Expected (dashed black line) and observed (solid red line) 95% CL exclusion limits on the higgsino simplified model being considered. These are shown with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively. The limits set by the latest ATLAS searches using the soft lepton and disappearing track signatures are illustrated by the blue and green regions, respectively, while the limit imposed by the LEP experiments is shown in gray. The dot-dashed gray line indicates the predicted mass-splitting for the pure higgsino scenario.

Expected (dashed black line) and observed (solid red line) 95% CL exclusion limits on the higgsino simplified model being considered. These are shown with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively. The limits set by the latest ATLAS searches using the soft lepton and disappearing track signatures are illustrated by the blue and green regions, respectively, while the limit imposed by the LEP experiments is shown in gray. The dot-dashed gray line indicates the predicted mass-splitting for the pure higgsino scenario.

Expected (dashed black line) and observed (solid red line) 95% CL exclusion limits on the higgsino simplified model being considered. These are shown with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively. The limits set by the latest ATLAS searches using the soft lepton and disappearing track signatures are illustrated by the blue and green regions, respectively, while the limit imposed by the LEP experiments is shown in gray. The dot-dashed gray line indicates the predicted mass-splitting for the pure higgsino scenario.

Expected (dashed black line) and observed (solid red line) 95% CL exclusion limits on the higgsino simplified model being considered. These are shown with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively. The limits set by the latest ATLAS searches using the soft lepton and disappearing track signatures are illustrated by the blue and green regions, respectively, while the limit imposed by the LEP experiments is shown in gray. The dot-dashed gray line indicates the predicted mass-splitting for the pure higgsino scenario.

Expected (dashed black line) and observed (solid red line) 95% CL exclusion limits on the higgsino simplified model being considered. These are shown with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively. The limits set by the latest ATLAS searches using the soft lepton and disappearing track signatures are illustrated by the blue and green regions, respectively, while the limit imposed by the LEP experiments is shown in gray. The dot-dashed gray line indicates the predicted mass-splitting for the pure higgsino scenario.

Expected (dashed black line) and observed (solid red line) 95% CL exclusion limits on the higgsino simplified model being considered. These are shown with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively. The limits set by the latest ATLAS searches using the soft lepton and disappearing track signatures are illustrated by the blue and green regions, respectively, while the limit imposed by the LEP experiments is shown in gray. The dot-dashed gray line indicates the predicted mass-splitting for the pure higgsino scenario.

Expected (dashed black line) and observed (solid red line) 95% CL exclusion limits on the higgsino simplified model being considered. These are shown with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively. The limits set by the latest ATLAS searches using the soft lepton and disappearing track signatures are illustrated by the blue and green regions, respectively, while the limit imposed by the LEP experiments is shown in gray. The dot-dashed gray line indicates the predicted mass-splitting for the pure higgsino scenario.

Expected (dashed black line) and observed (solid red line) 95% CL exclusion limits on the higgsino simplified model being considered. These are shown with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively. The limits set by the latest ATLAS searches using the soft lepton and disappearing track signatures are illustrated by the blue and green regions, respectively, while the limit imposed by the LEP experiments is shown in gray. The dot-dashed gray line indicates the predicted mass-splitting for the pure higgsino scenario.

Expected (dashed black line) and observed (solid red line) 95% CL exclusion limits on the higgsino simplified model being considered. These are shown with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively. The limits set by the latest ATLAS searches using the soft lepton and disappearing track signatures are illustrated by the blue and green regions, respectively, while the limit imposed by the LEP experiments is shown in gray. The dot-dashed gray line indicates the predicted mass-splitting for the pure higgsino scenario.

Expected (dashed black line) and observed (solid red line) 95% CL exclusion limits on the higgsino simplified model being considered. These are shown with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively. The limits set by the latest ATLAS searches using the soft lepton and disappearing track signatures are illustrated by the blue and green regions, respectively, while the limit imposed by the LEP experiments is shown in gray. The dot-dashed gray line indicates the predicted mass-splitting for the pure higgsino scenario.

Expected (dashed black line) and observed (solid red line) 95% CL exclusion limits on the higgsino simplified model being considered. These are shown with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively. The limits set by the latest ATLAS searches using the soft lepton and disappearing track signatures are illustrated by the blue and green regions, respectively, while the limit imposed by the LEP experiments is shown in gray. The dot-dashed gray line indicates the predicted mass-splitting for the pure higgsino scenario.

Expected and observed CLs values per signal point represented by the grey numbers. The expected (dashed) and observed (solid) 95% CL exclusion limits are overlaid along with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively.

Expected and observed CLs values per signal point represented by the grey numbers. The expected (dashed) and observed (solid) 95% CL exclusion limits are overlaid along with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively.

Expected and observed CLs values per signal point represented by the grey numbers. The expected (dashed) and observed (solid) 95% CL exclusion limits are overlaid along with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively.

Expected and observed CLs values per signal point represented by the grey numbers. The expected (dashed) and observed (solid) 95% CL exclusion limits are overlaid along with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively.

Expected and observed cross-section upper-limit per signal point represented by the grey numbers. The expected (dashed) and observed (solid) 95% CL exclusion limits are overlaid along with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively.

Expected and observed cross-section upper-limit per signal point represented by the grey numbers. The expected (dashed) and observed (solid) 95% CL exclusion limits are overlaid along with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively.

Expected and observed cross-section upper-limit per signal point represented by the grey numbers. The expected (dashed) and observed (solid) 95% CL exclusion limits are overlaid along with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively.

Expected and observed cross-section upper-limit per signal point represented by the grey numbers. The expected (dashed) and observed (solid) 95% CL exclusion limits are overlaid along with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively.

Truth-level signal acceptances for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$) in a SR with the $S(d_0)$ requirement removed. 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, where the signal candidate track is identified as the charged particle with the largest distance between the interaction vertex and the secondary vertex of the higgsino decays.

Truth-level signal acceptances for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$) in a SR with the $S(d_0)$ requirement removed. 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, where the signal candidate track is identified as the charged particle with the largest distance between the interaction vertex and the secondary vertex of the higgsino decays.

Truth-level signal acceptances for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$) in a SR with the $S(d_0)$ requirement removed. 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, where the signal candidate track is identified as the charged particle with the largest distance between the interaction vertex and the secondary vertex of the higgsino decays.

Truth-level signal acceptances for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$) in a SR with the $S(d_0)$ requirement removed. 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, where the signal candidate track is identified as the charged particle with the largest distance between the interaction vertex and the secondary vertex of the higgsino decays.

Truth-level signal acceptances for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$) in a SR with the $S(d_0)$ requirement removed. 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, where the signal candidate track is identified as the charged particle with the largest distance between the interaction vertex and the secondary vertex of the higgsino decays.

Truth-level signal acceptances for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$) in a SR with the $S(d_0)$ requirement removed. 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, where the signal candidate track is identified as the charged particle with the largest distance between the interaction vertex and the secondary vertex of the higgsino decays.

Truth-level signal acceptances for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$) in a SR with the $S(d_0)$ requirement removed. 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, where the signal candidate track is identified as the charged particle with the largest distance between the interaction vertex and the secondary vertex of the higgsino decays.

Truth-level signal acceptances for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$) in a SR with the $S(d_0)$ requirement removed. 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, where the signal candidate track is identified as the charged particle with the largest distance between the interaction vertex and the secondary vertex of the higgsino decays.

Truth-level signal acceptances for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$) in a SR with the $S(d_0)$ requirement removed. 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, where the signal candidate track is identified as the charged particle with the largest distance between the interaction vertex and the secondary vertex of the higgsino decays.

Truth-level signal acceptances for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$) in a SR with the $S(d_0)$ requirement removed. 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, where the signal candidate track is identified as the charged particle with the largest distance between the interaction vertex and the secondary vertex of the higgsino decays.

Truth-level signal acceptances for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$) in a SR with the $S(d_0)$ requirement removed. 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, where the signal candidate track is identified as the charged particle with the largest distance between the interaction vertex and the secondary vertex of the higgsino decays.

Truth-level signal acceptances for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$) in a SR with the $S(d_0)$ requirement removed. 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, where the signal candidate track is identified as the charged particle with the largest distance between the interaction vertex and the secondary vertex of the higgsino decays.

Signal efficiencies in SR-Low for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Signal efficiencies in SR-Low for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Signal efficiencies in SR-Low for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Signal efficiencies in SR-Low for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Signal efficiencies in SR-Low for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Signal efficiencies in SR-Low for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Signal efficiencies in SR-Low for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Signal efficiencies in SR-Low for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Signal efficiencies in SR-Low for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Signal efficiencies in SR-Low for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Signal efficiencies in SR-Low for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Signal efficiencies in SR-Low for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Signal efficiencies in SR-High for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Signal efficiencies in SR-High for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Signal efficiencies in SR-High for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Signal efficiencies in SR-High for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Signal efficiencies in SR-High for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Signal efficiencies in SR-High for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Signal efficiencies in SR-High for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Signal efficiencies in SR-High for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Signal efficiencies in SR-High for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Signal efficiencies in SR-High for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Signal efficiencies in SR-High for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Signal efficiencies in SR-High for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Event selection cutflows for signal samples with $m(\tilde{\chi}_{1}^0)$ = 150 GeV and $\Delta m(\tilde{\chi}_{1}^\pm, \tilde{\chi}_{1}^0)$ = 1.5, 1.0, and 0.75 GeV, including all six production processes ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$). The cross-section used to obtain the initial number of events ($\sigma(\mathrm{n}_{\mathrm{jets}}) \geq 1$) refers to an emission of at least one gluon or quark with $p_{\mathrm{T}} > 50$ GeV at the parton level.

Event selection cutflows for signal samples with $m(\tilde{\chi}_{1}^0)$ = 150 GeV and $\Delta m(\tilde{\chi}_{1}^\pm, \tilde{\chi}_{1}^0)$ = 1.5, 1.0, and 0.75 GeV, including all six production processes ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$). The cross-section used to obtain the initial number of events ($\sigma(\mathrm{n}_{\mathrm{jets}}) \geq 1$) refers to an emission of at least one gluon or quark with $p_{\mathrm{T}} > 50$ GeV at the parton level.

Event selection cutflows for signal samples with $m(\tilde{\chi}_{1}^0)$ = 150 GeV and $\Delta m(\tilde{\chi}_{1}^\pm, \tilde{\chi}_{1}^0)$ = 0.5, 0.35, and 0.25 GeV, including all six production processes ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$). The cross-section used to obtain the initial number of events ($\sigma(\mathrm{n}_{\mathrm{jets}}) \geq 1$) refers to an emission of at least one gluon or quark with $p_{\mathrm{T}} > 50$ GeV at the parton level.

Event selection cutflows for signal samples with $m(\tilde{\chi}_{1}^0)$ = 150 GeV and $\Delta m(\tilde{\chi}_{1}^\pm, \tilde{\chi}_{1}^0)$ = 0.5, 0.35, and 0.25 GeV, including all six production processes ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$). The cross-section used to obtain the initial number of events ($\sigma(\mathrm{n}_{\mathrm{jets}}) \geq 1$) refers to an emission of at least one gluon or quark with $p_{\mathrm{T}} > 50$ GeV at the parton level.

Definition of the tetralepton signal regions.

Definition of the fiducial volumes at particle- and parton-level. Leptons refer exclusively to electrons and muons - they are dressed with additional radiation at particle-level, but not at parton-level.

Definition of the dilepton $t\bar{t}$ validation regions.

