The unfolded differential charge asymmetry as a function of the transverse momentum of the top pair system. The measured values are given with statistical and systematic uncertainties. The SM theory predictions calculated at NNLO in QCD and NLO in EW theory are listed. The scale uncertainty is obtained by varying renormalisation and factorisation scales independently by a factor of 2 or 0.5 around $\mu_0$ to calculate the maximum and minimum value of the asymmetry, respectively. The nominal value $\mu_0$ is chosen as $H_T/4$. The variations in which one scale is multiplied by 2 while the other scale is divided by 2 are excluded. Finally, the scale and MC integration uncertainties are added in quadrature.

The unfolded differential charge asymmetry as a function of the longitudinal boost of the top pair system. The measured values are given with statistical and systematic uncertainties. The SM theory predictions calculated at NNLO in QCD and NLO in EW theory are listed. The scale uncertainty is obtained by varying renormalisation and factorisation scales independently by a factor of 2 or 0.5 around $\mu_0$ to calculate the maximum and minimum value of the asymmetry, respectively. The nominal value $\mu_0$ is chosen as $H_T/4$. The variations in which one scale is multiplied by 2 while the other scale is divided by 2 are excluded. Finally, the scale and MC integration uncertainties are added in quadrature.

The unfolded inclusive leptonic asymmetry. The unfolded $A_C^{\ell\bar{\ell}}$ is obtained in the reduced phase-space defined by the requirement $|\Delta |\eta_{\ell\bar{\ell}}||<2.5$. The measured values are given with statistical and systematic uncertainties. The SM theory predictions calculated at NLO in QCD and NLO in EW theory are listed. The theory uncertainty is obtained by varying both scales by a factor of 0.5 or 2.0 to calculate the minimum and maximum value of the asymmetry, respectively.

The unfolded differential leptonic asymmetry as a function of the invariant mass of the di-lepton pair. The unfolded $A_C^{\ell\bar{\ell}}$ is obtained in the reduced phase-space defined by the requirement $|\Delta |\eta_{\ell\bar{\ell}}||<2.5$. The measured values are given with statistical and systematic uncertainties. The SM theory predictions calculated at NLO in QCD and NLO in EW theory are listed. The theory uncertainty is obtained by varying both scales by a factor of 0.5 or 2.0 to calculate the minimum and maximum value of the asymmetry, respectively.

The unfolded differential leptonic asymmetry as a function of the transverse momentum of the di-lepton pair. The unfolded $A_C^{\ell\bar{\ell}}$ is obtained in the reduced phase-space defined by the requirement $|\Delta |\eta_{\ell\bar{\ell}}||<2.5$. The measured values are given with statistical and systematic uncertainties. The SM theory predictions calculated at NLO in QCD and NLO in EW theory are listed. The theory uncertainty is obtained by varying both scales by a factor of 0.5 or 2.0 to calculate the minimum and maximum value of the asymmetry, respectively.

The unfolded differential leptonic asymmetry as a function of the longitudinal boost of the di-lepton pair. The unfolded $A_C^{\ell\bar{\ell}}$ is obtained in the reduced phase-space defined by the requirement $|\Delta |\eta_{\ell\bar{\ell}}||<2.5$. The measured values are given with statistical and systematic uncertainties. The SM theory predictions calculated at NLO in QCD and NLO in EW theory are listed. The theory uncertainty is obtained by varying both scales by a factor of 0.5 or 2.0 to calculate the minimum and maximum value of the asymmetry, respectively.

Individual 68% and 95% CL bounds on the relevant Wilson coefficients of the SM Effective Field Theory in units of $\text{TeV}^{-2}$. The bounds are derived from the $A_C^{t\bar{t}}$ inclusive measurement. The experimental uncertainties are accounted for, in the form of the complete covariance matrix that keeps track of correlations between bins for the differential measurement. The theory uncertainty from the NNLO QCD + NLO EW calculation is included by explicitly varying the renormalization and factorization scales, or the parton density functions, in the calculation and registering the variations in the intervals.

Individual 68% and 95% CL bounds on the relevant Wilson coefficients of the SM Effective Field Theory in units of $\text{TeV}^{-2}$. The bounds are derived from the $A_C^{t\bar{t}}$ vs $m_{t\bar{t}}$ measurement. The experimental uncertainties are accounted for, in the form of the complete covariance matrix that keeps track of correlations between bins for the differential measurement. The theory uncertainty from the NNLO QCD + NLO EW calculation is included by explicitly varying the renormalization and factorization scales, or the parton density functions, in the calculation and registering the variations in the intervals.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ inclusive measurement. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $\beta_{z,t\bar{t}}$ measurement for $\beta_{z,t\bar{t}}$ $\in$ [0,0.3]. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $\beta_{z,t\bar{t}}$ measurement for $\beta_{z,t\bar{t}}$ $\in$ [0.3,0.6]. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $\beta_{z,t\bar{t}}$ measurement for $\beta_{z,t\bar{t}}$ $\in$ [0.6,0.8]. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $\beta_{z,t\bar{t}}$ measurement for $\beta_{z,t\bar{t}}$ $\in$ [0.8,1]. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $m_{t\bar{t}}$ measurement for $m_{t\bar{t}}$ < 500 GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $m_{t\bar{t}}$ measurement for $m_{t\bar{t}}$ $\in$ [500,750] GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $m_{t\bar{t}}$ measurement for $m_{t\bar{t}}$ $\in$ [750,1000] GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $m_{t\bar{t}}$ measurement for $m_{t\bar{t}}$ $\in$ [1000,1500] GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $m_{t\bar{t}}$ measurement for $m_{t\bar{t}}$ > 1500 GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $p_{T,t\bar{t}}$ measurement for $p_{T,t\bar{t}}$ < 30 GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $p_{T,t\bar{t}}$ measurement for $p_{T,t\bar{t}}$ $\in$ [30,120] GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $p_{T,t\bar{t}}$ measurement for $p_{T,t\bar{t}}$ > 120 GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ inclusive measurement. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ vs $\beta_{z,\ell\bar{\ell}}$ measurement for $\beta_{z,\ell\bar{\ell}}$ $\in$[0,0.3]. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ vs $\beta_{z,\ell\bar{\ell}}$ measurement for $\beta_{z,\ell\bar{\ell}}$ $\in$[0.3,0.6]. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ vs $\beta_{z,\ell\bar{\ell}}$ measurement for $\beta_{z,\ell\bar{\ell}}$ $\in$[0.6,0.8]. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ vs $\beta_{z,\ell\bar{\ell}}$ measurement for $\beta_{z,\ell\bar{\ell}}$ $\in$[0.8,1]. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ vs $m_{\ell\bar{\ell}}$ measurement for $m_{\ell\bar{\ell}}$ < 200 GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ vs $m_{\ell\bar{\ell}}$ measurement for $m_{\ell\bar{\ell}}$ $\in$ [200,300] GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ vs $m_{\ell\bar{\ell}}$ measurement for $m_{\ell\bar{\ell}}$ $\in$ [300,400] GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ vs $m_{\ell\bar{\ell}}$ measurement for $m_{\ell\bar{\ell}}$ > 400 GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ vs $p_{T,\ell\bar{\ell}}$ measurement for $p_{T,\ell\bar{\ell}}$ < 20 GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ vs $p_{T,\ell\bar{\ell}}$ measurement for $p_{T,\ell\bar{\ell}}$ $\in$ [20, 70] GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ vs $p_{T,\ell\bar{\ell}}$ measurement for $p_{T,\ell\bar{\ell}}$ > 70 GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Post-marginalisation correlation coefficients $\rho_{ij}$ of nuisance parameters for the $A_C^{t\bar{t}}$ inclusive measurement. Only $|\rho_{ij}| > 0.05$ values are included.

Post-marginalisation correlation coefficients $\rho_{ij}$ of nuisance parameters for the $A_C^{t\bar{t}}$ vs $m_{t\bar{t}}$ measurement. Only $|\rho_{ij}| > 0.05$ values are included.

Post-marginalisation correlation coefficients $\rho_{ij}$ of nuisance parameters for the $A_C^{t\bar{t}}$ vs $p_{T,t\bar{t}}$ measurement. Only $|\rho_{ij}| > 0.05$ values are included.

Post-marginalisation correlation coefficients $\rho_{ij}$ of nuisance parameters for the $A_C^{t\bar{t}}$ vs $\beta_{z,t\bar{t}}$ measurement. Only $|\rho_{ij}| > 0.05$ values are included.

Post-marginalisation correlation coefficients $\rho_{ij}$ of nuisance parameters for the $A_C^{\ell\ell}$ inclusive measurement. Only $|\rho_{ij}| > 0.05$ values are included.

Post-marginalisation correlation coefficients $\rho_{ij}$ of nuisance parameters for the $A_C^{\ell\ell}$ vs $m_{\ell\bar{\ell}}$ measurement. Only $|\rho_{ij}| > 0.05$ values are included.

Post-marginalisation correlation coefficients $\rho_{ij}$ of nuisance parameters for the $A_C^{\ell\ell}$ vs $p_{T,\ell\bar{\ell}}$ measurement. Only $|\rho_{ij}| > 0.05$ values are included.

