Exclusion limits on higgsino pair production divided by the theory cross-section.The results of the low-mass analysis are used below m(higgsino) = 300 GeV, while those of the high-mass analysis are used above. The figure shows the observed and expected 95% upper limits on the higgsino pair production cross-section as a function of m(higgsino).

Observed and expected 95% limits in the m(higgsino) vs BR(higgsino to higgs+gravitino) plane. The regions above the lines are excluded by the analyses.

The observed and expected 95% upper limits on the total pair production cross section for degenerate higgsinos as a function of m(higgsino) for the high-mass search. Only the high-mass analysis results are used in this figure.

The observed and expected 95% upper limits on the total pair production cross section for degenerate higgsinos as a function of m(higgsino) for the high-mass search, divided by the theory cross section. Only the high-mass analysis results are used in this figure.

The observed and expected 95% upper limits on the total pair production cross section for degenerate higgsinos as a function of m(higgsino) for the low-mass search. Only the low-mass analysis results are used in this figure.

The observed and expected 95% upper limits on the total pair production cross section for degenerate higgsinos as a function of m(higgsino) for the low-mass search, divided by the theory cross section. Only the low-mass analysis results are used in this figure.

Particle-level acceptance for the low-mass discovery signal regions low-SR-MET0-meff440 and low-SR-MET150-meff440, shown as a function of higgsino mass. The acceptance is defined as the fraction of signal events passing the particle-level event selection that emulates the detector-level selection. The acceptance calculation considers only those signal events where both higgsinos decay to Higgs bosons that subsequently both decay to b-quarks.

The experimental efficiency of the low-mass analysis, for the two discovery signal regions low-SR-MET0-meff440 and low-SR-MET150-meff440, as a function of higgsino mass. The experimental efficiency is defined as the number of events passing the detector-level event selection divided by the number of events passing the event selection for a perfect detector. The denominator is obtained by implementing particle-level event selection that emulate the detector-level selection. Such particle-level selection is not applied on the numerator.

Particle-level acceptance for the high-mass discovery signal regions SR-4b-meff1-A-disc and SR-3b-meff3-A, shown as a function of higgsino mass. The acceptance is defined as the fraction of signal events passing the particle-level event selection that emulates the detector-level selection. The acceptance calculation considers only those signal events where both higgsinos decay to Higgs bosons that subsequently both decay to b-quarks.

The experimental efficiency of the high-mass analysis, for the two discovery signal regions SR-4b-meff1-A-disc and SR-3b-meff3-A, as a function of higgsino mass. The experimental efficiency is defined as the number of events passing the detector-level event selection divided by the number of events passing the event selection for a perfect detector. The denominator is obtained by implementing particle-level event selection that emulate the detector-level selection. Such particle-level selection is not applied on the numerator.

Example cutflow for SR-3b-meff3-A.

Example cutflow for SR-4b-meff1-A-disc.

Cutflow for low-mass analysis for each signal mass point.

Two-dimensional distribution of the invariant mass $m_{DV}$ and the track multiplicity in the High-pT jet SR for expected signal events in the strong gluino pair pair production model with m(gluino)=1.8 TeV, m(chi0)=0.2 TeV, tau(chi0)=0.1 ns

Two-dimensional distribution of the invariant mass $m_{DV}$ and the track multiplicity in the Trackless jet SR for observed data events

Two-dimensional distribution of the invariant mass $m_{DV}$ and the track multiplicity in the Trackless jet SR for expected signal events in the electroweak pair production model

Expected exclusion limits at 95% CL on the lifetime and mass of the neutralino in electroweakino pair production models

Expected (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in electroweakino pair production models

Expected (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in electroweakino pair production models

Observed exclusion limits at 95% CL on the lifetime and mass of the neutralino in electroweakino pair production models

Observed (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in electroweakino pair production models

Observed (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in electroweakino pair production models

Expected exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.4 TeV

Expected (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.4 TeV

Expected (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.4 TeV

Observed exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.4 TeV

Observed (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.4 TeV

Observed (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.4 TeV

Exclusion limits at 95% CL on the production cross section in the electroweak pair production model.

Exclusion limits at 95% CL on the production cross section in the strong gluino pair production models and m(gluino)=2.4 TeV

Expected exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.0 TeV

Expected (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.0 TeV

Expected (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.0 TeV

Observed exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.0 TeV

Observed (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.0 TeV

Observed (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.0 TeV

Expected exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.2 TeV

Expected (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.2 TeV

Expected (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.2 TeV

Observed exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.2 TeV

Observed (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.2 TeV

Observed (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.2 TeV

Expected exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=50 GeV

Expected (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=50 GeV

Expected (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=50 GeV

Observed exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=50 GeV

Observed (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=50 GeV

Observed (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=50 GeV

Expected exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=450 GeV

Expected (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=450 GeV

Expected (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=450 GeV

Observed exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=450 GeV

Observed (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=450 GeV

Observed (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=450 GeV

Expected exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.01 ns

Expected (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.01 ns

Expected (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.01 ns

Observed exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.01 ns

Observed (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.01 ns

Observed (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.01 ns

Expected exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.1 ns

Expected (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.1 ns

Expected (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.1 ns

Observed exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.1 ns

Observed (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.1 ns

Observed (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.1 ns

Expected exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=1 ns

Expected (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=1 ns

Expected (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=1 ns

Observed exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=1 ns

Observed (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=1 ns

Observed (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=1 ns

Expected exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=10 ns

Expected (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=10 ns

Expected (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=10 ns

Observed exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=10 ns

Observed (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=10 ns

Observed (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=10 ns

Exclusion limits at 95% CL on the production cross section in the strong gluino pair production models and m($ ilde{\chi}^0_1$)=1.25 TeV

Acceptance cutflow for the High-pT SR for representative points in the strong gluino pair production model. See additional resources for more information.

Acceptance cutflow for the Trackless SR for representative points in the electroweak pair production model. See additional resources for more information.

Acceptance cutflow for the Trackless SR for representative points in the electroweak pair production model with heavy-flavor quarks final state. See additional resources for more information.

Acceptance cutflow for the High-pT SR for representative points in the electroweak pair production model with heavy-flavor quarks final state. See additional resources for more information.

Reinterpretation Material: Event-level Efficiency for HighPt SR selections, R < 1150 mm

Reinterpretation Material: Event-level Efficiency for HighPt SR selections, R [1150, 3870] mm

Reinterpretation Material: Event-level Efficiency for HighPt SR selections, R > 3870 mm

Reinterpretation Material: Event-level Efficiency for Trackless SR selections, R < 1150 mm

Reinterpretation Material: Event-level Efficiency for Trackless SR selections, R [1150, 3870] mm

Reinterpretation Material: Event-level Efficiency for Trackless SR selections, R > 3870 mm

Reinterpretation Material: Vertex-level Efficiency for R < 22 mm

Reinterpretation Material: Vertex-level Efficiency for R [22, 25] mm

Reinterpretation Material: Vertex-level Efficiency for R [25, 29] mm

Reinterpretation Material: Vertex-level Efficiency for R [29, 38] mm

Reinterpretation Material: Vertex-level Efficiency for R [38, 46] mm

Reinterpretation Material: Vertex-level Efficiency for R [46, 73] mm

Reinterpretation Material: Vertex-level Efficiency for R [73, 84] mm

Reinterpretation Material: Vertex-level Efficiency for R [84, 111] mm

Reinterpretation Material: Vertex-level Efficiency for R [111, 120] mm

Reinterpretation Material: Vertex-level Efficiency for R [120, 145] mm

Reinterpretation Material: Vertex-level Efficiency for R [145, 180] mm

Reinterpretation Material: Vertex-level Efficiency for R [180, 300] mm

Cutflow (acceptance x efficiency) for the High-pT SR for representative points in the strong gluino pair production model. See additional resources for more information.

Cutflow (acceptance x efficiency) for the Trackless SR for representative points in the electroweak pair production model. See additional resources for more information.

Cutflow (acceptance x efficiency) for the Trackless SR for representative points in the electroweak pair production model with heavy-flavor quarks. See additional resources for more information.

Cutflow (acceptance x efficiency) for the High-pT SR for representative points in the electroweak pair production model with heavy-flavor quarks. See additional resources for more information.

The observed mass distribution in the SR-Inclusive_High signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

List of expected and observed events, $p_{0}$-value and the corresponding $Z$ local significance, as well as the 95% CLs upper limit of the expected and observed signal events ($S^{95}_ ext{exp} and $S^{95}_ ext{obs}$ ) in each mass window for SR-Inclusive bins of the short lifetime regime.

List of expected and observed events, $p_{0}$-value and the corresponding $Z$ local significance, as well as the 95% CLs upper limit of the expected and observed signal events ($S^{95}_ ext{exp} and $S^{95}_ ext{obs}$ ) in each mass window for SR-Inclusive bins of the long lifetime regime.

The observed $p_{\rm T$ distribution in the SR-Inclusive_Low signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

The observed $p_{\rm T$ distribution in the SR-Inclusive_High signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

The observed $|\eta|$ distribution in the SR-Inclusive_Low signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

The observed $|\eta|$ distribution in the SR-Inclusive_High signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

The observed dE/dx distribution in the SR-Inclusive_Low signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

The observed dE/dx distribution in the SR-Inclusive_High signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

The observed mass distribution in the SR-Trk-IBL0_Low signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

The observed mass distribution in the SR-Mu-IBL0_Low signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

The observed mass distribution in the SR-Trk-IBL0_High signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

The observed mass distribution in the SR-Mu-IBL0_High signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

The observed mass distribution in the SR-Trk-IBL1 signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

The observed mass distribution in the SR-Mu-IBL1 signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

Lower limits on the gluino mass, from gluino $R$-hadron pair production, as a function of gluino lifetime for two neutralino mass assumptions of (a) $m(\tilde{\chi}_{1}^{0}) = 100 \text{GeV}$ and (b) $\Delta m(\tilde{g}, \tilde{\chi}_{1}^{0}) = 30 \text{GeV}$. The upper $1 \sigma_\text{exp}$ expected bound is very close to the expected limit for some lifetime values due to the expected background getting very close to 0 events.

Lower limits on the gluino mass, from gluino $R$-hadron pair production, as a function of gluino lifetime for two neutralino mass assumptions of (a) $m(\tilde{\chi}_{1}^{0}) = 100 \text{GeV}$ and (b) $\Delta m(\tilde{g}, \tilde{\chi}_{1}^{0}) = 30 \text{GeV}$. The upper $1 \sigma_\text{exp}$ expected bound is very close to the expected limit for some lifetime values due to the expected background getting very close to 0 events.

Lower limits on the gluino mass, from gluino $R$-hadron pair production, as a function of gluino lifetime for two neutralino mass assumptions of (a) $m(\tilde{\chi}_{1}^{0}) = 100 \text{GeV}$ and (b) $\Delta m(\tilde{g}, \tilde{\chi}_{1}^{0}) = 30 \text{GeV}$. The upper $1 \sigma_\text{exp}$ expected bound is very close to the expected limit for some lifetime values due to the expected background getting very close to 0 events.