Pre-fit distribution of the number of $b$-jets in 2L-$e\mu$-6j2b, this distribution is not used in the fit.

Pre-fit distribution of the DNN output 2L-$e\mu$-6j1b, this distribution is not used in the fit.

Pre-fit distribution of the DNN output 2L-$e\mu$-5j2b, this distribution is not used in the fit.

Pre-fit distribution of the DNN output 2L-$e\mu$-6j2b, this distribution is not used in the fit.

Definition of the tetralepton control region.

Definition of the trilepton fakes control regions.

Pre-fit distribution of jet multiplicity in CR-$t\bar{t}$-e region.

Pre-fit distribution of loose lepton transverse momentum in CR-$t\bar{t}$-$\mu$ region.

Pre-fit distribution of the transverse mass of the trailing lepton and the missing transverse momentum in CR-Z-e region.

Post-fit distribution of jet multiplicity in CR-$t\bar{t}$-e region

Post-fit distribution of loose lepton transverse momentum in CR-$t\bar{t}$-$\mu$ region

Post-fit distribution of the transverse mass of the trailing lepton and the missing transverse momentum in CR-Z-e region

Post-fit distribution of NN output in SR-2L-5j2b region.

Post-fit distribution of NN output in SR-2L-6j1b region.

Post-fit distribution of NN output in SR-2L-6j2b region.

Post-fit distribution of DNN-$t\bar{t}Z$ output in 3L-SR-ttZ region.

Post-fit distribution of DNN-$t\bar{t}Z$ outputt in 3L-SR-tZq region.

Post fit events yields in 3L-SR-WZ region.

Post-fit distribution of NN output in 4L-SR-SF region.

Post-fit distribution of NN output in 4L-SR-DF region.

Post-fit distribution of b-tagger output for leading b-jet in 4L-CR-ZZ region.

Measured values of the background normalizations obtained from the combined fit. The uncertainties include statistical and systematic sources.

Measured $\sigma_{t\bar{t}\text{Z}}$ cross sections obtained from the fits in the different lepton channels. The uncertainties include statistical and systematic sources.

Grouped impact of systematic uncertainties in the combined inclusive fit to data.

Unfolded absolute cross section as a function of $p^{Z}_{T}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 8 top-left).

Unfolded absolute cross section as a function of $p^{Z}_{T}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 8 top-right).

Unfolded normalized cross section as a function of $p^{Z}_{T}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 8 bottom-left).

Unfolded normalized cross section as a function of $p^{Z}_{T}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 8 bottom-right).

Unfolded absolute cross section as a function of $|y^{Z}$| in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 17 top-left and Figure 11 top-left).

Unfolded absolute cross section as a function of $|y^{Z}$| in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 17 top-right).

Unfolded normalized cross section as a function of $|y^{Z}$| in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 17 bottom-left).

Unfolded normalized cross section as a function of $|y^{Z}$| in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 17 bottom-right).

Unfolded absolute cross section as a function of cos $\theta_{Z}^{*}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 18 top-left and Figure 11 top-right).

Unfolded absolute cross section as a function of cos $\theta_{Z}^{*}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 18 top-right).

Unfolded normalized cross section as a function of cos $\theta_{Z}^{*}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 18 bottom-left).

Unfolded normalized cross section as a function of cos $\theta_{Z}^{*}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 18 bottom-right).

Unfolded absolute cross section as a function of $p_{T}^{\mathrm{top}}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 19 top-left and Figure 11 bottom-left).

Unfolded absolute cross section as a function of $p_{T}^{\mathrm{top}}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 19, top-right).

Unfolded normalized cross section as a function of $p_{T}^{\mathrm{top}}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 19, bottom-left).

Unfolded normalized cross section as a function of $p_{T}^{\mathrm{top}}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 19, bottom-right).

Unfolded absolute cross section as a function of $p_{T}^{t\bar{t}}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 20 top-left and Figure 11 bottom-right).

Unfolded absolute cross section as a function of $p_{T}^{t\bar{t}}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 20, top-right).

Unfolded normalized cross section as a function of $p_{T}^{t\bar{t}}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 20, bottom-left)

Unfolded normalized cross section as a function of $p_{T}^{t\bar{t}}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 20, bottom-right)

Unfolded absolute cross section as a function of $|\Delta\Phi(t\bar{t}, Z)|/\pi$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 21 top-left and Figure 12 top-left).

Unfolded absolute cross section as a function of $|\Delta\Phi(t\bar{t}, Z)|/\pi$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 21, top-right).

Unfolded normalized cross section as a function of $|\Delta\Phi(t\bar{t}, Z)|/\pi$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 21, bottom-left).

Unfolded normalized cross section as a function of $|\Delta\Phi(t\bar{t}, Z)|/\pi$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 21, top-right).

Unfolded absolute cross section as a function of $m^{t\bar{t}Z}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 22 top-left and Figure 12 bottom-left).

Unfolded absolute cross section as a function of $m^{t\bar{t}Z}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 22, top-right).

Unfolded normalized cross section as a function of $m^{t\bar{t}Z}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 22, bottom-left).

Unfolded normalized cross section as a function of $m^{t\bar{t}Z}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 22, bottom-right).

Unfolded absolute cross section as a function of $m^{t\bar{t}}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 23 top-left and Figure 12 bottom-right).

Unfolded absolute cross section as a function of $m^{t\bar{t}}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 23, top-right).

Unfolded normalized cross section as a function of $m^{t\bar{t}}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 23, bottom-left).

Unfolded normalized cross section as a function of $m^{t\bar{t}}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 23, bottom-right).

Unfolded absolute cross section as a function of $|y^{t\bar{t}Z}|$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 24 top-left and Figure 12 top-right).

Unfolded absolute cross section as a function of $|y^{t\bar{t}Z}|$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 24, top-right).

Unfolded normalized cross section as a function of $|y^{t\bar{t}Z}|$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 24, bottom-left).

Unfolded normalized cross section as a function of $|y^{t\bar{t}Z}|$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 24, bottom-right).

Unfolded absolute cross section as a function of $H_{\text{T}}^{\text{l}}$ in the trilepton channel at particle-level (Figure 25 top-left and Figure 9 top-left).

Unfolded absolute cross section as a function of $H_{\text{T}}^{\text{l}}$ in the trilepton channel at parton-level (Figure 25 top-right).

Unfolded normalized cross section as a function of $H_{\text{T}}^{\text{l}}$ in the trilepton channel at particle-level (Figure 25 bottom-left).

Unfolded normalized cross section as a function of $H_{\text{T}}^{\text{l}}$ in the trilepton channel at parton-level (Figure 25 bottom-right).

Unfolded absolute cross section as a function of $|\Delta\Phi(Z, t_{lep})|/\pi$ in the trilepton channel at particle-level (Figure 26 top-left and Figure 10 bottom-left).

Unfolded absolute cross section as a function of $|\Delta\Phi(Z, t_{lep})|/\pi$ in the trilepton channel at parton-level (Figure 26 top-right).

Unfolded normalized cross section as a function of $|\Delta\Phi(Z, t_{lep})|/\pi$ in the trilepton channel at particle-level (Figure 26 bottom-left).

Unfolded normalized cross section as a function of $|\Delta\Phi(Z, t_{lep})|/\pi$ in the trilepton channel at parton-level (Figure 26 bottom-right).

Unfolded absolute cross section as a function of $|\Delta y(Z, t_{lep})|$ in the trilepton channel at particle-level (Figure 27 top-left and Figure 10 bottom-right).

Unfolded absolute cross section as a function of $|\Delta y(Z, t_{lep})|$ in the trilepton channel at parton-level (Figure 27 top-right).

Unfolded normalized cross section as a function of $|\Delta y(Z, t_{lep})|$ in the trilepton channel at particle-level (Figure 27 bottom-left).

Unfolded normalized cross section as a function of $|\Delta y(Z, t_{lep})|$ in the trilepton channel at parton-level (Figure 27 bottom-right).

Unfolded absolute cross section as a function of $p_{\text{T}}^{\ell, non-Z}$ in the trilepton channel at particle-level (Figure 28 top-left and Figure 10 top-left).

Unfolded absolute cross section as a function of $p_{\text{T}}^{\ell, non-Z}$ in the trilepton channel at parton-level (Figure 28 top-right).

Unfolded normalized cross section as a function of $p_{\text{T}}^{\ell, non-Z}$ in the trilepton channel at particle-level (Figure 28 bottom-left).

Unfolded normalized cross section as a function of $p_{\text{T}}^{\ell, non-Z}$ in the trilepton channel at parton-level (Figure 28 bottom-right).

Unfolded absolute cross section as a function of $N_{\text{jets}}$ in the trilepton channel at particle-level (Figure 29 left and Figure 9 bottom-left).

Unfolded normalized cross section as a function of $N_{\text{jets}}$ in the trilepton channel at particle-level (Figure 29 right).

Unfolded absolute cross section as a function of $H_{\text{T}}^{\text{l}}$ in the tetralepton channel at particle-level (Figure 30 top-left and Figure 9 top-right).

Unfolded absolute cross section as a function of $H_{\text{T}}^{\text{l}}$ in the tetralepton channel at parton-level (Figure 30 top-right).

Unfolded normalized cross section as a function of $H_{\text{T}}^{\text{l}}$ in the tetralepton channel at particle-level (Figure 30 bottom-left).

Unfolded normalized cross section as a function of $H_{\text{T}}^{\text{l}}$ in the tetralepton channel at parton-level (Figure 30 bottom-right).

Unfolded absolute cross section as a function of $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ in the tetralepton channel at particle-level (Figure 31 top-left and Figure 10 top-right).

Unfolded absolute cross section as a function of $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ in the tetralepton channel at parton-level (Figure 31 top-right).

Unfolded normalized cross section as a function of $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ in the tetralepton channel at particle-level (Figure 31 bottom-left).

Unfolded normalized cross section as a function of $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ in the tetralepton channel at parton-level (Figure 31 bottom-right).

Unfolded absolute cross section as a function of $N_{\text{jets}}$ in the tetralepton channel at particle-level (Figure 32 left and Figure 9 bottom-right).

Unfolded normalized cross section as a function of $N_{\text{jets}}$ in the tetralepton channel at particle-level (Figure 32 right).

