Example description

Example description

Example description

Observed profiled likelihood on $f_{\Lambda1}$ using Approach 1. The signal strength modifiers are treated as free parameters. Axis scales are varied to improve the visibility of important features.

Expected profiled likelihood on $f_{a3}$ using Approach 1. The signal strength modifiers are treated as free parameters.

Observed profiled likelihood on $f_{a3}$ using Approach 1. The signal strength modifiers are treated as free parameters.

Expected profiled likelihood on $f_{\Lambda1}^{Z\gamma}$ using Approach 1. The signal strength modifiers are treated as free parameters.

Observed profiled likelihood on $f_{\Lambda1}^{Z\gamma}$ using Approach 1. The signal strength modifiers are treated as free parameters.

Expected profiled likelihood on $f_{a2}$ using Approach 2. The other two anomalous coupling cross section fractions are fixed to zero. The signal strength modifiers are treated as free parameters. Axis scales are varied to improve the visibility of important features.

Observed profiled likelihood on $f_{a2}$ using Approach 2. The other two anomalous coupling cross section fractions are fixed to zero. The signal strength modifiers are treated as free parameters. Axis scales are varied to improve the visibility of important features.

Expected profiled likelihood on $f_{\Lambda1}$ using Approach 2. The other two anomalous coupling cross section fractions are fixed to zero. The signal strength modifiers are treated as free parameters. Axis scales are varied to improve the visibility of important features.

Observed profiled likelihood on $f_{\Lambda1}$ using Approach 2. The other two anomalous coupling cross section fractions are fixed to zero. The signal strength modifiers are treated as free parameters. Axis scales are varied to improve the visibility of important features.

Expected profiled likelihood on $f_{a3}$ using Approach 2. The other two anomalous coupling cross section fractions are fixed to zero. The signal strength modifiers are treated as free parameters.

Observed profiled likelihood on $f_{a3}$ using Approach 2. The other two anomalous coupling cross section fractions are fixed to zero. The signal strength modifiers are treated as free parameters.

Expected profiled likelihood on $f_{a2}$ using Approach 2. The other two anomalous coupling cross section fractions are left floating in the fit. The signal strength modifiers are treated as free parameters. Axis scales are varied to improve the visibility of important features.

Observed profiled likelihood on $f_{a2}$ using Approach 2. The other two anomalous coupling cross section fractions are left floating in the fit. The signal strength modifiers are treated as free parameters. Axis scales are varied to improve the visibility of important features.

Expected profiled likelihood on $f_{\Lambda1}$ using Approach 2. The other two anomalous coupling cross section fractions are left floating in the fit. The signal strength modifiers are treated as free parameters. Axis scales are varied to improve the visibility of important features.

Observed profiled likelihood on $f_{\Lambda1}$ using Approach 2. The other two anomalous coupling cross section fractions are left floating in the fit. The signal strength modifiers are treated as free parameters. Axis scales are varied to improve the visibility of important features.

Expected profiled likelihood on $f_{a3}$ using Approach 2. The other two anomalous coupling cross section fractions are left floating in the fit. The signal strength modifiers are treated as free parameters.

Observed profiled likelihood on $f_{a3}$ using Approach 2. The other two anomalous coupling cross section fractions are left floating in the fit. The signal strength modifiers are treated as free parameters.

Expected profiled likelihood on the $\delta c_{Z}$ coupling of the SMEFT Higgs basis.

Observed profiled likelihood on the $\delta c_{Z}$ coupling of the SMEFT Higgs basis.

Expected profiled likelihood on the $c_{Z\Box}$ coupling of the SMEFT Higgs basis.

Observed profiled likelihood on the $c_{Z\Box}$ coupling of the SMEFT Higgs basis.

Expected profiled likelihood on the $c_{ZZ}$ coupling of the SMEFT Higgs basis.

Observed profiled likelihood on the $c_{ZZ}$ coupling of the SMEFT Higgs basis.

Expected profiled likelihood on the $\tilde{c}_{ZZ}$ coupling of the SMEFT Higgs basis.

Observed profiled likelihood on the $\tilde{c}_{ZZ}$ coupling of the SMEFT Higgs basis.

Expected profiled likelihood on $f_{a3}^{ggH}$. The signal strength modifiers and the CP-odd HVV anomalous coupling cross section fraction are treated as free parameters.

Observed profiled likelihood on $f_{a3}^{ggH}$. The signal strength modifiers and the CP-odd HVV anomalous coupling cross section fraction are treated as free parameters.

Distributions of reconstructed VLQ mass for expected postfit background (blue histogram), signal plus background (colored lines), and observed data (black points) for events in the hadronic 5-jet bHbH channel.

Distributions of reconstructed VLQ mass for expected postfit background (blue histogram), signal plus background (colored lines), and observed data (black points) for events in the hadronic 5-jet bHbZ channel.

Distributions of reconstructed VLQ mass for expected postfit background (blue histogram), signal plus background (colored lines), and observed data (black points) for events in the hadronic 5-jet bZbZ channel.

Distributions of reconstructed VLQ mass for expected postfit background (blue histogram), signal plus background (colored lines), and observed data (black points) for events in the hadronic 5-jet bHtW channel.

Distributions of reconstructed VLQ mass for expected postfit background (blue histogram), signal plus background (colored lines), and observed data (black points) for events in the hadronic 5-jet bZtW channel.

Distributions of reconstructed VLQ mass for expected postfit background (blue histogram), signal plus background (colored lines), and observed data (black points) for events in the hadronic 6-jet bHbH channel.

Distributions of reconstructed VLQ mass for expected postfit background (blue histogram), signal plus background (colored lines), and observed data (black points) for events in the hadronic 6-jet bHbZ channel.

Distributions of reconstructed VLQ mass for expected postfit background (blue histogram), signal plus background (colored lines), and observed data (black points) for events in the hadronic 6-jet bZbZ channel.

Distributions of reconstructed VLQ mass for expected postfit background (blue histogram), signal plus background (colored lines), and observed data (black points) for events in the hadronic 6-jet bHtW channel.

Distributions of reconstructed VLQ mass for expected postfit background (blue histogram), signal plus background (colored lines), and observed data (black points) for events in the hadronic 6-jet bZtW channel.

Distributions of reconstructed VLQ mass for expected postfit background (blue histogram), signal plus background (colored lines), and observed data (black points) for events in the semileptonic 3-jet bHbZ channel.

Distributions of reconstructed VLQ mass for expected postfit background (blue histogram), signal plus background (colored lines), and observed data (black points) for events in the semileptonic 3-jet bZbZ channel.

Distributions of reconstructed VLQ mass for expected postfit background (blue histogram), signal plus background (colored lines), and observed data (black points) for events in the semileptonic 4-jet bHbZ channel.

Distributions of reconstructed VLQ mass for expected postfit background (blue histogram), signal plus background (colored lines), and observed data (black points) for events in the semileptonic 4-jet bZbZ channel.

The limit at 95% CL on the cross section for VLQ pair production for the branching fraction hypothesis 0% $\mathcal{B}(B \to bH)$, 100% $\mathcal{B}(B \to bH)$, and 0% $\mathcal{B}(B \to bH)$

The limit at 95% CL on the cross section for VLQ pair production for the branching fraction hypothesis 25% $\mathcal{B}(B \to bH)$, 25% $\mathcal{B}(B \to bH)$, and 50% $\mathcal{B}(B \to bH)$

The limit at 95% CL on the cross section for VLQ pair production for the branching fraction hypothesis 50% $\mathcal{B}(B \to bH)$, 50% $\mathcal{B}(B \to bH)$, and 0% $\mathcal{B}(B \to bH)$

The limit at 95% CL on the cross section for VLQ pair production for the branching fraction hypothesis 100% $\mathcal{B}(B \to bH)$, 0% $\mathcal{B}(B \to bH)$, and 0% $\mathcal{B}(B \to bH)$

Median expected exclusion limits on the VLQ mass at 95% CL as a function of the branching fractions $\mathcal{B}(B \to bH)$ and $\mathcal{B}(B \to tW)$, with $\mathcal{B}(B \to tW) = 1 - \mathcal{B}(B \to bH) - \mathcal{B}(B \to bZ)$. The grey area corresponds to the region where the exclusion limit is less than 1000 GeV.

Median observed exclusion limits on the VLQ mass at 95% CL as a function of the branching fractions $\mathcal{B}(B \to bH)$ and $\mathcal{B}(B \to tW)$, with $\mathcal{B}(B \to tW) = 1 - \mathcal{B}(B \to bH) - \mathcal{B}(B \to bZ)$. The grey area corresponds to the region where the exclusion limit is less than 1000 GeV.

The geometric acceptance multiplied by the efficiency of the $\it{p}_{T}^\text{miss} >$ 200 GeV selection as a function of the proper decay length c$\tau$ for a scalar particle S with a mass of 40 GeV. The acceptance region for DT is defined by requiring the LLP to decay in the region with |z| < 661 cm and 380 cm < r < 736 cm. The acceptance region for CSC is defined by requiring the LLP decay in the region with $|\eta| < 2.4$, r < 695.5 cm, and 661 cm < |z| < 1100 cm or in the region with $|\eta| < 2.4$, r < 270 cm, and 500 cm < |z| < 661 cm. Single CSC cluster requires exactly one LLP to decay in CSC; Single DT cluster requires exactly one LLP to decay in DT; Double cluster requires both LLP to decay in CSC or DT. The denominator in this plot includes all generated events. The nominator includes events that pass the acceptance requirements above and $\it{p}_{T}^\text{miss} >$ 200 GeV.

Distributions of the cluster time for signal, where S decaying to $d\bar{d}$ for a proper decay length c$\tau$ of 1 m and mass of 40 GeV, and for a background-enriched sample in data selected by inverting the $N_\text{hits}$ requirement.

The distributions of $N_\text{hits}$ for single CSC clusters are shown for signal (assuming B(H $\rightarrow$ SS) = 1%, S $\rightarrow d\bar{d}$, and c$\tau$ = 1 m).

The distributions of $N_\text{hits}$ for single CSC clusters are shown for compared to the OOT background ($t_\text{clusters} < 12.5$ ns). The OOT background is representative of the overall background shape, because the background passing all the selections described above is dominated by pileup and underlying events.

The distributions of $\Delta\phi(\it{p}_{T}^\text{miss} \text{,cluster)}$ for single CSC clusters are shown for signal (assuming B(H $\rightarrow$ SS) = 1%, S $\rightarrow d\bar{d}$, and c$\tau$ = 1 m), compared to the shape of background in a selection in which the cluster is not matched to any RPC hit and passes all other selections. The background is dominated by clusters from noise and low-pT particles.

The distributions of $N_\text{hits}$ for single CSC clusters are shown for signal (assuming B(H $\rightarrow$ SS) = 1%, S $\rightarrow d\bar{d}$, and c$\tau$ = 1 m), compared to the shape of background in a selection in which the cluster is not matched to any RPC hit and passes all other selections. The background is dominated by clusters from noise and low-pT particles.

The distributions of $\Delta\phi(\it{p}_{T}^\text{miss} \text{,cluster)}$ for single CSC clusters are shown for signal (assuming B(H $\rightarrow$ SS) = 1%, S $\rightarrow d\bar{d}$, and c$\tau$ = 1 m), compared to the shape of background in a selection in which the cluster is not matched to any RPC hit and passes all other selections. The background is dominated by clusters from noise and low-pT particles.

The signal (assuming B(H $\rightarrow$ SS) = 1%, S $\rightarrow d\bar{d}$, and c$\tau$ = 1 m), background, and data distributions of $N_\text{clusters}$ passing the $N_\text{hits}$ selection in the search region for CSC-CSC category.

The signal (assuming B(H $\rightarrow$ SS) = 1%, S $\rightarrow d\bar{d}$, and c$\tau$ = 1 m), background, and data distributions of $N_\text{clusters}$ passing the $N_\text{hits}$ selection in the search region for DT-DT category.

The signal (assuming B(H $\rightarrow$ SS) = 1%, S $\rightarrow d\bar{d}$, and c$\tau$ = 1 m), background, and data distributions of $N_\text{clusters}$ passing the $N_\text{hits}$ selection in the search region for DT-CSC category.

The signal (assuming B(H $\rightarrow$ SS) = 1%, S $\rightarrow d\bar{d}$, and c$\tau$ = 1 m), background, and data distributions of $N_\text{hits}$ in the search region of the single-CSC cluster category are shown. The $N_\text{hits}$ distribution includes only events in bins A and D. The right-hand bin in the Nhits distribution includes overflow events.

The signal (assuming B(H $\rightarrow$ SS) = 1%, S $\rightarrow d\bar{d}$, and c$\tau$ = 1 m), background, and data distributions of $\Delta\phi(\it{p}_{T}^\text{miss} \text{,cluster)}$ in the search region of the single-CSC cluster category are shown. The $\Delta\phi(\it{p}_{T}^\text{miss} \text{,cluster)}$ distribution includes only events in bins A and B.

The signal (assuming B(H $\rightarrow$ SS) = 1%, S $\rightarrow d\bar{d}$, and c$\tau$ = 1 m), background, and data distributions of $N_\text{hits}$ in the search region of the single-DT cluster category are shown. The $N_\text{hits}$ distribution includes only events in bins A and D. The right-hand bin in the Nhits distribution includes overflow events.

