Transverse momentum distribution for the second leading lepton for events in the SR2 signal region for DATA and SM predictions.

Transverse momentum distribution for the third leading lepton for events in the SR1 signal region for DATA and SM predictions.

Transverse momentum distribution for the third leading lepton for events in the SR2 signal region for DATA and SM predictions.

Missing transverse energy for events in the SR1 signal region for DATA and SM predictions.

Missing transverse energy for events in the SR2 signal region for DATA and SM predictions.

Invariant mass of the same-flavour-opposite-sign (SFOS) lepton pair for events in the SR1 signal region for DATA and SM predictions.

The Cross Section in signal region SR1 for the SUSY pMSSM model with M1=100 GeV grid.

The Cross Section in signal region SR1 for the SUSY simplified model grid.

The Number of generated Events in signal region SR1 for the SUSY pMSSM model with M1=100 GeV grid.

The Number of generated Events in signal region SR1 for the SUSY simplified model grid.

The Efficiency in signal region SR1 for the SUSY pMSSM model with M1=100 GeV grid.

The Efficiency in signal region SR1 for the SUSY simplified model grid.

The Acceptance in signal region SR1 for the SUSY pMSSM model with M1=100 GeV grid.

The Acceptance in signal region SR1 for the SUSY simplified model grid.

The Acceptance*Efficiency in signal region SR1 for the SUSY pMSSM model with M1=100 GeV grid.

The Acceptance*Efficiency in signal region SR1 for the SUSY simplified model grid.

The Systematic Uncertainty of the data (excluding the Monte Carlo) in signal region SR1 for the SUSY pMSSM model with M1=100 GeV grid.

The Systematic Uncertainty of the data (excluding the Monte Carlo) in signal region SR1 for the SUSY simplified model grid.

CL values for the pMSSM with M1=100 GeV model grid for the SR1 signal region.

CL values for the simplified model model grid for the SR1 signal region.

(1) Number of generated MC events for the spin 1/2 top partner signal grid (2) Relative Cross section uncertainties for the spin 1/2 top partner signal grid.

(1) Acceptance of the same flavour selection for the spin 1/2 top partner signal grid (2) Selection efficiency of the same flavour selection for the spin 1/2 top partner signal grid (3) Product of the acceptance and efficiency of the same flavour selection for the spin 1/2 top partner signal grid (4) Relative experimental uncertainties on the acceptance times efficiency of the same flavour selection for the spin 1/2 top partner signal grid.

(1) Acceptance of the different flavour selection for the spin 1/2 top partner signal grid (2) Selection efficiency of the different flavour selection for the spin 1/2 top partner signal grid (3) Product of the acceptance and efficiency of the different flavour selection for the spin 1/2 top partner signal grid (4) Relative experimental uncertainties on the acceptance times efficiency of the different flavour selection for the spin 1/2 top partner signal grid.

(1) Observed CLs values for the scalar top signal grid (2) Expected CLs values for the scalar top signal grid.

(1) Observed CLs values for the spin 1/2 top partner signal grid (2) Expected CLs values for the spin 1/2 top partner signal grid.

Cross section limits [pb] for the scalar top signal grid.

Cross section limits [pb] for the spin 1/2 top partner signal grid.

Observed 95% CL limit for stop grid as a function of the scalar top and neutralino masses.

Observed 95% CL limit for stop grid as a function of the scalar top and neutralino masses, varying signal cross section of +1sigma.

Observed 95% CL limit for stop grid as a function of the scalar top and neutralino masses, varying signal cross section of -1sigma.

Expected 95% CL limit for stop grid as a function of the scalar top and neutralino masses.

Expected 95% CL limit for stop grid as a function of the scalar top and neutralino masses, varying the uncertainty of +1sigma.

Expected 95% CL limit for stop grid as a function of the scalar top and neutralino masses, varying the uncertainty of -1sigma.

Observed 95% CL limit for top partner grid as a function of the top partner and neutralino masses.

Observed 95% CL limit for top partner grid as a function of the top partner and neutralino masses, varying signal cross section of +1sigma.

Observed 95% CL limit for top partner grid as a function of the top partner and neutralino masses, varying signal cross section of -1sigma.