Bootstrap replicas (0-499) for data in all regions used in inclusive cross section measurement. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (500-999) for data in all regions used in inclusive cross section measurement. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (0-499) for data, variable $|\Delta\Phi(t\bar{t}, Z)|/\pi$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (500-999) for data, variable $|\Delta\Phi(t\bar{t}, Z)|/\pi$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (0-499) for data, variable $|\Delta\Phi(Z, t_{lep})|/\pi$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (500-999) for data, variable $|\Delta\Phi(Z, t_{lep})|/\pi$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (0-499) for data, variable $m^{t\bar{t}}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (500-999) for data, variable $m^{t\bar{t}}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (0-499) for data, variable $N_{\text{jets}}$ in $3\ell$ channel. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (500-999) for data, variable $N_{\text{jets}}$ in $3\ell$ channel. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (0-499) for data, variable $|y^{t\bar{t}Z}|$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (500-999) for data, variable $|y^{t\bar{t}Z}|$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (0-499) for data, variable $H_{\text{T}}^{\text{l}}$ in $3\ell$ channel. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (500-999) for data, variable $H_{\text{T}}^{\text{l}}$ in $3\ell$ channel. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (0-499) for data, variable $y^{Z}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (500-999) for data, variable $y^{Z}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (0-499) for data, variable $p_{T}^{\mathrm{top}}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (500-999) for data, variable $p_{T}^{\mathrm{top}}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (0-499) for data, variable cos $\theta^{*}_{Z}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (500-999) for data, variable cos $\theta^{*}_{Z}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (0-499) for data, variable $p_{\text{T}}^{\ell, non-Z}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (500-999) for data, variable $p_{\text{T}}^{\ell, non-Z}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (0-499) for data, variable $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (500-999) for data, variable $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (0-499) for data, variable $H_{\text{T}}^{\text{l}}$ in $4\ell$ channel. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (500-999) for data, variable $H_{\text{T}}^{\text{l}}$ in $4\ell$ channel. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (0-499) for data, variable $m^{t\bar{t}Z}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (500-999) for data, variable $m^{t\bar{t}Z}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (0-499) for data, variable $N_{\text{jets}}$ in $4\ell$ channel. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (500-999) for data, variable $N_{\text{jets}}$ in $4\ell$ channel. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (0-499) for data, variable $|\Delta y(Z, t_{lep})|$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (500-999) for data, variable $|\Delta y(Z, t_{lep})|$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (0-499) for data, variable $p^{Z}_{T}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (500-999) for data, variable $p^{Z}_{T}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (0-499) for data, variable $p_{T}^{t\bar{t}}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (500-999) for data, variable $p_{T}^{t\bar{t}}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Parton-level acceptance and selection efficiency histograms for $|\Delta\Phi(Z, t_{lep})|/\pi$ variable.

Parton-level acceptance and selection efficiency histograms for $|\Delta y(Z, t_{lep})|$ variable.

Parton-level acceptance and selection efficiency histograms for $H_{\text{T}}^{\text{ l}}$ variable.

Parton-level acceptance and selection efficiency histograms for $p_{\text{T}}^{\ell, non-Z}$ variable.

Parton-level acceptance and selection efficiency histograms for $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ variable.

Parton-level acceptance and selection efficiency histograms for $H_{\text{T}}^{\text{ l}}$ variable.

Parton-level acceptance and selection efficiency histograms for cos $\theta_{Z}^{*}$ variable.

Parton-level acceptance and selection efficiency histograms for $p^{Z}_{T}$ variable.

Parton-level acceptance and selection efficiency histograms for $|y^{Z}$| variable.

Parton-level acceptance and selection efficiency histograms for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable.

Parton-level acceptance and selection efficiency histograms for $m^{t\bar{t}}$ variable.

Parton-level acceptance and selection efficiency histograms for $m^{t\bar{t}Z}$ variable.

Parton-level acceptance and selection efficiency histograms for $p_{T}^{\mathrm{top}}$ variable.

Parton-level acceptance and selection efficiency histograms for $p_{T}^{t\bar{t}}$ variable.

Parton-level acceptance and selection efficiency histograms for $|y^{t\bar{t}Z}|$ variable.

Particle-level acceptance and selection efficiency histograms for $|\Delta\Phi(Z, t_{lep})|/\pi$ variable.

Particle-level acceptance and selection efficiency histograms for $|\Delta y(Z, t_{lep})|$ variable.

Particle-level acceptance and selection efficiency histograms for $H_{\text{T}}^{\text{ l}}$ variable.

Particle-level acceptance and selection efficiency histograms for $N_{\text{jets}}$ variable.

Particle-level acceptance and selection efficiency histograms for $p_{\text{T}}^{\ell, non-Z}$ variable.

Particle-level acceptance and selection efficiency histograms for $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ variable.

Particle-level acceptance and selection efficiency histograms for $H_{\text{T}}^{\text{ l}}$ variable.

Particle-level acceptance and selection efficiency histograms for $N_{\text{jets}}$ variable.

Particle-level acceptance and selection efficiency histograms for cos $\theta_{Z}^{*}$ variable.

Particle-level acceptance and selection efficiency histograms for $p^{Z}_{T}$ variable.

Particle-level acceptance and selection efficiency histograms for $|y^{Z}$| variable.

Particle-level acceptance and selection efficiency histograms for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable.

Particle-level acceptance and selection efficiency histograms for $m^{t\bar{t}}$ variable.

Particle-level acceptance and selection efficiency histograms for $m^{t\bar{t}Z}$ variable.

Particle-level acceptance and selection efficiency histograms for $p_{T}^{\mathrm{top}}$ variable.

Particle-level acceptance and selection efficiency histograms for $p_{T}^{t\bar{t}}$ variable.

Particle-level acceptance and selection efficiency histograms for $|y^{t\bar{t}Z}|$ variable.

Migration matrix for cos $\theta_{Z}^{*}$ variable at particle-level in region SR-3L-ttZ.

Migration matrix for cos $\theta_{Z}^{*}$ variable at particle-level in region SR-3L-tZq.

Migration matrix for cos $\theta_{Z}^{*}$ variable at particle-level in region SR-3L-WZ.

Migration matrix for cos $\theta_{Z}^{*}$ variable at particle-level in region SR-4L-DF.

Migration matrix for cos $\theta_{Z}^{*}$ variable at particle-level in region SR-4L-SF.

Migration matrix for cos $\theta_{Z}^{*}$ variable at particle-level in region CR-4L-ZZ.

Migration matrix for cos $\theta_{Z}^{*}$ variable at parton-level in region SR-3L-ttZ.

Migration matrix for cos $\theta_{Z}^{*}$ variable at parton-level in region SR-3L-tZq.

Migration matrix for cos $\theta_{Z}^{*}$ variable at parton-level in region SR-3L-WZ.

Migration matrix for cos $\theta_{Z}^{*}$ variable at parton-level in region SR-4L-DF.

Migration matrix for cos $\theta_{Z}^{*}$ variable at parton-level in region SR-4L-SF.

Migration matrix for cos $\theta_{Z}^{*}$ variable at parton-level in region CR-4L-ZZ.

Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at particle-level in region SR-3L-ttZ.

Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at particle-level in region SR-3L-tZq.

Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at particle-level in region SR-3L-WZ.

Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at particle-level in region SR-4L-DF.

Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at particle-level in region SR-4L-SF.

Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at particle-level in region CR-4L-ZZ.

Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at parton-level in region SR-3L-ttZ.

Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at parton-level in region SR-3L-tZq.

Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at parton-level in region SR-3L-WZ.

Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at parton-level in region SR-4L-DF.

Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at parton-level in region SR-4L-SF.

Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at parton-level in region CR-4L-ZZ.

Migration matrix for $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ variable at particle-level in region SR-4L-DF.

Migration matrix for $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ variable at particle-level in region SR-4L-SF.

Migration matrix for $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ variable at particle-level in region CR-4L-ZZ.

Migration matrix for $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ variable at parton-level in region SR-4L-DF.

Migration matrix for $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ variable at parton-level in region SR-4L-SF.

Migration matrix for $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ variable at parton-level in region CR-4L-ZZ.

Migration matrix for $|\Delta\Phi(Z, t_{lep})|/\pi$ variable at particle-level in region SR-3L-ttZ.

Migration matrix for $|\Delta\Phi(Z, t_{lep})|/\pi$ variable at particle-level in region SR-3L-tZq.

Migration matrix for $|\Delta\Phi(Z, t_{lep})|/\pi$ variable at particle-level in region SR-3L-WZ.

Migration matrix for $|\Delta\Phi(Z, t_{lep})|/\pi$ variable at parton-level in region SR-3L-ttZ.

Migration matrix for $|\Delta\Phi(Z, t_{lep})|/\pi$ variable at parton-level in region SR-3L-tZq.

Migration matrix for $|\Delta\Phi(Z, t_{lep})|/\pi$ variable at parton-level in region SR-3L-WZ.

Migration matrix for $|\Delta y(Z, t_{lep})|$ variable at particle-level in region SR-3L-ttZ.

Migration matrix for $|\Delta y(Z, t_{lep})|$ variable at particle-level in region SR-3L-tZq.

Migration matrix for $|\Delta y(Z, t_{lep})|$ variable at particle-level in region SR-3L-WZ.

Migration matrix for $|\Delta y(Z, t_{lep})|$ variable at parton-level in region SR-3L-ttZ.

Migration matrix for $|\Delta y(Z, t_{lep})|$ variable at parton-level in region SR-3L-tZq.

Migration matrix for $|\Delta y(Z, t_{lep})|$ variable at parton-level in region SR-3L-WZ.

Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at particle-level in region SR-4L-DF.

Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at particle-level in region SR-4L-SF.

Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at particle-level in region CR-4L-ZZ.

Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at parton-level in region SR-4L-DF.

Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at parton-level in region SR-4L-SF.

Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at parton-level in region CR-4L-ZZ.

Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at particle-level in region SR-3L-ttZ.

Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at particle-level in region SR-3L-tZq.

Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at particle-level in region SR-3L-WZ.

Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at parton-level in region SR-3L-ttZ.

Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at parton-level in region SR-3L-tZq.

Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at parton-level in region SR-3L-WZ.

Migration matrix for $m^{t\bar{t}Z}$ variable at particle-level in region SR-3L-ttZ.

Migration matrix for $m^{t\bar{t}Z}$ variable at particle-level in region SR-3L-tZq.

Migration matrix for $m^{t\bar{t}Z}$ variable at particle-level in region SR-3L-WZ.

Migration matrix for $m^{t\bar{t}Z}$ variable at particle-level in region SR-4L-DF.

Migration matrix for $m^{t\bar{t}Z}$ variable at particle-level in region SR-4L-SF.

Migration matrix for $m^{t\bar{t}Z}$ variable at particle-level in region CR-4L-ZZ.

Migration matrix for $m^{t\bar{t}Z}$ variable at parton-level in region SR-3L-ttZ.

Migration matrix for $m^{t\bar{t}Z}$ variable at parton-level in region SR-3L-tZq.

Migration matrix for $m^{t\bar{t}Z}$ variable at parton-level in region SR-3L-WZ.

Migration matrix for $m^{t\bar{t}Z}$ variable at parton-level in region SR-4L-DF.

Migration matrix for $m^{t\bar{t}Z}$ variable at parton-level in region SR-4L-SF.

Migration matrix for $m^{t\bar{t}Z}$ variable at parton-level in region CR-4L-ZZ.

Migration matrix for $m^{t\bar{t}}$ variable at particle-level in region SR-3L-ttZ.

Migration matrix for $m^{t\bar{t}}$ variable at particle-level in region SR-3L-tZq.

Migration matrix for $m^{t\bar{t}}$ variable at particle-level in region SR-3L-WZ.

Migration matrix for $m^{t\bar{t}}$ variable at particle-level in region SR-4L-DF.

Migration matrix for $m^{t\bar{t}}$ variable at particle-level in region SR-4L-SF.

Migration matrix for $m^{t\bar{t}}$ variable at particle-level in region CR-4L-ZZ.

Migration matrix for $m^{t\bar{t}}$ variable at parton-level in region SR-3L-ttZ.

Migration matrix for $m^{t\bar{t}}$ variable at parton-level in region SR-3L-tZq.

Migration matrix for $m^{t\bar{t}}$ variable at parton-level in region SR-3L-WZ.

Migration matrix for $m^{t\bar{t}}$ variable at parton-level in region SR-4L-DF.

Migration matrix for $m^{t\bar{t}}$ variable at parton-level in region SR-4L-SF.

Migration matrix for $m^{t\bar{t}}$ variable at parton-level in region CR-4L-ZZ.

Migration matrix for $N_{\text{jets}}$ variable at particle-level in region SR-4L-DF.

Migration matrix for $N_{\text{jets}}$ variable at particle-level in region SR-4L-SF.

