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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L0b, in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde \chi_1^\pm)$ = 1200 GeV, $m(\tilde \chi_2^0)$ = 1000 GeV and $m(\tilde \chi_1^0)$ = 800 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L0b, in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde \chi_1^\pm)$ = 1200 GeV, $m(\tilde \chi_2^0)$ = 1000 GeV and $m(\tilde \chi_1^0)$ = 800 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L0b, in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde \chi_1^\pm)$ = 1200 GeV, $m(\tilde \chi_2^0)$ = 1000 GeV and $m(\tilde \chi_1^0)$ = 800 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L0b, in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde \chi_1^\pm)$ = 1200 GeV, $m(\tilde \chi_2^0)$ = 1000 GeV and $m(\tilde \chi_1^0)$ = 800 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L1b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 850 GeV, $m(\tilde \chi_1^\pm)$ = 500 GeV and $m(\tilde \chi_1^0)$ = 400 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L1b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 850 GeV, $m(\tilde \chi_1^\pm)$ = 500 GeV and $m(\tilde \chi_1^0)$ = 400 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L1b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 850 GeV, $m(\tilde \chi_1^\pm)$ = 500 GeV and $m(\tilde \chi_1^0)$ = 400 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L1b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 850 GeV, $m(\tilde \chi_1^\pm)$ = 500 GeV and $m(\tilde \chi_1^0)$ = 400 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L2b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 850 GeV, $m(\tilde \chi_1^\pm)$ = 500 GeV and $m(\tilde \chi_1^0)$ = 400 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L2b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 900 GeV, $m(\tilde \chi_1^\pm)$ = 150 GeV and $m(\tilde \chi_1^0)$ = 50 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L2b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 900 GeV, $m(\tilde \chi_1^\pm)$ = 150 GeV and $m(\tilde \chi_1^0)$ = 50 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L2b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 900 GeV, $m(\tilde \chi_1^\pm)$ = 150 GeV and $m(\tilde \chi_1^0)$ = 50 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc3LSS1b, in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate. The masses of the superpartners involved in the process are set to $m(\tilde{t}^{}_1)$ = 800 GeV, $m(\tilde \chi_2^0)$ = 625 GeV, $m(\tilde \chi_1^\pm)\approx m(\tilde \chi_1^0)$ = 525 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc3LSS1b, in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate. The masses of the superpartners involved in the process are set to $m(\tilde{t}^{}_1)$ = 800 GeV, $m(\tilde \chi_2^0)$ = 625 GeV, $m(\tilde \chi_1^\pm)\approx m(\tilde \chi_1^0)$ = 525 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc3LSS1b, in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate. The masses of the superpartners involved in the process are set to $m(\tilde{t}^{}_1)$ = 800 GeV, $m(\tilde \chi_2^0)$ = 625 GeV, $m(\tilde \chi_1^\pm)\approx m(\tilde \chi_1^0)$ = 525 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc3LSS1b, in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate. The masses of the superpartners involved in the process are set to $m(\tilde{t}^{}_1)$ = 800 GeV, $m(\tilde \chi_2^0)$ = 625 GeV, $m(\tilde \chi_1^\pm)\approx m(\tilde \chi_1^0)$ = 525 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpv2L, in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde{t}^{}_{1})$ = 800 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpv2L, in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde{t}^{}_{1})$ = 800 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpv2L, in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde{t}^{}_{1})$ = 800 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpv2L, in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde{t}^{}_{1})$ = 800 GeV. Only statistical uncertainties are shown.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Acceptances on TRUTH level of the DMt samples in the tW1L channel for all bins in the SR. The acceptance is defined as the number of weighted TRUTH events in the SR over the number of expected events without any selections. The maps include all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.

Efficiencies of the DMt samples in the tW2L SR. The efficiency is defined as the number of weighted reconstructed events over the number of weighted TRUTH events in the SR. The maps include all samples in the $m_a - m_H$ plane with $tan\beta = 1$.

Acceptances on TRUTH level of the DMt samples in the tW2L SR. The acceptance is defined as the number of weighted TRUTH events in the SR over the number of expected events without any selections. The maps include all samples in the $m_a - m_H$ plane with $tan\beta = 1$.