The signal (assuming B(H $\rightarrow$ SS) = 1%, S $\rightarrow d\bar{d}$, and c$\tau$ = 1 m), background, and data distributions of $\Delta\phi(\it{p}_{T}^\text{miss} \text{,cluster)}$ in the search region of the single-DT cluster category are shown. The $\Delta\phi(\it{p}_{T}^\text{miss} \text{,cluster)}$ distribution includes only events in bins A and B.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 3 GeV mass and $ S \rightarrow d\bar{d}$ decay mode.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 7 GeV mass and $ S \rightarrow d\bar{d}$ decay mode.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 15 GeV mass and $ S \rightarrow d\bar{d}$ decay mode.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 40 GeV mass and $ S \rightarrow d\bar{d}$ decay mode.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 55 GeV mass and $ S \rightarrow d\bar{d}$ decay mode.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 0.4 GeV mass and $ S \rightarrow \pi^{0} \pi^{0}$ decay mode.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 1 GeV mass and $ S \rightarrow \pi^{0} \pi^{0}$ decay mode.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 7 GeV mass and $ S \rightarrow \tau^{+} \tau^{-}$ decay mode.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 15 GeV mass and $ S \rightarrow \tau^{+} \tau^{-}$ decay mode.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 40 GeV mass and $ S \rightarrow \tau^{+} \tau^{-}$ decay mode.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 55 GeV mass and $ S \rightarrow \tau^{+} \tau^{-}$ decay mode.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 15 GeV mass and $ S \rightarrow b\bar{b}$ decay mode.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 40 GeV mass and $ S \rightarrow b\bar{b}$ decay mode.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 55 GeV mass and $ S \rightarrow b\bar{b}$ decay mode.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 0.4 GeV mass and $ S \rightarrow \pi^{+} \pi^{-}$ decay mode.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 1 GeV mass and $ S \rightarrow \pi^{+} \pi^{-}$ decay mode.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 1.5 GeV mass and $ S \rightarrow K^{+}K^{-}$ decay mode.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 1.5 GeV mass and $ S \rightarrow K^{0}K^{0}$ decay mode.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 0.4 GeV mass and $ S \rightarrow \gamma\gamma$ decay mode.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) for 0.4 GeV mass and $ S \rightarrow \e^{+} \e^{-}$ decay mode.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) as functions of mass and c$\tau$ assuming S inherits all couplings from the Higgs boson evaluated at the LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) as functions of mass and c$\tau$ assuming S inherits all couplings from the Higgs boson evaluated at the LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) as functions of mass and c$\tau$ assuming S inherits all couplings from the Higgs boson evaluated at the LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) as functions of mass and c$\tau$ assuming S inherits all couplings from the Higgs boson evaluated at the LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) as functions of mass and c$\tau$ assuming S inherits all couplings from the Higgs boson evaluated at the LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) as functions of mass and c$\tau$ assuming S inherits all couplings from the Higgs boson evaluated at the LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) as functions of mass and c$\tau$ assuming S inherits all couplings from the Higgs boson evaluated at the LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) as functions of mass and c$\tau$ assuming S inherits all couplings from the Higgs boson evaluated at the LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) as functions of mass and c$\tau$ assuming S inherits all couplings from the Higgs boson evaluated at the LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow$ SS) as functions of mass and c$\tau$ assuming S inherits all couplings from the Higgs boson evaluated at the LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for vector portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (1, 1)$ and 2 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for vector portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (1, 1)$ and 5 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for vector portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (1, 1)$ and 10 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for vector portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (1, 1)$ and 15 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for vector portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (1, 1)$ and 20 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for gluon portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (2.5, 1)$ and 5 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for gluon portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (2.5, 1)$ and 10 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for gluon portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (2.5, 1)$ and 15 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for gluon portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (2.5, 1)$ and 20 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for gluon portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (2.5, 2.5)$ and 5 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for gluon portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (2.5, 2.5)$ and 10 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for gluon portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (2.5, 2.5)$ and 15 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for gluon portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (2.5, 2.5)$ and 20 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for gluon portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (1, 1)$ and 5 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for gluon portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (1, 1)$ and 10 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for gluon portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (1, 1)$ and 15 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for gluon portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (1, 1)$ and 20 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for photon portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (2.5, 1)$ and 2 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for photon portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (2.5, 1)$ and 5 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for photon portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (2.5, 1)$ and 10 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for photon portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (2.5, 1)$ and 15 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for photon portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (2.5, 1)$ and 20 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for photon portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (2.5, 2.5)$ and 2 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for photon portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (2.5, 2.5)$ and 5 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for photon portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (2.5, 2.5)$ and 10 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for photon portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (2.5, 2.5)$ and 15 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for photon portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (2.5, 2.5)$ and 20 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for photon portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (1, 1)$ and 2 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for photon portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (1, 1)$ and 5 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for photon portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (1, 1)$ and 10 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for photon portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (1, 1)$ and 15 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for photon portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (1, 1)$ and 20 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for higgs portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (2.5, 1)$ and 4 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for higgs portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (2.5, 1)$ and 5 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for higgs portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (2.5, 1)$ and 10 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for higgs portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (2.5, 1)$ and 15 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for higgs portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (2.5, 1)$ and 20 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for higgs portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (2.5, 2.5)$ and 4 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for higgs portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (2.5, 2.5)$ and 5 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for higgs portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (2.5, 2.5)$ and 10 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for higgs portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (2.5, 2.5)$ and 15 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for higgs portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (2.5, 2.5)$ and 20 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for higgs portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (1, 1)$ and 4 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for higgs portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (1, 1)$ and 5 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for higgs portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (1, 1)$ and 10 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for higgs portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (1, 1)$ and 15 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for higgs portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (1, 1)$ and 20 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for darkphoton portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (2.5, 1)$ and 5 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for darkphoton portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (2.5, 1)$ and 10 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for darkphoton portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (2.5, 1)$ and 15 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for darkphoton portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (2.5, 1)$ and 20 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for darkphoton portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (2.5, 2.5)$ and 5 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for darkphoton portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (2.5, 2.5)$ and 10 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for darkphoton portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (2.5, 2.5)$ and 15 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for darkphoton portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (2.5, 2.5)$ and 20 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for darkphoton portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (1, 1)$ and 5 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for darkphoton portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (1, 1)$ and 10 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for darkphoton portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (1, 1)$ and 15 GeV LLP mass.

The 95% CL observed and expected limits on the branching fraction B(H $\rightarrow \Psi\Psi$) for darkphoton portal, assuming $(\xi_{\omega}$, $\xi_{\Lambda}) = (1, 1)$ and 20 GeV LLP mass.

Correlation matrix for the differential branching fraction extraction between different $q^2$ bins in the simultaneous fit.

The product of acceptance and efficiency ($A\epsilon$) of the $\mathcal{B}(\mathrm{B}^+\to\mathrm{K}^+\mu^+\mu^-)$ channel, as a function of the muon pair $q^2$, as measured in simulated signal events, after all the corrections applied. In the figure, regions corresponding to resonances are displayed with red markers.

Same as Table 5, but for the bins containing the J$\psi$ and $\psi$(2S) resonances.

Integrated branching fraction $\mathcal{B}(\mathrm{B}^\pm \to \mathrm{K}^\pm\mu^+\mu^-)$ in the low-$q^2$ region.

Ratio of branching fractions $\mathcal{B}(\text{B}^\pm \to \text{K}^\pm\mu^+\mu^-)$ to $\mathcal{B}(\text{B}^\pm \to \text{K}^\pm\text{e}^+\text{e}^-)$, determined from the measured double ratio $R$(K) of these decays to the respective branching fractions of the decay chains $\text{B}^\pm\to\text{J/}\psi\text{K}^\pm$ with $\text{J/}\psi\to\mu^+\mu^-$ and $\text{e}^+\text{e}^-$.

Negative log likelihood function from the fit profiled as a function of the inverse ratio $R(\mathrm{K})^{-1}$.

Post-fit distributon of BDT discriminants for $\rho_{tc}=1.0$ with $m_A$ = 350 GeV interfered with H.($m_A - m_H$ = 50 GeV)

Observed and expected 95% CL upper limit on the signal strength as a function of $m_A$ for the g2HDM signal model using different coupling assumptions: $\rho_{tu}$ = 0.1, 0.4, 1.0.

Observed and expected 95% CL upper limit on the signal strength as a function of $m_A$ for the g2HDM signal model using different coupling assumptions: $\rho_{tc}$ = 0.1, 0.4, 1.0.

Observed and expected 95% CL upper limit on the signal strength as a function of $m_A$ for the g2HDM signal model using different coupling assumptions: $\rho_{tu}$ = 0.1, 0.4, 1.0 with A–H interference assuming $m_A$ − $m_H$ = 50 GeV.

Observed and expected 95% CL upper limit on the signal strength as a function of $m_A$ for the g2HDM signal model using different coupling assumptions: $\rho_{tc}$ = 0.1, 0.4, 1.0 with A–H interference assuming $m_A$ − $m_H$ = 50 GeV.

Observed 95% CL upper limit on the signal strength as a function of $m_A$ and $\rho_{tu}$ for the g2HDM signal model.

Expected exclusion as a function of $m_A$ and $\rho_{tu}$ for the g2HDM signal model

Observed exclusion as a function of $m_A$ and $\rho_{tu}$ for the g2HDM signal model

Observed 95% CL upper limit on the signal strength as a function of $m_A$ and $\rho_{tc}$ for the g2HDM signal model.

Expected exclusion as a function of $m_A$ and $\rho_{tc}$ for the g2HDM signal model

Observed exclusion as a function of $m_A$ and $\rho_{tc}$ for the g2HDM signal model

Observed 95% CL upper limit on the signal strength as a function of $m_A$ and $\rho_{tu}$ for the g2HDM signal model with A–H interference assuming $m_A$ − $m_H$ = 50 GeV.

Expected exclusion as a function of $m_A$ and $\rho_{tu}$ for the g2HDM signal model with A–H interference assuming $m_A$ − $m_H$ = 50 GeV

Observed exclusion as a function of $m_A$ and $\rho_{tu}$ for the g2HDM signal model with A–H interference assuming $m_A$ − $m_H$ = 50 GeV

Observed 95% CL upper limit on the signal strength as a function of $m_A$ and $\rho_{tc}$ for the g2HDM signal model with A–H interference assuming $m_A$ − $m_H$ = 50 GeV.

Expected exclusion as a function of $m_A$ and $\rho_{tc}$ for the g2HDM signal model with A–H interference assuming $m_A$ − $m_H$ = 50 GeV

Observed exclusion as a function of $m_A$ and $\rho_{tc}$ for the g2HDM signal model with A–H interference assuming $m_A$ − $m_H$ = 50 GeV

The $m_{e\mu}$ distribution of the observed data is shown, with the $S+B$ fit at $m_{X}=146\mathrm{GeV}$ in red solid line, and the background component of the fit in red dotted line. Events and fit in each category are weighted by $S/(S+B)$. The one and two standard deviation uncertainty bands of the background component are shown in green and yellow. The lower panel shows the residuals after subtracting the background component of the fit from data.

Observed (expected) 95% confidence level upper limits on $\sigma(p p \to X(146) \to e \mu)$ for each individual analysis category (as shown in the left axis label) and for the combination of all analysis categories assuming the relative SM-like production cross sections of the ggH and VBF production modes.

The $m_{e\mu}$ distribution of the observed data in the category ggH cat 0 is shown, with the $S+B$ fit at $m_{X}=146\mathrm{GeV}$ in solid red line, and the background component of the fit in dotted red line. The green and yellow bands represent the one and two standard deviations of the background component. The lower panel shows the residuals after subtracting the background component of the fit from data.

The $m_{e\mu}$ distribution of the observed data in the category ggH cat 1 is shown, with the $S+B$ fit at $m_{X}=146\mathrm{GeV}$ in solid red line, and the background component of the fit in dotted red line. The green and yellow bands represent the one and two standard deviations of the background component. The lower panel shows the residuals after subtracting the background component of the fit from data.

The $m_{e\mu}$ distribution of the observed data in the category ggH cat 2 is shown, with the $S+B$ fit at $m_{X}=146\mathrm{GeV}$ in solid red line, and the background component of the fit in dotted red line. The green and yellow bands represent the one and two standard deviations of the background component. The lower panel shows the residuals after subtracting the background component of the fit from data.

The $m_{e\mu}$ distribution of the observed data in the category ggH cat 3 is shown, with the $S+B$ fit at $m_{X}=146\mathrm{GeV}$ in solid red line, and the background component of the fit in dotted red line. The green and yellow bands represent the one and two standard deviations of the background component. The lower panel shows the residuals after subtracting the background component of the fit from data.

The $m_{e\mu}$ distribution of the observed data in the category VBF cat 0 is shown, with the $S+B$ fit at $m_{X}=146\mathrm{GeV}$ in solid red line, and the background component of the fit in dotted red line. The green and yellow bands represent the one and two standard deviations of the background component. The lower panel shows the residuals after subtracting the background component of the fit from data.

The $m_{e\mu}$ distribution of the observed data in the category VBF cat 1 is shown, with the $S+B$ fit at $m_{X}=146\mathrm{GeV}$ in solid red line, and the background component of the fit in dotted red line. The green and yellow bands represent the one and two standard deviations of the background component. The lower panel shows the residuals after subtracting the background component of the fit from data.

Best fit of $\sigma(p p \to X(146) \to e \mu)$ for each analysis category (black point) compared to the best fit for the combination of all analysis categories (blue line). The one standard deviation uncertainty of the per-category best fit is shown in red line and the one standard deviation uncertainty of the combined best fit is shown in green band.

The observed and expected 95% CL upper limits on $\sigma_{ggH,f_{VBF}}(p p \to X \to e \mu)$ and $\sigma_{VBF,f_{VBF}}(p p \to X \to e \mu)$ with $f_{VBF}$ = 0.0.

The observed and expected 95% CL upper limits on $\sigma_{ggH,f_{VBF}}(p p \to X \to e \mu)$ and $\sigma_{VBF,f_{VBF}}(p p \to X \to e \mu)$ with $f_{VBF}$ = 0.1.

The observed and expected 95% CL upper limits on $\sigma_{ggH,f_{VBF}}(p p \to X \to e \mu)$ and $\sigma_{VBF,f_{VBF}}(p p \to X \to e \mu)$ with $f_{VBF}$ = 0.2.

The observed and expected 95% CL upper limits on $\sigma_{ggH,f_{VBF}}(p p \to X \to e \mu)$ and $\sigma_{VBF,f_{VBF}}(p p \to X \to e \mu)$ with $f_{VBF}$ = 0.3.

The observed and expected 95% CL upper limits on $\sigma_{ggH,f_{VBF}}(p p \to X \to e \mu)$ and $\sigma_{VBF,f_{VBF}}(p p \to X \to e \mu)$ with $f_{VBF}$ = 0.4.

The observed and expected 95% CL upper limits on $\sigma_{ggH,f_{VBF}}(p p \to X \to e \mu)$ and $\sigma_{VBF,f_{VBF}}(p p \to X \to e \mu)$ with $f_{VBF}$ = 0.5.

The observed and expected 95% CL upper limits on $\sigma_{ggH,f_{VBF}}(p p \to X \to e \mu)$ and $\sigma_{VBF,f_{VBF}}(p p \to X \to e \mu)$ with $f_{VBF}$ = 0.6.

The observed and expected 95% CL upper limits on $\sigma_{ggH,f_{VBF}}(p p \to X \to e \mu)$ and $\sigma_{VBF,f_{VBF}}(p p \to X \to e \mu)$ with $f_{VBF}$ = 0.7.

