Best fit values of $\sigma(gg\to H\to ZZ)$, $\sigma_i/\sigma_{gg\mathrm{F}}$, and $\mathrm{B}^f/\mathrm{B}^{ZZ}$ relative to their SM prediction from the combined analysis of the $\sqrt{s}$=7 and 8 TeV data. The results are shown for the combination of ATLAS and CMS, and also separately for each experiment, together with their total uncertainties and their breakdown into the four components described in the text. The expected uncertainties in the measurements are also shown.

Best fit values of $\sigma(gg\to H\to WW)$, $\sigma_i/\sigma_{gg\mathrm{F}}$, and $\mathrm{B}^f/\mathrm{B}^{WW}$ from the combined analysis of the $\sqrt{s}$=7 and 8 TeV data. The values involving cross sections are given for $\sqrt{s}$=8 TeV, assuming the SM values for $\sigma_i(7 \mathrm{TeV})/\sigma_i(8 \mathrm{TeV})$. The results are shown for the combination of ATLAS and CMS, and also separately for each experiment, together with their total uncertainties and their breakdown into the four components described in the text. The expected uncertainties in the measurements are also shown.

Best fit values of $\sigma(gg\to H\to WW)$, $\sigma_i/\sigma_{gg\mathrm{F}}$, and $\mathrm{B}^f/\mathrm{B}^{WW}$ relative to their SM prediction from the combined analysis of the $\sqrt{s}$=7 and 8 TeV data. The results are shown for the combination of ATLAS and CMS, and also separately for each experiment, together with their total uncertainties and their breakdown into the four components described in the text. The expected uncertainties in the measurements are also shown.

Best fit values of $\kappa_{gZ}= \kappa_{g}\cdot\kappa_{Z} / \kappa_{H}$ and of the ratios of coupling modifiers, as defined in the most generic parameterisation described in the context of the $\kappa$ framework, from the combined analysis of the $\sqrt{s}$=7 and 8 TeV data. The results are shown for the combination of ATLAS and CMS and also separately for each experiment, together with their total uncertainties and their breakdown into the four components described in the text. The uncertainties in $\lambda_{tg}$ and $\lambda_{WZ}$, for which a negative solution is allowed, are calculated around the overall best fit value. The expected total uncertainties in the measurements are also shown. For those parameters with no sensitivity to the sign, only the absolute values are shown.

Measured global signal strength $\mu$ and its total uncertainty, together with the breakdown of the uncertainty into its four components as defined in the text. The results are shown for the combination of ATLAS and CMS, and separately for each experiment. The expected uncertainty, with its breakdown, is also shown.

Measured signal strengths $\mu$ and their total uncertainties for different Higgs boson production processes. The results are shown for the combination of ATLAS and CMS, and separately for each experiment, for the combined $\sqrt{s}$=7 and 8 TeV data. The expected uncertainties in the measurements are also displayed. These results are obtained assuming that the Higgs boson branching fractions are the same as in the SM.

Measured signal strengths $\mu$ and their total uncertainties for different Higgs boson decay channels. The results are shown for the combination of ATLAS and CMS, and separately for each experiment, for the combined $\sqrt{s}$=7 and 8 TeV data. The expected uncertainties in the measurements are also displayed. These results are obtained assuming that the Higgs boson production process cross sections at $\sqrt{s}$ = 7 and 8 TeV are the same as in the SM.

Results of the ten-parameter fit of $\mu_F^f = \mu_{gg\mathrm{F}+ttH}^f$ and $\mu_V^f = \mu_{\mathrm{VBF}+VH}^f$ for each of the five decay channels. The results are shown for the combination of ATLAS and CMS, together with their measured and expected uncertainties. The measured results are also shown separately for each experiment.

Results of the six-parameter fit of the global ratio $\mu_V/\mu_F = \mu_{\mathrm{VBF}+VH}/\mu_{gg\mathrm{F}+ttH}$ together with $\mu_F^f$ for each of the five decay channels. The results are shown for the combination of ATLAS and CMS, together with their measured and expected uncertainties. The measured results are also shown separately for each experiment.