Efficiencies of the DMt samples in the tW2L SR. The efficiency is defined as the number of weighted reconstructed events over the number of weighted TRUTH events in the SR. The maps include all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.

Acceptances on TRUTH level of the DMt samples in the tW2L SR. The acceptance is defined as the number of weighted TRUTH events in the SR over the number of expected events without any selections. The maps include all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.

Efficiencies of the DMt samples in the tj1L channel for all bins in the SR. The efficiency is defined as the number of weighted reconstructed events over the number of weighted TRUTH events in the SR. The map includes all used samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.

Acceptances on TRUTH level of the DMt samples in the tj1L channel for all bins in the SR. The acceptance is defined as the number of weighted TRUTH events in the SR over the number of expected events without any selections. The map includes all used samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.

Upper limits on signal strength (excluded cross section over theoretical cross section) of the tW1L analysis considering only DMt signal.

Upper limits on excluded cross sections of the tW1L analysis considering only the DMt signal.

The expected exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming only $tW$+DM contributions, for the tW1L analysis channel.

The observed exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming only $tW$+DM contributions, for the tW1L analysis channel.

Upper limits on signal strength (excluded cross section over theoretical cross section) of the tW1L analysis considering only DMt signal.

Upper limits on excluded cross sections of the tW1L analysis considering only the DMt signal.

The expected exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming only $tW$+DM contributions, for the tW1L analysis channel.

The observed exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming only $tW$+DM contributions, for the tW1L analysis channel.

Upper limits on signal strength (excluded cross section over theoretical cross section) of the tW2L analysis considering only DMt signal.

Upper limits on excluded cross sections of the tW2L analysis considering only the DMt signal.

The expected exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming only $tW$+DM contributions, for the tW2L analysis channel.

The observed exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming only $tW$+DM contributions, for the tW2L analysis channel.

Upper limits on signal strength (excluded cross section over theoretical cross section) of the tW2L analysis considering only DMt signal.

Upper limits on excluded cross sections of the tW2L analysis considering only the DMt signal.

The expected exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming only $tW$+DM contributions, for the tW2L analysis channel.

The observed exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming only $tW$+DM contributions, for the tW2L analysis channel.

Upper limits on signal strength (excluded cross section over theoretical cross section) of the combined tW1L and tW2L analyses considering only the DMt signal.

Upper limits on excluded cross sections of the combined tW1L and tW2L analyses considering only the DMt signal.

The expected exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming only $tW$+DM contributions, for the statistical combination of the tW1L and tW2L analysis channel.

The observed exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming only $tW$+DM contributions, for the statistical combination of the tW1L and tW2L analysis channel.

Upper limits on signal strength (excluded cross section over theoretical cross section) of the combined tW1L and tW2L analyses considering only the DMt signal.

Upper limits on excluded cross sections of the combined tW1L and tW2L analyses considering only the DMt signal.

The expected exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming only $tW$+DM contributions, for the statistical combination of the tW1L and tW2L analysis channel.

The observed exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming only $tW$+DM contributions, for the statistical combination of the tW1L and tW2L analysis channel.

Upper limits on signal strength (excluded cross section over theoretical cross section) of the tW1L analysis considering the DMt$\bar{t}$+DMt signal.

The expected exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the tW1L analysis channel.

The observed exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the tW1L analysis channel.

Upper limits on signal strength (excluded cross section over theoretical cross section) of the tW1L analysis considering the DMt$\bar{t}$+DMt signal.

The expected exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the tW1L analysis channel.

The observed exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the tW1L analysis channel.

Upper limits on signal strength (excluded cross section over theoretical cross section) of the tW2L analysis considering the DMt$\bar{t}$+DMt signal.

The expected exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the tW2L analysis channel.

The observed exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the tW2L analysis channel.

Upper limits on signal strength (excluded cross section over theoretical cross section) of the tW2L analysis considering the DMt$\bar{t}$+DMt signal.

The expected exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the tW2L analysis channel.

The observed exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the tW2L analysis channel.

Upper limits on signal strength (excluded cross section over theoretical cross section) of the combined tW1L and tW2L analyses considering the DMt$\bar{t}$+DMt signal.

The expected exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the statistical combination of the tW1L and tW2L analysis channel.

