaled to the observed number of events. The last bin includes overflows.

Contributions from different categories of uncertainties relative to the expected background yields in the defined SRs, as obtained after performing the likelihood ratio test discussed in Section 9 in the paper. The uncertainties are shown for the combination of the individual channels of the $2\ell^{sc}$, $3\ell$ and $4\ell$ SRs. The SRs are indicated along the horizontal axis. In the HEPData entry, the x-axis is simplified for easier visualisation. The first number indicates the sub channel (2:$2\ell^{sc}$, 3:$3\ell$, 4:$4\ell$), while the second number indicates the mass point (2:200, 3:300, 4:400, 5:500).

Data event yields compared with the expected contributions from relevant background sources, for the combination of the individual channels of the $2\ell^{sc}$, $3\ell$ and $4\ell$ SRs. The total uncertainties in the expected event yields are shown as the hatched bands. The SRs are indicated along the horizontal axis. In the HEPData entry, the x-axis is simplified for easier visualisation. The first number indicates the sub channel (2:$2\ell^{sc}$, 3:$3\ell$, 4:$4\ell$), while the second number indicates the mass point (2:200, 3:300, 4:400, 5:500).

The $E_{T}^{miss}$ distribution for the SRs of the $m_{H^{\pm\pm}} = 300~GeV$ signal mass hypothesis, where the selection requirement on $E_{T}^{miss}$ has been removed. In the attached plot, the signals are stacked on top of the backgrounds while individuals contributions of the $2\ell^{sc}$ channel are shown in HEPData. The last bin, isolated by a vertical red dashed line, is inclusive and corresponds to the SR.

The $E_{T}^{miss}$ distribution for the SRs of the $m_{H^{\pm\pm}} = 300~GeV$ signal mass hypothesis, where the selection requirement on $E_{T}^{miss}$ has been removed. In the attached plot, the signals are stacked on top of the backgrounds while individuals contributions of the $3\ell$ channel are shown in HEPData. The last bin, isolated by a vertical red dashed line, is inclusive and corresponds to the SR.

The $E_{T}^{miss}$ distribution for the SRs of the $m_{H^{\pm\pm}} = 300~GeV$ signal mass hypothesis, where the selection requirement on $E_{T}^{miss}$ has been removed. In the attached plot, the signals are stacked on top of the backgrounds while individuals contributions of the $4\ell$ channel are shown in HEPData. The last bin, isolated by a vertical red dashed line, is inclusive and corresponds to the SR.

Observed and expected upper limits of the $H^{\pm\pm}$ pair production cross section times branching fraction at 95% CL obtained from the combination of 2$\ell^{sc}$, 3$\ell$ and 4$\ell$ channels. The region above the observed limit is excluded by the measurement. The bands represent the expected exclusion curves within one and two standard deviations.

The theoretical prediction of Figure 9(a) in the paper.

Observed and expected upper limits of the $H^{\pm\pm}$ and $H^{\pm}$ production cross section times branching fraction at 95% CL obtained from the combination of 2$\ell^{sc}$, 3$\ell$ and 4$\ell$ channels. The region above the observed limit is excluded by the measurement. The bands represent the expected exclusion curves within one and two standard deviations.

The theoretical prediction of Figure 9(b) in the paper.

Data event yields compared with the estimated background in the $m_{H^{\pm\pm}} = 200~GeV$ or $m_{H^{\pm\pm}} = 220~GeV$ SRs. SFOC 0 and SFOC 1,2 refer to the number of same-flavour opposite charge lepton pairs. The total uncertainties in the estimated background yields are shown as the hashed bands. In the HEPData entry, the x-axis is simplified for easier visualisation (1:$e^{\pm}e^{\pm}$, 2:$e^{\pm}\mu^{\pm}$, 3:$\mu^{\pm}\mu^{\pm}$, 4:SFOC 0, 5:SFOC 1,2, 6:$4\ell$).

Data event yields compared with the estimated background in the $m_{H^{\pm\pm}} = 300~GeV$ or $m_{H^{\pm\pm}} = 350~GeV$ SRs. SFOC 0 and SFOC 1,2 refer to the number of same-flavour opposite charge lepton pairs. The total uncertainties in the estimated background yields are shown as the hashed bands. In the HEPData entry, the x-axis is simplified for easier visualisation (1:$e^{\pm}e^{\pm}$, 2:$e^{\pm}\mu^{\pm}$, 3:$\mu^{\pm}\mu^{\pm}$, 4:SFOC 0, 5:SFOC 1,2, 6:$4\ell$).

Data event yields compared with the estimated background in the $m_{H^{\pm\pm}} = 400~GeV$ or $m_{H^{\pm\pm}} = 450~GeV$ SRs. SFOC 0 and SFOC 1,2 refer to the number of same-flavour opposite charge lepton pairs. The total uncertainties in the estimated background yields are shown as the hashed bands. In the HEPData entry, the x-axis is simplified for easier visualisation (1:$e^{\pm}e^{\pm}$, 2:$e^{\pm}\mu^{\pm}$, 3:$\mu^{\pm}\mu^{\pm}$, 4:SFOC 0, 5:SFOC 1,2, 6:$4\ell$).

Data event yields compared with the estimated background in the $m_{H^{\pm\pm}} = 500~GeV$ or $m_{H^{\pm\pm}} = 550~GeV$ or $m_{H^{\pm\pm}} = 600~GeV$ SRs. SFOC 0 and SFOC 1,2 refer to the number of same-flavour opposite charge lepton pairs. The total uncertainties in the estimated background yields are shown as the hashed bands. In the HEPData entry, the x-axis is simplified for easier visualisation (1:$e^{\pm}e^{\pm}$, 2:$e^{\pm}\mu^{\pm}$, 3:$\mu^{\pm}\mu^{\pm}$, 4:SFOC 0, 5:SFOC 1,2, 6:$4\ell$).

Post-fit $m_{T}$ distribution in the SR 4J b-tag N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.

Post-fit $m_{T}$ distribution in the SR 6J b-veto N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.

Post-fit $m_{T}$ distribution in the SR 6J b-tag N-1 region. N-1 refers to all cuts except for the requirement on $m_T$ being applied. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.

Post-fit $m_{eff}$ distribution in the 2J b-tag signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.

Post-fit $m_{eff}$ distribution in the 2J b-veto signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.

Post-fit $m_{eff}$ distribution in the 4J low-x b-tag signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.

Post-fit $m_{eff}$ distribution in the 4J low-x b-veto signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.

Post-fit $m_{eff}$ distribution in the 4J high-x b-tag signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.

Post-fit $m_{eff}$ distribution in the 4J high-x b-veto signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.

Post-fit $m_{eff}$ distribution in the 6J b-tag signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.

Post-fit $m_{eff}$ distribution in the 6J b-veto signal region. Uncertainties include statistical and systematic uncertainties. Including exemplary signal points. The value 9999 is used as a placeholder for infinity.

Observed 95% CL exclusion contours for the gluino one-step x = 1/2 model.

Expected 95% CL exclusion contours for the gluino one-step x = 1/2 model. space.

Observed 95% CL exclusion contours for the gluino one-step variable-x

Expected 95% CL exclusion contours for the gluino one-step variable-x

Observed 95% CL exclusion contours for the squark one-step x = 1/2 model.

Observed 95% CL exclusion contours for the squark one-step x = 1/2 model.

Observed 95% CL exclusion contours for one-flavour schemes in one-step x = 1/2 model.

Observed 95% CL exclusion contours for one-flavour schemes in one-step x = 1/2 model.

Expected 95% CL exclusion contours for the squark one-step variable-x

Expected 95% CL exclusion contours for the squark one-step variable-x

Expected 95% CL exclusion contours for the squark one-flavour schemes in variable-x

Expected 95% CL exclusion contours for the squark one-flavour schemes in variable-x

Upper limits on the signal cross section for simplified model gluino one-step x = 1/2

Upper limits on the signal cross section for simplified model gluino one-step variable-x

Upper limits on the signal cross section for simplified model squark one-step x = 1/2

Upper limits on the signal cross section for simplified model squark one-step variable-x

Upper limits on the signal cross section for simplified model squark one-step x=1/2 in one-flavour schemes

Upper limits on the signal cross section for simplified model squark one-step variable-x in one-flavour schemes

Post-fit $m_{eff}$ distribution in the 2J b-tag validation region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.

Post-fit $m_{eff}$ distribution in the 2J b-veto validation region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.

Post-fit $m_{eff}$ distribution in the 4J b-tag validation region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.

Post-fit $m_{eff}$ distribution in the 4J b-veto validation region. Uncertainties include statistical and systematic uncertainties. The value 9999 is used as a placeholder for infinity.

Post-fit $m_{eff}$ distribution in the 6J b-tag validation region. Uncertainties include statistical and systematic uncertainties.

Post-fit $m_{eff}$ distribution in the 6J b-veto validation region. Uncertainties include statistical and systematic uncertainties.

Event selection cutflow for two representative signal samples for the SR2JBT. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.

Event selection cutflow for two representative signal samples for the SR2JBV. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.

Event selection cutflow for two representative signal samples for the SR4JBT. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.

Event selection cutflow for two representative signal samples for the SR4JBV. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.

Event selection cutflow for two representative signal samples for the SR6JBT. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.

Event selection cutflow for two representative signal samples for the SR6JBV. The gluino, squark, chargino and neutralino masses are reported. Weighted events including statistical uncertainties are shown.