The observed and expected 95% CL upper limits on $\sigma_{ggH,f_{VBF}}(p p \to X \to e \mu)$ and $\sigma_{VBF,f_{VBF}}(p p \to X \to e \mu)$ with $f_{VBF}$ = 0.8.

The observed and expected 95% CL upper limits on $\sigma_{ggH,f_{VBF}}(p p \to X \to e \mu)$ and $\sigma_{VBF,f_{VBF}}(p p \to X \to e \mu)$ with $f_{VBF}$ = 0.9.

The observed and expected 95% CL upper limits on $\sigma_{ggH,f_{VBF}}(p p \to X \to e \mu)$ and $\sigma_{VBF,f_{VBF}}(p p \to X \to e \mu)$ with $f_{VBF}$ = 1.0.

Observed and expected 95% CL upper limits on ${{(\sigma_{\text{H}}/\sigma_{\text{H}}^{\mathrm{SM}}) \times {{\mathcal{B}(\text{H} \to \text{inv})}}}}$ for the combined VBF, ttH, VH and ggH channels using all available CMS data for 2016--2018, Run1, 2015, and their combination, assuming a SM Higgs boson with a mass of 125 GeV.

Observed and expected 95% CL upper limits on ${{(\sigma_{\text{H}}/\sigma_{\text{H}}^{\mathrm{SM}}) \times {{\mathcal{B}(\text{H} \to \text{inv})}}}}$ for the VBF, ttH(lep), ttH(had), V(qq)H, Z(ll)H, Z(bb)H and ggH channels using all available CMS data, and their combination, assuming a SM Higgs boson with a mass of 125 GeV.

The 90% CL upper limits on the spin-independent DM-nucleon scattering cross section in Higgs-portal models, assuming a scalar, fermionic or vectorial DM candidate (with a UV-complete vector model), compared to direct detection experimets CRESST-III, DarkSide-50, LUX_ZEPLIN and PandaX-4T (2022 results).

Postfit event yields in each category and hadronic recoil bin of the ttH category SR for the different background and signal processes summed across 2016, 2017 and 2018 samples. The background and signal yields and the corresponding uncertainties are obtained after performing a combined fit across all of the CRs and SR or CR-only. The Postfit signal contributions for a Higgs boson, produced in ttH, VH (split into WH and ZH), ggH and VBF, decaying to invisible particles with a branching fraction of $\mathcal{B}(\text{H} \to \text{inv}) = 1$, and the observed event yields are reported.

Postfit event yields in each category and hadronic recoil bin of the VH category SR for the different background and signal processes summed across 2016, 2017 and 2018 samples. The background and signal yields and the corresponding uncertainties are obtained after performing a combined fit across all of the CRs and SR or CR-only. The Postfit signal contributions for a Higgs boson, produced in ttH, VH (split into WH and ZH), ggH and VBF, decaying to invisible particles with a branching fraction of $\mathcal{B}(\text{H} \to \text{inv}) = 1$, and the observed event yields are reported.

Postfit event yields in each category and $p\mathrm{_{T}^{miss}}$ bin of the ttH category e$+$jets CR for the different background processes summed across 2016, 2017 and 2018 samples. The background yields and the corresponding uncertainties are obtained after performing a combined fit across all of the CRs and SR or CR-only.

Postfit event yields in each category and $p\mathrm{_{T}^{miss}}$ bin of the VH category e$+$jets CR for the different background processes summed across 2016, 2017 and 2018 samples. The background yields and the corresponding uncertainties are obtained after performing a combined fit across all of the CRs and SR or CR-only.

Postfit event yields in each category and $p\mathrm{_{T}^{miss}}$ bin of the ttH category $\mu+$jets CR for the different background processes summed across 2016, 2017 and 2018 samples. The background yields and the corresponding uncertainties are obtained after performing a combined fit across all of the CRs and SR or CR-only.

Postfit event yields in each category and $p\mathrm{_{T}^{miss}}$ bin of the VH category $\mu+$jets CR for the different background processes summed across 2016, 2017 and 2018 samples. The background yields and the corresponding uncertainties are obtained after performing a combined fit across all of the CRs and SR or CR-only.

Postfit event yields in each category and $p\mathrm{_{T}^{miss}}$ bin of the ttH category ee$+$jets, $\mu\mu+$jets, and $\ell\ell+$jets CRs for the different background processes summed across 2016, 2017 and 2018 samples. The background yields and the corresponding uncertainties are obtained after performing a combined fit across all of the CRs and SR or CR-only.

Postfit event yields in each category and $p\mathrm{_{T}^{miss}}$ bin of the VH category ee$+$jets, $\mu\mu+$jets, and $\gamma+$jets CRs for the different background processes summed across 2016, 2017 and 2018 samples. The background yields and the corresponding uncertainties are obtained after performing a combined fit across all of the CRs and SR or CR-only.

Bayesian upper exclusion limits on the ratio $g_{W'}/g_{W}$ for an SSM-like W$\prime$ boson are shown. The unity coupling ratio (blue dotted curve) corresponds to the SSM common benchmark. The 68 and 95% quantiles of the limits are represented by the green and yellow bands, respectively.

Bayesian lower exclusion limits on the NUGIM G(221) mixing angle $\cot(\theta_{E})$ are shown as a function of the W$\prime$ boson mass. The theoretically excluded region is shaded in grey. The 68 and 95% quantiles of the limits are represented by the green and yellow bands, respectively.

Bayesian upper exclusion limits at 95% CL on the product of the production cross section and branching fraction of a QBH in an associated $ au$ lepton and neutrino final state. Minimum threshold masses $m_{th}$ of up to 6.6 TeV are excluded at 95% CL. The observed limit (solid line) is obtained from the intersection with the LO QBH cross section (blue dotted curve). The 68 and 95% quantiles of the limits are represented by the green and yellow bands, respectively.

Bayesian upper limits at 95% CL on the cross section of the process $pp\rightarrow\tau\nu$ mediated via LQ exchange in the t-channel. The inner (green) band and the outer (yellow) band indicate the regions containing 68 and 95%, respectively, of the distribution of limits expected under the background-only hypothesis. The predicted LQ cross section at LO in the three coupling benchmark scenarios is depicted in different colors for $g_{U}=1$. The uncertainty bandy correspond to the sum in quadrature of PDF and scale variations. The first benchmark scenario considers only couplings to left-handed SM fermions (i.e. $\beta_{\text{R}}^{ij}=0$) and is referred to as "best fit LH". The second benchmark, referred to as "best fit LH+RH", considers $|\beta_{\text{R}}^{\text{b}\tau}|=1$ and all other $\beta_{\text{R}}^{ij}=0$. In the third "democratic" benchmark, equal couplings only to LH fermions are assumed, i.e. $\beta_{\text{L}}^{ij}=1$ and $\beta_{\text{R}}^{ij}=0$ for all $i$ and $j$.

Expected and observed lower limits of the LQ mass as a function of the coupling $g_{U}$ in the LH scenario. The blue band shows the 68% and 95% regions of $g_{U}$ preferred by the fit to the b anomalies data.

Expected and observed lower limits of the LQ mass as a function of the coupling $g_{U}$ in the LH+RH scenario. The blue band shows the 68% and 95% regions of $g_{U}$ preferred by the fit to the b anomalies data.

Expected and observed lower limits of the LQ mass as a function of the coupling $g_{U}$ in the democratic scenario. The blue band shows the 68% and 95% regions of $g_{U}$ preferred by the fit to the b anomalies data.

Bayesian upper exclusion limits at 95% CL on each of the Wilson coefficients described by the EFT model based on 2016-2018 data. The three different coupling types represent a left-handed vector coupling ($\epsilon^{cb}_{L}$), tensor-like coupling ($\epsilon^{cb}_{T}$), and scalar-tensor-like coupling ($\epsilon^{cb}_{S_{L}}$). The 68 and 95% quantiles of the limits are represented by the green and yellow bands, respectively.

Summary of exclusion limits (expected and observed) calculated at 95% CL for full Run-2 CMS data.

Background prediction and observed data yields in the signal region bins. The background yields are obtained from the background-only fit and serve as input to the simplified likelihood reinterpretation scheme. The naming of the bins is "year_binnumber", following the binning from Figure 4.

Matrix of covariance coefficients between signal region bins. The coefficients are obtained from the background-only fit and serve as input to the simplified likelihood reinterpretation scheme. The naming of the bins is "year_binnumber", following the binning used in Figure 4.

Predicted signal yields for the 2017 data-taking period, corresponding to 41.3 fb$^{-1}$, after the application of each search requirement (cumulative) for various signal hypothesis. The requirements listed are presented as total efficiencies w.r.t. the previous selection step.

Feynman diagrams of the effective neutralino pair production in the GMSB simplified model in which the two neutralinos decay into two gravitinos ($\tilde{G}$) and two $Z$ bosons (left), a $Z$ and a Higgs boson ($H$) (center), or two Higgs bosons (right).

Feynman diagrams of the effective neutralino pair production in the GMSB simplified model in which the two neutralinos decay into two gravitinos ($\tilde{G}$) and two $Z$ bosons (left), a $Z$ and a Higgs boson ($H$) (center), or two Higgs bosons (right).

Feynman diagrams of the effective neutralino pair production in the GMSB simplified model in which the two neutralinos decay into two gravitinos ($\tilde{G}$) and two $Z$ bosons (left), a $Z$ and a Higgs boson ($H$) (center), or two Higgs bosons (right).

Feynman diagrams of the effective neutralino pair production in the GMSB simplified model in which the two neutralinos decay into two gravitinos ($\tilde{G}$) and two $Z$ bosons (left), a $Z$ and a Higgs boson ($H$) (center), or two Higgs bosons (right).

Feynman diagrams of the effective neutralino pair production in the GMSB simplified model in which the two neutralinos decay into two gravitinos ($\tilde{G}$) and two $Z$ bosons (left), a $Z$ and a Higgs boson ($H$) (center), or two Higgs bosons (right).

The distributions of the most impactful input variables to the TD jet tagger for signal (red, lighter) and collision background (blue, darker). They include the charged (upper left) and neutral (upper right) hadron energy fractions, the number of track constituents in the jet (middle left), the $\Delta R$ between the jet axis and the closest track associated with the PV (middle right), and the jet time (lower).

The distributions of the most impactful input variables to the TD jet tagger for signal (red, lighter) and collision background (blue, darker). They include the charged (upper left) and neutral (upper right) hadron energy fractions, the number of track constituents in the jet (middle left), the $\Delta R$ between the jet axis and the closest track associated with the PV (middle right), and the jet time (lower).

The distributions of the most impactful input variables to the TD jet tagger for signal (red, lighter) and collision background (blue, darker). They include the charged (upper left) and neutral (upper right) hadron energy fractions, the number of track constituents in the jet (middle left), the $\Delta R$ between the jet axis and the closest track associated with the PV (middle right), and the jet time (lower).

The distributions of the most impactful input variables to the TD jet tagger for signal (red, lighter) and collision background (blue, darker). They include the charged (upper left) and neutral (upper right) hadron energy fractions, the number of track constituents in the jet (middle left), the $\Delta R$ between the jet axis and the closest track associated with the PV (middle right), and the jet time (lower).

The distributions of the most impactful input variables to the TD jet tagger for signal (red, lighter) and collision background (blue, darker). They include the charged (upper left) and neutral (upper right) hadron energy fractions, the number of track constituents in the jet (middle left), the $\Delta R$ between the jet axis and the closest track associated with the PV (middle right), and the jet time (lower).

The distributions of the most impactful input variables to the TD jet tagger for signal (red, lighter) and collision background (blue, darker). They include the charged (upper left) and neutral (upper right) hadron energy fractions, the number of track constituents in the jet (middle left), the $\Delta R$ between the jet axis and the closest track associated with the PV (middle right), and the jet time (lower).

The distributions of the most impactful input variables to the TD jet tagger for signal (red, lighter) and collision background (blue, darker). They include the charged (upper left) and neutral (upper right) hadron energy fractions, the number of track constituents in the jet (middle left), the $\Delta R$ between the jet axis and the closest track associated with the PV (middle right), and the jet time (lower).

The distributions of the most impactful input variables to the TD jet tagger for signal (red, lighter) and collision background (blue, darker). They include the charged (upper left) and neutral (upper right) hadron energy fractions, the number of track constituents in the jet (middle left), the $\Delta R$ between the jet axis and the closest track associated with the PV (middle right), and the jet time (lower).

The distributions of the most impactful input variables to the TD jet tagger for signal (red, lighter) and collision background (blue, darker). They include the charged (upper left) and neutral (upper right) hadron energy fractions, the number of track constituents in the jet (middle left), the $\Delta R$ between the jet axis and the closest track associated with the PV (middle right), and the jet time (lower).

The distributions of the most impactful input variables to the TD jet tagger for signal (red, lighter) and collision background (blue, darker). They include the charged (upper left) and neutral (upper right) hadron energy fractions, the number of track constituents in the jet (middle left), the $\Delta R$ between the jet axis and the closest track associated with the PV (middle right), and the jet time (lower).

TD jet tagger score distributions (left) for signal (red, lighter) and collision background (blue, darker). Identification probability for the signal versus the misidentification probability for the background (right) with the tagger working point (w.~p.) used in the analysis shown as a blue marker.

TD jet tagger score distributions (left) for signal (red, lighter) and collision background (blue, darker). Identification probability for the signal versus the misidentification probability for the background (right) with the tagger working point (w.~p.) used in the analysis shown as a blue marker. Both are evaluated using an independent sample of testing events.

TD jet tagger score distributions (left) for signal (red, lighter) and collision background (blue, darker). Identification probability for the signal versus the misidentification probability for the background (right) with the tagger working point (w.~p.) used in the analysis shown as a blue marker.

TD jet tagger score distributions (left) for signal (red, lighter) and collision background (blue, darker). Identification probability for the signal versus the misidentification probability for the background (right) with the tagger working point (w.~p.) used in the analysis shown as a blue marker. Both are evaluated using an independent sample of testing events.

The TD jet tagger score distributions for simulation (shaded histogram) and data (black markers) when using electrons from $W\to e\nu_e$ events as proxy objects for signal jets. The last bin contains jets with tagger scores greater than 0.996, the threshold used to tag signal jets. Similar levels of agreement are observed for photon proxy objects from the $Z\to\ell^+\ell^-\gamma$ sample.

