The background estimate and the observed data in the number of tagged jets >= 2 bin, for each of the seven validation samples (VS$_{1}$ through VS$_{7}$), along with the signal sample (Sig S). Signal model distributions for scalar masses of 15 and 55 GeV with a proper mean decay length of 20 mm are also shown. The Higgs boson branching fraction to long-lived scalars (B(H$\rightarrow $ SS)) is set to 20%.

Exclusion limits at 95% CL on the Higgs boson branching fraction to long-lived scalars B(H$\rightarrow$ SS) as a function of the mean proper decay length of the scalar for scalar mass 15 GeV and the S$\rightarrow d\bar{d}$ decay mode.

Exclusion limits at 95% CL on the Higgs boson branching fraction to long-lived scalars B(H$\rightarrow$ SS) as a function of the mean proper decay length of the scalar for scalar mass 40 GeV and the S$\rightarrow d\bar{d}$ decay mode.

Exclusion limits at 95% CL on the Higgs boson branching fraction to long-lived scalars B(H$\rightarrow$ SS) as a function of the mean proper decay length of the scalar for scalar mass 55 GeV and the S$\rightarrow d\bar{d}$ decay mode.

Exclusion limits at 95% CL on the Higgs boson branching fraction to long-lived scalars B(H$\rightarrow$ SS) as a function of the mean proper decay length of the scalar for scalar mass 15 GeV and the S$\rightarrow b\bar{b}$ decay mode.

Exclusion limits at 95% CL on the Higgs boson branching fraction to long-lived scalars B(H$\rightarrow$ SS) as a function of the mean proper decay length of the scalar for scalar mass 40 GeV and the S$\rightarrow b\bar{b}$ decay mode.

Exclusion limits at 95% CL on the Higgs boson branching fraction to long-lived scalars B(H$\rightarrow$ SS) as a function of the mean proper decay length of the scalar for scalar mass 55 GeV and the S$\rightarrow b\bar{b}$ 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 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 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 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 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 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 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 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 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 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 55 GeV mass and $ S \rightarrow b\bar{b}$ decay mode.

The cluster efficiency in bins of hadronic and EM energy in region A. Region A is defined as 391 cm $< r <$ 695.5 cm and 400 cm $< |z| <$ 671 cm. The cluster efficiency is estimated with LLPs decaying to $\tau^{+} \tau^{-}$. The sample contains equal fractions of events with LLP mass of 7, 15, 40, and 55 GeV and LLP lifetime of 0.1, 1, 10, and 100m. The first hadronic energy bins correspond to LLPs that decayed leptonically with 0 hadronic energy. The cluster efficiency includes all cluster-level selections described in the paper, except for the jet veto, time cut, and $\Delta\phi$ cut. The full simulation signal yield prediction for samples with various LLP mass between 7 - 55 GeV, lifetime between 0.1 - 100 m, and decay mode to $d\bar{d}$ and $\tau^{+} \tau^{-}$ can be reproduced using this parameterization to within 35% and 20% for region A and B, respectively.

The cluster efficiency in bins of hadronic and EM energy in region A. Region A is defined as 391 cm $< r <$ 695.5 cm and 400 cm $< |z| <$ 671 cm. The cluster efficiency is estimated with LLPs decaying to $\tau^{+} \tau^{-}$. The sample contains equal fractions of events with LLP mass of 7, 15, 40, and 55 GeV and LLP lifetime of 0.1, 1, 10, and 100m. The first hadronic energy bins correspond to LLPs that decayed leptonically with 0 hadronic energy. The cluster efficiency includes all cluster-level selections described in the paper, except for the jet veto, time cut, and $\Delta\phi$ cut. The full simulation signal yield prediction for samples with various LLP mass between 7 - 55 GeV, lifetime between 0.1 - 100 m, and decay mode to $d\bar{d}$ and $\tau^{+} \tau^{-}$ can be reproduced using this parameterization to within 35% and 20% for region A and B, respectively.