Signal acceptance in SR2J b-Tag bin1 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR2J b-Tag bin2 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR2J b-Tag bin3 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR2J b-Veto bin1 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR2J b-Veto bin2 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR2J b-Veto bin3 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR2J discovery high region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR2J discovery low region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR4Jhx discovery region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR4Jhx b-Tag bin1 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR4Jhx b-Tag bin2 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR4Jhx b-Tag bin3 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR4Jhx b-Veto bin1 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR4Jhx b-Veto bin2 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR4Jhx b-Veto bin3 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR4Jlx discovery region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR4Jlx b-Tag bin1 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR4Jlx b-Tag bin2 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR4Jlx b-Tag bin3 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR4Jlx b-Veto bin1 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR4Jlx b-Veto bin2 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR4Jlx b-Veto bin3 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR6J b-Tag bin1 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR6J b-Tag bin2 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR6J b-Tag bin3 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR6J b-Tag bin4 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR6J b-Veto bin1 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR6J b-Veto bin2 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR6J b-Veto bin3 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR6J b-Veto bin4 region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR6J discovery high region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR6J discovery low region for gluino production one-step x = 1/2 simplified models

Signal acceptance in SR2J b-Tag bin1 region for gluino production one-step variable-x simplified models

Signal acceptance in SR2J b-Tag bin2 region for gluino production one-step variable-x simplified models

Signal acceptance in SR2J b-Tag bin3 region for gluino production one-step variable-x simplified models

Signal acceptance in SR2J b-Veto bin1 region for gluino production one-step variable-x simplified models

Signal acceptance in SR2J b-Veto bin2 region for gluino production one-step variable-x simplified models

Signal acceptance in SR2J b-Veto bin3 region for gluino production one-step variable-x simplified models

Signal acceptance in SR2J discovery high region for gluino production one-step variable-x simplified models

Signal acceptance in SR2J discovery low region for gluino production one-step variable-x simplified models

Signal acceptance in SR4Jhx discovery region for gluino production one-step variable-x simplified models

Signal acceptance in SR4Jhx b-Tag bin1 region for gluino production one-step variable-x simplified models

Signal acceptance in SR4Jhx b-Tag bin2 region for gluino production one-step variable-x simplified models

Signal acceptance in SR4Jhx b-Tag bin3 region for gluino production one-step variable-x simplified models

Signal acceptance in SR4Jhx b-Veto bin1 region for gluino production one-step variable-x simplified models

Signal acceptance in SR4Jhx b-Veto bin2 region for gluino production one-step variable-x simplified models

Signal acceptance in SR4Jhx b-Veto bin3 region for gluino production one-step variable-x simplified models

Signal acceptance in SR4Jlx discovery region for gluino production one-step variable-x simplified models

Signal acceptance in SR4Jlx b-Tag bin1 region for gluino production one-step variable-x simplified models

Signal acceptance in SR4Jlx b-Tag bin2 region for gluino production one-step variable-x simplified models

Signal acceptance in SR4Jlx b-Tag bin3 region for gluino production one-step variable-x simplified models

Signal acceptance in SR4Jlx b-Veto bin1 region for gluino production one-step variable-x simplified models

Signal acceptance in SR4Jlx b-Veto bin2 region for gluino production one-step variable-x simplified models

Signal acceptance in SR4Jlx b-Veto bin3 region for gluino production one-step variable-x simplified models

Signal acceptance in SR6J b-Tag bin1 region for gluino production one-step variable-x simplified models

Signal acceptance in SR6J b-Tag bin2 region for gluino production one-step variable-x simplified models

Signal acceptance in SR6J b-Tag bin3 region for gluino production one-step variable-x simplified models

Signal acceptance in SR6J b-Tag bin4 region for gluino production one-step variable-x simplified models

Signal acceptance in SR6J b-Veto bin1 region for gluino production one-step variable-x simplified models

Signal acceptance in SR6J b-Veto bin2 region for gluino production one-step variable-x simplified models

Signal acceptance in SR6J b-Veto bin3 region for gluino production one-step variable-x simplified models

Signal acceptance in SR6J b-Veto bin4 region for gluino production one-step variable-x simplified models

Signal acceptance in SR6J discovery high region for gluino production one-step variable-x simplified models

Signal acceptance in SR6J discovery low region for gluino production one-step variable-x simplified models

Signal acceptance in SR2J b-Tag bin1 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR2J b-Tag bin2 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR2J b-Tag bin3 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR2J b-Veto bin1 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR2J b-Veto bin2 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR2J b-Veto bin3 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR2J discovery high region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR2J discovery low region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR4Jhx discovery region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR4Jhx b-Tag bin1 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR4Jhx b-Tag bin2 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR4Jhx b-Tag bin3 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR4Jhx b-Veto bin1 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR4Jhx b-Veto bin2 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR4Jhx b-Veto bin3 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR4Jlx discovery region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR4Jlx b-Tag bin1 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR4Jlx b-Tag bin2 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR4Jlx b-Tag bin3 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR4Jlx b-Veto bin1 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR4Jlx b-Veto bin2 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR4Jlx b-Veto bin3 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR6J b-Tag bin1 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR6J b-Tag bin2 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR6J b-Tag bin3 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR6J b-Tag bin4 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR6J b-Veto bin1 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR6J b-Veto bin2 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR6J b-Veto bin3 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR6J b-Veto bin4 region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR6J discovery high region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR6J discovery low region for squark production one-step x = 1/2 simplified models

Signal acceptance in SR2J b-Tag bin1 region for squark production one-step variable-x simplified models

Signal acceptance in SR2J b-Tag bin2 region for squark production one-step variable-x simplified models

Signal acceptance in SR2J b-Tag bin3 region for squark production one-step variable-x simplified models

Signal acceptance in SR2J b-Veto bin1 region for squark production one-step variable-x simplified models

Signal acceptance in SR2J b-Veto bin2 region for squark production one-step variable-x simplified models

Signal acceptance in SR2J b-Veto bin3 region for squark production one-step variable-x simplified models

Signal acceptance in SR2J discovery high region for squark production one-step variable-x simplified models

Signal acceptance in SR2J discovery low region for squark production one-step variable-x simplified models

Signal acceptance in SR4Jhx discovery region for squark production one-step variable-x simplified models

Signal acceptance in SR4Jhx b-Tag bin1 region for squark production one-step variable-x simplified models

Signal acceptance in SR4Jhx b-Tag bin2 region for squark production one-step variable-x simplified models

Signal acceptance in SR4Jhx b-Tag bin3 region for squark production one-step variable-x simplified models

Signal acceptance in SR4Jhx b-Veto bin1 region for squark production one-step variable-x simplified models

Signal acceptance in SR4Jhx b-Veto bin2 region for squark production one-step variable-x simplified models

Signal acceptance in SR4Jhx b-Veto bin3 region for squark production one-step variable-x simplified models

Signal acceptance in SR4Jlx discovery region for squark production one-step variable-x simplified models

Signal acceptance in SR4Jlx b-Tag bin1 region for squark production one-step variable-x simplified models

Signal acceptance in SR4Jlx b-Tag bin2 region for squark production one-step variable-x simplified models

Signal acceptance in SR4Jlx b-Tag bin3 region for squark production one-step variable-x simplified models

Signal acceptance in SR4Jlx b-Veto bin1 region for squark production one-step variable-x simplified models

Signal acceptance in SR4Jlx b-Veto bin2 region for squark production one-step variable-x simplified models

Signal acceptance in SR4Jlx b-Veto bin3 region for squark production one-step variable-x simplified models

Signal acceptance in SR6J b-Tag bin1 region for squark production one-step variable-x simplified models

Signal acceptance in SR6J b-Tag bin2 region for squark production one-step variable-x simplified models

Signal acceptance in SR6J b-Tag bin3 region for squark production one-step variable-x simplified models

Signal acceptance in SR6J b-Tag bin4 region for squark production one-step variable-x simplified models

Signal acceptance in SR6J b-Veto bin1 region for squark production one-step variable-x simplified models

Signal acceptance in SR6J b-Veto bin2 region for squark production one-step variable-x simplified models

Signal acceptance in SR6J b-Veto bin3 region for squark production one-step variable-x simplified models

Signal acceptance in SR6J b-Veto bin4 region for squark production one-step variable-x simplified models

Signal acceptance in SR6J discovery high region for squark production one-step variable-x simplified models

Signal acceptance in SR6J discovery low region for squark production one-step variable-x simplified models

Signal efficiency in SR2J b-Tag bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Tag bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Tag bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Veto bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Veto bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Veto bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J discovery high region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J discovery low region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx discovery region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Tag bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Tag bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Tag bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Veto bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Veto bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Veto bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx discovery region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Tag bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Tag bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Tag bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Veto bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Veto bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Veto bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin4 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin1 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin2 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin3 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin4 region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J discovery high region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J discovery low region for gluino production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Tag bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Tag bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Tag bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Veto bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Veto bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Veto bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J discovery high region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J discovery low region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx discovery region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Tag bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Tag bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Tag bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Veto bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Veto bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Veto bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx discovery region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Tag bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Tag bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Tag bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Veto bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Veto bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Veto bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin4 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin1 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin2 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin3 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin4 region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J discovery high region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J discovery low region for gluino production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Tag bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Tag bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Tag bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Veto bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Veto bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Veto bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J discovery high region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J discovery low region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx discovery region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Tag bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Tag bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Tag bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Veto bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Veto bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Veto bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx discovery region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Tag bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Tag bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Tag bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Veto bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Veto bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Veto bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin4 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin1 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin2 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin3 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin4 region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J discovery high region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J discovery low region for squark production one-step x = 1/2 simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Tag bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Tag bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Tag bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Veto bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Veto bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J b-Veto bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J discovery high region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR2J discovery low region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx discovery region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Tag bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Tag bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Tag bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Veto bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Veto bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jhx b-Veto bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx discovery region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Tag bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Tag bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Tag bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Veto bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Veto bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR4Jlx b-Veto bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Tag bin4 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin1 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin2 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin3 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J b-Veto bin4 region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J discovery high region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Signal efficiency in SR6J discovery low region for squark production one-step variable-x simplified models. The -1 value indicates the truth yields for this point is 0 but the reco yields is not 0

Acceptances on TRUTH level of the DMt samples in the tW1L channel for all bins in the SR. The acceptance is defined as the number of weighted TRUTH events in the SR over the number of expected events without any selections. The maps include all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.

