Observed and expected 95% CL upper limits on the product of the production cross section ($\sigma$) and the branching fraction, obtained after combining all categories with 138 $\mathrm{fb}^{−1}$ of data at $\sqrt{s}$ = 13 TeV for $\mathrm{V'}$ to $VV$ + $VH$ signal in HVT model C.

Total signal efficiency including all event categories as a function of the resonance mass $M_X$ for all DY/ggF signal models under consideration. The estimates from MC simulation (markers) are interpolated with a functional form (lines).

Total signal efficiency including all event categories as a function of the resonance mass $M_X$ for all VBF signal models under consideration. The estimates from MC simulation (markers) are interpolated with a functional form (lines).

Comparison of the $m_{miss}$ shapes for the simulated signal events within the fiducial region and those outside it, after including the effect of PU protons as describe in the text, for a generated $m_{X}$ mass of 1000 GeV. The distributions are shown for single(+z)-single(−z) proton reconstruction categories.

Product of the acceptance times the combined reconstruction and identification efficiency, as a function of $m_{X}$ , for events generated inside the fiducial volume defined in Table 1. The curves shown panel display the different final states. The definition of the fiducial region and signal model used to estimate the acceptance is provided in the text.

Product of the acceptance times the combined reconstruction and identification efficiency, as a function of $m_{X}$ , for different proton reconstruction categories in the $Z \rightarrow \mu\mu $ analysis, and for events generated inside the fiducial volume defined in Table 1. The curves shown panel display the different final states. The definition of the fiducial region and signal model used to estimate the acceptance is provided in the text.

Distributions of the reconstructed proton $\xi$ in the negative arm from the proton mixing procedure with simulated MC events, are compared to data. The ee final states are shown.The ee events are displayed without the Z boson $p_T$ requirement.For illustration, the simulated signal distributions are superimposed for various choices of $m_{X}$ , normalised to a generated fiducial cross section of 100 pb.

Distributions of the reconstructed proton $\xi$ in the positive arm from the proton mixing procedure with simulated MC events, are compared to data. The ee final states are shown.The ee events are displayed without the Z boson $p_T$ requirement.For illustration, the simulated signal distributions are superimposed for various choices of $m_{X}$ , normalised to a generated fiducial cross section of 100 pb.

Distributions of the reconstructed di-proton rapidity from the proton mixing procedure with simulated MC events, are compared to data. The ee final states are shown.The ee events are displayed without the Z boson $p_T$ requirement.For illustration, the simulated signal distributions are superimposed for various choices of $m_{X}$ , normalised to a generated fiducial cross section of 100 pb.

Distributions of the reconstructed proton $\xi$ in the negative arm from the proton mixing procedure with simulated MC events, are compared to data. The $\mu\mu$ final states are shown.The $\mu\mu$ events are displayed without the Z boson $p_T$ requirement.For illustration, the simulated signal distributions are superimposed for various choices of $m_{X}$ , normalised to a generated fiducial cross section of 100 pb.

Distributions of the reconstructed proton $\xi$ in the positive arm from the proton mixing procedure with simulated MC events, are compared to data. The $\mu\mu$ final states are shown.The $\mu\mu$ events are displayed without the Z boson $p_T$ requirement.For illustration, the simulated signal distributions are superimposed for various choices of $m_{X}$ , normalised to a generated fiducial cross section of 100 pb.

Distributions of the reconstructed di-proton rapidity from the proton mixing procedure with simulated MC events, are compared to data. The $\mu\mu$ final states are shown.The $\mu\mu$ events are displayed without the Z boson $p_T$ requirement.For illustration, the simulated signal distributions are superimposed for various choices of $m_{X}$ , normalised to a generated fiducial cross section of 100 pb.

Distributions of the reconstructed proton $\xi$ in the negative arm from the proton mixing procedure with simulated MC events, are compared to data. The $\gamma$ final states are shown.For illustration, the simulated signal distributions are superimposed for various choices of $m_{X}$ , normalised to a generated fiducial cross section of 100 pb.

Distributions of the reconstructed proton $\xi$ in the positive arm from the proton mixing procedure with simulated MC events, are compared to data. The $\gamma$ final states are shown.For illustration, the simulated signal distributions are superimposed for various choices of $m_{X}$ , normalised to a generated fiducial cross section of 100 pb.

