Dependence of $\overline{p}$-$\overline{d}$ correlation on pseudorapidity acceptance of $\overline{p}$ and $\overline{d}$ selection in Pb-Pb collisions at $\sqrt{s_\mathrm{NN}}$ = 5.02 TeV. Results are for 20.0--30.0$\%$ collision centrality.

Dependence of $\overline{p}$-$\overline{d}$ correlation on pseudorapidity acceptance of $\overline{p}$ and $\overline{d}$ selection in Pb-Pb collisions at $\sqrt{s_\mathrm{NN}}$ = 5.02 TeV. Results are for 50.0--60.0$\%$ collision centrality.

Differential excess $e^+e^-$ yield in 70--90\% Pb--Pb collisions at $\sqrt{s_{\rm NN}}$ = 5.02 TeV as a function of $m_{\rm ee}$ for $p_{\rm T,ee} < 0.1$ GeV/$c$. Electrons are measured within $|\eta_{\rm e}| < 0.8$ and $p_{\rm T,e} > 0.2$ GeV/$c$.

Differential $e^+e^-$ yield in 70--90\% Pb--Pb collisions at $\sqrt{s_{\rm NN}}$ = 5.02 TeV as a function of $p_{\rm T,ee}$ for 0.4 $< m_{\rm ee} < 0.7$ GeV/$c^{\rm 2}$. Electrons are measured within $|\eta_{\rm e}| < 0.8$ and $p_{\rm T,e} > 0.2$ GeV/$c$.

Differential $e^+e^-$ yield in 70--90\% Pb--Pb collisions at $\sqrt{s_{\rm NN}}$ = 5.02 TeV as a function of $p_{\rm T,ee}$ for 0.7 $< m_{\rm ee} < 1.1$ GeV/$c^{\rm 2}$. Electrons are measured within $|\eta_{\rm e}| < 0.8$ and $p_{\rm T,e} > 0.2$ GeV/$c$. The quoted upper limits correspond to a 90% confidence level.

Differential $e^+e^-$ yield in 70--90\% Pb--Pb collisions at $\sqrt{s_{\rm NN}}$ = 5.02 TeV as a function of $p_{\rm T,ee}$ for 1.1 $< m_{\rm ee} < 2.7$ GeV/$c^{\rm 2}$. Electrons are measured within $|\eta_{\rm e}| < 0.8$ and $p_{\rm T,e} > 0.2$ GeV/$c$. The quoted upper limits correspond to a 90% confidence level.

Differential excess $e^+e^-$ yield in 70--90\% Pb--Pb collisions at $\sqrt{s_{\rm NN}}$ = 5.02 TeV as a function of $p^{2}_{\rm T,ee}$ for 0.4 $< m_{\rm ee} < 0.7$ GeV/$c^{\rm 2}$. Electrons are measured within $|\eta_{\rm e}| < 0.8$ and $p_{\rm T,e} > 0.2$ GeV/$c$. The quoted upper limits correspond to a 90% confidence level.

Differential excess $e^+e^-$ yield in 70--90\% Pb--Pb collisions at $\sqrt{s_{\rm NN}}$ = 5.02 TeV as a function of $p^{2}_{\rm T,ee}$ for 0.7 $< m_{\rm ee} < 1.1$ GeV/$c^{\rm 2}$. Electrons are measured within $|\eta_{\rm e}| < 0.8$ and $p_{\rm T,e} > 0.2$ GeV/$c$. The quoted upper limits correspond to a 90% confidence level.

Differential excess $e^+e^-$ yield in 70--90\% Pb--Pb collisions at $\sqrt{s_{\rm NN}}$ = 5.02 TeV as a function of $p^{2}_{\rm T,ee}$ for 1.1 $< m_{\rm ee} < 2.7$ GeV/$c^{\rm 2}$. Electrons are measured within $|\eta_{\rm e}| < 0.8$ and $p_{\rm T,e} > 0.2$ GeV/$c$.

Fig. 6b: Number density $N_{\rm ch}$ (left) and $\Sigma p_{\rm T}$ (right) distributions as a function of $p_{\rm T}^{\rm trig}$ in Away and Toward regions after the subtraction of Number density $N_{\rm ch}$ and $\Sigma p_{\rm T}$ distributions in the transverse region for p-Pb collisions for $p_{\rm T} >$ 0.5 GeV/$c$. The shaded areas and the error bars around the data points represent the systematic and statistical uncertainties, respectively.

Fig. 7a: $<p_{\rm T}>$ as a function of $p_{\rm T}^{\rm trig}$ in Toward (left) and Away (right) regions after the subtraction of transverse region for pp collisions for $p_{\rm T} >$ 0.5 GeV/$c$. The shaded areas and the error bars around the data points represent the systematic and statistical uncertainties, respectively.

Fig. 7b: $<p_{\rm T}>$ as a function of $p_{\rm T}^{\rm trig}$ in Toward (left) and Away (right) regions after the subtraction of transverse region for p-Pb collisions for $p_{\rm T} >$ 0.5 GeV/$c$. The shaded areas and the error bars around the data points represent the systematic and statistical uncertainties, respectively.

Fig. A1: Number density $N_{\rm ch}$ (left) and $\Sigma p_{\rm T}$ (right) distributions as a function of $p_{\rm T}^{\rm trig}$ in Transverse, Away, and Toward regions for $p_{\rm T} >$ 0.15 GeV/$c$. The shaded areas and the error bars around the data points represent the systematic and statistical uncertainties, respectively.

Fig. A2: Number density $N_{\rm ch}$ (left) and $\Sigma p_{\rm T}$ (right) distributions as a function of $p_{\rm T}^{\rm trig}$ in Transverse, Away, and Toward regions for $p_{\rm T} >$ 1.0 GeV/$c$. The shaded areas and the error bars around the data points represent the systematic and statistical uncertainties, respectively.

Fig. A3: Number density $N_{\rm ch}$ (left) and $\Sigma p_{\rm T}$ (right) distributions as a function of $p_{\rm T}^{\rm trig}$ in Transverse, Away, and Toward regions for $p_{\rm T} >$ 0.15 GeV/$c$. The shaded areas and the error bars around the data points represent the systematic and statistical uncertainties, respectively.

Fig. A4: Number density $N_{\rm ch}$ (left) and $\Sigma p_{\rm T}$ (right) distributions as a function of $p_{\rm T}^{\rm trig}$ in Transverse, Away, and Toward regions for $p_{\rm T} >$ 1.0 GeV/$c$. The shaded areas and the error bars around the data points represent the systematic and statistical uncertainties, respectively.

Differential cross-section for non-prompt chi_c2 production, measured in bins of J/psi pT, assuming unpolarised chi_c production. The measurements are not corrected for the branching fractions of the decays chi_c --> J/psi + gamma and J/psi --> mu+ mu-. The uncertainty envelope associated with the unknown chi_c spin alignment is also shown.