Efficiencies of the DMt samples in the tW2L SR. The efficiency is defined as the number of weighted reconstructed events over the number of weighted TRUTH events in the SR. The maps include all samples in the $m_a - m_H$ plane with $tan\beta = 1$.

Acceptances on TRUTH level of the DMt samples in the tW2L SR. The acceptance is defined as the number of weighted TRUTH events in the SR over the number of expected events without any selections. The maps include all samples in the $m_a - m_H$ plane with $tan\beta = 1$.

Efficiencies of the DMt samples in the tW2L SR. The efficiency is defined as the number of weighted reconstructed events over the number of weighted TRUTH events in the SR. The maps include all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.

Acceptances on TRUTH level of the DMt samples in the tW2L SR. The acceptance is defined as the number of weighted TRUTH events in the SR over the number of expected events without any selections. The maps include all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.

Efficiencies of the DMt samples in the tj1L channel for all bins in the SR. The efficiency is defined as the number of weighted reconstructed events over the number of weighted TRUTH events in the SR. The map includes all used samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.

Acceptances on TRUTH level of the DMt samples in the tj1L channel for all bins in the SR. The acceptance is defined as the number of weighted TRUTH events in the SR over the number of expected events without any selections. The map includes all used samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.

Upper limits on signal strength (excluded cross section over theoretical cross section) of the tW1L analysis considering only DMt signal.

Upper limits on excluded cross sections of the tW1L analysis considering only the DMt signal.

The expected exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming only $tW$+DM contributions, for the tW1L analysis channel.

The observed exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming only $tW$+DM contributions, for the tW1L analysis channel.

Upper limits on signal strength (excluded cross section over theoretical cross section) of the tW1L analysis considering only DMt signal.

Upper limits on excluded cross sections of the tW1L analysis considering only the DMt signal.

The expected exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming only $tW$+DM contributions, for the tW1L analysis channel.

The observed exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming only $tW$+DM contributions, for the tW1L analysis channel.

Upper limits on signal strength (excluded cross section over theoretical cross section) of the tW2L analysis considering only DMt signal.

Upper limits on excluded cross sections of the tW2L analysis considering only the DMt signal.

The expected exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming only $tW$+DM contributions, for the tW2L analysis channel.

The observed exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming only $tW$+DM contributions, for the tW2L analysis channel.

Upper limits on signal strength (excluded cross section over theoretical cross section) of the tW2L analysis considering only DMt signal.

Upper limits on excluded cross sections of the tW2L analysis considering only the DMt signal.

The expected exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming only $tW$+DM contributions, for the tW2L analysis channel.

The observed exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming only $tW$+DM contributions, for the tW2L analysis channel.

Upper limits on signal strength (excluded cross section over theoretical cross section) of the combined tW1L and tW2L analyses considering only the DMt signal.

Upper limits on excluded cross sections of the combined tW1L and tW2L analyses considering only the DMt signal.

The expected exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming only $tW$+DM contributions, for the statistical combination of the tW1L and tW2L analysis channel.

The observed exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming only $tW$+DM contributions, for the statistical combination of the tW1L and tW2L analysis channel.

Upper limits on signal strength (excluded cross section over theoretical cross section) of the combined tW1L and tW2L analyses considering only the DMt signal.

Upper limits on excluded cross sections of the combined tW1L and tW2L analyses considering only the DMt signal.

The expected exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming only $tW$+DM contributions, for the statistical combination of the tW1L and tW2L analysis channel.

The observed exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming only $tW$+DM contributions, for the statistical combination of the tW1L and tW2L analysis channel.

Upper limits on signal strength (excluded cross section over theoretical cross section) of the tW1L analysis considering the DMt$\bar{t}$+DMt signal.

The expected exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the tW1L analysis channel.

The observed exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the tW1L analysis channel.

Upper limits on signal strength (excluded cross section over theoretical cross section) of the tW1L analysis considering the DMt$\bar{t}$+DMt signal.

The expected exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the tW1L analysis channel.

The observed exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the tW1L analysis channel.

Upper limits on signal strength (excluded cross section over theoretical cross section) of the tW2L analysis considering the DMt$\bar{t}$+DMt signal.

The expected exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the tW2L analysis channel.

The observed exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the tW2L analysis channel.

Upper limits on signal strength (excluded cross section over theoretical cross section) of the tW2L analysis considering the DMt$\bar{t}$+DMt signal.

The expected exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the tW2L analysis channel.

The observed exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the tW2L analysis channel.

Upper limits on signal strength (excluded cross section over theoretical cross section) of the combined tW1L and tW2L analyses considering the DMt$\bar{t}$+DMt signal.

The expected exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the statistical combination of the tW1L and tW2L analysis channel.

The observed exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the statistical combination of the tW1L and tW2L analysis channel.

Upper limits on signal strength (excluded cross section over theoretical cross section) of the combined tW1L and tW2L analyses considering the DMt$\bar{t}$+DMt signal.

The expected exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the statistical combination of the tW1L and tW2L analysis channel.

The observed exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the statistical combination of the tW1L and tW2L analysis channel.

Upper limits on signal strength (excluded cross section over theoretical cross section) of the tj1L analysis considering only the DMt signal.

Upper limits on upper limits on excluded cross sections of the tj1L analysis considering only the DMt signal.

The expected and observed cross section exclusion limits as a function of $m_{H^{\pm}}$ in the tj1L analysis channel for signal models with $m_a = 250~GeV$, and $\tan\beta=0.3$. The $\sigma^{}_\mathrm{BSM}$ is the cross section of the $t$-channel DM production process.

The expected and observed cross section exclusion limits as a function of $m_{H^{\pm}}$ in the tj1L analysis channel for signal models with $m_a = 250~GeV$, and $\tan\beta=0.5$. The $\sigma^{}_\mathrm{BSM}$ is the cross section of the $t$-channel DM production process.

Cross sections of the DMt samples in the tW1L channel. The maps include all samples in the $m_a - m_H$ plane with $tan\beta = 1$.

Cross sections of the DMt samples in the tW1L channel. The maps include all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.

Cross sections times branching ratio of the DMt samples in the tW2L channel. The maps include all samples in the $m_a - m_H$ plane with $tan\beta = 1$.

Cross sections times branching ratio of the DMt samples in the tW2L channel. The maps include all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.

Cross sections of the DMt samples in the tj1L channel. The map includes all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.

MC generator filter efficiencies of the DMt samples in the tW1L channel. The maps include all samples in the $m_a - m_H$ plane with $tan\beta = 1$.

MC generator filter efficiencies of the DMt samples in the tW1L channel. The maps include all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.

MC generator filter efficiencies of the DMt samples in the tW2L channel. The maps include all samples in the $m_a - m_H$ plane with $tan\beta = 1$.

MC generator filter efficiencies of the DMt samples in the tW2L channel. The maps include all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.

MC generator filter efficiencies of the DMt samples in the tj1L channel. The map includes all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.

Background-only fit results for the tW1L and tW2L signal regions. The backgrounds which contribute only a small amount (rare processes such as triboson, Higgs boson production processes, $t\bar{t}t\bar{t}$, $t\bar{t}WW$ and non-prompt or misidentified leptons background) are grouped and labelled as ``Others´´. The quoted uncertainties on the fitted SM background include both the statistical and systematic uncertainties.

Background-only fit results for the tj1L signal regions. The backgrounds which contribute only a small amount ($Z$+jets, rare processes such as $tWZ$, triboson, Higgs boson production processes, ,$t\bar{t}t\bar{t}$, $t\bar{t}WW$) are grouped and labelled as ``Others´´. The quoted uncertainties on the fitted SM background include both the statistical and systematic uncertainties.

Cutflow of the weighted events with statistical uncertainties for two DMt samples in all bins of the tW1L channel. The PreSelection includes at least 1 lepton in the event, at least 1 $b$-jet with $p_{\mathrm{T}} > 50~GeV$, $m\mathrm{_{T}^{lep}} > 30~GeV$, $\Delta\phi\mathrm{_{4jets, MET}^{min}} > 0.5$ and $E\mathrm{_{T}^{miss}} > 200~GeV$.

Cutflow of the weighted events with statistical uncertainties for two DMt samples in the tW2L channel. The PreSelection includes at least 2 leptons in the event, at least 1 $b$-jet with $p_{\mathrm{T}} > 40~GeV$, $m_{ll} > 40~GeV$, $m\mathrm{_{T2}} > 40~GeV$, $\Delta\phi\mathrm{_{4jets, MET}^{min}} > 0.5$ and $E\mathrm{_{T}^{miss}} > 200~GeV$.