The observed exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the statistical combination of the tW1L and tW2L analysis channel.

Upper limits on signal strength (excluded cross section over theoretical cross section) of the combined tW1L and tW2L analyses considering the DMt$\bar{t}$+DMt signal.

The expected exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the statistical combination of the tW1L and tW2L analysis channel.

The observed exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the statistical combination of the tW1L and tW2L analysis channel.

Upper limits on signal strength (excluded cross section over theoretical cross section) of the tj1L analysis considering only the DMt signal.

Upper limits on upper limits on excluded cross sections of the tj1L analysis considering only the DMt signal.

The expected and observed cross section exclusion limits as a function of $m_{H^{\pm}}$ in the tj1L analysis channel for signal models with $m_a = 250~GeV$, and $\tan\beta=0.3$. The $\sigma^{}_\mathrm{BSM}$ is the cross section of the $t$-channel DM production process.

The expected and observed cross section exclusion limits as a function of $m_{H^{\pm}}$ in the tj1L analysis channel for signal models with $m_a = 250~GeV$, and $\tan\beta=0.5$. The $\sigma^{}_\mathrm{BSM}$ is the cross section of the $t$-channel DM production process.

Cross sections of the DMt samples in the tW1L channel. The maps include all samples in the $m_a - m_H$ plane with $tan\beta = 1$.

Cross sections of the DMt samples in the tW1L channel. The maps include all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.

Cross sections times branching ratio of the DMt samples in the tW2L channel. The maps include all samples in the $m_a - m_H$ plane with $tan\beta = 1$.

Cross sections times branching ratio of the DMt samples in the tW2L channel. The maps include all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.

Cross sections of the DMt samples in the tj1L channel. The map includes all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.

MC generator filter efficiencies of the DMt samples in the tW1L channel. The maps include all samples in the $m_a - m_H$ plane with $tan\beta = 1$.

MC generator filter efficiencies of the DMt samples in the tW1L channel. The maps include all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.

MC generator filter efficiencies of the DMt samples in the tW2L channel. The maps include all samples in the $m_a - m_H$ plane with $tan\beta = 1$.

MC generator filter efficiencies of the DMt samples in the tW2L channel. The maps include all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.

MC generator filter efficiencies of the DMt samples in the tj1L channel. The map includes all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.

Background-only fit results for the tW1L and tW2L signal regions. The backgrounds which contribute only a small amount (rare processes such as triboson, Higgs boson production processes, $t\bar{t}t\bar{t}$, $t\bar{t}WW$ and non-prompt or misidentified leptons background) are grouped and labelled as ``Others´´. The quoted uncertainties on the fitted SM background include both the statistical and systematic uncertainties.

Background-only fit results for the tj1L signal regions. The backgrounds which contribute only a small amount ($Z$+jets, rare processes such as $tWZ$, triboson, Higgs boson production processes, ,$t\bar{t}t\bar{t}$, $t\bar{t}WW$) are grouped and labelled as ``Others´´. The quoted uncertainties on the fitted SM background include both the statistical and systematic uncertainties.

Cutflow of the weighted events with statistical uncertainties for two DMt samples in all bins of the tW1L channel. The PreSelection includes at least 1 lepton in the event, at least 1 $b$-jet with $p_{\mathrm{T}} > 50~GeV$, $m\mathrm{_{T}^{lep}} > 30~GeV$, $\Delta\phi\mathrm{_{4jets, MET}^{min}} > 0.5$ and $E\mathrm{_{T}^{miss}} > 200~GeV$.

Cutflow of the weighted events with statistical uncertainties for two DMt samples in the tW2L channel. The PreSelection includes at least 2 leptons in the event, at least 1 $b$-jet with $p_{\mathrm{T}} > 40~GeV$, $m_{ll} > 40~GeV$, $m\mathrm{_{T2}} > 40~GeV$, $\Delta\phi\mathrm{_{4jets, MET}^{min}} > 0.5$ and $E\mathrm{_{T}^{miss}} > 200~GeV$.