Differential cross-section for prompt chi_c1 production, measured in bins of chi_c1 pT, assuming unpolarised chi_c production. The measurements are not corrected for the branching fractions of the decays chi_c --> J/psi + gamma and J/psi --> mu+ mu-. The uncertainty envelope associated with the unknown chi_c spin alignment is also shown.

Differential cross-section for prompt chi_c2 production, measured in bins of chi_c2 pT, assuming unpolarised chi_c production. The measurements are not corrected for the branching fractions of the decays chi_c --> J/psi + gamma and J/psi --> mu+ mu-. The uncertainty envelope associated with the unknown chi_c spin alignment is also shown.

Differential cross-section for non-prompt chi_c1 production, measured in bins of chi_c1 pT, assuming unpolarised chi_c production. The measurements are not corrected for the branching fractions of the decays chi_c --> J/psi + gamma and J/psi --> mu+ mu-. The uncertainty envelope associated with the unknown chi_c spin alignment is also shown.

Differential cross-section for non-prompt chi_c2 production, measured in bins of chi_c2 pT, assuming unpolarised chi_c production. The measurements are not corrected for the branching fractions of the decays chi_c --> J/psi + gamma and J/psi --> mu+ mu-. The uncertainty envelope associated with the unknown chi_c spin alignment is also shown.

Fraction of prompt J/psi produced in feed-down from radiative chi_c decays as a function of J/psi pT, assuming unpolarised chi_c production. The uncertainty envelope associated with the unknown chi_c spin alignment is also shown. The spin-alignment envelope assumes that prompt J/psi are produced unpolarised and represents the maximum uncertainty due to the unknown chi_c spin alignment.

Production rate of prompt chi_c2 relative to prompt chi_c1, measured in bins of J/psi pT, assuming unpolarised chi_c production. The ratio is not corrected for the branching fractions of chi_c1 and chi_c2 into J/psi gamma. The uncertainty envelope associated with the unknown chi_c spin alignment is also shown.

Production rate of non-prompt chi_c2 relative to non-prompt chi_c1, measured in bins of J/psi pT, assuming unpolarised chi_c production. The ratio is not corrected for the branching fractions of chi_c1 and chi_c2 into J/psi gamma. The uncertainty envelope associated with the unknown chi_c spin alignment is also shown.

Fraction of chi_c1 produced in b-hadron decays as a function of chi_c1 pT, assuming unpolarised chi_c production. The uncertainty envelope associated with the unknown chi_c spin alignment is also shown.

Fraction of chi_c2 produced in b-hadron decays as a function of chi_c2 pT, assuming unpolarised chi_c production. The uncertainty envelope associated with the unknown chi_c spin alignment is also shown.

Distribution of mT2 for events passing all the signal candidate selection requirements, except that on mT2 of the L100 selection, for DF events.

Distribution of mT2 for events passing all the signal candidate selection requirements, except that on mT2 of the L110 selection, for SF events.

Distribution of mT2 for events passing all the signal candidate selection requirements, except that on mT2 of the L110 selection, for DF events.

Observed 95% CL exclusion contour in the (STOP1, CHARGINO1) mass plane for a fixed value of m(NEUTRALINO1) = 1 GeV.

Expected 95% CL exclusion contour in the (STOP1, CHARGINO1) mass plane for a fixed value of m(NEUTRALINO1) = 1 GeV.

Observed 95% CL exclusion minus 1 sigma contour in the (STOP1, CHARGINO1) mass plane for a fixed value of m(NEUTRALINO1) = 1 GeV.

Observed 95% CL exclusion contour in the (STOP1, NEUTRALINO1) mass plane for a fixed value of m(STOP1) - m(CHARGINO1) = 10 GeV.

Expected 95% CL exclusion contour in the (STOP1, NEUTRALINO1) mass plane for a fixed value of m(STOP1) - m(CHARGINO1) = 10 GeV.

Observed 95% CL exclusion minus 1 sigma contour in the (STOP1, NEUTRALINO1) mass plane for a fixed value of m(STOP1) - m(CHARGINO1) = 10 GeV.

Observed 95% CL exclusion contour in the (CHARGINO1, NEUTRALINO1) mass plane for a fixed value of m(STOP1) = 300 GeV.

Expected 95% CL exclusion contour in the (CHARGINO1, NEUTRALINO1) mass plane for a fixed value of m(STOP1) = 300 GeV.

Observed 95% CL exclusion minus one sigma contour in the (CHARGINO1, NEUTRALINO1) mass plane for a fixed value of m(STOP1) = 300 GeV.

Observed 95% CL exclusion contour in the (STOP1, NEUTRALINO1) mass plane of m(CHARGINO1) = 2 m(NEUTRALINO1).

Expected 95% CL exclusion contour in the (STOP1, NEUTRALINO1) mass plane for m(CHARGINO1) = 2 m(NEUTRALINO1).

Observed 95% CL exclusion minus one sigma contour in the (STOP1, NEUTRALINO1) mass plane for m(CHARGINO1) = 2 m(NEUTRALINO1).

Observed 95% CL exclusion contour in the (STOP1, NEUTRALINO1) mass plane.

Expected 95% CL exclusion contour in the (STOP1, NEUTRALINO1) mass plane.

Observed 95% CL exclusion minus one sigma contour in the (STOP1, NEUTRALINO1) mass plane.

Observed 95% CL exclusion contour in the (STOP1, NEUTRALINO1) mass plane.

Expected 95% CL exclusion contour in the (STOP1, NEUTRALINO1) mass plane.

Observed 95% CL exclusion minus one sigma contour in the (STOP1, NEUTRALINO1) mass plane.

Observed 95% CL exclusion contour in the (STOP1, NEUTRALINO1) mass plane for a fixed value of m(CHARGINO1) = 106 GeV.

Expected 95% CL exclusion contour in the (STOP1, NEUTRALINO1) mass plane for a fixed value of m(CHARGINO1) = 106 GeV.

Observed 95% CL exclusion minus one sigma contour in the (STOP1, NEUTRALINO1) mass plane for a fixed value of m(CHARGINO1) = 106 GeV.

Expected CLs values for Fig. 14.

Observed CLs values for Fig. 14.

Observed cross-section limits for Fig. 14.

Expected CLs values for Fig. 15.

Observed CLs values for Fig. 15.

Observed cross-section limits for Fig. 15.

Expected CLs values for Fig. 16.

Observed CLs values for Fig. 16.

Observed cross-section limits for Fig. 14.

Expected CLs values for Fig. 17.

Observed CLs values for Fig. 17.

Observed cross-section limits for Fig. 17.

Expected CLs values for Fig. 19.

Observed CLs values for Fig. 19.

Observed cross-section limits for Fig. 19.

Number of generated events for Fig. 16.

Acceptance of S1 for Fig. 16.

Efficiency of S1 for Fig. 16.

Total systematic uncertainty IN PCT on signal yields in S1 for Fig. 16.

Acceptance of S2 for Fig. 16.

Efficiency of S2 for Fig. 16.

Total systematic uncertainty IN PCT on signal yields in S2 for Fig. 16.

Acceptance of S3 for Fig. 16.

Efficiency of S3 for Fig. 16.