The efficiency of the TD jet tagger working point used in the analysis is shown as a function of the lab frame transverse decay length for simulated signals with $\chi$ mass of 400 GeV. The uncertainties shown account for lifetime dependence and statistical uncertainty.

The TD jet tagger misidentification probability measured using the nominal $W$+jets MR is shown along with the systematic uncertainty, quantifying the degree of process dependence measured from alternative MRs. On the left, this probability is shown for the first 19.9 fb$^{-1}$ of data collected in 2016, while on the right it is shown for the last 16.4 fb$^{-1}$ of data collected in 2016combined with data collected in 2017-2018.

The TD jet tagger score distributions for simulation (shaded histogram) and data (black markers) when using electrons from $W\to e\nu_e$ events as proxy objects for signal jets. The histograms and data points have been normalized to unit area. The last bin contains jets with tagger scores greater than 0.996, the threshold used to tag signal jets. Similar levels of agreement are observed for photon proxy objects from the $Z\to\ell^+\ell^-\gamma$ sample.

The TD jet tagger misidentification probability measured using the nominal $W$+jets MR is shown along with the systematic uncertainty, quantifying the degree of process dependence measured from alternative MRs. On the left, this probability is shown for the first 19.9 fb$^{-1}$ of data collected in 2016, while on the right it is shown for the last 16.4 fb$^{-1}$ of data collected in 2016combined with data collected in 2017-2018.

The TD jet tagger misidentification probability measured using the nominal $W$+jets MR (black round markers) is shown along with the systematic uncertainty (gray band), quantifying the degree of process dependence measured from alternative MRs. The measurements in the alternative MRs are displayed as well ($Z$+jets MR as green round markers, $t\bar{t}$ MR as red squared markers, QCD MR as blue triangular markers) along with their respective statistical uncertainty. On the left, this probability is shown for the first 19.9 fb$^{-1}$ of data collected in 2016, while on the right it is shown for the last 16.4 fb$^{-1}$ of data collected in 2016combined with data collected in 2017-2018.

Distribution of the number of TD tagged jets for the $m_{\chi} = 400$ GeVsimulated signal samples with $c\tau_{\chi} = 0.5$ m (solid red line) and $c\tau_{\chi} = 3.0$ m (dotted green line), estimated background (blue square markers), and data (black round markers). The blue shaded region indicates the systematic uncertainty in the background prediction. No background prediction is shown for the bin with zero TD tagged jets as it is the main control region used to predict the background for the other two bins. There are zero observed events in the bin with two or more TD tagged jets.

The TD jet tagger misidentification probability measured using the nominal $W$+jets MR (black round markers) is shown along with the systematic uncertainty (gray band), quantifying the degree of process dependence measured from alternative MRs. The measurements in the alternative MRs are displayed as well ($Z$+jets MR as green round markers, $t\bar{t}$ MR as red squared markers, QCD MR as blue triangular markers) along with their respective statistical uncertainty. On the left, this probability is shown for the first 19.9 fb$^{-1}$ of data collected in 2016, while on the right it is shown for the last 16.4 fb$^{-1}$ of data collected in 2016combined with data collected in 2017-2018.

Expected and observed 95% CL upper limits on $\sigma_{\chi\chi}$ as functions of $m_\chi$ in a scenario with $\mathcal{B}(\chi\to HG) = 0.5$ and $c\tau = 0.5$ m (left) or 3 m (right).

Distribution of the number of TD tagged jets for the $m_{\chi} = 400$ GeVsimulated signal samples with $c\tau_{\chi} = 0.5$ m (solid red line) and $c\tau_{\chi} = 3.0$ m (dotted green line), estimated background (blue square markers), and data (black round markers). The signal distributions are normalized to the expected cross section limit. The blue shaded region indicates the systematic uncertainty in the background prediction. No background prediction is shown for the bin with zero TD tagged jets as it is the main control region used to predict the background for the other two bins. There are zero observed events in the bin with two or more TD tagged jets.

Expected and observed 95% CL upper limits on $\sigma_{\chi\chi}$ as functions of $m_\chi$ in a scenario with $\mathcal{B}(\chi\to HG) = 0.5$ and $c\tau = 0.5$ m (left) or 3 m (right).

Expected and observed 95% CL upper limits on $\sigma_{\chi\chi}$ as functions of $m_\chi$ in a scenario with $\mathcal{B}(\chi\to HG) = 0.5$ and $c\tau = 0.5$ m (left) or 3 m (right).

Expected and observed 95% CL upper limits on $\sigma_{\chi\chi}$ as functions of $c\tau_{\chi}$ in a scenario with $\mathcal{B}(\chi\to H\tilde{G}) = 0.5$ and $m_{\chi} = 400$ GeV (left) or 1000 GeV (right).

Expected and observed 95% CL upper limits on $\sigma_{\chi\chi}$ as functions of $m_\chi$ in a scenario with $\mathcal{B}(\chi\to HG) = 0.5$ and $c\tau = 0.5$ m (left) or 3 m (right).

Expected and observed 95% CL upper limits on $\sigma_{\chi\chi}$ as functions of $c\tau_{\chi}$ in a scenario with $\mathcal{B}(\chi\to H\tilde{G}) = 0.5$ and $m_{\chi} = 400$ GeV (left) or 1000 GeV (right).

Expected and observed 95% CL upper limits on $\sigma_{\chi\chi}$ as functions of $c\tau_{\chi}$ in a scenario with $\mathcal{B}(\chi\to H\tilde{G}) = 0.5$ and $m_{\chi} = 400$ GeV (left) or 1000 GeV (right).

The observed 95% CL upper limit on $\sigma_{\chi\chi}$ as a function of $m_{\chi}$ and $c\tau_{\chi}$ in a scenario with $\mathcal{B}(\chi\to H\tilde{G}) = 0.5$. The area enclosed by the dotted black line corresponds to the observed excluded region.

Expected and observed 95% CL upper limits on $\sigma_{\chi\chi}$ as functions of $c\tau_{\chi}$ in a scenario with $\mathcal{B}(\chi\to H\tilde{G}) = 0.5$ and $m_{\chi} = 400$ GeV (left) or 1000 GeV (right).

The observed 95% CL upper limit on $\sigma_{\chi\chi}$ as a function of $m_{\chi}$ and $c\tau_{\chi}$ in a scenario with $\mathcal{B}(\chi\to H\tilde{G}) = 0.5$. The area enclosed by the dotted black line corresponds to the observed excluded region.

The distribution of the jet charged hadron energy fraction, a variable used as input to the TD jet tagger score, for simulation (shaded histogram) and data (black markers) when using electrons from $W\to e\nu_e$ events as proxy objects for signal jets. The histograms and data points have been normalized to unit area. Similar levels of agreement are observed for photon proxy objects from the $Z\to\ell^+\ell^-\gamma$ sample.

The distribution of the jet neutral hadron energy fraction, a variable used as input to the TD jet tagger score, for simulation (shaded histogram) and data (black markers) when using electrons from $W\to e\nu_e$ events as proxy objects for signal jets. The histograms and data points have been normalized to unit area. Similar levels of agreement are observed for photon proxy objects from the $Z\to\ell^+\ell^-\gamma$ sample.

The distribution of the number of track constituents in the jet, a variable used as input to the TD jet tagger score, for simulation (shaded histogram) and data (black markers) when using electrons from $W\to e\nu_e$ events as proxy objects for signal jets. The histograms and data points have been normalized to unit area. Similar levels of agreement are observed for photon proxy objects from the $Z\to\ell^+\ell^-\gamma$ sample.

The $\eta$ distribution of TD-tagged jets in a background-enriched control region that comprises events with exactly one TD-tagged jet. Observed data (black round markers) and the corresponding prediction based on control samples in data (empty squared markers), measured using the nominal $W$+jets MR, are compared. The prediction uncertainty (gray band) includes the systematic uncertainty quantifying the degree of process dependence measured from alternative MRs. The predictions for the shape and the normalization of the $\eta$ distribution are consistent with the data.

Jet time distribution in a sample of b-tagged jets from dilepton $t \bar{t}$ events in 2017 data-taking period (black round markers) and simulation (filled histogram). A Gaussian smearing procedure is applied to the jet time in the $t \bar{t}$ sample (green line) to correct for effects that are difficult to simulate (timing drift caused by crystals transparency loss due to detector aging, electronics jitter).

The observed 95% CL upper limit on $\sigma_{\chi\chi}$ as a function of $m_{\chi}$ and $c\tau_{\chi}$ in a scenario with $\mathcal{B}(\chi\to H\tilde{G}) = 1$. The area enclosed by the dotted black line corresponds to the observed excluded region.

The observed 95% CL upper limit on $\sigma_{\chi\chi}$ as a function of $m_{\chi}$ and $c\tau_{\chi}$ in a scenario with $\mathcal{B}(\chi\to H\tilde{G}) = 0.75$, $\mathcal{B}(\chi\to Z\tilde{G}) = 0.25$. The area enclosed by the dotted black line corresponds to the observed excluded region.

The observed 95% CL upper limit on $\sigma_{\chi\chi}$ as a function of $m_{\chi}$ and $c\tau_{\chi}$ in a scenario with $\mathcal{B}(\chi\to H\tilde{G}) = 0.25$, $\mathcal{B}(\chi\to Z\tilde{G}) = 0.75$. The area enclosed by the dotted black line corresponds to the observed excluded region.

The observed 95% CL upper limit on $\sigma_{\chi\chi}$ as a function of $m_{\chi}$ and $c\tau_{\chi}$ in a scenario with $\mathcal{B}(\chi\to Z\tilde{G}) = 1$. The area enclosed by the dotted black line corresponds to the observed excluded region.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 127 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the merged topology, namely, the H (or Z) decay products are produced with an angular separation $\Delta R < 0.8$, and the H (or Z) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 3\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 127 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with exactly one quark in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and only one b-quark (or light quark) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 5\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 127 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with two quarks in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and both b-quarks (or light quarks) have $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 7\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 150 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the merged topology, namely, the H (or Z) decay products are produced with an angular separation $\Delta R < 0.8$, and the H (or Z) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 3\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 150 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with exactly one quark in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and only one b-quark (or light quark) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 5\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 150 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with two quarks in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and both b-quarks (or light quarks) have $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 7\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 175 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the merged topology, namely, the H (or Z) decay products are produced with an angular separation $\Delta R < 0.8$, and the H (or Z) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 3\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 175 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with exactly one quark in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and only one b-quark (or light quark) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 5\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 175 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with two quarks in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and both b-quarks (or light quarks) have $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 7\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 200 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the merged topology, namely, the H (or Z) decay products are produced with an angular separation $\Delta R < 0.8$, and the H (or Z) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 3\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 200 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with exactly one quark in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and only one b-quark (or light quark) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 5\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 200 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with two quarks in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and both b-quarks (or light quarks) have $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 7\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 250 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the merged topology, namely, the H (or Z) decay products are produced with an angular separation $\Delta R < 0.8$, and the H (or Z) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 3\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 250 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with exactly one quark in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and only one b-quark (or light quark) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 5\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 250 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with two quarks in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and both b-quarks (or light quarks) have $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 7\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 300 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the merged topology, namely, the H (or Z) decay products are produced with an angular separation $\Delta R < 0.8$, and the H (or Z) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 3\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 300 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with exactly one quark in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and only one b-quark (or light quark) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 5\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 300 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with two quarks in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and both b-quarks (or light quarks) have $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 7\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 400 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the merged topology, namely, the H (or Z) decay products are produced with an angular separation $\Delta R < 0.8$, and the H (or Z) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 3\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 400 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with exactly one quark in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and only one b-quark (or light quark) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 5\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 400 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with two quarks in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and both b-quarks (or light quarks) have $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 7\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 600 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the merged topology, namely, the H (or Z) decay products are produced with an angular separation $\Delta R < 0.8$, and the H (or Z) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 3\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 600 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with exactly one quark in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and only one b-quark (or light quark) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 5\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 600 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with two quarks in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and both b-quarks (or light quarks) have $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 7\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 800 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the merged topology, namely, the H (or Z) decay products are produced with an angular separation $\Delta R < 0.8$, and the H (or Z) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 3\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 800 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with exactly one quark in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and only one b-quark (or light quark) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 5\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 800 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with two quarks in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and both b-quarks (or light quarks) have $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 7\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 1000 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the merged topology, namely, the H (or Z) decay products are produced with an angular separation $\Delta R < 0.8$, and the H (or Z) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 3\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 1000 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with exactly one quark in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and only one b-quark (or light quark) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 5\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 1000 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with two quarks in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and both b-quarks (or light quarks) have $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 7\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 1250 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the merged topology, namely, the H (or Z) decay products are produced with an angular separation $\Delta R < 0.8$, and the H (or Z) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 3\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 1250 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with exactly one quark in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and only one b-quark (or light quark) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 5\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 1250 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with two quarks in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and both b-quarks (or light quarks) have $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 7\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 1500 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the merged topology, namely, the H (or Z) decay products are produced with an angular separation $\Delta R < 0.8$, and the H (or Z) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 3\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 1500 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with exactly one quark in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and only one b-quark (or light quark) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 5\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 1500 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with two quarks in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and both b-quarks (or light quarks) have $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 7\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 1800 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the merged topology, namely, the H (or Z) decay products are produced with an angular separation $\Delta R < 0.8$, and the H (or Z) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 3\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 1800 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with exactly one quark in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and only one b-quark (or light quark) has $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 5\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

The efficiency of identifying a LLP decay as a TD-tagged jet in bins of the LLP transverse and longitudinal decay position. The sample used to compute the efficiency contains events with pair production of $\chi$ with a mass of 1800 GeV and a lifetime of 0.5 and 3 m, and considering the combinations of the $\chi$ decay modes considered in this search ($H \tilde{G} \rightarrow b\bar{b} \tilde{G}$ or $Z\tilde{G} \rightarrow q\bar{q} \tilde{G}$). The efficiency is calculated on top of the acceptance definition for the resolved topology with two quarks in acceptance, namely, the H (or Z) decay products are produced with an angular separation $\Delta R \geq 0.8$, and both b-quarks (or light quarks) have $p_T > 30$ GeV and $|\eta|<1$. The full simulation signal yield prediction can be reproduced within 7\%. This nonclosure uncertainty is added in quadrature to the statistical uncertainty of each bin.

Cutflow table for a $\tilde{\chi}_{1}^{0}$ signal sample with a mass of 127 GeV.

Cutflow table for a $\tilde{\chi}_{1}^{0}$ signal sample with a mass of 127 GeV.

