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.

Normalized differential cross-sections for the absolute rapidity (|y|) of the ttbar system. The cross-section in each bin is given as the integral of the normalized differential cross-section over the bin width, divided by the bin width. The calculation of the cross-sections in the last bins includes events falling outside of the bin edges, and the normalization is done within the quoted bin width. The full covariance matrice is provided in Table 8 below.

Bin-wise full covariance matrices for the normalized differential cross-sections of the hadronically decaying top-quark PT. The elements of the covariance matrices are in units of TeV$^{-2}$.

Bin-wise full covariance matrices for the normalized differential cross-sections of the mass of the ttbar system. The elements of the covariance matrices are in units of TeV$^{-2}$.

Bin-wise full covariance matrices for the normalized differential cross-sections of the PT of the ttbar system. The elements of the covariance matrices are in units of TeV$^{-2}$.

Bin-wise full covariance matrices for the normalized differential cross-sections of the absolute rapidity (|y|) of the ttbar system.

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.