Observed and expected 95% CL upper limits on the total cross-section σ($pp$ → $T$ → $Ht/Zt$) as a function of $T$-quark mass in the SU(2) doublet representation assuming $\kappa$=0.5. The expected limits for the individual analyses are shown. The $HtZt$ analysis is only included in the limit calculation for $m_{\mathrm{T}}$ < 2.1 TeV.

Observed 95% CL exclusion limits on the total cross-section σ($pp$ → $T$ → $Ht/Zt$) as a function of the universal coupling constant and the $T$-quark mass in the SU(2) singlet representation. Limits are only presented in the regime $\Gamma/m_{\mathrm{T}}$ < 50%, where the theory calculations are known to be valid.

Expected 95% CL exclusion limits on the total cross-section σ($pp$ → $T$ → $Ht/Zt$) as a function of the universal coupling constant and the $T$-quark mass in the SU(2) singlet representation. Limits are only presented in the regime $\Gamma/m_{\mathrm{T}}$ < 50%, where the theory calculations are known to be valid.

Observed 95% CL exclusion limits on the total cross-section σ($pp$ → $T$ → $Ht/Zt$) as a function of the universal coupling constant and the $T$-quark mass in the SU(2) doublet representation. Limits are only presented in the regime $\Gamma/m_{\mathrm{T}}$ < 50%, where the theory calculations are known to be valid.

Expected 95% CL exclusion limits on the total cross-section σ($pp$ → $T$ → $Ht/Zt$) as a function of the universal coupling constant and the $T$-quark mass in the SU(2) doublet representation. Limits are only presented in the regime $\Gamma/m_{\mathrm{T}}$ < 50%, where the theory calculations are known to be valid.

Obs.Comb 95% CL exclusion limits on the universal coupling constant $\kappa$ as a function of the $T$ quark mass in the SU(2) singlet representations for the combination. Limits are only presented in the regime $\Gamma_{\mathrm{T}}/m_{\mathrm{T}} < 50\%$, where the theory calculations are known to be valid.

Exp.Comb 95% CL exclusion limits on the universal coupling constant $\kappa$ as a function of the $T$ quark mass in the SU(2) singlet representations for the combination. Limits are only presented in the regime $\Gamma_{\mathrm{T}}/m_{\mathrm{T}} < 50\%$, where the theory calculations are known to be valid.

Exp.$+1\sigma$ for the 95% CL exclusion limits on the universal coupling constant $\kappa$ as a function of the $T$ quark mass in the SU(2) singlet representations for the combination. Limits are only presented in the regime $\Gamma_{\mathrm{T}}/m_{\mathrm{T}} < 50\%$, where the theory calculations are known to be valid.

Exp.$-1\sigma$ for the 95% CL exclusion limits on the universal coupling constant $\kappa$ as a function of the $T$ quark mass in the SU(2) singlet representations for the combination. Limits are only presented in the regime $\Gamma_{\mathrm{T}}/m_{\mathrm{T}} < 50\%$, where the theory calculations are known to be valid.

Exp.$+2\sigma$ for the 95% CL exclusion limits on the universal coupling constant $\kappa$ as a function of the $T$ quark mass in the SU(2) singlet representations for the combination. Limits are only presented in the regime $\Gamma_{\mathrm{T}}/m_{\mathrm{T}} < 50\%$, where the theory calculations are known to be valid.

Exp.$-2\sigma$ for the 95% CL exclusion limits on the universal coupling constant $\kappa$ as a function of the $T$ quark mass in the SU(2) singlet representations for the combination. Limits are only presented in the regime $\Gamma_{\mathrm{T}}/m_{\mathrm{T}} < 50\%$, where the theory calculations are known to be valid.

Exp.OSML 95% CL exclusion limits on the universal coupling constant $\kappa$ as a function of the $T$ quark mass in the SU(2) singlet representations for the combination. Limits are only presented in the regime $\Gamma_{\mathrm{T}}/m_{\mathrm{T}} < 50\%$, where the theory calculations are known to be valid.

Exp.HTZT 95% CL exclusion limits on the universal coupling constant $\kappa$ as a function of the $T$ quark mass in the SU(2) singlet representations for the combination. Limits are only presented in the regime $\Gamma_{\mathrm{T}}/m_{\mathrm{T}} < 50\%$, where the theory calculations are known to be valid.

Exp.Monotop 95% CL exclusion limits on the universal coupling constant $\kappa$ as a function of the $T$ quark mass in the SU(2) singlet representations for the combination. Limits are only presented in the regime $\Gamma_{\mathrm{T}}/m_{\mathrm{T}} < 50\%$, where the theory calculations are known to be valid.

Obs.Comb 95% CL exclusion limits on the universal coupling constant $\kappa$ as a function of the $T$ quark mass in the SU(2) doublet representations for the combination. Limits are only presented in the regime $\Gamma_{\mathrm{T}}/m_{\mathrm{T}} < 50\%$, where the theory calculations are known to be valid.

Exp.Comb 95% CL exclusion limits on the universal coupling constant $\kappa$ as a function of the $T$ quark mass in the SU(2) doublet representations for the combination. Limits are only presented in the regime $\Gamma_{\mathrm{T}}/m_{\mathrm{T}} < 50\%$, where the theory calculations are known to be valid.

Exp.$+1\sigma$ for the 95% CL exclusion limits on the universal coupling constant $\kappa$ as a function of the $T$ quark mass in the SU(2) doublet representations for the combination. Limits are only presented in the regime $\Gamma_{\mathrm{T}}/m_{\mathrm{T}} < 50\%$, where the theory calculations are known to be valid.

Exp.$-1\sigma$ for the 95% CL exclusion limits on the universal coupling constant $\kappa$ as a function of the $T$ quark mass in the SU(2) doublet representations for the combination. Limits are only presented in the regime $\Gamma_{\mathrm{T}}/m_{\mathrm{T}} < 50\%$, where the theory calculations are known to be valid.

Exp.$+2\sigma$ for the 95% CL exclusion limits on the universal coupling constant $\kappa$ as a function of the $T$ quark mass in the SU(2) doublet representations for the combination. Limits are only presented in the regime $\Gamma_{\mathrm{T}}/m_{\mathrm{T}} < 50\%$, where the theory calculations are known to be valid.

Exp.$-2\sigma$ for the 95% CL exclusion limits on the universal coupling constant $\kappa$ as a function of the $T$ quark mass in the SU(2) doublet representations for the combination. Limits are only presented in the regime $\Gamma_{\mathrm{T}}/m_{\mathrm{T}} < 50\%$, where the theory calculations are known to be valid.

Exp.OSML 95% CL exclusion limits on the universal coupling constant $\kappa$ as a function of the $T$ quark mass in the SU(2) doublet representations for the combination. Limits are only presented in the regime $\Gamma_{\mathrm{T}}/m_{\mathrm{T}} < 50\%$, where the theory calculations are known to be valid.

Exp.HTZT 95% CL exclusion limits on the universal coupling constant $\kappa$ as a function of the $T$ quark mass in the SU(2) doublet representations for the combination. Limits are only presented in the regime $\Gamma_{\mathrm{T}}/m_{\mathrm{T}} < 50\%$, where the theory calculations are known to be valid.

Observed upper limits at 95% CL on the $T$ quark mass as a function of the relative resonance width ($\Gamma_{\mathrm{T}}/m_{\mathrm{T}}$) and the relative coupling parameter $\xi_W$.

Expected upper limits at 95% CL on the $T$ quark mass as a function of the relative resonance width ($\Gamma_{\mathrm{T}}/m_{\mathrm{T}}$) and the relative coupling parameter $\xi_W$.

Observed and expected 95% CL upper limits on the total cross-section σ($pp$ → $T$ → $Ht/Zt$) as a function of $T$-quark mass in the SU(2) singlet representation assuming $\kappa$=0.7. The expected limits for the individual analyses are shown.

Observed and expected 95% CL upper limits on the total cross-section σ($pp$ → $T$ → $Ht/Zt$) as a function of $T$-quark mass in the SU(2) doublet representation assuming $\kappa$=0.7. The expected limits for the individual analyses are shown.

Observed and expected 95% CL upper limits on the total cross-section σ($pp$ → $T$ → $Ht/Zt$) as a function of $T$-quark mass in the SU(2) singlet representation assuming $\kappa$=0.3. The observed limits for the individual analyses are shown. The $HtZt$ analysis is only included in the limit calculation for $m_{\mathrm{T}}$ < 2.1 TeV.

Observed and expected 95% CL upper limits on the total cross-section σ($pp$ → $T$ → $Ht/Zt$) as a function of $T$-quark mass in the SU(2) singlet representation assuming $\kappa$=0.5. The observed limits for the individual analyses are shown. The $HtZt$ analysis is only included in the limit calculation for $m_{\mathrm{T}}$ < 2.1 TeV.

Observed and expected 95% CL upper limits on the total cross-section σ($pp$ → $T$ → $Ht/Zt$) as a function of $T$-quark mass in the SU(2) singlet representation assuming $\kappa$=0.7. The observed limits for the individual analyses are shown.

Observed and expected 95% CL upper limits on the total cross-section σ($pp$ → $T$ → $Ht/Zt$) as a function of $T$-quark mass in the SU(2) doublet representation assuming $\kappa$=0.3. The observed limits for the individual analyses are shown. The $HtZt$ analysis is only included in the limit calculation for $m_{\mathrm{T}}$ < 2.1 TeV.

Observed and expected 95% CL upper limits on the total cross-section σ($pp$ → $T$ → $Ht/Zt$) as a function of $T$-quark mass in the SU(2) doublet representation assuming $\kappa$=0.5. The observed limits for the individual analyses are shown. The $HtZt$ analysis is only included in the limit calculation for $m_{\mathrm{T}}$ < 2.1 TeV.

Observed and expected 95% CL upper limits on the total cross-section σ($pp$ → $T$ → $Ht/Zt$) as a function of $T$-quark mass in the SU(2) doublet representation assuming $\kappa$=0.7. The observed limits for the individual analyses are shown.

Obs.Comb 95% CL exclusion limits on the universal coupling constant $\kappa$ as a function of the $T$ quark mass in the SU(2) singlet representations for the combination. Limits are only presented in the regime $\Gamma_{\mathrm{T}}/m_{\mathrm{T}} < 50\%$, where the theory calculations are known to be valid.

Exp.Comb 95% CL exclusion limits on the universal coupling constant $\kappa$ as a function of the $T$ quark mass in the SU(2) singlet representations for the combination. Limits are only presented in the regime $\Gamma_{\mathrm{T}}/m_{\mathrm{T}} < 50\%$, where the theory calculations are known to be valid.