Migration matrix for $N_{\text{jets}}$ variable at particle-level in region CR-4L-ZZ.

Migration matrix for $N_{\text{jets}}$ variable at particle-level in region SR-3L-ttZ.

Migration matrix for $N_{\text{jets}}$ variable at particle-level in region SR-3L-tZq.

Migration matrix for $N_{\text{jets}}$ variable at particle-level in region SR-3L-WZ.

Migration matrix for $p^{Z}_{T}$ variable at particle-level in region SR-3L-ttZ.

Migration matrix for $p^{Z}_{T}$ variable at particle-level in region SR-3L-tZq.

Migration matrix for $p^{Z}_{T}$ variable at particle-level in region SR-3L-WZ.

Migration matrix for $p^{Z}_{T}$ variable at particle-level in region SR-4L-DF.

Migration matrix for $p^{Z}_{T}$ variable at particle-level in region SR-4L-SF.

Migration matrix for $p^{Z}_{T}$ variable at particle-level in region CR-4L-ZZ.

Migration matrix for $p^{Z}_{T}$ variable at parton-level in region SR-3L-ttZ.

Migration matrix for $p^{Z}_{T}$ variable at parton-level in region SR-3L-tZq.

Migration matrix for $p^{Z}_{T}$ variable at parton-level in region SR-3L-WZ.

Migration matrix for $p^{Z}_{T}$ variable at parton-level in region SR-4L-DF.

Migration matrix for $p^{Z}_{T}$ variable at parton-level in region SR-4L-SF.

Migration matrix for $p^{Z}_{T}$ variable at parton-level in region CR-4L-ZZ.

Migration matrix for $p_{T}^{\mathrm{top}}$ variable at particle-level in region SR-3L-ttZ.

Migration matrix for $p_{T}^{\mathrm{top}}$ variable at particle-level in region SR-3L-tZq.

Migration matrix for $p_{T}^{\mathrm{top}}$ variable at particle-level in region SR-3L-WZ.

Migration matrix for $p_{T}^{\mathrm{top}}$ variable at particle-level in region SR-4L-DF.

Migration matrix for $p_{T}^{\mathrm{top}}$ variable at particle-level in region SR-4L-SF.

Migration matrix for $p_{T}^{\mathrm{top}}$ variable at particle-level in region CR-4L-ZZ.

Migration matrix for $p_{T}^{\mathrm{top}}$ variable at parton-level in region SR-3L-ttZ.

Migration matrix for $p_{T}^{\mathrm{top}}$ variable at parton-level in region SR-3L-tZq.

Migration matrix for $p_{T}^{\mathrm{top}}$ variable at parton-level in region SR-3L-WZ.

Migration matrix for $p_{T}^{\mathrm{top}}$ variable at parton-level in region SR-4L-DF.

Migration matrix for $p_{T}^{\mathrm{top}}$ variable at parton-level in region SR-4L-SF.

Migration matrix for $p_{T}^{\mathrm{top}}$ variable at parton-level in region CR-4L-ZZ.

Migration matrix for $p_{T}^{t\bar{t}}$ variable at particle-level in region SR-3L-ttZ.

Migration matrix for $p_{T}^{t\bar{t}}$ variable at particle-level in region SR-3L-tZq.

Migration matrix for $p_{T}^{t\bar{t}}$ variable at particle-level in region SR-3L-WZ.

Migration matrix for $p_{T}^{t\bar{t}}$ variable at particle-level in region SR-4L-DF.

Migration matrix for $p_{T}^{t\bar{t}}$ variable at particle-level in region SR-4L-SF.

Migration matrix for $p_{T}^{t\bar{t}}$ variable at particle-level in region CR-4L-ZZ.

Migration matrix for $p_{T}^{t\bar{t}}$ variable at parton-level in region SR-3L-ttZ.

Migration matrix for $p_{T}^{t\bar{t}}$ variable at parton-level in region SR-3L-tZq.

Migration matrix for $p_{T}^{t\bar{t}}$ variable at parton-level in region SR-3L-WZ.

Migration matrix for $p_{T}^{t\bar{t}}$ variable at parton-level in region SR-4L-DF.

Migration matrix for $p_{T}^{t\bar{t}}$ variable at parton-level in region SR-4L-SF.

Migration matrix for $p_{T}^{t\bar{t}}$ variable at parton-level in region CR-4L-ZZ.

Migration matrix for $p_{\text{T}}^{\ell, non-Z}$ variable at particle-level in region SR-3L-ttZ.

Migration matrix for $p_{\text{T}}^{\ell, non-Z}$ variable at particle-level in region SR-3L-tZq.

Migration matrix for $p_{\text{T}}^{\ell, non-Z}$ variable at particle-level in region SR-3L-WZ.

Migration matrix for $p_{\text{T}}^{\ell, non-Z}$ variable at parton-level in region SR-3L-ttZ.

Migration matrix for $p_{\text{T}}^{\ell, non-Z}$ variable at parton-level in region SR-3L-tZq.

Migration matrix for $p_{\text{T}}^{\ell, non-Z}$ variable at parton-level in region SR-3L-WZ.

Migration matrix for $|y^{Z}$| variable at particle-level in region SR-3L-ttZ.

Migration matrix for $|y^{Z}$| variable at particle-level in region SR-3L-tZq.

Migration matrix for $|y^{Z}$| variable at particle-level in region SR-3L-WZ.

Migration matrix for $|y^{Z}$| variable at particle-level in region SR-4L-DF.

Migration matrix for $|y^{Z}$| variable at particle-level in region SR-4L-SF.

Migration matrix for $|y^{Z}$| variable at particle-level in region CR-4L-ZZ.

Migration matrix for $|y^{Z}$| variable at parton-level in region SR-3L-ttZ.

Migration matrix for $|y^{Z}$| variable at parton-level in region SR-3L-tZq.

Migration matrix for $|y^{Z}$| variable at parton-level in region SR-3L-WZ.

Migration matrix for $|y^{Z}$| variable at parton-level in region SR-4L-DF.

Migration matrix for $|y^{Z}$| variable at parton-level in region SR-4L-SF.

Migration matrix for $|y^{Z}$| variable at parton-level in region CR-4L-ZZ.

Migration matrix for $|y^{t\bar{t}Z}|$ variable at particle-level in region SR-3L-ttZ.

Migration matrix for $|y^{t\bar{t}Z}|$ variable at particle-level in region SR-3L-tZq.

Migration matrix for $|y^{t\bar{t}Z}|$ variable at particle-level in region SR-3L-WZ.

Migration matrix for $|y^{t\bar{t}Z}|$ variable at particle-level in region SR-4L-DF.

Migration matrix for $|y^{t\bar{t}Z}|$ variable at particle-level in region SR-4L-SF.

Migration matrix for $|y^{t\bar{t}Z}|$ variable at particle-level in region CR-4L-ZZ.

Migration matrix for $|y^{t\bar{t}Z}|$ variable at parton-level in region SR-3L-ttZ.

Migration matrix for $|y^{t\bar{t}Z}|$ variable at parton-level in region SR-3L-tZq.

Migration matrix for $|y^{t\bar{t}Z}|$ variable at parton-level in region SR-3L-WZ.

Migration matrix for $|y^{t\bar{t}Z}|$ variable at parton-level in region SR-4L-DF.

Migration matrix for $|y^{t\bar{t}Z}|$ variable at parton-level in region SR-4L-SF.

Migration matrix for $|y^{t\bar{t}Z}|$ variable at parton-level in region CR-4L-ZZ.

Covariance matrix for absolute cross section as a function of $p_{T}^{\mathrm{top}}$ at particle-level.

Covariance matrix for normalized cross section as a function of $p_{T}^{\mathrm{top}}$ at particle-level.

Covariance matrix for absolute cross section as a function of $p_{T}^{\mathrm{top}}$ at parton-level.

Covariance matrix for normalized cross section as a function of $p_{T}^{\mathrm{top}}$ at parton-level.

Covariance matrix for absolute cross section as a function of $p_{T}^{t\bar{t}}$ at particle-level.

Covariance matrix for normalized cross section as a function of $p_{T}^{t\bar{t}}$ at particle-level.

Covariance matrix for absolute cross section as a function of $p_{T}^{t\bar{t}}$ at parton-level.

Covariance matrix for normalized cross section as a function of $p_{T}^{t\bar{t}}$ at parton-level.

Covariance matrix for absolute cross section as a function of $|\Delta\Phi(t\bar{t}, Z)|/\pi$ at particle-level.

Covariance matrix for normalized cross section as a function of $|\Delta\Phi(t\bar{t}, Z)|/\pi$ at particle-level.

Covariance matrix for absolute cross section as a function of $|\Delta\Phi(t\bar{t}, Z)|/\pi$ at parton-level.

Covariance matrix for normalized cross section as a function of $|\Delta\Phi(t\bar{t}, Z)|/\pi$ at parton-level.

Covariance matrix for absolute cross section as a function of $m^{t\bar{t}Z}$ at particle-level.

Covariance matrix for normalized cross section as a function of $m^{t\bar{t}Z}$ at particle-level.

Covariance matrix for absolute cross section as a function of $m^{t\bar{t}Z}$ at parton-level.

Covariance matrix for normalized cross section as a function of $m^{t\bar{t}Z}$ at parton-level.

Covariance matrix for absolute cross section as a function of $m^{t\bar{t}}$ at particle-level.

Covariance matrix for normalized cross section as a function of $m^{t\bar{t}}$ at particle-level.

Covariance matrix for absolute cross section as a function of $m^{t\bar{t}}$ at parton-level.

Covariance matrix for normalized cross section as a function of $m^{t\bar{t}}$ at parton-level.

Covariance matrix for absolute cross section as a function of $|y^{t\bar{t}Z}|$ at particle-level.

Covariance matrix for normalized cross section as a function of $|y^{t\bar{t}Z}|$ at particle-level.

Covariance matrix for absolute cross section as a function of $|y^{t\bar{t}Z}|$ at parton-level.

Covariance matrix for normalized cross section as a function of $|y^{t\bar{t}Z}|$ at parton-level.

Covariance matrix for absolute cross section as a function of cos $\theta_{Z}^{*}$ at particle-level.

Covariance matrix for normalized cross section as a function of cos $\theta_{Z}^{*}$ at particle-level.

Covariance matrix for absolute cross section as a function of cos $\theta_{Z}^{*}$ at parton-level.

Covariance matrix for normalized cross section as a function of cos $\theta_{Z}^{*}$ at parton-level.

Covariance matrix for absolute cross section as a function of $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ at particle-level.

Covariance matrix for normalized cross section as a function of $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ at particle-level.

Covariance matrix for absolute cross section as a function of $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ at parton-level.

Covariance matrix for normalized cross section as a function of $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ at parton-level.

Covariance matrix for absolute cross section as a function of $|\Delta\Phi(Z, t_{lep})|/\pi$ at particle-level.

Covariance matrix for normalized cross section as a function of $|\Delta\Phi(Z, t_{lep})|/\pi$ at particle-level.

Covariance matrix for absolute cross section as a function of $|\Delta\Phi(Z, t_{lep})|/\pi$ at parton-level.

Covariance matrix for normalized cross section as a function of $|\Delta\Phi(Z, t_{lep})|/\pi$ at parton-level.

Covariance matrix for absolute cross section as a function of $|\Delta y(Z, t_{lep})|$ at particle-level.

Covariance matrix for normalized cross section as a function of $|\Delta y(Z, t_{lep})|$ at particle-level.