Fit results allowing BSM loop couplings, assuming that $|\kappa_{V}| \le$ 1, where $\kappa_{V}$ denotes $\kappa_{Z}$ or $\kappa_{W}$, and that $\mathrm{B_{BSM}} \ge$ 0. The results for the combination of ATLAS and CMS are reported with their measured and expected uncertainties. Also shown are the results from each experiment. For the parameters with both signs allowed, the other 1$\sigma$ interval is shown on a second line. For those parameters with no sensitivity to the sign, only the absolute values are shown.

Fit results allowing BSM loop couplings, assuming that there are no additional BSM contributions to the Higgs boson width, i.e. $\mathrm{B_{BSM}}=0$. The results for the combination of ATLAS and CMS are reported with their measured and expected uncertainties. Also shown are the results from each experiment. For the parameters with both signs allowed, the other 1$\sigma$ interval is shown on a second line. When a parameter is constrained and reaches a boundary, namely $\mathrm{B_{BSM}}$ = 0, the uncertainty is not indicated. For those parameters with no sensitivity to the sign, only the absolute values are shown.

Fit results for the parameterisation assuming the absence of BSM particles in the loops ($\mathrm{B_{BSM}}$=0). The results with their measured and expected uncertainties are reported for the combination of ATLAS and CMS, together with the individual results from each experiment. For the parameters with both signs allowed, the other 1$\sigma$ CL interval is shown on a second line. When a parameter is constrained and reaches a boundary, namely $|\kappa_\mu|$ = 0, the uncertainty is not indicated. For those parameters with no sensitivity to the sign, only the absolute values are shown.

Summary of fit results for a parameterisation probing the ratios of coupling modifiers for up-type versus down-type fermions. The results for the combination of ATLAS and CMS are reported together with their measured and expected uncertainties. Also shown are the results from each experiment. The parameter $\kappa_{uu}$ is positive definite since $\kappa_H$ is always assumed to be positive. For the parameter $\lambda_{du}$, for which both signs are allowed, the other 1$\sigma$ CL interval is shown on a second line. Negative values for the parameter $\lambda_{Vu}$ are excluded by more than 4$\sigma$.

Summary of fit results for a parameterisation probing the ratios of coupling modifiers for leptons versus quarks. The results for the combination of ATLAS and CMS are reported together with their measured and expected uncertainties. Also shown are the results from each experiment. The parameter $\kappa_{qq}$ is positive definite since $\kappa_H$ is always assumed to be positive. For the parameter $\lambda_{lq}$, for which there is no sensitivity to the sign, only the absolute values are shown. Negative values for the parameter $\lambda_{Vq}$ are excluded by more than 4$\sigma$.

Correlation matrix obtained from the fit combining the ATLAS and CMS data using the generic parameterisation with 23 parameters, $\sigma_i\cdot\mathrm{B}^f$ for each specific channel $i\to H\to f$. Only 20 parameters are shown because the other three, corresponding to the $H\to ZZ$ decay channel for the $WH$, $ZH$, and $ttH$ production processes, are not measured with a meaningful precision.

Correlation matrix obtained from the fit combining the ATLAS and CMS data using the generic parameterisation with nine parameters, $\sigma(gg\to H\to ZZ)$, $\sigma_i/\sigma_{gg\mathrm{F}}$, and $\mathrm{B}^f/\mathrm{B}^{ZZ}$.

Correlation matrix obtained from the fit combining the ATLAS and CMS data using the generic parameterisation with seven parameters, $\kappa_{gZ}=\kappa_{g}\cdot\kappa_{Z} / \kappa_{H}$ and the ratios of coupling modifiers.

Expected correlation matrix obtained from the fit combining ATLAS and CMS pre-fit Asimov data sets using the generic parameterisation with 23 parameters, $\sigma_i\cdot\mathrm{B}^f$ for each specific channel $i\to H\to f$. Only 20 parameters are shown because the other three, corresponding to the $H\to ZZ$ decay channel for the $WH$, $ZH$, and $ttH$ production processes, are not measured with a meaningful precision.