Post-marginalisation correlation coefficients $\rho_{ij}$ of nuisance parameters for the $A_C^{\ell\ell}$ vs $\beta_{z,\ell\bar{\ell}}$ measurement. Only $|\rho_{ij}| > 0.05$ values are included.

Covariance matrix for the $A_C^{t\bar{t}}$ vs $m_{t\bar{t}}$ measurement.

Covariance matrix for the $A_C^{t\bar{t}}$ vs $p_{T,t\bar{t}}$ measurement.

Covariance matrix for the $A_C^{t\bar{t}}$ vs $\beta_{z,t\bar{t}}$ measurement.

Covariance matrix for the $A_C^{\ell\ell}$ vs $m_{\ell\bar{\ell}}$ measurement.

Covariance matrix for the $A_C^{\ell\ell}$ vs $p_{T,\ell\bar{\ell}}$ measurement.

Covariance matrix for the $A_C^{\ell\ell}$ vs $\beta_{z,\ell\bar{\ell}}$ measurement.

Electron $p_{T}$ distribution using 2016-2018 data sets. The complete set of selection criteria were applied. Two examples of SSM WPRIME boson signal samples with masses of 3.8 and 5.6 TeV are shown. The lower panel shows the ratio of data to SM prediction, and the shaded band represents the systematic uncertainties.

$p_{T}^{miss}$ distribution in the electron channel using 2016-2018 data sets. The complete set of selection criteria were applied. Two examples of SSM WPRIME boson signal samples with masses of 3.8 and 5.6 TeV are shown. The lower panel shows the ratio of data to SM prediction, and the shaded band represents the systematic uncertainties.

Muon $p_T$ distribution using 2016-2018 data sets. The complete set of selection criteria were applied. Two examples of SSM WPRIME boson signal samples with masses of 3.8 and 5.6 TeV are shown. The lower panel shows the ratio of data to SM prediction, and the shaded band represents the systematic uncertainties.

$p_T^{miss}$ distribution in the muon channel using 2016-2018 data sets. The complete set of selection criteria were applied. Two examples of SSM WPRIME boson signal samples with masses of 3.8 and 5.6 TeV are shown. The lower panel shows the ratio of data to SM prediction, and the shaded band represents the systematic uncertainties.

$M_T$ distribution for the E+INVISIBLE system using 2016-2018 data sets. The complete set of selection criteria were applied. Two examples of SSM WPRIME boson signal samples with masses of 3.8 and 5.6 TeV are shown. The lower panel shows the ratio of data to SM prediction, and the shaded band represents the systematic uncertainties.

$M_T$ distribution for the MU+INVISIBLE system using 2016-2018 data sets. The complete set of selection criteria were applied. Two examples of SSM WPRIME boson signal samples with masses of 3.8 and 5.6 TeV are shown. The lower panel shows the ratio of data to SM prediction, and the shaded band represents the systematic uncertainties.

Theoretical prediction for the production and decay cross-section of SSM WPRIME bosons (W --> LEPTON + NU) as a function of the WPRIME mass, for the range 200-6400 GeV and inclusive in phase-space (no cuts). The uncertainty shown covers PDF and ALPHAS uncertainties. These theoretical predictions are obtained with PYTHIA (LO) and corrected to NNLO in QCD using FEWZ program.

Observed (solid line) and expected (dashed line) upper limits at 95% CL on the product of WPRIME cross-section production and BF(WPRIME --> LEPTON + NU) for an SSM WPRIME boson, as a function of the boson mass, for the electron decay channel. The shaded bands represent the one (green) and two (yellow) standard deviation uncertainty bands for the expected limits. The theoretical predictions for the SSM at NNLO precision in QCD are shown with narrow gray bands corresponding to the PDF and ALPHAS uncertainties.

Observed (solid line) and expected (dashed line) upper limits at 95% CL on the product of WPRIME cross-section production and BF(WPRIME --> LEPTON + NU) for an SSM WPRIME boson, as a function of the boson mass, for the muon decay channel. The shaded bands represent the one (green) and two (yellow) standard deviation uncertainty bands for the expected limits. The theoretical predictions for the SSM at NNLO precision in QCD are shown with narrow gray bands corresponding to the PDF and ALPHAS uncertainties.

Observed (solid line) and expected (dashed line) upper limits at 95% CL on the product of WPRIME cross-section production and BF(WPRIME --> LEPTON + NU) for an SSM WPRIME boson, as a function of the boson mass, for the combined electron and muon decay channels. The shaded bands represent the one (green) and two (yellow) standard deviation uncertainty bands for the expected limits. The theoretical predictions for the SSM at NNLO precision in QCD are shown with narrow gray bands corresponding to the PDF and ALPHAS uncertainties.

The 95% CL observed (solid line) and expected (dashed line) model independent cross section upper limits as function of the $MT_{min}$ threshold, for the electron decay channel. The shaded bands represent the one (green) and two (yellow) standard deviation uncertainty bands for the expected limits.

The 95% CL observed (solid line) and expected (dashed line) model independent cross section upper limits as function of the $MT_{min}$ threshold, for the muon decay channel. The shaded bands represent the one (green) and two (yellow) standard deviation uncertainty bands for the expected limits.

The 95% CL observed (solid line) and expected (dashed line) model independent cross section upper limits as function of the $MT_{min}$ threshold, for the combined electron and muon decay channels. The shaded bands represent the one (green) and two (yellow) standard deviation uncertainty bands for the expected limits.

Observed (solid line) and expected (dashed line) upper limits at 95% CL on the coupling strength ratio, gWprime/gW as a function of the mass of the WPRIME boson, for the electron channel. The one (green) and two (yellow) standard deviation uncertainty bands for the expected limits are shown. The area above the limit curve is excluded. The dotted line represents the case of SSM coupling, gWprime, being equal to gW, the SM coupling.

Observed (solid line) and expected (dashed line) upper limits at 95% CL on the coupling strength ratio, gWprime/gW, as a function of the mass of the WPRIME boson, for the muon channel. The one (green) and two (yellow) standard deviation uncertainty bands for the expected limits are shown. The area above the limit curve is excluded. The dotted line represents the case of SSM coupling, gWprime , being equal to gW, the SM coupling.

Exclusion limits in the 2D plane (1/R, $\mu$) for the split-UED interpretation for the n = 2 case, for the electron channel for the 2016-2018 data sets. R is the radius of the additional spatial dimension and $\mu$ the bulk mass for the fermion field in five dimensions. The expected limit is depicted as a black dashed line. The one (green) and two (yellow) standard deviation uncertainty bands for the expected limits are shown. The experimentally excluded region is the entire area to the left of the solid black line.

Exclusion limits in the 2D plane (1/R, $\mu$) for the split-UED interpretation for the n = 2 case, for the muon channel for the 2016-2018 data sets. R is the radius of the additional spatial dimension and $\mu$ the bulk mass for the fermion field in five dimensions. The expected limit is depicted as a black dashed line. The one (green) and two (yellow) standard deviation uncertainty bands for the expected limits are shown. The experimentally excluded region is the entire area to the left of the solid black line.

Exclusion limits in the 2D plane (1/R, $\mu$) for the split-UED interpretation for the n = 2 case, for the combined electron and muon channels for the 2016-2018 data sets. R is the radius of the additional spatial dimension and $\mu$ the bulk mass for the fermion field in five dimensions. The expected limit is depicted as a black dashed line. The one (green) and two (yellow) standard deviation uncertainty bands for the expected limits are shown. The experimentally excluded region is the entire area to the left of the solid black line.

Observed (solid line) and expected (dashed line) upper limits at 95% CL on the ${\lambda}_{231}$ coupling in the RPV SUSY model with a STAU mediator, as a function of the mass of STAU, for the electron channel and for the production coupling, ${\lambda}^{'}_{3ij}$=0.5 . The couplings ${\lambda}^{'}_{3ij}$, ${\lambda}_{231}$, and ${\lambda}_{132}$ are defined in Fig. 1. The one (green) and two (yellow) standard deviation uncertainty bands for the expected limits are shown. The area above the limit curve is excluded. Limits for other values of ${\lambda}^{'}_{3ij}$ are obtained multiplying the ones shown by the ratio ${\lambda}^{'}_{3ij}$/0.5

Observed (solid line) and expected (dashed line) upper limits at 95% CL on the ${\lambda}_{132}$ coupling in the RPV SUSY model with a stau mediator, as a function of the mass of the stau, for the muon channel and for the production coupling, ${\lambda}^{'}_{3ij}$ = 0.5 . The couplings ${\lambda}^{'}_{3ij}$, ${\lambda}_{231}$, and ${\lambda}_{132}$ are defined in Fig. 1. The one (green) and two (yellow) standard deviation uncertainty bands for the expected limits are shown. The area above the limit curve is excluded. Limits for other values of ${\lambda}^{'}_{3ij}$ are obtained multiplying these ones by the ratio ${\lambda}^{'}_{3ij}$/0.5

Region in the oblique (W,Y) parameter phase space allowed by the current analysis at 95% CL. The combination of the electron and muon channel distributions from the 2017 and 2018 data sets at sqrt(s) = 13 TeV is used, having 101 fb-1 of luminosity.