Covariance matrix for absolute cross section as a function of $|\Delta y(Z, t_{lep})|$ at parton-level.

Covariance matrix for normalized cross section as a function of $|\Delta y(Z, t_{lep})|$ at parton-level.

Covariance matrix for absolute cross section as a function of $H_{\text{T}}^{\text{l}}$ at in the tetralepton channel particle-level.

Covariance matrix for normalized cross section as a function of $H_{\text{T}}^{\text{l}}$ at in the tetralepton channel particle-level.

Covariance matrix for absolute cross section as a function of $H_{\text{T}}^{\text{l}}$ at in the tetralepton channel parton-level.

Covariance matrix for normalized cross section as a function of $H_{\text{T}}^{\text{l}}$ in the tetralepton channel at parton-level.

Covariance matrix for absolute cross section as a function of $H_{\text{T}}^{\text{l}}$ in the trilepton channel at particle-level.

Covariance matrix for normalized cross section as a function of $H_{\text{T}}^{\text{l}}$ in the trilepton channel at particle-level.

Covariance matrix for absolute cross section as a function of $H_{\text{T}}^{\text{l}}$ in the trilepton channel at parton-level.

Covariance matrix for normalized cross section as a function of $H_{\text{T}}^{\text{l}}$ in the trilepton channel at parton-level.

Covariance matrix for absolute cross section as a function of $N_{\text{jets}}$ in the tetralepton channel at particle-level.

Covariance matrix for normalized cross section as a function of $N_{\text{jets}}$ in the tetralepton channel at particle-level.

Covariance matrix for absolute cross section as a function of $N_{\text{jets}}$ in the trilepton channel at particle-level.

Covariance matrix for normalized cross section as a function of $N_{\text{jets}}$ in the trilepton channel at particle-level.

Covariance matrix for absolute cross section as a function of $p^{Z}_{T}$ at particle-level.

Covariance matrix for normalized cross section as a function of $p^{Z}_{T}$ at particle-level.

Covariance matrix for absolute cross section as a function of $p^{Z}_{T}$ at parton-level.

Covariance matrix for normalized cross section as a function of $p^{Z}_{T}$ at parton-level.

Covariance matrix for absolute cross section as a function of $p_{\text{T}}^{\ell, non-Z}$ at particle-level.

Covariance matrix for normalized cross section as a function of $p_{\text{T}}^{\ell, non-Z}$ at particle-level.

Covariance matrix for absolute cross section as a function of $p_{\text{T}}^{\ell, non-Z}$ at parton-level.

Covariance matrix for normalized cross section as a function of $p_{\text{T}}^{\ell, non-Z}$ at parton-level.

Covariance matrix for absolute cross section as a function of $|y^{Z}$| at particle-level.

Covariance matrix for normalized cross section as a function of $|y^{Z}$| at particle-level.

Covariance matrix for absolute cross section as a function of $|y^{Z}$| at parton-level.

Covariance matrix for normalized cross section as a function of $|y^{Z}$| at parton-level.

Ranking of nuisance parameters and background normalizations on signal strength for inclusive cross section measurement in combination of all channels

Observed and expected 68% and 95% credible intervals for the top-boson operators, in the marginalised linear fit.

Observed and expected 68% and 95% credible intervals for the top-boson operators, in the marginalised quadratic fit.

Observed and expected 68% and 95% credible intervals for the top-boson operators, in the independent quadratic fits (allowing only one Wilson Coefficient to be non-zero).

Observed and expected 68% and 95% credible intervals for the four-quark operators, in the marginalised linear fit.

Observed and expected 68% and 95% credible intervals for the four-quark operators, in the marginalised quadratic fit.

Observed and expected 68% and 95% credible intervals for the four-quark operators, in the independent quadratic fits (allowing only one Wilson Coefficient to be non-zero).

Observed and expected 68% and 95% credible intervals for Fisher-rotated directions of EFT sensitivity, in the marginalised linear fit.

Correlation matrix of the input particle-level observables used in the EFT fit.

Observed exclusion limits at the 95% CL in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$ and a $-1 \sigma$ deviation of the NNLO+NNLL theoretical cross-section of a $\tilde{t}_1$ pair-production.

Expected exclusion limits at the 95% CL in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.

The $1\sigma$ variation of expected 95% CL exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.

The $2\sigma$ variation of expected 95%CL exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.

Observed exclusion limits at the 95% CL in the $m_{\tilde{t}_1} - $BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1)$ plane, assuming $m_{\tilde\chi^0_1} = 1 \mathrm{GeV}$.

Observed exclusion limits at the 95% CL in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming $m_{\tilde\chi^0_1} = 1 \mathrm{ GeV}$ and a $+1 \sigma$ deviation of the NNLO+NNLL theoretical cross-section of a $\tilde{t}_1$ pair-production.

Observed exclusion limits at the 95% CL in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming $m_{\tilde\chi^0_1} = 1 \mathrm{ GeV}$ and a $-1 \sigma$ deviation of the NNLO+NNLL theoretical cross-section of a $\tilde{t}_1$ pair-production.

Expected exclusion limits at the 95% CL in the $m_{\tilde{t}_1} - $BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1)$ plane, assuming $m_{\tilde\chi^0_1} = 1 \mathrm{GeV}$.

The $1\sigma$ variation of expected 95% CL exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties in the $m_{\tilde{t}_1} - $BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1)$ plane, assuming $m_{\tilde\chi^0_1} = 1 \mathrm{GeV}$.

The $2\sigma$ variation of expected 95%CL exclusion contour obtained by varying MC statistical uncertainties, detector-related systematic uncertainties, and theoretical uncertainties in the $m_{\tilde{t}_1} - $BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1)$ plane, assuming $m_{\tilde\chi^0_1} = 1 \mathrm{GeV}$.

Observed upper limits on the top-spartner pair production cross-section in fb at the 95% CL in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$

Expected upper limits on the top-spartner pair production cross-section in fb at the 95% CL in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$

Observed upper limits on the top-spartner pair production cross-section in fb at the 95% CL in the $m_{\tilde{t}_1} - $BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1)$ plane, assuming $m_{\tilde\chi^0_1} = 1 \mathrm{GeV}$.

Expected upper limits on the top-spartner pair production cross-section in fb at the 95% CL in the $m_{\tilde{t}_1} - $BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1)$ plane, assuming $m_{\tilde\chi^0_1} = 1 \mathrm{GeV}$.

Post-fit distribution of $N_{\mathrm{tops}}^{\mathrm{DNN}} (\mathrm{R=1.0})$ in the SRA signal region presented without the associated SRA applied to the variable. For each bin yields for the data and total SM prediction are provided. The SM prediction is provided with the total uncertainty, including the MC statistical uncertainty, detector-related systematic uncertainties and theoretical uncertainties. The rightmost bin includes overflow events.

Post-fit distribution of $m_{\mathrm{T2}}(j^{b}_{R=1.0}, c)$ in the SRA signal region presented without the associated SRA applied to the variable. For each bin yields for the data and total SM prediction are provided. The SM prediction is provided with the total uncertainty, including the MC statistical uncertainty, detector-related systematic uncertainties and theoretical uncertainties. The rightmost bin includes overflow events.

Post-fit distribution of $p_{\mathrm{T}}(c_{1})$ in the SRB signal region presented without the associated SRB applied to the variable. For each bin yields for the data and total SM prediction are provided. The SM prediction is provided with the total uncertainty, including the MC statistical uncertainty, detector-related systematic uncertainties and theoretical uncertainties. The rightmost bin includes overflow events.

Post-fit distribution of $m_{\mathrm{T}}(j, \mathrm{E}_{\mathrm{T}}^{\mathrm{miss}})_{\mathrm{close}}$ in the SRB signal region presented without the associated SRB applied to the variable. For each bin yields for the data and total SM prediction are provided. The SM prediction is provided with the total uncertainty, including the MC statistical uncertainty, detector-related systematic uncertainties and theoretical uncertainties. The rightmost bin includes overflow events.

Post-fit distribution of $\mathrm{E}_{\mathrm{T}}^{\mathrm{miss}} \textrm{Significance}$ in the SRC signal region presented without the associated SRC applied to the variable. For each bin yields for the data and total SM prediction are provided. The SM prediction is provided with the total uncertainty, including the MC statistical uncertainty, detector-related systematic uncertainties and theoretical uncertainties. The rightmost bin includes overflow events.

Post-fit distribution of $m_{\mathrm{T}}(j, \mathrm{E}_{\mathrm{T}}^{\mathrm{miss}})_{\mathrm{close}}$ in the SRC signal region presented without the associated SRC applied to the variable. For each bin yields for the data and total SM prediction are provided. The SM prediction is provided with the total uncertainty, including the MC statistical uncertainty, detector-related systematic uncertainties and theoretical uncertainties. The rightmost bin includes overflow events.

Post-fit distribution of NN signal score in the SRD signal region presented without the associated SRD applied to the variable. For each bin yields for the data and total SM prediction are provided. The SM prediction is provided with the total uncertainty, including the MC statistical uncertainty, detector-related systematic uncertainties and theoretical uncertainties. The rightmost bin includes overflow events.

Post-fit distribution of $m_{\mathrm{eff}}$ in the SRD signal region. For each bin yields for the data and total SM prediction are provided. The SM prediction is provided with the total uncertainty, including the MC statistical uncertainty, detector-related systematic uncertainties and theoretical uncertainties. The rightmost bin includes overflow events.

Pull plots showing the SRA, SRB and SRC post-fit data and SM agreement using the background-only fit configuration

Pull plots showing the SRD post-fit data and SM agreement using the background-only fit configuration

Cutflow for the reference point $(m_{\tilde{t}_1}, m_{\tilde\chi^0_1})=$ (900,1) , (700,300), (550,375) in the Signal region A. Results are shown including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$.

Cutflow for the reference point $(m_{\tilde{t}_1}, m_{\tilde\chi^0_1})=$ (900,1) , (700,300), (550,375) in the Signal region B. Results are shown including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$.

Cutflow for the reference point $(m_{\tilde{t}_1}, m_{\tilde\chi^0_1})=$ (900,1) , (700,300), (550,375) in the Signal region C. Results are shown including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$.

Cutflow for the reference point $(m_{\tilde{t}_1}, m_{\tilde\chi^0_1})=$ (900,1) , (700,300), (550,375) in the Signal region D 750. Results are shown including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$.

Cutflow for the reference point $(m_{\tilde{t}_1}, m_{\tilde\chi^0_1})=$ (900,1) , (700,300), (550,375) in the Signal region D 1000. Results are shown including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$.

Cutflow for the reference point $(m_{\tilde{t}_1}, m_{\tilde\chi^0_1})=$ (900,1) , (700,300), (550,375) in the Signal region D 1250. Results are shown including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$.

Cutflow for the reference point $(m_{\tilde{t}_1}, m_{\tilde\chi^0_1})=$ (900,1) , (700,300), (550,375) in the Signal region D 1500. Results are shown including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$.

Cutflow for the reference point $(m_{\tilde{t}_1}, m_{\tilde\chi^0_1})=$ (900,1) , (700,300), (550,375) in the Signal region D 1750. Results are shown including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$.

Cutflow for the reference point $(m_{\tilde{t}_1}, m_{\tilde\chi^0_1})=$ (900,1) , (700,300), (550,375) in the Signal region D 2000. Results are shown including all correction factors applied to simulation, and is normalised to 139 fb$^{-1}$.

Signal acceptance in the SRA$^{[450,575]}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$ (a factor of 10 larger than in the plots).