Total systematic uncertainty IN PCT on signal yields in S3 for Fig. 16.

Acceptance of S4 for Fig. 16.

Efficiency of S4 for Fig. 16.

Total systematic uncertainty IN PCT on signal yields in S4 for Fig. 16.

Acceptance of S5 for Fig. 16.

Efficiency of S5 for Fig. 16.

Total systematic uncertainty IN PCT on signal yields in S5 for Fig. 16.

Acceptance of S6 for Fig. 16.

Efficiency of S6 for Fig. 16.

Total systematic uncertainty IN PCT on signal yields in S6 for Fig. 16.

Acceptance of S7 for Fig. 16.

Efficiency of S7 for Fig. 16.

Total systematic uncertainty IN PCT on signal yields in S7 for Fig. 16.

Acceptance of H160 for Fig. 16.

Efficiency of H160 for Fig. 16.

Total systematic uncertainty IN PCT on signal yields in H160 for Fig. 16.

Observed cross-section limits for Fig. 20.

Observed cross-section limits for Fig. 20.

Expected cross-section limits for Fig. 20.

Total number of generated MC events for each point of the grid.

Observed upper limit on the signal cross-section, in pb, for each point of the grid in the different flavour channel.

Observed upper limit on the signal cross-section, in pb, for each point of the grid in the same flavour channel.

The best expected signal region chosen for each point of the grid in the different flavour channel.

The best expected signal region chosen for each point of the grid in the same flavour channel.

Observed CLs for each point of the grid in the different flavour channel.

Observed CLs for each point of the grid in the same flavour channel.

Expected CLs for each point of the grid in the different flavour channel.

Expected CLs for each point of the grid in the same flavour channel.

Signal acceptance for all the analysis cuts, except the BDTG cut, for each point of the grid in the different flavour channel.

Signal acceptance for all the analysis cuts, except the BDTG cut, for each point of the grid in the same flavour channel.

Signal efficiency, including the acceptance of the BDTG cut, for each point of the grid in the different flavour channel.

Signal efficiency, including the acceptance of the BDTG cut, for each point of the grid in the same flavour channel.

Total signal experimental systematic uncertainty for each point of the grid in the different flavour channel.

Signal efficiency, including the acceptance of the BDTG cut, for each point of the grid in the same flavour channel.

Number of simulated events passing various stages of the selection in the hadronic mT2 analysis for a signal sample with m(STOP1)=300 GeV, m(CHARGINO1) = 150 GeV and m(NEUTRALINO1) = 50 GeV, and with the top squark decaying as STOP1 --> CHARGINO1+ BOTTOM -> W(*)+NEUTRALINO1+ BOTTOM with unit probability. Event weights are applied to correct simulated events to data. "Isolation" includes the effects of tight ID for electrons and the isolation selection for both electrons and muons. "Cleaning cuts" refer to cuts applied to remove non-collision backgrounds and detector noise.

Number of simulated events passing various stages of the selection in the hadronic mT2 analysis for a signal sample with m(STOP1)=250 GeV, m(CHARGINO1) = 106 GeV and m(NEUTRALINO1) = 60 GeV, and with the top squark decaying as STOP1 --> CHARGINO1+ BOTTOM -> W(*)+NEUTRALINO1+ BOTTOM with unit probability. Event weights are applied to correct simulated events to data. "Isolation" includes the effects of tight ID for electrons and the isolation selection for both electrons and muons. "Cleaning cuts" refer to cuts applied to remove non-collision backgrounds and detector noise.

Number of simulated events passing various stages of the selection in the leptonic mT2 analysis for two signal samples with the top squark decaying as STOP1 --> CHARGINO1+ BOTTOM -> W(*)+NEUTRALINO1+BOTTOM with unit probability. Event weights are applied to correct simulated events to data. "Isolation" includes the effects of tight ID for electrons and the isolation selection for both electrons and muons. "Cleaning cuts" refer to cuts applied to remove non-collision backgrounds and detector noise.

Number of simulated events passing various stages of the selection in the leptonic mT2 analysis for a signal sample with m(STOP1)=180 GeV and m(NEUTRALINO1) = 60 GeV, and with the top squark decaying as STOP1 --> W + BOTTOM + NEUTRALINO1 with unit probability. Event weights are applied to correct simulated events to data. "Isolation" includes the effects of tight ID for electrons and the isolation selection for both electrons and muons. "Cleaning cuts" refer to cuts applied to remove non-collision backgrounds and detector noise.

Number of simulated events passing various stages of the selection in the in the MVA analysis for all signal samples used to train the BDTG and with the top squark decaying as STOP1 --> TOP + NEUTRALINO1 with unit probability. Event weights are applied to correct simulated events to data. "Isolation" includes the effects of tight ID for electrons and the isolation selection for both electrons and muons. "Cleaning cuts" refer to cuts applied to remove non-collision backgrounds and detector noise. The index i in category (Ci) is the one reported in table 3 for each signal point, SF and DF.

Expected CLs contour in the GMSB (LAMBDA, TAU(NEUTRALINO) ) signal space.

Expected CLs contour with minus 1-sigma in the GMSB (LAMBDA, TAU(NEUTRALINO) ) signal space.

Expected CLs contour with plus 1-sigma in the GMSB (LAMBDA, TAU(NEUTRALINO) ) signal space.

The total expected and observed limits on SPS8 cross-section [fb] for each signal point.

The total expected and observed limits on number of accepted signal events for each signal point.

The total normalization systematic for each signal point.

Cutflow showing the number of events passing various cuts for the $\Lambda =$ 300 TeV, $\tau =$ 2 ns GMSB SPS8 signal point.

The number of events in the signal region sub-divided into the different bins used in the limit setting procedure for the $\Lambda =$ 300 TeV, $\tau =$ 2 ns GMSB SPS8 signal point. Maximum values of $|t_\gamma| <$ 4 ns and $\Delta z_\gamma<$ 2000 mm have been applied to both photons in the event.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Lower limits at 95% CL on the mass of $H_{\mathrm{L}}^{\pm \pm}$ and $H_{\mathrm{R}}^{\pm \pm}$ bosons, assuming a 100% branching ratio to $e^{\pm}e^{\pm}$, $e^{\pm}/\mu^{\pm}$ and $\mu^{\pm}\mu^{\pm}$ pairs. The $1\sigma$ variations are also shown for the expected limits.

Observed limit on cross section times acceptance for each intrinsic width and mass of Breit-Wigner signal shape tested. The limits in this table correspond to the gg PDF.

Observed limit on cross section times acceptance for each intrinsic width and mass of Breit-Wigner signal shape tested. The limits in this table correspond to the q anti-q PDF.

The transverse momentum, $p_{T}$, dependence of the pixel track (PXT) reconstruction efficiency for three pseudorapidity ranges in 0-10% centrality interval.

The transverse momentum, $p_{T}$, dependence of the pixel track (PXT) reconstruction efficiency for three pseudorapidity ranges in 40-50% centrality interval.