Exp.$+1\sigma$ for the 95% CL exclusion limits on the universal coupling constant $\kappa$ as a function of the $T$ quark mass in the SU(2) singlet representations for the combination. Limits are only presented in the regime $\Gamma_{\mathrm{T}}/m_{\mathrm{T}} < 50\%$, where the theory calculations are known to be valid.

Exp.$-1\sigma$ for the 95% CL exclusion limits on the universal coupling constant $\kappa$ as a function of the $T$ quark mass in the SU(2) singlet representations for the combination. Limits are only presented in the regime $\Gamma_{\mathrm{T}}/m_{\mathrm{T}} < 50\%$, where the theory calculations are known to be valid.

Exp.$+2\sigma$ for the 95% CL exclusion limits on the universal coupling constant $\kappa$ as a function of the $T$ quark mass in the SU(2) singlet representations for the combination. Limits are only presented in the regime $\Gamma_{\mathrm{T}}/m_{\mathrm{T}} < 50\%$, where the theory calculations are known to be valid.

Exp.$-2\sigma$ for the 95% CL exclusion limits on the universal coupling constant $\kappa$ as a function of the $T$ quark mass in the SU(2) singlet representations for the combination. Limits are only presented in the regime $\Gamma_{\mathrm{T}}/m_{\mathrm{T}} < 50\%$, where the theory calculations are known to be valid.

Obs.OSML 95% CL exclusion limits on the universal coupling constant $\kappa$ as a function of the $T$ quark mass in the SU(2) singlet representations for the combination. Limits are only presented in the regime $\Gamma_{\mathrm{T}}/m_{\mathrm{T}} < 50\%$, where the theory calculations are known to be valid.

Obs.HTZT 95% CL exclusion limits on the universal coupling constant $\kappa$ as a function of the $T$ quark mass in the SU(2) singlet representations for the combination. Limits are only presented in the regime $\Gamma_{\mathrm{T}}/m_{\mathrm{T}} < 50\%$, where the theory calculations are known to be valid.

Obs.Monotop 95% CL exclusion limits on the universal coupling constant $\kappa$ as a function of the $T$ quark mass in the SU(2) singlet representations for the combination. Limits are only presented in the regime $\Gamma_{\mathrm{T}}/m_{\mathrm{T}} < 50\%$, where the theory calculations are known to be valid.

Obs.Comb 95% CL exclusion limits on the universal coupling constant $\kappa$ as a function of the $T$ quark mass in the SU(2) doublet representations for the combination. Limits are only presented in the regime $\Gamma_{\mathrm{T}}/m_{\mathrm{T}} < 50\%$, where the theory calculations are known to be valid.

Exp.Comb 95% CL exclusion limits on the universal coupling constant $\kappa$ as a function of the $T$ quark mass in the SU(2) doublet representations for the combination. Limits are only presented in the regime $\Gamma_{\mathrm{T}}/m_{\mathrm{T}} < 50\%$, where the theory calculations are known to be valid.

Exp.$+1\sigma$ for the 95% CL exclusion limits on the universal coupling constant $\kappa$ as a function of the $T$ quark mass in the SU(2) doublet representations for the combination. Limits are only presented in the regime $\Gamma_{\mathrm{T}}/m_{\mathrm{T}} < 50\%$, where the theory calculations are known to be valid.

Exp.$-1\sigma$ for the 95% CL exclusion limits on the universal coupling constant $\kappa$ as a function of the $T$ quark mass in the SU(2) doublet representations for the combination. Limits are only presented in the regime $\Gamma_{\mathrm{T}}/m_{\mathrm{T}} < 50\%$, where the theory calculations are known to be valid.

Exp.$+2\sigma$ for the 95% CL exclusion limits on the universal coupling constant $\kappa$ as a function of the $T$ quark mass in the SU(2) doublet representations for the combination. Limits are only presented in the regime $\Gamma_{\mathrm{T}}/m_{\mathrm{T}} < 50\%$, where the theory calculations are known to be valid.

Exp.$-2\sigma$ for the 95% CL exclusion limits on the universal coupling constant $\kappa$ as a function of the $T$ quark mass in the SU(2) doublet representations for the combination. Limits are only presented in the regime $\Gamma_{\mathrm{T}}/m_{\mathrm{T}} < 50\%$, where the theory calculations are known to be valid.

Obs.OSML 95% CL exclusion limits on the universal coupling constant $\kappa$ as a function of the $T$ quark mass in the SU(2) doublet representations for the combination. Limits are only presented in the regime $\Gamma_{\mathrm{T}}/m_{\mathrm{T}} < 50\%$, where the theory calculations are known to be valid.

Obs.HTZT 95% CL exclusion limits on the universal coupling constant $\kappa$ as a function of the $T$ quark mass in the SU(2) doublet representations for the combination. Limits are only presented in the regime $\Gamma_{\mathrm{T}}/m_{\mathrm{T}} < 50\%$, where the theory calculations are known to be valid.

Observed (solid line) and expected (dashed line) upper limits at the 95&percnt; CL on the cross-section times branching fraction as a function of c&tau; for a selection of models targeted in the CalR+W channel for (a) WALP models and (b) WHS models with a SM Higgs boson mediator.

Observed (solid line) and expected (dashed line) upper limits at the 95&percnt; CL on the cross-section times branching fraction as a function of c&tau; for a selection of models targeted in the CalR+W channel for (a) WALP models and (b) WHS models with a SM Higgs boson mediator.

Observed (solid line) and expected (dashed line) upper limits at the 95&percnt; CL on the cross-section times branching fraction as a function of c&tau; for a variety of models probed by the CalR+Z channel for (a) ZALP models, (b) ZHS models with the SM Higgs boson as a mediator, and (c) HZZ_d models.

Observed (solid line) and expected (dashed line) upper limits at the 95&percnt; CL on the cross-section times branching fraction as a function of c&tau; for a variety of models probed by the CalR+Z channel for (a) ZALP models, (b) ZHS models with the SM Higgs boson as a mediator, and (c) HZZ_d models.

Observed (solid line) and expected (dashed line) upper limits at the 95&percnt; CL on the cross-section times branching fraction as a function of c&tau; for a variety of models probed by the CalR+Z channel for (a) ZALP models, (b) ZHS models with the SM Higgs boson as a mediator, and (c) HZZ_d models.

Summary of the observed (solid line) and expected (dashed line) upper limits at the 95&percnt; CL on C_G as a function of C_W for a variety of ALP mass hypotheses probed by the CalR+R and Cal+Z channels for (a) WALP and (b) ZALP models.

Summary of the observed (solid line) and expected (dashed line) upper limits at the 95&percnt; CL on C_G as a function of C_W for a variety of ALP mass hypotheses probed by the CalR+R and Cal+Z channels for (a) WALP and (b) ZALP models.

Regions in the ALP mass versus its coupling to gluons scaled by the ALP energy scale g_agg=4C_G/f_a excluded at 95&percnt; CL, for C_W=1, C_W=0.5, C_W=0.3 and C_W=0.15, in the (a) WALP and (b) ZALP models. The contours are obtained by interpolating between the exclusions for different LLP masses considered in the analysis, taking the logical union of the regions excluded for each mass.

Regions in the ALP mass versus its coupling to gluons scaled by the ALP energy scale g_agg=4C_G/f_a excluded at 95&percnt; CL, for C_W=1, C_W=0.5, C_W=0.3 and C_W=0.15, in the (a) WALP and (b) ZALP models. The contours are obtained by interpolating between the exclusions for different LLP masses considered in the analysis, taking the logical union of the regions excluded for each mass.

Signal efficiencies as a function of c&tau; for HS signals in the CalR+2J channel for samples with mediator masses (a) below 400 GeV and (b) equal to or above 400 GeV. The extrapolation of efficiencies to new mean LLP lifetimes is done via the event reweighting procedure. Only statistical uncertainties are shown.

Signal efficiencies as a function of c&tau; for HS signals in the CalR+2J channel for samples with mediator masses (a) below 400 GeV and (b) equal to or above 400 GeV. The extrapolation of efficiencies to new mean LLP lifetimes is done via the event reweighting procedure. Only statistical uncertainties are shown.

Signal efficiencies as a function of c&tau; for WALP and WHS signals in the CalR+W channel for (a) the WALP selection, (b) the CalR+W low-E_T selection and (c) the CalR+W high-E_T selection. The extrapolation of efficiencies to new mean LLP lifetimes is done via the event reweighting procedure. Only statistical uncertainties are shown.

Signal efficiencies as a function of c&tau; for WALP and WHS signals in the CalR+W channel for (a) the WALP selection, (b) the CalR+W low-E_T selection and (c) the CalR+W high-E_T selection. The extrapolation of efficiencies to new mean LLP lifetimes is done via the event reweighting procedure. Only statistical uncertainties are shown.

Signal efficiencies as a function of c&tau; for WALP and WHS signals in the CalR+W channel for (a) the WALP selection, (b) the CalR+W low-E_T selection and (c) the CalR+W high-E_T selection. The extrapolation of efficiencies to new mean LLP lifetimes is done via the event reweighting procedure. Only statistical uncertainties are shown.

Signal efficiencies as a function of c&tau; for ZALP, HZZ_d and ZHS signals in the CalR+Z channel for (a, b) the CalR+Z low-E_T selection and (c, d) the CalR+Z high-E_T selection. The extrapolation of efficiencies to new mean LLP lifetimes is done via the event reweighting procedure. Only statistical uncertainties are shown.

Signal efficiencies as a function of c&tau; for ZALP, HZZ_d and ZHS signals in the CalR+Z channel for (a, b) the CalR+Z low-E_T selection and (c, d) the CalR+Z high-E_T selection. The extrapolation of efficiencies to new mean LLP lifetimes is done via the event reweighting procedure. Only statistical uncertainties are shown.

Signal efficiencies as a function of c&tau; for ZALP, HZZ_d and ZHS signals in the CalR+Z channel for (a, b) the CalR+Z low-E_T selection and (c, d) the CalR+Z high-E_T selection. The extrapolation of efficiencies to new mean LLP lifetimes is done via the event reweighting procedure. Only statistical uncertainties are shown.

Signal efficiencies as a function of c&tau; for ZALP, HZZ_d and ZHS signals in the CalR+Z channel for (a, b) the CalR+Z low-E_T selection and (c, d) the CalR+Z high-E_T selection. The extrapolation of efficiencies to new mean LLP lifetimes is done via the event reweighting procedure. Only statistical uncertainties are shown.