The cluster efficiency in bins of hadronic and EM energy in region B. Region B is defined as 671 cm $< |z| <$ 1100 cm, $r <$ 695.5 cm, and $|\eta| <$ 2. The cluster efficiency is estimated with LLPs decaying to $\tau^{+} \tau^{-}$. The sample contains equal fractions of events with LLP mass of 7, 15, 40, and 55 GeV and LLP lifetime of 0.1, 1, 10, and 100m. The first hadronic energy bins correspond to LLPs that decayed leptonically with 0 hadronic energy. The cluster efficiency includes all cluster-level selections described in the paper, except for the jet veto, time cut, and $\Delta\phi$ cut. The full simulation signal yield prediction for samples with various LLP mass between 7 - 55 GeV, lifetime between 0.1 - 100 m, and decay mode to $d\bar{d}$ and $\tau^{+} \tau^{-}$ can be reproduced using this parameterization to within 35% and 20% for region A and B, respectively.

The cluster efficiency in bins of hadronic and EM energy in region B. Region B is defined as 671 cm $< |z| <$ 1100 cm, $r <$ 695.5 cm, and $|\eta| <$ 2. The cluster efficiency is estimated with LLPs decaying to $\tau^{+} \tau^{-}$. The sample contains equal fractions of events with LLP mass of 7, 15, 40, and 55 GeV and LLP lifetime of 0.1, 1, 10, and 100m. The first hadronic energy bins correspond to LLPs that decayed leptonically with 0 hadronic energy. The cluster efficiency includes all cluster-level selections described in the paper, except for the jet veto, time cut, and $\Delta\phi$ cut. The full simulation signal yield prediction for samples with various LLP mass between 7 - 55 GeV, lifetime between 0.1 - 100 m, and decay mode to $d\bar{d}$ and $\tau^{+} \tau^{-}$ can be reproduced using this parameterization to within 35% and 20% for region A and B, respectively.

The efficiency of $N_{station} > 1$ requirement in bins of hadronic energy in region B. Region B is defined as 671 cm $< |z| <$ 1100 cm, $r <$ 695.5 cm, and $|\eta| <$ 2. The cluster efficiency is estimated with LLPs decaying to $\tau^{+} \tau^{-}$. The sample contains equal fractions of events with LLP mass of 7, 15, 40, and 55 GeV and LLP lifetime of 0.1, 1, 10, and 100m. The first hadronic energy bin corresponds to LLPs that decayed leptonically with 0 hadronic energy. The efficiency is calculated with respect to clusters that pass all cluster-level cuts described in the paper, except for the jet veto, time cut, and $\Delta\phi$ cut. The full simulation signal yield prediction for samples with various LLP mass between 7 - 55 GeV, lifetime between 0.1 - 100 m, and decay mode to $d\bar{d}$ and $\tau^{+} \tau^{-}$ can be reproduced using this parameterization to within 10%.

The efficiency of $N_{station} > 1$ requirement in bins of hadronic energy in region B. Region B is defined as 671 cm $< |z| <$ 1100 cm, $r <$ 695.5 cm, and $|\eta| <$ 2. The cluster efficiency is estimated with LLPs decaying to $\tau^{+} \tau^{-}$. The sample contains equal fractions of events with LLP mass of 7, 15, 40, and 55 GeV and LLP lifetime of 0.1, 1, 10, and 100m. The first hadronic energy bin corresponds to LLPs that decayed leptonically with 0 hadronic energy. The efficiency is calculated with respect to clusters that pass all cluster-level cuts described in the paper, except for the jet veto, time cut, and $\Delta\phi$ cut. The full simulation signal yield prediction for samples with various LLP mass between 7 - 55 GeV, lifetime between 0.1 - 100 m, and decay mode to $d\bar{d}$ and $\tau^{+} \tau^{-}$ can be reproduced using this parameterization to within 10%.

The geometric signal acceptance as a function of $c\tau$. The acceptance is shown for four different LLP mass hypotheses: 7, 15, 40, and 55 GeV. The acceptance is defined by requiring at least 1 LLP to decay in the region defined as 400 cm $< |z| <$ 1100 cm, $r < $ 695.5 cm, and $|\eta| <$ 2.4.

The distributions of the transfer factor ($\alpha$) versus $m_T$ in the HP VBF category is shown. The last bin corresponds to the value obtained by integrating events above the penultimate bin.

The distributions of the transfer factor ($\alpha$) versus $m_T$ in the HP ggF/DY category is shown. The last bin corresponds to the value obtained by integrating events above the penultimate bin.

The distributions of the transfer factor ($\alpha$) versus $m_T$ in the LP VBF category is shown. The last bin corresponds to the value obtained by integrating events above the penultimate bin.