The transverse momentum, $p_{T}$, dependence of the pixel track (PXT) reconstruction efficiency for three pseudorapidity ranges in 70-80% centrality interval.

The transverse momentum, $p_{T}$, dependence of the pixel track (PXT) reconstruction fake rate for three pseudorapidity ranges in 0-10% centrality interval.

The transverse momentum, $p_{T}$, dependence of the pixel track (PXT) reconstruction fake rate for three pseudorapidity ranges in 40-50% centrality interval.

The transverse momentum, $p_{T}$, dependence of the pixel track (PXT) reconstruction fake rate for three pseudorapidity ranges in 70-80% centrality interval.

The transverse momentum, $p_{T}$, dependence of the inner detector track (IDT) reconstruction efficiency for three pseudorapidity ranges in 0-10% centrality interval.

The transverse momentum, $p_{T}$, dependence of the inner detector track (IDT) reconstruction efficiency for three pseudorapidity ranges in 40-50% centrality interval.

The transverse momentum, $p_{T}$, dependence of the inner detector track (IDT) reconstruction efficiency for three pseudorapidity ranges in 70-80% centrality interval.

The transverse momentum, $p_{T}$, dependence of the inner detector track (IDT) reconstruction fake rate for three pseudorapidity ranges in 0-10% centrality interval.

The transverse momentum, $p_{T}$, dependence of the inner detector track (IDT) reconstruction fake rate for three pseudorapidity ranges in 40-50% centrality interval.

The transverse momentum, $p_{T}$, dependence of the inner detector track (IDT) reconstruction fake rate for three pseudorapidity ranges in 70-80% centrality interval.

Elliptic flow $v_{2}$ integrated over transverse momentum $p_{T}>p_{T,0}$ as a function of $p_{T,0}$ for 0-10% centrality interval, obtained with different charged-particle reconstruction methods: the tracklet (TKT) method with $p_{T,0}=0.07$ GeV, the pixel track (PXT) method with $p_{T,0} \geq 0.1$ GeV and the ID track (IDT) method with $p_{T,0}=0.5$ GeV. Error bars indicate statistical and systematic uncertainties added in quadrature.

Elliptic flow $v_{2}$ integrated over transverse momentum $p_{T}>p_{T,0}$ as a function of $p_{T,0}$ for 10-20% centrality interval, obtained with different charged-particle reconstruction methods: the tracklet (TKT) method with $p_{T,0}=0.07$ GeV, the pixel track (PXT) method with $p_{T,0} \geq 0.1$ GeV and the ID track (IDT) method with $p_{T,0}=0.5$ GeV. Error bars indicate statistical and systematic uncertainties added in quadrature.

Elliptic flow $v_{2}$ integrated over transverse momentum $p_{T}>p_{T,0}$ as a function of $p_{T,0}$ for 20-30% centrality interval, obtained with different charged-particle reconstruction methods: the tracklet (TKT) method with $p_{T,0}=0.07$ GeV, the pixel track (PXT) method with $p_{T,0} \geq 0.1$ GeV and the ID track (IDT) method with $p_{T,0}=0.5$ GeV. Error bars indicate statistical and systematic uncertainties added in quadrature.

Elliptic flow $v_{2}$ integrated over transverse momentum $p_{T}>p_{T,0}$ as a function of $p_{T,0}$ for 30-40% centrality interval, obtained with different charged-particle reconstruction methods: the tracklet (TKT) method with $p_{T,0}=0.07$ GeV, the pixel track (PXT) method with $p_{T,0} \geq 0.1$ GeV and the ID track (IDT) method with $p_{T,0}=0.5$ GeV. Error bars indicate statistical and systematic uncertainties added in quadrature.

Elliptic flow $v_{2}$ integrated over transverse momentum $p_{T}>p_{T,0}$ as a function of $p_{T,0}$ for 40-50% centrality interval, obtained with different charged-particle reconstruction methods: the tracklet (TKT) method with $p_{T,0}=0.07$ GeV, the pixel track (PXT) method with $p_{T,0} \geq 0.1$ GeV and the ID track (IDT) method with $p_{T,0}=0.5$ GeV. Error bars indicate statistical and systematic uncertainties added in quadrature.

Elliptic flow $v_{2}$ integrated over transverse momentum $p_{T}>p_{T,0}$ as a function of $p_{T,0}$ for 50-60% centrality interval, obtained with different charged-particle reconstruction methods: the tracklet (TKT) method with $p_{T,0}=0.07$ GeV, the pixel track (PXT) method with $p_{T,0} \geq 0.1$ GeV and the ID track (IDT) method with $p_{T,0}=0.5$ GeV. Error bars indicate statistical and systematic uncertainties added in quadrature.

Elliptic flow $v_{2}$ integrated over transverse momentum $p_{T}>p_{T,0}$ as a function of $p_{T,0}$ for 60-70% centrality interval, obtained with different charged-particle reconstruction methods: the tracklet (TKT) method with $p_{T,0}=0.07$ GeV, the pixel track (PXT) method with $p_{T,0} \geq 0.1$ GeV and the ID track (IDT) method with $p_{T,0}=0.5$ GeV. Error bars indicate statistical and systematic uncertainties added in quadrature.

Elliptic flow $v_{2}$ integrated over transverse momentum $p_{T}>p_{T,0}$ as a function of $p_{T,0}$ for 70-80% centrality interval, obtained with different charged-particle reconstruction methods: the tracklet (TKT) method with $p_{T,0}=0.07$ GeV, the pixel track (PXT) method with $p_{T,0} \geq 0.1$ GeV and the ID track (IDT) method with $p_{T,0}=0.5$ GeV. Error bars indicate statistical and systematic uncertainties added in quadrature.

Pseudorapidity dependence of elliptic flow, $v_{2}$, integrated over transverse momentum, $p_{T}$, for different charged particle reconstruction methods and different low-$p_{T}$ thresholds for the 0-10% centrality interval. Error bars indicate statistical and systematic uncertainties added in quadrature.

Pseudorapidity dependence of elliptic flow, $v_{2}$, integrated over transverse momentum, $p_{T}$, for different charged particle reconstruction methods and different low-$p_{T}$ thresholds for the 10-20% centrality interval. Error bars indicate statistical and systematic uncertainties added in quadrature.

Pseudorapidity dependence of elliptic flow, $v_{2}$, integrated over transverse momentum, $p_{T}$, for different charged particle reconstruction methods and different low-$p_{T}$ thresholds for the 20-30% centrality interval. Error bars indicate statistical and systematic uncertainties added in quadrature.

Pseudorapidity dependence of elliptic flow, $v_{2}$, integrated over transverse momentum, $p_{T}$, for different charged particle reconstruction methods and different low-$p_{T}$ thresholds for the 30-40% centrality interval. Error bars indicate statistical and systematic uncertainties added in quadrature.

Pseudorapidity dependence of elliptic flow, $v_{2}$, integrated over transverse momentum, $p_{T}$, for different charged particle reconstruction methods and different low-$p_{T}$ thresholds for the 40-50% centrality interval. Error bars indicate statistical and systematic uncertainties added in quadrature.