Cutflow table for a $\tilde{\chi}_{1}^{0}$ signal sample with a mass of 150 GeV.

Cutflow table for a $\tilde{\chi}_{1}^{0}$ signal sample with a mass of 150 GeV.

Cutflow table for a $\tilde{\chi}_{1}^{0}$ signal sample with a mass of 175 GeV.

Cutflow table for a $\tilde{\chi}_{1}^{0}$ signal sample with a mass of 175 GeV.

Cutflow table for a $\tilde{\chi}_{1}^{0}$ signal sample with a mass of 200 GeV.

Cutflow table for a $\tilde{\chi}_{1}^{0}$ signal sample with a mass of 200 GeV.

Cutflow table for a $\tilde{\chi}_{1}^{0}$ signal sample with a mass of 250 GeV.

Cutflow table for a $\tilde{\chi}_{1}^{0}$ signal sample with a mass of 250 GeV.

Cutflow table for a $\tilde{\chi}_{1}^{0}$ signal sample with a mass of 300 GeV.

Cutflow table for a $\tilde{\chi}_{1}^{0}$ signal sample with a mass of 300 GeV.

Cutflow table for a $\tilde{\chi}_{1}^{0}$ signal sample with a mass of 400 GeV.

Expected and observed upper limits on the AQGC operators $a^Z_C/\Lambda^2$, with no unitarization. The $y$ axis shows the limit on the ratio of the observed cross section to the cross section predicted for each anomalous coupling value ($\sigma_\mathrm{AQGC}$).

Limits on LEP-like dimension-6 anomalous quartic gauge coupling parameters, with and without unitarization via a clipping procedure.

Conversion of limits on $a^W_0$ to dimension-8 $f_{M,i}$ operators, using the assumption of vanishing $WWZ\gamma$ couplings to eliminate some parameters. When quoting limits on one of the operators, the other is fixed to zero. The results for $|f_{M,0}/\Lambda^{4}|$ and $|f_{M,4}/\Lambda^{4}|$ are shown with and without clipping of the signal model at 1.4 TeV, when the other parameter is fixed to the SM value of zero.

Conversion of limits on $a^W_0$ and $a^W_C$ to dimension-8 $f_{M,i}$ operators, using the assumption that all $f_{M,i}$ except one are equal to zero. The results are shown with and without clipping of the signal model at 1.4 TeV.

{Expected and observed limits in the two-dimensional plane of $a^W_0/\Lambda^2$ vs. $a^W_C/\Lambda^2$. The limits are described by analytical ellipses of equation $(x-x0)^2/a^2 + (y-y0)^2/b^2 = 1$ and rotated counter-clockwise by $\theta$ degrees, where $x$ and $y$ in the equation correspond to the $a_0^W$ and $a_C^W$ couplings, respectively.

{Expected and observed limits in the two-dimensional plane of $a^W_0/\Lambda^2$ vs. $a^W_C/\Lambda^2$ with unitarization imposed by clipping the signal model at 1.4 TeV. The limits are described by analytical ellipses of equation $(x-x0)^2/a^2 + (y-y0)^2/b^2 = 1$ and rotated counter-clockwise by $\theta$ degrees, where $x$ and $y$ in the equation correspond to the $a_0^W$ and $a_C^W$ couplings, respectively.

{Expected and observed limits in the two-dimensional plane of $a^Z_0/\Lambda^2$ vs. $a^Z_C/\Lambda^2$. The limits are described by analytical ellipses of equation $(x-x0)^2/a^2 + (y-y0)^2/b^2 = 1$ and rotated counter-clockwise by $\theta$ degrees, where $x$ and $y$ in the equation correspond to the $a_0^Z$ and $a_C^Z$ couplings, respectively.

Distribution of the MLP W+jets score in the CRs for the $T\overline{T}$ search. The observed data, predicted $T\overline{T}$ signal with mass of 1.2 (1.5) TeV in the singlet scenario, and the background are all shown. Statistical and systematic uncertainties in the background prediction before performing the fit to data are also shown.

Distribution of DeepAK8 jet tags in the DeepAK8 CR of the $T\overline{T}$ search. The observed data are shown using black markers, $T\overline{T}$ signals using solid lines, and background using filled histograms. Statistical and systematic uncertainties in the background prediction before performing the fit to data are shown by the hatched region.

Distribution of HT in the W+jets CR of the $T\overline{T}$ search. The observed data are shown using black markers, $T\overline{T}$ signals using solid lines, and background using filled histograms. Statistical and systematic uncertainties in the background prediction before performing the fit to data are shown by the hatched region.

Distribution of HT in the $T\overline{T}$ CR of the $T\overline{T}$ search. The observed data are shown using black markers, $T\overline{T}$ signals using solid lines, and background using filled histograms. Statistical and systematic uncertainties in the background prediction before performing the fit to data are shown by the hatched region.

Numbers of predicted and observed CR events in 2016--2018 data for the $T\overline{T}$ signal hypotheses in the single-lepton channel, after a background-only fit to data. Predicted numbers of signal events before the fit to data are included for comparison, using the singlet branching fraction scenario. Uncertainties include statistical and systematic components, and lepton flavor categories are combined with their uncertainties added in quadrature. Values in the DeepAK8 CR represent the number of large-radius jets rather than number of events.

Numbers of predicted and observed CR events in 2016--2018 data for the $B\overline{B}$ signal hypotheses in the single-lepton channel, after a background-only fit to data. Predicted numbers of signal events before the fit to data are included for comparison, using the singlet branching fraction scenario. Uncertainties include statistical and systematic components, and lepton flavor categories are combined with their uncertainties added in quadrature. Values in the DeepAK8 CR represent the number of large-radius jets rather than number of events.

Numbers of predicted and observed CR events in 2017--2018 data in the same-sign dilepton channel, after a background-only fit to data. Predicted numbers of signal events before the fit to data are included for comparison, using the singlet branching fraction scenario. Uncertainties include statistical and systematic components. Predictions for 2017 and 2018 are combined with their uncertainties added in quadrature.

Distribution of lepton $p_T$ in 2017 in the multilepton channel nonprompt lepton control region for all flavor categories, evaluated with the best-fit nonprompt rates. The uncertainty shown is the quadratic sum of statistical and systematics uncertainties.

Distribution of lepton $p_T$ in 2018 in the multilepton channel nonprompt lepton control region for all flavor categories, evaluated with the best-fit nonprompt rates. The uncertainty shown is the quadratic sum of statistical and systematics uncertainties.

Numbers of predicted and observed CR events in 2017--2018 data in the multilepton channel, after a background-only fit to data. Predicted numbers of signal events before the fit to data are included for comparison, using the singlet branching fraction scenario. Uncertainties include statistical and systematic components. Predictions for 2017 and 2018 are combined with their uncertainties added in quadrature.

Numbers of predicted and observed $T\overline{T}$ SR events in 2016--2018 data in the single-lepton channel, after a background-only fit to data. Predicted numbers of signal events before the fit to data are included for comparison, using the singlet branching fraction scenario. Uncertainties include statistical and systematic components, and lepton flavor categories are combined with their uncertainties added in quadrature.

Distribution of the VLQ score in single-lepton category 1. Observed data is shown using black markers, $T\overline{T}$ signal with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region. Electron and muon categories have been combined with their uncertainties added in quadrature.

Distribution of the VLQ score in single-lepton category 2. Observed data is shown using black markers, $T\overline{T}$ signal with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region. Electron and muon categories have been combined with their uncertainties added in quadrature.

Distribution of the VLQ score in single-lepton category 3. Observed data is shown using black markers, $T\overline{T}$ signal with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region. Electron and muon categories have been combined with their uncertainties added in quadrature.

Distribution of the VLQ score in single-lepton category 4. Observed data is shown using black markers, $T\overline{T}$ signal with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region. Electron and muon categories have been combined with their uncertainties added in quadrature.

Distribution of the VLQ score in single-lepton category 5. Observed data is shown using black markers, $T\overline{T}$ signal with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region. Electron and muon categories have been combined with their uncertainties added in quadrature.

Distribution of the VLQ score in single-lepton category 6. Observed data is shown using black markers, $T\overline{T}$ signal with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region. Electron and muon categories have been combined with their uncertainties added in quadrature.

Distribution of the VLQ score in single-lepton category 7. Observed data is shown using black markers, $T\overline{T}$ signal with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region. Electron and muon categories have been combined with their uncertainties added in quadrature.

Distribution of the VLQ score in single-lepton category 8. Observed data is shown using black markers, $T\overline{T}$ signal with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region. Electron and muon categories have been combined with their uncertainties added in quadrature.

Distribution of the VLQ score in single-lepton category 9. Observed data is shown using black markers, $T\overline{T}$ signal with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region. Electron and muon categories have been combined with their uncertainties added in quadrature.

Distribution of the VLQ score in single-lepton category 10. Observed data is shown using black markers, $T\overline{T}$ signal with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region. Electron and muon categories have been combined with their uncertainties added in quadrature.

Distribution of the VLQ score in single-lepton category 11. Observed data is shown using black markers, $T\overline{T}$ signal with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region. Electron and muon categories have been combined with their uncertainties added in quadrature.

Distribution of the VLQ score in single-lepton category 12. Observed data is shown using black markers, $T\overline{T}$ signal with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region. Electron and muon categories have been combined with their uncertainties added in quadrature.

Distribution of $H_T^{\mathrm{lep}}$ in the same-sign dilepton signal region for $ee$ category. Data from 2017 and 2018 is shown using black markers, $T\overline{T}$ signals with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region.

Distribution of $H_T^{\mathrm{lep}}$ in the same-sign dilepton signal region for $e\mu$ category. Data from 2017 and 2018 is shown using black markers, $T\overline{T}$ signals with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region.

Distribution of $H_T^{\mathrm{lep}}$ in the same-sign dilepton signal region for $\mu\mu$ category. Data from 2017 and 2018 is shown using black markers, $T\overline{T}$ signals with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region.

Distribution of $S_T$ in the multilepton signal region for $eee$ category. Data from 2017 and 2018 is shown using black markers, $T\overline{T}$ signals with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region.

Distribution of $S_T$ in the multilepton signal region for $ee\mu$ category. Data from 2017 and 2018 is shown using black markers, $T\overline{T}$ signals with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region.

Distribution of $S_T$ in the multilepton signal region for $e\mu\mu$ category. Data from 2017 and 2018 is shown using black markers, $T\overline{T}$ signals with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region.

Distribution of $S_T$ in the multilepton signal region for $\mu\mu\mu$ category. Data from 2017 and 2018 is shown using black markers, $T\overline{T}$ signals with mass of 1.2 (1.5) TeV in the singlet scenario using solid (dashed) lines, and post-fit background using filled histograms. Statistical and systematic uncertainties in the background prediction after performing the fit to data are shown by the hatched region.

Numbers of predicted and observed $B\overline{B}$ SR events in 2016--2018 data in the single-lepton channel, after a background-only fit to data. Predicted numbers of signal events before the fit to data are included for comparison, using the singlet branching fraction scenario. Uncertainties include statistical and systematic components, and lepton flavor categories are combined with their uncertainties added in quadrature.

Numbers of predicted and observed SR events in 2017--2018 data in the same-sign dilepton channel, after a background-only fit to data. Predicted numbers of signal events before the fit to data are included for comparison, using the singlet branching fraction scenario. Uncertainties include statistical and systematic components. Predictions for 2017 and 2018 are combined with their uncertainties added in quadrature.

Numbers of predicted and observed SR events in 2017--2018 data in the multilepton channel, after a background-only fit to data. Predicted numbers of signal events before the fit to data are included for comparison, using the singlet branching fraction scenario. Uncertainties include statistical and systematic components. Predictions for 2017 and 2018 are combined with their uncertainties added in quadrature.

Expected and observed lower limits on the VLT quark masses.

Expected and observed lower limits on the VLB quark masses.

Expected 95% CL upper limits on $T\overline{T}$ production cross sections for the singlet combination.

Expected 95% CL upper limits on $T\overline{T}$ production cross sections for the doublet combination.

Expected 95% CL upper limits on $B\overline{B}$ production cross sections for the singlet combination.

Expected 95% CL upper limits on $B\overline{B}$ production cross sections for the doublet combination.

The 95% CL expected lower mass limits on pair-produced T quark masses as functions of their branching ratios to W and H bosons.

The 95% CL observed lower mass limits on pair-produced T quark masses as functions of their branching ratios to W and H bosons.

The 95% CL expected lower mass limits on pair-produced B quark masses as functions of their branching ratios to W and H bosons.

The 95% CL observed lower mass limits on pair-produced B quark masses as functions of their branching ratios to W and H bosons.

Invariant mass distribution of the diphoton pairs for the elastic selection region with events satisfying a < 0.005 (signal contribution is magnified by a factor 5000).

Predicted number of events having an elastic diphoton pair in association with a pair of protons observed within the range where the proton detectors have a radiation inefficiency less than 10%. The yields where the two-photon and two-proton systems mass and rapidity are matching at 2 and 3$\sigma$ are also quoted. This corresponds to a search region of $m_{\gamma\gamma} > 350$ GeV, $0.070 < \xi^+ < 0.111$, and $0.070 < \xi^- < 0.138$.

Predicted number of events having an elastic diphoton pair in association with a pair of protons observed within the range where the proton detectors have a radiation inefficiency less than 10%. The yields where the two-photon and two-proton systems mass and rapidity are matching at 2 and 3$\sigma$ are also quoted. This corresponds to a search region of $m_{\gamma\gamma} > 350$ GeV, $0.070 < \xi^+ < 0.111$, and $0.070 < \xi^- < 0.138$.

95% CL expected and observed frequentist upper limit for the LbL cross section within the $m_{\gamma\gamma} > 350$ GeV, $0.070 < \xi^+ < 0.111$, and $0.070 < \xi^- < 0.138$ search region.

95% CL expected and observed frequentist upper limit for the LbL cross section within the $m_{\gamma\gamma} > 350$ GeV, $0.070 < \xi^+ < 0.111$, and $0.070 < \xi^- < 0.138$ search region.

95% expected and observed one-dimensional limits on $\zeta_1$ and $\zeta_2$ anomalous LbyL production parameters, when the other parameter is set to zero. This corresponds to a search region of $m_{\gamma\gamma} > 350$ GeV, $0.070 < \xi^+ < 0.111$, and $0.070 < \xi^- < 0.138$.

