Vertex selection efficiency for the $\tilde{t}$ $R$-hadron benchmark model as a function of the transverse decay distance $r_{DV}$.

Track multiplicity $n_{Tracks}$ for preselected DVs in MET-triggered events with at least one muon passing the full selection. Along with the data shown with black markers, the stacked filled histograms represent the background estimates, and predictions for signal scenarios are overlaid with dashed lines. The errors include statistical and systematic uncertainties and are indicated by hatched bands. The DV full selection requirements, $n_{Tracks} \geq 3$ and $m_{DV} > 20$ GeV are visualized with a black arrow.

Track multiplicity $n_{Tracks}$ for preselected DVs in MET-triggered events with at least one muon passing the full selection. Along with the data shown with black markers, the stacked filled histograms represent the background estimates, and predictions for signal scenarios are overlaid with dashed lines. The errors include statistical and systematic uncertainties and are indicated by hatched bands. The DV full selection requirements, $n_{Tracks} \geq 3$ and $m_{DV} > 20$ GeV are visualized with a black arrow.

Track multiplicity $n_{Tracks}$ for preselected DVs in muon-triggered events with at least one muon passing the full selection. Along with the data shown with black markers, the stacked filled histograms represent the background estimates, and predictions for signal scenarios are overlaid with dashed lines. The errors include statistical and systematic uncertainties and are indicated by hatched bands. The DV full selection requirements, $n_{Tracks} \geq 3$ and $m_{DV} > 20$ GeV are visualized with a black arrow.

Invariant mass $m_{DV}$ for the highest-mass preselected DV with at least three associated tracks in MET-triggered events with at least one muon passing the full selection. Along with the data shown with black markers, the stacked filled histograms represent the background estimates, and predictions for signal scenarios are overlaid with dashed lines. The errors include statistical and systematic uncertainties and are indicated by hatched bands. The DV full selection requirements, $n_{Tracks} \geq 3$ and $m_{DV} > 20$ GeV are visualized with a black arrow.

Invariant mass $m_{DV}$ for the highest-mass preselected DV with at least three associated tracks in muon-triggered events with at least one muon passing the full selection. Along with the data shown with black markers, the stacked filled histograms represent the background estimates, and predictions for signal scenarios are overlaid with dashed lines. The errors include statistical and systematic uncertainties and are indicated by hatched bands. The DV full selection requirements, $n_{Tracks} \geq 3$ and $m_{DV} > 20$ GeV are visualized with a black arrow.

The observed event yields in the control, validation and signal regions are shown for the MET Trigger selections, along with the predicted background yields. The bottom panel shows the ratio of observed events to the total background yields. The errors represent the total uncertainty of the backgrounds prediction, including the statistical and systematic uncertainties added in quadrature.

The observed event yields in the control, validation and signal regions are shown for the Muon Trigger selections, along with the predicted background yields. The bottom panel shows the ratio of observed events to the total background yields. The errors represent the total uncertainty of the backgrounds prediction, including the statistical and systematic uncertainties added in quadrature.

Expected exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.

Expected (1 sigma band) exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.

Expected (2 sigma band) exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.

Observed exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.

Observed exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.

Observed (+1 sigma) exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.

Observed (-1 sigma) exclusion limits at 95% CL on m($\tilde{t}$) as a function of $\tau(\tilde{t})$.

Exclusion limits on the production cross section as a function of m($\tilde{t}$) are shown for several values of $\tau(\tilde{t})$ along with the nominal signal production cross section and its theoretical uncertainty.

Parameterized event selection efficiencies for the $E_{T}^{miss}$ Trigger SR. The event-level efficiencies for each SR are extracted for all events passing the acceptance of the corresponding SR.

Parameterized event selection efficiencies for the Muon Trigger SR. The event-level efficiencies for each SR are extracted for all events passing the acceptance of the corresponding SR.

Parameterized muon-level reconstruction efficiencies as a function of the muon $p_{T}$ and $d_{0}$. The muon-level efficiencies are extracted using muons passing the muon acceptance criteria.

