Observed and expected background and signal effective mass distributions for SR2jl. For signal, a squark direct decay model with $m(\tilde q)=800$ GeV and $m(\tilde\chi^0_1)=400$ GeV is shown.

Observed and expected background and signal effective mass distributions for SR2jm. For signal, a gluino direct decay model with $m(\tilde g)=750$ GeV and $m(\tilde\chi^0_1)=660$ GeV is shown.

Observed and expected background and signal effective mass distributions for SR2jt. For signal, a squark direct decay model with $m(\tilde q)=1200$ GeV and $m(\tilde\chi^0_1)=0$ GeV is shown.

Observed and expected background and signal effective mass distributions for SR4jt. For signal, a gluino direct decay model with $m(\tilde g)=1400$ GeV and $m(\tilde\chi^0_1)=0$ GeV is shown.

Observed and expected background and signal effective mass distributions for SR5j. For signal, a gluino one-step decay model with $m(\tilde g)=1265$ GeV, $m(\tilde\chi^\pm_1)=945$ GeV and $m(\tilde\chi^0_1)=625$ GeV is shown.

Observed and expected background and signal effective mass distributions for SR6jm. For signal, a gluino one-step decay model with $m(\tilde g)=1265$ GeV, $m(\tilde\chi^\pm_1)=945$ GeV and $m(\tilde\chi^0_1)=625$ GeV is shown.

Observed and expected background and signal effective mass distributions for SR6jt. For signal, a gluino one-step decay model with $m(\tilde g)=1385$ GeV, $m(\tilde\chi^\pm_1)=705$ GeV and $m(\tilde\chi^0_1)=25$ GeV is shown.

Expected limit at 95% CL for squark direct decay model grid.

Expected limits at 95% CL +1 sigma excursion due to experimental and background-only theoretical uncertainties for squark direct decay model grid.

Expected limits at 95% CL -1 sigma excursion due to experimental and background-only theoretical uncertainties for squark direct decay model grid.

Observed limits at 95% CL for squark direct decay model grid.

Observed limits at 95% CL +1 sigma excursion due to the signal cross-section uncertainty for squark direct decay model grid.

Observed limits at 95% CL -1 sigma excursion due to the signal cross-section uncertainty for squark direct decay model grid.

Expected limit at 95% CL for gluino direct decay model grid.

Expected limits at 95% CL +1 sigma excursion due to experimental and background-only theoretical uncertainties for gluino direct decay model grid.

Expected limits at 95% CL -1 sigma excursion due to experimental and background-only theoretical uncertainties for gluino direct decay model grid.

Observed limits at 95% CL for gluino direct decay model grid.

Observed limits at 95% CL +1 sigma excursion due to the signal cross-section uncertainty for gluino direct decay model grid.

Observed limits at 95% CL -1 sigma excursion due to the signal cross-section uncertainty for gluino direct decay model grid.

Expected limit at 95% CL for gluino one-step decay model grid.

Expected limits at 95% CL +1 sigma excursion due to experimental and background-only theoretical uncertainties for gluino one-step decay model grid.

Expected limits at 95% CL -1 sigma excursion due to experimental and background-only theoretical uncertainties for gluino one-step decay model grid.

Observed limits at 95% CL for gluino one-step decay model grid.

Observed limits at 95% CL +1 sigma excursion due to the signal cross-section uncertainty for gluino one-step decay model grid.

Observed limits at 95% CL -1 sigma excursion due to the signal cross-section uncertainty for gluino one-step decay model grid.

Observed and expected background effective mass distributions in control region CRgamma for SR2jl.

Observed and expected background effective mass distributions in validation region VRZ for SR2jl.

Observed and expected background effective mass distributions in control region CRW for SR2jl.

Observed and expected background effective mass distributions in control region CRT for SR2jl.

Observed and expected background effective mass distributions in control region CRgamma for SR2jm.

Observed and expected background effective mass distributions in validation region VRZ for SR2jm.

Observed and expected background effective mass distributions in control region CRW for SR2jm.

Observed and expected background effective mass distributions in control region CRT for SR2jm.

Observed and expected background effective mass distributions in control region CRgamma for SR2jt.

Observed and expected background effective mass distributions in validation region VRZ for SR2jt.

Observed and expected background effective mass distributions in control region CRW for SR2jt.

Observed and expected background effective mass distributions in control region CRT for SR2jt.

Observed and expected background effective mass distributions in control region CRgamma for SR4jt.

Observed and expected background effective mass distributions in validation region VRZ for SR4jt.

Observed and expected background effective mass distributions in control region CRW for SR4jt.

Observed and expected background effective mass distributions in control region CRT for SR4jt.

Observed and expected background effective mass distributions in control region CRgamma for SR5j.

Observed and expected background effective mass distributions in validation region VRZ for SR5j.

Observed and expected background effective mass distributions in control region CRW for SR5j.

Observed and expected background effective mass distributions in control region CRT for SR5j.

Observed and expected background effective mass distributions in control region CRgamma for SR6jm.

Observed and expected background effective mass distributions in validation region VRZ for SR6jm.

Observed and expected background effective mass distributions in control region CRW for SR6jm.

Observed and expected background effective mass distributions in control region CRT for SR6jm.

Observed and expected background effective mass distributions in control region CRgamma for SR6jt.

Observed and expected background effective mass distributions in validation region VRZ for SR6jt.

Observed and expected background effective mass distributions in control region CRW for SR6jt.

Observed and expected background effective mass distributions in control region CRT for SR6jt.

Observed and expected event yields in VRZ as a function of signal region.

Observed and expected event yields in VRW as a function of signal region.

Observed and expected event yields in VRWv as a function of signal region.

Observed and expected event yields in VRT as a function of signal region.

Observed and expected event yields in VRTv as a function of signal region.

Observed and expected event yields in VRQa as a function of signal region.

Observed and expected event yields in VRQb as a function of signal region.

Signal acceptance for SR2jl in squark direct decay model grid.

Signal acceptance times efficiency for SR2jl in squark direct decay model grid.

Signal acceptance for SR2jm in squark direct decay model grid.

Signal acceptance times efficiency for SR2jm in squark direct decay model grid.

Signal acceptance for SR2jt in squark direct decay model grid.

Signal acceptance times efficiency for SR2jt in squark direct decay model grid.

Signal acceptance for SR4jt in squark direct decay model grid.

Signal acceptance times efficiency for SR4jt in squark direct decay model grid.

Signal acceptance for SR5j in squark direct decay model grid.

Signal acceptance times efficiency for SR5j in squark direct decay model grid.

Signal acceptance for SR6jm in squark direct decay model grid.

Signal acceptance times efficiency for SR6jm in squark direct decay model grid.

Signal acceptance for SR6jt in squark direct decay model grid.

Signal acceptance times efficiency for SR6jt in squark direct decay model grid.

Signal acceptance for SR2jl in gluino direct decay model grid.

Signal acceptance times efficiency for SR2jl in gluino direct decay model grid.

Signal acceptance for SR2jm in gluino direct decay model grid.

Signal acceptance times efficiency for SR2jm in gluino direct decay model grid.

Signal acceptance for SR2jt in gluino direct decay model grid.

Signal acceptance times efficiency for SR2jt in gluino direct decay model grid.

Signal acceptance for SR4jt in gluino direct decay model grid.

Signal acceptance times efficiency for SR4jt in gluino direct decay model grid.

Signal acceptance for SR5j in gluino direct decay model grid.

Signal acceptance times efficiency for SR5j in gluino direct decay model grid.

Signal acceptance for SR6jm in gluino direct decay model grid.

Signal acceptance times efficiency for SR6jm in gluino direct decay model grid.

Signal acceptance for SR6jt in gluino direct decay model grid.

Signal acceptance times efficiency for SR6jt in gluino direct decay model grid.

Signal acceptance for SR2jl in gluino one-step decay model grid.

Signal acceptance times efficiency for SR2jl in gluino one-step decay model grid.

Signal acceptance for SR2jm in gluino one-step decay model grid.

Signal acceptance times efficiency for SR2jm in gluino one-step decay model grid.

Signal acceptance for SR2j5 in gluino one-step decay model grid.