Expected correlation matrix obtained from the fit combining ATLAS and CMS pre-fit Asimov data sets using the generic parameterisation with nine parameters, $\sigma(gg\to H\to ZZ)$, $\sigma_i/\sigma_{gg\mathrm{F}}$, and $\mathrm{B}^f/\mathrm{B}^{ZZ}$.

Expected correlation matrix obtained from the fit combining ATLAS and CMS pre-fit Asimov data sets using the generic parameterisation with seven parameters, $\kappa_{gZ}=\kappa_{g}\cdot\kappa_{Z} / \kappa_{H}$ and the ratios of coupling modifiers.

ATLAS+CMS combined best-fit and 68% and 95% CL negative log-likelihood contours in the ($\kappa_{g}$,$\kappa_{\gamma}$) plane.

ATLAS best-fit and 68% and 95% CL negative log-likelihood contours in the ($\kappa_{g}$,$\kappa_{\gamma}$) plane.

CMS best-fit and 68% and 95% CL negative log-likelihood contours in the ($\kappa_{g}$,$\kappa_{\gamma}$) plane.

Best-fit and 68% and 95% CL negative log-likelihood contours in the ($\kappa_{F}$,$\kappa_{V}$) plane.

Best-fit and 68% CL negative log-likelihood contour in the ($\kappa_{F}$,$\kappa_{V}$) plane for the $H\rightarrow\gamma\gamma$ channel.

Best-fit and 68% CL negative log-likelihood contour in the ($\kappa_{F}$,$\kappa_{V}$) plane for the $H\rightarrow ZZ$ channel.

Best-fit and 68% CL negative log-likelihood contour in the ($\kappa_{F}$,$\kappa_{V}$) plane for the $H\rightarrow WW$ channel.

Best-fit and 68% CL negative log-likelihood contour in the ($\kappa_{F}$,$\kappa_{V}$) plane for the $H\rightarrow\tau\tau$ channel.

Best-fit and 68% CL negative log-likelihood contour in the ($\kappa_{F}$,$\kappa_{V}$) plane for the $H\rightarrow bb$ channel.

ATLAS best-fit and 68% and 95% CL negative log-likelihood contours in the ($\kappa_{F}$,$\kappa_{V}$) plane.

CMS best-fit and 68% and 95% CL negative log-likelihood contours in the ($\kappa_{F}$,$\kappa_{V}$) plane.

Best-fit and 68% CL negative log-likelihood contour in the ($\kappa_{F}$,$\kappa_{V}$) plane for the $H\rightarrow\gamma\gamma$ channel, assuming $\kappa_{F}>0$.

Best-fit and 68% CL negative log-likelihood contour in the ($\kappa_{F}$,$\kappa_{V}$) plane for the $H\rightarrow ZZ$ channel, assuming $\kappa_{F}>0$.

Best-fit and 68% CL negative log-likelihood contour in the ($\kappa_{F}$,$\kappa_{V}$) plane for the $H\rightarrow WW$ channel, assuming $\kappa_{F}>0$.

Best-fit and 68% CL negative log-likelihood contour in the ($\kappa_{F}$,$\kappa_{V}$) plane for the $H\rightarrow\tau\tau$ channel, assuming $\kappa_{F}>0$.

Best-fit and 68% CL negative log-likelihood contour in the ($\kappa_{F}$,$\kappa_{V}$) plane for the $H\rightarrow bb$ channel, assuming $\kappa_{F}>0$.

Best-fit and 68% and 95% CL negative log-likelihood contours in the ($\mu^{f}_{gg\mathrm{F}+ttH}$,$\mu^{f}_{\mathrm{VBF}+VH}$) plane for the $H\rightarrow\gamma\gamma$ channel.

Best-fit and 68% and 95% CL negative log-likelihood contours in the ($\mu^{f}_{gg\mathrm{F}+ttH}$,$\mu^{f}_{\mathrm{VBF}+VH}$) plane for the $H\rightarrow ZZ$ channel.