Negative Log-Likelihood for the determination of the oblique W parameter, for the combination of the electron and muon channel and for 2017 and 2018 data sets (L=101 fb-1) at sqrt(s) = 13 TeV.

Total background estimate and observed data in all bins used in the limit calculation for the SSM WPRIME limits. The total event sample is split into the three years of data taking and the two lepton flavors.The distributions being shown are $M_T$ ones. The associated integrated luminosities for each year are of 35.9, 41.5, and 59.4 fb$̣^{-1}. The mass bins are numbered in ascending order.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Parametrization of the $A_{X}$ factor, defined as the fraction of diphoton resonances satisfying the fiducial acceptance at the particle level, as function of $m_{X}$ obtained from the narrow width simulated signal samples produced in gluon fusion.

The correction factor, $C_{X}$, defined as the ratio between the number of reconstructed signal events passing the analysis cuts and the number of signal events at the particle level generated within the fiducial volume, and acceptance correction factor, $A_{X}$, defined as the fraction of diphoton resonances satisfying the fiducial acceptance at the particle level. Both are computed for NWA spin-0 models as a function of $m_{X}$.

Effect of event selections on a scalar MC signal sample generated for $m_{X}$ = 15 GeV and on the data. For the MC sample, the efficiencies are shown after applying event weights and a truth level filter that requires two photons with $p^{\gamma\gamma}_{T}>40$ GeV; for the data, the absolute yields are shown. The initial yields for data include a trigger preselection that is the OR of a list of single photon and diphoton triggers. The "2 $loose$ photons" step includes the kinematic acceptance cuts.

Parameterization of the Double Sided Crystal Ball function parameters describing the scalar mass resolution model as a function of $m_{X}$ [GeV].

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Etmiss distribution for SRC1 after all selection requirements except those on Etmiss.

Etmiss distribution for SRC2 after all selection requirements except those on Etmiss.

Etmiss distribution for SRC3 after all selection requirements except those on Etmiss.

Observed exclusion limit at 95% CL in the ( M(STOP), M(NEUTRALINO) ) mass plane for the stop pair production scenario.

Expected exclusion limit at 95% CL in the ( M(STOP), M(NEUTRALINO) ) mass plane for the stop pair production scenario.

Observed exclusion limit at 95% CL in the ( M(STOP), M(NEUTRALINO) ) mass plane for the stop pair production scenario where BR(stop --> top+neutralino)=50%.

Expected exclusion limit at 95% CL in the ( M(STOP), M(NEUTRALINO) ) mass plane for the stop pair production scenario where BR(stop --> top+neutralino)=50%.

Observed exclusion limit at 95% CL in the ( M(STOP), M(NEUTRALINO) ) mass plane for the stop pair production scenario where BR(stop --> top+neutralino)=100%.

Expected exclusion limit at 95% CL in the ( M(STOP), M(NEUTRALINO) ) mass plane for the stop pair production scenario where BR(stop --> top+neutralino)=100%.

Observed exclusion limit at 95% CL in the ( M(STOP), M(NEUTRALINO) ) mass plane for the stop pair production scenario where BR(stop --> top+neutralino)=75%.

Expected exclusion limit at 95% CL in the ( M(STOP), M(NEUTRALINO) ) mass plane for the stop pair production scenario where BR(stop --> top+neutralino)=75%.

Observed exclusion limit at 95% CL in the ( M(STOP), M(NEUTRALINO) ) mass plane for the stop pair production scenario where BR(stop --> top+neutralino)=50%.

Expected exclusion limit at 95% CL in the ( M(STOP), M(NEUTRALINO) ) mass plane for the stop pair production scenario where BR(stop --> top+neutralino)=50%.

Observed exclusion limit at 95% CL in the ( M(STOP), M(NEUTRALINO) ) mass plane for the stop pair production scenario where BR(stop --> top+neutralino)=25%.

Expected exclusion limit at 95% CL in the ( M(STOP), M(NEUTRALINO) ) mass plane for the stop pair production scenario where BR(stop --> top+neutralino)=25%.

Observed exclusion limit at 95% CL in the ( M(STOP), M(NEUTRALINO) ) mass plane for the stop pair production scenario where BR(stop --> top+neutralino)=0%.

Expected exclusion limit at 95% CL in the ( M(STOP), M(NEUTRALINO) ) mass plane for the stop pair production scenario where BR(stop --> top+neutralino)=0%.

Nominal observed excluded cross sections at 95% CL in the ( M(STOP), M(NEUTRALINO) ) mass plane for the stop pair production scenario, once corrected by the recorded luminosity and the efficiency times acceptance of the model itself.

Signal region (SR) combination providing the lowest expected CLs in the ( M(STOP), M(NEUTRALINO) ) mass plane for the stop pair production scenario.

Signal region (SR) combination providing the lowest expected CLs in the ( M(STOP), M(NEUTRALINO) ) mass plane for the stop pair production scenario where BR(stop --> top+neutralino)=75%.

Signal region (SR) combination providing the lowest expected CLs in the ( M(STOP), M(NEUTRALINO) ) mass plane for the stop pair production scenario where BR(stop --> top+neutralino)=50%.

Signal region (SR) combination providing the lowest expected CLs in the ( M(STOP), M(NEUTRALINO) ) mass plane for the stop pair production scenario where BR(stop --> top+neutralino)=25%.

Signal region (SR) combination providing the lowest expected CLs in the ( M(STOP), M(NEUTRALINO) ) mass plane for the stop pair production scenario where BR(stop --> top+neutralino)=0%.

Signal acceptance for the different signal regions (SR) in the ( M(STOP), M(NEUTRALINO) ) mass plane for the stop pair production scenario with both stops decaying to top+neutralino. The acceptance is defined in Appendix A of arXiv:1403.4853.

Signal efficiency for the different signal regions (SR) in the ( M(STOP), M(NEUTRALINO) ) mass plane for the stop pair production scenario with both stops decaying to top+neutralino.

Signal acceptance for the different signal regions (SR) in the ( M(STOP), M(NEUTRALINO) ) mass plane for the stop pair production scenario with both stops decaying to b+chargino. The acceptance is defined in Appendix A of arXiv:1403.4853.

Signal efficiency for the different signal regions (SR) in the ( M(STOP), M(NEUTRALINO) ) mass plane for the stop pair production scenario with both stops decaying to b+chargino.

Number of generated Monte Carlo events in the ( M(STOP), M(NEUTRALINO) ) mass plane for the stop pair production scenario where both stops decay to top+neutralino.

Number of generated Monte Carlo events in the ( M(STOP), M(NEUTRALINO) ) mass plane in the stop pair production scenario where both stops decay to b+chargino.

Stop signal production cross sections in the ( M(STOP), M(NEUTRALINO) ) mass plane.

Total experimental systematic uncertainty in percent on the signal yield for SRA1 in the ( M(STOP), M(NEUTRALINO) ) mass plane for the stop pair production scenario where both stops decay to top+neutralino. The uncertainty does not include Monte Carlo statistical uncertainties, nor theoretical uncertainties on the signal cross section.

Total experimental systematic uncertainty in percent on the signal yield for SRA2 in the ( M(STOP), M(NEUTRALINO) ) mass plane for the stop pair production scenario where both stops decay to top+neutralino. The uncertainty does not include Monte Carlo statistical uncertainties, nor theoretical uncertainties on the signal cross section.

Total experimental systematic uncertainty in percent on the signal yield for SRA3 in the ( M(STOP), M(NEUTRALINO) ) mass plane for the stop pair production scenario where both stops decay to top+neutralino. The uncertainty does not include Monte Carlo statistical uncertainties, nor theoretical uncertainties on the signal cross section.

Total experimental systematic uncertainty in percent on the signal yield for SRA4 in the ( M(STOP), M(NEUTRALINO) ) mass plane for the stop pair production scenario where both stops decay to top+neutralino. The uncertainty does not include Monte Carlo statistical uncertainties, nor theoretical uncertainties on the signal cross section.

Total experimental systematic uncertainty in percent on the signal yield for SRB in the ( M(STOP), M(NEUTRALINO) ) mass plane for the stop pair production scenario where both stops decay to top+neutralino. The uncertainty does not include Monte Carlo statistical uncertainties, nor theoretical uncertainties on the signal cross section.

Total experimental systematic uncertainty in percent on the signal yield for SRC1 in the ( M(STOP), M(NEUTRALINO) ) mass plane for the stop pair production scenario where both stops decay to top+neutralino. The uncertainty does not include Monte Carlo statistical uncertainties, nor theoretical uncertainties on the signal cross section.

Total experimental systematic uncertainty in percent on the signal yield for SRC2 in the ( M(STOP), M(NEUTRALINO) ) mass plane for the stop pair production scenario where both stops decay to top+neutralino. The uncertainty does not include Monte Carlo statistical uncertainties, nor theoretical uncertainties on the signal cross section.

Total experimental systematic uncertainty in percent on the signal yield for SRC3 in the ( M(STOP), M(NEUTRALINO) ) mass plane for the stop pair production scenario where both stops decay to top+neutralino. The uncertainty does not include Monte Carlo statistical uncertainties, nor theoretical uncertainties on the signal cross section.