Expected 95% CL limit for top partner grid as a function of the top partner and neutralino masses.

Expected 95% CL limit for top partner grid as a function of the top partner and neutralino masses, varying the uncertainty of +1sigma.

Expected 95% CL limit for top partner grid as a function of the top partner and neutralino masses, varying the uncertainty of -1sigma.

The expected limit contour in the GLUINO-NEUTRALINO plane.

The observed limit contour in the SQUARK-NEUTRALINO plane.

The expected limit contour in the SQUARK-NEUTRALINO plane.

The stop pair production cross section and its uncertainty due to PDF, factorization and the renormalization scales.

1$\tau$ MediumMass SR eff.

2$\tau$ Compressed SR eff.

2$\tau$ Compressed SR eff.

2$\tau$ HighMass SR eff.

2$\tau$ HighMass SR eff.

2$\tau$ multibin SR eff.

2$\tau$ multibin SR eff.

2$\tau$ GMSB SR eff.

2$\tau$ GMSB SR eff.

1$\tau$ Compressed SR eff.

1$\tau$ Compressed SR eff.

1$\tau$ MediumMass SR eff.

1$\tau$ MediumMass SR eff.

2$\tau$ Compressed SR eff.

2$\tau$ Compressed SR eff.

2$\tau$ HighMass SR eff.

2$\tau$ HighMass SR eff.

2$\tau$ multibin SR eff.

2$\tau$ multibin SR eff.

2$\tau$ GMSB SR eff.

2$\tau$ GMSB SR eff.

1$\tau$ Compressed SR acceptance.

1$\tau$ Compressed SR acceptance.

1$\tau$ MediumMass SR acceptance.

1$\tau$ MediumMass SR acceptance.

2$\tau$ Compressed SR acceptance.

2$\tau$ Compressed SR acceptance.

2$\tau$ HighMass SR acceptance.

2$\tau$ HighMass SR acceptance.

2$\tau$ multibin SR acceptance.

2$\tau$ multibin SR acceptance.

2$\tau$ GMSB SR acceptance.

2$\tau$ GMSB SR acceptance.

1$\tau$ Compressed SR acceptance.

1$\tau$ Compressed SR acceptance.

1$\tau$ MediumMass SR acceptance.

1$\tau$ MediumMass SR acceptance.

2$\tau$ Compressed SR acceptance.

2$\tau$ Compressed SR acceptance.

2$\tau$ HighMass SR acceptance.

2$\tau$ HighMass SR acceptance.

2$\tau$ multibin SR acceptance.

2$\tau$ multibin SR acceptance.

2$\tau$ GMSB SR acceptance.

2$\tau$ GMSB SR acceptance.

Cutflow table of the $1\tau$ compressed SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $1\tau$ compressed SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $1\tau$ medium-mass SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $1\tau$ medium-mass SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $2\tau$ compressed SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $2\tau$ compressed SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $2\tau$ high-mass SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $2\tau$ high-mass SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $2\tau$ multibin SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $2\tau$ multibin SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $2\tau$ GMSB SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Cutflow table of the $2\tau$ GMSB SR for the four signal benchmark scenarios of low, medium, and high mass-splitting in the simplified model as well as the GMSB model.

Best performing fit setups entering the final combination as a function of the LSP mass and the gluino mass. 'S' marks the simultaneous fit of the four simplified model single-bin SRs, 'M' denotes the simultaneous fit of the two $1\tau$ SRs and the $2\tau$ multibin SR.

Best performing fit setups entering the final combination as a function of the LSP mass and the gluino mass. 'S' marks the simultaneous fit of the four simplified model single-bin SRs, 'M' denotes the simultaneous fit of the two $1\tau$ SRs and the $2\tau$ multibin SR.

Observed exclusion contour at 95% CL as a function of tanBeta and the SUSY-breaking mass scale Lambda.

Observed exclusion contour at 95% CL as a function of tanBeta and the SUSY-breaking mass scale Lambda.

Expected exclusion contour at 95% CL as a function of tanBeta and the SUSY-breaking mass scale Lambda.

Expected exclusion contour at 95% CL as a function of tanBeta and the SUSY-breaking mass scale Lambda.

Observed exclusion contour at 95% CL as a function of the LSP mass and the gluino mass.