The distributions of the transfer factor ($\alpha$) versus $m_T$ in the LP ggF/DY category is shown. The last bin corresponds to the value obtained by integrating events above the penultimate bin.

Distributions of mT for high-purity ggF/DY CR events after performing background-only fits. The last bin corresponds to the yields integrated above the penultimate bin. Both the ggF and VBF-produced 1 TeV graviton signals (normalized to 10 fb) are shown in the plot. Nonresonant background corresponds to the Z+jets and W+jets events. Resonant background corresponds to the ttbar, single top, and di/tri-boson events.

Distributions of mT for high-purity VBF CR events after performing background-only fits. The last bin corresponds to the yields integrated above the penultimate bin. Both the ggF and VBF-produced 1 TeV graviton signals (normalized to 10 fb) are shown in the plot. Nonresonant background corresponds to the Z+jets and W+jets events. Resonant background corresponds to the ttbar, single top, and di/tri-boson events.

Distributions of mT for low-purity ggF/DY CR events after performing background-only fits. The last bin corresponds to the yields integrated above the penultimate bin. Both the ggF and VBF-produced 1 TeV graviton signals (normalized to 10 fb) are shown in the plot. Nonresonant background corresponds to the Z+jets and W+jets events. Resonant background corresponds to the ttbar, single top, and di/tri-boson events.

Distributions of mT for low-purity VBF CR events after performing background-only fits. The last bin corresponds to the yields integrated above the penultimate bin. Both the ggF and VBF-produced 1 TeV graviton signals (normalized to 10 fb) are shown in the plot. Nonresonant background corresponds to the Z+jets and W+jets events. Resonant background corresponds to the ttbar, single top, and di/tri-boson events.

Distributions of mT for high-purity ggF/DY SR events after performing background-only fits. The last bin corresponds to the yields integrated above the penultimate bin. Both the ggF and VBF-produced 1 TeV graviton signals (normalized to 10 fb) are shown in the plot. Nonresonant background corresponds to the Z+jets and W+jets events. Resonant background corresponds to the ttbar, single top, and di/tri-boson events.

Distributions of mT for high-purity VBF SR events after performing background-only fits. The last bin corresponds to the yields integrated above the penultimate bin. Both the ggF and VBF-produced 1 TeV graviton signals (normalized to 10 fb) are shown in the plot. Nonresonant background corresponds to the Z+jets and W+jets events. Resonant background corresponds to the ttbar, single top, and di/tri-boson events.

Distributions of mT for low-purity ggF/DY SR events after performing background-only fits. The last bin corresponds to the yields integrated above the penultimate bin. Both the ggF and VBF-produced 1 TeV graviton signals (normalized to 10 fb) are shown in the plot. Nonresonant background corresponds to the Z+jets and W+jets events. Resonant background corresponds to the ttbar, single top, and di/tri-boson events.

Distributions of mT for low-purity VBF SR events after performing background-only fits. The last bin corresponds to the yields integrated above the penultimate bin. Both the ggF and VBF-produced 1 TeV graviton signals (normalized to 10 fb) are shown in the plot. Nonresonant background corresponds to the Z+jets and W+jets events. Resonant background corresponds to the ttbar, single top, and di/tri-boson events.

Expected and observed 95% CL upper limits on the product of the radion (R) production (gluon-gluon fusion) cross section and the R -> ZZ branching fraction versus the radion mass.

Expected and observed 95% CL upper limits on the product of the radion (R) production (vector boson fusion) cross section and the R -> ZZ branching fraction versus the radion mass.

Expected and observed 95% CL upper limits on the product of the W' (W') production (Drell-Yan) cross section and the W' -> WZ branching fraction versus the W' mass.

Expected and observed 95% CL upper limits on the product of the W' (W') production (vector boson fusion) cross section and the W' -> WZ branching fraction versus the W' mass.

Expected and observed 95% CL upper limits on the product of the graviton (G) production (gluon-gluon fusion) cross section and the G -> ZZ branching fraction versus the graviton mass.

Expected and observed 95% CL upper limits on the product of the graviton (G) production (vector boson fusion) cross section and the G -> ZZ branching fraction versus the graviton mass.

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

Theory cross sections vs m($\widetilde{\chi}^0_1$) for SMS model TChiHH-G, $\widetilde{\chi}^0_1, \widetilde{\chi}^0_2$ NLSPs only.