Distributions of the reconstructed di-proton rapidity from the proton mixing procedure with simulated MC events, are compared to data. The $\gamma$ final states are shown.For illustration, the simulated signal distributions are superimposed for various choices of $m_{X}$ , normalised to a generated fiducial cross section of 100 pb.

Validation of the background modelling method, using the $e\mu$ control sample. Selected $e\mu$ events are mixed with protons from $Z\rightarrow \mu \mu$ events with $p_{T}(Z)<10$ GeV to simulate the combinatorial background shape, while the data points are unaltered $e\mu$ events. The proton $\xi$ distribution for the positive CT-PPS arm is shown.

Validation of the background modelling method, using the $e\mu$ control sample. Selected $e\mu$ events are mixed with protons from $Z\rightarrow \mu \mu$ events with $p_{T}(Z)<10$ GeV to simulate the combinatorial background shape, while the data points are unaltered $e\mu$ events. The proton $\xi$ distribution for the negative CT-PPS arm is shown.

Validation of the background modelling method, using the $e\mu$ control sample. Selected $e\mu$ events are mixed with protons from $Z\rightarrow \mu \mu$ events with $p_{T}(Z)<10$ GeV to simulate the combinatorial background shape, while the data points are unaltered $e\mu$ events. The di-proton invariant mass is shown.

Validation of the background modelling method, using the $e\mu$ control sample. Selected $e\mu$ events are mixed with protons from $Z\rightarrow \mu \mu$ events with $p_{T}(Z)<10$ GeV to simulate the combinatorial background shape, while the data points are unaltered $e\mu$ events. The $m_{miss}$ is shown.

$m_{miss}$ distributions in the $pp\rightarrow ppZeeX$, with the protons reconstructed with the multi(+z)-multi(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 1 pb.

$m_{miss}$ distributions in the $pp\rightarrow ppZeeX$, with the protons reconstructed with the multi(+z)-single(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 1 pb.

$m_{miss}$ distributions in the $pp\rightarrow ppZeeX$, with the protons reconstructed with the single(+z)-multi(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 1 pb.

$m_{miss}$ distributions in the $pp\rightarrow ppZeeX$, with the protons reconstructed with the single(+z)-single(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 1 pb.

$m_{miss}$ distributions in the $pp\rightarrow ppZ\mu\mu X$, with the protons reconstructed with the multi(+z)-multi(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 1 pb.

$m_{miss}$ distributions in the $pp\rightarrow ppZ\mu\mu X$, with the protons reconstructed with the multi(+z)-single(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 1 pb.

$m_{miss}$ distributions in the $pp\rightarrow ppZ\mu\mu X$, with the protons reconstructed with the single(+z)-multi(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 1 pb.

$m_{miss}$ distributions in the $pp\rightarrow ppZ\mu\mu X$, with the protons reconstructed with the single(+z)-single(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 1 pb.

$m_{miss}$ distributions in the $pp\rightarrow pp\gamma X$, with the protons reconstructed with the multi(+z)-multi(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 10 pb.

$m_{miss}$ distributions in the $pp\rightarrow pp\gamma X$, with the protons reconstructed with the multi(+z)-single(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 10 pb.

$m_{miss}$ distributions in the $pp\rightarrow pp\gamma X$, with the protons reconstructed with the single(+z)-multi(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 10 pb.

$m_{miss}$ distributions in the $pp\rightarrow pp\gamma X$, with the protons reconstructed with the single(+z)-single(-z)method. The background distributions are shown after the fit. The expectations for a signal with $m_{X} = 1000$ GeV are superimposed, where the fiducial production cross section is normalised to 10 pb.

Upper limits on the $pp\rightarrow ppZ/\gamma X$ cross section at 95% CL, as a function of $m_X$. The 68 and 95% central intervals of the expected limits are represented by the green and yellow bands, respectively, while the observed limit is superimposed as a curve. The plot corresponds to the $Z\rightarrow ee$ analysis.

Upper limits on the $pp\rightarrow ppZ/\gamma X$ cross section at 95% CL, as a function of $m_X$. The 68 and 95% central intervals of the expected limits are represented by the green and yellow bands, respectively, while the observed limit is superimposed as a curve. The plot corresponds to the $Z\rightarrow \mu\mu$ analysis.