Signal efficiency in the SRA$^{[450,575]}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.

Signal acceptance in the SRA$^{\geq 575}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$ (a factor of 10 larger than in the plots).

Signal efficiency in the SRA$^{\geq 575}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.

Signal acceptance in the SRB$^{[100,150]}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$ (a factor of 10 larger than in the plots).

Signal efficiency in the SRB$^{[100,150]}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.

Signal acceptance in the SRB$^{[150,400]}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$ (a factor of 10 larger than in the plots).

Signal efficiency in the SRB$^{[150,400]}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.

Signal acceptance in the SRB$^{\geq 400}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$ (a factor of 10 larger than in the plots).

Signal efficiency in the SRB$^{\geq 400}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.

Signal acceptance in the SRC$^{[100,150]}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$ (a factor of 10 larger than in the plots).

Signal efficiency in the SRC$^{[100,150]}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.

Signal acceptance in the SRC$^{[150,300]}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$ (a factor of 10 larger than in the plots).

Signal efficiency in the SRC$^{[150,300]}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.

Signal acceptance in the SRC$^{[300,500]}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$ (a factor of 10 larger than in the plots).

Signal efficiency in the SRC$^{[300,500]}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.

Signal acceptance in the SRC$^{\geq 500}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$ (a factor of 10 larger than in the plots).

Signal efficiency in the SRC$^{\geq 500}$ region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.

Signal acceptance in the SRD750 region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$ (a factor of 10 larger than in the plots).

Signal efficiency in the SRD750 region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.

Signal acceptance in the SRD1000 region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$ (a factor of 10 larger than in the plots).

Signal efficiency in the SRD1000 region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.

Signal acceptance in the SRD1250 region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$ (a factor of 10 larger than in the plots).

Signal efficiency in the SRD1250 region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.

Signal acceptance in the SRD1500 region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$ (a factor of 10 larger than in the plots).

Signal efficiency in the SRD1500 region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.

Signal acceptance in the SRD1750 region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$ (a factor of 10 larger than in the plots).

Signal efficiency in the SRD1750 region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.

Signal acceptance in the SRD2000 region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$. Please mind that the acceptance given in the table is multiplied by factor of $10^{3}$ (a factor of 10 larger than in the plots).

Signal efficiency in the SRD2000 region in the $\tilde{t}_1 - \tilde\chi^0_1$ mass plane, assuming BR$(\tilde{t}_1 \rightarrow t + \tilde\chi^0_1) = 0.5$.

Distributions of representative kinematic variables in the misidentified background-enriched same-sign region: (a) the Higgs boson transverse momentum ($p_\text{T}^H$) in the $WH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ category, (b) the missing transverse momentum (${E_{\mathrm{T}}^{\mathrm{miss}}}$) in the $WH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ category, (c) the radial distance (dR$(\ell,\ell)$) between the two light leptons associated to the $Z\to\ell{}\ell$ decay process in the $ZH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ category, and (d) the invariant mass ($m_{\ell\ell}$) of the two light leptons associated to the $Z\to\ell{}\ell$ decay in the $ZH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ category. The hatched band represents the pre-fit statistical, experimental and theoretical uncertainties. The signal contributions are considered as part of the predictions and are normalized as predicted by the Standard Model.

Post-fit distributions for NN-based analysis of the NN-scores in the $ZH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ (a), $ZH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ (b), $WH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ (c) and $WH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ (d) categories. The hatched band indicates the total post-fit uncertainty of the total predicted yields. The post-fit signal contributions are considered as part of the predictions.

Post-fit distributions for NN-based analysis of the NN-scores in the $ZH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ (a), $ZH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ (b), $WH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ (c) and $WH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ (d) categories. The hatched band indicates the total post-fit uncertainty of the total predicted yields. The post-fit signal contributions are considered as part of the predictions.

Post-fit distributions for NN-based analysis of the NN-scores in the $ZH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ (a), $ZH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ (b), $WH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ (c) and $WH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ (d) categories. The hatched band indicates the total post-fit uncertainty of the total predicted yields. The post-fit signal contributions are considered as part of the predictions.

Post-fit distributions for NN-based analysis of the NN-scores in the $ZH(\\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ (a), $ZH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ (b), $WH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ (c) and $WH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ (d) categories. The hatched band indicates the total post-fit uncertainty of the total predicted yields. The post-fit signal contributions are considered as part of the predictions.

Post-fit yields from the NN-based fit performed with $\mu_{VH}^{\tau\tau}=\mu_{ZH}^{\tau\tau}=\mu_{WH}^{\tau\tau}$. The symbol $-$ is used when no events or $<10^{-2}$ events are present.

Event yields as a function of $\log_{10}(S/B)$ for data, background, and a Higgs boson signal with $m_{H} = 125$ GeV. Final-discriminant bins in all regions are combined into bins of $\log_{10}(S/B)$, where $S$ is the fitted signal and $B$ is the fitted background from the NN-based fit. The Higgs boson signal contribution is shown after re-scaling the SM cross-section according to the value of the signal strength extracted from data ($\mu = 1.28$). In the lower panel, the pull of the data relative to the background-only expectation, evaluated as the difference between the data and the background-only expectation divided by the square-root sum of the data and background statistical uncertainty, is shown. The solid line shows the expected pull in each bin for the best-fit signal value.

The fitted values of the Higgs boson signal strength $\mu_{VH}^{\tau\tau}$ for $m_{H} = 125$ GeV for the $WH$ and $ZH$ processes and their combination from the NN-based fit. The individual $\mu_{VH}^{\tau\tau}$ values for the $(W/Z)H$ processes are obtained from a simultaneous fit with the signal strength for each of the $WH$ and $ZH$ processes floating independently. The probability of compatibility of the individual signal strengths is 56\%.

Post-fit distributions for mass-based analysis for $m_{\mathrm{MMC}}$ in the (a) $ZH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$, (b) $ZH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$, and for $m_{\mathrm{2T}}$ in the (c) $WH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ and (d) $WH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ categories. The hatched band indicates the total post-fit uncertainty of the total predicted yields. The post-fit signal contributions are considered as part of the predictions.

Post-fit distributions for mass-based analysis for $m_{\mathrm{MMC}}$ in the (a) $ZH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$, (b) $ZH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$, and for $m_{\mathrm{2T}}$ in the (c) $WH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ and (d) $WH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ categories. The hatched band indicates the total post-fit uncertainty of the total predicted yields. The post-fit signal contributions are considered as part of the predictions.

Post-fit distributions for mass-based analysis for $m_{\mathrm{MMC}}$ in the (a) $ZH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$, (b) $ZH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$, and for $m_{\mathrm{2T}}$ in the (c) $WH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ and (d) $WH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ categories. The hatched band indicates the total post-fit uncertainty of the total predicted yields. The post-fit signal contributions are considered as part of the predictions.

Post-fit distributions for mass-based analysis for $m_{\mathrm{MMC}}$ in the (a) $ZH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$, (b) $ZH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$, and for $m_{\mathrm{2T}}$ in the (c) $WH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})# and (d) $WH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ categories. The hatched band indicates the total post-fit uncertainty of the total predicted yields. The post-fit signal contributions are considered as part of the predictions.

The fitted values from the NN-based fit of the Higgs boson signal strength $\mu_{VH}^{\tau\tau}$ for $m_{H} = 125$ GeV are shown separately for the $WH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$, $WH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$, $ZH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$, $ZH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ categories, the $WH$ and $ZH$ processes, and their full combination. The individual $\mu_{VH}^{\tau\tau}$ values for the $(W/Z)H$ processes are obtained from a simultaneous fit with the signal strength for each of the $WH$ and $ZH$ processes floating independently.

Summary table with the expected (exp) and observed (obs) values of the $\mu^{\tau\tau}_{\text{VH}}$ and the significance resulting from the mass-based fit.

Event yields as a function of $\log_{10}(S/B)$ for data, background, and a Higgs boson signal with $m_{H} = 125$ GeV. Final-discriminant bins in all regions are combined into bins of $\log_{10}(S/B)$, where $S$ is the fitted signal and $B$ is the fitted background from the NN-based fit. The Higgs boson signal contribution is shown after re-scaling the SM cross-section according to the value of the signal strength extracted from data ($\mu = 1.28$). In the lower panel, the pull of the data relative to the background-only expectation, evaluated as the difference between the data and the background-only expectation divided by the square-root sum of the data and background statistical uncertainty, is shown. The solid line shows the expected pull in each bin for the best-fit signal value.

Summary table with the expected (exp) and observed (obs) values of the $\mu^{\tau\tau}_{\text{VH}}$ and the significance resulting from the mass-based fit.

The fitted values from the mass-based fit of the Higgs boson signal strength $\mu_{VH}^{\tau\tau}$ for $m_{H} = 125$ GeV are shown for the $WH$ and $ZH$ processes and their combination. The individual $\mu_{VH}^{\tau\tau}$ values for the $(W/Z)H$ processes are obtained from a simultaneous fit with the signal strength for each of the $WH$ and $ZH$ processes floating independently. The probability of compatibility of the individual signal strengths is 85\%.

The fitted values from the mass-based fit of the Higgs boson signal strength $\mu_{VH}^{\tau\tau}$ for $m_{H} = 125$ GeV are shown separately for the $WH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$, $WH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$, $ZH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$, $ZH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ categories, the $WH$ and $ZH$ processes, and their full combination. The individual $\mu_{VH}^{\tau\tau}$ values for the $(W/Z)H$ processes are obtained from a simultaneous fit with the signal strength for each of the $WH$ and $ZH$ processes floating independently.

Distributions of $d\phi({E_{\mathrm{T}}^{\mathrm{miss}}},\tau_{1})$ (left) and $\eta$ of the leading $p_\text{T}$ $\tau_{\mathrm{had}-\mathrm{vis}}$ (right) in the $WH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ $Z\to\tau\tau$ validation region. The hatched band represents the pre-fit statistical, experimental and theoretical uncertainties. The signal contributions are considered as part of the predictions.

Distributions of $d\phi({E_{\mathrm{T}}^{\mathrm{miss}}},\tau_{1})$ (left) and $\eta$ of the leading $p_\text{T}$ $\tau_{\mathrm{had}-\mathrm{vis}}$ (right) in the $WH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ $Z\to\tau\tau$ validation region. The hatched band represents the pre-fit statistical, experimental and theoretical uncertainties. The signal contributions are considered as part of the predictions.

Distributions of the radial distance $dR(\tau_{1},\tau_{2})$ between the two $\tau_{\mathrm{had}-\mathrm{vis}}$ (left) and of the ${E_{\mathrm{T}}^{\mathrm{miss}}}$ (right) in the $WH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ $W\mathrm{ +jets}$ validation region. The hatched band represents the pre-fit statistical, experimental and theoretical uncertainties. The signal contributions are considered as part of the predictions.

Distributions of the radial distance $dR(\tau_{1},\tau_{2})$ between the two $\tau_{\mathrm{had}-\mathrm{vis}}$ (left) and of the ${E_{\mathrm{T}}^{\mathrm{miss}}}$ (right) in the $WH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ $W\mathrm{ +jets}$ validation region. The hatched band represents the pre-fit statistical, experimental and theoretical uncertainties. The signal contributions are considered as part of the predictions.

Distributions of the ${m_{\mathrm{MMC}}}$ (left) and of the $p_\text{T}$ of the leading $p_\text{T}$ light lepton (right) in the $WH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ $t\bar{t}$ validation region. The hatched band represents the pre-fit statistical, experimental and theoretical uncertainties. The signal contributions are considered as part of the predictions.