95&percnt; CL expected (dashed black line) and observed (solid line) upper limits on the cross-section times branching fraction in the CalR+2J channel for the benchmark HS models with mass pairs (m_&Phi;, m_S) (a) (60, 16), (b) (125, 35), (c) (125, 55), (d) (200, 50), (e) (400, 100), (f) (600, 150), (g) (600, 275), (h) (1000, 275), and (i) (1000, 475) GeV.

95&percnt; CL expected (dashed black line) and observed (solid line) upper limits on the cross-section times branching fraction in the CalR+2J channel for the benchmark HS models with mass pairs (m_&Phi;, m_S) (a) (60, 16), (b) (125, 35), (c) (125, 55), (d) (200, 50), (e) (400, 100), (f) (600, 150), (g) (600, 275), (h) (1000, 275), and (i) (1000, 475) GeV.

95&percnt; CL expected (dashed black line) and observed (solid line) upper limits on the cross-section times branching fraction in the CalR+2J channel for the benchmark HS models with mass pairs (m_&Phi;, m_S) (a) (60, 16), (b) (125, 35), (c) (125, 55), (d) (200, 50), (e) (400, 100), (f) (600, 150), (g) (600, 275), (h) (1000, 275), and (i) (1000, 475) GeV.

95&percnt; CL expected (dashed black line) and observed (solid line) upper limits on the cross-section times branching fraction in the CalR+2J channel for the benchmark HS models with mass pairs (m_&Phi;, m_S) (a) (60, 16), (b) (125, 35), (c) (125, 55), (d) (200, 50), (e) (400, 100), (f) (600, 150), (g) (600, 275), (h) (1000, 275), and (i) (1000, 475) GeV.

95&percnt; CL expected (dashed black line) and observed (solid line) upper limits on the cross-section times branching fraction in the CalR+2J channel for the benchmark HS models with mass pairs (m_&Phi;, m_S) (a) (60, 16), (b) (125, 35), (c) (125, 55), (d) (200, 50), (e) (400, 100), (f) (600, 150), (g) (600, 275), (h) (1000, 275), and (i) (1000, 475) GeV.

95&percnt; CL expected (dashed black line) and observed (solid line) upper limits on the cross-section times branching fraction in the CalR+2J channel for the benchmark HS models with mass pairs (m_&Phi;, m_S) (a) (60, 16), (b) (125, 35), (c) (125, 55), (d) (200, 50), (e) (400, 100), (f) (600, 150), (g) (600, 275), (h) (1000, 275), and (i) (1000, 475) GeV.

95&percnt; CL expected (dashed black line) and observed (solid line) upper limits on the cross-section times branching fraction in the CalR+2J channel for the benchmark HS models with mass pairs (m_&Phi;, m_S) (a) (60, 16), (b) (125, 35), (c) (125, 55), (d) (200, 50), (e) (400, 100), (f) (600, 150), (g) (600, 275), (h) (1000, 275), and (i) (1000, 475) GeV.

95&percnt; CL expected (dashed black line) and observed (solid line) upper limits on the cross-section times branching fraction in the CalR+2J channel for the benchmark HS models with mass pairs (m_&Phi;, m_S) (a) (60, 16), (b) (125, 35), (c) (125, 55), (d) (200, 50), (e) (400, 100), (f) (600, 150), (g) (600, 275), (h) (1000, 275), and (i) (1000, 475) GeV.

95&percnt; CL expected (dashed black line) and observed (solid line) upper limits on the cross-section times branching fraction in the CalR+2J channel for the benchmark HS models with mass pairs (m_&Phi;, m_S) (a) (60, 16), (b) (125, 35), (c) (125, 55), (d) (200, 50), (e) (400, 100), (f) (600, 150), (g) (600, 275), (h) (1000, 275), and (i) (1000, 475) GeV.

95&percnt; CL expected (dashed line) and observed (solid line) upper limits on the cross-section times branching fraction in the WHS channel for the low-E_T WHS selection for benchmark WHS models with mass pairs (m_&Phi;, m_S) (a) (60, 5) and (60, 15), (b) (200, 50) and (200, 80), (c) (400, 100) and (400, 175), (d) (600, 50), (600, 150), and (600, 275), (e) (1000, 50), (1000, 275), and (1000, 475) GeV

95&percnt; CL expected (dashed line) and observed (solid line) upper limits on the cross-section times branching fraction in the WHS channel for the low-E_T WHS selection for benchmark WHS models with mass pairs (m_&Phi;, m_S) (a) (60, 5) and (60, 15), (b) (200, 50) and (200, 80), (c) (400, 100) and (400, 175), (d) (600, 50), (600, 150), and (600, 275), (e) (1000, 50), (1000, 275), and (1000, 475) GeV

95&percnt; CL expected (dashed line) and observed (solid line) upper limits on the cross-section times branching fraction in the WHS channel for the low-E_T WHS selection for benchmark WHS models with mass pairs (m_&Phi;, m_S) (a) (60, 5) and (60, 15), (b) (200, 50) and (200, 80), (c) (400, 100) and (400, 175), (d) (600, 50), (600, 150), and (600, 275), (e) (1000, 50), (1000, 275), and (1000, 475) GeV

95&percnt; CL expected (dashed line) and observed (solid line) upper limits on the cross-section times branching fraction in the WHS channel for the low-E_T WHS selection for benchmark WHS models with mass pairs (m_&Phi;, m_S) (a) (60, 5) and (60, 15), (b) (200, 50) and (200, 80), (c) (400, 100) and (400, 175), (d) (600, 50), (600, 150), and (600, 275), (e) (1000, 50), (1000, 275), and (1000, 475) GeV

95&percnt; CL expected (dashed line) and observed (solid line) upper limits on the cross-section times branching fraction in the WHS channel for the low-E_T WHS selection for benchmark WHS models with mass pairs (m_&Phi;, m_S) (a) (60, 5) and (60, 15), (b) (200, 50) and (200, 80), (c) (400, 100) and (400, 175), (d) (600, 50), (600, 150), and (600, 275), (e) (1000, 50), (1000, 275), and (1000, 475) GeV

95&percnt; CL expected (dashed line) and observed (solid line) limits on the branching fraction in the low-E_T WHS selection for benchmark WHS models with mass pairs (m_&Phi;, m_S) (a) (125, 16), (b) (600, 150) GeV, and the WALP selection for WALP models with (c) m_ALP = 1 GeV.

95&percnt; CL expected (dashed line) and observed (solid line) limits on the branching fraction in the low-E_T WHS selection for benchmark WHS models with mass pairs (m_&Phi;, m_S) (a) (125, 16), (b) (600, 150) GeV, and the WALP selection for WALP models with (c) m_ALP = 1 GeV.

95&percnt; CL expected (dashed line) and observed (solid line) limits on the branching fraction in the low-E_T WHS selection for benchmark WHS models with mass pairs (m_&Phi;, m_S) (a) (125, 16), (b) (600, 150) GeV, and the WALP selection for WALP models with (c) m_ALP = 1 GeV.

95&percnt; CL expected (dashed line) and observed (solid line) limits on the branching fraction in the CalR+Z channel for benchmark HZZ_d models with mass pairs (m_&Phi;, m_{Z_d}) (a) (400, 100) and (400, 200), (b) (600, 150) and (600, 400). The ZHS sample is shown for masses (m_&Phi;, m_S) in GeV: (c) (200, 50) and (200, 80), (d) (400, 100) and (400, 175), (e) (600, 50), (600, 150) and (600, 275), (f) (1000, 50), (1000, 275) and (1000, 475) GeV.

95&percnt; CL expected (dashed line) and observed (solid line) limits on the branching fraction in the CalR+Z channel for benchmark HZZ_d models with mass pairs (m_&Phi;, m_{Z_d}) (a) (400, 100) and (400, 200), (b) (600, 150) and (600, 400). The ZHS sample is shown for masses (m_&Phi;, m_S) in GeV: (c) (200, 50) and (200, 80), (d) (400, 100) and (400, 175), (e) (600, 50), (600, 150) and (600, 275), (f) (1000, 50), (1000, 275) and (1000, 475) GeV.

95&percnt; CL expected (dashed line) and observed (solid line) limits on the branching fraction in the CalR+Z channel for benchmark HZZ_d models with mass pairs (m_&Phi;, m_{Z_d}) (a) (400, 100) and (400, 200), (b) (600, 150) and (600, 400). The ZHS sample is shown for masses (m_&Phi;, m_S) in GeV: (c) (200, 50) and (200, 80), (d) (400, 100) and (400, 175), (e) (600, 50), (600, 150) and (600, 275), (f) (1000, 50), (1000, 275) and (1000, 475) GeV.

95&percnt; CL expected (dashed line) and observed (solid line) limits on the branching fraction in the CalR+Z channel for benchmark HZZ_d models with mass pairs (m_&Phi;, m_{Z_d}) (a) (400, 100) and (400, 200), (b) (600, 150) and (600, 400). The ZHS sample is shown for masses (m_&Phi;, m_S) in GeV: (c) (200, 50) and (200, 80), (d) (400, 100) and (400, 175), (e) (600, 50), (600, 150) and (600, 275), (f) (1000, 50), (1000, 275) and (1000, 475) GeV.

95&percnt; CL expected (dashed line) and observed (solid line) limits on the branching fraction in the CalR+Z channel for benchmark HZZ_d models with mass pairs (m_&Phi;, m_{Z_d}) (a) (400, 100) and (400, 200), (b) (600, 150) and (600, 400). The ZHS sample is shown for masses (m_&Phi;, m_S) in GeV: (c) (200, 50) and (200, 80), (d) (400, 100) and (400, 175), (e) (600, 50), (600, 150) and (600, 275), (f) (1000, 50), (1000, 275) and (1000, 475) GeV.

95&percnt; CL expected (dashed line) and observed (solid line) limits on the branching fraction in the CalR+Z channel for benchmark HZZ_d models with mass pairs (m_&Phi;, m_{Z_d}) (a) (400, 100) and (400, 200), (b) (600, 150) and (600, 400). The ZHS sample is shown for masses (m_&Phi;, m_S) in GeV: (c) (200, 50) and (200, 80), (d) (400, 100) and (400, 175), (e) (600, 50), (600, 150) and (600, 275), (f) (1000, 50), (1000, 275) and (1000, 475) GeV.

Expected value of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_\lambda$ parameter for $b\bar{b}\gamma\gamma$.

Expected value of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_\lambda$ parameter for $b\bar{b}\ell\ell+E_\text{T}^{\text{miss}}$.