Lower limits on the gluino mass, from gluino $R$-hadron pair production, as a function of gluino lifetime for two neutralino mass assumptions of (a) $m(\tilde{\chi}_{1}^{0}) = 100 \text{GeV}$ and (b) $\Delta m(\tilde{g}, \tilde{\chi}_{1}^{0}) = 30 \text{GeV}$. The upper $1 \sigma_\text{exp}$ expected bound is very close to the expected limit for some lifetime values due to the expected background getting very close to 0 events.

(a) Lower limits on the chargino mass as a function of lifetime, and (b) the contours around the excluded mass-lifetime region for stau pair production.

(a) Lower limits on the chargino mass as a function of lifetime, and (b) the contours around the excluded mass-lifetime region for stau pair production.

(a) Lower limits on the chargino mass as a function of lifetime, and (b) the contours around the excluded mass-lifetime region for stau pair production.

(a) Lower limits on the chargino mass as a function of lifetime, and (b) the contours around the excluded mass-lifetime region for stau pair production.

Comparison of the observed and expected VAR distributionsin VR-LowPt-Trk-IBL0_Low. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.

Comparison of the observed and expected VAR distributionsin VR-LowPt-Mu-IBL0_Low. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.

Comparison of the observed and expected VAR distributionsin VR-LowPt-Trk-IBL0_High. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.

Comparison of the observed and expected VAR distributionsin VR-LowPt-Mu-IBL0_High. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.

Comparison of the observed and expected VAR distributionsin VR-LowPt-Trk-IBL1. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.

Comparison of the observed and expected VAR distributionsin VR-LowPt-Mu-IBL1. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.

Comparison of the observed and expected VAR distributionsin VR-HiEta-Trk-IBL0_Low. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.

Comparison of the observed and expected VAR distributionsin VR-HiEta-Mu-IBL0_Low. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.

Comparison of the observed and expected VAR distributionsin VR-HiEta-Trk-IBL0_High. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.

Comparison of the observed and expected VAR distributionsin VR-HiEta-Mu-IBL0_High. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.

Comparison of the observed and expected VAR distributionsin VR-HiEta-Trk-IBL1. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.

Comparison of the observed and expected VAR distributionsin VR-HiEta-Mu-IBL1. The band on the expected background estimation indicates the total uncertainty of the estimation. Downward triangle markers at the bottom of the panels indicate there is no events observed in the corresponding bin, while upward triangle markers at the bottom panel indicate the observed data is beyond the range.

The observed $p_{\rm T$ distribution in the SR-Trk-IBL0_Low signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

The observed $p_{\rm T$ distribution in the SR-Mu-IBL0_Low signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

The observed $p_{\rm T$ distribution in the SR-Trk-IBL0_High signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

The observed $p_{\rm T$ distribution in the SR-Mu-IBL0_High signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

The observed $p_{\rm T$ distribution in the SR-Trk-IBL1 signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

The observed $p_{\rm T$ distribution in the SR-Mu-IBL1 signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

The observed dE/dx distribution in the SR-Trk-IBL0_Low signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

The observed dE/dx distribution in the SR-Mu-IBL0_Low signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

The observed dE/dx distribution in the SR-Trk-IBL0_High signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

The observed dE/dx distribution in the SR-Mu-IBL0_High signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

The observed dE/dx distribution in the SR-Trk-IBL1 signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

The observed dE/dx distribution in the SR-Mu-IBL1 signal-region bin. The band on the expected background indicates the total uncertainty of the estimation. Several representative signal models are overlaid. Events outside the shown range are accumulated in the rightmost bin indicated as 'Overflow'. Downward triangle markers at the bottom of the panels indicate that no events are observed in the corresponding mass bin, while upward triangle markers in the lower panels indicate that the observed data is beyond the range.

Expected and observed distributions in SR-Inclusive_Low of missing transverse momentum. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.

Expected and observed distributions in SR-Inclusive_High of missing transverse momentum. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.

Expected and observed distributions in SR-Inclusive_Low of relative phi-angle between pTmiss and the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.

Expected and observed distributions in SR-Inclusive_High of relative phi-angle between pTmiss and the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.

Expected and observed distributions in SR-Inclusive_Low of the transverse mass of pTmiss and the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.

Expected and observed distributions in SR-Inclusive_High of the transverse mass of pTmiss and the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.

Expected and observed distributions in SR-Inclusive_Low of the leading jet pT, required to be separated by at least deltaR > 0.4 with respect to the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.

Expected and observed distributions in SR-Inclusive_High of the leading jet pT, required to be separated by at least deltaR > 0.4 with respect to the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.

Expected and observed distributions in SR-Inclusive_Low of the relative phi-angle between the leading jet pT, required to be separated by at least deltaR > 0.4 with respect to the signal candidate track, and the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.

Expected and observed distributions in SR-Inclusive_High of the relative phi-angle between the leading jet pT, required to be separated by at least deltaR > 0.4 with respect to the signal candidate track, and the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.

Expected and observed distributions in SR-Inclusive_Low of the relative phi-angle between pTmiss and the leading jet pT, required to be separated by at least deltaR > 0.4 with respect to the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.

Expected and observed distributions in SR-Inclusive_High of the relative phi-angle between pTmiss and the leading jet pT, required to be separated by at least deltaR > 0.4 with respect to the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.

Expected and observed distributions in SR-Inclusive_Low of the transverse mass of pTmiss and the leading jet pT, required to be separated by at least deltaR > 0.4 with respect to the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.

Expected and observed distributions in SR-Inclusive_High of the transverse mass of pTmiss and the leading jet pT, required to be separated by at least deltaR > 0.4 with respect to the signal candidate track. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.

Expected and observed distributions in SR-Inclusive_Low of the effective mass, defined as the scalar sum pT of the signal candidate track, jets satisfying pT > 30 GeV, excluding ones within deltaR < 0.4 with respect to the signal candidate track, and pTmiss. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.

Expected and observed distributions in SR-Inclusive_High of the effective mass, defined as the scalar sum pT of the signal candidate track, jets satisfying pT > 30 GeV, excluding ones within deltaR < 0.4 with respect to the signal candidate track, and pTmiss. The expected background distribution is calculated for each |eta| slice using CR-kin control region as the template and applying the scale factor using the dE/dx distribution in CR-dEdx of the corresponding |eta| slice. The last bins of the plots include overflow events above the range.

The expected upper limits on cross-section for gluinos with $m(\tilde{\chi}_{1}^{0}) = 100 \text{GeV}$, with lifetime with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, (d) 30 ns, and (e) stable.

The expected upper limits on cross-section for gluinos with $m(\tilde{\chi}_{1}^{0}) = 100 \text{GeV}$, with lifetime with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, (d) 30 ns, and (e) stable.

The expected upper limits on cross-section for gluinos with $m(\tilde{\chi}_{1}^{0}) = 100 \text{GeV}$, with lifetime with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, (d) 30 ns, and (e) stable.

The expected upper limits on cross-section for gluinos with $m(\tilde{\chi}_{1}^{0}) = 100 \text{GeV}$, with lifetime with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, (d) 30 ns, and (e) stable.

The expected upper limits on cross-section for gluinos with $m(\tilde{\chi}_{1}^{0}) = 100 \text{GeV}$, with lifetime with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, (d) 30 ns, and (e) stable.

The expected upper limits on cross-section for gluinos with $\Delta m(\tilde{g}, \tilde{\chi}_{1}^{0}) = 30 \text{GeV}$, with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, and (d) 30 ns.

The expected upper limits on cross-section for gluinos with $\Delta m(\tilde{g}, \tilde{\chi}_{1}^{0}) = 30 \text{GeV}$, with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, and (d) 30 ns.

The expected upper limits on cross-section for gluinos with $\Delta m(\tilde{g}, \tilde{\chi}_{1}^{0}) = 30 \text{GeV}$, with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, and (d) 30 ns.

The expected upper limits on cross-section for gluinos with $\Delta m(\tilde{g}, \tilde{\chi}_{1}^{0}) = 30 \text{GeV}$, with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, and (d) 30 ns.

The expected upper limits on cross-section for charginos with lifetime (c) 10 ns, (d) 30 ns, and (e) stable.

The expected upper limits on cross-section for charginos with lifetime (c) 10 ns, (d) 30 ns, and (e) stable.

The expected upper limits on cross-section for charginos with lifetime (c) 10 ns, (d) 30 ns, and (e) stable.

The expected upper limits on cross-section for charginos with lifetime (c) 10 ns, (d) 30 ns, and (e) stable.

The expected upper limits on cross-section for charginos with lifetime (c) 10 ns, (d) 30 ns, and (e) stable.

The expected upper limits on cross-section for sleptons with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, (d) 30 ns, and (e) stable.

The expected upper limits on cross-section for sleptons with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, (d) 30 ns, and (e) stable.

The expected upper limits on cross-section for sleptons with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, (d) 30 ns, and (e) stable.

The expected upper limits on cross-section for sleptons with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, (d) 30 ns, and (e) stable.

The expected upper limits on cross-section for sleptons with lifetime (a) 1 ns, (b) 3 ns, (c) 10 ns, (d) 30 ns, and (e) stable.

Muon reconstruction efficiency as a function of β and |η| for (a) stable charginos and (b) stable charged R-hadrons. For weakly interacting LLPs with calorimeter materials the efficiency for the chargino is recommended to refer to. The muon reconstruction efficiency for R-hadrons is significantly lower due to having QCD interactions with materials.

Muon reconstruction efficiency as a function of β and |η| for (a) stable charginos and (b) stable charged R-hadrons. For weakly interacting LLPs with calorimeter materials the efficiency for the chargino is recommended to refer to. The muon reconstruction efficiency for R-hadrons is significantly lower due to having QCD interactions with materials.

Trigger and event selection efficiencies. The band on the marker indicates a typical size of fluctuation by the LLP mass and lifetime observed by the samples used in efficiency derivation, but it does not indicate the full envelope of model dependence.

Trigger and event selection efficiencies. The band on the marker indicates a typical size of fluctuation by the LLP mass and lifetime observed by the samples used in efficiency derivation, but it does not indicate the full envelope of model dependence.

Signal track selection efficiency as a function of CLLP $\beta\gamma$ for SR-Inclusive_Low and SR-Inclusive_High bins. The band on the marker indicates a typical size of fluctuation by the LLP mass and lifetime observed by the samples used in efficiency derivation, but it does not indicate the full envelope of model dependence.

Signal selection efficiency by the mass window for SR-Inclusive_Low and SR-Inclusive_High bins.

Acceptance for the R-hadron pair-production model with m(N1) = 100 GeV for various masses and lifetimes. The acceptance is defined as the fraction of events having at least one charged LLP satisfying pT > 120 GeV, |\eta| < 1.8 and r_decay > 500 mm.