Distributions of the ${m_{\mathrm{MMC}}}$ (left) and of the $p_\text{T}$ of the leading $p_\text{T}$ light lepton (right) in the $WH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ $t\bar{t}$ validation region. The hatched band represents the pre-fit statistical, experimental and theoretical uncertainties. The signal contributions are considered as part of the predictions.

Distributions of the $m_{\mathrm{2T}}$ (left) and of the $\eta$ of the leading $p_\text{T}$ $\tau_{\mathrm{had}-\mathrm{vis}}$ in the $WH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ $Z\to\tau\tau$ validation region. The hatched band represents the pre-fit statistical, experimental and theoretical uncertainties. The signal contributions are considered as part of the predictions.

Distributions of the $m_{\mathrm{2T}}$ (left) and of the $\eta$ of the leading $p_\text{T}$ $\tau_{\mathrm{had}-\mathrm{vis}}$ in the $WH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ $Z\to\tau\tau$ validation region. The hatched band represents the pre-fit statistical, experimental and theoretical uncertainties. The signal contributions are considered as part of the predictions.

Distributions of the $dR({\tau_{\mathrm{lep}}},{\tau_{\mathrm{had}}})$ between the two objects associated to the Higgs boson decay and of the invariant mass $m_{\ell,\ell}$ of the two light leptons in the $WH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ all-same-sign validation region. The hatched band represents the pre-fit statistical, experimental and theoretical uncertainties. The signal contributions are considered as part of the predictions.

Distributions of the $dR({\tau_{\mathrm{lep}}},{\tau_{\mathrm{had}}})$ between the two objects associated to the Higgs boson decay and of the invariant mass $m_{\ell,\ell}$ of the two light leptons in the $WH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ all-same-sign validation region. The hatched band represents the pre-fit statistical, experimental and theoretical uncertainties. The signal contributions are considered as part of the predictions.

Distributions of the NN-score in the signal regions sidebands of the $ZH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ (a), $ZH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ (b), $WH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ (c), $WH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ (d) categories.The hatched band represents the pre-fit statistical, experimental and theoretical uncertainties. The signal contributions are considered as part of the predictions and are normalized to the fit result performed with one parameter of interest.

Distributions of the NN-score in the signal regions sidebands of the $ZH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ (a), $ZH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ (b), $WH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ (c), $WH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ (d) categories.The hatched band represents the pre-fit statistical, experimental and theoretical uncertainties. The signal contributions are considered as part of the predictions and are normalized to the fit result performed with one parameter of interest.

Distributions of the NN-score in the signal regions sidebands of the $ZH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ (a), $ZH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ (b), $WH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ (c), $WH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ (d) categories.The hatched band represents the pre-fit statistical, experimental and theoretical uncertainties. The signal contributions are considered as part of the predictions and are normalized to the fit result performed with one parameter of interest.

Distributions of the NN-score in the signal regions sidebands of the $ZH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ (a), $ZH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ (b), $WH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ (c), $WH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ (d) categories.The hatched band represents the pre-fit statistical, experimental and theoretical uncertainties. The signal contributions are considered as part of the predictions and are normalized to the fit result performed with one parameter of interest.

Predicted and observed yields as a function of $m_{4\ell}$ in the VBS-Suppressed region. Overflow events are included in the last bin of the distribution.

Relative systematic uncertainties in the unfolded differential cross section for 4ljj production in the VBS-Enhanced region as a function of m_{jj}

Relative systematic uncertainties in the unfolded differential cross section for 4ljj production in the VBS-Enhanced region as a function of m_{4\ell}

Differential cross-sections for inclusive 4ljj production in the VBS-Enhanced region as a function of $m_{jj}$. Overflow events are included in the last bin of the distribution.

Differential cross-sections for inclusive 4ljj production in the VBS-Suppressed region as a function of $m_{jj}$. Overflow events are included in the last bin of the distribution.

Differential cross-sections for inclusive 4ljj production in the VBS-Enhanced region as a function of $m_{4\ell}$. Overflow events are included in the last bin of the distribution.

Differential cross-sections for inclusive 4ljj production in the VBS-Suppressed region as a function of $m_{4\ell}$. Overflow events are included in the last bin of the distribution.

Differential cross-sections for inclusive 4ljj production in the VBS-Enhanced region as a function of $ p_{T,4l}$. Overflow events are included in the last bin of the distribution.

Differential cross-sections for inclusive 4ljj production in the VBS-Suppressed region as a function of $ p_{T,4l}$. Overflow events are included in the last bin of the distribution.

Differential cross-sections for inclusive 4ljj production in the VBS-Enhanced region as a function of $\Delta\phi_{jj}$. Overflow events are included in the last bin of the distribution.

Differential cross-sections for inclusive 4ljj production in the VBS-Suppressed region as a function of $\Delta\phi_{jj}$. Overflow events are included in the last bin of the distribution.

Differential cross-sections for inclusive 4ljj production in the VBS-Enhanced region as a function of $|\Delta y_{jj}|$. Overflow events are included in the last bin of the distribution.

Differential cross-sections for inclusive 4ljj production in the VBS-Suppressed region as a function of $|\Delta y_{jj}|$. Overflow events are included in the last bin of the distribution.

Differential cross-sections for inclusive 4ljj production in the VBS-Enhanced region as a function of $cos(\theta^{*}_{12})$. Overflow events are included in the last bin of the distribution.

Differential cross-sections for inclusive 4ljj production in the VBS-Suppressed region as a function of $cos(\theta^{*}_{12})$. Overflow events are included in the last bin of the distribution.

Differential cross-sections for inclusive 4ljj production in the VBS-Enhanced region as a function of $cos(\theta^{*}_{34})$. Overflow events are included in the last bin of the distribution.

Differential cross-sections for inclusive 4ljj production in the VBS-Suppressed region as a function of $cos(\theta^{*}_{34})$. Overflow events are included in the last bin of the distribution.

Differential cross-sections for inclusive 4ljj production in the VBS-Enhanced region as a function of $p_{T,jj}$. Overflow events are included in the last bin of the distribution.

Differential cross-sections for inclusive 4ljj production in the VBS-Suppressed region as a function of $p_{T,jj}$. Overflow events are included in the last bin of the distribution.

Differential cross-sections for inclusive 4ljj production in the VBS-Enhanced region as a function of $p_{T,4ljj}$. Overflow events are included in the last bin of the distribution.

Differential cross-sections for inclusive 4ljj production in the VBS-Suppressed region as a function of $p_{T,4ljj}$. Overflow events are included in the last bin of the distribution.

Differential cross-sections for inclusive 4ljj production in the VBS-Enhanced region as a function of $S_{T,4ljj}$. Overflow events are included in the last bin of the distribution.

Differential cross-sections for inclusive 4ljj production in the VBS-Suppressed region as a function of $S_{T,4ljj}$. Overflow events are included in the last bin of the distribution.

Statistical correlation between different bins of the unfolded cross-section for all the measured observables in the VBS-Enhanced region.

Statistical correlation between different bins of the unfolded cross-section for all the measured observables in the VBS-Suppressed region.

Summary of the observed and expected 95% CL upper limits on the cross section for $\mathrm{LQ}_{\mathrm{mix}}^{\mathrm{d}}$ pair production as a function of $m_{\mathrm{LQ}_{\mathrm{mix}}^{\mathrm{d}}}$ under the assumptions of B(LQ$\rightarrow t\mu$)=1.

Summary of observed and predicted yields in the four signal region categories. The background prediction is shown after the combined likelihood fit to data under the background-only hypothesis across all control region and signal region categories. The expected signal yields that are obtained by using their theoretical cross sections are also shown with their pre-fit uncertainties, assuming B=1 and $\mu$=1. The "Other" contribution is dominated by $t\bar{t}t\bar{t}$ and $t\bar{t}WW$ in the $3\ell$ SRs, whereas it is dominated by $tWZ$ and $t\bar{t}WW$ in the $4\ell$ SRs. Dashes refer to components that are negligible or not applicable.

Summary of the data, background and signal yields in the four signal region categories. The background prediction is shown before the combined likelihood fit to data. Dashes (--) refer to components that are negligible or not applicable.

Summary of the data and background yields in the seven control region categories. The background prediction is shown before the combined likelihood fit to data. Dashes (--) refer to components that are negligible or not applicable.

Summary of the data and background yields in the seven control region categories. The background prediction is shown after the combined likelihood fit to data under the background-only hypothesis across all control region categories. Dashes (--) refer to components that are negligible or not applicable.

Distribution of the diphoton invariant mass in validation region VR2. The solid histograms are stacked to show the SM expectations after the 2&times;2D background estimation technique is applied. Background and signal predictions are normalised to the luminosity. The background category "h (other)" includes events originating from VBF, Vh, ggF, thq, thW and bb&#772;h, all subdominant in this signature. Statistical and systematic uncertainties are indicated by the shaded area. The lower panel of each plot shows the ratio of the data to the SM prediction for the respective bin. The first and last bins include the underflows and overflows respectively.

Distribution of the missing transverse momentum in validation region VR2. The solid histograms are stacked to show the SM expectations after the 2&times;2D background estimation technique is applied. Background and signal predictions are normalised to the luminosity. The background category "h (other)" includes events originating from VBF, Vh, ggF, thq, thW and bb&#772;h, all subdominant in this signature. Statistical and systematic uncertainties are indicated by the shaded area. The lower panel of each plot shows the ratio of the data to the SM prediction for the respective bin. The first and last bins include the underflows and overflows respectively.

Distribution of the diphoton invariant mass with all selections of the signal regions applied, except on m_{&gamma;&gamma;} itself, for signal region SR1h. The background estimation techniques described in the text are applied. The different backgrounds are stacked to add up to the total SM prediction in each bin. The predicted yields for signal benchmark models of varying &chi;&#771;⁰₁ mass are also overlaid (not stacked) assuming B(&chi;&#771;⁰₁ &rarr; hG&#771; ) to equal 100%. Background and signal predictions are normalised to the luminosity. The background category "h (other)" includes events originating from VBF, Vh, ggF, thq, thW and bb&#772;h, all subdominant in this signature. The sizes of the statistical and systematic uncertainties are indicated by the shaded areas. The lower panels show the ratio of the data to the SM prediction. Arrows indicate the borders of the signal region (|m_{&gamma;&gamma;}-125 GeV|&lt;5 GeV). The first and last bins include the underflows and overflows respectively.

Distribution of the diphoton invariant mass with all selections of the signal regions applied, except on m_{&gamma;&gamma;} itself, for signal region SR1Z. The background estimation techniques described in the text are applied. The different backgrounds are stacked to add up to the total SM prediction in each bin. The predicted yields for signal benchmark models of varying &chi;&#771;⁰₁ mass are also overlaid (not stacked) assuming B(&chi;&#771;⁰₁ &rarr; hG&#771; ) to equal 50%. Background and signal predictions are normalised to the luminosity. The background category "h (other)" includes events originating from VBF, Vh, ggF, thq, thW and bb&#772;h, all subdominant in this signature. The sizes of the statistical and systematic uncertainties are indicated by the shaded areas. The lower panels show the ratio of the data to the SM prediction. Arrows indicate the borders of the signal region (|m_{&gamma;&gamma;}-125 GeV|&lt;5 GeV). The first and last bins include the underflows and overflows respectively.