Cutflow of the weighted events with the statistical uncertainties (except for the first cuts) for two DMt samples in all bins off the tj1L channel. The PreSelection includes at least 1 lepton in the event, at least 1 $b$-jet with $p_{\mathrm{T}} > 50~GeV$, $m\mathrm{_{T}^{lep}} > 30~GeV$, $\Delta\phi\mathrm{_{4jets, MET}^{min}} > 0.5$ and $E\mathrm{_{T}^{miss}} > 200~GeV$.

Upper limits on observed signal cross section, $\sigma_\text{obs}^\text{95}$, where all slepton flavors are mass degenerate (co-NLSP).

Upper limits on observed signal cross section, $\sigma_\text{obs}^\text{95}$, for the selectron signal model. Selectron ($\tilde{e}_{L, R}$) refers to the scalar superpartners of left- and right-handed electrons.

Upper limits on observed signal cross section, $\sigma_\text{obs}^\text{95}$, for the superpartners of the left-handed electrons, $\tilde{e}_L$.

Upper limits on observed signal cross section, $\sigma_\text{obs}^\text{95}$, for the superpartners of the right-handed electrons, $\tilde{e}_R$.

Upper limits on observed signal cross section, $\sigma_\text{obs}^\text{95}$, for the smuon signal model. Smuon ($\tilde{\mu}_{L, R}$) refers to the scalar superpartners of left- and right-handed muons.

Upper limits on observed signal cross section, $\sigma_\text{obs}^\text{95}$, for the superpartners of the left-handed muons, $\tilde{\mu}_L$.

Upper limits on observed signal cross section, $\sigma_\text{obs}^\text{95}$, for the superpartners of the right-handed muons, $\tilde{\mu}_R$.

Upper limits on observed signal cross section, $\sigma_\text{obs}^\text{95}$, for the stau signal model. Staus, $\tilde{\tau}_{1,2}$ are the mixed states of the superpartners of the left- and right-handed $\tau$ leptons, with mixing angle $\sin\theta_{\tilde\tau}=0.95$.

Upper limits on observed signal cross section, $\sigma_\text{obs}^\text{95}$, for $\tilde{\tau}_L$ production, where $\tilde{\tau}_L$ is pure-state superpartner of the left-handed $\tau$.

The expected and observed yields in the signal regions. Combined statistical and systematic uncertainties are presented. Estimates are truncated at 0 if the size of measured systematic uncertainties would yield a negative result.

Reconstruction efficiency as a function of $|d_{0}|$ and $p_\text{T}$ for signal electrons. Monte Carlo samples with $\tilde{e}$ or $\tilde{\mu}$ with mass 400 GeV and 1 ns lifetime were used. Efficiency is defined as the number of leptons passing all signal requirements and matched to generator-level muons divided by the number of generator level leptons with $p_\text{T} > 65$ GeV, $|d_{0}| >$ 3 mm, and |$\eta$| $<$ 2.47 for electrons. No event-level selections are made. Reconstructed leptons must pass all quality criteria, including the cosmic veto. Electron selection scale factors are included on the reconstructed leptons. The overflow is not shown in these plots.

Reconstruction efficiency as a function of $|d_{0}|$ and $p_\text{T}$ for signal muons. Monte Carlo samples with $\tilde{e}$ or $\tilde{\mu}$ with mass 400 GeV and 1 ns lifetime were used. Efficiency is defined as the number of leptons passing all signal requirements and matched to generator-level muons divided by the number of generator level leptons with $p_\text{T} > 65$ GeV, $|d_{0}| >$ 3 mm, and |$\eta$| $<$ 2.5 for muons. No event-level selections are made. Reconstructed leptons must pass all quality criteria, including the cosmic veto. Muon selection scale factors are included on the reconstructed leptons. The overflow is not shown in these plots.

Acceptance for $\tilde{e}$ of various masses and lifetimes in SR-$ee$. Acceptance is defined as the number of accepted events at generator level in signal Monte Carlo simulation divided by the total number of events in the sample. To be accepted, events are required to have at least 2 truth electrons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.47, $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$.

Acceptance for $\tilde{\mu}$ of various masses and lifetimes in SR-$\mu\mu$. Acceptance is defined as the number of accepted events at generator level in signal Monte Carlo simulation divided by the total number of events in the sample. To be accepted, events are required to have at least 2 truth muons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.5, $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$.

Efficiency for $\tilde{e}$ of various masses and lifetimes in SR-$ee$. Efficiency is defined as the number of selected reconstruced events divided by the acceptance. To be accepted, events are required to have at least 2 truth electrons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.47, $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$. To be selected, events must satisfy all signal region requirements.

Efficiency for $\tilde{\mu}$ of various masses and lifetimes in SR-$\mu\mu$. Efficiency is defined as the number of selected reconstruced events divided by the acceptance. To be accepted, events are required to have at least 2 truth muons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.5, $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$. To be selected, events must satisfy all signal region requirements.

Acceptance as a function of the generator-level $p_\text{T}$ of the leading and subleading lepton in SR-$ee$ from $\tilde{e}$ decays. The plot is made from signal Monte Carlo events with $\tilde{\ell}$ with mass of 400 GeV and lifetime of 1 ns. To be accepted, events are required to have at least 2 truth leptons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.47 for electrons, $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$. The overflow is not shown in these plots.

Acceptance as a function of the generator-level $p_\text{T}$ of the leading and subleading lepton in SR-$\mu\mu$ from $\tilde{\mu}$ decays. The plot is made from signal Monte Carlo events with $\tilde{\ell}$ with mass of 400 GeV and lifetime of 1 ns. To be accepted, events are required to have at least 2 truth leptons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.5 for muons, $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$. The overflow is not shown in these plots.

Acceptance for $\tilde{\tau}$ of various masses and lifetimes in SR-$ee$. Acceptance is defined as the number of accepted events at generator level in signal Monte Carlo simulation divided by the total number of events in the sample. To be accepted, events are required to have at least 2 truth electrons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.47, $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$.

Acceptance for $\tilde{\tau}$ of various masses and lifetimes in SR-$e\mu$. Acceptance is defined as the number of accepted events at generator level in signal Monte Carlo simulation divided by the total number of events in the sample. To be accepted, events are required to have at least 2 truth leptons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.5 (2.47) for muons (electrons), $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$.

Acceptance for $\tilde{\tau}$ of various masses and lifetimes in SR-$\mu\mu$. Acceptance is defined as the number of accepted events at generator level in signal Monte Carlo simulation divided by the total number of events in the sample. To be accepted, events are required to have at least 2 truth muons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.5, $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$.

Efficiency for $\tilde{\tau}$ of various masses and lifetimes in SR-$ee$. Efficiency is defined as the number of selected reconstruced events divided by the acceptance. To be accepted, events are required to have at least 2 truth electrons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.47, $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$. To be selected, events must satisfy all signal region requirements.

Efficiency for $\tilde{\tau}$ of various masses and lifetimes in SR-$e\mu$. Efficiency is defined as the number of selected reconstruced events divided by the acceptance. To be accepted, events are required to have at least 2 truth leptons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.5 (2.47) for muons (electrons), $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$. To be selected, events must satisfy all signal region requirements.

Efficiency for $\tilde{\tau}$ of various masses and lifetimes in SR-$\mu\mu$. Efficiency is defined as the number of selected reconstruced events divided by the acceptance. To be accepted, events are required to have at least 2 truth muons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.5, $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$. To be selected, events must satisfy all signal region requirements.

Acceptance as a function of the generator-level $p_\text{T}$ of the leading and subleading lepton in SR-$e\mu$ from $\tilde{\tau}$ decays. The plot is made from signal Monte Carlo events with $\tilde{\ell}$ with mass of 400 GeV and lifetime of 1 ns. To be accepted, events are required to have at least 2 truth leptons with $p_\text{T} > 65$ GeV, |$\eta$| $<$ 2.5 (2.47) for muons (electrons), $|d_{0}| > 3$ mm, and $\Delta R_{\ell\ell} > 0.2$. Events are also required to fall into one of the acceptance regions of the triggers used. At generator level, events must have one of the following: one electron with $p_\text{T} >$ 160 GeV, 2 electrons each with $p_\text{T} >$ 60 GeV, or 1 muon with $p_\text{T} >$ 60 GeV and $|\eta| < 1.07$. The overflow is not shown in these plots.

Observed 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane where all slepton flavors and chiralities are mass degenerate.

Expected 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane where all slepton flavors and chiralities are mass degenerate.

Observed 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$ee$ targeting selectron production. Selectrons ($\tilde{e}_{L, R}$) refer to the scalar superpartners of left- and right-handed electrons, which are assumed to be mass degenerate.

Expected 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$ee$ targeting selectron production. Selectrons ($\tilde{e}_{L, R}$) refer to the scalar superpartners of left- and right-handed electrons, which are assumed to be mass degenerate.

Observed 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$ee$ targeting selectron production. Selectrons ($\tilde{e}_{L}$) refer to the scalar superpartners of left-handed electrons.

Expected 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$ee$ targeting selectron production. Selectrons ($\tilde{e}_{L}$) refer to the scalar superpartners of left-handed electrons.

Observed 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$ee$ targeting selectron production. Selectrons ($\tilde{e}_{R}$) refer to the scalar superpartners of right-handed electrons. Purple denotes the region excluded by LEP.

Expected 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$ee$ targeting selectron production. Selectrons ($\tilde{e}_{R}$) refer to the scalar superpartners of right-handed electrons. Purple denotes the region excluded by LEP.

Observed 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$\mu\mu$ targeting smuon production. Smuons ($\tilde{\mu}_{L, R}$) refer to the scalar superpartners of left- and right-handed muons, which are assumed to be mass degenerate.