Signal acceptance times efficiency for SR2jt in gluino one-step decay model grid.

Signal acceptance for SR4jt in gluino one-step decay model grid.

Signal acceptance times efficiency for SR4jt in gluino one-step decay model grid.

Signal acceptance for SR5j in gluino one-step decay model grid.

Signal acceptance times efficiency for SR5j in gluino one-step decay model grid.

Signal acceptance for SR6jm in gluino one-step decay model grid.

Signal acceptance times efficiency for SR6jm in gluino one-step decay model grid.

Signal acceptance for SR6jt in gluino one-step decay model grid.

Signal acceptance times efficiency for SR6jt in gluino one-step decay model grid.

Distribution of $m_\text{T2}^{\chi^2}$ for SRA-T0 after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.

Distribution of $m_\text{T}^{b,\text{max}}$ for SRB-TW after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.

Distribution of $m_\text{T}^{b,\text{max}}$ for SRB-TW after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.

Distribution of $R_\text{ISR}$ for SRC1-5 after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.

Distribution of $R_\text{ISR}$ for SRC1-5 after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.

Distribution of $m_\text{T}^{b,\text{max}}$ for SRD-high after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.

Distribution of $m_\text{T}^{b,\text{max}}$ for SRD-high after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.

Distribution of $H_\text{T}$ for SRE after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.

Distribution of $H_\text{T}$ for SRE after the likelihood fit. The stacked histograms show the SM expectation and the hatched uncertainty band around the SM expectation shows the MC statistical and detector-related systematic uncertainties. A representative signal point is shown for each distribution.

Expected (blue solid line) exclusion limits at 95% CL as a function of stop and LSP masses in the scenario where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Expected (blue solid line) exclusion limits at 95% CL as a function of stop and LSP masses in the scenario where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Observed (red solid line) exclusion limits at 95% CL as a function of stop and LSP masses in the scenario where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Observed (red solid line) exclusion limits at 95% CL as a function of stop and LSP masses in the scenario where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.

Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.

Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.

Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.

Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.

Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.

Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.

Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.

Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.

Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.

Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.

Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.

Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.

Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.

Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.

Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.

Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.

Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.

Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.

Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.

Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.

Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.

Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.

Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses and branching fraction to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ in the Natural SUSY-inspired mixed grid scenario where $m_{\tilde{\chi^{\pm}_{1}}}=m_{\tilde{\chi^{0}_{1}}}$+1 GeV.

Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small tan$\beta$ assumption.

Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small tan$\beta$ assumption.

Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small tan$\beta$ assumption.

Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small tan$\beta$ assumption.

Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small tan$\beta$ assumption.

Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small tan$\beta$ assumption.

Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a large tan$\beta$ assumption.

Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a large tan$\beta$ assumption.

Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a large tan$\beta$ assumption.

Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a large tan$\beta$ assumption.

Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a large tan$\beta$ assumption.

Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a large tan$\beta$ assumption.

Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small right-handed top-squark mass parameter assumption.

Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small right-handed top-squark mass parameter assumption.

Expected exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small right-handed top-squark mass parameter assumption.

Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small right-handed top-squark mass parameter assumption.

Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small right-handed top-squark mass parameter assumption.

Observed exclusion limits at 95% CL as a function of $m_{\tilde{t}}$ and $m_{\tilde{\chi^{0}_{1}}}$ for the pMSSM-inspired non-asymptotic Higgsino simplified model for a small right-handed top-squark mass parameter assumption.

Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a negative value of $\mu$.

Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a negative value of $\mu$.

Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a negative value of $\mu$.

Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a negative value of $\mu$.

Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a negative value of $\mu$.

Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a negative value of $\mu$.

Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a positive value of $\mu$.

Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a positive value of $\mu$.

Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a positive value of $\mu$.

Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a positive value of $\mu$.

Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a positive value of $\mu$.

Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for the Wino NLSP pMSSM model for a positive value of $\mu$.

Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the left-handed top-squark mass parameter scan in the well-tempered pMSSM model.

Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the left-handed top-squark mass parameter scan in the well-tempered pMSSM model.

Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the left-handed top-squark mass parameter scan in the well-tempered pMSSM model.

Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the left-handed top-squark mass parameter scan in the well-tempered pMSSM model.

Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the left-handed top-squark mass parameter scan in the well-tempered pMSSM model.

Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the left-handed top-squark mass parameter scan in the well-tempered pMSSM model.

Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the right-handed top-squark mass parameter scan in the well-tempered pMSSM model.

Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the right-handed top-squark mass parameter scan in the well-tempered pMSSM model.

Expected exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the right-handed top-squark mass parameter scan in the well-tempered pMSSM model.

Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the right-handed top-squark mass parameter scan in the well-tempered pMSSM model.

Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the right-handed top-squark mass parameter scan in the well-tempered pMSSM model.

Observed exclusion limits at 95% CL as a function of $\tilde{t}$ and $\tilde{\chi^{0}_{1}}$ masses for for the right-handed top-squark mass parameter scan in the well-tempered pMSSM model.

Expected exclusion limits at 95% CL exclusion as a function of $\tilde{g}$ and $\tilde{t}$ masses in the scenario where both gluinos decay via $\tilde{g}\to t \tilde{t}\to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.

Expected exclusion limits at 95% CL exclusion as a function of $\tilde{g}$ and $\tilde{t}$ masses in the scenario where both gluinos decay via $\tilde{g}\to t \tilde{t}\to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.

Expected exclusion limits at 95% CL exclusion as a function of $\tilde{g}$ and $\tilde{t}$ masses in the scenario where both gluinos decay via $\tilde{g}\to t \tilde{t}\to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.

Observed exclusion limits at 95% CL exclusion as a function of $\tilde{g}$ and $\tilde{t}$ masses in the scenario where both gluinos decay via $\tilde{g}\to t \tilde{t}\to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.

Observed exclusion limits at 95% CL exclusion as a function of $\tilde{g}$ and $\tilde{t}$ masses in the scenario where both gluinos decay via $\tilde{g}\to t \tilde{t}\to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.

Observed exclusion limits at 95% CL exclusion as a function of $\tilde{g}$ and $\tilde{t}$ masses in the scenario where both gluinos decay via $\tilde{g}\to t \tilde{t}\to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.

Results of the exclusion fits for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ from the combination of SRA, SRB, SRC, SRD and SRE, based on the best expected $CL_s$. The numbers centered on the grid points indicate which of the signal regions gave the best expected $CL_s$ (with 1, 2, 3, 4, 5, 6 corresponding to SRA, SRB, SRC, SRD-low,SR D-high, SRE respectively).

Results of the exclusion fits for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ from the combination of SRA, SRB, SRC, SRD and SRE, based on the best expected $CL_s$. The numbers centered on the grid points indicate which of the signal regions gave the best expected $CL_s$ (with 1, 2, 3, 4, 5, 6 corresponding to SRA, SRB, SRC, SRD-low,SR D-high, SRE respectively).

Results of the exclusion fits for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ from the combination of SRA, SRB, SRC, SRD and SRE, based on the best expected $CL_s$. The numbers centered on the grid points indicate which of the signal regions gave the best expected $CL_s$ (with 1, 2, 3, 4, 5, 6 corresponding to SRA, SRB, SRC, SRD-low,SR D-high, SRE respectively).

Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 0%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).

Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 0%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).

Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 0%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).

Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 25%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).

Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 25%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).

Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 25%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).

Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 50%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).

Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 50%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).

Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 50%. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).

Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 0 (top left), 25% (top right), 50% (middle left), 75% middle right) and 100% (bottom). The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).

Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 0 (top left), 25% (top right), 50% (middle left), 75% middle right) and 100% (bottom). The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).

Results of the exclusion fits in the grid with two stop decay channels: $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV. The results are shown as a function of the branching ratio to $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$: 0 (top left), 25% (top right), 50% (middle left), 75% middle right) and 100% (bottom). The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRC, SRD-low and SRD-high, The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high, 5: SRC).

Results of the exclusion fits in the wino NLSP grid for negative values of $\mu$. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).

Results of the exclusion fits in the wino NLSP grid for negative values of $\mu$. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).

Results of the exclusion fits in the wino NLSP grid for negative values of $\mu$. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).

Results of the exclusion fits in the wino NLSP grid for positive values of $\mu$. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).