Acceptance for the R-hadron pair-production model with DeltaM(gluino, N1) = 30 GeV for various masses and lifetimes. The acceptance is defined as the fraction of events having at least one charged LLP satisfying pT > 120 GeV, |eta| < 1.8 and r_decay > 500 mm.

Acceptance for the chargino pair-production model for various masses and lifetimes. The acceptance is defined as the fraction of events having at least one charged LLP satisfying pT > 120 GeV, |\eta| < 1.8 and r_decay > 500 mm.

Acceptance for the stau pair-production model for various masses and lifetimes. The acceptance is defined as the fraction of events having at least one charged LLP satisfying pT > 120 GeV, |\eta| < 1.8 and r_decay > 500 mm.

Event-level efficiency for the R-hadron pair-production model with m(N1) = 100 GeV for various masses and lifetimes. The efficiency is defined as the fraction of events satisfying the selection of trigger, event and jet cleaning, ETmiss and primary vertex requirements per events satisfying the acceptance criteria.

Event-level efficiency for the R-hadron pair-production model with DeltaM(gluino, N1) = 30 GeV for various masses and lifetimes. The efficiency is defined as the fraction of events satisfying the selection of trigger, event and jet cleaning, ETmiss and primary vertex requirements per events satisfying the acceptance criteria.

Event-level efficiency for the chargino pair-production model for various masses and lifetimes. The efficiency is defined as the fraction of events satisfying the selection of trigger, event and jet cleaning, ETmiss and primary vertex requirements per events satisfying the acceptance criteria.

Event-level efficiency for the stau pair-production model for various masses and lifetimes. The efficiency is defined as the fraction of events satisfying the selection of trigger, event and jet cleaning, ETmiss and primary vertex requirements per events satisfying the acceptance criteria.

Efficiency of SR-Inclusive_Highfor the R-hadron pair-production model with m(N1) = 100 GeV for various masses and lifetimes. The efficiency is defined as the ratio of events satisfying the signal region selection to those satisfying the acceptance criteria. The mass window is not applied for the presented numbers.

Efficiency of SR-Inclusive_Highfor the R-hadron pair-production model with DeltaM(gluino, N1) = 30 GeV for various masses and lifetimes. The efficiency is defined as the ratio of events satisfying the signal region selection to those satisfying the acceptance criteria. The mass window is not applied for the presented numbers.

Efficiency of SR-Inclusive_Highfor the chargino pair-production model for various masses and lifetimes. The efficiency is defined as the ratio of events satisfying the signal region selection to those satisfying the acceptance criteria. The mass window is not applied for the presented numbers.

Efficiency of SR-Inclusive_Highfor the stau pair-production model for various masses and lifetimes. The efficiency is defined as the ratio of events satisfying the signal region selection to those satisfying the acceptance criteria. The mass window is not applied for the presented numbers.

Efficiency of SR-Inclusive_Low for the R-hadron pair-production model with m(N1) = 100 GeV for various masses and lifetimes. The efficiency is defined as the ratio of events satisfying the signal region selection to those satisfying the acceptance criteria. The mass window is not applied for the presented numbers.

Efficiency of SR-Inclusive_Low for the R-hadron pair-production model with DeltaM(gluino, N1) = 30 GeV for various masses and lifetimes. The efficiency is defined as the ratio of events satisfying the signal region selection to those satisfying the acceptance criteria. The mass window is not applied for the presented numbers.

Efficiency of SR-Inclusive_Low for the chargino pair-production model for various masses and lifetimes. The efficiency is defined as the ratio of events satisfying the signal region selection to those satisfying the acceptance criteria. The mass window is not applied for the presented numbers.

Efficiency of SR-Inclusive_Low for the stau pair-production model for various masses and lifetimes. The efficiency is defined as the ratio of events satisfying the signal region selection to those satisfying the acceptance criteria. The mass window is not applied for the presented numbers.

Passing events in event selection steps for the R-hadron pair-production model with m(N1) = 100 GeV for various masses and lifetimes.

Passing events in event selection steps for the R-hadron pair-production model with DeltaM(gluino, N1) = 30 GeV for various masses and lifetimes.

Passing events in event selection steps for the chargino pair-production model for various masses and lifetimes.

Passing events in event selection steps for the stau pair-production model for various masses and lifetimes.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[110,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[120,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[120,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[130,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[130,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[100,105)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[100,105)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[105,110)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[105,110)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[110,115)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[110,115)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[115,120)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[115,120)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[120,125)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[120,125)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[125,130)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[125,130)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[130,140)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[130,140)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[140,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-0J $m_{\mathrm{T2}}^{100} \in[140,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[100,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[100,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[110,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[110,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[120,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[120,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[130,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[130,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[100,105)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[100,105)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[105,110)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[105,110)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[110,115)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[110,115)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[115,120)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[115,120)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[120,125)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[120,125)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[125,130)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[125,130)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[130,140)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[130,140)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[140,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the slepton pair production model, in the SR-1J $m_{\mathrm{T2}}^{100} \in[140,\infty)$ region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

Cutflow table for the slepton signal sample with $m(\tilde{\ell},\tilde{\chi}_1^0) = (100,70)$ GeV, in the SR-0J $m_{\mathrm{T2}}^{100} \in [100,\infty)$ region. The yields include the process cross section and are weighted to the 139 fb$^{-1}$ luminosity. 246000 events were generated for the sample.

Cutflow table for the slepton signal sample with $m(\tilde{\ell},\tilde{\chi}_1^0) = (100,70)$ GeV, in the SR-1J $m_{\mathrm{T2}}^{100} \in [100,\infty)$ region. The yields include the process cross section and are weighted to the 139 fb$^{-1}$ luminosity. 246000 events were generated for the sample.

Observed and expected exclusion limits on SUSY simplified models, with observed upper limits on signal cross-section (fb) overlaid, for slepton-pair production in the $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ plane. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.

Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.

Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.

Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.

Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.

Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.

Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.

Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.

Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.

Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.

Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.

Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.

Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the (a) $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\ell})-\Delta m(\tilde{\ell},\tilde{\chi}_1^0)$ planes. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP for $\tilde{\mu}_{\textup{R}}$ and by the ATLAS experiment in previous searches are also shown.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for direct selectron production in the (a) $m(\tilde{e})-m(\tilde{\chi}_1^0)$ and (c) $m(\tilde{e})-\Delta m(\tilde{e},\tilde{\chi}_1^0)$ planes, and for direct smuon production in the (b) $m(\tilde{\mu})-m(\tilde{\chi}_1^0)$ and (d) $m(\tilde{\mu})-\Delta m(\tilde{\mu},\tilde{\chi}_1^0)$ planes. In Figure (a) and (c) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{e}_{\textup{L,R}}$ and for $\tilde{e}_{\textup{L}}$ and $\tilde{e}_{\textup{R}}$. In Figure (b) and (d) the observed (solid thick lines) and expected (dashed lines) exclusion contours are indicated for combined $\tilde{\mu}_{\textup{L,R}}$ and for $\tilde{\mu}_{\textup{L}}$. No unique sensitivity to $\tilde{\mu}_{\textup{R}}$ is observed. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown in the shaded areas.

Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ plane. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The red contour shows the exclusion limits obtained using both the SR-0J and SR-1J region, as presented in Figure 6. The blue and green contours correspond to the result obtained considering only SR-0J and SR-1J region respectively. All limits are computed at 95% CL. The observed limits obtained by the ATLAS experiment in previous searches are also shown.

Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ plane. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The red contour shows the exclusion limits obtained using both the SR-0J and SR-1J region, as presented in Figure 6. The blue and green contours correspond to the result obtained considering only SR-0J and SR-1J region respectively. All limits are computed at 95% CL. The observed limits obtained by the ATLAS experiment in previous searches are also shown.

Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ plane. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The red contour shows the exclusion limits obtained using both the SR-0J and SR-1J region, as presented in Figure 6. The blue and green contours correspond to the result obtained considering only SR-0J and SR-1J region respectively. All limits are computed at 95% CL. The observed limits obtained by the ATLAS experiment in previous searches are also shown.

Observed and expected exclusion limits on SUSY simplified models for slepton-pair production in the $m(\tilde{\ell})-m(\tilde{\chi}_1^0)$ plane. Only $\tilde{e}$ and $\tilde{\mu}$ are considered. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The red contour shows the exclusion limits obtained using both the SR-0J and SR-1J region, as presented in Figure 6. The blue and green contours correspond to the result obtained considering only SR-0J and SR-1J region respectively. All limits are computed at 95% CL. The observed limits obtained by the ATLAS experiment in previous searches are also shown.

The upper panel shows the observed number of events in each of the binned SRs defined in Table 3, together with the expected SM backgrounds obtained after applying the efficiency correction method to compute the number of expected FSB events. `Others' include the non-dominant background sources, e.g. $t \bar{t}$+$V$, Higgs boson and Drell--Yan events. The uncertainty band includes systematic and statistical errors from all sources. The distributions of two signal points with mass splittings $\Delta m(\tilde{\ell},\tilde{\chi}_1^0) = m(\tilde{\ell})-m(\tilde{\chi}_1^0) = 30$ GeV and $\Delta m(\tilde{\ell},\tilde{\chi}_1^0) = m(\tilde{\ell})-m(\tilde{\chi}_1^0) = 50$ GeV are overlaid. The lower panel shows the significance as defined in Ref. [115].

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR$^{\text{-DF BDT-signal}\in(0.81,1]}_{\text{-SF BDT-signal}\in(0.77,1]}$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR$^{\text{-DF BDT-signal}\in(0.81,1]}_{\text{-SF BDT-signal}\in(0.77,1]}$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.81,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.81,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.82,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.82,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.83,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.83,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.84,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.84,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.85,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.85,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.81,0.8125]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.81,0.8125]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8125,0.815]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8125,0.815]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.815,0.8175]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.815,0.8175]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8175,0.82]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8175,0.82]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.82,0.8225]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.82,0.8225]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8225,0.825]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8225,0.825]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.825,0.8275]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.825,0.8275]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8275,0.83]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8275,0.83]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.83,0.8325]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.83,0.8325]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8325,0.835]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8325,0.835]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.835,0.8375]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.835,0.8375]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8375,0.84]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.8375,0.84]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.84,0.845]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.84,0.845]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.845,0.85]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.845,0.85]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.85,0.86]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.85,0.86]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.86,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-DF BDT-signal$\in(0.86,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.77,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.77,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.78,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.78,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.79,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.79,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.80,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.80,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.77,0.775]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.77,0.775]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.775,0.78]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.775,0.78]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.78,0.785]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.78,0.785]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.785,0.79]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.785,0.79]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.79,0.795]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.79,0.795]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.795,0.80]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.795,0.80]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.80,0.81]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.80,0.81]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.81,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

The figure shows the signal acceptance (a) and efficiency (b) plots for the $\tilde{\chi}_1^+\tilde{\chi}_1^-$ production with $W$-boson-mediated decay model, in the SR-SF BDT-signal$\in(0.81,1]$ inclusive region. Acceptance is calculated by applying the signal region requirements to particle-level objects, which do not suffer from identification inefficiencies or mismeasurements. The efficiency is calculated with fully reconstructed objects with the acceptance divided out. Large acceptance and efficiency differences in neighbouring points are due to statistical fluctuations.