Expected value of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_\lambda$ parameter for Multilepton.

Expected value of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_\lambda$ parameter for combination.

Expected value of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_{2V}$ parameter for $b\bar{b}b\bar{b}$.

Expected value of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_{2V}$ parameter for $b\bar{b}\tau\tau$.

Expected value of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_{2V}$ parameter for $b\bar{b}\gamma\gamma$.

Expected value of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_{2V}$ parameter for $b\bar{b}\ell\ell+E_\text{T}^{\text{miss}}$.

Expected value of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_{2V}$ parameter for Multilepton.

Expected value of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_{2V}$ parameter for combination.

Observed and expected 95&percnt; CL upper limits on the signal strength for the inclusive ggF HH production from the bb&#772;&tau;⁺&tau;^-, bb&#772;&gamma;&gamma;, bb&#772;bb&#772;, multilepton and bb&#772;&#8467;&#8467;+E_T^miss decay channels, and their statistical combination. When deriving the limit on &mu;_ggF^HH (&mu;_VBF^HH), the VBF (ggF) HH production cross-section is fixed to the SM predicted value for m_H=125 GeV. The expected limit, along with the &plusmn;1&sigma; and &plusmn;2&sigma; bands, is calculated under the assumption of no HH process and with all NPs profiled to the observed data.

Observed and expected 95&percnt; CL upper limits on the signal strength for the VBF HH production from the bb&#772;&tau;⁺&tau;^-, bb&#772;&gamma;&gamma;, bb&#772;bb&#772;, multilepton and bb&#772;&#8467;&#8467;+E_T^miss decay channels, and their statistical combination. When deriving the limit on &mu;_ggF^HH (&mu;_VBF^HH), the VBF (ggF) HH production cross-section is fixed to the SM predicted value for m_H=125 GeV. The expected limit, along with the &plusmn;1&sigma; and &plusmn;2&sigma; bands, is calculated under the assumption of no HH process and with all NPs profiled to the observed data.

Observed and expected upper limits at 95&percnt; CL on the inclusive ggF and VBF HH production cross-section from the bb&#772;&tau;⁺&tau;^-, bb&#772;&gamma;&gamma;, bb&#772;bb&#772;, multilepton and bb&#772;&#8467;&#8467;+E_T^miss decay channels, and their statistical combination. The Higgs boson mass is set to 125&nbsp;GeV when deriving the predicted SM cross-section (red band). The expected limits, along with the &plusmn;1&sigma; and &plusmn;2&sigma; bands, are calculated under the assumption of no Higgs boson pair production and with all NPs profiled to the observed data.

Observed value of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_\lambda$ parameter for $b\bar{b}b\bar{b}$.

Observed value of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_\lambda$ parameter for $b\bar{b}\tau\tau$.

Observed value of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_\lambda$ parameter for $b\bar{b}\gamma\gamma$.

Observed value of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_\lambda$ parameter for $b\bar{b}\ell\ell+E_\text{T}^{\text{miss}}$.

Observed value of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_\lambda$ parameter for Multilepton.

Observed value of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_\lambda$ parameter for combination.

Observed value of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_{2V}$ parameter for $b\bar{b}b\bar{b}$.

Observed value of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_{2V}$ parameter for $b\bar{b}\tau\tau$.

Observed value of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_{2V}$ parameter for $b\bar{b}\gamma\gamma$.

Observed value of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_{2V}$ parameter for $b\bar{b}\ell\ell+E_\text{T}^{\text{miss}}$.

Observed value of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_{2V}$ parameter for Multilepton.

Observed value of the test statistic (-2ln$\Lambda$), as a function of the $\kappa_{2V}$ parameter for combination.

Observed (solid lines) and expected (dashed lines) 95&percnt; CL exclusion limits on the HH production cross-sections of (a) the inclusive ggF and VBF processes as a function of &kappa;_&lambda;, for the bb&#772;&gamma;&gamma; (purple), bb&#772;&tau;⁺&tau;^- (green), multilepton (cyan), bb&#772;bb&#772; (blue) and bb&#772;&#8467;&#8467;+E_T^miss (brown) decay channels and their combination (black). The expected limits assume no HH production. The red line shows the theory prediction for the ggF and VBF HH production cross-section as a function of &kappa;_&lambda;. The bands surrounding the red cross-section lines indicate the theoretical uncertainties on the predicted cross-section.

Observed (solid lines) and expected (dashed lines) 95&percnt; CL exclusion limits on the HH production cross-sections of the VBF process as a function of &kappa;_2V, for the bb&#772;&gamma;&gamma; (purple), bb&#772;&tau;⁺&tau;^- (green), multilepton (cyan), bb&#772;bb&#772; (blue) and bb&#772;&#8467;&#8467;+E_T^miss (brown) decay channels and their combination (black). The expected limits assume no VBF HH production. The ggF HH production cross-section is assumed to be as predicted by the SM. The ggF HH production cross-section is assumed to be as predicted by the SM. The red line shows the predicted VBF HH cross-section as a function of &kappa;_2V. The bands surrounding the red cross-section lines indicate the theoretical uncertainties on the predicted cross-section.

Observed value of the test statistic (-2ln$\Lambda$), as a function of the $c_{gghh}$ parameter for $b\bar{b}b\bar{b}$.

Observed value of the test statistic (-2ln$\Lambda$), as a function of the $c_{gghh}$ parameter for $b\bar{b}\tau\tau$.

Observed value of the test statistic (-2ln$\Lambda$), as a function of the $c_{gghh}$ parameter for $b\bar{b}\gamma\gamma$.

Observed value of the test statistic (-2ln$\Lambda$), as a function of the $c_{gghh}$ parameter for combination.

Expected value of the test statistic (-2ln$\Lambda$), as a function of the $c_{gghh}$ parameter for $b\bar{b}b\bar{b}$.

Expected value of the test statistic (-2ln$\Lambda$), as a function of the $c_{gghh}$ parameter for $b\bar{b}\tau\tau$.

Expected value of the test statistic (-2ln$\Lambda$), as a function of the $c_{gghh}$ parameter for $b\bar{b}\gamma\gamma$.

Expected value of the test statistic (-2ln$\Lambda$), as a function of the $c_{gghh}$ parameter for combination.

Observed value of the test statistic (-2ln$\Lambda$), as a function of the $c_{tthh}$ parameter for $b\bar{b}b\bar{b}$.

Observed value of the test statistic (-2ln$\Lambda$), as a function of the $c_{tthh}$ parameter for $b\bar{b}\tau\tau$.

Observed value of the test statistic (-2ln$\Lambda$), as a function of the $c_{tthh}$ parameter for $b\bar{b}\gamma\gamma$.

Observed value of the test statistic (-2ln$\Lambda$), as a function of the $c_{tthh}$ parameter for combination.

Expected value of the test statistic (-2ln$\Lambda$), as a function of the $c_{tthh}$ parameter for $b\bar{b}b\bar{b}$.

Expected value of the test statistic (-2ln$\Lambda$), as a function of the $c_{tthh}$ parameter for $b\bar{b}\tau\tau$.

Expected value of the test statistic (-2ln$\Lambda$), as a function of the $c_{tthh}$ parameter for $b\bar{b}\gamma\gamma$.

Expected value of the test statistic (-2ln$\Lambda$), as a function of the $c_{tthh}$ parameter for combination.

Observed and expected 95&percnt; CL combined upper limits on the cross-section for the SM and seven BSM HEFT benchmarks (arXiv:2304.01968 [hep-ph]) in the ggF process, describing representative signal kinematics and m_HH shape features obtained by varying multiple HEFT coefficients. The expected limits from the bb&#772;&tau;⁺&tau;^-, bb&#772;&gamma;&gamma; and bb&#772;bb&#772; decay channels are presented as well. Theoretical predictions, estimated using specific sets of coefficient values defined in the benchmarks, are shown as red cross dots.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of the number of $b$-jets compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of the number of $l/c$-jets compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $H_{\text{T}}^{\text{had}}$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $\Delta R_{\text{avg}}^{bb}$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $p_{\text{T}}(b_{1})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $p_{\text{T}}(b_{2})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $p_{\text{T}}(b_{1}^{\text{top}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $p_{\text{T}}(b_{2}^{\text{top}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $p_{\text{T}}(b_{3})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $p_{\text{T}}(b_{1}^{\text{add}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $m(b_{1}b_{2})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $p_{\text{T}}(b_{1}b_{2})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $m(bb^{\text{top}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $p_{\text{T}}(bb^{\text{top}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $\Delta R(e\mu bb^{\text{top}}, b_{1}^{\text{add}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets and at least one $l/c$-jet as a function of $\Delta R(e\mu bb^{\text{top}}, l/c\text{-jet}_{1})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets and at least one $l/c$-jet as a function of $p_{\text{T}}(l/c\text{-jet}_{1})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets and at least one $l/c$-jet as a function of $p_{\text{T}}(l/c\text{-jet}_{1}) - p_{\text{T}}(b_{1}^{\text{add}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $m(bb^{\text{min}\Delta R})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $p_{\text{T}}(bb^{\text{min}\Delta R})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $m(bb^{\text{add}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $p_{\text{T}}(bb^{\text{add}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $|\eta(b_{3})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $|\eta(b_{1}^{\text{add}})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $\Delta R(b_{1}b_{2})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $m(e\mu bb^{\text{top}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $|\eta(l/c\text{-jet}_{1})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $\Delta\eta_{\text{max}}^{jj}$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $H_{\text{T}}^{\text{all}}$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $m(e\mu b_{1}b_{2})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $|\eta(b_{1})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $|\eta(b_{2})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $|\eta(b_{1}^{\text{top}})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least three $b$-jets as a function of $|\eta(b_{2}^{\text{top}})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $p_{\text{T}}(b_{1})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $p_{\text{T}}(b_{2})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $p_{\text{T}}(b_{1}^{\text{top}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $p_{\text{T}}(b_{2}^{\text{top}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $p_{\text{T}}(b_{3})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $p_{\text{T}}(b_{4})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $p_{\text{T}}(b_{1}^{\text{add}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $p_{\text{T}}(b_{2}^{\text{add}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $m(b_{1}b_{2})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $p_{\text{T}}(b_{1}b_{2})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $m(bb^{\text{top}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $p_{\text{T}}(bb^{\text{top}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $H_{\text{T}}^{\text{all}}$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $m(e\mu b_{1}b_{2})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $m(e\mu bb^{\text{top}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $H_{\text{T}}^{\text{had}}$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $\text{min}\Delta R(bb)$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $\Delta R(e\mu bb^{\text{top}}, b_{1}^{\text{add}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $\Delta R_{\text{avg}}^{bb}$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $\Delta\eta_{\text{max}}^{jj}$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of the number of $l/c$-jets compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets and at least one $l/c$-jet as a function of $p_{\text{T}}(l/c\text{-jet}_{1})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets and at least one $l/c$-jet as a function of $|\eta(l/c\text{-jet}_{1})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets and at least one $l/c$-jet as a function of $\Delta R(e\mu bb^{\text{top}}, l/c\text{-jet}_{1})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets and at least one $l/c$-jet as a function of $p_{\text{T}}(l/c\text{-jet}_{1}) - p_{\text{T}}(b_{1}^{\text{add}})$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $|\eta(b_{1})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $|\eta(b_{2})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $|\eta(b_{1}^{\text{top}})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at leastfour $b$-jets as a function of $|\eta(b_{2}^{\text{top}})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $|\eta(b_{3})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $|\eta(b_{4})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $|\eta(b_{1}^{\text{add}})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

Data bootstraps post unfolding for the normalised differential cross-section in the phase space with at least four $b$-jets as a function of $|\eta(b_{2}^{\text{add}})|$ compared with predictions. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the BootstrapGenerator software package (https://gitlab.cern.ch/atlas-physics/sm/StandardModelTools_BootstrapGenerator/BootstrapGenerator), which implements a technique described in ATL-PHYS-PUB-2021-011 (https://cds.cern.ch/record/2759945). The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. The last bin contains the overflow.