The 95% CL observed and expected upper limits on the production cross sections of the TChiHH signal model as a function of the $\widetilde{\chi}^0_2$ and $\widetilde{\chi}^0_1$ masses. Relative to Fig. 13, the binning of the table is adjusted to align with the model points that were sampled. In addition, a small correction has been applied that affects the cross section upper limits for points with $m(\widetilde{\chi}^0_1) = 1$ GeV. For that row of points in the figure, the small region of model phase space reached by both the resolved and boosted selections was inadvertently double counted in computing the signal contribution to the predicted yield.

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

Cross section, 95% CL upper limit plus theory vs m($\widetilde{g}$) for SMS model T5HH.

Pre-fit background covariance matrix $\sigma_{xy}$ for the 22 analysis bins, ordered as in Fig. 10.

Pre-fit background correlation matrix $\rho_{xy}$ for the 22 analysis bins, ordered as in Fig. 10.

Significance vs $(m(\widetilde{\chi}^0_2), m(\widetilde{\chi}^0_1))$ for SMS model TChiHH.

Significance vs $m(\widetilde{g})$ for SMS model T5HH.

Likelihood profile at $(m(\widetilde{\chi}^0_2) = $275, $m(\widetilde{\chi}^0_1) = $1) for SMS model TChiHH.

Likelihood profile at $(m(\widetilde{\chi}^0_2) = $300, $m(\widetilde{\chi}^0_1) = $1) for SMS model TChiHH.

Likelihood profile at $(m(\widetilde{\chi}^0_2) = $300, $m(\widetilde{\chi}^0_1) = $50) for SMS model TChiHH.

Likelihood profile at $(m(\widetilde{\chi}^0_2) = $450, $m(\widetilde{\chi}^0_1) = $1) for SMS model TChiHH.

Likelihood profile at $(m(\widetilde{\chi}^0_2) = $750, $m(\widetilde{\chi}^0_1) = $1) for SMS model TChiHH.

Likelihood profile at $(m(\widetilde{\chi}^0_2) = $750, $m(\widetilde{\chi}^0_1) = $200) for SMS model TChiHH.

Efficiency vs $m(\widetilde{\chi}^0_1)$ for SMS model TChiHH-G. The denominator includes all 22 signal regions, and assumes $\mathcal{B}(\mathrm{H}$-->$\mathrm{b}\overline{\mathrm{b}})=100\%$.

Efficiency vs $m(\widetilde{g})$ for SMS model T5HH. The denominator includes all 22 signal regions, and no constraint on $\mathcal{B}(\mathrm{H}$-->$\mathrm{b}\overline{\mathrm{b}})$.

Efficiency vs $(m(\widetilde{\chi}^0_2), m(\widetilde{\chi}^0_1))$ for SMS model TChiHH. The denominator includes all 22 signal regions, and assumes $\mathcal{B}(\mathrm{H}$-->$\mathrm{b}\overline{\mathrm{b}})=100\%$.

Signal and control region populations for the resolved signature.

Signal and control region populations for the boosted signature.

Cut flow table for the resolved topology showing expected event yields at 137 fb$^{-1}$ for selected signal models as successive selections are applied.

Cut flow table for the boosted topology showing expected event yields at 137 fb$^{-1}$ for selected signal model points as successive selections are applied. Here the hadronic baseline is defined by $N_{\mathrm{jet}}\geq$2, \ptmiss$>$300 GeV, $\Delta\phi$ cuts, and the isolated lepton and track vetoes.

Correlation between the Wilson coefficients (in %), after the 5D fit to data.

SR1 diboson invariant mass distribution in the resolved tagged category after fitting the signal and sideband regions using a signal (ALP linear ZZ) plus background model. The last bin includes events with diboson invariant masses up to 3000 GeV. The signal is normalized to the 95% CL cross section limit at $f_a$ = 3 TeV (the scale factor used in the original figure for better visibility is not applied here).

SR2 diboson invariant mass distribution in the boosted untagged category after fitting the signal and sideband regions using a signal (ALP chiral ZH) plus background model. The last bin includes events with diboson invariant masses up to 3000 GeV. The signal is normalized to the 95% CL cross section limit at $f_a$ = 3 TeV (the scale factor used in the original figure for better visibility is not applied here).