Best-fit and 68% and 95% CL negative log-likelihood contours in the ($\mu^{f}_{gg\mathrm{F}+ttH}$,$\mu^{f}_{\mathrm{VBF}+VH}$) plane for the $H\rightarrow WW$ channel.

Best-fit and 68% and 95% CL negative log-likelihood contours in the ($\mu^{f}_{gg\mathrm{F}+ttH}$,$\mu^{f}_{\mathrm{VBF}+VH}$) plane for the $H\rightarrow\tau\tau$ channel.

Best-fit and 68% and 95% CL negative log-likelihood contours in the ($\mu^{f}_{gg\mathrm{F}+ttH}$,$\mu^{f}_{\mathrm{VBF}+VH}$) plane for the $H\rightarrow bb$ channel.

Left pannel. The vertical bars (boxes) represent the statistical (bin-to-bin systematic) uncertainties, while the horizontal bars give the bin widths. The global uncertainty (of 2.3%) is not graphically represented. The blue line represents the average for $p_T > 18$ GeV. For comparison, the LHCb measurement [10.1103/PhysRevLett.124.122002] is also shown. $ 12 < \mathrm{B} \, p_T < 70$ GeV and $ 0 < |y| < 2.4 $. Global uncertanties are not included in the table (2.3%)

Left pannel. The vertical bars (boxes) represent the statistical (bin-to-bin systematic) uncertainties, while the horizontal bars give the bin widths. The global uncertainty (of 2.3%) is not graphically represented. The blue line represents the average for $p_T > 18$ GeV. For comparison, the LHCb measurement [10.1103/PhysRevLett.124.122002] is also shown. $ 12 < \mathrm{B} \, p_T < 70$ GeV and $ 0 < |y| < 2.4 $. Global uncertanties are not included in the table (2.3%)

Left pannel. The vertical bars (boxes) represent the statistical (bin-to-bin systematic) uncertainties, while the horizontal bars give the bin widths. The global uncertainty (of 2.3%) is not graphically represented. The blue line represents the average for $p_T > 18$ GeV. For comparison, the LHCb measurement [10.1103/PhysRevLett.124.122002] is also shown. $ 12 < \mathrm{B} \, p_T < 70$ GeV and $ 0 < |y| < 2.4 $. Global uncertanties are not included in the table (2.3%)

Right pannel. The vertical bars (boxes) represent the statistical (bin-to-bin systematic) uncertainties, while the horizontal bars give the bin widths. The global uncertainty (of 2.3%) is not graphically represented. The blue line represents the average for $p_T > 18$ GeV. For comparison, the LHCb measurement [10.1103/PhysRevLett.124.122002] is also shown. $ 12 < \mathrm{B} \, p_T < 70$ GeV and $ 0 < |y| < 2.4 $. Global uncertanties are not included in the table (2.3%)

Right pannel. The vertical bars (boxes) represent the statistical (bin-to-bin systematic) uncertainties, while the horizontal bars give the bin widths. The global uncertainty (of 2.3%) is not graphically represented. The blue line represents the average for $p_T > 18$ GeV. For comparison, the LHCb measurement [10.1103/PhysRevLett.124.122002] is also shown. $ 12 < \mathrm{B} \, p_T < 70$ GeV and $ 0 < |y| < 2.4 $. Global uncertanties are not included in the table (2.3%)

Right pannel. The vertical bars (boxes) represent the statistical (bin-to-bin systematic) uncertainties, while the horizontal bars give the bin widths. The global uncertainty (of 2.3%) is not graphically represented. The blue line represents the average for $p_T > 18$ GeV. For comparison, the LHCb measurement [10.1103/PhysRevLett.124.122002] is also shown. $ 12 < \mathrm{B} \, p_T < 70$ GeV and $ 0 < |y| < 2.4 $. Global uncertanties are not included in the table (2.3%)

Left panel.The vertical bars (boxes) represent the statistical (bin-to-bin systematic) uncertainties, while the horizontal bars give the bin widths. The global uncertainty (of 4.9\%) is not graphically represented. The blue line represents the average of all the points. $ 12 < \mathrm{B} \, p_T < 70$ GeV and $ 0 < |y| < 2.4 $. Global uncertanties are not included in the table (4.9%)