Observed and expected CLs in the ( M(STOP), M(NEUTRALINO) ) mass plane for the stop pair production scenario. The value for the best expected signal region combination is shown.

Expected and observed $am_{T2}$ distribution for bCd_high1 SR, before applying the $am_{T2}>200$ GeV requirement. The uncertainty includes statistical and all experimental systematic uncertainties. The last bin includes overflows.

Expected and observed leading b-jet $p_T$ distribution for bCd_high2 SR, before applying the leading b-jet $p_T>170$ GeV requirement. The uncertainty includes statistical and all experimental systematic uncertainties. The last bin includes overflows.

Expected and observed $E_T^{miss}$ distribution for tNbC_mix SR, before applying the $E_T^{miss}>270$ GeV requirement. The uncertainty includes statistical and all experimental systematic uncertainties. The last bin includes overflows.

Expected and observed lepton $p_T$ distribution for bCa_low SR. The uncertainty includes statistical and all experimental systematic uncertainties. The last bin includes overflows.

Expected and observed lepton $p_T$ distribution for bCa_med SR. The uncertainty includes statistical and all experimental systematic uncertainties. The last bin includes overflows.

Expected and observed $am_T2$ distribution for bCb_med1 SR. The uncertainty includes statistical and all experimental systematic uncertainties. The last bin includes overflows.

Expected and observed $am_T2$ distribution for bCb_high SR. The uncertainty includes statistical and all experimental systematic uncertainties. The last bin includes overflows.

Best expected signal region for the $\tilde t_1\to t\chi^0_1$ scenario with $m_{\tilde t_1}>m_t+m_{\chi^0_1}$. This mapping is used for the final combined exclusion limits.

Best expected signal region for the $\tilde t_1$ three-body scenario ($\tilde t_1\to bW\chi^0_1$). This mapping is used for the final combined exclusion limits.

Best expected signal region for the $\tilde t_1$ four-body scenario ($\tilde t_1\to bff'\chi^0_1$). This mapping is used for the final combined exclusion limits.

Best expected signal region for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$. This mapping is used for the final combined exclusion limits.

Best expected signal region for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=150$ GeV. This mapping is used for the final combined exclusion limits.

Best expected signal region for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=106$ GeV. This mapping is used for the final combined exclusion limits.

Best expected signal region for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+5$ GeV. This mapping is used for the final combined exclusion limits.

Best expected signal region for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV. This mapping is used for the final combined exclusion limits.

Best expected signal region for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\tilde t_1}-10$ GeV. This mapping is used for the final combined exclusion limits.

Best expected signal region for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\tilde t_1}=300$ GeV. This mapping is used for the final combined exclusion limits.

Upper limits on the model cross-section for the $\tilde t_1\to t\chi^0_1$ scenario with $m_{\tilde t_1}>m_t+m_{\chi^0_1}$.

Observed exclusion contour for the $\tilde t_1\to t\chi^0_1$ scenario with $m_{\tilde t_1}>m_t+m_{\chi^0_1}$.

Expected exclusion contour for the $\tilde t_1\to t\chi^0_1$ scenario with $m_{\tilde t_1}>m_t+m_{\chi^0_1}$.

Upper limit on signal events for the $\tilde t_1$ three-body scenario ($\tilde t_1\to bW\chi^0_1$).

Observed exclusion contour for the $\tilde t_1$ three-body scenario ($\tilde t_1\to bW\chi^0_1$).

Expected exclusion contour for the $\tilde t_1$ three-body scenario ($\tilde t_1\to bW\chi^0_1$).

Upper limit on signal events for the $\tilde t_1$ four-body scenario ($\tilde t_1\to bff'\chi^0_1$).

Observed exclusion contour for the $\tilde t_1$ four-body scenario ($\tilde t_1\to bff'\chi^0_1$).

Expected exclusion contour for the $\tilde t_1$ four-body scenario ($\tilde t_1\to bff'\chi^0_1$).

Upper limit on signal events for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$.

Observed exclusion contour for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$.

Expected exclusion contour for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$.

Upper limit on signal events for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=150$ GeV.

Observed exclusion contour for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=150$ GeV.

Expected exclusion contour for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=150$ GeV.

Upper limit on signal events for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=106$ GeV.

Observed exclusion contour for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=106$ GeV.

Expected exclusion contour for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=106$ GeV.

Upper limit on signal events for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+5$ GeV.

Observed exclusion contour for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+5$ GeV.

Expected exclusion contour for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+5$ GeV.

Upper limit on signal events for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV.

Observed exclusion contour for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV.

Expected exclusion contour for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV.

Upper limit on signal events for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\tilde t_1}-10$ GeV.

Observed exclusion contour for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\tilde t_1}-10$ GeV.

Expected exclusion contour for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\tilde t_1}-10$ GeV.

Upper limit on signal events for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\tilde t_1}=300$ GeV.

Observed exclusion contour for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\tilde t_1}=300$ GeV.

Expected exclusion contour for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\tilde t_1}=300$ GeV.

Acceptance of tN_diag SR ($E_T^{miss}>150$ GeV, $m_T>140$ GeV) for the $\tilde t_1\to t\chi^0_1$ scenario with $m_{\tilde t_1}>m_t+m_{\chi^0_1}$. The acceptance is defined as the fraction of signal events that pass the analysis selection performed on generator-level objects, therefore emulating an ideal detector with perfect particle identification and no measurement resolution effects.

Acceptance of tN_med SR for the $\tilde t_1\to t\chi^0_1$ scenario with $m_{\tilde t_1}>m_t+m_{\chi^0_1}$. The acceptance is defined as the fraction of signal events that pass the analysis selection performed on generator-level objects, therefore emulating an ideal detector with perfect particle identification and no measurement resolution effects.

Acceptance of tN_boost SR for the $\tilde t_1\to t\chi^0_1$ scenario with $m_{\tilde t_1}>m_t+m_{\chi^0_1}$. The acceptance is defined as the fraction of signal events that pass the analysis selection performed on generator-level objects, therefore emulating an ideal detector with perfect particle identification and no measurement resolution effects.

Acceptance of bCb_med2 SR ($am_{T2}>250$ GeV, $m_T>60$ GeV) for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$. The acceptance is defined as the fraction of signal events that pass the analysis selection performed on generator-level objects, therefore emulating an ideal detector with perfect particle identification and no measurement resolution effects.

Acceptance of bCc_diag SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$. The acceptance is defined as the fraction of signal events that pass the analysis selection performed on generator-level objects, therefore emulating an ideal detector with perfect particle identification and no measurement resolution effects.

Acceptance of bCd_bulk SR ($am_{T2}>175$ GeV, $m_T>120$ GeV) for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$. The acceptance is defined as the fraction of signal events that pass the analysis selection performed on generator-level objects, therefore emulating an ideal detector with perfect particle identification and no measurement resolution effects.

Acceptance of bCd_high1 SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$. The acceptance is defined as the fraction of signal events that pass the analysis selection performed on generator-level objects, therefore emulating an ideal detector with perfect particle identification and no measurement resolution effects.

Acceptance of bCd_high2 SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$. The acceptance is defined as the fraction of signal events that pass the analysis selection performed on generator-level objects, therefore emulating an ideal detector with perfect particle identification and no measurement resolution effects.

Acceptance of bCa_med for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV. The acceptance is defined as the fraction of signal events that pass the analysis selection performed on generator-level objects, therefore emulating an ideal detector with perfect particle identification and no measurement resolution effects.

Acceptance of bCa_low for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV. The acceptance is defined as the fraction of signal events that pass the analysis selection performed on generator-level objects, therefore emulating an ideal detector with perfect particle identification and no measurement resolution effects.

Acceptance of bCb_med1 for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV. The acceptance is defined as the fraction of signal events that pass the analysis selection performed on generator-level objects, therefore emulating an ideal detector with perfect particle identification and no measurement resolution effects.

Acceptance of bCb_high for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV. The acceptance is defined as the fraction of signal events that pass the analysis selection performed on generator-level objects, therefore emulating an ideal detector with perfect particle identification and no measurement resolution effects.

Acceptance of 3-body SR ($80<am_{T2}<90$ GeV, $m_T>120$ GeV) for the 3-body scenario ($\tilde t_1\to b W\chi^0_1$). The acceptance is defined as the fraction of signal events that pass the analysis selection performed on generator-level objects, therefore emulating an ideal detector with perfect particle identification and no measurement resolution effects.

Acceptance of tNbC_mix SR for the asymmetric scenario ($\tilde t_1$, $\tilde t_1\to t\chi^0_1$, b $\chi^\pm_1$) with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$. The acceptance is defined as the fraction of signal events that pass the analysis selection performed on generator-level objects, therefore emulating an ideal detector with perfect particle identification and no measurement resolution effects.

Efficiency of tN_diag SR ($E_T^{miss}>150$ GeV, $m_T>140$ GeV) for the $\tilde t_1\to t\chi^0_1$ scenario with $m_{\tilde t_1}>m_t+m_{\chi^0_1}$. The efficiency is the ratio between the expected signal rate calculated with simulated data passing all the reconstruction level cuts applied to reconstructed objects, and the signal rate for an ideal detector (with perfect particle identification and no measurement resolution effects).