SR2 diboson invariant mass distribution in the boosted tagged category after fitting the signal and sideband regions using a signal (ALP chiral ZH) plus background model. The last bin includes events with diboson invariant masses up to 3000 GeV. The signal is normalized to the 95% CL cross section limit at $f_a$ = 3 TeV.

SR2 diboson invariant mass distribution in the resolved untagged category after fitting the signal and sideband regions using a signal (ALP chiral ZH) plus background model. The last bin includes events with diboson invariant masses up to 3000 GeV. The signal is normalized to the 95% CL cross section limit at $f_a$ = 3 TeV (the scale factor used in the original figure for better visibility is not applied here).

SR2 diboson invariant mass distribution in the resolved tagged category after fitting the signal and sideband regions using a signal (ALP chiral ZH) plus background model. The last bin includes events with diboson invariant masses up to 3000 GeV. The signal is normalized to the 95% CL cross section limit at $f_a$ = 3 TeV (the scale factor used in the original figure for better visibility is not applied here).

Observed and expected 95% CL upper limit on $\sigma \mathcal{B}$(G -> ZZ) as a function of the resonance mass, taking into account all statistical and systematic uncertainties. The electron and muon channels and the various categories used in the analysis are combined. The inner green band and the outer yellow band represent the 68 and 95% coverage of the expected limits in the background-only hypothesis.

Observed and expected 95% CL upper limit on $\sigma \mathcal{B}$(W' -> ZW) as a function of the resonance mass, taking into account all statistical and systematic uncertainties. The electron and muon channels and the various categories used in the analysis are combined. The inner green band and the outer yellow band represent the 68 and 95% coverage of the expected limits in the background-only hypothesis.

Observed and expected 95% CL upper limit on the product of the ALP coupling to gluons and the coupling to Z bosons as a function of the mass scale $f_a$ for ALP masses smaller than 100 GeV.

Observed and expected 95% CL upper limit on the product of the ALP coupling to gluons and the chiral $a_\widetilde{2D}$ coupling as a function of the mass scale $f_a$ for ALP masses smaller than 100 GeV.

The observed and expected (in parentheses) 95% CL lower mass limits on RPV SUSY, Z′ ($\mathcal{B}=0.1$) , and QBH signals for the e$\mu$, e$\tau$, and $\mu\tau$ channels.

Expected and observed 95% CL upper limits on the product of cross section times branching fraction as a function of the $ au$ sneutrino mass in an RPV SUSY model for the e$\mu$ channel. The shaded bands represent the one and two standard deviation (s.d.) uncertainties in the expected limits. The red and blue solid lines show the product of cross section times branching fraction as a function of the tau sneutrino mass for two different values of couplings.

Expected and observed 95% CL upper limits on the product of cross section times branching fraction as a function of the $ au$ sneutrino mass in an RPV SUSY model for the e$\tau$ channel. The shaded bands represent the one and two standard deviation (s.d.) uncertainties in the expected limits. The red and blue solid lines show the product of cross section times branching fraction as a function of the tau sneutrino mass for two different values of couplings.

Expected and observed 95% CL upper limits on the product of cross section times branching fraction as a function of the $ au$ sneutrino mass in an RPV SUSY model for the $\mu\tau$ channel. The shaded bands represent the one and two standard deviation (s.d.) uncertainties in the expected limits. The red and blue solid lines show the product of cross section times branching fraction as a function of the tau sneutrino mass for two different values of couplings.

Expected (black dashed line) and observed (black solid line) 95% CL upper limits on the product of cross section and branching fraction for a Z′ ($\mathcal{B}=0.1$) boson with LFV decays, in the e$\mu$ channel.The shaded bands represent the one and two standard deviation (s.d.) uncertainties in the expected limits. The red solid lines show the product of cross section times branching fraction as a function of the Z′ mass.

Expected (black dashed line) and observed (black solid line) 95% CL upper limits on the product of cross section and branching fraction for a Z′ ($\mathcal{B}=0.1$) boson with LFV decays, in the e$\tau$ channel.The shaded bands represent the one and two standard deviation (s.d.) uncertainties in the expected limits. The red solid lines show the product of cross section times branching fraction as a function of the Z′ mass.