Cutflow table for the chargino signal sample with $m\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0=(125,25)$ GeV, in the SR-SF BDT-signal$\in (0.77,1]$ and SR-DF BDT-signal$\in (0.81,1]$ regions. The yields include the process cross-section and are weighted to the 139 fb$^{-1}$ luminosity. 170000 events were generated for the sample.

Observed and expected exclusion limits on SUSY simplified models, with observed upper limits on signal cross-section (fb) overlaid, for chargino-pair production with $W$-boson-mediated decays in the $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ plane. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.

Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.

Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.

Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.

Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.

Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.

Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.

Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.

Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.

Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.

Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.

Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.

Observed and expected exclusion limits on SUSY simplified models for chargino-pair production with $W$-boson-mediated decays in the (a) $m(\tilde{\chi}_1^{\pm})-m(\tilde{\chi}_1^0)$ and (b) $m(\tilde{\chi}_1^{\pm})-\Delta m(\tilde{\chi}_1^{\pm},\tilde{\chi}_1^0)$ planes. The observed (solid thick line) and expected (thin dashed line) exclusion contours are indicated. The shaded band around the dashed line corresponds to the $\pm 1 \sigma$ variations in the expected limit, including all uncertainties except theoretical uncertainties in the signal cross-section. The dotted lines around the observed limit illustrate the change in the observed limit as the nominal signal cross-section is scaled up and down by the theoretical uncertainty. All limits are computed at 95% CL. The observed limits obtained at LEP and by the ATLAS experiment in previous searches are also shown. In case of the search performed on ATLAS Run 1 data at $\sqrt{s} = 8$ TeV no sensitivity was expected for the exclusion in the mass plane.

The upper panel shows the observed number of events in the SRs defined in Table 3, together with the expected SM backgrounds obtained after the background fit in the CRs. `Others' include the non-dominant background sources, e.g.$t \bar{t}$+$V$, Higgs boson and Drell--Yan events. The uncertainty band includes systematic and statistical errors from all sources. Distributions for three benchmark signal points are overlaid for comparison. The lower panel shows the significance as defined in Ref. [115].

Observed (points with error bars) and expected background (solid histograms) distributions for $E_{T}^{miss}$ in the signal region (a) SRL, (b) SRM and (c) SRH after the background-only fit applied to the CRs. The predicted signal distributions for the two models with a gluino mass of 2000 GeV and neutralino mass of 250 GeV (SRL), 1050 GeV (SRM) or 1950 GeV (SRH) are also shown for comparison. The uncertainties in the SM background are only statistical.

Observed and expected exclusion limit in the gluino-neutralino mass plane at 95% CL combined using the signal region with the best expected sensitivity at each point, for the full Run-2 dataset corresponding to an integrated luminosity of $139~\mathrm{fb}^{-1}$, for $\gamma/Z$ (a) and $\gamma/h$ (b) signal models. The black solid line corresponds to the expected limits at 95% CL, with the light (yellow) bands indicating the 1$\sigma$ exclusions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves, the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties. For each point in the higgsino-bino parameter space, the labels indicate the best-expected signal region, where L, M and H mean SRL, SRM and SRH, respectively.

Observed and expected exclusion limit in the gluino-neutralino mass plane at 95% CL combined using the signal region with the best expected sensitivity at each point, for the full Run-2 dataset corresponding to an integrated luminosity of $139~\mathrm{fb}^{-1}$, for $\gamma/Z$ (a) and $\gamma/h$ (b) signal models. The black solid line corresponds to the expected limits at 95% CL, with the light (yellow) bands indicating the 1$\sigma$ exclusions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves, the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties. For each point in the higgsino-bino parameter space, the labels indicate the best-expected signal region, where L, M and H mean SRL, SRM and SRH, respectively.

Acceptance (left) and efficiency (right) for the $\gamma/Z$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).

Acceptance (left) and efficiency (right) for the $\gamma/Z$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).

Acceptance (left) and efficiency (right) for the $\gamma/Z$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).

Acceptance (left) and efficiency (right) for the $\gamma/Z$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).

Acceptance (left) and efficiency (right) for the $\gamma/Z$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).

Acceptance (left) and efficiency (right) for the $\gamma/Z$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).

Acceptance (left) and efficiency (right) for the $\gamma/h$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).

Acceptance (left) and efficiency (right) for the $\gamma/h$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).

Acceptance (left) and efficiency (right) for the $\gamma/h$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).

Acceptance (left) and efficiency (right) for the $\gamma/h$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).

Acceptance (left) and efficiency (right) for the $\gamma/h$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).

Acceptance (left) and efficiency (right) for the $\gamma/h$ model signal grid for SRL (top), SRM (middle) and SRH (bottom).

Cutflow for the SRL selection, for two relevant signal points for both $\gamma/Z$ and $\gamma/h$ models, where the gluinos have mass of 2000 GeV and the neutralinos have a mass of 250 GeV (10000 generated events). The numbers are normalized to a luminosity of 139 $fb^{-1}$.

Cutflow for the SRM selection, for two relevant signal points for both $\gamma/Z$ and $\gamma/h$ models, where the gluinos have mass of 2000 GeV and the neutralinos have a mass of 1050 GeV (10000 generated events). The numbers are normalized to a luminosity of 139 $fb^{-1}$.

Cutflow for the SRH selection, for two relevant signal points for both $\gamma/Z$ and $\gamma/h$ models, where the gluinos have mass of 2000 GeV and the neutralinos have a mass of 1950 GeV (10000 generated events). The numbers are normalized to a luminosity of 139 $fb^{-1}$.

Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.

Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.

Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.

Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.

Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.

Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.

Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.

Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.

Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.

Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.

Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.

Observed and expected exclusion limits in the gluino–neutralino mass plane at 95% CL for the full Run-2 dataset corresponding to an integrated luminosity of 139 fb−1 , for the (a) $\gamma/Z$ and (b) $\gamma/h$ signal models. They are obtained by combining limits from the signal region with the best expected sensitivity at each point. The dashed (black) line corresponds to the expected limits at 95% CL, with the light (yellow) band indicating the $\pm 1\sigma$ excursions due to experimental and background-theory uncertainties. The observed limits are indicated by medium (red) curves: the solid contour represents the nominal limit, and the dotted lines are obtained by varying the signal cross section by the theoretical scale and PDF uncertainties.

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 %.

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 contour are excluded.

The minus $1\sigma$ variation of observed exclusion contour obtained by varying the signal cross section within its uncertainty. The contour is given as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$.

The minus $1\sigma$ variation of observed exclusion contour obtained by varying the signal cross section within its uncertainty. The contour is given as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$.

The plus $1\sigma$ variation of observed exclusion contour obtained by varying the signal cross section within its uncertainty. The contour is given as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$.

The plus $1\sigma$ variation of observed exclusion contour obtained by varying the signal cross section within its uncertainty. The contour is given as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$.

The minus $1\sigma$ variation of expected exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties (excluding signal cross section uncertainties). The contour is given as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$.

The minus $1\sigma$ variation of expected exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties (excluding signal cross section uncertainties). The contour is given as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$.

The plus $1\sigma$ variation of expected exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties (excluding signal cross section uncertainties). The contour is given as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$.

The plus $1\sigma$ variation of expected exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties (excluding signal cross section uncertainties). The contour is given as a function of the $\it{m}_{\tilde{\chi}^{0}_{1}}$ vs. $\it{m}_{\tilde{t}}$.

The observed exclusion contour at 95% CL as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$. Points that are within the contours are excluded.

The observed exclusion contour at 95% CL as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$. Points that are within the contours are excluded.

The expected exclusion contour at 95% CL as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$. Points that are within the contours are excluded.

The expected exclusion contour at 95% CL as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$. Points that are within the contours are excluded.

The minus $1\sigma$ variation of observed exclusion contour obtained by varying the signal cross section within its uncertainty. The contour is given as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$

The minus $1\sigma$ variation of observed exclusion contour obtained by varying the signal cross section within its uncertainty. The contour is given as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$

The plus $1\sigma$ variation of observed exclusion contour obtained by varying the signal cross section within its uncertainty. The contour is given as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$

The plus $1\sigma$ variation of observed exclusion contour obtained by varying the signal cross section within its uncertainty. The contour is given as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$

The plus $1\sigma$ variation of expected exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties (excluding signal cross section uncertainties). The contour is given as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$

The plus $1\sigma$ variation of expected exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties (excluding signal cross section uncertainties). The contour is given as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$

The minus $1\sigma$ variation of expected exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties (excluding signal cross section uncertainties). The contour is given as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$

The minus $1\sigma$ variation of expected exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties (excluding signal cross section uncertainties). The contour is given as a function of the $\it{m}_{LQ_{3}^{u}}$ vs. $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau)$

Model dependent upper limit on the cross section for the $(\tilde{t},\tilde{\chi}^{0}_{1})$ signal grid. The column titled 'Leading Region' stores information on which of the fit regions (SRA-B, SRC or SRD) is the dominant based on the expected CLs values.

Model dependent upper limit on the cross section for the $(\tilde{t},\tilde{\chi}^{0}_{1})$ signal grid. The column titled 'Leading Region' stores information on which of the fit regions (SRA-B, SRC or SRD) is the dominant based on the expected CLs values.

Expected model dependent upper limit on the cross section for the $(\tilde{t},\tilde{\chi}^{0}_{1})$ signal grid. The column titled 'Leading Region' stores information on which of the fit regions (SRA-B, SRC or SRD) is the dominant based on the expected CLs values.

Expected model dependent upper limit on the cross section for the $(\tilde{t},\tilde{\chi}^{0}_{1})$ signal grid. The column titled 'Leading Region' stores information on which of the fit regions (SRA-B, SRC or SRD) is the dominant based on the expected CLs values.

Model dependent upper limit on the cross section for the $LQ_{3}^{u}$ signal grid with $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau))=0$ %. Only the SRA-B fit region is considered in this interpretation.

Model dependent upper limit on the cross section for the $LQ_{3}^{u}$ signal grid with $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau))=0$ %. Only the SRA-B fit region is considered in this interpretation.

Expected model dependent upper limit on the cross section for the $LQ_{3}^{u}$ signal grid with $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau))=0$ %. Only the SRA-B fit region is considered in this interpretation.

Expected model dependent upper limit on the cross section for the $LQ_{3}^{u}$ signal grid with $\mathrm{BR}(\it{m}_{LQ_{3}^{u}}\rightarrow b \tau))=0$ %. Only the SRA-B fit region is considered in this interpretation.

The distributions of $S$ in SRA-TW. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.

The distributions of $S$ in SRA-TW. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.

The distributions of $\it{m}^{\mathrm{R=1.2}}_{1}$ in SRB-TT. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.

The distributions of $\it{m}^{\mathrm{R=1.2}}_{1}$ in SRB-TT. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.

The distributions of R$_{ISR}$ in SRC signal regions before R$_{ISR}$ cuts are applied. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.