The measured normalised differential cross-section as a function of $N_{b-\text{jets}}$ in the $e\mu+\geq2b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $H_{\text{T}}^{\text{had}}$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $H_{\text{T}}^{\text{all}}$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $\Delta R_{\text{avg}}^{bb}$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $\Delta\eta_{\text{max}}^{jj}$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{1})$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{1}^{\text{top}})$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{2})$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{2}^{\text{top}})$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{3})$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{1}^{\text{add}})$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $|\eta(b_{1})|$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $|\eta(b_{1}^{\text{top}})|$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $|\eta(b_{2})|$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $|\eta(b_{2}^{\text{top}})|$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $|\eta(b_{3})|$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $|\eta(b_{1}^{\text{add}})|$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $m(b_{1}b_{2})$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{1}b_{2})$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $m(bb^{\text{top}})$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(bb^{\text{top}})$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $m(e\mu b_{1}b_{2})$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $m(e\mu bb^{\text{top}})$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $\Delta R(b_{1}b_{2})$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $N_{l/c-\text{jets}}$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $\Delta R(e\mu b_{1}b_{2},b_{3})$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $\Delta R(e\mu bb^{\text{top}}, b_{1}^{\text{add}})$ in the $e\mu+\geq3b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $\Delta R(e\mu bb^{\text{top}},l/c-\text{jet})$ in the $e\mu+\geq3b+\geq1l/c-\text{jet}$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(l/c\text{-jet}_{1}) - p_{\text{T}}(b_{1}^{\text{add}})$ in the $e\mu+\geq3b+\geq1l/c-\text{jet}$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $|\eta(l/c\text{-jet}_{1})|$ in the $e\mu+\geq3b+\geq1l/c-\text{jet}$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(l/c\text{-jet}_{1})$ in the $e\mu+\geq3b+\geq1l/c-\text{jet}$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $H_{\text{T}}^{\text{had}}$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $H_{\text{T}}^{\text{all}}$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $\Delta R_{\text{avg}}^{bb}$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $\Delta\eta_{\text{max}}^{jj}$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{1})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{1}^{\text{top}})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{2})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{2}^{\text{top}})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{3})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{1}^{\text{add}})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{4})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{2}^{\text{add}})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $|\eta(b_{1})|$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $|\eta(b_{1}^{\text{top}})|$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $|\eta(b_{2})|$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $|\eta(b_{2}^{\text{top}})|$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $|\eta(b_{3})|$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $|\eta(b_{1}^{\text{add}})|$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $|\eta(b_{4})|$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $|\eta(b_{2}^{\text{add}})|$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $m(b_{1}b_{2})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(b_{1}b_{2})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $m(bb^{\text{top}})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(bb^{\text{top}})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $m(e\mu b_{1}b_{2})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $m(e\mu bb^{\text{top}})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $m(bb^{\text{min}\Delta R})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(bb^{\text{min}\Delta R})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $m(bb^{\text{add}})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(bb^{\text{add}})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $\text{min}\Delta R(bb)$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $\Delta R(b_{1}b_{2})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $N_{l/c-\text{jets}}$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $\Delta R(e\mu b_{1}b_{2},b_{3})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $\Delta R(e\mu bb^{\text{top}}, b_{1}^{\text{add}})$ in the $e\mu+\geq4b$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $\Delta R(e\mu bb^{\text{top}}, l/c\text{-jet}_{1})$ in the $e\mu+\geq4b+\geq1l/c-\text{jet}$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(l/c\text{-jet}_{1}) - p_{\text{T}}(b_{1}^{\text{add}})$ in the $e\mu+\geq4b+\geq1l/c-\text{jet}$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $|\eta(l/c\text{-jet}_{1})|$ in the $e\mu+\geq4b+\geq1l/c-\text{jet}$ phase space. The overflow is included in the last bin.

The measured normalised differential cross-section as a function of $p_{\text{T}}(l/c\text{-jet}_{1})$ in the $e\mu+\geq4b+\geq1l/c-\text{jet}$ phase space. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $N_{b-\text{jets}}$ in the phase space with at least two b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $N_{b-\text{jets}}$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $H_{\text{T}}^{\text{had}}$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $H_{\text{T}}^{\text{all}}$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $\Delta R_{\text{avg}}^{bb}$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $\Delta\eta_{\text{max}}^{jj}$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{1})$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{1}^{\text{top}})$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{2})$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{2}^{\text{top}})$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{3})$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{1}^{\text{add}})$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(b_{1})|$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(b_{1}^{\text{top}})|$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(b_{2}^{\text{top}})|$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(b_{2}^{\text{top}})|$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(b_{3})|$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(b_{1}^{\text{add}})|$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $m(b_{1}b_{2})$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{1}b_{2})$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $m(bb^{\text{top}})$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(bb^{\text{top}})$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $m(e\mu b_{1}b_{2})$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $m(e\mu bb^{\text{top}})$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $\Delta R(b_{1}b_{2})$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $N_{l/c-\text{jets}}$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $\Delta R(e\mu b_{1}b_{2},b_{3})$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $\Delta R(e\mu bb^{\text{top}}, b_{1}^{\text{add}})$ in the phase space with at least three b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $\Delta R(e\mu bb^{\text{top}},l/c-\text{jet})$ in the phase space with at least three b-jets and at least one $l/c$-jet. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(l/c\text{-jet}_{1}) - p_{\text{T}}(b_{1}^{\text{add}})$ in the phase space with at least three b-jets and at least one $l/c$-jet. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(l/c\text{-jet}_{1})|$ in the phase space with at least three b-jets and at least one $l/c$-jet. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(l/c\text{-jet}_{1})$ in the phase space with at least three b-jets and at least one $l/c$-jet. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $H_{\text{T}}^{\text{had}}$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $H_{\text{T}}^{\text{all}}$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $\Delta R_{\text{avg}}^{bb}$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $\Delta\eta_{\text{max}}^{jj}$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{1})$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{1}^{\text{top}})$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{2})$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{2}^{\text{top}})$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{3})$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{1}^{\text{add}})$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{4})$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{2}^{\text{add}})$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(b_{1})|$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(b_{1}^{\text{top}})|$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(b_{2})|$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(b_{2}^{\text{top}})|$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(b_{3})|$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(b_{1}^{\text{add}})|$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(b_{4})|$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(b_{2}^{\text{add}})|$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $m(b_{1}b_{2})$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(b_{1}b_{2})$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $m(bb^{\text{top}})$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(bb^{\text{top}})$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $m(e\mu b_{1}b_{2})$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $m(e\mu bb^{\text{top}})$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $m(bb^{\text{min}\Delta R})$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(bb^{\text{min}\Delta R})$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $m(bb^{\text{add}})$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(bb^{\text{add}})$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $\text{min}\Delta R(bb)$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $\Delta R(b_{1}b_{2})$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $N_{l/c-\text{jets}}$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $\Delta R(e\mu b_{1}b_{2},b_{3})$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $\Delta R(e\mu bb^{\text{top}}, b_{1}^{\text{add}})$ in the phase space with at least four b-jets. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $\Delta R(e\mu bb^{\text{top}}, l/c\text{-jet}_{1})$ in the phase space with at least four b-jets and at least one $l/c$-jet. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(l/c\text{-jet}_{1}) - p_{\text{T}}(b_{1}^{\text{add}})$ in the phase space with at least four b-jets and at least one $l/c$-jet. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $|\eta(l/c\text{-jet}_{1})|$ in the phase space with at least four b-jets and at least one $l/c$-jet. The overflow is included in the last bin.

The correlation matrix for the measured normalised differential cross-section in terms of $p_{\text{T}}(l/c\text{-jet}_{1})$ in the phase space with at least four b-jets and at least one $l/c$-jet. The overflow is included in the last bin.

The Charged-hadron yields as a function of pT in different y selections in p+Pb collisions.

The K^{0}_{S} yields as a function of pT in different y selections in Pb+Pb photo-nuclear collisions.

The #Lambda yields as a function of pT in different y selections in Pb+Pb photo-nuclear collisions.

The #Xi^{-} yields as a function of pT in different y selections in Pb+Pb photo-nuclear collisions.

The K^{0}_{S} yields as a function of pT in different y selections in p+Pb collisions.

The #Lambda yields as a function of pT in different y selections in p+Pb collisions.

The #Xi^{-} yields as a function of pT in different y selections in p+Pb collisions.

The Charged-hadron and identified-hadron yields as a function of y in Pb+Pb photo-nuclear collisions.

The Charged-hadron and identified-hadron yields as a function of y in Pb+Pb photo-nuclear collisions.

The Charged-hadron and identified-hadron yields as a function of y in p+Pb collisions.

The Charged-hadron and identified-hadron yields as a function of y in p+Pb collisions.

The meanpT of charged hadrons and identified hadrons as a function of Nchrec in Pb+Pb photo-nuclear collisions.

The meanpT of charged hadrons and identified hadrons as a function of Nchrec in Pb+Pb photo-nuclear collisions.

The meanpT of charged hadrons and identified hadrons as a function of Nchrec in Pb+Pb photo-nuclear collisions.