Cutflow of the weighted events with the statistical uncertainties (except for the first cuts) for two DMt samples in all bins off the tj1L channel. The PreSelection includes at least 1 lepton in the event, at least 1 $b$-jet with $p_{\mathrm{T}} > 50~GeV$, $m\mathrm{_{T}^{lep}} > 30~GeV$, $\Delta\phi\mathrm{_{4jets, MET}^{min}} > 0.5$ and $E\mathrm{_{T}^{miss}} > 200~GeV$.

Ranking of the systematic uncertainties on the measured cross-section, normalised to the predicted value, in the inclusive fit to data. The impact of each nuisance parameter, $\Delta \sigma_{\text{inc}}/\sigma^{\text{pred.}}_{\text{inc}}$, is computed by comparing the nominal best-fit value of $\sigma_{\text{inc}}/\sigma^{\text{pred}}_{\text{inc}}$ with the result of the fit when fixing the considered nuisance parameter to its best-fit value, $\theta$, shifted by its pre-fit (post-fit) uncertainties $\pm \Delta \theta$ ($\pm \Delta \hat{\theta}$). The figure shows the effect of the ten most significant uncertainties.

Ranking of the systematic uncertainties on the measured cross-section, normalised to the predicted value, in the fiducial fit to data. The impact of each nuisance parameter, $\Delta \sigma_{\text{fid}}/\sigma^{\text{pred.}}_{\text{fid}}$, is computed by comparing the nominal best-fit value of $\sigma_{\text{fid}}/\sigma^{\text{pred}}_{\text{fid}}$ with the result of the fit when fixing the considered nuisance parameter to its best-fit value, $\theta$, shifted by its pre-fit (post-fit) uncertainties $\pm \Delta \theta$ ($\pm \Delta \hat{\theta}$). The figure shows the effect of the ten most significant uncertainties.

Ranking of the systematic uncertainties on the measured cross-section, normalised to the predicted value, in the fiducial fit to data. The impact of each nuisance parameter, $\Delta \sigma_{\text{fid}}/\sigma^{\text{pred.}}_{\text{fid}}$, is computed by comparing the nominal best-fit value of $\sigma_{\text{fid}}/\sigma^{\text{pred}}_{\text{fid}}$ with the result of the fit when fixing the considered nuisance parameter to its best-fit value, $\theta$, shifted by its pre-fit (post-fit) uncertainties $\pm \Delta \theta$ ($\pm \Delta \hat{\theta}$). The figure shows the effect of the ten most significant uncertainties.

Impact of different categories of systematic uncertainties on the fiducial and inclusive measurements. The quoted values are obtained by repeating the fit, fixing a set of nuisance parameters of the sources corresponding to the considered category, and subtracting in quadrature the resulting uncertainty from the total uncertainty of the nominal fit. The total uncertainty is different from the sum in quadrature of the different components due to correlations between nuisance parameters built by the fit.

Impact of different categories of systematic uncertainties on the fiducial and inclusive measurements. The quoted values are obtained by repeating the fit, fixing a set of nuisance parameters of the sources corresponding to the considered category, and subtracting in quadrature the resulting uncertainty from the total uncertainty of the nominal fit. The total uncertainty is different from the sum in quadrature of the different components due to correlations between nuisance parameters built by the fit.

Fiducial region definition

Fiducial region definition

Summary of results for charm and bottom muon v2 as a function of pT. Uncertainties are statistical and systematic, respectively.

Distribution for the maxPT jet (P=3) from 260 to 310 GeV.

Distribution for the maxPT jet (P=3) from 310 to 400 GeV.

Distribution for the maxPT jet (P=3) from 400 to 500 GeV.

Distribution for the maxPT jet (P=3) from 500 to 600 GeV.

Distribution for the maxPT jet (P=3) from 600 to 800 GeV.

Distribution for the maxPT jet (P=3) from 800 to 10000 GeV.

Inclusive J/psi production cross-section as a function of J/psi pT in the J/psi rapidity (|y|) bin 1.5<|y|<2. The first uncertainty is statistical, the second is systematic and the third encapsulates any possible variation due to spin-alignment from the unpolarised central value.

Inclusive J/psi production cross-section as a function of J/psi pT in the J/psi rapidity (|y|) bin 0.75<|y|<1.5. The first uncertainty is statistical, the second is systematic and the third encapsulates any possible variation due to spin-alignment from the unpolarised central value.