Results of the exclusion fits in the wino NLSP grid for positive values of $\mu$. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).

Results of the exclusion fits in the wino NLSP grid for positive values of $\mu$. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).

Results of the exclusion fits in the well-tempered neutralino grid for the $m_{q3L}$ scenario. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).

Results of the exclusion fits in the well-tempered neutralino grid for the $m_{q3L}$ scenario. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).

Results of the exclusion fits in the well-tempered neutralino grid for the $m_{q3L}$ scenario. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).

Results of the exclusion fits in the well-tempered neutralino grid for the $m_{tR}$ scenario. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).

Results of the exclusion fits in the well-tempered neutralino grid for the $m_{tR}$ scenario. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).

Results of the exclusion fits in the well-tempered neutralino grid for the $m_{tR}$ scenario. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 4: SRD-low, 5: SRD-high).

Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenarios with large tan$\beta$ (top left) is shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).

Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenarios with large tan$\beta$ (top left) is shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).

Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenarios with large tan$\beta$ (top left) is shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).

Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenarios with small tan$\beta$ are shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).

Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenarios with small tan$\beta$ are shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).

Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenarios with small tan$\beta$ are shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).

Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenario with a mostly right-handed top squark partner is shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).

Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenario with a mostly right-handed top squark partner is shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).

Results of the exclusion fits in the non-asymptotic higgsino grid with $m(\tilde{\chi^{\pm}_{1}}) - m(\tilde{\chi^{0}_{1}}) = 5$ GeV. A scenario with a mostly right-handed top squark partner is shown. The results are based on taking the signal region with the best expected $CL_s$, using SRA, SRB, SRD-low and SRD-high, where SRA and SRB are the statistical combinations of their respective regions. The numbers centered on the grid points indicate the signal region used (1: SRA, 2: SRB, 3: SRD-low, 4: SRD-high).

Acceptance for SRA-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRA-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRA-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRB-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRB-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRB-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRE for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRE for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRE for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRA-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRA-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRA-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRB-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRB-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRB-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRA-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRA-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRA-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRB-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRB-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRB-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRC1 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRC1 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRC1 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRC2 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRC2 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRC2 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRC3 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRC3 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRC3 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRC4 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRC4 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRC4 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRC5 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRC5 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRC5 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Acceptance for SRD-low for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.

Acceptance for SRD-low for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.

Acceptance for SRD-low for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.

Acceptance for SRD-high for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.

Acceptance for SRD-high for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.

Acceptance for SRE for gluino pair production in the case where both gluinos decay via $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.

Acceptance for SRE for gluino pair production in the case where both gluinos decay via $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.

Efficiencies for SRA-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Efficiencies for SRA-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Efficiencies for SRB-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Efficiencies for SRB-TT for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Efficiencies for SRE for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Efficiencies for SRE for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Efficiencies for SRA-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Efficiencies for SRA-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Efficiencies for SRB-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Efficiencies for SRB-TW for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Efficiencies for SRA-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Efficiencies for SRA-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Efficiencies for SRB-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Efficiencies for SRB-T0 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Efficiencies for SRC1 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Efficiencies for SRC1 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Efficiencies for SRC2 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Efficiencies for SRC2 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Efficiencies for SRC3 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Efficiencies for SRC3 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Efficiencies for SRC4 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Efficiencies for SRC4 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Efficiencies for SRC5 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Efficiencies for SRC5 for top squark pair production in the case where both top squarks decay via $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$.

Efficiencies for SRD-low for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.

Efficiencies for SRD-low for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.

Efficiencies for SRD-high for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.

Efficiencies for SRD-high for the natural SUSY-inspired mixed grid in which two decay modes are considered, the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ and $\tilde{t}\to b \tilde{\chi^{\pm}_{1}} \to b W^{(*)} \tilde{\chi^{0}_{1}}$, with $m(\tilde{\chi^{\pm}_{1}})-m(\tilde{\chi^{0}_{1}}) = 1$ GeV.

Efficiencies for SRE for gluino pair production in the case where both gluinos decay via $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.

Efficiencies for SRE for gluino pair production in the case where both gluinos decay via $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft and $\Delta m(\tilde{t},\tilde{\chi^{0}_{1}})=5$ GeV.

Upper limit cross-section, in femtobarn, for the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ grid.

Upper limit cross-section, in femtobarn, for the $\tilde{t}\to t^{(*)} \tilde{\chi^{0}_{1}}$ grid.

Upper limit cross-section, in femtobarn, for the $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft grid.

Upper limit cross-section, in femtobarn, for the $\tilde{g}\to t \tilde{t} \to t\tilde{\chi^{0}_{1}}+$soft grid.

Cutflow for SRA for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (800,1) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.

Cutflow for SRA for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (800,1) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.

Cutflow SRB for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (600,300) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.

Cutflow SRB for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (600,300) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.

Cutflow for SRC1 and SRC2 for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (250,77) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.

Cutflow for SRC1 and SRC2 for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (250,77) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.

Cutflow for SRC3, SRC4, and SRC5 for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (500,327) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.

Cutflow for SRC3, SRC4, and SRC5 for a signal model with top squark pair production in the case where both top squarks decay via $\tilde{t}_1\to t^{(*)} \tilde\chi^0_1$ with $m(\tilde{t}_1,\tilde\chi^0_1)=$ (500,327) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.

Cutflow for SRD-high for a signal model with bottom squark pair production in the case where both bottom squarks decay via $b\tilde\chi^{\pm}_1\to bW^{(*)} \tilde\chi^0_1$, with $m(\tilde\chi^{\pm}_1)-m(\tilde\chi^0_1) = 1$ GeV with $m(\tilde{b}_1,\tilde\chi^{\pm}_1)=$ (750,200) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.

Cutflow for SRD-high for a signal model with bottom squark pair production in the case where both bottom squarks decay via $b\tilde\chi^{\pm}_1\to bW^{(*)} \tilde\chi^0_1$, with $m(\tilde\chi^{\pm}_1)-m(\tilde\chi^0_1) = 1$ GeV with $m(\tilde{t}_1,\tilde\chi^{\pm}_1)=$ (800,100) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.

Cutflow for SRD-low for a signal model with bottom squark pair production in the case where both bottom squarks decay via $b\tilde\chi^{\pm}_1\to bW^{(*)} \tilde\chi^0_1$, with $m(\tilde\chi^{\pm}_1)-m(\tilde\chi^0_1) = 1$ GeV witht $m(\tilde{b}_1,\tilde\chi^{\pm}_1)=$ (400,200) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.

Cutflow for SRD-low for a signal model with bottom squark pair production in the case where both bottom squarks decay via $b\tilde\chi^{\pm}_1\to bW^{(*)} \tilde\chi^0_1$, with $m(\tilde\chi^{\pm}_1)-m(\tilde\chi^0_1) = 1$ GeV witht $m(\tilde{t}_1,\tilde\chi^{\pm}_1)=$ (600,200) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.

Cutflow for SRE for a signal model with gluino pair production in the case where both gluinos decay via $\tilde{g}\to t\tilde{t}_1\to t\tilde\chi^0_1+$soft and $\Delta m(\tilde{t}_1, \tilde\chi^0_1)=5$ GeV with $m(\tilde{g},\tilde{t}_1)=$ (1700,400) GeV. An integrated luminosity of 36.1 $\mathrm{fb}^{-1}$ is assumed when calculating the weighted yields. For the derivation skim at least one of the following four criteria is required: $H_{\mathrm{T}}$ $>$ 150 GeV; at least one loose electron with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two loose electrons with $p_{\mathrm{T}}$ $>$ 20 GeV; at least one muon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two muons with $p_{\mathrm{T}}$ $>$ 20 GeV; or at least one photon with $p_{\mathrm{T}}$ $>$ 100 GeV or at least two photons with $p_{\mathrm{T}}$ $>$ 50 GeV.

The observed exclusion contour at 95% CL as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$. Masses that are within the contours are excluded. Limits are shown in the case of a higgsino LSP. The results are constrained by the kinematic limits of the top-squark decay into a chargino and a bottom quark (upper diagonal line) and into a neutralino and a top quark (lower diagonal line), respectively.