Pseudorapidity dependence of elliptic flow, $v_{2}$, integrated over transverse momentum, $p_{T}$, for different charged particle reconstruction methods and different low-$p_{T}$ thresholds for the 50-60% centrality interval. Error bars indicate statistical and systematic uncertainties added in quadrature.

Pseudorapidity dependence of elliptic flow, $v_{2}$, integrated over transverse momentum, $p_{T}$, for different charged particle reconstruction methods and different low-$p_{T}$ thresholds for the 60-70% centrality interval. Error bars indicate statistical and systematic uncertainties added in quadrature.

Pseudorapidity dependence of elliptic flow, $v_{2}$, integrated over transverse momentum, $p_{T}$, for different charged particle reconstruction methods and different low-$p_{T}$ thresholds for the 70-80% centrality interval. Error bars indicate statistical and systematic uncertainties added in quadrature.

Integrated elliptic flow, $v_{2}$, as a function of $|\eta| - y_{beam}$ for three centrality intervals Error bars indicate statistical and systematic uncertainties added in quadrature.

The transverse momentum, $p_{T}$, dependence of the TKT track reconstruction efficiency for $\pi^{\pm}$, $K^{\pm}$ and $p^{\pm}$ in the pseudorapidity range $|\eta| < 1$ for 0-10% centrality interval.

The transverse momentum, $p_{T}$, dependence of the TKT track reconstruction efficiency for $\pi^{\pm}$, $K^{\pm}$ and $p^{\pm}$ in the pseudorapidity range $|\eta| < 1$ for 40-50% centrality interval.

The transverse momentum, $p_{T}$, dependence of the TKT track reconstruction efficiency for $\pi^{\pm}$, $K^{\pm}$ and $p^{\pm}$ in the pseudorapidity range $|\eta| < 1$ for 70-80% centrality interval.

The transverse momentum, $p_{T}$, dependence of the PXT track reconstruction efficiency for $\pi^{\pm}$, $K^{\pm}$ and $p^{\pm}$ in the pseudorapidity range $|\eta| < 1$ for 0-10% centrality interval.

The transverse momentum, $p_{T}$, dependence of the PXT track reconstruction efficiency for $\pi^{\pm}$, $K^{\pm}$ and $p^{\pm}$ in the pseudorapidity range $|\eta| < 1$ for 40-50% centrality interval.

The transverse momentum, $p_{T}$, dependence of the PXT track reconstruction efficiency for $\pi^{\pm}$, $K^{\pm}$ and $p^{\pm}$ in the pseudorapidity range $|\eta| < 1$ for 70-80% centrality interval.

Distribution of ETmiss in the signal region for data and for the background predicted from the fit in the CRs. Overflows are included in the final bin.

Limits at 90% C.L. on the EFT suppression scale M* as a function of the WIMP mass m_chi, for the vector operator D5. Results where EFT truncation is applied are also shown, assuming coupling values sqrt(g_f g_chi)= 1, 4pi.

Limits at 90% C.L. on the EFT suppression scale M* as a function of the WIMP mass m_chi, for the axial-vector operator D8. Results where EFT truncation is applied are also shown, assuming coupling values sqrt(g_f g_chi)= 1, 4pi.

Limits at 90% C.L. on the EFT suppression scale M* as a function of the WIMP mass m_chi, for the tensor operator D9. Results where EFT truncation is applied are also shown, assuming coupling values sqrt(g_f g_chi)= 1, 4pi.

Upper limits at 90% C.L. on the WIMP-nucleon scattering cross section as a function of m_chi for spin-independent and spin-dependent interactions, for a coupling strength g = sqrt(g_f g_chi) of unity or the maximum value (4 pi) that keeps the model within its perturbative regime. The truncation procedure is applied for both cases.

Upper limits at 95% C.L. on the WIMP simplified model coupling parameter, sqrt(g_f g_chi), with vector coupling and mediator width Gamma=m_V/3, as a function of WIMP (m_chi) and the mediator particle (m_V) masses.

Observed lower limits at 95% C.L. on the EFT suppression scale M* as a function of the mediator mass mV, for a Z'-like mediator with vector interactions. For a dark-matter mass m_chi of 50 or 400 GeV, results are shown for different values of the mediator total decay width Gamma.

Observed lower limits at 95% C.L. on the EFT suppression scale M* as a function of the mediator mass mV, for a Z'-like mediator with axial-vector interactions. For a dark-matter mass m_chi of 50 or 400 GeV, results are shown for different values of the mediator total decay width Gamma.

Limits at 95% C.L. on the effective mass scale M* in the (k2, k1) parameter plane for the s-channel EFT model inspired by Fermi-LAT gamma-ray line, for m_chi = 130 GeV. The upper part of the plane is excluded.

Lower limits at 95% C.L. on the mass scale M_D in the ADD models of large extra dimensions, for several values of the number of extra dimensions.

Upper limits at 95% C.L. on the cross section for the compressed squark model, as a function of the squark mass, m_squark, and of the difference between the squark mass and the mass of the neutralino, m_squark-m_neutralino, in the compressed region of m_squark-m_neutralino < 50 GeV.

Number of data events (20.3 fb$^{-1}$), number of predicted events from the fit, statistical uncertainty on the fit, systematic uncertainty on the choice of control region, and on the choice of fit function versus inclusive $H_{\textrm{T}}^{\textrm{min}}$ lower bin edge for inclusive jet multiplicity $N_{\textrm{Jet}} \geq 6$. The total uncertainty is obtained by adding the three uncertainties linearly.

Number of data events (20.3 fb$^{-1}$), number of predicted events from the fit, statistical uncertainty on the fit, systematic uncertainty on the choice of control region, and on the choice of fit function versus inclusive $H_{\textrm{T}}^{\textrm{min}}$ lower bin edge for inclusive jet multiplicity $N_{\textrm{Jet}} \geq 7$. The total uncertainty is obtained by adding the three uncertainties linearly.

Number of data events (20.3 fb$^{-1}$), number of predicted events from the fit, statistical uncertainty on the fit, systematic uncertainty on the choice of control region, and on the choice of fit function versus inclusive $H_{\textrm{T}}^{\textrm{min}}$ lower bin edge for inclusive jet multiplicity $N_{\textrm{Jet}} \geq 8$. The total uncertainty is obtained by adding the three uncertainties linearly.

Upper limits on the visible cross section (cross section ($\sigma$) times acceptance ($A$) times efficiency ($\epsilon$)) at the 95% CL versus inclusive $H_{\textrm{T}}^{\textrm{min}}$ for $N_{\textrm{Jet}}\geq 3$.

Upper limits on the visible cross section (cross section ($\sigma$) times acceptance ($A$) times efficiency ($\epsilon$)) at the 95% CL versus inclusive $H_{\textrm{T}}^{\textrm{min}}$ for $N_{\textrm{Jet}}\geq 4$.