Observed exclusion contour at 95% CL as a function of the LSP mass and the gluino mass.

Expected exclusion contour at 95% CL as a function of the LSP mass and the gluino mass.

Expected exclusion contour at 95% CL as a function of the LSP mass and the gluino mass.

Observed upper limits on the production cross section at 95% CL in pb as a function of tanBeta and SUSY breaking mass scale Lambda.

Observed upper limits on the production cross section at 95% CL in pb as a function of tanBeta and SUSY breaking mass scale Lambda.

Observed upper limits on the production cross section at 95% CL in pb as a function of the LSP mass and the gluino mass.

Observed upper limits on the production cross section at 95% CL in pb as a function of the LSP mass and the gluino mass.

Yields of the expected background from the SM in the bins of the multibin SR of the $2\tau$ channel with all bins being simultaneously used to constrain the background prediction. Expectation is given with the scalings computed in the combined fit applied. Uncertainties are statistial plus systematrics. Only the subsamples contributing the respective region are considered.

Yields of the expected background from the SM in the bins of the multibin SR of the $2\tau$ channel with all bins being simultaneously used to constrain the background prediction. Expectation is given with the scalings computed in the combined fit applied. Uncertainties are statistial plus systematrics. Only the subsamples contributing the respective region are considered.

$m_{\mathrm{T}}^{\tau}$ in the compressed $m_{\mathrm{T}}^{\tau}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$m_{\mathrm{T}}^{\tau}$ in the compressed $m_{\mathrm{T}}^{\tau}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$E_{\mathrm{T}}^{\mathrm{miss}}$ in the compressed $E_{\mathrm{T}}^{\mathrm{miss}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$E_{\mathrm{T}}^{\mathrm{miss}}$ in the compressed $E_{\mathrm{T}}^{\mathrm{miss}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$m_{\mathrm{T}}^{\tau}$ in the medium-mass $m_{\mathrm{T}}^{\tau}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$m_{\mathrm{T}}^{\tau}$ in the medium-mass $m_{\mathrm{T}}^{\tau}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$E_{\mathrm{T}}^{\mathrm{miss}}$ in the medium-mass $E_{\mathrm{T}}^{\mathrm{miss}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$E_{\mathrm{T}}^{\mathrm{miss}}$ in the medium-mass $E_{\mathrm{T}}^{\mathrm{miss}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$H_{\mathrm{T}}$ in the medium-mass $H_{\mathrm{T}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$H_{\mathrm{T}}$ in the medium-mass $H_{\mathrm{T}}$ VR of the $1\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$m_{\mathrm{T}}^{\tau_1}$ + $m_{\mathrm{T}}^{\tau_2}$ in the top VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$m_{\mathrm{T}}^{\tau_1}$ + $m_{\mathrm{T}}^{\tau_2}$ in the top VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$H_{\mathrm{T}}$ in the $W$ VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$H_{\mathrm{T}}$ in the $W$ VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$m_{\mathrm{T}}^{\tau_1}$ + $m_{\mathrm{T}}^{\tau_2}$ in the $Z$ VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$m_{\mathrm{T}}^{\tau_1}$ + $m_{\mathrm{T}}^{\tau_2}$ in the $Z$ VR of the $2\tau$ channel, illustrating the background modeling after the fit. The last bin includes overflow events.

$m_{\mathrm{T}}^{\tau}$ in the compressed SR of the $1\tau$ channel before application of the $m_{\mathrm{T}}^{\tau}$ > 80 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

$m_{\mathrm{T}}^{\tau}$ in the compressed SR of the $1\tau$ channel before application of the $m_{\mathrm{T}}^{\tau}$ > 80 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

$H_{\mathrm{T}}$ in the medium-mass SR of the $1\tau$ channel before application of the $H_{\mathrm{T}}$ > 1000 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

$H_{\mathrm{T}}$ in the medium-mass SR of the $1\tau$ channel before application of the $H_{\mathrm{T}}$ > 1000 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

$m_{\mathrm{T}}^{\mathrm{sum}}$ in the compressed SR of the $2\tau$ channel before application of the $m_{\mathrm{T}}^{\mathrm{sum}}$ > 1600 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