Efficiency of tN_med SR for the $\tilde t_1\to t\chi^0_1$ scenario with $m_{\tilde t_1}>m_t+m_{\chi^0_1}$. The efficiency is the ratio between the expected signal rate calculated with simulated data passing all the reconstruction level cuts applied to reconstructed objects, and the signal rate for an ideal detector (with perfect particle identification and no measurement resolution effects).

Efficiency of tN_boost SR for the $\tilde t_1\to t\chi^0_1$ scenario with $m_{\tilde t_1}>m_t+m_{\chi^0_1}$. The efficiency is the ratio between the expected signal rate calculated with simulated data passing all the reconstruction level cuts applied to reconstructed objects, and the signal rate for an ideal detector (with perfect particle identification and no measurement resolution effects).

Efficiency of bCb_med2 SR ($am_{T2}>250$ GeV, $m_T>60$ GeV) for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$. The efficiency is the ratio between the expected signal rate calculated with simulated data passing all the reconstruction level cuts applied to reconstructed objects, and the signal rate for an ideal detector (with perfect particle identification and no measurement resolution effects).

Efficiency of bCc_diag SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$. The efficiency is the ratio between the expected signal rate calculated with simulated data passing all the reconstruction level cuts applied to reconstructed objects, and the signal rate for an ideal detector (with perfect particle identification and no measurement resolution effects).

Efficiency of bCd_bulk SR ($am_{T2}>175$ GeV, $m_T>120$ GeV) for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$. The efficiency is the ratio between the expected signal rate calculated with simulated data passing all the reconstruction level cuts applied to reconstructed objects, and the signal rate for an ideal detector (with perfect particle identification and no measurement resolution effects).

Efficiency of bCd_high1 SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$. The efficiency is the ratio between the expected signal rate calculated with simulated data passing all the reconstruction level cuts applied to reconstructed objects, and the signal rate for an ideal detector (with perfect particle identification and no measurement resolution effects).

Efficiency of bCd_high2 SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$. The efficiency is the ratio between the expected signal rate calculated with simulated data passing all the reconstruction level cuts applied to reconstructed objects, and the signal rate for an ideal detector (with perfect particle identification and no measurement resolution effects).

Efficiency of bCa_med for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV. The efficiency is the ratio between the expected signal rate calculated with simulated data passing all the reconstruction level cuts applied to reconstructed objects, and the signal rate for an ideal detector (with perfect particle identification and no measurement resolution effects).

Efficiency of bCa_low for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV. The efficiency is the ratio between the expected signal rate calculated with simulated data passing all the reconstruction level cuts applied to reconstructed objects, and the signal rate for an ideal detector (with perfect particle identification and no measurement resolution effects).

Efficiency of bCb_med1 for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV. The efficiency is the ratio between the expected signal rate calculated with simulated data passing all the reconstruction level cuts applied to reconstructed objects, and the signal rate for an ideal detector (with perfect particle identification and no measurement resolution effects).

Efficiency of bCb_high for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV. The efficiency is the ratio between the expected signal rate calculated with simulated data passing all the reconstruction level cuts applied to reconstructed objects, and the signal rate for an ideal detector (with perfect particle identification and no measurement resolution effects).

Efficiency of 3-body SR ($80<am_{T2}<90$ GeV, $m_T>120$ GeV) for the 3-body scenario ($\tilde t_1\to b W\chi^0_1$). The efficiency is the ratio between the expected signal rate calculated with simulated data passing all the reconstruction level cuts applied to reconstructed objects, and the signal rate for an ideal detector (with perfect particle identification and no measurement resolution effects).

Efficiency of tNbC_mix SR for the asymmetric scenario ($\tilde t_1$, $\tilde t_1\to t\chi^0_1$, b $\chi^\pm_1$) with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$. The efficiency is the ratio between the expected signal rate calculated with simulated data passing all the reconstruction level cuts applied to reconstructed objects, and the signal rate for an ideal detector (with perfect particle identification and no measurement resolution effects).

Number of generated events for the $\tilde t_1\to t\chi^0_1$ scenario with $m_{\tilde t_1}>m_t+m_{\chi^0_1}$.

Number of generated events for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$.

Number of generated events for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV; $E_T^{miss}$(gen)$>60$ GeV.

Number of generated events for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV; $E_T^{miss}$(gen)$>250$ GeV.

Number of generated events for the 3-body scenario ($\tilde t_1\to b W\chi^0_1$).

Number of generated events for the asymmetric scenario ($\tilde t_1$, $\tilde t_1\to t\chi^0_1$, b $\chi^\pm_1$) with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$.

Cross-section for the $\tilde t_1\to t\chi^0_1$ scenario with $m_{\tilde t_1}>m_t+m_{\chi^0_1}$.

Cross-section for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$.

Cross-section for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV.

Cross-section for the 3-body scenario ($\tilde t_1\to b W\chi^0_1$).

Cross-section for the asymmetric scenario ($\tilde t_1$, $\tilde t_1\to t\chi^0_1$, b $\chi^\pm_1$) with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$.

Combined experimental systematic uncertainty of expected tN_diag SR yields for the $\tilde t_1\to t\chi^0_1$ scenario with $m_{\tilde t_1}>m_t+m_{\chi^0_1}$, using the 2 highest $E_T^{miss}$ and 2 highest $m_T$ bins.

Combined experimental systematic uncertainty of expected tN_med SR yields for the $\tilde t_1\to t\chi^0_1$ scenario with $m_{\tilde t_1}>m_t+m_{\chi^0_1}$.

Combined experimental systematic uncertainty of expected tN_boost SR yields for the $\tilde t_1\to t\chi^0_1$ scenario with $m_{\tilde t_1}>m_t+m_{\chi^0_1}$.

Combined experimental systematic uncertainty of expected bCb_med2 SR yields for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$, using the 2 highest $am_{T2}$ and 2 highest $m_T$ bins.

Combined experimental systematic uncertainty of expected bCc_diag SR yields for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$.

Combined experimental systematic uncertainty of expected bCd_bulk SR yields for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$, using the 2 highest $am_{T2}$ and 2 highest $m_T$ bins.

Combined experimental systematic uncertainty of expected bCd_high1 SR yields for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$.

Combined experimental systematic uncertainty of expected bCd_high2 SR yields for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$.

Combined experimental systematic uncertainty of expected bCa_med SR yields for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV.

Combined experimental systematic uncertainty of expected bCa_low SR yields for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV.

Combined experimental systematic uncertainty of expected bCb_med1 SR yields for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV.

Combined experimental systematic uncertainty of expected bCb_high SR yields for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV.

Combined experimental systematic uncertainty of expected 3-body SR yields for the 3-body scenario ($\tilde t_1\to b W\chi^0_1$), using the 2 lowest $am_{T2}$ and 2 highest $m_T$ bins.

Combined experimental systematic uncertainty of expected tNbC_mix SR yields for the asymmetric scenario ($\tilde t_1$, $\tilde t_1\to t\chi^0_1$, b $\chi^\pm_1$) with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$.

Observed CLs in tN_diag SR for the $\tilde t_1\to t\chi^0_1$ scenario with $m_{\tilde t_1}>m_t+m_{\chi^0_1}$.

Observed CLs in tN_med SR for the $\tilde t_1\to t\chi^0_1$ scenario with $m_{\tilde t_1}>m_t+m_{\chi^0_1}$.

Observed CLs in tN_boost SR for the $\tilde t_1\to t\chi^0_1$ scenario with $m_{\tilde t_1}>m_t+m_{\chi^0_1}$.

Observed CLs in bCb_med2 SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$.

Observed CLs in bCc_diag SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$.

Observed CLs in bCd_bulk SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$.

Observed CLs in bCd_high1 SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$.

Observed CLs in bCd_high2 SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$.

Observed CLs in bCa_med SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV.

Observed CLs in bCa_low SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV.

Observed CLs in bCb_med1 SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV.

Observed CLs in bCb_high SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV.

Observed CLs in 3-body SR for the 3-body scenario ($\tilde t_1\to b W\chi^0_1$).

Observed CLs in tNbC_mix SR for the mixed scenario (50% $\tilde t_1\to t\chi^0_1$, 50% $\tilde t_1\to b\chi^0_1$).

Expected CLs in tN_diag SR for the $\tilde t_1\to t\chi^0_1$ scenario with $m_{\tilde t_1}>m_t+m_{\chi^0_1}$.

Expected CLs in tN_med SR for the $\tilde t_1\to t\chi^0_1$ scenario with $m_{\tilde t_1}>m_t+m_{\chi^0_1}$.

Expected CLs in tN_boost SR for the $\tilde t_1\to t\chi^0_1$ scenario with $m_{\tilde t_1}>m_t+m_{\chi^0_1}$.

Expected CLs in bCb_med2 SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$.

Expected CLs in bCc_diag SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$.

Expected CLs in bCd_bulk SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$.

Expected CLs in bCd_high1 SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$.

Expected CLs in bCd_high2 SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=2\times m_{\chi^0_1}$.

Expected CLs in bCa_med SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV.

Expected CLs in bCa_low SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV.

Expected CLs in bCb_med1 SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV.