Upper limits on the visible cross section (cross section ($\sigma$) times acceptance ($A$) times efficiency ($\epsilon$)) at the 95% CL versus inclusive $H_{\textrm{T}}^{\textrm{min}}$ for $N_{\textrm{Jet}}\geq 5$.

Upper limits on the visible cross section (cross section ($\sigma$) times acceptance ($A$) times efficiency ($\epsilon$)) at the 95% CL versus inclusive $H_{\textrm{T}}^{\textrm{min}}$ for $N_{\textrm{Jet}}\geq 6$.

Upper limits on the visible cross section (cross section ($\sigma$) times acceptance ($A$) times efficiency ($\epsilon$)) at the 95% CL versus inclusive $H_{\textrm{T}}^{\textrm{min}}$ for $N_{\textrm{Jet}}\geq 7$.

Upper limits on the visible cross section (cross section ($\sigma$) times acceptance ($A$) times efficiency ($\epsilon$)) at the 95% CL versus inclusive $H_{\textrm{T}}^{\textrm{min}}$ for $N_{\textrm{Jet}}\geq 8$.

Mean reconstruction efficiencies $(\epsilon)$ and RMS of the reconstruction efficiencies for various black hole and string ball models.

Observed 90% C.L. lower limits on the mass scale, M*, of considered effective field theories as a function of mChi. For each operator, the values below the corresponding line are excluded.

Expected 95% C.L. upper limits on the cross section times branching fraction as a function of mChi. For each operator, the values above the corresponding line are excluded.

Observed 95% C.L. upper limits on the cross section times branching fraction as a function of mChi. For each operator, the values above the corresponding line are excluded.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

mjj region 1600 - 2000 GeV. The observed systematic is the experimental uncertainty, while the SM prediction systematic is the theoretical uncertainty.

mjj region 2000 - 2600 GeV. The observed systematic is the experimental uncertainty, while the SM prediction systematic is the theoretical uncertainty.

mjj region 2600 - 3200 GeV. The observed systematic is the experimental uncertainty, while the SM prediction systematic is the theoretical uncertainty.

mjj region 3200 - 8000 GeV. The observed systematic is the experimental uncertainty, while the SM prediction systematic is the theoretical uncertainty.

Mean number of jets in rapidity interval as a function of leading dijet scalar mean pT in GeV.

First azimuthal angular moment as a function of leading dijet rapidity separation.

First azimuthal angular moment as a function of leading dijet scalar mean pT in GeV.

Ratio of second azimuthal angular moment to first as a function of leading dijet rapidity separation.

Ratio of second azimuthal angular moment to first as a function of leading dijet scalar mean pT in GeV.

First azimuthal angular moment as a function of leading dijet rapidity separation.

First azimuthal angular moment as a function of leading dijet scalar mean pT in GeV.

Ratio of second azimuthal angular moment to first as a function of leading dijet rapidity separation.

Ratio of second azimuthal angular moment to first as a function of leading dijet scalar mean pT in GeV.

Differential cross section as a function of dijet azimuthal separation for events satisfying 0 < dijet rapidity separation <= 1.

Differential cross section as a function of dijet azimuthal separation for events satisfying 1 < dijet rapidity separation <= 2.

Differential cross section as a function of dijet azimuthal separation for events satisfying 2 < dijet rapidity separation <= 3.

Differential cross section as a function of dijet azimuthal separation for events satisfying 3 < dijet rapidity separation <= 4.

Differential cross section as a function of dijet azimuthal separation for events satisfying 4 < dijet rapidity separation <= 5.

Differential cross section as a function of dijet azimuthal separation for events satisfying 5 < dijet rapidity separation <= 6.

Differential cross section as a function of dijet azimuthal separation for events satisfying 6 < dijet rapidity separation <= 7.

Differential cross section as a function of dijet azimuthal separation for events satisfying 7 < dijet rapidity separation <= 8.

Differential cross section as a function of dijet azimuthal separation for events satisfying 0 < dijet rapidity separation <= 1.

Differential cross section as a function of dijet azimuthal separation for events satisfying 1 < dijet rapidity separation <= 2.

Differential cross section as a function of dijet azimuthal separation for events satisfying 2 < dijet rapidity separation <= 3.

Differential cross section as a function of dijet azimuthal separation for events satisfying 3 < dijet rapidity separation <= 4.

Differential cross section as a function of dijet azimuthal separation for events satisfying 4 < dijet rapidity separation <= 5.

Differential cross section as a function of dijet azimuthal separation for events satisfying 5 < dijet rapidity separation <= 6.

Differential cross section as a function of dijet azimuthal separation for events satisfying 6 < dijet rapidity separation <= 7.

Differential cross section as a function of dijet azimuthal separation for events satisfying 7 < dijet rapidity separation <= 8.

Gap fraction as a function of veto scale in GeV for events satisfying 0 < dijet rapidity separation <= 1.

Gap fraction as a function of veto scale in GeV for events satisfying 1 < dijet rapidity separation <= 2.

Gap fraction as a function of veto scale in GeV for events satisfying 2 < dijet rapidity separation <= 3.

Gap fraction as a function of veto scale in GeV for events satisfying 3 < dijet rapidity separation <= 4.

Gap fraction as a function of veto scale in GeV for events satisfying 4 < dijet rapidity separation <= 5.

Gap fraction as a function of veto scale in GeV for events satisfying 5 < dijet rapidity separation <= 6.

Gap fraction as a function of veto scale in GeV for events satisfying 6 < dijet rapidity separation <= 7.

Gap fraction as a function of veto scale in GeV for events satisfying 7 < dijet rapidity separation <= 8.

Second azimuthal angular moment as a function of leading dijet rapidity separation.

Second azimuthal angular moment as a function of leading dijet scalar mean pT in GeV.

Second azimuthal angular moment as a function of leading dijet rapidity separation.

Second azimuthal angular moment as a function of leading dijet scalar mean pT in GeV.

The measured leading jet $p_T$ distribution in the $W \rightarrow \mu \nu$ control region, for the M1 selection, compared to the background predictions. The latter include the global normalization factors extracted from the fit.

The measured $E_T^{miss}$ distribution in the $W \rightarrow e \nu$ control region, for the M1 selection, compared to the background predictions. The latter include the global normalization factors extracted from the fit.

The measured leading jet $p_T$ distribution in the $W \rightarrow e \nu$ control region, for the M1 selection, compared to the background predictions. The latter include the global normalization factors extracted from the fit.

The measured $E_T^{miss}$ distribution in the $Z \rightarrow \mu \mu$ control region, for the M1 selection, compared to the background predictions. The latter include the global normalization factors extracted from the fit.

The measured leading jet $p_T$ distribution in the $Z \rightarrow \mu \mu$ control region, for the M1 selection, compared to the background predictions. The latter include the global normalization factors extracted from the fit.

The measured $E_T^{miss}$ distribution in the $W\rightarrow \mu \nu$ control region, for the c-tagged selection, compared to the background predictions. The latter include the global normalization factors extracted from the fit.

The measured leading jet $p_T$ distribution in the $W\rightarrow \mu \nu$ control region, for the c-tagged selection, compared to the background predictions. The latter include the global normalization factors extracted from the fit.