The distributions of R$_{ISR}$ in SRC signal regions before R$_{ISR}$ cuts are applied. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.

The distributions of $E^{miss}_{T}/\sqrt{H_{T}}$ in SRD0. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.

The distributions of $E^{miss}_{T}/\sqrt{H_{T}}$ in SRD0. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.

The distributions of $E^{miss}_{T}/\sqrt{H_{T}}$ in SRD1. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.

The distributions of $E^{miss}_{T}/\sqrt{H_{T}}$ in SRD1. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.

The distributions of $E^{miss}_{T}/\sqrt{H_{T}}$ in SRD2. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.

The distributions of $E^{miss}_{T}/\sqrt{H_{T}}$ in SRD2. For each bin yields for the data, total SM prediction and a representative signal point are provided. The SM prediction is provided with the MC statistical uncertainties, labeled 'stat', and the remaining uncertainties, labeled 'syst' that include detector-related systematic uncertainties and theoretical uncertainties. The signal predictions is provided with the MC statistical uncertainties only. The rightmost bin includes overflow events.

Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (1300,1)\ \mathrm{GeV} $ in SRA-TT. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 30000 raw MC events were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.

Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (1300,1)\ \mathrm{GeV} $ in SRA-TT. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 30000 raw MC events were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.

Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (1300,1)\ \mathrm{GeV} $ in SRA-TW. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 30000 raw MC events were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.

Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (1300,1)\ \mathrm{GeV} $ in SRA-TW. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 30000 raw MC events were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.

Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (1300,1)\ \mathrm{GeV} $ in SRA-T0. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 30000 raw MC events were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.

Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (1300,1)\ \mathrm{GeV} $ in SRA-T0. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 30000 raw MC events were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.

Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (700,400)\ \mathrm{GeV} $ in signal regions SRB-TT, SRB-TW and SRB-T0. The regions differ by the last cut applied. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 60000 raw MC events were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.

Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (700,400)\ \mathrm{GeV} $ in signal regions SRB-TT, SRB-TW and SRB-T0. The regions differ by the last cut applied. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 60000 raw MC events were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.

Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (500,327)\ \mathrm{GeV} $ in regions SRC-1, SRC-2, SRC-3, SRC-4 and SRC-5. The regions differ by the last cut applied. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 150000 raw MC events with filter efficiency of 0.384 were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.

Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (500,327)\ \mathrm{GeV} $ in regions SRC-1, SRC-2, SRC-3, SRC-4 and SRC-5. The regions differ by the last cut applied. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 150000 raw MC events with filter efficiency of 0.384 were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.

Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (550,500)\ \mathrm{GeV} $ in SRD0. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 90000 raw MC events with filter efficiency of 0.428 were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.

Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (550,500)\ \mathrm{GeV} $ in SRD0. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 90000 raw MC events with filter efficiency of 0.428 were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.

Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (550,500)\ \mathrm{GeV} $ in SRD1. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 90000 raw MC events with filter efficiency of 0.428 were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.

Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (550,500)\ \mathrm{GeV} $ in SRD1. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 90000 raw MC events with filter efficiency of 0.428 were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.

Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (550,500)\ \mathrm{GeV} $ in SRD2. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 90000 raw MC events with filter efficiency of 0.428 were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.

Cutflow for the reference point $(\it{m}_{\tilde{t}}, \it{m}_{\tilde{\chi}^{0}_{1}})= (550,500)\ \mathrm{GeV} $ in SRD2. The column labelled ''Weighted yield'' shows the results including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$. A notable exception concerns results in the first row, labelled ''Total'', that corresponds to plain $\sigma \cdot \mathcal{L}$ expected. The ''Derivation skim'' includes the requirements that $H_{T}$, the scalar sum of $p_{T}$ of jets and leptons, $H_{T}>150\ \mathrm{GeV}$ or that a ''baseline'' electron or muon has $p_{T}>20\ \mathrm{GeV}$. The definition of ''baseline'' electron/muons, lepton and $\tau$ vetos are described in the main body of the paper. In total 90000 raw MC events with filter efficiency of 0.428 were generated prior to the specified cuts, with the column ''Unweighted yield'' collecting the numbers after each cut.

Signal acceptance in SRA-TT for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$

Signal acceptance in SRA-TT for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$

Signal efficiency in SRA-TT for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.

Signal efficiency in SRA-TT for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.

Signal acceptance in SRA-TW for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$

Signal acceptance in SRA-TW for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$

Signal efficiency in SRA-TW for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.

Signal efficiency in SRA-TW for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.

Signal acceptance in SRA-T0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$

Signal acceptance in SRA-T0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$

Signal efficiency in SRA-T0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.

Signal efficiency in SRA-T0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.

Signal acceptance in SRB-TT for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$

Signal acceptance in SRB-TT for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$

Signal efficiency in SRB-TT for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.

Signal efficiency in SRB-TT for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.

Signal acceptance in SRB-TW for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$

Signal acceptance in SRB-TW for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$

Signal efficiency in SRB-TW for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.

Signal efficiency in SRB-TW for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.

Signal acceptance in SRB-T0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$

Signal acceptance in SRB-T0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$

Signal efficiency in SRB-T0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.

Signal efficiency in SRB-T0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in %.

Signal acceptance in SRC1 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal acceptance in SRC1 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal efficiency in SRC1 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal efficiency in SRC1 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal acceptance in SRC2 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal acceptance in SRC2 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal efficiency in SRC2 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal efficiency in SRC2 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal acceptance in SRC3 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal acceptance in SRC3 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal efficiency in SRC3 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal efficiency in SRC3 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal acceptance in SRC4 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal acceptance in SRC4 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal efficiency in SRC4 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ plane showed in the paper plot.

Signal efficiency in SRC4 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ plane showed in the paper plot.

Signal acceptance in SRC5 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ plane showed in the paper plot.

Signal acceptance in SRC5 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ plane showed in the paper plot.

Signal efficiency in SRC5 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal efficiency in SRC5 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal acceptance in SRD0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal acceptance in SRD0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal efficiency in SRD0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal efficiency in SRD0 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal acceptance in SRD1 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal acceptance in SRD1 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal efficiency in SRD1 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal efficiency in SRD1 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal acceptance in SRD2 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal acceptance in SRD2 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the acceptance given in the table is multiplied by factor of $10^{5}$ and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal efficiency in SRD2 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Signal efficiency in SRD2 for simplified $(\tilde{t},\tilde{\chi^{0}_1})$ model. Please mind that the efficiency in the table is reported in % and the results are given here in the $\it{m}_{\tilde{t}}-\it{m}_{\tilde{\chi}^{0}_{1}}$ plane as opposed to the $\it{m}_{\tilde{t}}-\Delta(\it{m}_{\tilde{\chi}^{0}_{1}},\it{m}_{\tilde{t}})$ one showed in the paper plot.

Post-fit yields for data and prediction in each of the single-bin signal regions of the analysis.

Observed 95% confidence level limit for the two-step signal grid.

Observed 95% confidence level limit for the two-step signal grid with the signal cross section increased by one sigma.

Observed 95% confidence level limit for the two-step signal grid with the signal cross section decreased by one sigma.

Expected 95% confidence level limit for the two-step signal grid.

Expected 95% confidence level limit for the two-step signal grid plus one sigma from experimental systematics.

Expected 95% confidence level limit for the two-step signal grid minus one sigma from experimental systematics.

Observed 95% confidence level limit for the Gtt signal grid.

Observed 95% confidence level limit for the Gtt signal grid with the signal cross section increased by one sigma.

Observed 95% confidence level limit for the Gtt signal grid with the signal cross section decreased by one sigma.

Expected 95% confidence level limit for the Gtt signal grid.

Expected 95% confidence level limit for the Gtt signal grid plus one sigma from experimental systematics.

Expected 95% confidence level limit for the Gtt signal grid minus one sigma from experimental systematics.

Observed 95% confidence level limit for the RPV signal grid.

Observed 95% confidence level limit for the RPV signal grid with the signal cross section increased by one sigma.

Observed 95% confidence level limit for the RPV signal grid with the signal cross section decreased by one sigma.

Expected 95% confidence level limit for the RPV signal grid.

Expected 95% confidence level limit for the RPV signal grid plus one sigma from experimental systematics.

Expected 95% confidence level limit for the RPV signal grid minus one sigma from experimental systematics.

Observed 95% confidence level limit for the two-step signal grid.

Expected 95% confidence level limit for the two-step signal grid.

Observed 95% confidence level limit for the Gtt signal grid.

Expected 95% confidence level limit for the Gtt signal grid.

Observed 95% confidence level limit for the RPV signal grid.

Expected 95% confidence level limit for the RPV signal grid.

$\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ distribution in the signal region SR-10ij50-0ib-MJ340. Two benchmark signal models are shown along with the background yields. These models, each representing a single mass point, are labelled 'RPV' with $(m_{\tilde{g}}, m_{\tilde{t}}) = (1600, 600) \, \mathrm{GeV}$ and 'two-step' with $(m_{\tilde{g}}, m_{\tilde{\chi^{0}_{1}}}) = (1600, 100) \, \mathrm{GeV}$.

$\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ distribution in the signal region SR-12ij50-2ib. Two benchmark signal models are shown along with the background yields. These models, each representing a single mass point, are labelled 'RPV' with $(m_{\tilde{g}}, m_{\tilde{t}}) = (1600, 600) \, \mathrm{GeV}$ and 'two-step' with $(m_{\tilde{g}}, m_{\tilde{\chi^{0}_{1}}}) = (1600, 100) \, \mathrm{GeV}$.

$\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ distribution in the signal region SR-9ij80-0ib. Two benchmark signal models are shown along with the background yields. These models, each representing a single mass point, are labelled 'RPV' with $(m_{\tilde{g}}, m_{\tilde{t}}) = (1600, 600) \, \mathrm{GeV}$ and 'two-step' with $(m_{\tilde{g}}, m_{\tilde{\chi^{0}_{1}}}) = (1600, 100) \, \mathrm{GeV}$.

Number of signal events expected for $139 \, \mathrm{fb}^{-1} $ after different analysis selections in the signal region SR-8ij50-0ib-MJ500. This 'two-step' model requires that a strongly produced gluino decays into quarks, the W and Z bosons, and the lightest stable neutralino where $(m_{\tilde{g}}, m_{\tilde{\chi^{0}_{1}}}) = (1600, 100) \, \mathrm{GeV}$.

Number of signal events expected for $139 \, \mathrm{fb}^{-1} $ after different analysis selections in the signal region SR-9ij50-0ib-MJ340. This 'two-step' model requires that a strongly produced gluino decays into quarks, the W and Z bosons, and the lightest stable neutralino where $(m_{\tilde{g}}, m_{\tilde{\chi^{0}_{1}}}) = (1600, 100) \, \mathrm{GeV}$.

Number of signal events expected for $139 \, \mathrm{fb}^{-1} $ after different analysis selections in the signal region SR-10ij50-0ib-MJ340. This 'two-step' model requires that a strongly produced gluino decays into quarks, the W and Z bosons, and the lightest stable neutralino where $(m_{\tilde{g}}, m_{\tilde{\chi^{0}_{1}}}) = (1600, 100) \, \mathrm{GeV}$.