95% expected and observed one-dimensional limits on $\zeta_1$ and $\zeta_2$ anomalous LbyL production parameters, when the other parameter is set to zero. This corresponds to a search region of $m_{\gamma\gamma} > 350$ GeV, $0.070 < \xi^+ < 0.111$, and $0.070 < \xi^- < 0.138$.

95% expected and observed limits on $\zeta_1$ and $\zeta_2$ anomalous LbyL production parameters. The parametric elliptic form is assumed: $a_0\zeta_1^2+a_1\zeta_1\zeta_2+a_2\zeta_2^2=1$. This corresponds to a search region of $m_{\gamma\gamma} > 350$ GeV, $0.070 < \xi^+ < 0.111$, and $0.070 < \xi^- < 0.138$.

95% expected and observed limits on $\zeta_1$ and $\zeta_2$ anomalous LbyL production parameters. The parametric elliptic form is assumed: $a_0\zeta_1^2+a_1\zeta_1\zeta_2+a_2\zeta_2^2=1$. This corresponds to a search region of $m_{\gamma\gamma} > 350$ GeV, $0.070 < \xi^+ < 0.111$, and $0.070 < \xi^- < 0.138$.

The number of background events obtained from the 1- and 2-leg predictions derived from data, together with the direct observation in data, in bins in ChF, where either the leading or subleading jet has a ChF within the bin edges, and both have a ChF below the upper bin threshold. The bottom panel shows the ratios of the observation in data to the 1-leg and the 2-leg background predictions.

The expected and observed 95% CL upper limits on the production cross section for SIMPs with masses between 1 and 1000 GeV, with the assumption that the SIMP interaction in the detector can be approximated as neutron-like. The theoretical prediction of a simplified model incorporating this approximation and including a scalar mediator with couplings g_chi = -1 and g_q = 1 is also shown (red line). For masses above 100 GeV, where the modelling of the SIMP-nucleon interaction becomes more speculative, the obtained cross section upper limits are increasingly uncertain (shaded area).

The ratio between the observed data and the simulation in the high $\Delta$m portion of the $\ell+\text{jets}$ control region as a function of $p_T^{miss}$ after scaling the simulation to match the total yield in data.

Comparison between data and simulation in the high $\Delta$m portion of the $\ell+\text{jets}$ control region as a function of $N_t$ after scaling the simulation to match the total yield in data. The hatched region indicates the total shape uncertainty in the simulation.

The ratio between the observed data and the simulation in the high $\Delta$m portion of the $\ell+\text{jets}$ control region as a function of $N_t$ after scaling the simulation to match the total yield in data.

Comparison between data and simulation in the high $\Delta$m portion of the $\ell+\text{jets}$ control region as a function of $N_W$ after scaling the simulation to match the total yield in data. The hatched region indicates the total shape uncertainty in the simulation.

The ratio between the observed data and the simulation in the high $\Delta$m portion of the $\ell+\text{jets}$ control region as a function of $N_W$ after scaling the simulation to match the total yield in data.

Comparison between data and simulation in the high $\Delta$m portion of the $\ell+\text{jets}$ control region as a function of $N_{\text{res}}$ after scaling the simulation to match the total yield in data. The hatched region indicates the total shape uncertainty in the simulation.

The ratio between the observed data and the simulation in the high $\Delta$m portion of the $\ell+\text{jets}$ control region as a function of $N_{\text{res}}$ after scaling the simulation to match the total yield in data.

Observed event yields in data (black points) and predicted SM background (filled histograms) for the low $\Delta$m search bins 0--52. The signal models are denoted in the legend with the masses in GeV of the SUSY particles in parentheses: $(m_{\tilde{t}}, m_{\tilde{\chi}^0_1})$ or $(m_{\tilde{g}}, m_{\tilde{\chi}^0_1})$ for the T2 or T1 signal models, respectively. The hatched bands correspond to the total uncertainty in the background prediction. The (unstacked) distributions for two example signal models are also shown.

The ratio of the data to the total background prediction for the low $\Delta$m search bins 0--52. The hatched bands correspond to the total uncertainty in the background prediction.

Observed event yields in data (black points) and predicted SM background (filled histograms) for the high $\Delta$m search bins 53--104. The signal models are denoted in the legend with the masses in GeV of the SUSY particles in parentheses: $(m_{\tilde{t}}, m_{\tilde{\chi}^0_1})$ or $(m_{\tilde{g}}, m_{\tilde{\chi}^0_1})$ for the T2 or T1 signal models, respectively. The hatched bands correspond to the total uncertainty in the background prediction. The (unstacked) distributions for two example signal models are also shown.

The ratio of the data to the total background prediction for the high $\Delta$m search bins 53--104. The hatched bands correspond to the total uncertainty in the background prediction.

Observed event yields in data (black points) and predicted SM background (filled histograms) for the high $\Delta$m search bins 105--152 with ${N_b = 2}$. The signal models are denoted in the legend with the masses in GeV of the SUSY particles in parentheses: $(m_{\tilde{t}}, m_{\tilde{\chi}^0_1})$ or $(m_{\tilde{g}}, m_{\tilde{\chi}^0_1})$ for the T2 or T1 signal models, respectively. The hatched bands correspond to the total uncertainty in the background prediction. The (unstacked) distributions for two example signal models are also shown.

The ratio of the data to the total background prediction for the high $\Delta$m search bins 105--152 with ${N_b = 2}$. The hatched bands correspond to the total uncertainty in the background prediction.

Observed event yields in data (black points) and predicted SM background (filled histograms) for the high $\Delta$m search bins 153--182 with ${N_b \geq 3}$. The signal models are denoted in the legend with the masses in GeV of the SUSY particles in parentheses: $(m_{\tilde{t}}, m_{\tilde{\chi}^0_1})$ or $(m_{\tilde{g}}, m_{\tilde{\chi}^0_1})$ for the T2 or T1 signal models, respectively. The hatched bands correspond to the total uncertainty in the background prediction. The (unstacked) distributions for two example signal models are also shown.

The ratio of the data to the total background prediction for the high $\Delta$m search bins 153--182 with ${N_b \geq 3}$. The hatched bands correspond to the total uncertainty in the background prediction.

The observed 95% CL upper limit on the production cross section of the T2tt simplified model as a function of the top squark and LSP masses. No interpretation is provided for signal models for which ${|{m_{\tilde{t}} - m_{\tilde{\chi}^0_1} - m_t}| < 25 GeV}$ and ${m_{\tilde{t}} < 275 GeV}$ as described in the text.

The expected 95% CL upper limit on the production cross section of the T2tt simplified model as a function of the top squark and LSP masses. No interpretation is provided for signal models for which ${|{m_{\tilde{t}} - m_{\tilde{\chi}^0_1} - m_t}| < 25 GeV}$ and ${m_{\tilde{t}} < 275 GeV}$ as described in the text.

The observed exclusion contour of the T2tt simplified model with respect to approximate NNLO+NNLL signal cross sections and the change in this contour due to variation of these cross sections within their theoretical uncertainties ($\sigma_{\text{theory}}$). No interpretation is provided for signal models for which ${|{m_{\tilde{t}} - m_{\tilde{\chi}^0_1} - m_t}| < 25 GeV}$ and ${m_{\tilde{t}} < 275 GeV}$ as described in the text.

The mean expected exclusion contour of the T2tt simplified model and the region containing 68 and 95\% ($\pm 1$ and $2\,\sigma_{\text{experiment}}$) of the distribution of expected exclusion limits under the background-only hypothesis. No interpretation is provided for signal models for which ${|{m_{\tilde{t}} - m_{\tilde{\chi}^0_1} - m_t}| < 25 GeV}$ and ${m_{\tilde{t}} < 275 GeV}$ as described in the text.

The observed 95% CL upper limit on the production cross section of the T2bW simplified model as a function of the top squark and LSP masses.

The expected 95% CL upper limit on the production cross section of the T2bW simplified model as a function of the top squark and LSP masses.

The observed exclusion contour of the T2bW simplified model with respect to approximate NNLO+NNLL signal cross sections and the change in this contour due to variation of these cross sections within their theoretical uncertainties ($\sigma_{\text{theory}}$).

The mean expected exclusion contour of the T2bW simplified model and the region containing 68 and 95\% ($\pm 1$ and $2\,\sigma_{\text{experiment}}$) of the distribution of expected exclusion limits under the background-only hypothesis.

The observed 95% CL upper limit on the production cross section of the T2tb simplified model as a function of the top squark and LSP masses.

The expected 95% CL upper limit on the production cross section of the T2tb simplified model as a function of the top squark and LSP masses.

The observed exclusion contour of the T2tb simplified model with respect to approximate NNLO+NNLL signal cross sections and the change in this contour due to variation of these cross sections within their theoretical uncertainties ($\sigma_{\text{theory}}$).

The mean expected exclusion contour of the T2tb simplified model and the region containing 68 and 95\% ($\pm 1$ and $2\,\sigma_{\text{experiment}}$) of the distribution of expected exclusion limits under the background-only hypothesis.

The observed 95% CL upper limit on the production cross section of the T2ttC simplified model as a function of the top squark mass and the difference between the top squark and LSP masses.

The expected 95% CL upper limit on the production cross section of the T2ttC simplified model as a function of the top squark mass and the difference between the top squark and LSP masses.

The observed exclusion contour of the T2ttC simplified model with respect to approximate NNLO+NNLL signal cross sections and the change in this contour due to variation of these cross sections within their theoretical uncertainties ($\sigma_{\text{theory}}$).

The mean expected exclusion contour of the T2ttC simplified model and the region containing 68\% ($\pm 1\,\sigma_{\text{experiment}}$) of the distribution of expected exclusion limits under the background-only hypothesis.

The observed 95% CL upper limit on the production cross section of the T2bWC simplified model as a function of the top squark mass and the difference between the top squark and LSP masses.

The expected 95% CL upper limit on the production cross section of the T2bWC simplified model as a function of the top squark mass and the difference between the top squark and LSP masses.

The observed exclusion contour of the T2bWC simplified model with respect to approximate NNLO+NNLL signal cross sections and the change in this contour due to variation of these cross sections within their theoretical uncertainties ($\sigma_{\text{theory}}$).

The mean expected exclusion contour of the T2bWC simplified model and the region containing 68\% ($\pm 1\,\sigma_{\text{experiment}}$) of the distribution of expected exclusion limits under the background-only hypothesis.

The observed 95% CL upper limit on the production cross section of the T2cc simplified model as a function of the top squark mass and the difference between the top squark and LSP masses.

The expected 95% CL upper limit on the production cross section of the T2cc simplified model as a function of the top squark mass and the difference between the top squark and LSP masses.

The observed exclusion contour of the T2cc simplified model with respect to approximate NNLO+NNLL signal cross sections and the change in this contour due to variation of these cross sections within their theoretical uncertainties ($\sigma_{\text{theory}}$).

The mean expected exclusion contour of the T2cc simplified model and the region containing 68\% ($\pm 1\,\sigma_{\text{experiment}}$) of the distribution of expected exclusion limits under the background-only hypothesis.

The observed 95% CL upper limit on the production cross section of the T1tttt simplified model as a function of the gluino and LSP masses.

The expected 95% CL upper limit on the production cross section of the T1tttt simplified model as a function of the gluino and LSP masses.

The observed exclusion contour of the T1tttt simplified model with respect to approximate NNLO+NNLL signal cross sections and the change in this contour due to variation of these cross sections within their theoretical uncertainties ($\sigma_{\text{theory}}$).

The mean expected exclusion contour of the T1tttt simplified model and the region containing 68 and 95\% ($\pm 1$ and $2\,\sigma_{\text{experiment}}$) of the distribution of expected exclusion limits under the background-only hypothesis.

The observed 95% CL upper limit on the production cross section of the T1ttbb simplified model as a function of the gluino and LSP masses.

The expected 95% CL upper limit on the production cross section of the T1ttbb simplified model as a function of the gluino and LSP masses.

The observed exclusion contour of the T1ttbb simplified model with respect to approximate NNLO+NNLL signal cross sections and the change in this contour due to variation of these cross sections within their theoretical uncertainties ($\sigma_{\text{theory}}$).

The mean expected exclusion contour of the T1ttbb simplified model and the region containing 68 and 95\% ($\pm 1$ and $2\,\sigma_{\text{experiment}}$) of the distribution of expected exclusion limits under the background-only hypothesis.

The observed 95% CL upper limit on the production cross section of the T5ttcc simplified model as a function of the gluino and LSP masses. The upper limits do not take into account contributions from direct top squark pair production; however, its effect is small for $m_{\tilde{\chi}^0_1} > 600 GeV$, which corresponds to the phase space beyond the exclusions based on direct top squark pair production. The excluded regions based on direct top squark pair production from this search and earlier searches are indicated by the hatched areas.

The expected 95% CL upper limit on the production cross section of the T5ttcc simplified model as a function of the gluino and LSP masses. The uppser limits do not take into account contributions from direct top squark pair production; however, its effect is small for $m_{\tilde{\chi}^0_1} > 600 GeV$, which corresponds to the phase space beyond the exclusions based on direct top squark pair production. The excluded regions based on direct top squark pair production from this search and earlier searches are indicated by the hatched areas.

The observed exclusion contour of the T5ttcc simplified model with respect to approximate NNLO+NNLL signal cross sections and the change in this contour due to variation of these cross sections within their theoretical uncertainties ($\sigma_{\text{theory}}$). The expected and observed upper limits do not take into account contributions from direct top squark pair production; however, its effect is small for $m_{\tilde{\chi}^0_1} > 600 GeV$, which corresponds to the phase space beyond the exclusions based on direct top squark pair production. The excluded regions based on direct top squark pair production from this search and earlier searches are indicated by the hatched areas.

The mean expected exclusion contour of the T5ttcc simplified model and the region containing 68% and 95% ($\pm 1$ and $2\,\sigma_{\text{experiment}}$) of the distribution of expected exclusion limits under the background-only hypothesis. The expected and observed upper limits do not take into account contributions from direct top squark pair production; however, its effect is small for $m_{\tilde{\chi}^0_1} > 600 GeV$, which corresponds to the phase space beyond the exclusions based on direct top squark pair production. The excluded regions based on direct top squark pair production from this search and earlier searches are indicated by the hatched areas.

The product of signal acceptance and efficiency in the 2l categories for the signal produced via vector boson fusion.

$m_{X}^{T}$ distribution in data in the 0l 2b non-VBF category. The data is shown as Events/10 GeV. The distribution is shown up 4000 GeV, which corresponds to the event with the highest $m_{X}^{T}$ observed in the SR.