Expected CLs in bCb_high SR for the $\tilde t_1\to b\chi^\pm_1$ scenario with $m_{\chi^\pm_1}=m_{\chi^0_1}+20$ GeV.

Expected CLs in 3-body SR for the 3-body scenario ($\tilde t_1\to b W\chi^0_1$).

Expected CLs in tNbC_mix SR for the mixed scenario (50% $\tilde t_1\to t\chi^0_1$, 50% $\tilde t_1\to b\chi^\pm_1$).

Observed and expected $E_T^{miss}$ distribution in soft dimuon signal region. The last bin includes the overflow.

Observed and expected $m_{eff}^{incl}$ distribution in hard single-lepton 3-jet signal region. The last bin includes the overflow.

Observed and expected $m_{eff}^{incl}$ distribution for hard single-lepton 5-jet signal region. The last bin includes the overflow.

Observed and expected $E_{T}^{miss}$ distribution for hard single-lepton 6-jet signal region. The last bin includes the overflow.

Observed and expected $M_{R}'$ distribution for hard same-flavour dilepton low-multiplicity signal region. The last bin includes the overflow.

Observed and expected $M_{R}'$ distribution for hard same-flavour dilepton 3-jet signal region. The last bin includes the overflow.

Observed and expected $M_{R}'$ distribution for hard opposite-flavour dilepton low-multiplicity signal region. The last bin includes the overflow.

Observed and expected $M_{R}'$ distribution for hard opposite-flavour dilepton 3-jet opposite-flavour signal region. The last bin includes the overflow.

Observed 95% exclusion contour for the mSUGRA/CMSSM model with $\tan\beta=30$, $A_{0}=-2m_{0}$ and $\mu > 0$.

Expected 95% exclusion contour for the mSUGRA/CMSSM model with $\tan\beta=30$, $A_{0}=-2m_{0}$ and $\mu > 0$.

Observed 95% exclusion contour for the bRPV MSUGRA/CMSSM model.

Expected 95% exclusion contour for the bRPV MSUGRA/CMSSM model.

Observed 95% exclusion contour for the natural gauge mediation with a stau NLSP model (nGM).

Expected 95% exclusion contour for the natural gauge mediation with a stau NLSP model (nGM).

Observed 95% exclusion contour for the non-universal higgs masses with gaugino mediation model (NUHMG).

Expected 95% exclusion contour for the non-universal higgs masses with gaugino mediation model (NUHMG).

Observed 95% exclusion contour for the minimal UED model from the combination of the hard dilepton and soft dilepton analyses.

Expected 95% exclusion contour for the minimal UED model from the combination of the hard dilepton and soft dilepton analyses.

Observed 95% exclusion contour for the minimal UED model from the hard dilepton analysis.

Expected 95% exclusion contour for the minimal UED model from the hard dilepton analysis.

Observed 95% exclusion contour for the minimal UED model from the soft dilepton analysis.

Expected 95% exclusion contour for the minimal UED model from the soft dilepton analysis.

Observed 95% exclusion contour for the simplified model with gluino-mediated top squark production where the top squark is assumed to decay exclusively via $\tilde{t} \rightarrow c \tilde{\chi}^{0}_{1}$.

Expected 95% exclusion contour for the simplified model with gluino-mediated top squark production, where the top squark is assumed to decay exclusively via $\tilde{t} \rightarrow c \tilde{\chi}^{0}_{1}$.

Observed 95% exclusion contour for the simplified model with gluino-mediated top squark production where the gluinos are assumed to decay exclusively through a virtual top squark, $\tilde{g} \rightarrow tt+\tilde{\chi}^{0}_{1}$.

Expected 95% exclusion contour for the simplified model with gluino-mediated top squark production where the gluinos are assumed to decay exclusively through a virtual top squark, $\tilde{g} \rightarrow tt+\tilde{\chi}^{0}_{1}$.

Observed 95% exclusion contour for the gluino simplified model from the combination of the soft single-lepton and hard single-lepton analyses for the case in which the chargino mass is fixed at x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) = 1/2.

Expected 95% exclusion contour for the gluino simplified model from the combination of the soft single-lepton and hard single-lepton analyses for the case in which the chargino mass is fixed at x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) = 1/2.

Observed 95% exclusion contour for the gluino simplified model from the hard single-lepton analyses for the case in which the chargino mass is fixed at x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) = 1/2.

Expected 95% exclusion contour for the gluino simplified model from the hard single-lepton analyses for the case in which the chargino mass is fixed at x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) = 1/2.

Observed 95% exclusion contour for the gluino simplified model from the soft single-lepton analyses for the case in which the chargino mass is fixed at x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) = 1/2.

Expected 95% exclusion contour for the gluino simplified model from the soft single-lepton analyses for the case in which the chargino mass is fixed at x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) = 1/2.

Observed 95% exclusion contour for the the first- and second-generation squark simplified model from the combination of the soft single-lepton and hard single-lepton analyses for the case in which the chargino mass is fixed at x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) = 1/2.

Expected 95% exclusion contour for the the first- and second-generation squark simplified model from the combination of the soft single-lepton and hard single-lepton analyses for the case in which the chargino mass is fixed at x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) = 1/2.

Observed 95% exclusion contour for the the first- and second-generation squark simplified model from the hard single-lepton analysis for the case in which the chargino mass is fixed at x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) = 1/2.

Expected 95% exclusion contour for the the first- and second-generation squark simplified model from the hard single-lepton analysis for the case in which the chargino mass is fixed at x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) = 1/2.

Observed 95% exclusion contour for the the first- and second-generation squark simplified model from the soft single-lepton analysis for the case in which the chargino mass is fixed at x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) = 1/2.

Expected 95% exclusion contour for the the first- and second-generation squark simplified model from the soft single-lepton analysis for the case in which the chargino mass is fixed at x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) = 1/2.

Observed 95% exclusion contour for the gluino simplified model from the combination of the soft single-lepton and hard single-lepton analyses for the case in which x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) is varied and the LSP mass is set at 60 GeV.

Expected 95% exclusion contour for the gluino simplified model from the combination of the soft single-lepton and hard single-lepton analyses for the case in which x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) is varied and the LSP mass is set at 60 GeV.

Observed 95% exclusion contour for the gluino simplified model from the hard single-lepton analysis for the case in which x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) is varied and the LSP mass is set at 60 GeV.

Expected 95% exclusion contour for the gluino simplified model from the hard single-lepton analysis for the case in which x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) is varied and the LSP mass is set at 60 GeV.

Observed 95% exclusion contour for the gluino simplified model from the soft single-lepton analysis for the case in which x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) is varied and the LSP mass is set at 60 GeV.

Expected 95% exclusion contour for the gluino simplified model from the soft single-lepton analysis for the case in which x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) is varied and the LSP mass is set at 60 GeV.

Observed 95% exclusion contour for the first- and second-generation squark simplified model from the combination of the soft single-lepton and hard single-lepton analyses for the case in which x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) is varied and the LSP mass is set at 60 GeV.

Expected 95% exclusion contour for the first- and second-generation squark simplified model from the combination of soft single-lepton and hard single-lepton analyses for the case in which x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) is varied and the LSP mass is set at 60 GeV.

Observed 95% exclusion contour for the first- and second-generation squark simplified model from the hard single-lepton analyses for the case in which x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) is varied and the LSP mass is set at 60 GeV.

Expected 95% exclusion contour for the first- and second-generation squark simplified model from the hard single-lepton analyses for the case in which x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) is varied and the LSP mass is set at 60 GeV.

Observed 95% exclusion contour for the first- and second-generation squark simplified model from the soft single-lepton analyses for the case in which x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) is varied and the LSP mass is set at 60 GeV.

Expected 95% exclusion contour for the first- and second-generation squark simplified model from the soft single-lepton analyses for the case in which x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) is varied and the LSP mass is set at 60 GeV.

Observed 95% exclusion contour for the two-step gluino simplified model with sleptons from the combination of the hard dilepton and hard single-lepton analyses.

Expected 95% exclusion contour for the two-step gluino simplified model with sleptons from the combination of the hard dilepton and hard single-lepton analyses.

Observed 95% exclusion contour for the two-step gluino simplified model with sleptons from the hard single-lepton analysis.

Expected 95% exclusion contour for the two-step gluino simplified model with sleptons from the hard single-lepton analysis.

Observed 95% exclusion contour for the two-step gluino simplified model with sleptons from the hard dilepton analysis.

Expected 95% exclusion contour for the two-step gluino simplified model with sleptons from the hard dilepton analysis.

Observed 95% exclusion contour for the two-step first- and second-generation squark simplified model with sleptons from the hard dilepton analysis.

Expected 95% exclusion contour for the two-step first- and second-generation squark simplified model with sleptons from the hard dilepton analysis.

Observed 95% exclusion contour for the two-step gluino simplified model without sleptons from the hard single-lepton analysis.

Expected 95% exclusion contour for the two-step gluino simplified model without sleptons from the hard single-lepton analysis.

Number of generated events in the gluino simplified model for the case in which the chargino mass is fixed at x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) = 1/2.

Production cross-section in the gluino simplified model for the case in which the chargino mass is fixed at x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) = 1/2.