Upper limits on the $pp\rightarrow ppZ/\gamma X$ cross section at 95% CL, as a function of $m_X$. The 68 and 95% central intervals of the expected limits are represented by the green and yellow bands, respectively, while the observed limit is superimposed as a curve. The plot corresponds to the $Z$ analysis.

Upper limits on the $pp\rightarrow ppZ/\gamma X$ cross section at 95% CL, as a function of $m_X$. The 68 and 95% central intervals of the expected limits are represented by the green and yellow bands, respectively, while the observed limit is superimposed as a curve. The plot corresponds to the $\gamma$ analysis.

Measured ratio of $\mathcal{B}_{4\mu}/\mathcal{B}_{2\mu}$

Measured branching fraction $\mathcal{B}_{4\mu}$

Measured branching fraction $\mathcal{B}_{4\mu}$

Inclusive cross section predictions up to QCD NNLO accuracy using the NNPDF3.1 PDF set

Measured production cross sections ratio $\sigma(W^+ + \overline{c})$ / $\sigma(W^- + c)$

Predictions for the cross sections ratio $\sigma(W^+ + \overline{c})$ / $\sigma(W^- + c)$ at QCD NLO accuracy from MCFM using different PDF sets

Predictions for the cross sections ratio $\sigma(W^+ + \overline{c})$ / $\sigma(W^- + c)$ up to QCD NNLO accuracy using the NNPDF3.1 PDF set

Measured diferential cross sections $\sigma(W^- + c) + \sigma(W^+ + \overline{c})$ as a function of the absolute value of the pseudorapidity of the lepton from the W decay, unfolded to the particle level.

Measured diferential cross sections as a function of the transverse momentum of the lepton from the W decay, unfolded to the particle level.

Measured diferential cross sections $\sigma(W^- + c) + \sigma(W^+ + \overline{c})$ as a function of the absolute value of the pseudorapidity of the lepton from the W decay, unfolded to the parton level.

Measured diferential cross sections as a function of the transverse momentum of the lepton from the W decay, unfolded to the parton level.

Measured diferential cross sections ratio $R=\sigma(W^+ + \overline{c}) / \sigma(W^- + c)$ as a function of the absolute value of the pseudorapidity of the lepton from the W decay.

Measured diferential cross sections ratio $R=\sigma(W^+ + \overline{c}) / \sigma(W^- + c)$ as a function of the transverse momentum of the lepton from the W decay.

Measured min-$d_{xy}$ distribution in the 2-match category, after requiring the $d_{xy}$ muon to pass the isolation requirement $I_{\mathrm{rel}}^{\mathrm{PF}} <0.25$ (i. e., the B and D bins of the ABCD plane). Overlaid with a red histogram is the background predicted from the region of the ABCD plane failing the same requirement (the A and C bins), as well as three signal benchmark hypotheses (as defined in the legends), assuming $\alpha_D = \alpha_{\mathrm{EM}}$ (the fine-structure constant). The red hatched bands correspond to the background prediction uncertainty. The last bin includes the overflow.

Two-dimensional exclusion surfaces for $\Delta = 0.1 \, m_1$ as a function of the DM mass $m_1$ and the signal strength $y$, with $m_{A'} = 3 \, m_1$. Filled histograms denote observed limits on $\sigma(\mathrm{pp} \to A' \to \chi_2 \chi_1) \, \mathcal{B}(\chi_2 \to \chi_1 \mu^+ \mu^-)$. Solid (dashed) curves denote the observed (expected) exclusion limits at 95% CL, with 68% CL uncertainty bands around the expectation. Regions above the curves are excluded, depending on the $\alpha_D$ hypothesis: $\alpha_{\mathrm{D}} = \alpha_{\mathrm{EM}}$ (dark blue) or 0.1 (light magenta).