Parameterized muon-level reconstruction efficiencies as a function of the muon $p_{T}$ and $d_{0}$. The muon-level efficiencies are extracted using muons passing the muon acceptance criteria.

Parameterized vertex-level reconstruction efficiencies as a function of the radial position of the truth vertex. The efficiency is calculated independent of the muons originating from this truth vertex.

Parameterized vertex-level reconstruction efficiencies as a function of the radial position of the truth vertex. The efficiency is calculated independent of the muons originating from this truth vertex.

Parameterized vertex-level reconstruction efficiencies as a function of the radial position of the truth vertex. The efficiency is calculated only for truth vertices which have a muon originating from them which is matched to a reconstructed muon.

Parameterized vertex-level reconstruction efficiencies as a function of the radial position of the truth vertex. The efficiency is calculated only for truth vertices which have a muon originating from them which is matched to a reconstructed muon.

The $p_{T}$ distribution of all muons originating from LLP decays in the samples used to calculate and validate the efficiencies.

The $p_{T}$ distribution of all muons originating from LLP decays in the samples used to calculate and validate the efficiencies.

The invariant mass and multiplicity of selected decay products of all truth vertices used in the calculation and validation of the reconstructed efficiencies.

The invariant mass and multiplicity of selected decay products of all truth vertices used in the calculation and validation of the reconstructed efficiencies.

Acceptance x efficiency versus $\kappa_{2V}$ for non-resonant signal of $HH$.

Acceptance x efficiency versus resonance mass for both narrow and broad resonance $X$ to $HH$.

Acceptance x efficiency versus resonance mass for both narrow and broad resonance $X$ to $HH$.

Acceptance x efficiency versus resonance mass for both narrow and broad resonance $X$ to $HH$.

Acceptance x efficiency versus resonance mass for both narrow and broad resonance $X$ to $HH$.

Post-fit mass distribution of the $HH$ candidates in the signal region. The expected background is shown after the profile-likelihood fit to data with the background-only hypothesis; the narrow-width resonant signal at 800 GeV and the non-resonant signal at $\kappa_{2V}$ = 3 are overlaid, both normalised to the corresponding observed upper limits on the cross-section.

Post-fit mass distribution of the $HH$ candidates in the signal region. The expected background is shown after the profile-likelihood fit to data with the background-only hypothesis; the narrow-width resonant signal at 800 GeV and the non-resonant signal at $\kappa_{2V}$ = 3 are overlaid, both normalised to the corresponding observed upper limits on the cross-section.

Post-fit mass distribution of the $HH$ candidates in the signal region. The expected background is shown after the profile-likelihood fit to data with the background-only hypothesis; the narrow-width resonant signal at 800 GeV and the non-resonant signal at $\kappa_{2V}$ = 3 are overlaid, both normalised to the corresponding observed upper limits on the cross-section.

Post-fit mass distribution of the $HH$ candidates in the signal region. The expected background is shown after the profile-likelihood fit to data with the background-only hypothesis; the narrow-width resonant signal at 800 GeV and the non-resonant signal at $\kappa_{2V}$ = 3 are overlaid, both normalised to the corresponding observed upper limits on the cross-section.

Observed and expected limits at 95% CL on the cross-sections of narrow resonance $X$ to $HH$ as a function of the mass $m_{X}$.

Observed and expected limits at 95% CL on the cross-sections of narrow resonance $X$ to $HH$ as a function of the mass $m_{X}$.

Observed and expected limits at 95% CL on the cross-sections of narrow resonance $X$ to $HH$ as a function of the mass $m_{X}$.

Observed and expected limits at 95% CL on the cross-section of narrow resonance $X$ to $HH$ as a function of the mass $m_{X}$.

Observed and expected limits at 95% CL on the cross-sections of broad resonance $X$ to $HH$ as a function of the mass $m_{X}$.

Observed and expected limits at 95% CL on the cross-sections of broad resonance $X$ to $HH$ as a function of the mass $m_{X}$.

Observed and expected limits at 95% CL on the cross-sections of broad resonance $X$ to $HH$ as a function of the mass $m_{X}$.