The measured $E_T^{miss}$ distribution in the $W\rightarrow e \nu$ control region, for the c-tagged selection, compared to the background predictions. The latter include the global normalization factors extracted from the fit.

The measured leading jet $p_T$ distribution in the $W\rightarrow e \nu$ control region, for the c-tagged selection, compared to the background predictions. The latter include the global normalization factors extracted from the fit.

The measured $E_T^{miss}$ distribution in the $Z\rightarrow ll$ control region, for the c-tagged selection, compared to the background predictions. The latter include the global normalization factors extracted from the fit.

The measured leading jet $p_T$ distribution in the $Z\rightarrow ll$ control region, for the c-tagged selection, compared to the background predictions. The latter include the global normalization factors extracted from the fit.

The measured $E_T^{miss}$ distribution in the t-(anti)-t control region, for the c-tagged selection, compared to the background predictions. The latter include the global normalization factors extracted from the fit.

The measured leading jet $p_T$ distribution in the t-(anti)-t control region, for the c-tagged selection, compared to the background predictions. The latter include the global normalization factors extracted from the fit.

Measured leading jet $p_T$ distribution for the V3 selections compared to the SM predictions.

Measured $E_T^{miss}$ distribution for the V4 selections compared to the SM predictions.

Measured leading jet $p_T$ distribution for the V5 selections compared to the SM predictions.

Measured $E_T^{miss}$ distribution for the V5 selections compared to the SM predictions.

Measured $E_T^{miss}$ distribution for the M1 selection compared to the SM predictions. For illustration purposes, the distribution of two different SUSY scenarios are included.

Measured leading jet $p_T$ distribution for the M1 selection compared to the SM predictions. For illustration purposes, the distribution of two different SUSY scenarios are included.

Measured $E_T^{miss}$ distribution for the M2 selection compared to the SM predictions. For illustration purposes, the distribution of two different SUSY scenarios are included.

Measured leading jet $p_T$ distribution for the M2 selection compared to the SM predictions. For illustration purposes, the distribution of two different SUSY scenarios are included.

Measured $E_T^{miss}$ distribution for the M3 selection compared to the SM predictions. For illustration purposes, the distribution of two different SUSY scenarios are included.

Measured leading jet $p_T$ distribution for the M3 selection compared to the SM predictions. For illustration purposes, the distribution of two different SUSY scenarios are included.

Measured $E_T^{miss}$ distribution for the C1 selection before the cut in the variable shown is applied. The data are compared to the SM predictions. For illustration purposes, the distribution of two different SUSY scenarios are included.

Measured leading jet $p_T$ distribution for the C1 selection before the cut in the variable shown is applied. The data are compared to the SM predictions. For illustration purposes, the distribution of two different SUSY scenarios are included.

Measured leading jet $p_T$ for the C2 selection. The data are compared to the SM predictions. For illustration purposes, the distribution of two different SUSY scenarios are included.

Measured jet multiplicity for the C2 selection. The data are compared to the SM predictions. For illustration purposes, the distribution of two different SUSY scenarios are included.

The measured $W$ transverse mass distribution in the $W \rightarrow \mu \nu$ control region for the M1 monojet-like selection, compared to the background predictions. The latter include the global normalization factors extracted from the fit.

The measured $W$ transverse mass distribution in the $W \rightarrow e \nu$ control region for the M1 monojet-like selection, compared to the background predictions. The latter include the global normalization factors extracted from the fit.

The measured dimuon invariant mass distribution in the $Z \rightarrow \mu \mu$ control region for the M1 monojet-like selection, compared to the background predictions. The latter include the global normalization factors extracted from the fit.

The measured $E_T^{miss}$ distribution in a multijet control sample for the monojet-like analysis. This region is defined with similar $E_T^{miss}$ and leading jet $p_T$ cuts as M1, but releasing the jet-veto and inverting the $\Delta \phi (jet, p_T^{miss})$ cut, now requiring it to be less than 0.4. The data are compared to predictions.

Measured jet multiplicity in the $W \rightarrow e \nu$ control region for the c-tagged analysis, compared to background predictions. The latter include the global normalization factors extracted from the fit.

Measured jet multiplicity in the $W \rightarrow \mu \nu$ control region for the c-tagged analysis, compared to background predictions. The latter include the global normalization factors extracted from the fit.

Measured jet multiplicity in the $Z \rightarrow ll$ control region for the c-tagged analysis, compared to background predictions. The latter include the global normalization factors extracted from the fit.

Measured jet multiplicity in the t-(anti)-t control region for the c-tagged analysis, compared to background predictions. The latter include the global normalization factors extracted from the fit.

Measured dilepton invariant mass in the $Z \rightarrow ll$ control region for the c-tagged analysis. The predictions include the global normalization factors extracted from the fit.

Measured jet multiplicity distribution for the M1 selection compared to the SM predictions. For illustration purposes, the impact of two different SUSY scenarios are included.

Measured leading jet $\eta$ distribution for the M1 selection compared to the SM predictions. For illustration purposes, the impact of two different SUSY scenarios are included.

Measured $\Delta \phi (jet, p_T^{miss})$ distribution for the M1 selection compared to the SM predictions. For illustration purposes, the impact of two different SUSY scenarios are included.

Measured $E_T^{miss}$ distribution after preselection cuts compared to background predictions.

Measured jet multiplicity distribution in the C1 c-tagged selection compared to background predictions.

Multiplicity of jets with loose heavy-flavor tags in the C1 selection.

Multiplicity of jets with medium heavy-flavor tags in the C1 selection.

Expected and observed CLs, number of events, acceptance and efficiency for M1 SR for $\tilde{t}_1 \rightarrow c + \tilde{\chi}^0_1$. The expected event yield in 20.3 fb$^{-1}$, $N_{\text{events}}$, is used to calculate $\sigma\times A\times\varepsilon$ and $A\times\varepsilon$. The acceptance $A$ is defined as the percentage of events passing the selection at truth level, and the efficiency $\varepsilon$ is the ratio of events passing the selection at reconstructed level over the number of events passing the selection at truth level. The modified efficiency $\varepsilon\prime$ is the ratio of events passing the selection at truth and reconstructed level over the number of events passing the selection at truth level.

Expected and observed CLs, number of events, acceptance and efficiency for M2 SR for $\tilde{t}_1 \rightarrow c + \tilde{\chi}^0_1$. The expected event yield in 20.3 fb$^{-1}$, $N_{\text{events}}$, is used to calculate $\sigma\times A\times\varepsilon$ and $A\times\varepsilon$. The acceptance $A$ is defined as the percentage of events passing the selection at truth level, and the efficiency $\varepsilon$ is the ratio of events passing the selection at reconstructed level over the number of events passing the selection at truth level. The modified efficiency $\varepsilon\prime$ is the ratio of events passing the selection at truth and reconstructed level over the number of events passing the selection at truth level.