Expected 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$\mu\mu$ targeting smuon production. Smuons ($\tilde{\mu}_{L, R}$) refer to the scalar superpartners of left- and right-handed muons, which are assumed to be mass degenerate.

Expected 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$\mu\mu$ targeting smuon production. Smuons ($\tilde{\mu}_{L}$) refer to the scalar superpartners of left-handed muons.

Observed 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$\mu\mu$ targeting smuon production. Smuons ($\tilde{\mu}_{L}$) refer to the scalar superpartners of left-handed muons.

Observed 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$\mu\mu$ targeting smuon production. Smuons ($\tilde{\mu}_{R}$) refer to the scalar superpartners of right-handed muons. Purple denotes the region excluded by LEP.

Expected 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\ell})$ plane in SR-$\mu\mu$ targeting smuon production. Smuons ($\tilde{\mu}_{R}$) refer to the scalar superpartners of right-handed muons. Purple denotes the region excluded by LEP.

Observed 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\tau})$ plane. Staus, $\tilde{\tau}_{1,2}$ are the mixed states of the superpartners of the left- and right-handed $\tau$ leptons, with mixing angle $\sin(\theta_{\tilde\tau})=0.95$, which are assumed to be mass degenerate.

Expected 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\tau})$ plane. Staus, $\tilde{\tau}_{1,2}$ are the mixed states of the superpartners of the left- and right-handed $\tau$ leptons, with mixing angle $\sin(\theta_{\tilde\tau})=0.95$, which are assumed to be mass degenerate.

Observed 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\tau}_L)$ plane, where $\tilde{\tau}_L$ is the pure-state super-partner of the left-handed $\tau$. Purple denotes the region excluded by LEP. This result does not present signficant sensitivity to the pure-state superpartner of the right-handed $\tau$.

Expected 95% CL exclusion sensitivity. The limit is displayed in the lifetime vs. $m(\tilde{\tau}_L)$ plane, where $\tilde{\tau}_L$ is the pure-state super-partner of the left-handed $\tau$. Purple denotes the region excluded by LEP. This result does not present signficant sensitivity to the pure-state superpartner of the right-handed $\tau$.

The mllbb mass distribution for the mbb window defined for (mA, mH)=(600, 300) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (600, 300) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH)=(670, 500) GeV in the 2 tag category with gluon-gluon fusion production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (670, 500) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (670, 500) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (670, 500) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

Upper bounds at 95% CL on the production cross-section times the branching ratio B(A->ZH)xB(H->bb) in pb for a narrow width A boson produced via gluon-gluon fusion. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected.

Upper bounds at 95% CL on the production cross-section times the branching ratio B(A->ZH)xB(H->bb) in pb for a narrow width A boson produced via b-associated production. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected.

Upper bounds at 95% CL on the total production cross-section (ggA + bbA) times the branching ratio B(A->ZH)xB(H->bb) for an A boson in the 2HDM of type-1 with tan(beta)=1. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used and cos(beta-alpha)=0 is assumed. The excluded contours in the figure correspond to the points of the 2HDM parameter space where the expected and observed limits match the theoretical prediction for the cross-section in the model.

Upper bounds at 95% CL on the total production cross-section (ggA + bbA) times the branching ratio B(A->ZH)xB(H->bb) for an A boson in the 2HDM of type-1 with tan(beta)=5. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used and cos(beta-alpha)=0 is assumed. The excluded contours in the figure correspond to the points of the 2HDM parameter space where the expected and observed limits match the theoretical prediction for the cross-section in the model.

Upper bounds at 95% CL on the total production cross-section (ggA + bbA) times the branching ratio B(A->ZH)xB(H->bb) for an A boson in the 2HDM of type-1 with tan(beta)=10. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used and cos(beta-alpha)=0 is assumed. The excluded contours in the figure correspond to the points of the 2HDM parameter space where the expected and observed limits match the theoretical prediction for the cross-section in the model.

Upper bounds at 95% CL on the total production cross-section (ggA + bbA) times the branching ratio B(A->ZH)xB(H->bb) for an A boson in the 2HDM of type-2 with tan(beta)=1. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used and cos(beta-alpha)=0 is assumed. The excluded contours in the figure correspond to the points of the 2HDM parameter space where the expected and observed limits match the theoretical prediction for the cross-section in the model.

Upper bounds at 95% CL on the total production cross-section (ggA + bbA) times the branching ratio B(A->ZH)xB(H->bb) for an A boson in the 2HDM of type-2 with tan(beta)=5. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used and cos(beta-alpha)=0 is assumed. The excluded contours in the figure correspond to the points of the 2HDM parameter space where the expected and observed limits match the theoretical prediction for the cross-section in the model.

Upper bounds at 95% CL on the total production cross-section (ggA + bbA) times the branching ratio B(A->ZH)xB(H->bb) for an A boson in the 2HDM of type-2 with tan(beta)=10. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used and cos(beta-alpha)=0 is assumed. The excluded contours in the figure correspond to the points of the 2HDM parameter space where the expected and observed limits match the theoretical prediction for the cross-section in the model.

Upper bounds at 95% CL on the total production cross-section (ggA + bbA) times the branching ratio B(A->ZH)xB(H->bb) for an A boson in the 2HDM of type-2 with tan(beta)=20. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used and cos(beta-alpha)=0 is assumed. The excluded contours in the figure correspond to the points of the 2HDM parameter space where the expected and observed limits match the theoretical prediction for the cross-section in the model.

Upper bounds at 95% CL on the total production cross-section (ggA + bbA) times the branching ratio B(A->ZH)xB(H->bb) for an A boson in the lepton specific 2HDM with tan(beta)=1. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used and cos(beta-alpha)=0 is assumed. The excluded contours in the figure correspond to the points of the 2HDM parameter space where the expected and observed limits match the theoretical prediction for the cross-section in the model.

Upper bounds at 95% CL on the total production cross-section (ggA + bbA) times the branching ratio B(A->ZH)xB(H->bb) for an A boson in the lepton specific 2HDM with tan(beta)=2. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used and cos(beta-alpha)=0 is assumed. The excluded contours in the figure correspond to the points of the 2HDM parameter space where the expected and observed limits match the theoretical prediction for the cross-section in the model.

Upper bounds at 95% CL on the total production cross-section (ggA + bbA) times the branching ratio B(A->ZH)xB(H->bb) for an A boson in the lepton specific 2HDM with tan(beta)=3. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used and cos(beta-alpha)=0 is assumed. The excluded contours in the figure correspond to the points of the 2HDM parameter space where the expected and observed limits match the theoretical prediction for the cross-section in the model.

Upper bounds at 95% CL on the total production cross-section (ggA + bbA) times the branching ratio B(A->ZH)xB(H->bb) for an A boson in the flipped 2HDM with tan(beta)=1. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used and cos(beta-alpha)=0 is assumed. The excluded contours in the figure correspond to the points of the 2HDM parameter space where the expected and observed limits match the theoretical prediction for the cross-section in the model.

Upper bounds at 95% CL on the total production cross-section (ggA + bbA) times the branching ratio B(A->ZH)xB(H->bb) for an A boson in the flipped 2HDM with tan(beta)=5. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used and cos(beta-alpha)=0 is assumed. The excluded contours in the figure correspond to the points of the 2HDM parameter space where the expected and observed limits match the theoretical prediction for the cross-section in the model.

Upper bounds at 95% CL on the total production cross-section (ggA + bbA) times the branching ratio B(A->ZH)xB(H->bb) for an A boson in the flipped 2HDM with tan(beta)=10. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used and cos(beta-alpha)=0 is assumed. The excluded contours in the figure correspond to the points of the 2HDM parameter space where the expected and observed limits match the theoretical prediction for the cross-section in the model.

Upper bounds at 95% CL on the total production cross-section (ggA + bbA) times the branching ratio B(A->ZH)xB(H->bb) for an A boson in the flipped 2HDM with tan(beta)=20. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected. The correct width as predicted by this particular parameter choice of the 2HDM is used and cos(beta-alpha)=0 is assumed. The excluded contours in the figure correspond to the points of the 2HDM parameter space where the expected and observed limits match the theoretical prediction for the cross-section in the model.

The mass distribution of the 4q system before any m4q window cuts for gluon-gluon fusion for the llWW channel. The signal distribution for (mA, mH) = (600, 300) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH)=(600, 300) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (600, 300) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH)=(670, 500) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (670, 500) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

Upper bounds at 95% CL on the production cross-section times the branching ratio B(A->ZH)xB(H->WW) in pb for a narrow width A boson produced via gluon-gluon fusion production. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected.

Upper bounds at 95% CL on the production cross-section times the branching ratio B(A->ZH)xB(H->bb) in pb for an A boson with a natural width that is 10% with respect to its mass, produced via gluon-gluon fusion for the llbb final state. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected.

Upper bounds at 95% CL on the production cross-section times the branching ratio B(A->ZH)xB(H->bb) in pb for an A boson with a natural width that is 10% with respect to its mass, via b-associated production for the llbb final state. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected.

Upper bounds at 95% CL on the production cross-section times the branching ratio B(A->ZH)xB(H->bb) in pb for an A boson with a natural width that is 20% with respect to its mass, produced via gluon-gluon fusion for the llbb final state. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected.

Upper bounds at 95% CL on the production cross-section times the branching ratio B(A->ZH)xB(H->bb) in pb for an A boson with a natural width that is 20% with respect to its mass, via b-associated production for the llbb final state. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected.