Observed and expected limits at 95% CL on the cross-section of broad resonance $X$ to $HH$ as a function of the mass $m_{X}$.

Observed and expected limits at 95% CL on the cross-sections of non-resonant $HH$ production via VBF as a function of the di-vector-boson-di-Higgs-boson coupling modifier $\kappa_{2V}$. The theory prediction of the cross-section as a function of $\kappa_{2V}$ is also shown. The minimum theory cross-section is 1.37 fb at $\kappa_{2V}=1.17$.

Observed and expected limits at 95% CL on the cross-sections of non-resonant $HH$ production via VBF as a function of the di-vector-boson-di-Higgs-boson coupling modifier $\kappa_{2V}$. The theory prediction of the cross-section as a function of $\kappa_{2V}$ is also shown. The minimum theory cross-section is 1.37 fb at $\kappa_{2V}=1.17$.

Observed and expected limits at 95% CL on the cross-sections of non-resonant $HH$ production via VBF as a function of the di-vector-boson-di-Higgs-boson coupling modifier $\kappa_{2V}$. The theory prediction of the cross-section as a function of $\kappa_{2V}$ is also shown. The minimum theory cross-section is 1.37 fb at $\kappa_{2V}=1.17$.

Observed and expected limits at 95% CL on the cross-sections of non-resonant $HH$ production via VBF as a function of the di-vector-boson-di-Higgs-boson coupling modifier $\kappa_{2V}$. The theory prediction of the cross-section as a function of $\kappa_{2V}$ is also shown. The minimum theory cross-section is 1.37 fb at $\kappa_{2V}=1.17$.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Observed $CL_S$ limits on $\sigma \times BR$ for $m_{\Phi} = 200-400$ GeV.

Observed $CL_S$ limits on $\sigma \times BR$ for $m_{\Phi} = 600-1000$ GeV.

Combined limits from this analysis (ID) and the CR and MS analyses for $m_{H} = 125$ GeV, $m_s = 15$ GeV.

Combined limits from this analysis (ID) and the CR and MS analyses for $m_{H} = 125$ GeV, $m_s = 25$ GeV.

Combined limits from this analysis (ID) and the CR and MS analyses for $m_{H} = 125$ GeV, $m_s = 40$ GeV.

Combined limits from this analysis (ID) and the CR and MS analyses for $m_{H} = 125$ GeV, $m_s = 55$ GeV.

Combined limits from this analysis (ID) and the CR and MS analyses for $m_{\Phi} = 200$ GeV, $m_s = 25$ GeV.

Combined limits from this analysis (ID) and the CR and MS analyses for $m_{\Phi} = 200$ GeV, $m_s = 50$ GeV.

Comparison of the IDVx reconstruction and selection efficiency for a Higgs with a mass of 125 GeV decaying to an LLP with a mass of 8 GeV, using only standard tracking versus using standard and large radius tracking for all ID vertices in the signal MC sample.

Comparison of the IDVx reconstruction and selection efficiency for a Higgs with a mass of 125 GeV decaying to an LLP with a mass of 8 GeV, using only standard tracking versus using standard and large radius tracking for ID vertices passing the full IDVx selection criteria.

Comparison of the IDVx reconstruction and selection efficiency for a $\Phi$ with a mass of 1000 GeV decaying to an LLP with a mass of 150 GeV, using only standard tracking versus using standard and large radius tracking for all ID vertices in the signal MC sample.

Comparison of the IDVx reconstruction and selection efficiency for a $\Phi$ with a mass of 1000 GeV decaying to an LLP with a mass of 150 GeV, using only standard tracking versus using standard and large radius tracking for ID vertices passing the full IDVx selection criteria.

The IDVx selection efficiency as a function of long-lived particle decay $z$ position for MC signal samples with a 125 GeV Higgs boson decaying to LLPs with masses of 8, 25, and 55 GeV. The efficiency for the 55 GeV LLP sample is shown both with and without the material veto applied.

The IDVx selection efficiency as a function of long-lived particle decay $z$ position for MC signal samples with mediators of masses 200, 400, and 600 GeV decaying to LLPs with a mass of 50 GeV. The efficiency for the 200 GeV mediator sample is shown both with and without the material veto applied.