The expected exclusion contour at 95% CL as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$. Masses that are within the contours are excluded. Limits are shown in the case of a higgsino LSP. The results are constrained by the kinematic limits of the top-squark decay into a chargino and a bottom quark (upper diagonal line) and into a neutralino and a top quark (lower diagonal line), respectively.

The observed exclusion contour at 95% CL as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$. Masses that are within the contours are excluded. Limits are shown for the region $m_{\tilde{t}} - m_{\tilde{\chi}^0_{1,2}, \tilde{\chi}^\pm_{1}} \geq m_\text{top}$ where $B(\tilde{t} \rightarrow b \chi^{+}_{1}) = B(\tilde{t} \rightarrow t \chi^{0}_{1,2}) = 0.5$.

The expected exclusion contour at 95% CL as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$. Masses that are within the contours are excluded. Limits are shown for the region $m_{\tilde{t}} - m_{\tilde{\chi}^0_{1,2}, \tilde{\chi}^\pm_{1}} \geq m_\text{top}$ where $B(\tilde{t} \rightarrow b \chi^{+}_{1}) = B(\tilde{t} \rightarrow t \chi^{0}_{1,2}) = 0.5$.

Observed model-dependent upper limit on the cross section for the $(\tilde{t},\tilde{\chi}^{\pm}_{1})$ signal grid. Limits are shown for $B(\tilde{t} \rightarrow b \chi^{+}_{1})$ equal to unity.

Observed model-dependent upper limit on the cross section for the $(\tilde{t},\tilde{\chi}^{\pm}_{1} / \tilde{\chi}^{0}_{1,2})$ signal grid. Limits are shown in the case of a higgsino LSP. The results are constrained by the kinematic limits of the top-squark decay into a chargino and a bottom quark (upper diagonal line) and into a neutralino and a top quark (lower diagonal line), respectively.

Expected model-dependent upper limit on the cross section for the $(\tilde{t},\tilde{\chi}^{\pm}_{1})$ signal grid. Limits are shown for $B(\tilde{t} \rightarrow b \chi^{+}_{1})$ equal to unity.

Expected model-dependent upper limit on the cross section for the $(\tilde{t},\tilde{\chi}^{\pm}_{1} / \tilde{\chi}^{0}_{1,2})$ signal grid. Limits are shown in the case of a higgsino LSP. The results are constrained by the kinematic limits of the top-squark decay into a chargino and a bottom quark (upper diagonal line) and into a neutralino and a top quark (lower diagonal line), respectively.

Expected background and observed number of events in different jet and $b$-tag multiplicity bins.

Cut flow for a model of top-squark pair production with the top squark decaying to a $b$-quark and a chargino. The chargino decays through the non-zero RPV coupling $\lambda^{''}_{323}$ via a virtual top squark to $bbs$ quark triplets ($m_{\tilde{t}}$ = 800 GeV, $m_{\tilde{\chi}^{\pm}_{1}}$ = 750 GeV). The multijet trigger consists of four jets satisfying $p_{\text{T}}\geq(100)120$ GeV for the 2015-2016 (2017-2018) data period. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed. The numbers in $N_{\text{weighted}}$ are normalized by the integrated luminosity of 139 fb$^{-1}$.

Signal acceptance for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.

Signal acceptance for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.

Signal acceptance for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.

Signal acceptance for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.

Signal acceptance for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.

Signal acceptance for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.

Signal acceptance for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.

Signal acceptance for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.

Signal acceptance for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.

Signal efficiency for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the efficiency given in the table is reported in %.

Signal efficiency for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the efficiency given in the table is reported in %.

Signal efficiency for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the efficiency given in the table is reported in %.

Signal efficiency for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the efficiency given in the table is reported in %.

Signal efficiency for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the efficiency given in the table is reported in %.

Signal efficiency for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the efficiency given in the table is reported in %.

Signal efficiency for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the efficiency given in the table is reported in %.

Signal efficiency for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the efficiency given in the table is reported in %.

Signal efficiency for $\tilde{t} \rightarrow b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the efficiency given in the table is reported in %.

Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.

Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.

Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.

Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.

Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.

Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.

Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.

Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.

Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.

Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.

Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.

Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.

Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.

Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.

Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.

Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.

Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.

Signal acceptance for $\tilde{t} \rightarrow t\tilde{\chi}^{0}_{1,2}(\tilde{\chi}^{0}_{1,2} \rightarrow tbs) / b\tilde{\chi}^{+}_{1}(\tilde{\chi}^{+}_{1} \rightarrow \bar{b}\bar{b}\bar{s}) $ and c.c. model. Please mind that the acceptance given in the table is reported in %.

Distributions in SR-low of the data and post-fit background prediction for p_T^soft/(p_T^soft + m_eff^3ℓ). The SR-low event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.

Distributions in SR-ISR of the data and post-fit background prediction for m_T. The SR-ISR event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.

Distributions in SR-ISR of the data and post-fit background prediction for R(E_T^miss,jets). The SR-ISR event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.

Distributions in SR-ISR of the data and post-fit background prediction for p_T^soft. The SR-ISR event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.

Distributions in SR-ISR of the data and post-fit background prediction for p_T^jets. The SR-ISR event selections are applied for each distribution except for the variable shown, where the selection is indicated by a red arrow. The normalization factor for the WZ background is derived from the background-only estimation described in Section 7. The expected distribution for a benchmark signal model is included for comparison. The first (last) bin includes underflow (overflow). The "Top-quark like" category contains the tt̄, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. The bottom panel shows the ratio of the data to the post-fit background prediction. The hatched bands indicate the combined theoretical, experimental, and MC statistical uncertainties.

Observed exclusion contour on C1N2 production assuming on-shell $W/Z$ decays as a function of the C1/N2 and N1 masses, and derived from the combined fit of low-mass and ISR regions.

Expected exclusion contour on C1N2 production assuming on-shell $W/Z$ decays as a function of the C1/N2 and N1 masses, and derived from the combined fit of low-mass and ISR regions.

Plus 1$\sigma$ uncertainty, varying the signal cross section within its uncertainty, on the observed exclusion contour on C1N2 production assuming on-shell $W/Z$ decays as a function of the C1/N2 and N1 masses, and derived from the combined fit of low-mass and ISR regions.

Minus 1$\sigma$ uncertainty, varying the signal cross section within its uncertainty, on the observed exclusion contour on C1N2 production assuming on-shell $W/Z$ decays as a function of the C1/N2 and N1 masses, and derived from the combined fit of low-mass and ISR regions.

Plus 1$\sigma$ uncertainty, due to uncertainties in the background prediction and experimental uncertainties affecting the signal, on the expected exclusion contour on C1N2 production assuming on-shell $W/Z$ decays as a function of the C1/N2 and N1 masses, and derived from the combined fit of low-mass and ISR regions.

Minus 1$\sigma$ uncertainty, due to uncertainties in the background prediction and experimental uncertainties affecting the signal, on the expected exclusion contour on C1N2 production assuming on-shell $W/Z$ decays as a function of the C1/N2 and N1 masses, and derived from the combined fit of low-mass and ISR regions.

Upper limits on observed wino-bino simplified model signal cross section $\sigma_\text{obs}^\text{95}$.

Upper limits on expected wino-bino simplified model signal cross section $\sigma_\text{exp}^\text{95}$.

Signal acceptance in SR-low, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} \geq 100$ GeV.

Signal efficiency in SR-low, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} \geq 100$ GeV.

Signal acceptance in SR-ISR, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} \geq 100$ GeV.

Signal efficiency in SR-ISR, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} \geq 100$ GeV.

Signal acceptance in SR-low, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} < 100$ GeV.

Signal efficiency in SR-low, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} < 100$ GeV.

Signal acceptance in SR-ISR, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} < 100$ GeV.

Signal efficiency in SR-ISR, for signals with $m(\widetilde{\chi}^{\pm}_{1}/\widetilde{\chi}^{0}_{2}) - m\widetilde{\chi}^{0}_{1} < 100$ GeV.