$m_{X}^{T}$ distribution in data in the 0l $\leq$1b non-VBF category. The data is shown as Events/10 GeV. The distribution is shown up 4000 GeV, which corresponds to the event with the highest $m_{X}^{T}$ observed in the SR.

$m_{X}$ distribution in data in the 2e 2b non-VBF category. The data is shown as Events/10 GeV. The distribution is shown up 4000 GeV, which corresponds to the event with the highest $m_{X}$ observed in the SR.

$m_{X}$ distribution in data in the 2e $\leq$1b non-VBF category. The data is shown as Events/10 GeV. The distribution is shown up 4000 GeV, which corresponds to the event with the highest $m_{X}$ observed in the SR.

$m_{X}$ distribution in data in the 2$\mu$ 2b non-VBF category. The data is shown as Events/10 GeV. The distribution is shown up 4000 GeV, which corresponds to the event with the highest $m_{X}$ observed in the SR.

$m_{X}$ distribution in data in the 2$\mu$ $\leq$1b non-VBF category. The data is shown as Events/10 GeV. The distribution is shown up 4000 GeV, which corresponds to the event with the highest $m_{X}$ observed in the SR.

$m_{X}^{T}$ distribution in data in the 0l 2b VBF category. The data is shown as Events/10 GeV. The distribution is shown up 4000 GeV, which corresponds to the event with the highest $m_{X}^{T}$ observed in the SR.

$m_{X}^{T}$ distribution in data in the 0l $\leq$1b VBF category. The data is shown as Events/10 GeV. The distribution is shown up 4000 GeV, which corresponds to the event with the highest $m_{X}^{T}$ observed in the SR.

$m_{X}$ distribution in data in the 2e 2b VBF category. The data is shown as Events/10 GeV. The distribution is shown up 4000 GeV, which corresponds to the event with the highest $m_{X}$ observed in the SR.

$m_{X}$ distribution in data in the 2e $\leq$1b VBF category. The data is shown as Events/10 GeV. The distribution is shown up 4000 GeV, which corresponds to the event with the highest $m_{X}$ observed in the SR.

$m_{X}$ distribution in data in the 2$\mu$ 2b VBF category. The data is shown as Events/10 GeV. The distribution is shown up 4000 GeV, which corresponds to the event with the highest $m_{X}$ observed in the SR.

$m_{X}$ distribution in data in the 2$\mu$ $\leq$1b VBF category. The data is shown as Events/10 GeV. The distribution is shown up 4000 GeV, which corresponds to the event with the highest $m_{X}$ observed in the SR.

Observed and expected 95% CL upper limit on $\sigma \mathcal{B}$(Z'-> ZH) with all categories combined for the non-VBF signal, including all statistical and systematic uncertainties. The inner green band and the outer yellow band indicate the regions containing 68 and 95%, respectively, of the distribution of expected limits under the background-only hypothesis. The CMS search for a heavy resonance using 2016 data and the same final state [JHEP 11 (2018) 172] is shown as a comparison.

Observed and expected 95% CL upper limit on $\sigma \mathcal{B}$(Z'-> ZH) with all categories combined for the VBF signal, including all statistical and systematic uncertainties. The inner green band and the outer yellow band indicate the regions containing 68 and 95%, respectively, of the distribution of expected limits under the background-only hypothesis.

Observed exclusion limit in the space of the HVT model parameters [$g_{V}c_{H}$, $g^{2}c_{F}/g_{V}$] for mass hypotheses of 2 TeV for the non-VBF signal.

Observed exclusion limit in the space of the HVT model parameters [$g_{V}c_{H}$, $g^{2}c_{F}/g_{V}$] for mass hypotheses of 3 TeV for the non-VBF signal.

Observed exclusion limit in the space of the HVT model parameters [$g_{V}c_{H}$, $g^{2}c_{F}/g_{V}$] for mass hypotheses of 4 TeV for the non-VBF signal.

Differential cross sections normalized to the fiducial cross section for the combined 4e, 2e2µ, and 4µ decay channels as a function of the invariant mass of the ZZ system

Differential cross sections normalized to the fiducial cross section for the combined 4e, 2e2µ, and 4µ decay channels as a function of azimuthal separation of the two Z bosons

Differential cross sections normalized to the fiducial cross section for the combined 4e, 2e2µ, and 4µ decay channels as a function of ∆R separation of the two Z bosons

Measured fiducial cross section for each data sample and combined. The first uncertainty is statistical, the second is experimental systematic, and the third is associated with the integrated luminosity.

Measured total σ(pp → ZZ) cross section for each data sample and combined. The first uncertainty is statistical, the second is experimental systematic, the third is theoretical systematic. The fourth uncertainty is associated with the integrated luminosity.

Expected and observed one-dimensional 95% CL limits on aTGC parameters. The corresponding constrains on EFT parameters are estimated using the transformation from Ref. [65].

Expected and observed one-dimensional 95% CL limits on aTGC parameters. The corresponding constrains on EFT parameters are estimated using the transformation from Ref. [65].

Reconstructed VLQ mass distributions for simulated signal events with a generated VLQ mass $m_{B} = 1200\GeV$. A moderate requirement of $\chi^{2}$/ndf < 2$ is applied to the events. Mass distributions for 4-jet (left), 5-jet (center), and 6-jet (right) events are shown for the three decay modes: bHbH (upper row), bHbZ (middle row), and bZbZ (lower row).

Reconstructed VLQ mass distributions for simulated signal events with a generated VLQ mass $m_{B} = 1200\GeV$. A moderate requirement of $\chi^{2}$/ndf < 2$ is applied to the events. Mass distributions for 4-jet (left), 5-jet (center), and 6-jet (right) events are shown for the three decay modes: bHbH (upper row), bHbZ (middle row), and bZbZ (lower row).

Reconstructed VLQ mass distributions for simulated signal events with a generated VLQ mass $m_{B} = 1200\GeV$. A moderate requirement of $\chi^{2}$/ndf < 2$ is applied to the events. Mass distributions for 4-jet (left), 5-jet (center), and 6-jet (right) events are shown for the three decay modes: bHbH (upper row), bHbZ (middle row), and bZbZ (lower row).

Reconstructed VLQ mass distributions for simulated signal events with a generated VLQ mass $m_{B} = 1200\GeV$. A moderate requirement of $\chi^{2}$/ndf < 2$ is applied to the events. Mass distributions for 4-jet (left), 5-jet (center), and 6-jet (right) events are shown for the three decay modes: bHbH (upper row), bHbZ (middle row), and bZbZ (lower row).

Reconstructed VLQ mass distributions for simulated signal events with a generated VLQ mass $m_{B} = 1200\GeV$. A moderate requirement of $\chi^{2}$/ndf < 2$ is applied to the events. Mass distributions for 4-jet (left), 5-jet (center), and 6-jet (right) events are shown for the three decay modes: bHbH (upper row), bHbZ (middle row), and bZbZ (lower row).

Reconstructed VLQ mass distributions for simulated signal events with a generated VLQ mass $m_{B} = 1200\GeV$. A moderate requirement of $\chi^{2}$/ndf < 2$ is applied to the events. Mass distributions for 4-jet (left), 5-jet (center), and 6-jet (right) events are shown for the three decay modes: bHbH (upper row), bHbZ (middle row), and bZbZ (lower row).

Reconstructed VLQ mass distributions for simulated signal events with a generated VLQ mass $m_{B} = 1200\GeV$. A moderate requirement of $\chi^{2}$/ndf < 2$ is applied to the events. Mass distributions for 4-jet (left), 5-jet (center), and 6-jet (right) events are shown for the three decay modes: bHbH (upper row), bHbZ (middle row), and bZbZ (lower row).

Distribution of $\chi^{2}$/ndf for the best jet combination for simulated 1200\GeV VLQ events (red histogram) and data (black points), for 4-jet events (left), 5-jet events (center), and 6-jet events (right). The simulated signal events and data events are normalized to the same value within the displayed $\chi^{2}$/ndf range.

Distribution of $\chi^{2}$/ndf for the best jet combination for simulated 1200\GeV VLQ events (red histogram) and data (black points), for 4-jet events (left), 5-jet events (center), and 6-jet events (right). The simulated signal events and data events are normalized to the same value within the displayed $\chi^{2}$/ndf range.

Distribution of $\chi^{2}$/ndf for the best jet combination for simulated 1200\GeV VLQ events (red histogram) and data (black points), for 4-jet events (left), 5-jet events (center), and 6-jet events (right). The simulated signal events and data events are normalized to the same value within the displayed $\chi^{2}$/ndf range.

Distributions of the average reconstructed mass of VLQ candidates for the jet combination with the least $\chi^{2}$ in 4-jet (left), 5-jet (center), and 6-jet (right) multiplicity events. The red lines show the exponential fit in the range 1000-2000 GeV. The lower panels show the fractional difference, (data-fit)/fit

Distributions of the average reconstructed mass of VLQ candidates for the jet combination with the least $\chi^{2}$ in 4-jet (left), 5-jet (center), and 6-jet (right) multiplicity events. The red lines show the exponential fit in the range 1000-2000 GeV. The lower panels show the fractional difference, (data-fit)/fit

Distributions of the average reconstructed mass of VLQ candidates for the jet combination with the least $\chi^{2}$ in 4-jet (left), 5-jet (center), and 6-jet (right) multiplicity events. The red lines show the exponential fit in the range 1000-2000 GeV. The lower panels show the fractional difference, (data-fit)/fit

Dependence of the BJTF on the average reconstructed VLQ mass in the control region, 12 < $\chi^{2}$/ndf < 48 for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes. The data is shown in black points, and the linear fit and its uncertainty are shown as the red line and the pale red band.

Dependence of the BJTF on the average reconstructed VLQ mass in the control region, 12 < $\chi^{2}$/ndf < 48 for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes. The data is shown in black points, and the linear fit and its uncertainty are shown as the red line and the pale red band.

Dependence of the BJTF on the average reconstructed VLQ mass in the control region, 12 < $\chi^{2}$/ndf < 48 for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes. The data is shown in black points, and the linear fit and its uncertainty are shown as the red line and the pale red band.

Dependence of the BJTF on the average reconstructed VLQ mass in the control region, 12 < $\chi^{2}$/ndf < 48 for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes. The data is shown in black points, and the linear fit and its uncertainty are shown as the red line and the pale red band.

Dependence of the BJTF on the average reconstructed VLQ mass in the control region, 12 < $\chi^{2}$/ndf < 48 for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes. The data is shown in black points, and the linear fit and its uncertainty are shown as the red line and the pale red band.

Dependence of the BJTF on the average reconstructed VLQ mass in the control region, 12 < $\chi^{2}$/ndf < 48 for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes. The data is shown in black points, and the linear fit and its uncertainty are shown as the red line and the pale red band.

Dependence of the BJTF on the average reconstructed VLQ mass in the control region, 12 < $\chi^{2}$/ndf < 48 for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes. The data is shown in black points, and the linear fit and its uncertainty are shown as the red line and the pale red band.

Dependence of the BJTF on the average reconstructed VLQ mass in the control region, 12 < $\chi^{2}$/ndf < 48 for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes. The data is shown in black points, and the linear fit and its uncertainty are shown as the red line and the pale red band.

Dependence of the BJTF on the average reconstructed VLQ mass in the control region, 12 < $\chi^{2}$/ndf < 48 for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes. The data is shown in black points, and the linear fit and its uncertainty are shown as the red line and the pale red band.

Dependence of the BJTF on $\chi^{2}$/ndf in the low-mass VLQ region, for 4-jet (left column), 5-jet, (center column) and 6-jet (right column) multiplicities and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes. The data is shown in black points, and the linear fit and its uncertainty are shown as the red line and the pale red band.

Dependence of the BJTF on $\chi^{2}$/ndf in the low-mass VLQ region, for 4-jet (left column), 5-jet, (center column) and 6-jet (right column) multiplicities and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes. The data is shown in black points, and the linear fit and its uncertainty are shown as the red line and the pale red band.

Dependence of the BJTF on $\chi^{2}$/ndf in the low-mass VLQ region, for 4-jet (left column), 5-jet, (center column) and 6-jet (right column) multiplicities and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes. The data is shown in black points, and the linear fit and its uncertainty are shown as the red line and the pale red band.

Dependence of the BJTF on $\chi^{2}$/ndf in the low-mass VLQ region, for 4-jet (left column), 5-jet, (center column) and 6-jet (right column) multiplicities and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes. The data is shown in black points, and the linear fit and its uncertainty are shown as the red line and the pale red band.

Dependence of the BJTF on $\chi^{2}$/ndf in the low-mass VLQ region, for 4-jet (left column), 5-jet, (center column) and 6-jet (right column) multiplicities and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes. The data is shown in black points, and the linear fit and its uncertainty are shown as the red line and the pale red band.

Dependence of the BJTF on $\chi^{2}$/ndf in the low-mass VLQ region, for 4-jet (left column), 5-jet, (center column) and 6-jet (right column) multiplicities and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes. The data is shown in black points, and the linear fit and its uncertainty are shown as the red line and the pale red band.

Dependence of the BJTF on $\chi^{2}$/ndf in the low-mass VLQ region, for 4-jet (left column), 5-jet, (center column) and 6-jet (right column) multiplicities and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes. The data is shown in black points, and the linear fit and its uncertainty are shown as the red line and the pale red band.

Dependence of the BJTF on $\chi^{2}$/ndf in the low-mass VLQ region, for 4-jet (left column), 5-jet, (center column) and 6-jet (right column) multiplicities and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes. The data is shown in black points, and the linear fit and its uncertainty are shown as the red line and the pale red band.

Dependence of the BJTF on $\chi^{2}$/ndf in the low-mass VLQ region, for 4-jet (left column), 5-jet, (center column) and 6-jet (right column) multiplicities and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes. The data is shown in black points, and the linear fit and its uncertainty are shown as the red line and the pale red band.

The reduction factor in data events, for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities, and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes.

The reduction factor in data events, for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities, and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes.

The reduction factor in data events, for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities, and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes.

The reduction factor in data events, for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities, and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes.

The reduction factor in data events, for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities, and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes.

The reduction factor in data events, for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities, and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes.

The reduction factor in data events, for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities, and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes.

The reduction factor in data events, for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities, and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes.

The reduction factor in data events, for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities, and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes.

The reduction factor in $m_B$ = 1200 GeV VLQ signal events, for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities, and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes.