Two-dimensional exclusion surfaces for $\Delta = 0.4 \, m_1$ as a function of the DM mass $m_1$ and the signal strength $y$, with $m_{A'} = 3 \, m_1$. Filled histograms denote observed limits on $\sigma(\mathrm{pp} \to A' \to \chi_2 \chi_1) \, \mathcal{B}(\chi_2 \to \chi_1 \mu^+ \mu^-)$. Solid (dashed) curves denote the observed (expected) exclusion limits at 95% CL, with 68% CL uncertainty bands around the expectation. Regions above the curves are excluded, depending on the $\alpha_D$ hypothesis: $\alpha_{\mathrm{D}} = \alpha_{\mathrm{EM}}$ (dark blue) or 0.1 (light magenta).

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.

Observed event yields and estimated backgrounds in the low- and high-mass control regions. The uncertainty in the background yield is the sum in quadrature of the statistical and systematic uncertainties.

Summary of the relative systematic uncertainties in heavy Majorana neutrino signal yields and the background from prompt same-sign leptons, both estimated from simulation. The relative systematic uncertainties assigned to the data-driven backgrounds for the misidentified lepton background and mismeasured charge background are also shown. The uncertainties are given for the low-mass selections.

Summary of the relative systematic uncertainties in heavy Majorana neutrino signal yields and the background from prompt same-sign leptons, both estimated from simulation. The relative systematic uncertainties assigned to the data-driven backgrounds for the misidentified lepton background and mismeasured charge background are also shown. The uncertainties are given for the high-mass selections.

Summary of contributions to the systematic uncertainty related to the prompt same-sign leptons background, misidentified lepton background, and mismeasured charge background on the total background uncertainty for the case of $m_{\rm N}$ = 100 and 500 GeV.

Observed event yields and estimated backgrounds after the application of all selection, except for the final optimization. The background predictions from prompt same-sign leptons (Prompt bkgd.), misidentified leptons (Misid. bkgd.), mismeasured charge (Charge mismeas. bkgd.) and the total background (Total bkgd.) are shown together withthe number of events observed in data. The uncertainties shown are the statistical and systematic components, respectively.

Dielectron channel results after final optimization. The background predictions from prompt same-sign leptons, misidentified leptons, and mismeasured charge are shown along with the total background estimate and the number of events observed in data. The uncertainties shown are the statistical and systematic components, respectively.

Electron-muon channel results after final optimization. The background predictions from prompt same-sign leptons and misidentified leptons are shown along with the total background estimate and the number of events observed in data. The uncertainties shown are the statistical and systematic components, respectively.

Distribution of the three leading leptons flavour in the SR-WZ with uncertainties evaluated after the inclusive cross section fit

Efficiency, acceptance, and proportion of events with leptonic tau decays in WZ production

WZ fiducial cross section in the four flavour exclusive and the flavour inclusive channels

WZ total cross section extrapolated from the four flavour exclusive and the flavour inclusive channels

Distribution of the total lepton charge in the SR-WZ with uncertainties evaluated after the inclusive cross section fit

W$^{+}$Z fiducial cross section in the four flavour exclusive and the flavour inclusive channels

W$^{-}$Z fiducial cross section in the four flavour exclusive and the flavour inclusive channels

WZ charge asymmetry ratio measured on each of the four flavour exclusive and the flavour inclusive channels

Distribution of the cosine of the W polarization angle times total lepton charge in the SR-WZ with uncertainties evaluated after the W polarization fit

Distribution of the cosine of the Z polarization angle in the SR-WZ with uncertainties evaluated after the Z polarization fit

Best fits to the W and Z polarization fractions

2D confidence regions at the 68, 95, and 99% CL in the $f_O^W$-$f_{L}^W-f_R^W$ plane

2D confidence regions at the 68, 95, and 99% CL in the $f_O^Z$-$f_{L}^Z-f_R^Z$ plane

Distribution of the invariant mass of the WZ system in the SR-WZ with uncertainties evaluated after the inclusive cross section fit

Best fit values and one dimensional confidence regions in several EFT coefficients obtained from the EFT fit considering both the SM interferences and purely BSM (order $\Lambda^{-2}$ and $\Lambda^{-4}$) terms

2D confidence regions at the 68, 95, and 99% CL in the $c_{www}$-$c_{w}$ plane

2D confidence regions at the 68, 95, and 99% CL in the $c_{w}$-$c_{b}$ plane

2D confidence regions at the 68, 95, and 99% CL in the $c_{www}$-$c_{w}$ plane

Best fit values and one dimensional confidence regions in several EFT coefficients obtained from the EFT fit considering only the SM-EFT interference (order $\Lambda^{-2}$) terms