Upper bounds at 95% CL on the production cross-section times the branching ratio B(A->ZH)xB(H->WW) in pb for an A boson with a natural width that is 10% with respect to its mass, produced via gluon-gluon fusion for the llWW final state. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected.

Upper bounds at 95% CL on the production cross-section times the branching ratio B(A->ZH)xB(H->WW) in pb for an A boson with a natural width that is 20% with respect to its mass, produced via gluon-gluon fusion for the llWW final state. For each signal point, characterised by the mass pair (mA, mH), two limits are provided, the observed and the expected.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (440, 130) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (440, 130) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (450, 140) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (450, 140) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (460, 150) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (460, 150) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (460, 160) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (460, 160) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (470, 170) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (470, 170) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (470, 180) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (470, 180) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (420, 190) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (420, 190) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (490, 200) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (490, 200) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (430, 210) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (430, 210) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (440, 220) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (440, 220) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (500, 230) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (500, 230) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (510, 240) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (510, 240) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (520, 250) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (520, 250) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (520, 260) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (520, 260) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (530, 270) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (530, 270) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (540, 280) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (540, 280) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (540, 290) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (540, 290) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (550, 300) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (550, 300) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (550, 310) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (550, 310) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (560, 320) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (560, 320) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (570, 330) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (570, 330) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (570, 340) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (570, 340) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (580, 350) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (580, 350) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (580, 360) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (580, 360) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (590, 370) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (590, 370) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (600, 380) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (600, 380) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (600, 390) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (600, 390) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (610, 400) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (610, 400) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (620, 410) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (620, 410) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (620, 420) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (620, 420) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (630, 430) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (630, 430) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (630, 440) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (630, 440) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (640, 450) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (640, 450) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (650, 460) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (650, 460) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (650, 470) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (650, 470) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (660, 480) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (660, 480) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (670, 490) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (670, 490) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (670, 500) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (670, 500) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (680, 510) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (680, 510) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (680, 520) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (680, 520) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (690, 530) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (690, 530) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (700, 540) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (700, 540) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (700, 550) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (700, 550) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (710, 560) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (710, 560) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (710, 570) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (710, 570) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (720, 580) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (720, 580) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (730, 590) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (730, 590) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (730, 600) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (730, 600) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (740, 610) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (740, 610) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (750, 620) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (750, 620) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (750, 630) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (750, 630) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (760, 640) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (760, 640) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (760, 650) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (760, 650) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (770, 660) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (770, 660) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (780, 670) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (780, 670) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (780, 680) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (780, 680) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (790, 690) GeV in the 2 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (790, 690) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (440, 130) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (440, 130) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (450, 140) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (450, 140) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (460, 150) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (460, 150) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (460, 160) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (460, 160) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (470, 170) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (470, 170) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (470, 180) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (470, 180) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (420, 190) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (420, 190) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (490, 200) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (490, 200) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (430, 210) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (430, 210) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (440, 220) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (440, 220) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (500, 230) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (500, 230) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (510, 240) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (510, 240) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (520, 250) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (520, 250) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (520, 260) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (520, 260) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (530, 270) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (530, 270) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (540, 280) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (540, 280) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (540, 290) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (540, 290) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (550, 300) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (550, 300) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (550, 310) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (550, 310) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (560, 320) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (560, 320) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (570, 330) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (570, 330) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (570, 340) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (570, 340) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (580, 350) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (580, 350) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (580, 360) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (580, 360) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (590, 370) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (590, 370) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (600, 380) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (600, 380) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (600, 390) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (600, 390) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (610, 400) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (610, 400) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (620, 410) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (620, 410) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (620, 420) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (620, 420) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (630, 430) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (630, 430) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (630, 440) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (630, 440) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (640, 450) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (640, 450) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (650, 460) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (650, 460) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (650, 470) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (650, 470) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (660, 480) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (660, 480) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (670, 490) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (670, 490) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (670, 500) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (670, 500) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (680, 510) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (680, 510) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (680, 520) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (680, 520) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (690, 530) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (690, 530) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (700, 540) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (700, 540) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (700, 550) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (700, 550) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (710, 560) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (710, 560) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (710, 570) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (710, 570) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (720, 580) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (720, 580) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (730, 590) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (730, 590) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (730, 600) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (730, 600) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (740, 610) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (740, 610) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (750, 620) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (750, 620) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (750, 630) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (750, 630) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (760, 640) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (760, 640) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (760, 650) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (760, 650) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (770, 660) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (770, 660) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (780, 670) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (780, 670) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (780, 680) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (780, 680) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The mllbb mass distribution for the mbb window defined for (mA, mH) = (790, 690) GeV in the 3 tag category with b-associated production is shown. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (790, 690) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->bb) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (400, 200) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (400, 200) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (430, 210) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (430, 210) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (440, 220) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (440, 220) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (500, 230) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (500, 230) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (510, 240) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (510, 240) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (520, 250) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (520, 250) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (520, 260) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (520, 260) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (530, 270) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (530, 270) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (540, 280) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (540, 280) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (540, 290) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (540, 290) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (550, 300) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (550, 300) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (550, 310) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (550, 310) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (560, 320) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (560, 320) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (570, 330) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (570, 330) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (570, 340) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (570, 340) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (580, 350) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (580, 350) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (580, 360) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (580, 360) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (590, 370) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (590, 370) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (600, 380) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (600, 380) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (600, 390) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (600, 390) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (610, 400) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (610, 400) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (620, 410) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (620, 410) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (620, 420) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (620, 420) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (630, 430) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (630, 430) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (630, 440) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (630, 440) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (640, 450) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (640, 450) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (650, 460) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (650, 460) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (650, 470) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (650, 470) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (660, 480) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (660, 480) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (670, 490) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (670, 490) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (670, 500) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (670, 500) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (680, 510) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (680, 510) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (680, 520) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (680, 520) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (690, 530) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (690, 530) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (700, 540) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (700, 540) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (700, 550) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (700, 550) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (710, 560) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (710, 560) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (710, 570) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (710, 570) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (720, 580) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (720, 580) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (730, 590) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (730, 590) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (730, 600) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (730, 600) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (740, 610) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (740, 610) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (750, 620) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (750, 620) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (750, 630) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (750, 630) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (760, 640) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (760, 640) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (760, 650) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (760, 650) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (770, 660) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (770, 660) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (780, 670) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (780, 670) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (780, 680) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (780, 680) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (790, 690) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (790, 690) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

The m2l4q mass distribution for the m4q window defined for (mA, mH) = (800, 700) GeV with gluon-gluon fusion production is shown for the llWW channel. The number of entries shown in each bin is the number of events in that bin divided by the width of the bin. The signal distribution for (mA, mH) = (800, 700) GeV is also shown, and is normalised such that the production cross-section times the branching ratios B(A->ZH)xB(H->WW) corresponds to 1 pb. Background components are displayed separately.

Distribution of $E^{miss}_T$ in data and for the expected SM background in the Two-Electron CR after performing the 'simplified shape fit'. Overflows are included in the fourth bin of each distribution. The $E^{miss}_T$ calculation in this CR does not include electron contribution. The error bars are statistical, and the dashed band includes statistical and systematic uncertainties determined by the fit. The lower panel shows the ratio of data to expected background event yields.

The observed exclusion contours on the $m_{\chi} - m_{med}$ plane for a simplified DM model involving an axial-vector mediator with couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0.

The expected exclusion contours on the $m_{\chi} - m_{med}$ plane for a simplified DM model involving an axial-vector mediator with couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0.

The expected + 1 sigma exclusion contours on the $m_{\chi} - m_{med}$ plane for a simplified DM model involving an axial-vector mediator with couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0.

The expected - 1 sigma exclusion contours on the $m_{\chi} - m_{med}$ plane for a simplified DM model involving an axial-vector mediator with couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0.

The observed exclusion contours on the $m_{\chi} - m_{med}$ plane for a simplified DM model involving an axial-vector mediator with couplings $g_{\chi}$ = 1, $g_q$ = 0.1 and $g_l$ = 0.1.

The expected exclusion contours on the $m_{\chi} - m_{med}$ plane for a simplified DM model involving an axial-vector mediator with couplings $g_{\chi}$ = 1, $g_q$ = 0.1 and $g_l$ = 0.1.

The expected + 1 sigma exclusion contours on the $m_{\chi} - m_{med}$ plane for a simplified DM model involving an axial-vector mediator with couplings $g_{\chi}$ = 1, $g_q$ = 0.1 and $g_l$ = 0.1.

The expected - 1 sigma exclusion contours on the $m_{\chi} - m_{med}$ plane for a simplified DM model involving an axial-vector mediator with couplings $g_{\chi}$ = 1, $g_q$ = 0.1 and $g_l$ = 0.1.

The observed exclusion contours on the $m_{\chi} - m_{med}$ plane for a vector mediator with couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0.

The expected exclusion contours on the $m_{\chi} - m_{med}$ plane for a vector mediator with couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0.

The expected + 1 sigma exclusion contours on the $m_{\chi} - m_{med}$ plane for a vector mediator with couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0.

The expected - 1 sigma exclusion contours on the $m_{\chi} - m_{med}$ plane for a vector mediator with couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0.

The observed exclusion contours on the $m_{\chi} - m_{med}$ plane for a vector mediator with couplings and $g_{\chi}$ = 1, $g_q$ = 0.1 and $g_l$ = 0.01

The expected exclusion contours on the $m_{\chi} - m_{med}$ plane for a vector mediator with couplings $g_{\chi}$ = 1, $g_q$ = 0.1 and $g_l$ = 0.01.