$m_{\mathrm{T}}^{\mathrm{sum}}$ in the compressed SR of the $2\tau$ channel before application of the $m_{\mathrm{T}}^{\mathrm{sum}}$ > 1600 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

$H_{\mathrm{T}}$ in the high-mass SR of the $2\tau$ channel before application of the $H_{\mathrm{T}}$ > 1100 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

$H_{\mathrm{T}}$ in the high-mass SR of the $2\tau$ channel before application of the $H_{\mathrm{T}}$ > 1100 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

mT(tau_1) + mT(tau_2) in the multibin SR of the 2T channel. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

mT(tau_1) + mT(tau_2) in the multibin SR of the 2T channel. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

$H_{\mathrm{T}}$ in the GMSB SR of the $2\tau$ channel before application of the $H_{\mathrm{T}}$ > 1900 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

$H_{\mathrm{T}}$ in the GMSB SR of the $2\tau$ channel before application of the $H_{\mathrm{T}}$ > 1900 GeV requirement. The last bin includes overflow events. Signal predictions corresponding to the simplified model scenarios of low (LM), medium (MM), and high mass-splitting (HM) as well as for the GMSB benchmark are given.

Upper limits at the 95% CL on the cross section for SSM $W^\prime$ production and decay to the muon+neutrino channel as a function of the $W^\prime$ pole mass.

Combined (electron and muon channels) upper limits at the 95% CL on the cross section for SSM $W^\prime$ production and decay to a single lepton generation as a function of the $W^\prime$ pole mass.

Observed upper limits at the 95% CL on the cross section for generic $W^\prime$ production and decay to the electron+neutrino channel as a function of the $W^\prime$ pole mass.

Observed upper limits at the 95% CL on the cross section for generic $W^\prime$ production and decay to the muon+neutrino channel as a function of the $W^\prime$ pole mass.

Combined (electron and muon channels) observed upper limits at the 95% CL on the cross section for generic $W^\prime$ production and decay to a single lepton generation as a function of the $W^\prime$ pole mass.

Observed upper limits at the 95% CL on the visible cross section in the electron+neutrino channel as a function of the transverse mass threshold.

Observed upper limits at the 95% CL on the visible cross section in the muon+neutrino channel as a function of the transverse mass threshold.

Product of acceptance and efficiency for the electron and muon selections as a function of the $W^\prime$ pole mass.

Expected upper limits at the 95% CL on the cross section for generic $W^\prime$ production and decay to the electron+neutrino channel as a function of the $W^\prime$ pole mass.

Expected upper limits at the 95% CL on the cross section for generic $W^\prime$ production and decay to the muon+neutrino channel as a function of the $W^\prime$ pole mass.

Combined (electron and muon channels) expected upper limits at the 95% CL on the cross section for generic $W^\prime$ production and decay to a single lepton generation as a function of the $W^\prime$ pole mass.

Distribution of the resonance mass in the c-tag Signal Region of the $ ce$ channel for the post-fit background, the observed data, and the expected signal with $m_{LQ} = 1$ TeV.

Distribution of the resonance mass in the b-tag Signal Region of the $ ce$ channel for the post-fit background, the observed data, and the expected signal with $m_{LQ} = 1$ TeV.

Distribution of the resonance mass in the untagged Signal Region of the $ c\mu$ channel for the post-fit background, the observed data, and the expected signal with $m_{LQ} = 1$ TeV.

Distribution of the resonance mass in the c-tag Signal Region of the $ c\mu$ channel for the post-fit background, the observed data, and the expected signal with $m_{LQ} = 1$ TeV.

Distribution of the resonance mass in the b-tag Signal Region of the $ c\mu$ channel for the post-fit background, the observed data, and the expected signal with $m_{LQ} = 1$ TeV.

Distribution of the resonance mass in the 0-tag Signal Region of the $ be$ channel for the post-fit background, the observed data, and the expected signal with $m_{LQ} = 1$ TeV.

Distribution of the resonance mass in the 1-tag Signal Region of the $ be$ channel for the post-fit background, the observed data, and the expected signal with $m_{LQ} = 1$ TeV.

Distribution of the resonance mass in the 2-tag Signal Region of the $ be$ channel for the post-fit background, the observed data, and the expected signal with $m_{LQ} = 1$ TeV.