Left panel.The vertical bars (boxes) represent the statistical (bin-to-bin systematic) uncertainties, while the horizontal bars give the bin widths. The global uncertainty (of 5.7%) is not graphically represented. The blue line represents the average of all the points. $ 12 < \mathrm{B} \, p_T < 70$ GeV and $ 0 < |y| < 2.4 $. Global uncertanties are not included in the table (5.7%)

Left panel.The vertical bars (boxes) represent the statistical (bin-to-bin systematic) uncertainties, while the horizontal bars give the bin widths. The global uncertainty (of 5.7%) is not graphically represented. The blue line represents the average of all the points. $ 12 < \mathrm{B} \, p_T < 70$ GeV and $ 0 < |y| < 2.4 $. Global uncertanties are not included in the table (5.7%)

Right panel.The vertical bars (boxes) represent the statistical (bin-to-bin systematic) uncertainties, while the horizontal bars give the bin widths. The global uncertainty (of 4.9\%) is not graphically represented. The blue line represents the average of all the points. $ 12 < \mathrm{B} \, p_T < 70$ GeV and $ 0 < |y| < 2.4 $. Global uncertanties are not included in the table (4.9%)

Right panel.The vertical bars (boxes) represent the statistical (bin-to-bin systematic) uncertainties, while the horizontal bars give the bin widths. The global uncertainty (of 5.7%) is not graphically represented. The blue line represents the average of all the points. $ 12 < \mathrm{B} \, p_T < 70$ GeV and $ 0 < |y| < 2.4 $. Global uncertanties are not included in the table (5.7%)

Right panel.The vertical bars (boxes) represent the statistical (bin-to-bin systematic) uncertainties, while the horizontal bars give the bin widths. The global uncertainty (of 5.7%) is not graphically represented. The blue line represents the average of all the points. $ 12 < \mathrm{B} \, p_T < 70$ GeV and $ 0 < |y| < 2.4 $. Global uncertanties are not included in the table (5.7%)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

The distribution of the BDT discriminants for the 2016--2018 data set for three different categories in the combined single-electron and single-muon channels. The three categories are defined by the number of resolved t tags ($N_\textrm{RT}$), b tags ($N_\textrm{b}$), and jets ($N_\textrm{j}$), selected as representative based on their sensitivity to signal. Here, $\textrm{t}\bar{\textrm{t}} + \geq 1 \textrm{b}$ refers to $\textrm{t}\bar{\textrm{t}}$ events with at least one additional b jet, while $\textrm{t}\bar{\textrm{t}} + 0 \textrm{b}$ includes all other $\textrm{t}\bar{\textrm{t}}$ events not produced in association with a boson. The TOP grouping contains single top quark production along with the other $\textrm{t}\bar{\textrm{t}}$ processes not explicitly shown, and EW refers to events that contain W and Z bosons but no top quarks.

Measured signal strength ($\mu = \sigma_{\textrm{t}\bar{\textrm{t}}\textrm{t}\bar{\textrm{t}}}/ \sigma_{\textrm{t}\bar{\textrm{t}}\textrm{t}\bar{\textrm{t}}} ^{\textrm{SM}}$), corresponding cross section (in fb), and the expected and observed significance (in standard deviations) for $\textrm{t}\bar{\textrm{t}}\textrm{t}\bar{\textrm{t}}$ production from all analysis channels. Uncertainties shown in this table are statistical and systematic uncertainties respectively. In this table, SSDL\&ML and OSDL (2016) represent results from EPJC 80 (2020) 75 and JHEP 11 (2019) 082 respectively.