The expected + 1 sigma exclusion contours on the $m_{\chi} - m_{med}$ plane for a vector mediator with couplings $g_{\chi}$ = 1, $g_q$ = 0.1 and $g_l$ = 0.01.

The expected - 1 sigma exclusion contours on the $m_{\chi} - m_{med}$ plane for a vector mediator with couplings $g_{\chi}$ = 1, $g_q$ = 0.1 and $g_l$ = 0.01.

The 90% CL exclusion limit on $\chi$-proton spin-dependent scattering cross section in an axial-vector model with couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0 as a function of the dark-matter mass $m_{\chi}$. The 90% CL exclusion limit is displayed only in the regime where the theory is perturbative.

The 90% CL exclusion limit on $\chi$-neutron spin-dependent scattering cross section in an axial-vector model with couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0 as a function of the dark-matter mass $m_{\chi}$. The 90% CL exclusion limit is displayed only in the regime where the theory is perturbative.

The 90% CL exclusion limit on $\chi$-nucleon spin-independent scattering cross section in a vector model with couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0 as a function of the dark-matter mass $m_{\chi}$.

Observed and expected exclusion at 95% CL on the coupling $c_W$ as a function of the effective scale $f_a$ for an ALP mass of 1 MeV.

The observed 95% CL upper limits on signal strength $\mu$, the ratio of the experimental limit to the predicted signal cross section, for a simplified model of dark matter production involving an axial-vector operator and couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0 as a function of the mass of the dark matter, $m_{\chi}$ and the mass of the axial-vector mediator, $m_{med}$.

The observed 95% CL upper limits on cross section for a simplified model of dark matter production involving an axial-vector operator and couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0 as a function of the mass of the dark matter, $m_{\chi}$ and the mass of the axial-vector mediator, $m_{med}$.

Acceptance in % for a simplified model of dark matter production involving an axial-vector operator with couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0 for different values of $m_{\chi}$ and $m_{med}$ in the four inclusive signal regions.

Acceptance in % for a simplified model of dark matter production involving an axial-vector operator with couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0 for different values of $m_{\chi}$ and $m_{med}$ in the three exclusive signal regions.

Efficiencies for a simplified model of dark matter production involving an axial-vector operator with couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0 for different values of $m_{\chi}$ and $m_{med}$ in the four inclusive signal regions.

Efficiencies for a simplified model of dark matter production involving an axial-vector operator with couplings $g_{\chi}$ = 1, $g_q$ = 0.25 and $g_l$ = 0 for different values of $m_{\chi}$ and $m_{med}$ in the three exclusive signal regions.

Observed metSig distributions in signal regions MB-GGd. The histograms show the MC background predictions normalised by the background-only fit. The hatched (red) error bands indicate experimental and MC statistical uncertainties. Expected distributions for benchmark signal model points, normalised using the approximate NNLO+NNLL cross-section times integrated luminosity, are also shown for comparison (masses in GeV).

Observed $m_{\mathrm{eff}}$ distributions in signal regions MB-C. The histograms show the MC background predictions normalised by the background-only fit. The hatched (red) error bands indicate experimental and MC statistical uncertainties. Expected distributions for benchmark signal model points, normalised using the approximate NNLO+NNLL cross-section times integrated luminosity, are also shown for comparison (masses in GeV).

Observed metSig distributions in signal regions MB-C. The histograms show the MC background predictions normalised by the background-only fit. The hatched (red) error bands indicate experimental and MC statistical uncertainties. Expected distributions for benchmark signal model points, normalised using the approximate NNLO+NNLL cross-section times integrated luminosity, are also shown for comparison (masses in GeV).

Observed BDT-GGd1 score distributions in signal regions GGd1. The histograms show the MC background predictions normalised by the background-only fit. The hatched (red) error bands indicate experimental and MC statistical uncertainties. Expected distributions for benchmark signal model points, normalised using the approximate NNLO+NNLL cross-section times integrated luminosity, are also shown for comparison (masses in GeV).

Observed BDT-GGo1 score distributions in signal regions GGo1. The histograms show the MC background predictions normalised by the background-only fit. The hatched (red) error bands indicate experimental and MC statistical uncertainties. Expected distributions for benchmark signal model points, normalised using the approximate NNLO+NNLL cross-section times integrated luminosity, are also shown for comparison (masses in GeV).

Signal region acceptance for simplified model with gluino pair production and decays to two quarks and neutralino in SR BDT-GGd1

Signal region acceptance for simplified model with gluino pair production and decays to two quarks and neutralino in SR BDT-GGd2

Signal region acceptance for simplified model with gluino pair production and decays to two quarks and neutralino in SR BDT-GGd3

Signal region acceptance for simplified model with gluino pair production and decays to two quarks and neutralino in SR BDT-GGd4

Signal region acceptance for simplified model with gluino pair production and decays to two quarks and chargino in SR BDT-GGo1

Signal region acceptance for simplified model with gluino pair production and decays to two quarks and chargino in SR BDT-GGo2

Signal region acceptance for simplified model with gluino pair production and decays to two quarks and chargino in SR BDT-GGo3

Signal region acceptance for simplified model with gluino pair production and decays to two quarks and chargino in SR BDT-GGo4

Signal region acceptance for simplified model with squark pair production and decays to a quark and neutralino in SR 2j-1600

Signal region acceptance for simplified model with squark pair production and decays to a quark and neutralino in SR 2j-2200

Signal region acceptance for simplified model with squark pair production and decays to a quark and neutralino in SR 2j-2800

Signal region acceptance for simplified model with gluino pair production and decays to two quarks and neutralino in SR 4j-1000

Signal region acceptance for simplified model with gluino pair production and decays to two quarks and neutralino in SR 4j-2200

Signal region acceptance for simplified model with gluino pair production and decays to two quarks and neutralino in SR 4j-3400

Signal region acceptance for simplified model with gluino pair production and decays to two quarks and neutralino in SR 5j-1600

Signal region acceptance for simplified model with gluino pair production and decays to two quarks and chargino in SR 6j-1000

Signal region acceptance for simplified model with gluino pair production and decays to two quarks and chargino in SR 6j-2200

Signal region acceptance for simplified model with gluino pair production and decays to two quarks and chargino in SR 6j-3400

Signal region efficiency for simplified model with gluino pair production and decays to two quarks and neutralino in SR BDT-GGd1. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.

Signal region efficiency for simplified model with gluino pair production and decays to two quarks and neutralino in SR BDT-GGd2. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.

Signal region efficiency for simplified model with gluino pair production and decays to two quarks and neutralino in SR BDT-GGd3. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.

Signal region efficiency for simplified model with gluino pair production and decays to two quarks and neutralino in SR BDT-GGd4. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.

Signal region efficiency for simplified model with gluino pair production and decays to two quarks and chargino in SR BDT-GGo1. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.

Signal region efficiency for simplified model with gluino pair production and decays to two quarks and chargino in SR BDT-GGo2. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.

Signal region efficiency for simplified model with gluino pair production and decays to two quarks and chargino in SR BDT-GGo3. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.

Signal region efficiency for simplified model with gluino pair production and decays to two quarks and chargino in SR BDT-GGo4. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.

Signal region efficiency for simplified model with squark pair production and decays to a quark and neutralino in SR 2j-1600. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.

Signal region efficiency for simplified model with squark pair production and decays to a quark and neutralino in SR 2j-2200. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.

Signal region efficiency for simplified model with squark pair production and decays to a quark and neutralino in SR 2j-2800. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.

Signal region efficiency for simplified model with gluino pair production and decays to two quarks and neutralino in SR 4j-1000. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.

Signal region efficiency for simplified model with gluino pair production and decays to two quarks and neutralino in SR 4j-2200. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.

Signal region efficiency for simplified model with gluino pair production and decays to two quarks and neutralino in SR 4j-3400. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.

Signal region efficiency for simplified model with gluino pair production and decays to two quarks and neutralino in SR 5j-1600. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.

Signal region efficiency for simplified model with gluino pair production and decays to two quarks and chargino in SR 6j-1000. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.

Signal region efficiency for simplified model with gluino pair production and decays to two quarks and chargino in SR 6j-2200. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.

Signal region efficiency for simplified model with gluino pair production and decays to two quarks and chargino in SR 6j-3400. Efficiencies on signal points with low statistics are not reported. The efficiency value -1.0 in the table corresponds to the case where efficiency cannot be calculated due to the null acceptance of the model point.

Exclusion limits in the mass plane of the lightest neutralino and first- and second-generation squarks assuming squark pair production and direct decays obtained by using the signal region with the best expected sensitivity at each point. The expected limits are indicated with a dark dashed curve, with the light (yellow) band indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.

Exclusion limits in the mass plane of the lightest neutralino and first- and second-generation squarks assuming squark pair production and direct decays obtained by using the signal region with the best expected sensitivity at each point. The observed limits are indicated by the medium dark (maroon) curve where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.

Exclusion limits in the mass plane of the lightest neutralino and non degenerated squark pair production and direct decays obtained by using the signal region with the best expected sensitivity at each point. The expected limits are indicated with a dark dashed curve, with the light (yellow) band indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.

Exclusion limits in the mass plane of the lightest neutralino and non degenerated squark pair production and direct decays obtained by using the signal region with the best expected sensitivity at each point. The observed limits are indicated by the medium dark (maroon) curve where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.

Exclusion limits in the mass plane of the lightest neutralino and the gluino for gluino pair production with direct decays obtained by using the signal region with the best expected sensitivity at each point. The expected limits are indicated with a dark dashed curve, with the light (yellow) band indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.