Evolution of the best fit and expected and observed 95% CI for the $c_{w}$ parameter as a function of the cutoff scale

Evolution of the best fit and expected and observed 95% CI for the $c_{b}$ parameter as a function of the cutoff scale

Evolution of the best fit and expected and observed 95% CI for the $c_{www}$ parameter as a function of the cutoff scale

Evolution of the best fit and expected and observed 95% CI for the $\tilde{c}_{www}$ parameter as a function of the cutoff scale

Evolution of the best fit and expected and observed 95% CI for the $\tilde{c}_{w}$ parameter as a function of the cutoff scale

Differential cross section with respect to the transverse momentum of the Z boson

Correlation matrix for the unfolded results obtained using NNLO bias, area con-straint, and no additional regularization for the $p_{T}$ of the Z boson

Response matrix for the $p_{T}$ of the Z boson obtained with POWHEG

Differential cross section with respect to the transverse momentum of the leading jet

Correlation matrix for the unfolded results obtained using NNLO bias, area con-straint, and no additional regularization for the $p_{T}$ of the leading jet

Response matrix for the $p_{T}$ of the leading jet obtained with POWHEG

Differential cross section with respect to the jet multiplicity

Correlation matrix for the unfolded results obtained using NNLO bias, area con-straint, and no additional regularization for the jet multiplicity

Response matrix for the jet multiplicity obtained with POWHEG

Differential cross section with respect to the invariant mass of the WZ system

Correlation matrix for the unfolded results obtained using NNLO bias, area con-straint, and no additional regularization for the invariant mass of the WZ system

Response matrix for the invariant mass of the WZ system obtained with POWHEG

Differential cross section with respect to the transverse momentum of the lepton associated to the W boson

Correlation matrix for the unfolded results obtained using NNLO bias, area con-straint, and no additional regularization for the $p_{T}$ of the lepton associated to the W boson

Response matrix for the $p_{T}$ of the lepton associated to the W boson obtained with POWHEG

Differential cross section with respect to the transverse momentum of the lepton associated to the W boson, W$^{+}$Z only

Correlation matrix for the unfolded results obtained using NNLO bias, area con-straint, and no additional regularization for the $p_{T}$ of the lepton associated to the W boson, W$^{+}$Z only

Differential cross section with respect to the transverse momentum of the lepton associated to the W boson, W$^{-}$Z only

Correlation matrix for the unfolded results obtained using NNLO bias, area con-straint, and no additional regularization for the $p_{T}$ of the lepton associated to the W boson, W$^{-}$Z only

Differential cross section with respect to the cosine of the W polarization angle times total lepton charge

Correlation matrix for the unfolded results obtained using NNLO bias, area con-straint, and no additional regularization for the cosine of the W polarization angle times total lepton charge

Response matrix for the cosine of the W polarization angle times total lepton charge obtained with POWHEG

Differential cross section with respect to the cosine of the W polarization angle times total lepton charge, W$^{+}$Z only

Correlation matrix for the unfolded results obtained using NNLO bias, area con-straint, and no additional regularization for the cosine of the W polarization angle times total lepton charge, W$^{+}$Z only

Differential cross section with respect to the cosine of the W polarization angle times total lepton charge, W$^{-}$Z only

Correlation matrix for the unfolded results obtained using NNLO bias, area con-straint, and no additional regularization for the cosine of the W polarization angle times total lepton charge, W$^{-}$Z only

Differential cross section with respect to the cosine of the Z polarization angle

Correlation matrix for the unfolded results obtained using NNLO bias, area con-straint, and no additional regularization for the cosine of the Z polarization angle

Response matrix for the cosine of the Z polarization angle obtained with POWHEG

Differential cross section with respect to the cosine of the Z polarization angle, W$^{+}$Z only

Correlation matrix for the unfolded results obtained using NNLO bias, area con-straint, and no additional regularization for the cosine of the Z polarization angle, W$^{+}$Z only

Differential cross section with respect to the cosine of the Z polarization angle, W$^{-}$Z only

Correlation matrix for the unfolded results obtained using NNLO bias, area con-straint, and no additional regularization for the cosine of the Z polarization angle, W$^{-}$Z only

Upper limits at 95% CL on $\sigma\times\mathcal{B}^2(\mathrm{H}_1\rightarrow b\bar{b})$ as a function of $m_{\mathrm{H_1}}$ for $m_{\mathrm{SUSY}}=1600\;\mathrm{GeV}$.