Inclusive J/psi production cross-section as a function of J/psi pT in the J/psi rapidity (|y|) bin |y|<0.75. The first uncertainty is statistical, the second is systematic and the third encapsulates any possible variation due to spin-alignment from the unpolarised central value.

Non-prompt to inclusive production cross-section fraction fB as a function of J/psi pT for J/psi rapidity |y|<0.75 under the assumption that prompt and non-prompt J/psi production is unpolarised (lambda_theta = 0). The spin-alignment envelope spans the range of possible prompt cross-sections under various polarisation hypotheses, plus the range of non-prompt cross-sections within lambda_theta = +/- 0.1. The first uncertainty is statistical, the second uncertainty is systematic, the third number is the uncertainty due to spin-alignment.}.

Non-prompt to inclusive production cross-section fraction fB as a function of J/psi pT for J/psi rapidity 0.75<|y|<1.5 under the assumption that prompt and non-prompt J/psi production is unpolarised (lambda_theta = 0). The spin-alignment envelope spans the range of possible prompt cross-sections under various polarisation hypotheses, plus the range of non-prompt cross-sections within lambda_theta = +/-0.1. The first uncertainty is statistical, the second uncertainty is systematic, the third number is the uncertainty due to spin-alignment.

Non-prompt to inclusive production cross-section fraction fB as a function of J/psi pT for J/psi rapidity 1.5<|y|<2 under the assumption that prompt and non-prompt J/psi production is unpolarised (lambda_theta = 0). The spin-alignment envelope spans the range of possible prompt cross-sections under various polarisation hypotheses, plus the range of non-prompt cross-sections within lambda_theta = +/-0.1. The first uncertainty is statistical, the second uncertainty is systematic, the third number is the uncertainty due to spin-alignment.

Non-prompt to inclusive production cross-section fraction fB as a function of J/psi pT for J/psi rapidity 2<|y|<2.4 under the assumption that prompt and non-prompt J/psi production is unpolarised (lambda_theta = 0). The spin-alignment envelope spans the range of possible prompt cross-sections under various polarisation hypotheses, plus the range of non-prompt cross-sections within lambda_theta =+/-0.1. The first uncertainty is statistical, the second uncertainty is systematic, the third number is the uncertainty due to spin-alignment.

Non-prompt J/psi production cross-sections as a function of J/psi pT for J/psi rapidity |y|<0.75 under the assumption that prompt and non-prompt J/psi production is unpolarised (lambda_theta = 0), and the spin-alignment envelope spans the range of non-prompt cross-sections within lambda_theta = +/- 0.1. The first uncertainty is statistical, the second uncertainty is systematic. Comparison is made to FONLL predictions.

Non-prompt J/psi production cross-sections as a function of J/psi pT for J/psi rapidity 0.75<|y|<1.5 under the assumption that prompt and non-prompt J/psi production is unpolarised (lambda_theta = 0), and the spin-alignment envelope spans the range of non-prompt cross-sections within lambda_theta = +/- 0.1. The first uncertainty is statistical, the second uncertainty is systematic. Comparison is made to FONLL predictions.

Non-prompt J/psi production cross-sections as a function of J/psi pT for J/psi rapidity 1.5<|y|<2 under the assumption that prompt and non-prompt J/psi production is unpolarised (lambda_theta = 0), and the spin-alignment envelope spans the range of non-prompt cross-sections within lambda_theta = +/- 0.1. The first uncertainty is statistical, the second uncertainty is systematic. Comparison is made to FONLL predictions.

Non-prompt J/psi production cross-sections as a function of J/psi pT for J/psi rapidity 2<|y|<2.4 under the assumption that prompt and non-prompt J/psi production is unpolarised (lambda_theta = 0), and the spin-alignment envelope spans the range of non-prompt cross-sections within lambda_theta = +/- 0.1. The first uncertainty is statistical, the second uncertainty is systematic. Comparison is made to FONLL predictions.

Prompt J/psi production cross-sections as a function of J/psi pT for J/psi rapidity |y|<0.75. The central value assumes unpolarised (lambda_theta = 0) prompt and non-prompt production, and the spin-alignment envelope spans the range of possible prompt cross-sections under various polarisation hypotheses. The first quoted uncertainty is statistical, the second uncertainty is systematic. Comparison is made to the Colour Evaporation Model prediction.