Exclusion limits in the mass plane of the lightest neutralino and the gluino for gluino pair production with direct decays obtained by using the signal region with the best expected sensitivity at each point. The observed limits are indicated by the medium dark (maroon) curve where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.

Exclusion limits in the mass plane of the lightest neutralino and squarks. The expected limits are indicated with dark dashed curves, with the light (yellow) bands indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.

Exclusion limits in the mass plane of the lightest neutralino and squarks. The observed limits are indicated by the medium dark (maroon) curves where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.

Exclusion limits for squark pair production with a one-step decay via an intermediate chargino. The neutralino mass is fixed at 60 GeV and exclusion limits are given for mass difference ratio, $X$, as a function of the squark mass. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The expected limits are indicated with dark dashed curves, with the light (yellow) bands indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.

Exclusion limits for squark pair production with a one-step decay via an intermediate chargino. The neutralino mass is fixed at 60 GeV and exclusion limits are given for mass difference ratio, $X$, as a function of the squark mass. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The observed limits are indicated by the medium dark (maroon) curves where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.

Exclusion limits in the mass plane of the lightest neutralino and gluinos. The expected limits are indicated with dark dashed curves, with the light (yellow) bands indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.

Exclusion limits in the mass plane of the lightest neutralino and gluinos. The observed limits are indicated by the medium dark (maroon) curve where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.

Exclusion limits for gluino pair production with a one-step decay via an intermediate chargino. The neutralino mass is fixed at 60 GeV and exclusion limits are given for mass difference ratio, $X$, as a function of the gluino mass. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The expected limits are indicated with dark dashed curves, with the light (yellow) bands indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.

Exclusion limits for gluino pair production with a one-step decay via an intermediate chargino. The neutralino mass is fixed at 60 GeV and exclusion limits are given for mass difference ratio, $X$, as a function of the gluino mass. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The observed limits are indicated by the medium dark (maroon) curves where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.

Exclusion limits for the model with combined production of squark pairs, gluino pairs, and of squark--gluino pairs. The neutralino mass is fixed at 0 GeV. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The expected limits are indicated with dark dashed curves, with the light (yellow) bands indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.

Exclusion limits for the model with combined production of squark pairs, gluino pairs, and of squark--gluino pairs. The neutralino mass is fixed at 0 GeV. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The observed limits are indicated by the medium dark (maroon) curves where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.

Exclusion limits for the model with combined production of squark pairs, gluino pairs, and of squark--gluino pairs. The neutralino mass is fixed at 995 GeV. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The expected limits are indicated with dark dashed curves, with the light (yellow) bands indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.

Exclusion limits for the model with combined production of squark pairs, gluino pairs, and of squark--gluino pairs. The neutralino mass is fixed at 995 GeV. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The observed limits are indicated by the medium dark (maroon) curves where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.

Exclusion limits for the model with combined production of squark pairs, gluino pairs, and of squark--gluino pairs. The neutralino mass is fixed at 1495 GeV. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The expected limits are indicated with dark dashed curves, with the light (yellow) bands indicating the $1\sigma$ excursions due to experimental and background-only theoretical uncertainties.

Exclusion limits for the model with combined production of squark pairs, gluino pairs, and of squark--gluino pairs. The neutralino mass is fixed at 1495 GeV. Exclusion limits are obtained by using the signal region with the best expected sensitivity at each point. The observed limits are indicated by the medium dark (maroon) curves where the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross-section by the renormalisation and factorisation scale and PDF uncertainties.

The observed upper limits on signal cross section corresponding to the best expected signal region in each mass point for squark-pair production with direct decays.

The observed upper limits on signal cross section corresponding to the best expected signal region in each mass point for gluino-pair production with direct decays

The observed upper limits on signal cross section corresponding to the best expected signal region in each mass point for squark-pair production with a one-step decay via an intermediate chargino.

The observed upper limits on signal cross section corresponding to the best expected signal region in each mass point for squark-pair production with a one-step decay via an intermediate chargino. The neutralino mass is fixed at 60 GeV and exclusion limits are given for mass difference ratio, $X$, as a function of the squark mass.

The observed upper limits on signal cross section corresponding to the best expected signal region in each mass point for gluino-pair production with a one-step decay via an intermediate chargino.

The observed upper limits on signal cross section corresponding to the best expected signal region in each mass point for gluino-pair production with a one-step decay via an intermediate chargino. The neutralino mass is fixed at 60~GeV and exclusio limits are given for mass difference ratio, $X$, as a function of the gluino mass.

Cut-flow for model-independent search regions targeting squarks for SS direct model points. Expected yields are normalized to a luminosity of 139 fb$^{-1}$.

Cut-flow for model-independent search regions targeting gluinos for GG direct model points. Expected yields are normalized to a luminosity of 139 fb$^{-1}$.

Cut-flow for model-independent search regions targeting squarks and gluinos in models with one-step decay. Expected yields are normalized to a luminosity of 139 $fb^{-1}$.

Cut-flow for BDT search regions targeting gluinos in models with one-step decays. Expected yields are normalized to a luminosity of 139 $fb^{-1}$.

Cut-flow for BDT search regions targeting gluinos in models with direct decays. Expected yields are normalized to a luminosity of 139 $fb^{-1}$.

The ratios (&mu;) of the 95&#37; C.L. upper limits on the combined s&rarr; W^&plusmn;W^&#8723; and s&rarr; ZZ cross section to simplified model expectations for the m_Z'=1 TeV scenario, for various m_s hypotheses. The observed limits (solid line) are consistent with the expectation under the SM-only hypothesis (dashed line) within uncertainties (filled band), except for a small excess for m_s=160 GeV, discussed in the text.

The ratios (&mu;) of the 95&#37; C.L. upper limits on the combined s&rarr; W^&plusmn;W^&#8723; and s&rarr; ZZ cross section to simplified model expectations for the m_Z'=1.7 TeV scenario, for various m_s hypotheses. The observed limits (solid line) are consistent with the expectation under the SM-only hypothesis (dashed line) within uncertainties (filled band), except for a small excess for m_s=160 GeV, discussed in the text.

Observed upper limits at 95&#37; C.L. on &sigma;(pp &rarr; s &chi;&chi;) × B(s&rarr; VV) for m_Z'=0.5 TeV signal points. The expected limits, varied up and down by one and two standard deviations, are shown as green and yellow bands, respectively. The observed and expected limits are compared to the theoretical LO cross section for the &sigma;(pp &rarr; s &chi;&chi;) × B(s&rarr; VV) process for m_Z'=0.5 TeV, shown in dashed blue.

Observed upper limits at 95&#37; C.L. on &sigma;(pp &rarr; s &chi;&chi;) × B(s&rarr; VV) for m_Z'=1 TeV signal points. The expected limits, varied up and down by one and two standard deviations, are shown as green and yellow bands, respectively. The observed and expected limits are compared to the theoretical LO cross section for the &sigma;(pp &rarr; s &chi;&chi;) × B(s&rarr; VV) process for m_Z'=1 TeV, shown in dashed blue.

Observed upper limits at 95&#37; C.L. on &sigma;(pp &rarr; s &chi;&chi;) × B(s&rarr; VV) for m_Z'=1.7 TeV signal points. The expected limits, varied up and down by one and two standard deviations, are shown as green and yellow bands, respectively. The observed and expected limits are compared to the theoretical LO cross section for the &sigma;(pp &rarr; s &chi;&chi;) × B(s&rarr; VV) process for m_Z'=1.7 TeV, shown in dashed blue.

SM background post-fit yields stacked in each SR and CR category and E_T^miss bin and data overlaid with the maximum likelihood estimators set to the conditional values of the combined signal and control region fit. The hatched uncertainty band shown includes simulation statistics uncertainties, experimental systematic uncertainties, and V+jets theory modelling systematic uncertainties. Pre-fit uncertainties cover differences between the data and pre-fit background prediction.

Cumulative efficiencies for the merged category for signal samples with m_s=160 GeV (a), m_s=235 GeV (b) and m_s=310 GeV (c), each with m_Z'=1 TeV. The dark Higgs candidate selection includes stringent jet substructure requirements and typically at most one candidate is present in signal events. Here, &Delta; &phi;_{jets_1,2,3 E_T^miss} is the smallest azimuthal angle between the E_T^miss and any of the three highest-p_T (leading) small-R jets.

Cumulative efficiencies for the intermediate category for signal samples with m_s=160 GeV (a), m_s=235 GeV (b) and m_s=310 GeV (c), each with m_Z'=1 TeV. The TAR+Comb algorithm reconstructs the dark Higgs candidate from a TAR jet with m^TAR&gt;60 GeV that is supplemented by up to two additional small-R jets within &Delta;R_cone=2.5 of the TAR jet. Here, &Delta; &phi;_{jets_1,2,3 E_T^miss} is the smallest azimuthal angle between the E_T^miss and any of the three highest-p_T (leading) small-R jets. For details see text.

The product of acceptance and efficiency (A &times; &varepsilon;), defined as the number of signal events satisfying the full set of selection criteria in the merged or intermediate signal regions, divided by the total number of generated signal events, for the s(W^&plusmn;W^&#8723;) dark Higgs signal points with dark Higgs boson mass m_s and Z' boson mass m_Z'.

The product of acceptance and efficiency (A &times; &varepsilon;), defined as the number of signal events satisfying the full set of selection criteria in the merged or intermediate signal regions, divided by the total number of generated signal events, for the s(ZZ) dark Higgs signal points with dark Higgs boson mass m_s and Z' boson mass m_Z'.