The reduction factor in $m_B$ = 1200 GeV VLQ signal events, for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities, and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes.

The reduction factor in $m_B$ = 1200 GeV VLQ signal events, for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities, and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes.

The reduction factor in $m_B$ = 1200 GeV VLQ signal events, for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities, and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes.

The reduction factor in $m_B$ = 1200 GeV VLQ signal events, for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities, and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes.

The reduction factor in $m_B$ = 1200 GeV VLQ signal events, for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities, and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes.

The reduction factor in $m_B$ = 1200 GeV VLQ signal events, for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities, and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes.

The reduction factor in $m_B$ = 1200 GeV VLQ signal events, for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities, and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes.

The reduction factor in $m_B$ = 1200 GeV VLQ signal events, for 4-jet (left column), 5-jet (center column), and 6-jet (right column) multiplicities, and for the bHbH (upper row), bHbZ (middle row), and bZbZ (lower row) event modes.

Data (black points), expected background (solid blue histogram), and expected background plus a VLQ signal for different VLQ masses (colored lines). Left column: 4-jet events, center column: 5-jet events, right column: 6-jet events; upper row: bHbH, middle row: bHbZ,lower row: bZbZ. For the signal, a 100% B -> bH branching fraction is assumed. The hatched regions for the background and background plus signal distributions indicate the systematic uncertainties. All three data-taking years are combined.

Data (black points), expected background (solid blue histogram), and expected background plus a VLQ signal for different VLQ masses (colored lines). Left column: 4-jet events, center column: 5-jet events, right column: 6-jet events; upper row: bHbH, middle row: bHbZ,lower row: bZbZ. For the signal, a 100% B -> bH branching fraction is assumed. The hatched regions for the background and background plus signal distributions indicate the systematic uncertainties. All three data-taking years are combined.

Data (black points), expected background (solid blue histogram), and expected background plus a VLQ signal for different VLQ masses (colored lines). Left column: 4-jet events, center column: 5-jet events, right column: 6-jet events; upper row: bHbH, middle row: bHbZ,lower row: bZbZ. For the signal, a 100% B -> bH branching fraction is assumed. The hatched regions for the background and background plus signal distributions indicate the systematic uncertainties. All three data-taking years are combined.

Data (black points), expected background (solid blue histogram), and expected background plus a VLQ signal for different VLQ masses (colored lines). Left column: 4-jet events, center column: 5-jet events, right column: 6-jet events; upper row: bHbH, middle row: bHbZ,lower row: bZbZ. For the signal, a 100% B -> bH branching fraction is assumed. The hatched regions for the background and background plus signal distributions indicate the systematic uncertainties. All three data-taking years are combined.

Data (black points), expected background (solid blue histogram), and expected background plus a VLQ signal for different VLQ masses (colored lines). Left column: 4-jet events, center column: 5-jet events, right column: 6-jet events; upper row: bHbH, middle row: bHbZ,lower row: bZbZ. For the signal, a 100% B -> bH branching fraction is assumed. The hatched regions for the background and background plus signal distributions indicate the systematic uncertainties. All three data-taking years are combined.

Data (black points), expected background (solid blue histogram), and expected background plus a VLQ signal for different VLQ masses (colored lines). Left column: 4-jet events, center column: 5-jet events, right column: 6-jet events; upper row: bHbH, middle row: bHbZ,lower row: bZbZ. For the signal, a 100% B -> bH branching fraction is assumed. The hatched regions for the background and background plus signal distributions indicate the systematic uncertainties. All three data-taking years are combined.

Data (black points), expected background (solid blue histogram), and expected background plus a VLQ signal for different VLQ masses (colored lines). Left column: 4-jet events, center column: 5-jet events, right column: 6-jet events; upper row: bHbH, middle row: bHbZ,lower row: bZbZ. For the signal, a 100% B -> bH branching fraction is assumed. The hatched regions for the background and background plus signal distributions indicate the systematic uncertainties. All three data-taking years are combined.

Data (black points), expected background (solid blue histogram), and expected background plus a VLQ signal for different VLQ masses (colored lines). Left column: 4-jet events, center column: 5-jet events, right column: 6-jet events; upper row: bHbH, middle row: bHbZ,lower row: bZbZ. For the signal, a 100% B -> bH branching fraction is assumed. The hatched regions for the background and background plus signal distributions indicate the systematic uncertainties. All three data-taking years are combined.

Data (black points), expected background (solid blue histogram), and expected background plus a VLQ signal for different VLQ masses (colored lines). Left column: 4-jet events, center column: 5-jet events, right column: 6-jet events; upper row: bHbH, middle row: bHbZ,lower row: bZbZ. For the signal, a 100% B -> bH branching fraction is assumed. The hatched regions for the background and background plus signal distributions indicate the systematic uncertainties. All three data-taking years are combined.

Expected limits on the VLQ mass at 95% CL as a function of the branching fractions $\mathcal{B}$( B -> bH ) and $\mathcal{B}$( B -> bZ)

Observed limits on the VLQ mass at 95% CL as a function of the branching fractions $\mathcal{B}$( B -> bH ) and $\mathcal{B}$( B -> bZ)

The 95% confidence limit on the cross section for VLQ pair production as a function of VLQ mass for three branching fraction hypotheses: B( B -> bH ) = 100% (upper left), B( B -> bZ ) = 100% (upper right), and and B( B -> bH ) = B( B -> bZ ) = 50% (lower). The solid black line indicates the observed limit and the dashed line indicates the expected limit with 1 sigma (green band) and 2 sigma (yellow band) uncertainties. The theoretical cross section and its uncertainty are shown as the red line and pale red band.

The 95% confidence limit on the cross section for VLQ pair production as a function of VLQ mass for three branching fraction hypotheses: B( B -> bH ) = 100% (upper left), B( B -> bZ ) = 100% (upper right), and and B( B -> bH ) = B( B -> bZ ) = 50% (lower). The solid black line indicates the observed limit and the dashed line indicates the expected limit with 1 sigma (green band) and 2 sigma (yellow band) uncertainties. The theoretical cross section and its uncertainty are shown as the red line and pale red band.

The 95% confidence limit on the cross section for VLQ pair production as a function of VLQ mass for three branching fraction hypotheses: B( B -> bH ) = 100% (upper left), B( B -> bZ ) = 100% (upper right), and and B( B -> bH ) = B( B -> bZ ) = 50% (lower). The solid black line indicates the observed limit and the dashed line indicates the expected limit with 1 sigma (green band) and 2 sigma (yellow band) uncertainties. The theoretical cross section and its uncertainty are shown as the red line and pale red band.

Cross section upper limit vs m(GLUINO) for SMS model T5ZZ.

Cross section upper limit vs m(GLUINO) for SMS model T5ZZ.

Cross section upper limit vs m(GLUINO) for SMS model T5ZZ.

Cross section vs m(GLUINO) for SMS model T5ZZ.

Cross section vs m(GLUINO) for SMS model T5ZZ.

Cross section vs m(GLUINO) for SMS model T5ZZ.

Number of events in the pTmiss CR, transfer factor, background prediction, and observed yield in each of the six pTmiss bins. The systematic uncertainties in the background prediction include the shape uncertainties in addition to the uncertainty in T. Also listed in the last column is the number of expected signal events and corresponding statistical uncertainties for one example mass point, m(GLUINO) = 1700 GeV. The last pTmiss bin includes overflows.

Pre-fit background covariance matrix $\sigma_{xy}$ for the 6 pTmiss bins.

Pre-fit background correlation matrix $\rho_{xy}$ for the 6 pTmiss bins.

Observed significance (in standard deviations) of the T5ZZ signal model as a function of the gluino mass.

Cut flow for the signal for two example mass points of the T5ZZ signal model. Here the hadronic baseline is defined by $N_{\mathrm{jets}}\ge 2$, $p_T^{\mathrm{miss}}$ > 300 GeV, $H_T$ > 300 GeV, $\Delta\phi$ cuts, and the isolated photon, lepton and track veto.

The rho distributions for the mixed-flavour category events corresponding to a signal hypothesis with mH = 261 GeV and mA = 150 GeV.

The rho distributions for the same-flavour category events corresponding to a signal hypothesis with mH = 442 GeV and mA = 193 GeV. The signal is normalised to its theoretical cross section.

The rho distributions for the mixed-flavour category events corresponding to a signal hypothesis with mH = 442 GeV and mA = 193 GeV.

Expected and observed 95% CL upper limits on the product of the production cross section and branching fraction for H(A) -> ZA(H) -> bbbar as a function of mA and mH. The limits are computed using the asymptotic CLs method, combining the ee and μμ channels.

Expected and observed 95% CL upper limits on the signal strength for the Type-II 2HDM benchmark (tan(beta)=1.5, cos(beta-alpha)=0.01) as a function of mA and mH . The limits are computed using the asymptotic CLs method, combining the ee and μμ channels.

Expected and observed 95% CL upper limits on the signal strength for the Type-II 2HDM benchmark (mH = 379 GeV and m A = 172 GeV) as a function of tan(beta) and cos(beta-alpha). The limits are computed using the asymptotic CLs method, combining the ee and μμ channels.

P-value for H(A) -> ZA(H) -> bbbar production as a function of mA and mH. The limits are computed using the asymptotic CLs method, combining the ee and μμ channels.

Observed yields and pre-fit background predictions for Njets 8-9.

Observed yields and pre-fit background predictions for Njets >=10.

Observed yields and pre-fit background predictions for aggregated bins.

Pre-fit background covariance matrix $\sigma_{xy}$ for the 174 analysis bins.

Pre-fit background correlation matrix $\rho_{xy}$ for the 174 analysis bins.

Observed yields and post-fit background predictions for Njets 2-3.

Observed yields and post-fit background predictions for Njets 4-5.

Observed yields and post-fit background predictions for Njets 6-7.

Observed yields and post-fit background predictions for Njets 8-9.

Observed yields and post-fit background predictions for Njets >=10.

Simulated signal yields for representative gluino signal model light-LSP points in the aggregate search regions. The uncertainties shown are statistical.

Simulated signal yields for representative gluino signal model compressed points in the aggregate search regions. The uncertainties shown are statistical.

Simulated signal yields for representative squark signal model light-LSP points in the aggregate search regions. The uncertainties shown are statistical.

Simulated signal yields for representative squark signal model compressed points in the aggregate search regions. The uncertainties shown are statistical.

The 95% CL observed and expected upper limits on the production cross sections of the T1tttt signal model as a function of the gluino and LSP masses.

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

The 95% CL observed and expected upper limits on the production cross sections of the T1bbbb signal model as a function of the gluino and LSP masses.

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

The 95% CL observed and expected upper limits on the production cross sections of the T1qqqq signal model as a function of the gluino and LSP masses.

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

The 95% CL observed and expected upper limits on the production cross sections of the T5qqqqVV signal model as a function of the gluino and LSP masses.

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

The 95% CL observed and expected upper limits on the production cross sections of the T2tt signal model as a function of the top squark and LSP masses.

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

The 95% CL observed and expected upper limits on the production cross sections of the T2bb signal model as a function of the bottom squark and LSP masses.

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

Exclusion limits assuming the approximate-NNLO+NNLL cross sections

The 95% CL observed and expected upper limits on the production cross sections of the T2qq signal model as a function of the LSP and light squark masses.

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (u d s c)

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (u d s c)

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (u d s c)

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (u d s c)

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (u d s c)

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (u d s c)

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (u d s c)

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (single flavor)

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (single flavor)

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (single flavor)

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (single flavor)

Exclusion limits assuming the approximate-NNLO+NNLL cross sections (single flavor)

The observed significance of the SMS models for T1tttt as function of the gluino and LSP masses.

The observed significance of the SMS models for T1bbbb as function of the gluino and LSP masses.

The observed significance of the SMS models for T1qqqq as function of the gluino and LSP masses.

The observed significance of the SMS models for T5qqqqVV as function of the gluino and LSP masses.

The observed significance of the SMS models for T2tt as function of the top squark and LSP masses.

The observed significance of the SMS models for T2bb as function of the bottom squark and LSP masses.

The observed significance of the SMS models for T2qq as function of the LSP and light squark masses.

The efficiency times acceptance of the SMS models for T1tttt as function of the gluino and LSP masses. The efficiency times acceptance is given for the total signal across the set of 174 search regions.

The efficiency times acceptance of the SMS models for T1bbbb as function of the gluino and LSP masses. The efficiency times acceptance is given for the total signal across the set of 174 search regions.

The efficiency times acceptance of the SMS models for T1qqqq as function of the gluino and LSP masses. The efficiency times acceptance is given for the total signal across the set of 174 search regions.

The efficiency times acceptance of the SMS models for T5qqqqVV as function of the gluino and LSP masses. The efficiency times acceptance is given for the total signal across the set of 174 search regions.

The efficiency times acceptance of the SMS models for T2tt as function of the top squark and LSP masses. The efficiency times acceptance is given for the total signal across the set of 174 search regions.

The efficiency times acceptance of the SMS models for T2bb as function of the bottom squark and LSP masses. The efficiency times acceptance is given for the total signal across the set of 174 search regions.

The efficiency times acceptance of the SMS models for T2qq as function of the LSP and light squark masses. The efficiency times acceptance is given for the total signal across the set of 174 search regions.

Absolute cumulative efficiencies in percent for each step of the event selection process, listed for four representative gluino pair production signal models with m(gluino) >> m(LSP). Only statistical uncertainties are shown.

Absolute cumulative efficiencies in percent for each step of the event selection process, listed for four representative gluino pair production signal models with m(gluino) ~ m(LSP). Only statistical uncertainties are shown.

Absolute cumulative efficiencies in percent for each step of the event selection process, listed for three representative squark pair production signal models with m(squark) >> m(LSP). Only statistical uncertainties are shown.

Absolute cumulative efficiencies in percent for each step of the event selection process, listed for three representative squark pair production signal models with m(squark) ~ m(LSP). Only statistical uncertainties are shown.

Expected and observed upper limits at 95% CL on $\mathcal{B}_{sig}=\mathcal{B}(\mathrm{t}\to\mathrm{b}\mathrm{H^{+}})\mathcal{B}(\mathrm{H^{+}}\to\mathrm{W^{+}}\mathrm{A})\mathcal{B}(\mathrm{A}\to\mu^{+}\mu^{-})$ for the A boson masses ($\mathit{m}_{\mathrm{A}}$). The $\mathrm{H^{+}}$ boson mass is assumed to be 160 GeV in the calculation.