Upper limits at 95% CL on $\sigma\times\mathcal{B}^2(\mathrm{H}_1\rightarrow b\bar{b})$ as a function of $m_{\mathrm{H_1}}$ for $m_{\mathrm{SUSY}}=2000\;\mathrm{GeV}$.

Upper limits at 95% CL on $\sigma\times\mathcal{B}^2(\mathrm{H}_1\rightarrow b\bar{b})$ as a function of $m_{\mathrm{H_1}}$ for $m_{\mathrm{SUSY}}=2200\;\mathrm{GeV}$.

Upper limits at 95% CL on $\sigma\times\mathcal{B}^2(\mathrm{H}_1\rightarrow b\bar{b})$ as a function of $m_{\mathrm{H_1}}$ for $m_{\mathrm{SUSY}}=2400\;\mathrm{GeV}$.

Upper limits at 95% CL on $\sigma\times\mathcal{B}^2(\mathrm{H}_1\rightarrow b\bar{b})$ as a function of $m_{\mathrm{H_1}}$ for $m_{\mathrm{SUSY}}=2600\;\mathrm{GeV}$.

Upper limits at 95% CL on $\sigma\times\mathcal{B}^2(\mathrm{H}_1\rightarrow b\bar{b})$ as a function of $m_{\mathrm{H_1}}$ for $m_{\mathrm{SUSY}}=2800\;\mathrm{GeV}$.

Differential signal yields for various signal hypotheses.

Differential signal yields for various signal hypotheses.

Differential signal yields for various signal hypotheses.

Differential signal yields for various signal hypotheses.

Differential signal yields for various signal hypotheses.

Differential signal yields for various signal hypotheses.

Differential signal yields for various signal hypotheses.

Differential signal yields for various signal hypotheses.

Differential signal yields for various signal hypotheses.

Differential signal yields for various signal hypotheses.

Differential signal yields for various signal hypotheses.

Differential signal yields for various signal hypotheses.

Differential signal yields for various signal hypotheses.

Background and data yields in the control and signal region bins. The prediction before ("prefit") and after the background only fit ("b-only") are given separately.

Background and data yields in the control and signal region bins. The prediction before ("prefit") and after the background only fit ("b-only") are given separately.

Background and data yields in the control and signal region bins. The prediction before ("prefit") and after the background only fit ("b-only") are given separately.

Background and data yields in the control and signal region bins. The prediction before ("prefit") and after the background only fit ("b-only") are given separately.

Background and data yields in the control and signal region bins. The prediction before ("prefit") and after the background only fit ("b-only") are given separately.

Background and data yields in the control and signal region bins. The prediction before ("prefit") and after the background only fit ("b-only") are given separately.

Matrix of covariance coefficients between signal region bins. The coefficients are obtained from the background-only fit to the control regions, and serve as input to the simplified likelihood reinterpretation scheme.

Matrix of covariance coefficients between signal region bins. The coefficients are obtained from the background-only fit to the control regions, and serve as input to the simplified likelihood reinterpretation scheme.

Background prediction and observed data yields in the signal region bins. The background yields are obtained from the background-only fit to the corresponding control regions, and serve as input to the simplified likelihood reinterpretation scheme.

Background prediction and observed data yields in the signal region bins. The background yields are obtained from the background-only fit to the corresponding control regions, and serve as input to the simplified likelihood reinterpretation scheme.

Matrix of covariance coefficients between signal region bins. The coefficients are obtained from the background-only fit to the control regions, and serve as input to the simplified likelihood reinterpretation scheme.

Matrix of covariance coefficients between signal region bins. The coefficients are obtained from the background-only fit to the control regions, and serve as input to the simplified likelihood reinterpretation scheme.

Background prediction and observed data yields in the signal region bins. The background yields are obtained from the background-only fit to the corresponding control regions, and serve as input to the simplified likelihood reinterpretation scheme.