The meanpT of charged hadrons and identified hadrons as a function of Nchrec in p+Pb collisions.

The meanpT of charged hadrons and identified hadrons as a function of Nchrec in p+Pb collisions.

The baryon to meson ratio as a function of pT in Pb+Pb photo-nuclear collisions.

The baryon to meson ratio as a function of pT in Pb+Pb photo-nuclear collisions.

The baryon to meson ratio as a function of pT in p+Pb collisions.

The baryon to meson ratio as a function of pT in p+Pb collisions.

The ratios of identified-strange-hadron yield to charged-hadron yields as a function of Nchrec in Pb+Pb photo-nuclear collisions.

The ratios of identified-strange-hadron yield to charged-hadron yields as a function of Nchrec in Pb+Pb photo-nuclear collisions.

The ratios of identified-strange-hadron yield to charged-hadron yields as a function of Nchrec in Pb+Pb photo-nuclear collisions.

The ratios of identified-strange-hadron yield to charged-hadron yields as a function of Nchrec in p+Pb collisions.

The ratios of identified-strange-hadron yield to charged-hadron yields as a function of Nchrec in p+Pb collisions.

Expected (dashed black line) and observed (solid red line) 95% CL exclusion limits on the compressed SUSY simplified model with a bino-like LSP and wino-like NLSPs being considered. These are shown with $\pm1\sigma_\text{exp}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm1\sigma^{\text{SUSY}}_{\text{theory}}$ (red dotted lines) from signal cross-section uncertainties, respectively. The limits set by the ATLAS searches using the soft lepton signature is illustrated by the blue region while the limit imposed by the LEP experiments is shown in grey.

Expected (dashed black line) and observed (solid red line) 95% CL exclusion limits on the compressed SUSY simplified model with a bino-like LSP and wino-like NLSPs being considered. These are shown with $\pm1\sigma_ ext{exp}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm1\sigma^{ ext{SUSY}}_{ ext{theory}}$ (red dotted lines) from signal cross-section uncertainties, respectively. The limits set by the ATLAS searches using the soft lepton signature is illustrated by the blue region while the limit imposed by the LEP experiments is shown in grey.

The expected upper limits on the cross-sections at 95% CL for the simplified SUSY model featuring the production of mass-degenerate pairs of wino-like $\widetilde{\chi}_{2}^{0}$ and $\widetilde{\chi}_{1}^{\pm}$ particles in association with at least two jets. The production modes considered are $\widetilde{\chi}_{2}^{0}\widetilde{\chi}_{1}^{\pm}$, $\widetilde{\chi}_{1}^{\pm}\widetilde{\chi}_{1}^{\mp}$, $\widetilde{\chi}_{2}^{0}\widetilde{\chi}_{2}^{0}$, and $\widetilde{\chi}_{1}^{\pm}\widetilde{\chi}_{1}^{\pm}$.

The observed upper limits on the cross-sections at 95% CL for the simplified SUSY model featuring the production of mass-degenerate pairs of wino-like $\widetilde{\chi}_{2}^{0}$ and $\widetilde{\chi}_{1}^{\pm}$ particles in association with at least two jets. The production modes considered are $\widetilde{\chi}_{2}^{0}\widetilde{\chi}_{1}^{\pm}$, $\widetilde{\chi}_{1}^{\pm}\widetilde{\chi}_{1}^{\mp}$, $\widetilde{\chi}_{2}^{0}\widetilde{\chi}_{2}^{0}$, and $\widetilde{\chi}_{1}^{\pm}\widetilde{\chi}_{1}^{\pm}$.

Truth-level signal acceptances in $\text{SR}_\text{2j}$ with BDT score $\in [0.88, 1.0]$. All of the considered production modes ($\widetilde{\chi}_{2}^{0}\widetilde{\chi}_{1}^{\pm}$, $\widetilde{\chi}_{1}^{\pm}\widetilde{\chi}_{1}^{\mp}$, $\widetilde{\chi}_{2}^{0}\widetilde{\chi}_{2}^{0}$, and $\widetilde{\chi}_{1}^{\pm}\widetilde{\chi}_{1}^{\pm}$) are included. The acceptance is defined as the fraction of accepted events divided by the total number of events in the generator-level signal Monte Carlo simulation. The generator-level selections are the same as the ones at reconstruction level.

Truth-level signal acceptances in $\text{SR}_{\geq\text{3j}}$ with BDT score $\in [0.88, 1.0]$. All of the considered production modes ($\widetilde{\chi}_{2}^{0}\widetilde{\chi}_{1}^{\pm}$, $\widetilde{\chi}_{1}^{\pm}\widetilde{\chi}_{1}^{\mp}$, $\widetilde{\chi}_{2}^{0}\widetilde{\chi}_{2}^{0}$, and $\widetilde{\chi}_{1}^{\pm}\widetilde{\chi}_{1}^{\pm}$) are included. The acceptance is defined as the fraction of accepted events divided by the total number of events in the generator-level signal Monte Carlo simulation. The generator-level selections are the same as the ones at reconstruction level.

Signal efficiencies in $\text{SR}_\text{2j}$ with BDT score $\in [0.88, 1.0]$. All of the considered production modes ($\widetilde{\chi}_{2}^{0}\widetilde{\chi}_{1}^{\pm}$, $\widetilde{\chi}_{1}^{\pm}\widetilde{\chi}_{1}^{\mp}$, $\widetilde{\chi}_{2}^{0}\widetilde{\chi}_{2}^{0}$, and $\widetilde{\chi}_{1}^{\pm}\widetilde{\chi}_{1}^{\pm}$) are included. The efficiency is defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level. The generator-level selections are the same as the ones at reconstruction level.

Signal efficiencies in $\text{SR}_{\geq\text{3j}}$ with BDT score $\in [0.88, 1.0]$. All of the considered production modes ($\widetilde{\chi}_{2}^{0}\widetilde{\chi}_{1}^{\pm}$, $\widetilde{\chi}_{1}^{\pm}\widetilde{\chi}_{1}^{\mp}$, $\widetilde{\chi}_{2}^{0}\widetilde{\chi}_{2}^{0}$, and $\widetilde{\chi}_{1}^{\pm}\widetilde{\chi}_{1}^{\pm}$) are included. The efficiency is defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level. The generator-level selections are the same as the ones at reconstruction level.

Event selection cutflows for signal samples with $m(\tilde\chi^0_2) =100~\text{GeV}$ and $\Delta m(\tilde\chi^0_2 / \tilde\chi^\pm_1,\tilde\chi^0_1) = 0.2~\text{GeV}, 1.0~\text{GeV},$ and $5.0~\text{GeV}$. The first number in the column for each mass point corresponds to the signal event yield after applying the associated cut while the second number in parentheses represents the efficiency with respect to the previous cut. All of the production modes are included. The total cross-section used to obtain the initial number of events ($\sigma$) includes the cuts applied at parton level as described in the main text.

Distribution of $E_{\text{T}}^{\text{miss}}$ in SROS-on-b-$e\mu\mu$. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by a black arrow. The last bin includes the overflow. The `Others' category contains the production of Higgs boson, 3-top, 4-top, and single-top processes. Distributions for SBH signals are overlaid. The bottom panels show the ratio of the observed data to the predicted total background yields. The hatched band includes all statistical and systematic uncertainties.

Distribution of $m_{\text{T}}^{\text{min}}$ in SROS-on-b-$e\mu\mu$. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by a black arrow. The last bin includes the overflow. The `Others' category contains the production of Higgs boson, 3-top, 4-top, and single-top processes. Distributions for SBH signals are overlaid. The bottom panels show the ratio of the observed data to the predicted total background yields. The hatched band includes all statistical and systematic uncertainties.

Distribution of $E_{\text{T}}^{\text{miss}}$ in SRSS-$2\mu$. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by a black arrow. The last bin includes the overflow. The `Others' category contains the production of Higgs boson, 3-top, 4-top, and single-top processes. Distributions for SBH signals are overlaid. The bottom panels show the ratio of the observed data to the predicted total background yields. The hatched band includes all statistical and systematic uncertainties.

Observed ($N_{\text{obs}}$) and expected ($N_{\text{exp}}$) yields after the background-only fit for the flavor-merged inclusive SRs. The third and fourth columns list the 95\% CL upper limits on the visible cross-section ($\sigma_{\text{vis}}^{95}$) and on the number of signal events ($S_\text{obs}^{95}$). The fifth column ($S_\text{exp}^{95}$) shows the 95\% CL upper limit on the number of signal events, given the expected number of background events and its $\pm 1\sigma$ variations. The last two columns indicate the CL$_{\text{b}}$ value, i.e. the confidence level observed for the background-only hypothesis, and the discovery $p$-value ($p(s = 0)$) with its associated statistical significance $Z$. If the observed yield is below the expected yield, the $p$-value is capped at 0.5.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ are considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ are considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ are considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ are considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ are considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ are considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where only $\tilde{e}_{\text{L}}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where only $\tilde{e}_{\text{L}}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where only $\tilde{e}_{\text{L}}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where only $\tilde{e}_{\text{L}}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where only $\tilde{e}_{\text{L}}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where only $\tilde{e}_{\text{L}}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where only $\tilde{\mu}_{\text{L}}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where only $\tilde{\mu}_{\text{L}}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where only $\tilde{\mu}_{\text{L}}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where only $\tilde{\mu}_{\text{L}}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where only $\tilde{\mu}_{\text{L}}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where only $\tilde{\mu}_{\text{L}}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Distribution of $E_{\text{T}}^{\text{miss}}$ in SROS-off-b-$e\mu\mu$. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by a black arrow. The last bin includes the overflow. The `Others' category contains the production of Higgs boson, 3-top, 4-top, and single-top processes. Distributions for SBH signals are overlaid. The bottom panels show the ratio of the observed data to the predicted total background yields. Ratio values outside the graph range are indicated by brown arrows. The hatched band includes all statistical and systematic uncertainties.

Distribution of $m_{\text{T}}^{\text{min}}$ in SROS-off-b-$e\mu\mu$. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by a black arrow. The last bin includes the overflow. The `Others' category contains the production of Higgs boson, 3-top, 4-top, and single-top processes. Distributions for SBH signals are overlaid. The bottom panels show the ratio of the observed data to the predicted total background yields. Ratio values outside the graph range are indicated by brown arrows. The hatched band includes all statistical and systematic uncertainties.