Expected (black dashed line) and observed (black solid line) 95% CL upper limits on the product of cross section and branching fraction for a Z′ ($\mathcal{B}=0.1$) boson with LFV decays, in the $\mu\tau$ channel.The shaded bands represent the one and two standard deviation (s.d.) uncertainties in the expected limits. The red solid lines show the product of cross section times branching fraction as a function of the Z′ mass.

Expected (black dashed line) and observed (black solid line) 95% CL upper limits on the product of cross section and branching fraction for quantum black hole production in an ADD model with $n=4$ extra dimensions, in the e$\mu$ channel. The shaded bands represent the one and two standard deviation (s.d.) uncertainties in the expected limits. The red solid lines show the product of cross section times branching fraction as a function of the QBH threshold mass.

Expected (black dashed line) and observed (black solid line) 95% CL upper limits on the product of cross section and branching fraction for quantum black hole production in an ADD model with $n=4$ extra dimensions, in the e$\tau$ channel. The shaded bands represent the one and two standard deviation (s.d.) uncertainties in the expected limits. The red solid lines show the product of cross section times branching fraction as a function of the QBH threshold mass.

Expected (black dashed line) and observed (black solid line) 95% CL upper limits on the product of cross section and branching fraction for quantum black hole production in an ADD model with $n=4$ extra dimensions, in the $\mu\tau$ channel. The shaded bands represent the one and two standard deviation (s.d.) uncertainties in the expected limits. The red solid lines show the product of cross section times branching fraction as a function of the QBH threshold mass.

Upper limits at 95% CL on the RPV SUSY model in the plane of $\tau$ sneutrino mass and $\lambda'$ coupling, for four values of $\lambda$ couplings for the e$\mu$ channel. The regions to the left of and above the curves are excluded.

Upper limits at 95% CL on the RPV SUSY model in the plane of $\tau$ sneutrino mass and $\lambda'$ coupling, for four values of $\lambda$ couplings for the e$\tau$ channel. The regions to the left of and above the curves are excluded.

Upper limits at 95% CL on the RPV SUSY model in the plane of $\tau$ sneutrino mass and $\lambda'$ coupling, for four values of $\lambda$ couplings for the $\mu\tau$ channel. The regions to the left of and above the curves are excluded.

Model-independent upper limits at 95% CL on the product of cross section, branching fraction, and acceptance are shown. Observed (expected) limits are shown in black solid (dashed) lines for the e$\mu$ channel. The shaded bands represent the one and two standard deviation (s.d.) uncertainties in the expected limits.

Model-independent upper limits at 95% CL on the product of cross section, branching fraction, and acceptance are shown. Observed (expected) limits are shown in black solid (dashed) lines for the e$\tau$ channel. The shaded bands represent the one and two standard deviation (s.d.) uncertainties in the expected limits.

Model-independent upper limits at 95% CL on the product of cross section, branching fraction, and acceptance are shown. Observed (expected) limits are shown in black solid (dashed) lines for the $\mu\tau$ channel. The shaded bands represent the one and two standard deviation (s.d.) uncertainties in the expected limits.

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 "channel_year_binnumber", following the binning from Figure 2.

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 "channel_year_binnumber", following the binning from Figure 2.

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 "channel_year_binnumber", following the binning from Figure 2.

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 "channel_year_binnumber", following the binning used in Figure 2.

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 "channel_year_binnumber", following the binning used in Figure 2.

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 "channel_year_binnumber", following the binning used in Figure 2.

Distribution of $m_{T}(W)$ in the $N_{jet}\geq 3$ signal region.

Distribution of $M_{3}$ in the $N_{jet}\geq 3$ signal region.

Distribution of $M_{3}$ in the $N_{jet}\geq 3$ signal region.

Distribution of $m(l,\gamma)$ in the $N_{jet}\geq 3$ signal region.

Distribution of $m(l,\gamma)$ in the $N_{jet}\geq 3$ signal region.

Distribution of $\Delta R(l,\gamma)$ in the $N_{jet}\geq 3$ signal region.

Distribution of $\Delta R(l,\gamma)$ in the $N_{jet}\geq 3$ signal region.

Distribution of $\Delta R(j,\gamma)$ in the $N_{jet}\geq 3$ signal region.

Distribution of $\Delta R(j,\gamma)$ in the $N_{jet}\geq 3$ signal region.

Fit result of the multijet template obtained with loosely isolated leptons and the electroweak background to the measured $m_{T}(W)$ distribution with isolated leptons in the $N_{jet}=2$, $N_{b jet}=0$ selection for electrons.