Number of generated events in the the first- and second-generation squark simplified model for the case in which x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) is varied and the LSP mass is set at 60 GeV. squark decaying to quark neutralino1 with varying x.

Production cross-section in the the first- and second-generation squark simplified model for the case in which x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) is varied and the LSP mass is set at 60 GeV.

Number of generated evens in the minimal UED model.

Production cross-section in the minimal UED model in pb.

Number of generated events in the two-step first- and second-generation squark simplified model with sleptons.

Production cross-section in the two-step first- and second-generation squark simplified model with sleptons.

Acceptance for soft single-lepton 3-jet signal region in the gluino simplified model for the case in which the chargino mass is fixed at x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) = 1/2.

Efficiency for soft single-lepton 3-jet signal region in the gluino simplified model for the case in which the chargino mass is fixed at x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) = 1/2.

Acceptance for soft single-lepton 5-jet signal region in the gluino simplified model for the case in which the chargino mass is fixed at x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) = 1/2.

Efficiency for soft single-lepton 5-jet signal region in the gluino simplified model for the case in which the chargino mass is fixed at x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) = 1/2.

Acceptance for soft single-lepton 3-jet inclusive signal region in the gluino simplified model for the case in which x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) is varied and the LSP mass is set at 60 GeV.

Efficiency for the soft single-lepton 3-jet inclusive signal region in the gluino simplified model for the case in x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) is varied and the LSP mass is set at 60 GeV.

Expected CLs from the combination of the soft single-lepton and hard single-lepton analyses in the gluino simplified model for the case in which the chargino mass is fixed at x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) = 1/2.

Expected CLs from the combination of the soft single-lepton and hard single-lepton analyses in the gluino simplified model for the case in which the chargino mass is varied and the LSP mass is set at 60 GeV. The chargino mass is parameterised using x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)).

Observed CLs from the combination of the soft single-lepton and hard single-lepton analyses in the gluino simplified model for the case in which the chargino mass is fixed at x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) = 1/2.

Observed CLs from the combination of the soft single-lepton and hard single-lepton analyses in the gluino simplified model for the case in which the chargino mass is varied and the LSP mass is set at 60 GeV. The chargino mass is parameterised using x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)).

Acceptance for soft dimuon signal region in the minimal UED model (mUED).

Efficiency for soft dimuon signal region in minimal UED model (mUED).

Acceptance for hard dilepton 3-jet opposite-flavour signal region in the two-step first- and second-generation squark simplified model with sleptons.

Efficiency for hard dilepton 3jet opposite-flavour signal region in the two-step first- and second-generation squark simplified model with sleptons.

Acceptance for hard dilepton 3-jet same-flavour signal region in the two-step first- and second-generation squark simplified model with sleptons.

Efficiency for hard dilepton 3-jet same-flavour signal region in the two-step first- and second-generation squark simplified model with sleptons.

Acceptance for hard dilepton low-multiplicity opposite-flavour signal region in the two-step first- and second-generation squark simplified model with sleptons.

Efficiency for hard dilepton low-multiplicity opposite-flavour signal region in the two-step first- and second-generation squark simplified model with sleptons.

Acceptance for hard dilepton low-multiplicity same-flavour signal region in the two-step first- and second-generation squark simplified model with sleptons.

Efficiency for hard dilepton low-multiplicity same-flavour signal region in the two-step first- and second-generation squark simplified model with sleptons.

Best expected signal region in the minimal UED model (mUED).

Expected CLs from hard dilepton analysis in the two-step first- and second-generation squark simplified model with sleptons.

Observed CLs from the hard dilepton analysis in the two-step first- and second-generation squark simplified model with sleptons.

Expected CLs from the combination of the soft dimuon and hard dilepton analyses in the minimal UED model (mUED).

Observed CLs from the combination of the soft dimuon and hard dilepton analyses in the minimal UED model (mUED).

Acceptance for hard single-lepton 3-jet signal region in the gluino simplified model for the case in which the chargino mass is fixed at x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) = 1/2.

Efficiency for hard single-lepton 3-jet signal region in the gluino simplified model for the case in which the chargino mass is fixed at x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) = 1/2.

Acceptance for hard single-lepton 5-jet signal region in the gluino simplified model for the case in which the chargino mass is fixed at x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) = 1/2.

Efficiency for hard single-lepton 5-jet signal region in the gluino simplified model for the case in which the chargino mass is fixed at x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) = 1/2.

Acceptance for hard single-lepton 6-jet signal region in the gluino simplified model for the case in which the chargino mass is fixed at x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) = 1/2.

Efficiency for hard single-lepton 6-jet signal region in the gluino simplified model for the case in which the chargino mass is fixed at x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) = 1/2.

Acceptance for hard single-lepton 3-jet signal region in the first- and second-generation squark simplified model for the case in which x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) is varied and the LSP mass is set at 60 GeV.

Efficiency for hard single-lepton 3-jet signal region in the first- and second-generation squark simplified model for the case in which x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) is varied and the LSP mass is set at 60 GeV.

Acceptance for hard single-lepton 5-jet signal region in the first- and second-generation squark simplified model for the case in which x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) is varied and the LSP mass is set at 60 GeV.

Efficiency for hard single-lepton 5-jet signal region in the first- and second-generation squark simplified model for the case in which x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) is varied and the LSP mass is set at 60 GeV.

Acceptance for hard single-lepton 6-jet signal region in the first- and second-generation squark simplified model for the case in which x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) is varied and the LSP mass is set at 60 GeV.

Efficiency for hard single-lepton 6-jet signal region in the first- and second-generation squark simplified model for the case in which x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) is varied and the LSP mass is set at 60 GeV.

Observed 95% upper limit on the visible cross-section in the gluino simplified model from the combination of the soft single-lepton and hard single-lepton analyses for the case in which the chargino mass is fixed at x = (m(gluino)-m(chargino))/(m(gluino)-m(LSP)) = 1/2.

Observed 95% upper limit on the visible cross-section in the first- and second-generation squark simplified model from the combination of the soft single-lepton and hard single-lepton analyses for the case in which x = (m(squark)-m(chargino))/(m(squark)-m(LSP)) is varied and the LSP mass is set at 60 GeV.

Observed 95% upper limit on the visible cross-section in the first- and second-generation squark simplified model with sleptons from the hard dilepton analysis.

Observed 95% upper limit on the visible cross-section in the minimal UED model (mUED) from the combination of the soft dimuon and hard dilepton analyses.

The effective mass distribution in VR2Z.

The ETmiss distribution in SR0noZa.

The effective mass distribution in SR0noZa.

The ETmiss distribution in SR1noZa.

The effective mass distribution in SR1noZa.

The ETmiss distribution in SR2noZa.

The effective mass distribution in SR2noZa.

The ETmiss distribution in SR0noZb.

The effective mass distribution in SR0noZb.

The ETmiss distribution in SR1noZb.

The effective mass distribution in SR1noZb.

The ETmiss distribution in SR2noZb.

The effective mass distribution in SR2noZb.

The ETmiss distribution in SR0Z.

The effective mass distribution in SR0Z.

The ETmiss distribution in SR1Z.

The effective mass distribution in SR1Z.

The ETmiss distribution in SR2Z.

The effective mass distribution in SR2Z.

Observed 95% CL exclusion contour for the RPV chargino NLSP model with lambda_121 != 0.

Expected 95% CL exclusion contour for the RPV chargino NLSP model with lambda_121 != 0.

Observed 95% CL exclusion contour for the RPV chargino NLSP model with lambda_122 != 0.

Expected 95% CL exclusion contour for the RPV chargino NLSP model with lambda_122 != 0.

Observed 95% CL exclusion contour for the RPV chargino NLSP model with lambda_133 != 0.

Expected 95% CL exclusion contour for the RPV chargino NLSP model with lambda_133 != 0.

Observed 95% CL exclusion contour for the RPV chargino NLSP model with lambda_233 != 0.

Expected 95% CL exclusion contour for the RPV chargino NLSP model with lambda_233 != 0.

Observed 95% CL exclusion contour for the RPV gluino NLSP model with lambda_121 != 0.

Expected 95% CL exclusion contour for the RPV gluino NLSP model with lambda_121 != 0.

Observed 95% CL exclusion contour for the RPV gluino NLSP model with lambda_122 != 0.

Expected 95% CL exclusion contour for the RPV gluino NLSP model with lambda_122 != 0.

Observed 95% CL exclusion contour for the RPV gluino NLSP model with lambda_133 != 0.

Expected 95% CL exclusion contour for the RPV gluino NLSP model with lambda_133 != 0.

Observed 95% CL exclusion contour for the RPV gluino NLSP model with lambda_233 != 0.

Expected 95% CL exclusion contour for the RPV gluino NLSP model with lambda_233 != 0.

Observed 95% CL exclusion contour for the RPV Lslepton NLSP model with lambda_121 != 0.

Expected 95% CL exclusion contour for the RPV Lslepton NLSP model with lambda_121 != 0.

Observed 95% CL exclusion contour for the RPV Lslepton NLSP model with lambda_122 != 0.

Expected 95% CL exclusion contour for the RPV Lslepton NLSP model with lambda_122 != 0.

Observed 95% CL exclusion contour for the RPV Lslepton NLSP model with lambda_133 != 0.