Distribution of $E_{\text{T}}^{\text{miss}}$ in SRSS-$eee$. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by a black arrow. The last bin includes the overflow. The `Others' category contains the production of Higgs boson, 3-top, 4-top, and single-top processes. Distributions for SBH signals are overlaid. The bottom panels show the ratio of the observed data to the predicted total background yields. Ratio values outside the graph range are indicated by brown arrows. The hatched band includes all statistical and systematic uncertainties.

Distribution of $E_{\text{T}}^{\text{miss}}$ in SRSS-$ee\mu$. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by a black arrow. The last bin includes the overflow. The `Others' category contains the production of Higgs boson, 3-top, 4-top, and single-top processes. Distributions for SBH signals are overlaid. The bottom panels show the ratio of the observed data to the predicted total background yields. Ratio values outside the graph range are indicated by brown arrows. The hatched band includes all statistical and systematic uncertainties.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 150 GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 150 GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 150 GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 150 GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 150 GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 150 GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ are considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $\Delta m(\tilde{\chi}^0_3, \tilde{\chi}^0_1)$ vs $\Delta m(\tilde{\ell}_{\text{L}}, \tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100 GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ are considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $\Delta m(\tilde{\chi}^0_3, \tilde{\chi}^0_1)$ vs $\Delta m(\tilde{\ell}_{\text{L}}, \tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100 GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ are considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $\Delta m(\tilde{\chi}^0_3, \tilde{\chi}^0_1)$ vs $\Delta m(\tilde{\ell}_{\text{L}}, \tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100 GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ are considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $\Delta m(\tilde{\chi}^0_3, \tilde{\chi}^0_1)$ vs $\Delta m(\tilde{\ell}_{\text{L}}, \tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100 GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ are considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $\Delta m(\tilde{\chi}^0_3, \tilde{\chi}^0_1)$ vs $\Delta m(\tilde{\ell}_{\text{L}}, \tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100 GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ are considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $\Delta m(\tilde{\chi}^0_3, \tilde{\chi}^0_1)$ vs $\Delta m(\tilde{\ell}_{\text{L}}, \tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100 GeV.

The expected upper limits on the cross-section for each signal point. The gray numbers represent the values. The expected (dashed) and observed (solid) 95% CL exclusion limits are overlaid. An asymptotic approximation is employed in the CL$_{\text{s}}$ calculation instead of the full calculation using pseudo-experiments.

The observed upper limits on the cross-section for each signal point. The gray numbers represent the values. The expected (dashed) and observed (solid) 95% CL exclusion limits are overlaid. An asymptotic approximation is employed in the CL$_{\text{s}}$ calculation instead of the full calculation using pseudo-experiments.

Acceptance for signals with $m(\tilde{\chi}^0_1)=100$ GeV in flavored-merged SRs. The acceptance is given by the ratio of weighted selected events in the SR to the weighted total number of generated events. The selection is based on generator-level particle information.

Acceptance for signals with $m(\tilde{\chi}^0_1)=100$ GeV in flavored-merged SRs. The acceptance is given by the ratio of weighted selected events in the SR to the weighted total number of generated events. The selection is based on generator-level particle information.

Acceptance for signals with $m(\tilde{\chi}^0_1)=100$ GeV in flavored-merged SRs. The acceptance is given by the ratio of weighted selected events in the SR to the weighted total number of generated events. The selection is based on generator-level particle information.

Acceptance for signals with $m(\tilde{\chi}^0_1)=100$ GeV in flavored-merged SRs. The acceptance is given by the ratio of weighted selected events in the SR to the weighted total number of generated events. The selection is based on generator-level particle information.

Acceptance for signals with $m(\tilde{\chi}^0_1)=100$ GeV in flavored-merged SRs. The acceptance is given by the ratio of weighted selected events in the SR to the weighted total number of generated events. The selection is based on generator-level particle information.

Acceptance for signals with $m(\tilde{\chi}^0_1)=100$ GeV in flavored-merged SRs. The acceptance is given by the ratio of weighted selected events in the SR to the weighted total number of generated events. The selection is based on generator-level particle information.

Acceptance for signals with $m(\tilde{\chi}^0_1)=100$ GeV in flavored-merged SRs. The acceptance is given by the ratio of weighted selected events in the SR to the weighted total number of generated events. The selection is based on generator-level particle information.

Efficiencies for signals with $m(\tilde{\chi}^0_1)=100$ GeV in the $m_{3\ell}$ merged SRSFOS and SRSS. The efficiency is defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level. Efficiencies below 0.002% are rounded to 0. The efficiency values are affected by statistical fluctuations due to the limited number of events.

Efficiencies for signals with $m(\tilde{\chi}^0_1)=100$ GeV in the $m_{3\ell}$ merged SRSFOS and SRSS. The efficiency is defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level. Efficiencies below 0.002% are rounded to 0. The efficiency values are affected by statistical fluctuations due to the limited number of events.

Efficiencies for signals with $m(\tilde{\chi}^0_1)=100$ GeV in the $m_{3\ell}$ merged SRSFOS and SRSS. The efficiency is defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level. Efficiencies below 0.002% are rounded to 0. The efficiency values are affected by statistical fluctuations due to the limited number of events.

Efficiencies for signals with $m(\tilde{\chi}^0_1)=100$ GeV in the $m_{3\ell}$ merged SRSFOS and SRSS. The efficiency is defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level. Efficiencies below 0.002% are rounded to 0. The efficiency values are affected by statistical fluctuations due to the limited number of events.

Efficiencies for signals with $m(\tilde{\chi}^0_1)=100$ GeV in the $m_{3\ell}$ merged SRSFOS and SRSS. The efficiency is defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level. Efficiencies below 0.002% are rounded to 0. The efficiency values are affected by statistical fluctuations due to the limited number of events.

Efficiencies for signals with $m(\tilde{\chi}^0_1)=100$ GeV in the $m_{3\ell}$ merged SRSFOS and SRSS. The efficiency is defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level. Efficiencies below 0.002% are rounded to 0. The efficiency values are affected by statistical fluctuations due to the limited number of events.

Efficiencies for signals with $m(\tilde{\chi}^0_1)=100$ GeV in the $m_{3\ell}$ merged SRSFOS and SRSS. The efficiency is defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level. Efficiencies below 0.002% are rounded to 0. The efficiency values are affected by statistical fluctuations due to the limited number of events.

Efficiencies for signals with $m(\tilde{\chi}^0_1)=100$ GeV in the $m_{3\ell}$ merged SRSFOS and SRSS. The efficiency is defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level. Efficiencies below 0.002% are rounded to 0. The efficiency values are affected by statistical fluctuations due to the limited number of events.

Efficiencies for signals with $m(\tilde{\chi}^0_1)=100$ GeV in the $m_{3\ell}$ merged SRSFOS and SRSS. The efficiency is defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level. Efficiencies below 0.002% are rounded to 0. The efficiency values are affected by statistical fluctuations due to the limited number of events.

Efficiencies for signals with $m(\tilde{\chi}^0_1)=100$ GeV in the $m_{3\ell}$ merged SRSFOS and SRSS. The efficiency is defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level. Efficiencies below 0.002% are rounded to 0. The efficiency values are affected by statistical fluctuations due to the limited number of events.

Efficiencies for signals with $m(\tilde{\chi}^0_1)=100$ GeV in the $m_{3\ell}$ merged SRSFOS and SRSS. The efficiency is defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level. Efficiencies below 0.002% are rounded to 0. The efficiency values are affected by statistical fluctuations due to the limited number of events.

Summary of the number of events passing each selection for the $m(\tilde{\ell}_{\text{L}}^{\pm},\tilde{\chi}^0_3,\tilde{\chi}^0_1)=(300, 200, 100)$, $(550, 300, 100)$, $(450, 180, 100)$ GeV signal points, including all production processes. After the initial selections, the table is split into row blocks per inclusive region, and then further for each SR channel. Flavor-binned SRs are shown for SROS-on-b for reference. The generator level selections require to have two or more leptons.

Summary of the number of events passing each selection for the $m(\tilde{\ell}_{\text{L}}^{\pm},\tilde{\chi}^0_3,\tilde{\chi}^0_1)=(300, 200, 100)$, $(550, 300, 100)$, $(450, 180, 100)$ GeV signal points, including all production processes. After the initial selections, the table is split into row blocks per inclusive region, and then further for each SR channel. Flavor-binned SRs are shown for SROS-off-b for reference. The generator level selections require to have two or more leptons.

Summary of the number of events passing each selection for the $m(\tilde{\ell}_{\text{L}}^{\pm},\tilde{\chi}^0_3,\tilde{\chi}^0_1)=(300, 200, 100)$, $(550, 300, 100)$, $(450, 180, 100)$ GeV signal points, including all production processes. After the initial selections, the table is split into row blocks per inclusive region, and then further for each SR channel. Flavor-binned SRs are shown. The generator level selections require to have two or more leptons.

Distributions of the $\mathrm{NN^{SvsB}}$ output for data and the expected background after the likelihood fit in the $SR_{cQu --}$ signal region. The post-fit background expectations are shown as filled histograms, the combined pre-fit background expectations are shown as dashed lines. The signal distribution using the Wilson coefficient values $c_{tu}^{(1)}=0.04$, $c_{Qu}^{(1)}=0.1$, $c_{Qu}^{(8)}=0.1$ is shown with a dotted line, normalized to the same number of events as the background.

Summary of the observed and predicted number of events in the five 2$\ell$ control regions. The background prediction is shown after the combined likelihood fit to data under the signal-plus-background hypothesis across all control regions and signal regions. The uncertainties in the total yields are smaller than the sum in quadrature of the uncertainties in the individual contributions due to anti-correlations resulting from the likelihood fit. Int Conv refers to events with photon conversions in the inner detector, while Mat Conv refers to events with photon conversions in the detector material. QMisID refers to events with charge-misidentified lepton.

Summary of the observed and predicted number of events in the four 3$\ell$ control regions. The background prediction is shown after the combined likelihood fit to data under the signal-plus-background hypothesis across all control regions and signal regions. The uncertainties in the total yields are smaller than the sum in quadrature of the uncertainties in the individual contributions due to anti-correlations resulting from the likelihood fit. Int Conv refers to events with photon conversions in the inner detector, while Mat Conv refers to events with photon conversions in the detector material. QMisID refers to events with charge-misidentified lepton.