The impact of the IDVx selections on the selection efficiency for the MC signal sample with a Higgs with a mass of 125 GeV decaying to an LLP with a mass of 8 GeV.

The impact of the IDVx selections on the selection efficiency for the MC signal sample with a Higgs with a mass of 125 GeV decaying to an LLP with a mass of 8 GeV.

The impact of the IDVx selections on the selection efficiency for the MC signal sample with a Higgs with a mass of 125 GeV decaying to an LLP with a mass of 8 GeV.

The impact of the IDVx selections on the selection efficiency for the MC signal sample with a $\Phi$ with a mass of 400 GeV decaying to an LLP with a mass of 50 GeV.

The impact of the IDVx selections on the selection efficiency for the MC signal sample with a $\Phi$ with a mass of 400 GeV decaying to an LLP with a mass of 50 GeV.

The impact of the IDVx selections on the selection efficiency for the MC signal sample with a $\Phi$ with a mass of 400 GeV decaying to an LLP with a mass of 50 GeV.

The impact of the IDVx selections on the selection efficiency for the MC signal sample with a $\Phi$ with a mass of 1000 GeV decaying to an LLP with a mass of 150 GeV.

The impact of the IDVx selections on the selection efficiency for the MC signal sample with a $\Phi$ with a mass of 1000 GeV decaying to an LLP with a mass of 150 GeV.

The impact of the IDVx selections on the selection efficiency for the MC signal sample with a $\Phi$ with a mass of 1000 GeV decaying to an LLP with a mass of 150 GeV.

$CL_S$ limits on $B_{H\rightarrow ss}$ for $m_{H} = 125$ GeV, $m_s = 8$ GeV.

$CL_S$ limits on $B_{H\rightarrow ss}$ for $m_{H} = 125$ GeV, $m_s = 15$ GeV.

$CL_S$ limits on $B_{H\rightarrow ss}$ for $m_{H} = 125$ GeV, $m_s = 25$ GeV.

$CL_S$ limits on $B_{H\rightarrow ss}$ for $m_{H} = 125$ GeV, $m_s = 40$ GeV.

$CL_S$ limits on $B_{H\rightarrow ss}$ for $m_{H} = 125$ GeV, $m_s = 55$ GeV.

$CL_S$ limits on $\sigma \times B_{\Phi\rightarrow ss}$ for $m_{\Phi} = 200$ GeV, $m_s = 8$ GeV.

$CL_S$ limits on $\sigma \times B_{\Phi\rightarrow ss}$ for $m_{\Phi} = 200$ GeV, $m_s = 25$ GeV.

$CL_S$ limits on $\sigma \times B_{\Phi\rightarrow ss}$ for $m_{\Phi} = 200$ GeV, $m_s = 50$ GeV.

$CL_S$ limits on $\sigma \times B_{\Phi\rightarrow ss}$ for $m_{\Phi} = 400$ GeV, $m_s = 50$ GeV.

$CL_S$ limits on $\sigma \times B_{\Phi\rightarrow ss}$ for $m_{\Phi} = 400$ GeV, $m_s = 100$ GeV.

$CL_S$ limits on $\sigma \times B_{\Phi\rightarrow ss}$ for $m_{\Phi} = 600$ GeV, $m_s = 50$ GeV.

$CL_S$ limits on $\sigma \times B_{\Phi\rightarrow ss}$ for $m_{\Phi} = 600$ GeV, $m_s = 150$ GeV.

$CL_S$ limits on $\sigma \times B_{\Phi\rightarrow ss}$ for $m_{\Phi} = 1000$ GeV, $m_s = 50$ GeV.

$CL_S$ limits on $\sigma \times B_{\Phi\rightarrow ss}$ for $m_{\Phi} = 1000$ GeV, $m_s = 150$ GeV.