Fit result of the multijet template obtained with loosely isolated leptons and the electroweak background to the measured $m_{T}(W)$ distribution with isolated leptons in the $N_{jet}=2$, $N_{b jet}=0$ selection for electrons.

Fit result of the multijet template obtained with loosely isolated leptons and the electroweak background to the measured $m_{T}(W)$ distribution with isolated leptons in the $N_{jet}=2$, $N_{b jet}=0$ selection for muons.

Fit result of the multijet template obtained with loosely isolated leptons and the electroweak background to the measured $m_{T}(W)$ distribution with isolated leptons in the $N_{jet}=2$, $N_{b jet}=0$ selection for muons.

Distribution of the invariant mass of the lepton and the photon ($m(l,\gamma)$) in the $N_{jet}\geq 3$, $N_{b jet}=0$ selection for the e channel.

Distribution of the invariant mass of the lepton and the photon ($m(l,\gamma)$) in the $N_{jet}\geq 3$, $N_{b jet}=0$ selection for the e channel.

Distribution of the invariant mass of the lepton and the photon ($m(l,\gamma)$) in the $N_{jet}\geq 3$, $N_{b jet}=0$ selection for the $\mu$ channel.

Distribution of the invariant mass of the lepton and the photon ($m(l,\gamma)$) in the $N_{jet}\geq 3$, $N_{b jet}=0$ selection for the $\mu$ channel.

Extracted scale factors for the contribution from misidentified electrons for the three data-taking periods, and the Z$\gamma$, W$\gamma$ simulations.

Extracted scale factors for the contribution from misidentified electrons for the three data-taking periods, and the Z$\gamma$, W$\gamma$ simulations.

Predicted and observed yields in the control regions in the $N_{jet}= 3$ and $\geq 4$ seletions using the post-fit values of the nuisance parameters.

Predicted and observed yields in the control regions in the $N_{jet}= 3$ and $\geq 4$ seletions using the post-fit values of the nuisance parameters.

Predicted and observed yields in the signal regions in the $N_{jet}= 3$ and $\geq 4$ seletions using the post-fit values of the nuisance parameters.

Predicted and observed yields in the signal regions in the $N_{jet}= 3$ and $\geq 4$ seletions using the post-fit values of the nuisance parameters.

The measured inclusive ttgamma cross section in the fiducial phase space compared to the prediction from simulation using Madgraph_aMC@NLO at a center-of-mass energy of 13 TeV.

The measured inclusive ttgamma cross section in the fiducial phase space compared to the prediction from simulation using Madgraph_aMC@NLO at a center-of-mass energy of 13 TeV.

Summary of the measured cross section ratios with respect to the NLO cross section prediction for signal regions binned in the electron channel, muon channel and the combined single lepton measurement.

Summary of the measured cross section ratios with respect to the NLO cross section prediction for signal regions binned in the electron channel, muon channel and the combined single lepton measurement.

The unfolded differential cross sections for $p_{T}(\gamma)$ and the comparison to simulations.

The unfolded differential cross sections for $p_{T}(\gamma)$ and the comparison to simulations.

The unfolded differential cross sections for $|\eta(\gamma)|$ and the comparison to simulations.

The unfolded differential cross sections for $|\eta(\gamma)|$ and the comparison to simulations.

The unfolded differential cross sections for $\Delta R(l,\gamma)$ and the comparison to simulations.

The unfolded differential cross sections for $\Delta R(l,\gamma)$ and the comparison to simulations.

The covariance matrix of systematic uncertainties for the unfolded differential measurement for $p_{T}(\gamma)$.

The covariance matrix of systematic uncertainties for the unfolded differential measurement for $p_{T}(\gamma)$.

The covariance matrix of systematic uncertainties for the unfolded differential measurement for $|\eta(\gamma)|$.

The covariance matrix of systematic uncertainties for the unfolded differential measurement for $|\eta(\gamma)|$.

The covariance matrix of systematic uncertainties for the unfolded differential measurement for $\Delta R(l,\gamma)$.

The covariance matrix of systematic uncertainties for the unfolded differential measurement for $\Delta R(l,\gamma)$.

The covariance matrix of statistic uncertainties for the unfolded differential measurement for $p_{T}(\gamma)$.