The observed and expected yields after the background-only fit in the SRs. The normalization factors of the $WZ$ sample for the low-mass and ISR regions are different and are treated separately in the combined fit. \The "Top-quark like" category contains the tt&#772;, Wt, and WW processes while the "Others" category contains backgrounds from triboson production and processes that include a Higgs boson, 3 or more tops, and tops produced in association with W or Z bosons. Combined statistical and systematic uncertainties are presented. The individual uncertainties can be correlated and do not necessarily add in quadrature to equal the total background uncertainty.

Summary of the expected background and data yields in $\text{SR-low}$ and $\text{SR-ISR}$. The second and third columns show the data and total expected background with systematic uncertainties. The fourth column gives the model-independent upper limits at 95\% CL on the visible cross section ($\sigma_\text{vis}$). The fifth and sixth columns give the visible number of observed ($S^{95}_\text{obs}$) and expected ($S^{95}_\text{exp}$) events of a generic beyond-the-SM process, where uncertainties on $S^{95}_\text{exp}$ reflect the $\pm 1 \sigma$ uncertainties on the background estimation. The last column shows the discovery $p$-value and Gaussian significance $Z$ assuming no signal.

Upper limits on observed (expected) wino-bino simplified model signal cross section $\sigma_\text{obs(exp)}^\text{95}$.

Full list of event selections and MC generator-weighted yields and in $\text{SR-ISR}$ for the main $WZ$ background and a representative $\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2}$ signal point of mass 200 GeV and mass splitting $\Delta m = 100$ GeV normalized to 139 fb$^{-1}$. 40000 events were generated.

Full list of event selections and MC generator-weighted yields and in $\text{SR-low}$ for the main $WZ$ background and a representative $\tilde{\chi}^{\pm}_{1}\tilde{\chi}^{0}_{2}$ signal point of mass 200 GeV and mass splitting $\Delta m = 100$ GeV normalized to 139 fb$^{-1}$. 40000 events were generated.

The expected 95% CL exclusion contours for the combined fit of SR-lowMass and SR-highMass for simplified models with combined ${\tilde{\tau}}^{+}_{R,L} {\tilde{\tau}}^{-}_{R,L}$ production.

The observed 95% CL exclusion contours for the combined fit of SR-lowMass and SR-highMass for simplified models with ${\tilde{\tau}}_L {\tilde{\tau}}_L$ only production.

The expected 95% CL exclusion contours for the combined fit of SR-lowMass and SR-highMass for simplified models with ${\tilde{\tau}}_L {\tilde{\tau}}_L$ only production.

Observed 95% CL exclusion limits for simplified models with direct stau pair production in SR-lowMass.

Expected 95% CL exclusion limits for simplified models with direct stau pair production in SR-lowMass.

Observed 95% CL exclusion limits for simplified models with direct stau pair production in SR-highMass.

Expected 95% CL exclusion limits for simplified models with direct stau pair production in SR-highMass.

Signal acceptance in SR highMass for combined stau final states

Signal acceptance in SR lowMass for combined stau final states

Signal efficiency in SR highMass for combined stau final states

Signal efficiency in SR lowMass for combined stau final states

Signal acceptance*efficiency in SR highMass for combined stau final states

Signal acceptance*efficiency in SR lowMass for combined stau final states

Cutflow for two reference points (${\tilde{\tau}}^{+}_{R,L} {\tilde{\tau}}^{-}_{R,L}$ production) in SR. The column labelled $N_{weighted}$ shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$, while $N_{raw}$ in brackets shows the results for the generated number of events. The quoted uncertainties are statistical only. The "Generator filter" includes the requirements that two $\tau$ in the event have ${p}_{T} > 15$ GeV and $|\eta| <$ 2.6. The "Baseline Cut" includes the requirement of two baseline $\tau$ with a minimum value at 0.01 of the boosted decision tree discriminant (JetBDTSigTransMin $>$ 0.01) and ${p}_{T, \tau_{1}} > 50$ GeV and ${p}_{T, \tau_{2}} > 40$ GeV. At the step "Trigger & offline cuts", the following requirements are applied: the event is recorded using the asymmetric di-$\tau$ trigger (di-$\tau$ $E_{T}^{miss}$ trigger) in SR-lowMass (SR-highMass), and the lepton $p_{T}$ and $E_{T}^{miss}$ are required at plateau.

Observed and expected numbers of events in the control and signal regions where all control and signal region bins are included as constraints in the likelihood. The expected event yields of SM processes are given after the background-only fit. The entries marked as "--" are negligible. The uncertainties correspond to the sum in quadrature of statistical and systematic uncertainties. The correlation of systematic uncertainties among control regions and among background processes is fully taken into account.

The post-fit $m_{T2}$ distribution for SR-lowMass. The stacked histograms show the expected SM backgrounds. The multi-jet contribution is estimated from data using the ABCD method. The contributions of multi-jet and $W$+jets events are scaled with the corresponding normalization factors derived from the background-only fit. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distributions from the SUSY reference points are also shown as dashed lines. The last bin includes the overflow events.

The post-fit $m_{T2}$ distribution for SR-highMass. The stacked histograms show the expected SM backgrounds. The multi-jet contribution is estimated from data using the ABCD method. The contributions of multi-jet and $W$+jets events are scaled with the corresponding normalization factors derived from the background-only fit. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distributions from the SUSY reference points are also shown as dashed lines. The last bin includes the overflow events.

The $m_{T2}$ post-fit distributions in the multi-jet background validation region VR-F (lowMass). The stacked histograms show the contribution of each relevant SM process. The multi-jet shape is taken from VR-E in the ABCD method and the normalization is determined by the transfer factor $T$ and rescaled by a correction factor determined by the fit. The hatched bands represent the combined statistical and systematic uncertainties in the sum of the SM backgrounds shown. For illustration, the distributions of the SUSY reference points are also shown as dashed lines.

The $m_{T2}$ post-fit distributions in the multi-jet background validation VR-F (highMass). The stacked histograms show the contribution of each relevant SM process. The multi-jet shape is taken from VR-E in the ABCD method and the normalization is determined by the transfer factor $T$ and rescaled by a correction factor determined by the fit. The hatched bands represent the combined statistical and systematic uncertainties in the sum of the SM backgrounds shown. For illustration, the distributions of the SUSY reference points are also shown as dashed lines.

The $E_{T}^{miss}$ post-fit distributions in the multi-jet background validation region VR-F (lowMass). The stacked histograms show the contribution of each relevant SM process. The multi-jet shape is taken from VR-E in the ABCD method and the normalization is determined by the transfer factor $T$ and rescaled by a correction factor determined by the fit. The hatched bands represent the combined statistical and systematic uncertainties in the sum of the SM backgrounds shown. For illustration, the distributions of the SUSY reference points are also shown as dashed lines.

The $E_{T}^{miss}$ post-fit distributions in the multi-jet background validation region VR-F (highMass). The stacked histograms show the contribution of each relevant SM process. The multi-jet shape is taken from VR-E in the ABCD method and the normalization is determined by the transfer factor $T$ and rescaled by a correction factor determined by the fit. The hatched bands represent the combined statistical and systematic uncertainties in the sum of the SM backgrounds shown. For illustration, the distributions of the SUSY reference points are also shown as dashed lines.

The pre-fit $m_{T2}$ distribution in the $WCR$. The SM backgrounds other than multi-jet production are estimated from MC simulation. The multi-jet contribution is estimated from data using the OS--SS method. The hatched bands represent the combined statistical and systematic uncertainties of the total SM background. For illustration, the distributions of the SUSY reference points are also shown as dashed lines.

The post-fit yields in the $WVR$, $TVRs$, $ZVRs$ and $VVVRs$. The SM backgrounds other than multi-jet production are estimated from MC simulation. The multi-jet contribution is negligible and is estimated from data using the ABCD method, using CRs obtained with the same technique used for the SRs. The hatched bands represent the combined statistical and systematic uncertainties of the total SM background. For illustration, the distributions of the SUSY reference points are also shown as dashed lines. The lower panels show the ratio of data to the SM background estimate.

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 $139~fb^{-1}$.

Efficiency in the Single-bin SR as a function of the M(Sbottom) vs. M(N2) with the $\Delta$ M(N2,N1) $= 130$ GeV. Keep in mind that the efficiency is given in units of $10^{-2}$.