Comparison of the observed limits on the three WCs to the limit obtained by the ATLAS Run~1 analysis of events with $b$-tagged jets and a same-sign lepton pair [JHEP10(2015)150]. The cross-section limits from that analysis are converted to the limits on the WCs by using the fitted EFT parametrization. The bounds on the WCs are shown at the 68$\%$ CL (solid) and/or 95$\%$ CL (dashed) levels. For the ATLAS Run~1 analysis only the bounds at 95$\%$ CL are available. The vertical bar represents the SM prediction. The new-physics scale is set to $\Lambda = 1 \, \text{TeV}$.

Observed lower limits at 95$\%$ confidence level on the scale of new physics $\Lambda$ for Wilson coefficient values of 0.01, 1 and $4\pi^2$. The limits are compared with the limits obtained by the ATLAS Run~1 analysis of events with $b$-tagged jets and a same-sign lepton pair.

Observed and expected limits at 95$\%$ confidence level on the cross-section of $\sigma(pp \rightarrow tt)$.

2D likelihood scans of the Wilson coefficients $c_{tu}^{(1)}$ versus $c_{Qu}^{(1)}$. The new-physics scale is set to $\Lambda = 1 \, \text{TeV}$. In the table the $2\Delta$NLL values are shown which correspond to the minimized negative log likelihood for a given Wilson coefficient pair.

2D likelihood scans of the Wilson coefficients $c_{tu}^{(1)}$ versus $c_{Qu}^{(8)}$. The new-physics scale is set to $\Lambda = 1 \, \text{TeV}$. In the table the $2\Delta$NLL values are shown which correspond to the minimized negative log likelihood for a given Wilson coefficient pair.

2D likelihood scans of the Wilson coefficients $c_{Qu}^{(1)}$ versus $c_{Qu}^{(8)}$. The new-physics scale is set to $\Lambda = 1 \, \text{TeV}$. In the table the $2\Delta$NLL values are shown which correspond to the minimized negative log likelihood for a given Wilson coefficient pair.

1D-likelihood scan for $c_{tu}^{(1)}$. The observed and expected limits at 68\% and 95\% confidence level (CL) can be read off by finding the intersection of the likelihood scan curve with the 1$\sigma$ and 2$\sigma$ lines. The new-physics scale is set to $\Lambda = 1 \, \text{TeV}$. In the table the $2\Delta$NLL values are shown which correspond to the minimized negative log likelihood for a given Wilson coefficient value.

1D-likelihood scan for $c_{Qu}^{(1)}$. The observed and expected limits at 68\% and 95\% confidence level (CL) can be read off by finding the intersection of the likelihood scan curve with the 1$\sigma$ and 2$\sigma$ lines. The new-physics scale is set to $\Lambda = 1 \, \text{TeV}$. In the table the $2\Delta$NLL values are shown which correspond to the minimized negative log likelihood for a given Wilson coefficient value.

1D-likelihood scan for $c_{Qu}^{(8)}$. The observed and expected limits at 68\% and 95\% confidence level (CL) can be read off by finding the intersection of the likelihood scan curve with the 1$\sigma$ and 2$\sigma$ lines. The new-physics scale is set to $\Lambda = 1 \, \text{TeV}$. In the table the $2\Delta$NLL values are shown which correspond to the minimized negative log likelihood for a given Wilson coefficient value.

The cutflow table for $N1$ and $N2$ signal samples for different mass points. The samples consist of both $ee$ and $\mu\mu$ final states in equal ratio. Each sample is normalized to a total cross-section of 0.1 pb. The abbreviations used in the table are, SC = Same Charge, SF = Same Flavor.

The cutflow table for $N3$ signal samples for different mass points. The samples consist of both $ee$ and $\mu\mu$ final states in equal ratio. Each sample is normalized to a total cross-section of 10 pb. The abbreviations used in the table are, SS = Same Charge, SF = Same Flavor.

Expected and observed upper limits on the strength of HNL mixing with electron neutrinos

Expected and observed upper limits on the strength of HNL mixing with muon neutrinos

Expected and observed upper limits on the strength of HNL mixing with tau neutrinos

95&percnt; CL expected and observed exclusion limits on the branching ratio of the Higgs boson to dark photons as a function of the &gamma;_d mass for the HAHM model.

95&percnt; CL expected and observed exclusion limits on the branching ratio of the Higgs boson to dark photons as a function of the &gamma;_d mass for the FRVZ model.

90&percnt; CL exclusion limit contours on the branching ratio of the Higgs boson to dark photons as functions of the &gamma;_d mass and kinetic mixing parameter &epsilon; for the HAHM model. These exclusions assume Higgs boson branching fractions to dark photons within a 0.01&percnt; and 10&percnt; range.

90&percnt; CL exclusion limit contours on the branching ratio of the Higgs boson to dark photons as functions of the &gamma;_d mass and kinetic mixing parameter &epsilon; for the FRVZ model. These exclusions assume Higgs boson branching fractions to dark photons within a 0.01&percnt; and 10&percnt; range.

The reconstruction efficiency for &mu;LJ objects produced in the decay of a &gamma;_d into a muon pair. The reconstruction efficiency is shown for different dark photon mass hypotheses generated according to the HAHM signal model. The efficiency is shown as a function of the dark photon p_T.

The reconstruction efficiency for &mu;LJ objects produced in the decay of a &gamma;_d into a muon pair. The reconstruction efficiency is shown for different dark photon mass hypotheses generated according to the FRVZ signal model. The efficiency is shown as a function of the dark photon p_T.

The reconstruction efficiency for &mu;LJ objects produced in the decay of a &gamma;_d into a muon pair. The reconstruction efficiency is shown for different dark photon mass hypotheses generated according to the HAHM signal model. The efficiency is shown as a function of the &Delta;R opening between the decay products of a dark photon.

The reconstruction efficiency for &mu;LJ objects produced in the decay of a &gamma;_d into a muon pair. The reconstruction efficiency is shown for different dark photon mass hypotheses generated according to the FRVZ signal model. The efficiency is shown as a function of the &Delta;R opening between the decay products of a dark photon.

The reconstruction efficiency for &mu;LJ objects produced in the decay of a &gamma;_d into a muon pair. The reconstruction efficiency is shown for a dark photon mass of 0.4 GeV, generated according to the HAHM and FRVZ signal models. The efficiency is shown as a function of the &gamma;_d p_T.

The reconstruction efficiency for &mu;LJ objects produced in the decay of a &gamma;_d into a muon pair. The reconstruction efficiency is shown for a dark photon mass of 0.4 GeV, generated according to the HAHM and FRVZ signal models. The efficiency is shown as a function of the &Delta;R opening between the decay products of a dark photon.

The reconstruction efficiency for eLJ objects produced in the decay of a &gamma;_d into an electron pair. The reconstruction efficiency is shown for different dark photon mass hypotheses generated according to the HAHM signal model. The efficiency is shown as a function of the dark photon p_T.

The reconstruction efficiency for eLJ objects produced in the decay of a &gamma;_d into an electron pair. The reconstruction efficiency is shown for different dark photon mass hypotheses generated according to the FRVZ signal model. The efficiency is shown as a function of the dark photon p_T.

The reconstruction efficiency for eLJ objects produced in the decay of a &gamma;_d into a pair of electrons. The reconstruction efficiency is shown for different dark photon mass hypotheses generated according to the HAHM signal model. The efficiency is shown as a function of the &Delta;R opening between the decay products of a dark photon. The decrease in efficiency, visible at 0.1, is due to the transition between the region of the phase space where eLJs are identified from merged EM showers with two tracks, to the one where eLJs are obtained by the clustering of two resolved electrons.

The reconstruction efficiency for eLJ objects produced in the decay of a &gamma;_d into a pair of electrons. The reconstruction efficiency is shown for different dark photon mass hypotheses generated according to the FRVZ signal model. The efficiency is shown as a function of the &Delta;R opening between the decay products of a dark photon. The decrease in efficiency, visible at 0.1, is due to the transition between the region of the phase space where eLJs are identified from merged EM showers with two tracks, to the one where eLJs are obtained by the clustering of two resolved electrons.

The reconstruction efficiency for eLJ objects produced in the decay of a &gamma;_d into a pair of electrons. The reconstruction efficiency is shown for a dark photon mass of 0.1 GeV, generated according to the HAHM and FRVZ signal models. The efficiency is shown as a function of the &gamma;_d p_T.

The reconstruction efficiency for eLJ objects produced in the decay of a &gamma;_d into a pair of electrons. The reconstruction efficiency is shown for a dark photon mass of 0.1 GeV, generated according to the HAHM and FRVZ signal models. The efficiency is shown as a function of the &Delta;R opening between the decay products of a dark photon.

95&percnt; CL expected and observed exclusion limits on the branching ratio of the Higgs boson to dark photons as a function of the &gamma;_d mass for the HAHM model, obtained from the &mu;LJ&ndash;&mu;LJ signal region.

95&percnt; CL expected and observed exclusion limits on the branching ratio of the Higgs boson to dark photons as a function of the &gamma;_d mass for the FRVZ model, obtained from the &mu;LJ&ndash;&mu;LJ signal region.

95&percnt; CL expected and observed exclusion limits on the branching ratio of the Higgs boson to dark photons as a function of the &gamma;_d mass for the HAHM model, obtained from the &mu;LJ&ndash;eLJ signal region.

95&percnt; CL expected and observed exclusion limits on the branching ratio of the Higgs boson to dark photons as a function of the &gamma;_d mass for the FRVZ model, obtained from the &mu;LJ&ndash;eLJ signal region.

Acceptance times efficiencies (A&times;&varepsilon;) as a function of the &gamma;_d mass for the HAHM process for the three signal regions of the analysis, eLJ-eLJ, eLJ-&mu;LJ and &mu;LJ-&mu;LJ. The decrease of the A&times;&varepsilon; is expected for increasing masses of the &gamma;_d, as its decay products become resolved and are no longer reconstructed as LJs. The local minimum around m_{&gamma;_d}=2 GeV observed for the eLJ-&mu;LJ distribution is expected, as the reconstruction efficiency for eLJs with merged EM showers decreases before the reconstruction of eLJ with two resolved electrons becomes efficient.

Acceptance times efficiencies (A&times;&varepsilon;) as a function of the &gamma;_d mass for the FRVZ process for the three signal regions of the analysis, eLJ-eLJ, eLJ-&mu;LJ and &mu;LJ-&mu;LJ. The decrease of the A&times;&varepsilon; is expected for increasing masses of the &gamma;_d, as its decay products become resolved and are no longer reconstructed as LJs. The local minimum around m_{&gamma;_d}=2 GeV observed for the eLJ-&mu;LJ distribution is expected, as the reconstruction efficiency for eLJs with merged EM showers decreases before the reconstruction of eLJ with two resolved electrons becomes efficient.