Distribution of the diphoton invariant mass with all selections of the signal regions applied, except on m_{&gamma;&gamma;} itself, for signal region SR2. The background estimation techniques described in the text are applied. The different backgrounds are stacked to add up to the total SM prediction in each bin. The predicted yields for signal benchmark models of varying &chi;&#771;⁰₁ mass are also overlaid (not stacked) assuming B(&chi;&#771;⁰₁ &rarr; hG&#771; ) to equal 100%. Background and signal predictions are normalised to the luminosity. The background category "h (other)" includes events originating from VBF, Vh, ggF, thq, thW and bb&#772;h, all subdominant in this signature. The sizes of the statistical and systematic uncertainties are indicated by the shaded areas. The lower panels show the ratio of the data to the SM prediction. Arrows indicate the borders of the signal region (|m_{&gamma;&gamma;}-125 GeV|&lt;5 GeV). The first and last bins include the underflows and overflows respectively.

Observed and expected limits on the pure higgsino cross-section at 95% CL assuming B(&chi;&#771;⁰₁ &rarr; hG&#771; )=100% for different &chi;&#771;⁰₁ masses, obtained by a statistical combination of the three signal regions SR1h, SR1Z and SR2. The inner and outer bands indicate the 1&sigma; and 2&sigma; variation on the expected limit respectively.

Observed and expected 95% CL limits on the pure-higgsino branching fraction to B(&chi;&#771;⁰₁ &rarr; hG&#771; ) as a function of the higgsino mass m(&chi;&#771;⁰₁) assuming it decays via either &chi;&#771;⁰₁&rarr; hG&#771; or &chi;&#771;⁰₁&rarr; ZG&#771;. Limits are obtained by performing a statistical combination of the three signal regions SR1h, SR1Z and SR2. The &plusmn; 1&sigma; variation on the expected limit is shown. The dotted lines indicate the observed limit obtained by a variation of theoretical prediction for the neutralino production cross-section by &plusmn;1 &sigma;. Values of B(&chi;&#771;⁰₁ &rarr; hG&#771; ) larger than the observed 95% CL limit are excluded, as indicated by the hatched area.

Observed and expected 95% CL limits on the pure-higgsino branching fraction to B(&chi;&#771;⁰₁ &rarr; hG&#771; ) as a function of the higgsino mass m(&chi;&#771;⁰₁) assuming it decays via either &chi;&#771;⁰₁&rarr; hG&#771; or &chi;&#771;⁰₁&rarr; ZG&#771;. Limits are obtained by performing a statistical combination of the three signal regions SR1h, SR1Z and SR2. The &plusmn; 1&sigma; variation on the expected limit is shown. The dotted lines indicate the observed limit obtained by a variation of theoretical prediction for the neutralino production cross-section by &plusmn;1 &sigma;. Values of B(&chi;&#771;⁰₁ &rarr; hG&#771; ) larger than the observed 95% CL limit are excluded, as indicated by the hatched area.

Observed and expected 95% CL limits on the pure-higgsino branching fraction to B(&chi;&#771;⁰₁ &rarr; hG&#771; ) as a function of the higgsino mass m(&chi;&#771;⁰₁) assuming it decays via either &chi;&#771;⁰₁&rarr; hG&#771; or &chi;&#771;⁰₁&rarr; ZG&#771;. Limits are obtained by performing a statistical combination of the three signal regions SR1h, SR1Z and SR2. The &plusmn; 1&sigma; variation on the expected limit is shown. The dotted lines indicate the observed limit obtained by a variation of theoretical prediction for the neutralino production cross-section by &plusmn;1 &sigma;. Values of B(&chi;&#771;⁰₁ &rarr; hG&#771; ) larger than the observed 95% CL limit are excluded, as indicated by the hatched area.

Observed and expected 95% CL limits on the pure-higgsino branching fraction to B(&chi;&#771;⁰₁ &rarr; hG&#771; ) as a function of the higgsino mass m(&chi;&#771;⁰₁) assuming it decays via either &chi;&#771;⁰₁&rarr; hG&#771; or &chi;&#771;⁰₁&rarr; ZG&#771;. Limits are obtained by performing a statistical combination of the three signal regions SR1h, SR1Z and SR2. The &plusmn; 1&sigma; variation on the expected limit is shown. The dotted lines indicate the observed limit obtained by a variation of theoretical prediction for the neutralino production cross-section by &plusmn;1 &sigma;. Values of B(&chi;&#771;⁰₁ &rarr; hG&#771; ) larger than the observed 95% CL limit are excluded, as indicated by the hatched area.

Observed and expected 95% CL limits on the pure-higgsino branching fraction to B(&chi;&#771;⁰₁ &rarr; hG&#771; ) as a function of the higgsino mass m(&chi;&#771;⁰₁) assuming it decays via either &chi;&#771;⁰₁&rarr; hG&#771; or &chi;&#771;⁰₁&rarr; ZG&#771;. Limits are obtained by performing a statistical combination of the three signal regions SR1h, SR1Z and SR2. The &plusmn; 1&sigma; variation on the expected limit is shown. The dotted lines indicate the observed limit obtained by a variation of theoretical prediction for the neutralino production cross-section by &plusmn;1 &sigma;. Values of B(&chi;&#771;⁰₁ &rarr; hG&#771; ) larger than the observed 95% CL limit are excluded, as indicated by the hatched area.

Observed and expected 95% CL limits on the pure-higgsino branching fraction to B(&chi;&#771;⁰₁ &rarr; hG&#771; ) as a function of the higgsino mass m(&chi;&#771;⁰₁) assuming it decays via either &chi;&#771;⁰₁&rarr; hG&#771; or &chi;&#771;⁰₁&rarr; ZG&#771;. Limits are obtained by performing a statistical combination of the three signal regions SR1h, SR1Z and SR2. The &plusmn; 1&sigma; variation on the expected limit is shown. The dotted lines indicate the observed limit obtained by a variation of theoretical prediction for the neutralino production cross-section by &plusmn;1 &sigma;. Values of B(&chi;&#771;⁰₁ &rarr; hG&#771; ) larger than the observed 95% CL limit are excluded, as indicated by the hatched area.

Numbers of signal and background events in the signal regions. The respective background estimation techniques are applied. The background category "h (other)" includes events originating from VBF, Vh, ggF, thq, thW and bb&#772;h, all subdominant in this signature. The different backgrounds are stacked to add up to the total Standard Model prediction in each bin. The predicted yields for signal benchmark models of varying &chi;&#771;⁰₁ mass are also plotted (not stacked), assuming B(&chi;&#771;⁰₁ &rarr; hG&#771; )=100% and a &chi;&#771;⁰₁ mass of 130 or 200 GeV. The statistical and systematic uncertainties are indicated by the shaded areas in the top plot. The bottom panel shows the statistical significance&nbsp;<a href="https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2020-025/">[Ref]</a> of the difference between the SM prediction and the observed data in each region.

Observed 95% CL limits in pb on the pure higgsino cross-section, shown in the m(&chi;&#771;⁰₁)-B(&chi;&#771;⁰₁ &rarr; hG&#771; ) plane. Limits are obtained by a statistical combination of the three signal regions SR1h, SR1Z and SR2, assuming the neutralino to decay via either &chi;&#771;⁰₁&rarr; hG&#771; or &chi;&#771;⁰₁&rarr; ZG&#771;.

Acceptances for all signal model points considered in the analysis, shown in the m(&chi;&#771;⁰₁)-B(&chi;&#771;⁰₁ &rarr; hG&#771; ) plane. Acceptances are provided separately for signal region SR1h, assuming the neutralino to decay via either &chi;&#771;⁰₁&rarr; hG&#771; or &chi;&#771;⁰₁&rarr; ZG&#771;.

Acceptances for all signal model points considered in the analysis, shown in the m(&chi;&#771;⁰₁)-B(&chi;&#771;⁰₁ &rarr; hG&#771; ) plane. Acceptances are provided separately for signal region SR1Z, assuming the neutralino to decay via either &chi;&#771;⁰₁&rarr; hG&#771; or &chi;&#771;⁰₁&rarr; ZG&#771;.

Acceptances for all signal model points considered in the analysis, shown in the m(&chi;&#771;⁰₁)-B(&chi;&#771;⁰₁ &rarr; hG&#771; ) plane. Acceptances are provided separately for signal region SR2, assuming the neutralino to decay via either &chi;&#771;⁰₁&rarr; hG&#771; or &chi;&#771;⁰₁&rarr; ZG&#771;.

Efficiencies for all signal model points considered in the analysis, shown in the m(&chi;&#771;⁰₁)-B(&chi;&#771;⁰₁ &rarr; hG&#771; ) plane. Efficiencies are provided separately for signal region SR1h, assuming the neutralino to decay via either &chi;&#771;⁰₁&rarr; hG&#771; or &chi;&#771;⁰₁&rarr; ZG&#771;.

Efficiencies for all signal model points considered in the analysis, shown in the m(&chi;&#771;⁰₁)-B(&chi;&#771;⁰₁ &rarr; hG&#771; ) plane. Efficiencies are provided separately for signal region SR1Z, assuming the neutralino to decay via either &chi;&#771;⁰₁&rarr; hG&#771; or &chi;&#771;⁰₁&rarr; ZG&#771;.

Efficiencies for all signal model points considered in the analysis, shown in the m(&chi;&#771;⁰₁)-B(&chi;&#771;⁰₁ &rarr; hG&#771; ) plane. Efficiencies are provided separately for signal region SR2, assuming the neutralino to decay via either &chi;&#771;⁰₁&rarr; hG&#771; or &chi;&#771;⁰₁&rarr; ZG&#771;.

Observed and expected numbers of events in the three signal regions. The background category "h (other)" includes events originating from VBF, Vh, ggF, thq, thW and bb&#772;h, all subdominant in this signature. The table also includes model-independent 95% CL upper limits on the visible number of BSM events (S⁹⁵_obs), the number of BSM events given the expected number of background events (S⁹⁵_exp) and the visible BSM cross-section (&lang;&epsilon; &sigma;&rang;_obs⁹⁵), all calculated from pseudo-experiments. The discovery p-value (p₀) is also shown and its value is capped at 0.5 if the observed number of events is below the expected number of events.

Cutflows of two benchmark signal points assuming B(&chi;&#771;⁰₁ &rarr; hG&#771; )=100% for all three discovery signal regions. The initial selection includes the leptons veto. Only statistical uncertainties are included. Expected yields are normalised to a luminosity of 139 fb^-1.

Expected and observed exclusion limits at 95% CL for $\sigma_{\mathrm{VBF}}(H_{5}^{\pm\pm}) \times \mathcal{B}(H_{5}^{\pm\pm} \to W^{\pm}W^{\pm})$ as a function of $m_{\mathrm{H_5}}$. The inner (outer) band represents the $68\%$ ($95\%$) confidence interval around the median expected limit.

Expected and observed exclusion limits at 95% CL for $\sin \theta_{{\mathrm{H}}}$ as a function of $m_{\mathrm{H_5}}$. The inner (outer) band represents the $68\%$ ($95\%$) confidence interval around the median expected limit. The exclusion limits are shown up to $m_{\mathrm{H_5}} = 1500$ GeV. The limits obtained separately in the $H_{5}^{\pm} \to W^{\pm}Z$ and $H_{5}^{\pm\pm} \to W^{\pm}W^{\pm}$ channels are also shown for comparison. The hatched region covers the parameter space where the intrinsic widths of the $H_{5}^{\pm}$ and $H_{5}^{\pm\pm}$ bosons would be larger than $10\%$ of $m_{\mathrm{H_5}}$ and is disfavoured in the GM model.