Background prediction and observed data yields in the signal region bins. The background yields are obtained from the background-only fit to the corresponding control regions, and serve as input to the simplified likelihood reinterpretation scheme.

Matrix of covariance coefficients between signal region bins. The coefficients are obtained from the background-only fit to the control regions, and serve as input to the simplified likelihood reinterpretation scheme.

Matrix of covariance coefficients between signal region bins. The coefficients are obtained from the background-only fit to the control regions, and serve as input to the simplified likelihood reinterpretation scheme.

Background prediction and observed data yields in the signal region bins. The background yields are obtained from the background-only fit to the corresponding control regions, and serve as input to the simplified likelihood reinterpretation scheme.

Background prediction and observed data yields in the signal region bins. The background yields are obtained from the background-only fit to the corresponding control regions, and serve as input to the simplified likelihood reinterpretation scheme.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Unweighted signal acceptance times efficiency at every cut stage. The requirements called "HCAL mitigation" refer to the requirements imposed in the 2018 data set in order to mitigate the localized failure of the HCAL detector.

Median Expected exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with axial couplings.

Median Expected exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with axial couplings.

Observed exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with axial couplings.

Observed exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with axial couplings.

Expected plus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with axial couplings.

Expected plus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with axial couplings.

Expected minus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with axial couplings.

Expected minus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with axial couplings.

Median Expected exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with vector couplings.

Median Expected exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with vector couplings.

Observed exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with vector couplings.

Observed exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with vector couplings.

Expected plus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with vector couplings.

Expected plus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with vector couplings.

Expected minus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with vector couplings.

Expected minus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the simplified model with vector couplings.

Upper limits on the coupling $g_{\chi}$ in the simplified model with a axial mediator.

Upper limits on the coupling $g_{\chi}$ in the simplified model with a axial mediator.

Upper limits on the coupling $g_{q}$ in the simplified model with a axial mediator.

Upper limits on the coupling $g_{q}$ in the simplified model with a axial mediator.

Upper limits on the coupling $g_{\chi}$ in the simplified model with a vector mediator.

Upper limits on the coupling $g_{\chi}$ in the simplified model with a vector mediator.

Upper limits on the coupling $g_{q}$ in the simplified model with a vector mediator.

Upper limits on the coupling $g_{q}$ in the simplified model with a vector mediator.

Exclusion limits on the signal strength in the simplified model with scalar couplings.

Exclusion limits on the signal strength in the simplified model with scalar couplings.

Exclusion limits on the signal strength in the simplified model with pseudoscalar couplings.

Exclusion limits on the signal strength in the simplified model with pseudoscalar couplings.

Exclusion limits on the fundamental Planck scale $M_{D}$ as a function of the number of extra dimensions $d$.

Exclusion limits on the fundamental Planck scale $M_{D}$ as a function of the number of extra dimensions $d$.

Median Expected exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the fermion portal model.

Median Expected exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the fermion portal model.

Observed exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the fermion portal model.

Observed exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the fermion portal model.

Expected plus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the fermion portal model.

Expected plus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the fermion portal model.

Expected minus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the fermion portal model.

Expected minus 1 s.d. exclusion contour in the $m_{med}$-$m_{\chi}$ plane in the fermion portal model.

Tagging efficiency for AK8 jets. The efficiency includes the effect of the machine-learning based DeepAK8 tagger, as well as the application of the mass window requirement on the jet. The efficiency is split depending on the matching generator-level object. For reinterpretation purposes, this efficiency can directly be applied to any AK8 jet that is matched to a given type of generator-level object, with no prior selection on the jet mass. Other acceptance requirements on jet $\p_{T}$ and $\eta$ should still be applied.

Tagging efficiency for AK8 jets. The efficiency includes the effect of the machine-learning based DeepAK8 tagger, as well as the application of the mass window requirement on the jet. The efficiency is split depending on the matching generator-level object. For reinterpretation purposes, this efficiency can directly be applied to any AK8 jet that is matched to a given type of generator-level object, with no prior selection on the jet mass. Other acceptance requirements on jet $\p_{T}$ and $\eta$ should still be applied.