Acceptance in the Multi-bin SR, $\min_{\Theta} < 0.5$ bin as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV. Keep in mind that the acceptance is given in units of $10^{-4}$.

Efficiency in the Multi-bin SR, $\min_{\Theta} < 0.5$ bin as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV. Keep in mind that the efficiency is given in units of $10^{-2}$.

Acceptance in the Multi-bin SR, $0.5 < \min_{\Theta} < 1.0$ bin as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV. Keep in mind that the acceptance is given in units of $10^{-4}$.

Efficiency in the Multi-bin SR, $0.5 < \min_{\Theta} < 1.0$ bin as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV. Keep in mind that the efficiency is given in units of $10^{-2}$.

Acceptance in the Multi-bin SR, $\min_{\Theta} > 1.0$ bin as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV. Keep in mind that the acceptance is given in units of $10^{-4}$.

Efficiency in the Multi-bin SR, $\min_{\Theta} > 1.0$ bin as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV. Keep in mind that the efficiency is given in units of $10^{-2}$.

Observed upper limits on the signal cross section as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV.

Expected upper limits on the signal cross section as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV.

Cutflows for the bechmarl signal point M(Sbottom) = 800 GeV, M(N2) = 180 GeV. Weighted event yields are reported starting with the "Preselection" line, normalized to an integrated luminosity of $139$ fb$^{−1}$.

Comparison of the expected and observed event yields in the signal regions. The top-quark and Z(mumu) background contributions are scaled with the normalization factors obtained from the background-only fit. The other contribution includes all the backgrounds not explicitly listed in the legend (V+jets except Z(mumu)+jets, di-/triboson, multijet). The hatched band indicates the total statistical and systematic uncertainties in the SM background. The contributions from three signal models to the signal regions are also displayed, where the masses M(Sbottom) and M(N2) are given in GeV in the legend. The lower panel shows the significance of the deviation of the observed yield from the expected background yield.

Dominant systematic uncertainties in the background prediction for the signal regions after the fit to the control regions. “Other” includes the uncertainties arising from muons, jet-vertex tagging, modeling of pile-up, the $E_{T}^{miss}$ computation, multijet background, and luminosity. The individual uncertainties can be correlated and do not necessarily add up quadratically to the total uncertainty.

Distributions of $m_{T2}$ in VR-top-low for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow.

Distributions of $m_{T2}$ in VR-top-high for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow.

Distributions of $E_T^{miss}$ in VR-WW-0J for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow.

Distributions of $E_T^{miss}$ in VR-WW-1J for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow.

Distributions of $E_T^{miss}$ significance in VR-VZ for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow.

Distributions of $E_T^{miss}$ significance in VR-top-WW for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow.

Breakdown of the dominant systematic uncertainties on background estimates in the inclusive SRs requiring $m_{T2}$>100 GeV after performing the profile likelihood fit. Note that the individual uncertainties can be correlated, and do not necessarily add up quadratically to the total background uncertainty. The percentages show the size of the uncertainty relative to the total expected background. "Top theoretical uncertainties" refers to $t\bar t$ theoretical uncertainties and the uncertainty associated to $Wt-t\bar t$ interference added quadratically.

Observed events and predicted post-fit background yields for the DF inclusive SRs. The model independent upper limits at 95% confidence level (CL) on the observed and expected number of beyond the SM events $S^{0.95}_{obs/exp}$ and the effective beyond the SM cross-section $\sigma^{0.95}_{obs}$ are also reported. The last row reports the $p_0$-value of the SM-only hypothesis. For SRs where the data yield is smaller than expected, the $p$-value is truncated at 0.50. The background denoted as "Other" in the Table includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$+V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.

Observed events and predicted post-fit background yields for the DF inclusive SRs. The model independent upper limits at 95% confidence level (CL) on the observed and expected number of beyond the SM events $S^{0.95}_{obs/exp}$ and the effective beyond the SM cross-section $\sigma^{0.95}_{obs}$ are also reported. The last row reports the $p_0$-value of the SM-only hypothesis. For SRs where the data yield is smaller than expected, the $p$-value is truncated at 0.50. The background denoted as "Other" in the Table includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$+V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.

Observed events and predicted post-fit background yields for the SF inclusive SRs. The model independent upper limits at 95% confidence level (CL) on the observed and expected number of beyond the SM events $S^{0.95}_{obs/exp}$ and the effective beyond the SM cross-section $\sigma^{0.95}_{obs}$ are also reported. The last row reports the $p_0$-value of the SM-only hypothesis. For SRs where the data yield is smaller than expected, the $p$-value is truncated at 0.50. The background denoted as "Other" in the Table includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$+V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.

Observed events and predicted post-fit background yields for the SF inclusive SRs. The model independent upper limits at 95% confidence level (CL) on the observed and expected number of beyond the SM events $S^{0.95}_{obs/exp}$ and the effective beyond the SM cross-section $\sigma^{0.95}_{obs}$ are also reported. The last row reports the $p_0$-value of the SM-only hypothesis. For SRs where the data yield is smaller than expected, the $p$-value is truncated at 0.50. The background denoted as "Other" in the Table includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$+V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.

Distributions of $m_{T2}$ in SRSF-0J for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow. Distributions for three benchmark signal points are overlaid for comparison.

Distributions of $m_{T2}$ in SRSF-1J for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow. Distributions for three benchmark signal points are overlaid for comparison.

Distributions of $m_{T2}$ in SRDF-0J for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow. Distributions for three benchmark signal points are overlaid for comparison.

Distributions of $m_{T2}$ in SRDF-1J for data and the estimated SM backgrounds. The normalisation factors extracted from the corresponding CRs are used to rescale the $t\bar t$, single top, WW, WZ and ZZ backgrounds. The fake and non-prompt leptons background (FNP) is calculated using the data-driven matrix method. The uncertainty band includes all sources of systematic and statistical errors and the last bin includes the overflow. Distributions for three benchmark signal points are overlaid for comparison.

Observed exclusion limits on SUSY simplified models for chargino-pair production with $W$ boson mediated decays. All limits are computed at 95% CL.

Expected exclusion limits on SUSY simplified models for chargino-pair production with $W$ boson mediated decays. All limits are computed at 95% CL.

Observed exclusion limits on SUSY simplified models for chargino-pair production with slepton/sneutrino mediated mediated decays. The mass relation $m(\tilde{l}_L)=\frac{1}{2}[m(\tilde{\chi}^{\pm}_1 + m(\tilde{\chi}^{0}_1)]$ is assumed. All limits are computed at 95% CL.

Expected exclusion limits on SUSY simplified models for chargino-pair production with slepton/sneutrino mediated mediated decays. The mass relation $m(\tilde{l}_L)=\frac{1}{2}[m(\tilde{\chi}^{\pm}_1 + m(\tilde{\chi}^{0}_1)]$ is assumed. All limits are computed at 95% CL.

Observed exclusion limits on SUSY simplified models for slepton-pair production. All limits are computed at 95% CL.

Expected exclusion limits on SUSY simplified models for slepton-pair production. All limits are computed at 95% CL.

Observed exclusion limits on SUSY simplified models for selectron-pair production, with left and right handed selectron production combined. All limits are computed at 95% CL.

Expected exclusion limits on SUSY simplified models for selectron-pair production, with left and right handed selectron production combined. All limits are computed at 95% CL.

Observed exclusion limits on SUSY simplified models for left-handed selectron-pair production. All limits are computed at 95% CL.

Expected exclusion limits on SUSY simplified models for left-handed selectron-pair production. All limits are computed at 95% CL.

Observed exclusion limits on SUSY simplified models for right-handed selectron-pair production. All limits are computed at 95% CL.

Expected exclusion limits on SUSY simplified models for right-handed selectron-pair production. All limits are computed at 95% CL.

Observed exclusion limits on SUSY simplified models for smuon-pair production, with left and right handed smuon production combined. All limits are computed at 95% CL.

Expected exclusion limits on SUSY simplified models for smuon-pair production, with left and right handed smuon production combined. All limits are computed at 95% CL.