Number of signal events expected for $139 \, \mathrm{fb}^{-1} $ after different analysis selections in the signal region SR-10ij50-0ib-MJ500. This 'two-step' model requires that a strongly produced gluino decays into quarks, the W and Z bosons, and the lightest stable neutralino where $(m_{\tilde{g}}, m_{\tilde{\chi^{0}_{1}}}) = (1600, 100) \, \mathrm{GeV}$.

Number of signal events expected for $139 \, \mathrm{fb}^{-1} $ after different analysis selections in the signal region SR-10ij50-1ib-MJ500. This 'two-step' model requires that a strongly produced gluino decays into quarks, the W and Z bosons, and the lightest stable neutralino where $(m_{\tilde{g}}, m_{\tilde{\chi^{0}_{1}}}) = (1600, 100) \, \mathrm{GeV}$.

Number of signal events expected for $139 \, \mathrm{fb}^{-1} $ after different analysis selections in the signal region SR-11ij50-0ib. This 'two-step' model requires that a strongly produced gluino decays into quarks, the W and Z bosons, and the lightest stable neutralino where $(m_{\tilde{g}}, m_{\tilde{\chi^{0}_{1}}}) = (1600, 100) \, \mathrm{GeV}$.

Number of signal events expected for $139 \, \mathrm{fb}^{-1} $ after different analysis selections in the signal region SR-12ij50-2ib. This 'two-step' model requires that a strongly produced gluino decays into quarks, the W and Z bosons, and the lightest stable neutralino where $(m_{\tilde{g}}, m_{\tilde{\chi^{0}_{1}}}) = (1600, 100) \, \mathrm{GeV}$.

Number of signal events expected for $139 \, \mathrm{fb}^{-1} $ after different analysis selections in the signal region SR-9ij80-0ib. This 'two-step' model requires that a strongly produced gluino decays into quarks, the W and Z bosons, and the lightest stable neutralino where $(m_{\tilde{g}}, m_{\tilde{\chi^{0}_{1}}}) = (1600, 100) \, \mathrm{GeV}$.

Acceptance for the signal region SR-8ij50-0ib-MJ500 showing the acceptance for the complete two-step signal grid.

Efficiency for the signal region SR-8ij50-0ib-MJ500 showing the efficiency for the complete two-step signal grid.

Acceptance for the signal region SR-9ij50-0ib-MJ340 showing the acceptance for the complete two-step signal grid.

Efficiency for the signal region SR-9ij50-0ib-MJ340 showing the efficiency for the complete two-step signal grid.

Acceptance for the signal region SR-10ij50-0ib-MJ340 showing the acceptance for the complete two-step signal grid.

Efficiency for the signal region SR-10ij50-0ib-MJ340 showing the efficiency for the complete two-step signal grid.

Acceptance for the signal region SR-10ij50-0ib-MJ500 showing the acceptance for the complete two-step signal grid.

Efficiency for the signal region SR-10ij50-0ib-MJ500 showing the efficiency for the complete two-step signal grid.

Acceptance for the signal region SR-10ij50-1ib-MJ500 showing the acceptance for the complete two-step signal grid.

Efficiency for the signal region SR-10ij50-1ib-MJ500 showing the efficiency for the complete two-step signal grid.

Acceptance for the signal region SR-11ij50-0ib showing the acceptance for the complete two-step signal grid.

Efficiency for the signal region SR-11ij50-0ib showing the efficiency for the complete two-step signal grid.

Acceptance for the signal region SR-12ij50-2ib showing the acceptance for the complete two-step signal grid.

Efficiency for the signal region SR-12ij50-2ib showing the efficiency for the complete two-step signal grid.

Acceptance for the signal region SR-9ij80-0ib showing the acceptance for the complete two-step signal grid.

Efficiency for the signal region SR-9ij80-0ib showing the efficiency for the complete two-step signal grid.

The normalisation factors for the dominant backgrounds of the analysis in each of the multi-bin and single-bin regions.

Post-fit yields for data and prediction in each of the single-bin validation regions to test the $N_{\mathrm{jet}}$ extraction.

Post-fit yields for data and prediction in each of the single-bin validation regions to test the $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ extrapolation.

Post-fit yields for data and prediction in each of the multi-bin validation regions to test the $N_{\mathrm{jet}}$ extraction.

Post-fit yields for data and prediction in each of the multi-bin validation regions to test the $\mathcal{S}(E_{\mathrm{T}}^{\mathrm{miss}})$ extrapolation.

The observed Cls from the best expected signal regions for the two-step decay.

The observed Cls from the best expected signal regions for the Gtt decay.

The observed Cls from the best expected signal regions for the RPV decay.

Number of events in each signal region broken down by background type and the number of observed data events.

From left to right; the $95\%$ CL upper limits on the visible cross section (${\langle \epsilon\sigma \rangle}^{95}_{obs}$) and on the number of signal events. Next is the $95\%$ CL upper limit on the number of signal events, given the expected number of background events. The last two columns show the confidence level for the background only hypothesis ($CL_{b}$) and the dicovery $p$-value along with the Gaussian significance (Z).

Visualisation of the highest jet multiplicity event selected in signal regions targeting long cascade decays of pair-produced gluinos. This event was recorded by ATLAS on 23 October 2016, and contains 16 jets, illustrated by cones. Yellow blocks represent the calorimeter energy measured in noise-suppressed clusters. Of the reconstructed jets, 13 (11) have transverse momenta above 50 GeV (80 GeV), with 3 (2) being b-tagged. The leading jet has a transverse momentum of 507 GeV, and the sum of jet transverse momenta $H_T=2.9$ TeV. A value of 343 GeV is observed for the $E_{T}^{miss}$, whose direction is shown by the dashed red line, producing a significance $S(E_{T}^{miss})=6.4$. The sum of the masses of large-radius jets is evaluated as $M_{J}^{\Sigma}=1070$ GeV.

Visualisation of the highest jet multiplicity event selected in a control region used to make predictions of the background from multijet production. This event was recorded by ATLAS on 18 July 2018, and contains 19 jets, illustrated by cones. Yellow blocks represent the calorimeter energy measured in in noise-suppressed clusters. Of the reconstructed jets, 16 (10) have transverse momenta above 50 GeV (80 GeV). No jets were b-tagged. The leading et has a transverse momentum of 371 GeV, and the sum of jet transverse momenta $H_T=2.2$ TeV. A value of 8 GeV is observed for the $E_{T}^{miss}$, whose direction is shown by the dashed red line, producing a significance $S(E_{T}^{miss})=0.2$. The sum of the masses of large-radius jets is evaluated as $M_{J}^{\Sigma}=767$ GeV.

Expected exclusion limits at 95% CL from Fig 7(a) for $\tilde{g}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

One $\sigma$ band of expected exclusion limits at 95% CL from Fig 7(a) for $\tilde{g}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

Observed exclusion limits at 95% CL from Fig 7(c) for $\tilde{g}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Positive one $\sigma$ observed exclusion limits at 95% CL from Fig 7(c) for $\tilde{g}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Negative one $\sigma$ observed exclusion limits at 95% CL from Fig 7(c) for $\tilde{g}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Expected exclusion limits at 95% CL from Fig 7(c) for $\tilde{g}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

One $\sigma$ band of expected exclusion limits at 95% CL from Fig 7(c) for $\tilde{g}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Observed exclusion limits at 95% CL from Fig 7(f) for $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$

Positive one $\sigma$ observed exclusion limits at 95% CL from Fig 7(f) for $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$

Negative one $\sigma$ observed exclusion limits at 95% CL from Fig 7(f) for $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$

Expected exclusion limits at 95% CL from Fig 7(f) for $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$

One $\sigma$ band of expected exclusion limits at 95% CL from Fig 7(f) for $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$

Observed exclusion limits at 95% CL from Fig 7(e) for direct $\tilde{\chi_{1}^{0}}$ decay into SM leptons and quarks via a non-zero RPV coupling $\lambda'$

Positive one $\sigma$ observed exclusion limits at 95% CL from Fig 7(e) for direct $\tilde{\chi_{1}^{0}}$ decay into SM leptons and quarks via a non-zero RPV coupling $\lambda'$

Negative one $\sigma$ observed exclusion limits at 95% CL from Fig 7(e) for direct $\tilde{\chi_{1}^{0}}$ decay into SM leptons and quarks via a non-zero RPV coupling $\lambda'$

Expected exclusion limits at 95% CL from Fig 7(e) for direct $\tilde{\chi_{1}^{0}}$ decay into SM leptons and quarks via a non-zero RPV coupling $\lambda'$

One $\sigma$ band of expected exclusion limits at 95% CL from Fig 7(e) for direct $\tilde{\chi_{1}^{0}}$ decay into SM leptons and quarks via a non-zero RPV coupling $\lambda'$

Observed exclusion limits at 95% CL from Fig 7(b) for $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

Positive one $\sigma$ observed exclusion limits at 95% CL from Fig 7(b) for $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

Negative one $\sigma$ observed exclusion limits at 95% CL from Fig 7(b) for $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

Expected exclusion limits at 95% CL from Fig 7(b) for $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

One $\sigma$ band of expected exclusion limits at 95% CL from Fig 7(b) for $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

Observed exclusion limits at 95% CL from Fig 7(d) for $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Positive one $\sigma$ observed exclusion limits at 95% CL from Fig 7(d) for $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Negative one $\sigma$ observed exclusion limits at 95% CL from Fig 7(d) for $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Expected exclusion limits at 95% CL from Fig 7(d) for $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

One $\sigma$ band of expected exclusion limits at 95% CL from Fig 7(d) for $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

N-1 distribution for $m_{\mathrm{eff}}$of observed data and expected background in SRGGWZ-H.

N-1 distribution for $E_{\mathrm{T}}^{\mathrm{miss}}$of observed data and expected background in SRGGSlep-M.

N-1 distribution for $\sum{p_{\mathrm{T}}^\mathrm{jet}}$of observed data and expected background in SRUDD-ge2b.

N-1 distribution for $m_{\mathrm{eff}}$of observed data and expected background in SRLQD.

N-1 distribution for $m_{\mathrm{eff}}$of observed data and expected background in SRSSWZ-H.

N-1 distribution for $m_{\mathrm{eff}}$of observed data and expected background in SRSSSlep-H(loose).