The covariance matrix of statistic uncertainties for the unfolded differential measurement for $p_{T}(\gamma)$.

The covariance matrix of statistic uncertainties for the unfolded differential measurement for $|\eta(\gamma)|$.

The covariance matrix of statistic uncertainties for the unfolded differential measurement for $|\eta(\gamma)|$.

The covariance matrix of statistic uncertainties for the unfolded differential measurement for $\Delta R(l,\gamma)$.

The covariance matrix of statistic uncertainties for the unfolded differential measurement for $\Delta R(l,\gamma)$.

The correlation matrix of statistical uncertainties for the unfolded differential measurement for $p_{T}(\gamma)$.

The correlation matrix of statistical uncertainties for the unfolded differential measurement for $p_{T}(\gamma)$.

The correlation matrix of statistical uncertainties for the unfolded differential measurement for $|\eta(\gamma)|$.

The correlation matrix of statistical uncertainties for the unfolded differential measurement for $|\eta(\gamma)|$.

The correlation matrix of statistical uncertainties for the unfolded differential measurement for $\Delta R(l,\gamma)$.

The correlation matrix of statistical uncertainties for the unfolded differential measurement for $\Delta R(l,\gamma)$.

The correlation matrix of systematic uncertainties for the unfolded differential measurement for $p_{T}(\gamma)$.

The correlation matrix of systematic uncertainties for the unfolded differential measurement for $p_{T}(\gamma)$.

The correlation matrix of systematic uncertainties for the unfolded differential measurement for $|\eta(\gamma)|$.

The correlation matrix of systematic uncertainties for the unfolded differential measurement for $|\eta(\gamma)|$.

The correlation matrix of systematic uncertainties for the unfolded differential measurement for $\Delta R(l,\gamma)$.

The correlation matrix of systematic uncertainties for the unfolded differential measurement for $\Delta R(l,\gamma)$.

Summary of the one-dimensional intervals at 68 and 95% CL.

Summary of the one-dimensional intervals at 68 and 95% CL.

The observed and predicted post-fit yields for the combined Run 2 data set in the SR3 signal region for the electron channel.

The observed and predicted post-fit yields for the combined Run 2 data set in the SR3 signal region for the electron channel.

The observed and predicted post-fit yields for the combined Run 2 data set in the SR3 signal region for the muon channel.

The observed and predicted post-fit yields for the combined Run 2 data set in the SR3 signal region for the muon channel.

The observed and predicted post-fit yields for the combined Run 2 data set in the SR4p signal region for the electron channel.

The observed and predicted post-fit yields for the combined Run 2 data set in the SR4p signal region for the electron channel.

The observed and predicted post-fit yields for the combined Run 2 data set in the SR4p signal region for the muon channel.

The observed and predicted post-fit yields for the combined Run 2 data set in the SR4p signal region for the muon channel.

Negative log-likelihood ratio values with respect to the best fit value of the one-dimensional profiled scan for the Wilson coefficient $c_{tZ}$.

Negative log-likelihood ratio values with respect to the best fit value of the one-dimensional profiled scan for the Wilson coefficient $c_{tZ}$.

Negative log-likelihood ratio values with respect to the best fit value of the one-dimensional profiled scan for the Wilson coefficient $c^{I}_{tZ}$.

Negative log-likelihood ratio values with respect to the best fit value of the one-dimensional profiled scan for the Wilson coefficient $c^{I}_{tZ}$.

Negative log-likelihood ratio values with respect to the best fit value of the one-dimensional scan for the Wilson coefficient $c_{tZ}$.

Negative log-likelihood ratio values with respect to the best fit value of the one-dimensional scan for the Wilson coefficient $c_{tZ}$.

Negative log-likelihood ratio values with respect to the best fit value of the one-dimensional scan for the Wilson coefficient $c^{I}_{tZ}$.

Negative log-likelihood ratio values with respect to the best fit value of the one-dimensional scan for the Wilson coefficient $c^{I}_{tZ}$.

Negative log-likelihood ratio values with respect to the best fit value of the two-dimensional scan for the Wilson coefficients $c_{tZ}$ and $c^{I}_{tZ}$.

Negative log-likelihood ratio values with respect to the best fit value of the two-dimensional scan for the Wilson coefficients $c_{tZ}$ and $c^{I}_{tZ}$.

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.