Prompt J/psi production cross-sections as a function of J/psi pT for J/psi rapidity 0.75<|y|<1.5. The central value assumes unpolarised (lambda_theta = 0) prompt and non-prompt production, and the spin-alignment envelope spans the range of possible prompt cross-sections under various polarisation hypotheses. The first quoted uncertainty is statistical, the second uncertainty is systematic. Comparison is made to the Colour Evaporation Model prediction.

Prompt J/psi production cross-sections as a function of J/psi pT for J/psi rapidity 1.5<|y|<2. The central value assumes unpolarised (lambda_theta = 0) prompt and non-prompt production, and the spin-alignment envelope spans the range of possible prompt cross-sections under various polarisation hypotheses. The first quoted uncertainty is statistical, the second uncertainty is systematic. Comparison is made to the Colour Evaporation Model prediction.

Prompt J/psi production cross-sections as a function of J/psi pT for J/psi rapidity 2<|y|<2.4. The central value assumes unpolarised (lambda_theta = 0) prompt and non-prompt production, and the spin-alignment envelope spans the range of possible prompt cross-sections under various polarisation hypotheses. The first quoted uncertainty is statistical, the second uncertainty is systematic. Comparison is made to the Colour Evaporation Model prediction.

Unweighted J/psi candidate yields in bins of $J/psi transverse momentum and rapidity. Uncertainties are statistical only.

Summary table of all sources of considered systematic uncertainty and statistical uncertainty (as a percentage) on the corrected inclusive J/psi production cross-section, for absolute J/psi rapidities within 2<|y|<2.4. The sources of systematic error shown are, in order, Acceptance, Muon recognition, Trigger, Fitting and the Total systematics. Also shown in the last error is the possible envelope of variation the central result due to uncertainty on spin-alignment of the J\psi.

Summary table of all sources of considered systematic uncertainty and statistical uncertainty (as a percentage) on the corrected inclusive J/psi production cross-section, for absolute J/psi rapidities within 1.5<|y|<2. The sources of systematic error shown are, in order, Acceptance, Muon recognition, Trigger, Fitting and the Total systematics. Also shown in the last error is the possible envelope of variation the central result due to uncertainty on spin-alignment of the J/psi.

Summary table of all sources of considered systematic uncertainty and statistical uncertainty (as a percentage) on the corrected inclusive J/psi production cross-section, for absolute J/psi rapidities within 0.75<|y|<1.5. The sources of systematic error shown are, in order, Acceptance, Muon recognition, Trigger, Fitting and the Total systematics. Also shown in the last error is the possible envelope of variation the central result due to uncertainty on spin-alignment of the J/psi.

Summary table of all sources of considered systematic uncertainty and statistical uncertainty (as a percentage) on the corrected inclusive J/psi production cross-section, for absolute rapidities within |y|<0.75. The sources of systematic error shown are, in order, Acceptance, Muon recognition, Trigger, Fitting and the Total systematics. Also shown in the last error is the possible envelope of variation the central result due to uncertainty on spin-alignment of the J/psi.

Breakdown of sources of systematic uncertainty on the non-prompt J/psi fraction measurements, for the bin |y|<0.75, as a function of the J/psi pT.

Breakdown of sources of systematic uncertainty on the non-prompt J/psi fraction measurements, for the bin 0.75<|y|<1.5, as a function of the J/psi pT.

Breakdown of sources of systematic uncertainty on the non-prompt J/psi fraction measurements, for the bin 1.75<|y|<2.0, as a function of the J/psi pT.

Breakdown of sources of systematic uncertainty on the non-prompt J/psi fraction measurements, for the bin 2.0<|y|<2.4, as a function of the J/psi pT.

7 TeV Particle density vs. Delta(phi) with leading particle pT > 1 GeV.

7 TeV Particle density vs. Delta(phi) with leading particle pT > 2 GeV.

7 TeV Particle density vs. Delta(phi) with leading particle pT > 3 GeV.

900 GeV Transverse region Particle density vs. leading particle pT.

7 TeV Transverse region Particle density vs. leading particle pT.

900 GeV Transverse region scalar pT sum density vs. leading particle pT.

7 TeV Transverse region scalar pT sum density vs. leading particle pT.