Distribution of the resonance mass in the 0-tag Signal Region of the $ b\mu$ channel for the post-fit background, the observed data, and the expected signal with $m_{LQ} = 1$ TeV.

Distribution of the resonance mass in the 1-tag Signal Region of the $ b\mu$ channel for the post-fit background, the observed data, and the expected signal with $m_{LQ} = 1$ TeV.

Distribution of the resonance mass in the 2-tag Signal Region of the $ b\mu$ channel for the post-fit background, the observed data, and the expected signal with $m_{LQ} = 1$ TeV.

The observed and expected limits on the leptoquark pair production cross-section at 95% CL for $\mathcal{B}=1$ into electrons, shown as a function of $m_{LQ}$ for the $qe$ channel.

The observed and expected limits on the leptoquark pair production cross-section at 95% CL for $\mathcal{B}=1$ into muons, shown as a function of $m_{LQ}$ for the $q\mu$ channel.

The observed and expected limits on the leptoquark pair production cross-section at 95% CL for $\mathcal{B}=1$ into electrons, shown as a function of $m_{LQ}$ for the $ce$ channel.

The observed and expected limits on the leptoquark pair production cross-section at 95% CL for $\mathcal{B}=1$ into muons, shown as a function of $m_{LQ}$ for the $c\mu$ channel.

The observed and expected limits on the leptoquark pair production cross-section at 95% CL for $\mathcal{B}=1$ into electrons, shown as a function of $m_{LQ}$ for the $be$ channel.

The observed and expected limits on the leptoquark pair production cross-section at 95% CL for $\mathcal{B}=1$ into muons, shown as a function of $m_{LQ}$ for the $b\mu$ channel.

The observed and expected limits on the leptoquark branching ratio at 95% CL, shown as a function of $m_{LQ}$ for the $qe$ channel.

The observed and expected limits on the leptoquark branching ratio at 95% CL, shown as a function of $m_{LQ}$ for the $q\mu$ channel.

The observed and expected limits on the leptoquark branching ratio at 95% CL, shown as a function of $m_{LQ}$ for the $ce$ channel.

The observed and expected limits on the leptoquark branching ratio at 95% CL, shown as a function of $m_{LQ}$ for the $c\mu$ channel.

The observed and expected limits on the leptoquark branching ratio at 95% CL, shown as a function of $m_{LQ}$ for the $be$ channel.

The observed and expected limits on the leptoquark branching ratio at 95% CL, shown as a function of $m_{LQ}$ for the $b\mu$ channel.

The signal selection efficiency x acceptance summed over all signal regions, for all masses and LQ decay channels considered.

The observed and expected limits for all masses and LQ decay channels considered.

Cutflow Table in the electron channel, considering signal samples with LQ mass of 1 TeV.

Cutflow Table in the muon channel, considering signal samples with LQ mass of 1 TeV.

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 H^boost. 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-low of the data and post-fit background prediction for m_eff^3ℓ/H^boost. 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-low of the data and post-fit background prediction for m_eff^3ℓ/H^boost. 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-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-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 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 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^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.

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.

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.

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.

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.

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.

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.

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

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

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 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 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 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 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 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 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 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.

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.

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.

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 $\sigma_\text{obs(exp)}^\text{95}$.

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 $\text{SR-ISR}$ 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.

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 observed upper limits on the model cross-section in units of pb for simplified models with ${\tilde{\tau}}_L {\tilde{\tau}}_L$ only production. Three points at $M({\tilde{\chi}}^{0}_{1})=200GeV$ were removed from the plot but kept in the table because they overlapped with the plot's legend and are far from the exclusion contour.

The observed 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 combined ${\tilde{\tau}}^{+}_{R,L} {\tilde{\tau}}^{-}_{R,L}$ production.

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 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 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.

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.

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.

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.

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.

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 highMass for combined stau final states

Signal acceptance in SR lowMass 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 highMass for combined stau final states

Signal efficiency in SR lowMass 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 highMass for combined stau final states

Signal acceptance*efficiency in SR lowMass 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.

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.

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-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 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 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 $m_{T2}$ 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 (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 $E_{T}^{miss}$ 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 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.

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.