Signal acceptance for SRGGWZ-H signal region from Fig 10(c) in a SUSY scenario where $\tilde{g}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

Signal efficiency for SRGGWZ-H signal region from Fig 15(c) in a SUSY scenario where $\tilde{g}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

Signal acceptance for SRGGWZ-M signal region from Fig 10(b) in a SUSY scenario where $\tilde{g}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

Signal efficiency for SRGGWZ-M signal region from Fig 15(b) in a SUSY scenario where $\tilde{g}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

Signal acceptance for SRGGWZ-L signal region from Fig 10(a) in a SUSY scenario where $\tilde{g}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

Signal efficiency for SRGGWZ-L signal region from Fig 15(a) in a SUSY scenario where $\tilde{g}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

Signal acceptance for SRGGSlep-L signal region from Fig 12(a) in a SUSY scenario where $\tilde{g}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Signal efficiency for SRGGSlep-L signal region from Fig 17(a) in a SUSY scenario where $\tilde{g}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Signal acceptance for SRGGSlep-M signal region from Fig 12(b) in a SUSY scenario where $\tilde{g}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Signal efficiency for SRGGSlep-M signal region from Fig 17(b) in a SUSY scenario where $\tilde{g}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Signal acceptance for SRGGSlep-H signal region from Fig 12(c) in a SUSY scenario where $\tilde{g}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Signal efficiency for SRGGSlep-H signal region from Fig 17(c) in a SUSY scenario where $\tilde{g}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Signal acceptance for SRUDD-1b signal region from Fig 14(b) in a SUSY scenario where $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$

Signal efficiency for SRUDD-1b signal region from Fig 19(b) in a SUSY scenario where $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$

Signal acceptance for SRUDD-2b signal region from Fig 14(c) in a SUSY scenario where $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$

Signal efficiency for SRUDD-2b signal region from Fig 19(c) in a SUSY scenario where $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$

Signal acceptance for SRUDD-ge2b signal region from Fig 14(d) in a SUSY scenario where $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$

Signal efficiency for SRUDD-ge2b signal region from Fig 19(d) in a SUSY scenario where $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$

Signal acceptance for SRUDD-ge3b signal region from Fig 14(e) in a SUSY scenario where $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$

Signal efficiency for SRUDD-ge3b signal region from Fig 19(e) in a SUSY scenario where $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$

Signal acceptance for SRLQD signal region from Fig 14(a) in a SUSY scenario where direct $\tilde{\chi_{1}^{0}}$ decay into SM leptons and quarks via a non-zero RPV coupling $\lambda'$

Signal efficiency for SRLQD signal region from Fig 19(a) in a SUSY scenario where direct $\tilde{\chi_{1}^{0}}$ decay into SM leptons and quarks via a non-zero RPV coupling $\lambda'$

Signal acceptance for SRSSWZ-L signal region from Fig 11(a) in a SUSY scenario where $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

Signal efficiency for SRSSWZ-L signal region from Fig 16(a) in a SUSY scenario where $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

Signal acceptance for SRSSWZ-ML signal region from Fig 11(b) in a SUSY scenario where $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

Signal efficiency for SRSSWZ-ML signal region from Fig 16(b) in a SUSY scenario where $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

Signal acceptance for SRSSWZ-MH signal region from Fig 11(c) in a SUSY scenario where $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

Signal efficiency for SRSSWZ-MH signal region from Fig 16(c) in a SUSY scenario where $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

Signal acceptance for SRSSWZ-H signal region from Fig 11(d) in a SUSY scenario where $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

Signal efficiency for SRSSWZ-H signal region from Fig 16(d) in a SUSY scenario where $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

Signal acceptance for SRSSSlep-H signal region from Fig 13(d) in a SUSY scenario where $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Signal efficiency for SRSSSlep-H signal region from Fig 18(d) in a SUSY scenario where $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Signal acceptance for SRSSSlep-MH signal region from Fig 13(c) in a SUSY scenario where $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Signal efficiency for SRSSSlep-MH signal region from Fig 18(c) in a SUSY scenario where $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Signal acceptance for SRSSSlep-L signal region from Fig 13(a) in a SUSY scenario where $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Signal efficiency for SRSSSlep-L signal region from Fig 18(a) in a SUSY scenario where $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Signal acceptance for SRSSSlep-ML signal region from Fig 13(b) in a SUSY scenario where $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Signal efficiency for SRSSSlep-ML signal region from Fig 18(b) in a SUSY scenario where $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Signal acceptance for SRSSSlep-H(loose) signal region from Fig 13(e) in a SUSY scenario where $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Signal efficiency for SRSSSlep-H(loose) signal region from Fig 18(e) in a SUSY scenario where $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRGGWZ-H in a susy scenario where $\tilde{g}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$. The masses of the superpartners involved in the process are set to $m(\tilde{g})$ = 1400 GeV, $m(\tilde{\chi_{1}^{0}})$ = 1000 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRGGWZ-M in a susy scenario where $\tilde{g}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$. The masses of the superpartners involved in the process are set to $m(\tilde{g})$ = 1400 GeV, $m(\tilde{\chi_{1}^{0}})$ = 1000 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRGGWZ-L in a susy scenario where $\tilde{g}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$. The masses of the superpartners involved in the process are set to $m(\tilde{g})$ = 1400 GeV, $m(\tilde{\chi_{1}^{0}})$ = 1000 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRGGSlep-L in a susy scenario where $\tilde{g}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$. The masses of the superpartners involved in the process are set to $m(\tilde{g})$ = 2000 GeV, $m(\tilde{\chi_{1}^{0}})$ = 500 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRGGSlep-M in a susy scenario where $\tilde{g}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$. The masses of the superpartners involved in the process are set to $m(\tilde{g})$ = 2000 GeV, $m(\tilde{\chi_{1}^{0}})$ = 500 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRGGSlep-H in a susy scenario where $\tilde{g}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$. The masses of the superpartners involved in the process are set to $m(\tilde{g})$ = 2000 GeV, $m(\tilde{\chi_{1}^{0}})$ = 500 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRUDD-1b in a susy scenario where $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$. The masses of the superpartners involved in the process are set to $m(\tilde{g})$ = 1600 GeV, $m(\tilde{t})$ = 600 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRUDD-2b in a susy scenario where $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$. The masses of the superpartners involved in the process are set to $m(\tilde{g})$ = 1600 GeV, $m(\tilde{t})$ = 600 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRUDD-ge2b in a susy scenario where $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$. The masses of the superpartners involved in the process are set to $m(\tilde{g})$ = 1600 GeV, $m(\tilde{t})$ = 600 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRUDD-ge3b in a susy scenario where $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$. The masses of the superpartners involved in the process are set to $m(\tilde{g})$ = 1600 GeV, $m(\tilde{t})$ = 600 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRLQD in a susy scenario where direct $\tilde{\chi_{1}^{0}}$ decay into SM leptons and quarks via a non-zero RPV coupling $\lambda'$. The masses of the superpartners involved in the process are set to $m(\tilde{g})$ = 2200 GeV, $m(\tilde{\chi_{1}^{0}})$ = 1870 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRSSWZ-L in a susy scenario where $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$. The masses of the superpartners involved in the process are set to $m(\tilde{q})$ = 800 GeV, $m(\tilde{\chi_{1}^{0}})$ = 600 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRSSWZ-ML in a susy scenario where $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$. The masses of the superpartners involved in the process are set to $m(\tilde{q})$ = 800 GeV, $m(\tilde{\chi_{1}^{0}})$ = 600 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRSSWZ-MH in a susy scenario where $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$. The masses of the superpartners involved in the process are set to $m(\tilde{q})$ = 800 GeV, $m(\tilde{\chi_{1}^{0}})$ = 600 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRSSWZ-H in a susy scenario where $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$. The masses of the superpartners involved in the process are set to $m(\tilde{q})$ = 800 GeV, $m(\tilde{\chi_{1}^{0}})$ = 600 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRSSSlep-H in a susy scenario where $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$. The masses of the superpartners involved in the process are set to $m(\tilde{q})$ = 1000 GeV, $m(\tilde{\chi_{1}^{0}})$ = 800 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRSSSlep-MH in a susy scenario where $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$. The masses of the superpartners involved in the process are set to $m(\tilde{q})$ = 1000 GeV, $m(\tilde{\chi_{1}^{0}})$ = 800 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRSSSlep-L in a susy scenario where $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$. The masses of the superpartners involved in the process are set to $m(\tilde{q})$ = 1000 GeV, $m(\tilde{\chi_{1}^{0}})$ = 800 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRSSSlep-ML in a susy scenario where $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$. The masses of the superpartners involved in the process are set to $m(\tilde{q})$ = 1000 GeV, $m(\tilde{\chi_{1}^{0}})$ = 800 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region SRSSSlep-H(loose) in a susy scenario where $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$. The masses of the superpartners involved in the process are set to $m(\tilde{q})$ = 1000 GeV, $m(\tilde{\chi_{1}^{0}})$ = 800 GeV. Only statistical uncertainties are shown.

Cross-section upper limits at 95% CL from Fig1(a) for $\tilde{g}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

Cross-section upper limits at 95% CL from Fig1(c) for $\tilde{g}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Cross-section upper limits at 95% CL from Fig1(f) for $\tilde{g}$ decays into anti-top and $\tilde{t}$ and $\tilde{t}$ decays via a non-zero RPV coupling $\lambda''$

Cross-section upper limits at 95% CL from Fig1(e) for direct $\tilde{\chi_{1}^{0}}$ decay into SM leptons and quarks via a non-zero RPV coupling $\lambda'$

Cross-section upper limits at 95% CL from Fig1(b) for $\tilde{q}$ decays into SM gauge bosons and $\tilde{\chi}^{0}_{1}$

Cross-section upper limits at 95% CL from Fig1(d) for $\tilde{q}$ decays into sleptons and subsequently to SM leptons and $\tilde{\chi}^{0}_{1}$

Distribution of the missing transverse momentum in validation region VR2. The solid histograms are stacked to show the SM expectations after the 2&times;2D background estimation technique is applied. Background and signal predictions are normalised to the luminosity. The background category "h (other)" includes events originating from VBF, Vh, ggF, thq, thW and bb&#772;h, all subdominant in this signature. Statistical and systematic uncertainties are indicated by the shaded area. The lower panel of each plot shows the ratio of the data to the SM prediction for the respective bin. The first and last bins include the underflows and overflows respectively.

Distribution of the diphoton invariant mass with all selections of the signal regions applied, except on m_{&gamma;&gamma;} itself, for signal region SR1h. The background estimation techniques described in the text are applied. The different backgrounds are stacked to add up to the total SM prediction in each bin. The predicted yields for signal benchmark models of varying &chi;&#771;⁰₁ mass are also overlaid (not stacked) assuming B(&chi;&#771;⁰₁ &rarr; hG&#771; ) to equal 100%. Background and signal predictions are normalised to the luminosity. The background category "h (other)" includes events originating from VBF, Vh, ggF, thq, thW and bb&#772;h, all subdominant in this signature. The sizes of the statistical and systematic uncertainties are indicated by the shaded areas. The lower panels show the ratio of the data to the SM prediction. Arrows indicate the borders of the signal region (|m_{&gamma;&gamma;}-125 GeV|&lt;5 GeV). The first and last bins include the underflows and overflows respectively.