Expected 95% CL exclusion contour for the RPV Lslepton NLSP model with lambda_133 != 0.

Observed 95% CL exclusion contour for the RPV Lslepton NLSP model with lambda_233 != 0.

Expected 95% CL exclusion contour for the RPV Lslepton NLSP model with lambda_233 != 0.

Observed 95% CL exclusion contour for the RPV Rslepton NLSP model with lambda_121 != 0.

Expected 95% CL exclusion contour for the RPV Rslepton NLSP model with lambda_121 != 0.

Observed 95% CL exclusion contour for the RPV Rslepton NLSP model with lambda_122 != 0.

Expected 95% CL exclusion contour for the RPV Rslepton NLSP model with lambda_122 != 0.

Observed 95% CL exclusion contour for the RPV Rslepton NLSP model with lambda_133 != 0.

Expected 95% CL exclusion contour for the RPV Rslepton NLSP model with lambda_133 != 0.

Observed 95% CL exclusion contour for the RPV Rslepton NLSP model with lambda_233 != 0.

Expected 95% CL exclusion contour for the RPV Rslepton NLSP model with lambda_233 != 0.

Observed 95% CL exclusion contour for the RPV sneutrino NLSP model with lambda_121 != 0.

Expected 95% CL exclusion contour for the RPV sneutrino NLSP model with lambda_121 != 0.

Observed 95% CL exclusion contour for the RPV sneutrino NLSP model with lambda_122 != 0.

Expected 95% CL exclusion contour for the RPV sneutrino NLSP model with lambda_122 != 0.

Observed 95% CL exclusion contour for the RPV sneutrino NLSP model with lambda_133 != 0.

Expected 95% CL exclusion contour for the RPV sneutrino NLSP model with lambda_133 != 0.

Observed 95% CL exclusion contour for the RPV sneutrino NLSP model with lambda_233 != 0.

Expected 95% CL exclusion contour for the RPV sneutrino NLSP model with lambda_233 != 0.

Observed 95% CL exclusion contour for the R-slepton RPC model.

Expected 95% CL exclusion contour for the R-slepton RPC model.

Observed and expected 95% CL cross-section upper limits for the Stau RPC model, together with the theoretically predicted cross-section.

Observed and expected 95% CL cross-section upper limits for the Z RPC model, together with the theoretically predicted cross-section.

Observed 95% CL exclusion contour for the GGM tan beta = 1.5 model.

Expected 95% CL exclusion contour for the GGM tan beta = 1.5 model.

Observed 95% CL exclusion contour for the GGM tan beta = 30 model.

Expected 95% CL exclusion contour for the GGM tan beta = 30 model.

Observed 95% CL cross-section upper limit for the RPV chargino NLSP models with lambda_121 != 0 and lambda_122 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).

Observed 95% CL cross-section upper limit for the RPV chargino NLSP models with lambda_133 != 0 and lambda_233 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).

Observed 95% CL cross-section upper limit for the RPV gluino NLSP models with lambda_121 != 0 and lambda_122 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).

Observed 95% CL cross-section upper limit for the RPV gluino NLSP models with lambda_133 != 0 and lambda_233 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).

Observed 95% CL cross-section upper limit for the RPV Lslepton NLSP models with lambda_121 != 0 and lambda_122 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).

Observed 95% CL cross-section upper limit for the RPV Lslepton NLSP models with lambda_133 != 0 and lambda_233 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).

Observed 95% CL cross-section upper limit for the RPV Rslepton NLSP models with lambda_121 != 0 and lambda_122 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).

Observed 95% CL cross-section upper limit for the RPV Rslepton NLSP models with lambda_133 != 0 and lambda_233 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).

Observed 95% CL cross-section upper limit for the RPV sneutrino NLSP models with lambda_121 != 0 and lambda_122 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).

Observed 95% CL cross-section upper limit for the RPV sneutrino NLSP models with lambda_133 != 0 and lambda_233 != 0, and the selection of Z-veto signal regions used to set limits in these models. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bba' means that the regions SR0noZb, SR1noZb and SR2noZa were used, in addition to the three Z-rich regions (SR0-2Z).

Observed 95% CL cross-section upper limit for the R-slepton RPC model, and the selection of Z-veto signal regions used to set limits in this model. The combination of regions used is ordered by the minimum number of hadronic taus required. For example, ``bbb' means that the regions SR0noZb, SR1noZb and SR2noZb were used, in addition to the three Z-rich regions (SR0-2Z). For the RPC stau and Z models, the ``aaa' combination of regions was used throughout.

Performance of the SR0noZa selection in the R-slepton RPC model: number of generated signal events; total signal cross-section; acceptance; efficiency; total experimental systematic uncertainty, not including Monte Carlo statistics; observed CL using this region alone; expected CL using this region alone.

Performance of the SR0noZb selection in the RPV chargino NLSP model with lambda_121 != 0: number of generated signal events; total signal cross-section; acceptance; efficiency; total experimental systematic uncertainty, not including Monte Carlo statistics; observed CL using this region alone; expected CL using this region alone.

Performance of the SR1noZa selection in the RPV sneutrino NLSP model with lambda_233 != 0: number of generated signal events; total signal cross-section; acceptance; efficiency; total experimental systematic uncertainty, not including Monte Carlo statistics; observed CL using this region alone; expected CL using this region alone.

Performance of the SR1noZb selection in the RPV gluino NLSP model with lambda_133 != 0: number of generated signal events; total signal cross-section; acceptance; efficiency; total experimental systematic uncertainty, not including Monte Carlo statistics; observed CL using this region alone; expected CL using this region alone.

Performance of the SR2noZa selection in the RPV sneutrino NLSP model with lambda_233 != 0: number of generated signal events; total signal cross-section; acceptance; efficiency; total experimental systematic uncertainty, not including Monte Carlo statistics; observed CL using this region alone; expected CL using this region alone.

Performance of the SR2noZb selection in the RPV gluino NLSP model with lambda_133 != 0: number of generated signal events; total signal cross-section; acceptance; efficiency; total experimental systematic uncertainty, not including Monte Carlo statistics; observed CL using this region alone; expected CL using this region alone.

Performance of the SR0Z selection in the GGM tan beta = 30 model: number of generated signal events; total signal cross-section; acceptance; efficiency; total experimental systematic uncertainty, not including Monte Carlo statistics; observed CL using this region alone; expected CL using this region alone.

Cut flows for a representative selection of SUSY signal points in the Z-veto signal regions. In each case, m2 and m1 refer to the axes of the plots in Sec. XI, where m2 is the larger of the two masses. The number of events expected for a luminosity of 20.3 fb-1 is quoted at each step of the selection. The preselection requires four baseline leptons, at least two of which are light leptons; the signal lepton selection is made at the ``Lepton Multiplicity' stage. ``Event Cleaning' refers to the selection criteria applied to remove non-collision backgrounds and detector noise.

Cut flows for a representative selection of SUSY signal points in the Z-rich signal regions. In each case, m2 and m1 refer to the axes of the plots in Sec. XI, where m2 is the larger of the two masses (or the value of mu in the case of GGM models). The number of events expected for a luminosity of 20.3 fb-1 is quoted at each step of the selection. The preselection requires four baseline leptons, at least two of which are light leptons; the signal lepton selection is made at the ``Lepton Multiplicity' stage. ``Event Cleaning' refers to the selection criteria applied to remove non-collision backgrounds and detector noise.

Cut flows by lepton channel for a representative selection of SUSY signal points in the SR0noZa signal region. In each case, m2 and m1 refer to the axes of the plots in Sec. XI, where m2 is the larger of the two masses. The number of events expected for a luminosity of 20.3 fb-1 is quoted at each step of the selection. The preselection requires four baseline leptons, at least two of which are light leptons; the signal lepton selection is made at the ``Lepton Multiplicity' stage. ``Event Cleaning' refers to the selection criteria applied to remove non-collision backgrounds and detector noise. The RPC R-slepton model is used, with (m2,m1) = (450,300) GeV.

Cut flows by lepton channel for a representative selection of SUSY signal points in the SR1noZb signal region. In each case, m2 and m1 refer to the axes of the plots in Sec. XI, where m2 is the larger of the two masses. The number of events expected for a luminosity of 20.3 fb-1 is quoted at each step of the selection. The preselection requires four baseline leptons, at least two of which are light leptons; the signal lepton selection is made at the ``Lepton Multiplicity' stage. ``Event Cleaning' refers to the selection criteria applied to remove non-collision backgrounds and detector noise. The RPV gluino NLSP model is used, with lambda_133 != 0 and (m2,m1) = (800,400) GeV.

Cut flows by lepton channel for a representative selection of SUSY signal points in the SR0Z signal region. In each case, m2 and m1 refer to the axes of the plots in Sec. XI, where m2 is the value of mu. The number of events expected for a luminosity of 20.3 fb-1 is quoted at each step of the selection. The preselection requires four baseline leptons, at least two of which are light leptons; the signal lepton selection is made at the ``Lepton Multiplicity' stage. ``Event Cleaning' refers to the selection criteria applied to remove non-collision backgrounds and detector noise. The GGM tan beta = 30 model is used, with (m2,m1) = (200,1000) GeV.