Observed exclusion limits on SUSY simplified models for left-handed smuon-pair production. All limits are computed at 95% CL.

Expected exclusion limits on SUSY simplified models for left-handed smuon-pair production. All limits are computed at 95% CL.

Observed exclusion limits on SUSY simplified models for right-handed smuon-pair production. All limits are computed at 95% CL.

Expected exclusion limits on SUSY simplified models for right-handed smuon-pair production. All limits are computed at 95% CL.

Observed events and predicted background yields from the fit in the binned DF SRs with $n_{non-b-tagged jets}=0$. For backgrounds whose normalisation is extracted from the fit in the CRs, the yield expected from the simulation before the fit is also reported. The background denoted as "Other" in the Table includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$ +V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.

Observed events and predicted background yields from the fit in the binned DF SRs with $n_{non-b-tagged jets}=1$. For backgrounds whose normalisation is extracted from the fit in the CRs, the yield expected from the simulation before the fit is also reported. The background denoted as "Other" in the Table includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$ +V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.

Observed events and predicted background yields from the fit in the binned SF SRs with $n_{non-b-tagged jets}=0$. For backgrounds whose normalisation is extracted from the fit in the CRs, the yield expected from the simulation before the fit is also reported. The background denoted as "Other" in the Table includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$ +V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.

Observed events and predicted background yields from the fit in the binned SF SRs with $n_{non-b-tagged jets}=1$. For backgrounds whose normalisation is extracted from the fit in the CRs, the yield expected from the simulation before the fit is also reported. The background denoted as "Other" in the Table includes the non-dominant background sources for this analysis, i.e. Z+jets, $t\bar t$ +V, Higgs and Drell-Yan events. A "–" symbol indicates that the background contribution is negligible.

Observed exclusion limits on SUSY simplified models for left-handed slepton-pair production. All limits are computed at 95% CL.

Expected exclusion limits on SUSY simplified models for left-handed slepton-pair production. All limits are computed at 95% CL.

Observed exclusion limits on SUSY simplified models for right-handed slepton-pair production. All limits are computed at 95% CL.

Expected exclusion limits on SUSY simplified models for right-handed slepton-pair production. All limits are computed at 95% CL.

Upper limits on signal cross-section (fb) for chargino-pair production with W -boson-mediated decays.

Upper limits on signal cross-section (fb) for chargino-pair production with slepton/sneutrino-mediated decays. The mass relation $m(\tilde{l}_L)=\frac{1}{2}[m(\tilde{\chi}^{\pm}_1 + m(\tilde{\chi}^{0}_1)]$ is assumed.

Upper limits on signal cross-section (fb) for slepton-pair production.

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[100,inf).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[100,inf).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[100,inf).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[100,inf).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[100,inf).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[100,inf).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[100,inf).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[100,inf).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[160,inf).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[160,inf).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[160,inf).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[160,inf).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[160,inf).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[160,inf).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[160,inf).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[160,inf).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[100,120).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[100,120).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[100,120).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[100,120).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[100,120).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[100,120).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[100,120).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[100,120).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[120,160).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[120,160).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[120,160).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[120,160).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[120,160).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[120,160).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[120,160).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[120,160).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[100,105).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[100,105).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[100,105).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[100,105).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[100,105).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[100,105).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[100,105).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[100,105).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[105,110).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[105,110).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[105,110).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[105,110).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[105,110).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[105,110).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[105,110).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[105,110).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[110,120).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[110,120).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[110,120).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[110,120).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[110,120).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[110,120).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[110,120).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[110,120).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[120,140).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[120,140).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[120,140).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[120,140).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[120,140).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[120,140).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[120,140).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[120,140).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[140,160).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[140,160).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[140,160).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[140,160).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[140,160).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[140,160).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[140,160).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[140,160).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[160,180).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[160,180).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[160,180).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[160,180).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[160,180).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[160,180).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[160,180).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[160,180).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[180,220).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[180,220).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[180,220).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[180,220).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[180,220).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[180,220).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[180,220).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[180,220).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[220,260).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[220,260).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[220,260).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[220,260).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[220,260).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[220,260).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[220,260).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[220,260).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[260,inf).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-0J-[260,inf).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[260,inf).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-SF-1J-[260,inf).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[260,inf).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-0J-[260,inf).

Signal Acceptance for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[260,inf).

Signal Efficiency for direct chargino-pair production with W-boson mediated decays in SR-DF-1J-[260,inf).

Cutflow for supersymmetric model where $\tilde{\chi}_1^{\pm}\tilde{\chi}_1^{\mp}$ decay via $W^{\pm}W^{\mp}$. The masses of the two charginos are 300 GeV, while the mass of $\tilde{\chi}_1^{0}$ is 50 GeV. The numbers are normalised to the luminosity of 139~fb$^{-1}$.

Cutflow for supersymmetric model where $\tilde{\chi}_1^{\pm}\tilde{\chi}_1^{\mp}$ decay via slepton-neutrino/sneutrino-lepton pair. The masses of the two charginos are 600 GeV, while the mass of $\tilde{\chi}_1^{0}$ is 1 GeV. The slepton/sneutrino masses are 300 GeV. The numbers are normalised to the luminosity of 139~fb$^{-1}$.

Cutflow for supersymmetric model where $\tilde\ell\tilde\ell$ are produced. Only $\tilde{e}$ and $\tilde{\mu}$ are considered in this model. The masses of the two sleptons are 400 GeV, while the mass of $\tilde{\chi}_1^{0}$ is 200 GeV. The numbers are normalised to the luminosity of 139~fb$^{-1}$.

The post-fit $m_{CT}$ distribution is shown in the validation region VR-onLM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.

The post-fit $m_{CT}$ distribution is shown in the validation region VR-onMM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.

The post-fit $m_{CT}$ distribution is shown in the validation region VR-onMM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.

The post-fit $m_{CT}$ distribution is shown in the validation region VR-onMM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.

The post-fit $m_{CT}$ distribution is shown in the validation region VR-onMM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.

The post-fit $m_{CT}$ distribution is shown in the validation region VR-onHM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.

The post-fit $m_{CT}$ distribution is shown in the validation region VR-onHM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.

The post-fit $m_{CT}$ distribution is shown in the validation region VR-onHM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.

The post-fit $m_{CT}$ distribution is shown in the validation region VR-onHM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.

The post-fit $m_{CT}$ distribution is shown in the validation region VR-offLM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.

The post-fit $m_{CT}$ distribution is shown in the validation region VR-offLM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.

The post-fit $m_{CT}$ distribution is shown in the validation region VR-offLM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.

The post-fit $m_{CT}$ distribution is shown in the validation region VR-offLM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.

The post-fit $m_{CT}$ distribution is shown in the validation region VR-offMM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.

The post-fit $m_{CT}$ distribution is shown in the validation region VR-offMM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.

The post-fit $m_{CT}$ distribution is shown in the validation region VR-offMM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.

The post-fit $m_{CT}$ distribution is shown in the validation region VR-offMM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.

The post-fit $m_{CT}$ distribution is shown in the validation region VR-offHM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.

The post-fit $m_{CT}$ distribution is shown in the validation region VR-offHM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.

The post-fit $m_{CT}$ distribution is shown in the validation region VR-offHM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.

The post-fit $m_{CT}$ distribution is shown in the validation region VR-offHM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.

The post-fit $m_{CT}$ distribution for SR-HM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.

The post-fit $m_{CT}$ distribution for SR-HM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.

The post-fit $m_{CT}$ distribution for SR-HM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.

The post-fit $m_{CT}$ distribution for SR-HM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.

The post-fit $m_{CT}$ distribution for SR-MM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.

The post-fit $m_{CT}$ distribution for SR-MM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.

The post-fit $m_{CT}$ distribution for SR-MM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.

The post-fit $m_{CT}$ distribution for SR-MM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.

The post-fit $m_{CT}$ distribution for SR-LM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.

The post-fit $m_{CT}$ distribution for SR-LM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.

The post-fit $m_{CT}$ distribution for SR-LM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.

The post-fit $m_{CT}$ distribution for SR-LM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.