Expected and observed CLs, number of events, acceptance and efficiency for M3 SR for $\tilde{t}_1 \rightarrow c + \tilde{\chi}^0_1$. The expected event yield in 20.3 fb$^{-1}$, $N_{\text{events}}$, is used to calculate $\sigma\times A\times\varepsilon$ and $A\times\varepsilon$. The acceptance $A$ is defined as the percentage of events passing the selection at truth level, and the efficiency $\varepsilon$ is the ratio of events passing the selection at reconstructed level over the number of events passing the selection at truth level. The modified efficiency $\varepsilon\prime$ is the ratio of events passing the selection at truth and reconstructed level over the number of events passing the selection at truth level.

Expected and observed CLs, number of events, acceptance and efficiency for C1 SR for $\tilde{t}_1 \rightarrow c + \tilde{\chi}^0_1$. The expected event yield in 20.3 fb$^{-1}$, $N_{\text{events}}$, is used to calculate $\sigma\times A\times\varepsilon$ and $A\times\varepsilon$. The acceptance $A$ is defined as the percentage of events passing the selection at truth level, and the efficiency $\varepsilon$ is the ratio of events passing the selection at reconstructed level over the number of events passing the selection at truth level.

Expected and observed CLs, number of events, acceptance and efficiency for C2 SR for $\tilde{t}_1 \rightarrow c + \tilde{\chi}^0_1$. The expected event yield in 20.3 fb$^{-1}$, $N_{\text{events}}$, is used to calculate $\sigma\times A\times\varepsilon$ and $A\times\varepsilon$. The acceptance $A$ is defined as the percentage of events passing the selection at truth level, and the efficiency $\varepsilon$ is the ratio of events passing the selection at reconstructed level over the number of events passing the selection at truth level.

Expected and observed CLs, number of events, acceptance and efficiency for M1 SR for $\tilde{b}_1 \rightarrow b + \tilde{\chi}^0_1$. The expected event yield in 20.3 fb$^{-1}$, $N_{\text{events}}$, is used to calculate $\sigma\times A\times\varepsilon$ and $A\times\varepsilon$. The acceptance $A$ is defined as the percentage of events passing the selection at truth level, and the efficiency $\varepsilon$ is the ratio of events passing the selection at reconstructed level over the number of events passing the selection at truth level. The modified efficiency $\varepsilon\prime$ is the ratio of events passing the selection at truth and reconstructed level over the number of events passing the selection at truth level.

Expected and observed CLs, number of events, acceptance and efficiency for M2 SR for $\tilde{b}_1 \rightarrow b + \tilde{\chi}^0_1$. The expected event yield in 20.3 fb$^{-1}$, $N_{\text{events}}$, is used to calculate $\sigma\times A\times\varepsilon$ and $A\times\varepsilon$. The acceptance $A$ is defined as the percentage of events passing the selection at truth level, and the efficiency $\varepsilon$ is the ratio of events passing the selection at reconstructed level over the number of events passing the selection at truth level. The modified efficiency $\varepsilon\prime$ is the ratio of events passing the selection at truth and reconstructed level over the number of events passing the selection at truth level.

Expected and observed CLs, number of events, acceptance and efficiency for M3 SR for $\tilde{b}_1 \rightarrow b + \tilde{\chi}^0_1$. The expected event yield in 20.3 fb$^{-1}$, $N_{\text{events}}$, is used to calculate $\sigma\times A\times\varepsilon$ and $A\times\varepsilon$. The acceptance $A$ is defined as the percentage of events passing the selection at truth level, and the efficiency $\varepsilon$ is the ratio of events passing the selection at reconstructed level over the number of events passing the selection at truth level. The modified efficiency $\varepsilon\prime$ is the ratio of events passing the selection at truth and reconstructed level over the number of events passing the selection at truth level.

Expected and observed CLs, number of events, acceptance and efficiency for M1 SR for $\tilde{t}_1 \rightarrow b + ff' + \tilde{\chi}^0_1$. The expected event yield in 20.3 fb$^{-1}$, $N_{\text{events}}$, is used to calculate $\sigma\times A\times\varepsilon$ and $A\times\varepsilon$. The acceptance $A$ is defined as the percentage of events passing the selection at truth level, and the efficiency $\varepsilon$ is the ratio of events passing the selection at reconstructed level over the number of events passing the selection at truth level. The modified efficiency $\varepsilon\prime$ is the ratio of events passing the selection at truth and reconstructed level over the number of events passing the selection at truth level.

Expected and observed CLs, number of events, acceptance and efficiency for M2 SR for $\tilde{t}_1 \rightarrow b + ff' + \tilde{\chi}^0_1$. The expected event yield in 20.3 fb$^{-1}$, $N_{\text{events}}$, is used to calculate $\sigma\times A\times\varepsilon$ and $A\times\varepsilon$. The acceptance $A$ is defined as the percentage of events passing the selection at truth level, and the efficiency $\varepsilon$ is the ratio of events passing the selection at reconstructed level over the number of events passing the selection at truth level. The modified efficiency $\varepsilon\prime$ is the ratio of events passing the selection at truth and reconstructed level over the number of events passing the selection at truth level.

Expected and observed CLs, number of events, acceptance and efficiency for M3 SR for $\tilde{t}_1 \rightarrow b + ff' + \tilde{\chi}^0_1$. The expected event yield in 20.3 fb$^{-1}$, $N_{\text{events}}$, is used to calculate $\sigma\times A\times\varepsilon$ and $A\times\varepsilon$. The acceptance $A$ is defined as the percentage of events passing the selection at truth level, and the efficiency $\varepsilon$ is the ratio of events passing the selection at reconstructed level over the number of events passing the selection at truth level. The modified efficiency $\varepsilon\prime$ is the ratio of events passing the selection at truth and reconstructed level over the number of events passing the selection at truth level.

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Observed 95% CL exclusion contour.

Expected 95% CL exclusion contour.

Observed 95% CL exclusion contour.

Expected 95% CL exclusion contour.

Observed 95% CL exclusion contour.

Expected 95% CL exclusion contour.

Observed 95% CL exclusion contour.

Expected 95% CL exclusion contour.

Observed 95% CL exclusion contour.

Expected 95% CL exclusion contour.

Observed 95% CL exclusion contour.

Expected 95% CL exclusion contour.

Observed 95% CL exclusion contour.

Expected 95% CL exclusion contour.

Observed 95% CL exclusion contour.

Expected 95% CL exclusion contour.

Observed 95% CL exclusion contour.

Expected 95% CL exclusion contour.

95% CL upper limits on the cross section [fb].

Number of signal events.

Acceptance [%].

Efficiency [%].

Experimental uncertainty.

Expected CLs.

Observed CLs.

Best signal region.

Observed 95% CL exclusion contour.

Expected 95% CL exclusion contour.

95% CL upper limits on the cross section [fb].

Observed 95% CL exclusion contour.

Expected 95% CL exclusion contour.

95% CL upper limits on the cross section [fb].

Number of signal events.

Acceptance [%].

Efficiency [%].

Uncertainty [%].

Expected CLs.

Observed CLs.

Best signal region.

Best signal region.