$CL_S$ limits on $\sigma \times B_{\Phi\rightarrow ss}$ for $m_{\Phi} = 1000$ GeV, $m_s = 400$ GeV.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Signal acceptance in SR highMass for combined stau final states

Signal acceptance in SR highMass for combined stau final states

Signal acceptance in SR lowMass for combined stau final states

Signal acceptance in SR lowMass for combined stau final states

Signal efficiency in SR highMass for combined stau final states

Signal efficiency in SR highMass for combined stau final states

Signal efficiency in SR lowMass for combined stau final states

Signal efficiency in SR lowMass for combined stau final states

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Observed 95% CL exclusion contours in signal region Rpc2L0b on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g \to q \bar{q}^{'} \tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm \to W^\pm \tilde{\chi}_2^0$ and $ \tilde{\chi}_2^0 \to Z \tilde{\chi}_1^0$.

Expected 95% CL exclusion contours in signal region Rpc2L0b on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.

Expected 95% CL exclusion contours in signal region Rpc2L0b on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.

Expected 95% CL exclusion contours in signal region Rpc2L0b on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.

Expected 95% CL exclusion contours in signal region Rpc2L0b on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.

Observed 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Observed 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Observed 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Observed 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Expected 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Expected 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Expected 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Expected 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Observed 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Observed 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Observed 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Observed 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Expected 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Expected 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Expected 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Expected 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L0b, in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde \chi_1^\pm)$ = 1200 GeV, $m(\tilde \chi_2^0)$ = 1000 GeV and $m(\tilde \chi_1^0)$ = 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 Rpc2L0b, in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde \chi_1^\pm)$ = 1200 GeV, $m(\tilde \chi_2^0)$ = 1000 GeV and $m(\tilde \chi_1^0)$ = 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 Rpc2L0b, in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde \chi_1^\pm)$ = 1200 GeV, $m(\tilde \chi_2^0)$ = 1000 GeV and $m(\tilde \chi_1^0)$ = 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 Rpc2L0b, in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde \chi_1^\pm)$ = 1200 GeV, $m(\tilde \chi_2^0)$ = 1000 GeV and $m(\tilde \chi_1^0)$ = 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 Rpc2L1b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 850 GeV, $m(\tilde \chi_1^\pm)$ = 500 GeV and $m(\tilde \chi_1^0)$ = 400 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 Rpc2L1b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 850 GeV, $m(\tilde \chi_1^\pm)$ = 500 GeV and $m(\tilde \chi_1^0)$ = 400 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 Rpc2L1b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 850 GeV, $m(\tilde \chi_1^\pm)$ = 500 GeV and $m(\tilde \chi_1^0)$ = 400 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 Rpc2L1b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 850 GeV, $m(\tilde \chi_1^\pm)$ = 500 GeV and $m(\tilde \chi_1^0)$ = 400 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 Rpc2L2b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 850 GeV, $m(\tilde \chi_1^\pm)$ = 500 GeV and $m(\tilde \chi_1^0)$ = 400 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 Rpc2L2b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 900 GeV, $m(\tilde \chi_1^\pm)$ = 150 GeV and $m(\tilde \chi_1^0)$ = 50 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 Rpc2L2b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 900 GeV, $m(\tilde \chi_1^\pm)$ = 150 GeV and $m(\tilde \chi_1^0)$ = 50 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 Rpc2L2b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 900 GeV, $m(\tilde \chi_1^\pm)$ = 150 GeV and $m(\tilde \chi_1^0)$ = 50 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 Rpc3LSS1b, in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate. The masses of the superpartners involved in the process are set to $m(\tilde{t}^{}_1)$ = 800 GeV, $m(\tilde \chi_2^0)$ = 625 GeV, $m(\tilde \chi_1^\pm)\approx m(\tilde \chi_1^0)$ = 525 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 Rpc3LSS1b, in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate. The masses of the superpartners involved in the process are set to $m(\tilde{t}^{}_1)$ = 800 GeV, $m(\tilde \chi_2^0)$ = 625 GeV, $m(\tilde \chi_1^\pm)\approx m(\tilde \chi_1^0)$ = 525 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 Rpc3LSS1b, in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate. The masses of the superpartners involved in the process are set to $m(\tilde{t}^{}_1)$ = 800 GeV, $m(\tilde \chi_2^0)$ = 625 GeV, $m(\tilde \chi_1^\pm)\approx m(\tilde \chi_1^0)$ = 525 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 Rpc3LSS1b, in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate. The masses of the superpartners involved in the process are set to $m(\tilde{t}^{}_1)$ = 800 GeV, $m(\tilde \chi_2^0)$ = 625 GeV, $m(\tilde \chi_1^\pm)\approx m(\tilde \chi_1^0)$ = 525 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 Rpv2L, in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde{t}^{}_{1})$ = 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 Rpv2L, in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde{t}^{}_{1})$ = 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 Rpv2L, in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde{t}^{}_{1})$ = 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 Rpv2L, in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde{t}^{}_{1})$ = 800 GeV. Only statistical uncertainties are shown.