Distribution of the diphoton invariant mass with all selections of the signal regions applied, except on m_{&gamma;&gamma;} itself, for signal region SR1Z. The background estimation techniques described in the text are applied. The different backgrounds are stacked to add up to the total SM prediction in each bin. The predicted yields for signal benchmark models of varying &chi;&#771;⁰₁ mass are also overlaid (not stacked) assuming B(&chi;&#771;⁰₁ &rarr; hG&#771; ) to equal 50%. Background and signal predictions are normalised to the luminosity. The background category "h (other)" includes events originating from VBF, Vh, ggF, thq, thW and bb&#772;h, all subdominant in this signature. The sizes of the statistical and systematic uncertainties are indicated by the shaded areas. The lower panels show the ratio of the data to the SM prediction. Arrows indicate the borders of the signal region (|m_{&gamma;&gamma;}-125 GeV|&lt;5 GeV). The first and last bins include the underflows and overflows respectively.

Distribution of the diphoton invariant mass with all selections of the signal regions applied, except on m_{&gamma;&gamma;} itself, for signal region SR2. The background estimation techniques described in the text are applied. The different backgrounds are stacked to add up to the total SM prediction in each bin. The predicted yields for signal benchmark models of varying &chi;&#771;⁰₁ mass are also overlaid (not stacked) assuming B(&chi;&#771;⁰₁ &rarr; hG&#771; ) to equal 100%. Background and signal predictions are normalised to the luminosity. The background category "h (other)" includes events originating from VBF, Vh, ggF, thq, thW and bb&#772;h, all subdominant in this signature. The sizes of the statistical and systematic uncertainties are indicated by the shaded areas. The lower panels show the ratio of the data to the SM prediction. Arrows indicate the borders of the signal region (|m_{&gamma;&gamma;}-125 GeV|&lt;5 GeV). The first and last bins include the underflows and overflows respectively.

Observed and expected limits on the pure higgsino cross-section at 95% CL assuming B(&chi;&#771;⁰₁ &rarr; hG&#771; )=100% for different &chi;&#771;⁰₁ masses, obtained by a statistical combination of the three signal regions SR1h, SR1Z and SR2. The inner and outer bands indicate the 1&sigma; and 2&sigma; variation on the expected limit respectively.

Observed and expected 95% CL limits on the pure-higgsino branching fraction to B(&chi;&#771;⁰₁ &rarr; hG&#771; ) as a function of the higgsino mass m(&chi;&#771;⁰₁) assuming it decays via either &chi;&#771;⁰₁&rarr; hG&#771; or &chi;&#771;⁰₁&rarr; ZG&#771;. Limits are obtained by performing a statistical combination of the three signal regions SR1h, SR1Z and SR2. The &plusmn; 1&sigma; variation on the expected limit is shown. The dotted lines indicate the observed limit obtained by a variation of theoretical prediction for the neutralino production cross-section by &plusmn;1 &sigma;. Values of B(&chi;&#771;⁰₁ &rarr; hG&#771; ) larger than the observed 95% CL limit are excluded, as indicated by the hatched area.

Observed and expected 95% CL limits on the pure-higgsino branching fraction to B(&chi;&#771;⁰₁ &rarr; hG&#771; ) as a function of the higgsino mass m(&chi;&#771;⁰₁) assuming it decays via either &chi;&#771;⁰₁&rarr; hG&#771; or &chi;&#771;⁰₁&rarr; ZG&#771;. Limits are obtained by performing a statistical combination of the three signal regions SR1h, SR1Z and SR2. The &plusmn; 1&sigma; variation on the expected limit is shown. The dotted lines indicate the observed limit obtained by a variation of theoretical prediction for the neutralino production cross-section by &plusmn;1 &sigma;. Values of B(&chi;&#771;⁰₁ &rarr; hG&#771; ) larger than the observed 95% CL limit are excluded, as indicated by the hatched area.

Observed and expected 95% CL limits on the pure-higgsino branching fraction to B(&chi;&#771;⁰₁ &rarr; hG&#771; ) as a function of the higgsino mass m(&chi;&#771;⁰₁) assuming it decays via either &chi;&#771;⁰₁&rarr; hG&#771; or &chi;&#771;⁰₁&rarr; ZG&#771;. Limits are obtained by performing a statistical combination of the three signal regions SR1h, SR1Z and SR2. The &plusmn; 1&sigma; variation on the expected limit is shown. The dotted lines indicate the observed limit obtained by a variation of theoretical prediction for the neutralino production cross-section by &plusmn;1 &sigma;. Values of B(&chi;&#771;⁰₁ &rarr; hG&#771; ) larger than the observed 95% CL limit are excluded, as indicated by the hatched area.

Observed and expected 95% CL limits on the pure-higgsino branching fraction to B(&chi;&#771;⁰₁ &rarr; hG&#771; ) as a function of the higgsino mass m(&chi;&#771;⁰₁) assuming it decays via either &chi;&#771;⁰₁&rarr; hG&#771; or &chi;&#771;⁰₁&rarr; ZG&#771;. Limits are obtained by performing a statistical combination of the three signal regions SR1h, SR1Z and SR2. The &plusmn; 1&sigma; variation on the expected limit is shown. The dotted lines indicate the observed limit obtained by a variation of theoretical prediction for the neutralino production cross-section by &plusmn;1 &sigma;. Values of B(&chi;&#771;⁰₁ &rarr; hG&#771; ) larger than the observed 95% CL limit are excluded, as indicated by the hatched area.

Observed and expected 95% CL limits on the pure-higgsino branching fraction to B(&chi;&#771;⁰₁ &rarr; hG&#771; ) as a function of the higgsino mass m(&chi;&#771;⁰₁) assuming it decays via either &chi;&#771;⁰₁&rarr; hG&#771; or &chi;&#771;⁰₁&rarr; ZG&#771;. Limits are obtained by performing a statistical combination of the three signal regions SR1h, SR1Z and SR2. The &plusmn; 1&sigma; variation on the expected limit is shown. The dotted lines indicate the observed limit obtained by a variation of theoretical prediction for the neutralino production cross-section by &plusmn;1 &sigma;. Values of B(&chi;&#771;⁰₁ &rarr; hG&#771; ) larger than the observed 95% CL limit are excluded, as indicated by the hatched area.

Observed and expected 95% CL limits on the pure-higgsino branching fraction to B(&chi;&#771;⁰₁ &rarr; hG&#771; ) as a function of the higgsino mass m(&chi;&#771;⁰₁) assuming it decays via either &chi;&#771;⁰₁&rarr; hG&#771; or &chi;&#771;⁰₁&rarr; ZG&#771;. Limits are obtained by performing a statistical combination of the three signal regions SR1h, SR1Z and SR2. The &plusmn; 1&sigma; variation on the expected limit is shown. The dotted lines indicate the observed limit obtained by a variation of theoretical prediction for the neutralino production cross-section by &plusmn;1 &sigma;. Values of B(&chi;&#771;⁰₁ &rarr; hG&#771; ) larger than the observed 95% CL limit are excluded, as indicated by the hatched area.

Numbers of signal and background events in the signal regions. The respective background estimation techniques are applied. The background category "h (other)" includes events originating from VBF, Vh, ggF, thq, thW and bb&#772;h, all subdominant in this signature. The different backgrounds are stacked to add up to the total Standard Model prediction in each bin. The predicted yields for signal benchmark models of varying &chi;&#771;⁰₁ mass are also plotted (not stacked), assuming B(&chi;&#771;⁰₁ &rarr; hG&#771; )=100% and a &chi;&#771;⁰₁ mass of 130 or 200 GeV. The statistical and systematic uncertainties are indicated by the shaded areas in the top plot. The bottom panel shows the statistical significance&nbsp;<a href="https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2020-025/">[Ref]</a> of the difference between the SM prediction and the observed data in each region.

Observed 95% CL limits in pb on the pure higgsino cross-section, shown in the m(&chi;&#771;⁰₁)-B(&chi;&#771;⁰₁ &rarr; hG&#771; ) plane. Limits are obtained by a statistical combination of the three signal regions SR1h, SR1Z and SR2, assuming the neutralino to decay via either &chi;&#771;⁰₁&rarr; hG&#771; or &chi;&#771;⁰₁&rarr; ZG&#771;.

Acceptances for all signal model points considered in the analysis, shown in the m(&chi;&#771;⁰₁)-B(&chi;&#771;⁰₁ &rarr; hG&#771; ) plane. Acceptances are provided separately for signal region SR1h, assuming the neutralino to decay via either &chi;&#771;⁰₁&rarr; hG&#771; or &chi;&#771;⁰₁&rarr; ZG&#771;.

Acceptances for all signal model points considered in the analysis, shown in the m(&chi;&#771;⁰₁)-B(&chi;&#771;⁰₁ &rarr; hG&#771; ) plane. Acceptances are provided separately for signal region SR1Z, assuming the neutralino to decay via either &chi;&#771;⁰₁&rarr; hG&#771; or &chi;&#771;⁰₁&rarr; ZG&#771;.

Acceptances for all signal model points considered in the analysis, shown in the m(&chi;&#771;⁰₁)-B(&chi;&#771;⁰₁ &rarr; hG&#771; ) plane. Acceptances are provided separately for signal region SR2, assuming the neutralino to decay via either &chi;&#771;⁰₁&rarr; hG&#771; or &chi;&#771;⁰₁&rarr; ZG&#771;.

Efficiencies for all signal model points considered in the analysis, shown in the m(&chi;&#771;⁰₁)-B(&chi;&#771;⁰₁ &rarr; hG&#771; ) plane. Efficiencies are provided separately for signal region SR1h, assuming the neutralino to decay via either &chi;&#771;⁰₁&rarr; hG&#771; or &chi;&#771;⁰₁&rarr; ZG&#771;.

Efficiencies for all signal model points considered in the analysis, shown in the m(&chi;&#771;⁰₁)-B(&chi;&#771;⁰₁ &rarr; hG&#771; ) plane. Efficiencies are provided separately for signal region SR1Z, assuming the neutralino to decay via either &chi;&#771;⁰₁&rarr; hG&#771; or &chi;&#771;⁰₁&rarr; ZG&#771;.

Efficiencies for all signal model points considered in the analysis, shown in the m(&chi;&#771;⁰₁)-B(&chi;&#771;⁰₁ &rarr; hG&#771; ) plane. Efficiencies are provided separately for signal region SR2, assuming the neutralino to decay via either &chi;&#771;⁰₁&rarr; hG&#771; or &chi;&#771;⁰₁&rarr; ZG&#771;.

Observed and expected numbers of events in the three signal regions. The background category "h (other)" includes events originating from VBF, Vh, ggF, thq, thW and bb&#772;h, all subdominant in this signature. The table also includes model-independent 95% CL upper limits on the visible number of BSM events (S⁹⁵_obs), the number of BSM events given the expected number of background events (S⁹⁵_exp) and the visible BSM cross-section (&lang;&epsilon; &sigma;&rang;_obs⁹⁵), all calculated from pseudo-experiments. The discovery p-value (p₀) is also shown and its value is capped at 0.5 if the observed number of events is below the expected number of events.

Cutflows of two benchmark signal points assuming B(&chi;&#771;⁰₁ &rarr; hG&#771; )=100% for all three discovery signal regions. The initial selection includes the leptons veto. Only statistical uncertainties are included. Expected yields are normalised to a luminosity of 139 fb^-1.