The post-fit $m_{bb}$ distribution is shown in the signal region SR-HM after all the selection requirements are applied other than the $m_{bb}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection.The overflow events, where present, are included in the last bin.

The post-fit $m_{bb}$ distribution is shown in the signal region SR-HM after all the selection requirements are applied other than the $m_{bb}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection.The overflow events, where present, are included in the last bin.

The post-fit $m_{bb}$ distribution is shown in the signal region SR-HM after all the selection requirements are applied other than the $m_{bb}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection.The overflow events, where present, are included in the last bin.

The post-fit $m_{bb}$ distribution is shown in the signal region SR-HM after all the selection requirements are applied other than the $m_{bb}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection.The overflow events, where present, are included in the last bin.

The post-fit $m_{bb}$ distribution is shown in the signal region SR-MM after all the selection requirements are applied other than the $m_{bb}$ cut. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection. The overflow events, where present, are included in the last bin.

The post-fit $m_{bb}$ distribution is shown in the signal region SR-MM after all the selection requirements are applied other than the $m_{bb}$ cut. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection. The overflow events, where present, are included in the last bin.

The post-fit $m_{bb}$ distribution is shown in the signal region SR-MM after all the selection requirements are applied other than the $m_{bb}$ cut. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection. The overflow events, where present, are included in the last bin.

The post-fit $m_{bb}$ distribution is shown in the signal region SR-MM after all the selection requirements are applied other than the $m_{bb}$ cut. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection. The overflow events, where present, are included in the last bin.

The post-fit $m_{bb}$ distribution is shown in the signal region SR-LM after all the selection requirements are applied other than the $m_{bb}$ cut. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection. The overflow events, where present, are included in the last bin.

The post-fit $m_{bb}$ distribution is shown in the signal region SR-LM after all the selection requirements are applied other than the $m_{bb}$ cut. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection. The overflow events, where present, are included in the last bin.

The post-fit $m_{bb}$ distribution is shown in the signal region SR-LM after all the selection requirements are applied other than the $m_{bb}$ cut. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection. The overflow events, where present, are included in the last bin.

The post-fit $m_{bb}$ distribution is shown in the signal region SR-LM after all the selection requirements are applied other than the $m_{bb}$ cut. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection. The overflow events, where present, are included in the last bin.

The observed exclusion for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. Experimental and theoretical systematic uncertainties are applied to background and signal samples and illustrated by the yellow band and the red dotted contour lines, respectively. The red dotted lines indicate the $\pm$ 1 standard-deviation variation on the observed exclusion limit due to theoretical uncertainties in the signal cross-section.

The observed exclusion for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. Experimental and theoretical systematic uncertainties are applied to background and signal samples and illustrated by the yellow band and the red dotted contour lines, respectively. The red dotted lines indicate the $\pm$ 1 standard-deviation variation on the observed exclusion limit due to theoretical uncertainties in the signal cross-section.

The observed exclusion for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. Experimental and theoretical systematic uncertainties are applied to background and signal samples and illustrated by the yellow band and the red dotted contour lines, respectively. The red dotted lines indicate the $\pm$ 1 standard-deviation variation on the observed exclusion limit due to theoretical uncertainties in the signal cross-section.

The observed exclusion for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. Experimental and theoretical systematic uncertainties are applied to background and signal samples and illustrated by the yellow band and the red dotted contour lines, respectively. The red dotted lines indicate the $\pm$ 1 standard-deviation variation on the observed exclusion limit due to theoretical uncertainties in the signal cross-section.

The observed exclusion up limit for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. The red dotted lines indicate the $\pm 1 \sigma$ on the observed exclusion limit due to the theoretical uncertainties in the signal cross-section.

The observed exclusion up limit for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. The red dotted lines indicate the $\pm 1 \sigma$ on the observed exclusion limit due to the theoretical uncertainties in the signal cross-section.

The observed exclusion up limit for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. The red dotted lines indicate the $\pm 1 \sigma$ on the observed exclusion limit due to the theoretical uncertainties in the signal cross-section.

The observed exclusion up limit for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. The red dotted lines indicate the $\pm 1 \sigma$ on the observed exclusion limit due to the theoretical uncertainties in the signal cross-section.

The observed exclusion down limit for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. The red dotted lines indicate the $\pm 1 \sigma$ on the observed exclusion limit due to the theoretical uncertainties in the signal cross-section.

The observed exclusion down limit for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. The red dotted lines indicate the $\pm 1 \sigma$ on the observed exclusion limit due to the theoretical uncertainties in the signal cross-section.

The observed exclusion down limit for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. The red dotted lines indicate the $\pm 1 \sigma$ on the observed exclusion limit due to the theoretical uncertainties in the signal cross-section.

The observed exclusion down limit for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. The red dotted lines indicate the $\pm 1 \sigma$ on the observed exclusion limit due to the theoretical uncertainties in the signal cross-section.

The expected exclusion for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. Experimental and theoretical systematic uncertainties are applied to background and signal samples and illustrated by the yellow band and the red dotted contour lines, respectively. The red dotted lines indicate the $\pm$ 1 standard-deviation variation on the observed exclusion limit due to theoretical uncertainties in the signal cross-section.

The expected exclusion for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. Experimental and theoretical systematic uncertainties are applied to background and signal samples and illustrated by the yellow band and the red dotted contour lines, respectively. The red dotted lines indicate the $\pm$ 1 standard-deviation variation on the observed exclusion limit due to theoretical uncertainties in the signal cross-section.

The expected exclusion for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. Experimental and theoretical systematic uncertainties are applied to background and signal samples and illustrated by the yellow band and the red dotted contour lines, respectively. The red dotted lines indicate the $\pm$ 1 standard-deviation variation on the observed exclusion limit due to theoretical uncertainties in the signal cross-section.

The expected exclusion for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. Experimental and theoretical systematic uncertainties are applied to background and signal samples and illustrated by the yellow band and the red dotted contour lines, respectively. The red dotted lines indicate the $\pm$ 1 standard-deviation variation on the observed exclusion limit due to theoretical uncertainties in the signal cross-section.

Upper limits on the cross sections for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Upper limits on the cross sections for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Upper limits on the cross sections for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Upper limits on the cross sections for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-LM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-LM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-LM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-LM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-LM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-LM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-LM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-LM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-LM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-LM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-LM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-LM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-LM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-LM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-LM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-LM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-MM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-MM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-MM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-MM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-MM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-MM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-MM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-MM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-MM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-MM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-MM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-MM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-MM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-MM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-MM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-MM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-HM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. 1lb\bar{b}$ production

Signal acceptance in SR-HM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. 1lb\bar{b}$ production

Signal acceptance in SR-HM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. 1lb\bar{b}$ production

Signal acceptance in SR-HM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. 1lb\bar{b}$ production

Signal acceptance in SR-HM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-HM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-HM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-HM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-HM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-HM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-HM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-HM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-HM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-HM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-HM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-HM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-LM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-LM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-LM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-LM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-LM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-LM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-LM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-LM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-LM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-LM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-LM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-LM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-LM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-LM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-LM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-LM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-MM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-MM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-MM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-MM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-MM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-MM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-MM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-MM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-MM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-MM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-MM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-MM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-MM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-MM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-MM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-MM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-HM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-HM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-HM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-HM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-HM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-HM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-HM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-HM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-HM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-HM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-HM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-HM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-HM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-HM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-HM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-HM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Event selection cutflow for a representative signal sample for the SR-LM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-LM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-LM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-LM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-LM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-LM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-LM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-LM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-LM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-LM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-LM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-LM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-MM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-MM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-MM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-MM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-MM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-MM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-MM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-MM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-MM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-MM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-MM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-MM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-HM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-HM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-HM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-HM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-HM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-HM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-HM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-HM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-HM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-HM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-HM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-HM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the discovery SR-LM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the discovery SR-LM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the discovery SR-LM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the discovery SR-LM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the discovery SR-MM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the discovery SR-MM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the discovery SR-MM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the discovery SR-MM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the discovery SR-HM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the discovery SR-HM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the discovery SR-HM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the discovery SR-HM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.