Signal acceptance for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.

Signal acceptance for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.

Signal acceptance for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.

Signal acceptance for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.

Signal acceptance for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Signal acceptance for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Signal acceptance for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Signal acceptance for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Signal acceptance for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Signal acceptance for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Signal acceptance for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Signal acceptance for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Signal acceptance for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Signal acceptance for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Signal acceptance for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Signal acceptance for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Signal acceptance for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.

Signal acceptance for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.

Signal acceptance for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.

Signal acceptance for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.

Signal efficiency for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.

Signal efficiency for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.

Signal efficiency for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.

Signal efficiency for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.

Signal efficiency for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Signal efficiency for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Signal efficiency for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Signal efficiency for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Signal efficiency for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Signal efficiency for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Signal efficiency for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Signal efficiency for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Signal efficiency for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Signal efficiency for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Signal efficiency for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Signal efficiency for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Signal efficiency for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.

Signal efficiency for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.

Signal efficiency for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.

Signal efficiency for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.

Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.

Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.

Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.

Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.

Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Observed 95% CL upper limit on $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Observed 95% CL upper limit on $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Observed 95% CL upper limit on $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Observed 95% CL upper limit on $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Observed 95% CL upper limit on $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.

Observed 95% CL upper limit on $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.

Observed 95% CL upper limit on $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.

Observed 95% CL upper limit on $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.

Best observed 95% CL exclusion contours selected from Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Best observed 95% CL exclusion contours selected from Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Best observed 95% CL exclusion contours selected from Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Best observed 95% CL exclusion contours selected from Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L0b from publication's Figure 5 . The last bin is inclusive.

N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L0b from publication's Figure 5 . The last bin is inclusive.

N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L0b from publication's Figure 5 . The last bin is inclusive.

N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L0b from publication's Figure 5 . The last bin is inclusive.

N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}} / m_{\mathrm{eff}}$ of observed data and expected background towards Rpc2L1b from publication's Figure 5 . The last bin is inclusive.

N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}} / m_{\mathrm{eff}}$ of observed data and expected background towards Rpc2L1b from publication's Figure 5 . The last bin is inclusive.

N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}} / m_{\mathrm{eff}}$ of observed data and expected background towards Rpc2L1b from publication's Figure 5 . The last bin is inclusive.

N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}} / m_{\mathrm{eff}}$ of observed data and expected background towards Rpc2L1b from publication's Figure 5 . The last bin is inclusive.

N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L2b from publication's Figure 5 . The last bin is inclusive.

N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L2b from publication's Figure 5 . The last bin is inclusive.

N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L2b from publication's Figure 5 . The last bin is inclusive.

N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L2b from publication's Figure 5 . The last bin is inclusive.

N-1 distributions for $m_{\mathrm{eff}}$ of observed data and expected background towards Rpv2L from publication's Figure 5 . The last bin is inclusive.

N-1 distributions for $m_{\mathrm{eff}}$ of observed data and expected background towards Rpv2L from publication's Figure 5 . The last bin is inclusive.

N-1 distributions for $m_{\mathrm{eff}}$ of observed data and expected background towards Rpv2L from publication's Figure 5 . The last bin is inclusive.

N-1 distributions for $m_{\mathrm{eff}}$ of observed data and expected background towards Rpv2L from publication's Figure 5 . The last bin is inclusive.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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