The distribution of the BDT discriminants for the 2016--2018 data set for three different categories in the combined single-electron and single-muon channels. The three categories are defined by the number of resolved t tags ($N_\textrm{RT}$), b tags ($N_\textrm{b}$), and jets ($N_\textrm{j}$), selected as representative based on their sensitivity to signal. Here, $\textrm{t}\bar{\textrm{t}} + \geq 1 \textrm{b}$ refers to $\textrm{t}\bar{\textrm{t}}$ events with at least one additional b jet, while $\textrm{t}\bar{\textrm{t}} + 0 \textrm{b}$ includes all other $\textrm{t}\bar{\textrm{t}}$ events not produced in association with a boson. The TOP grouping contains single top quark production along with the other $\textrm{t}\bar{\textrm{t}}$ processes not explicitly shown, and EW refers to events that contain W and Z bosons but no top quarks. The backgrounds and $\textrm{t}\bar{\textrm{t}}\textrm{t}\bar{\textrm{t}}$ signal (derived from the fit) are shown as a stacked histogram. The hatched bands correspond to the estimated total uncertainty after the fit. While the bins are shown to be equal width, they do not correspond to equal width in BDT value.

The distribution of the BDT discriminants for the full 2016--2018 data set in the all-hadronic channel. The SR category shown in this figure is defined by $N_\textrm{RT}=1$, $N_\textrm{BT} \geq 1$, HT > 1400 GeV. The background from QCD multijet and \ttbar production is derived from control regions in the data. Estimates for the \tttt signal and other backgrounds are shown using simulated samples.

The distribution of the BDT discriminants for the full 2016--2018 data set in the all-hadronic channel. The sample VR category shown is defined by $N_\textrm{RT}=1$, $N_\textrm{BT} \geq 1$, $H_T > 1400$ GeV. The background from QCD multijet and $\textrm{t}\bar{\textrm{t}}$ production is derived from control regions in the data. Estimates for the $\textrm{t}\bar{\textrm{t}}\textrm{t}\bar{\textrm{t}}$ signal and other backgrounds are shown using simulated samples. The hatched bands correspond to the estimated total uncertainty.

The distribution of the BDT discriminants for the full 2016--2018 data set in the all-hadronic channel. The SR category shown in this figure is defined by $N_\textrm{BT} \geq 2$, HT > 1100 GeV. The background from QCD multijet and \ttbar production is derived from control regions in the data. Estimates for the \tttt signal and other backgrounds are shown using simulated samples.

The distribution of the BDT discriminants for the full 2016--2018 data set in the all-hadronic channel. The sample VR category shown is defined by $N_\textrm{RT} \geq 2$, $H_T > 1100$ GeV. The background from QCD multijet and $\textrm{t}\bar{\textrm{t}}$ production is derived from control regions in the data. Estimates for the $\textrm{t}\bar{\textrm{t}}\textrm{t}\bar{\textrm{t}}$ signal and other backgrounds are shown using simulated samples. The hatched bands correspond to the estimated total uncertainty.

Expected and observed significance (in standard deviations) for $\textrm{t}\bar{\textrm{t}}\textrm{t}\bar{\textrm{t}}$ production from each final state and the combination with previous CMS results (EPJC 80 (2020) 75 and JHEP 11 (2019) 082). The same-sign dilepton and multilepton (SSDL\&ML) final state results are from EPJC 80 (2020) 75.

The distribution of the BDT discriminants for the full 2016--2018 data set in the all-hadronic channel. The SR category shown in this figure is defined by $N_\textrm{RT}=1$, $N_\textrm{BT} \geq 1$, $H_T > 1400$ GeV. The background from QCD multijet and $\textrm{t}\bar{\textrm{t}}$ production is derived from control regions in the data. Estimates for the $\textrm{t}\bar{\textrm{t}}\textrm{t}\bar{\textrm{t}}$ signal and other backgrounds are shown using simulated samples. The hatched bands correspond to the estimated total uncertainty after the fit.

Measured signal strength ($\mu = \sigma_{\textrm{t}\bar{\textrm{t}}\textrm{t}\bar{\textrm{t}}}/ \sigma_{\textrm{t}\bar{\textrm{t}}\textrm{t}\bar{\textrm{t}}} ^{\textrm{SM}}$), corresponding cross section (in fb), and the expected and observed significance (in standard deviations) for $\textrm{t}\bar{\textrm{t}}\textrm{t}\bar{\textrm{t}}$ production from all analysis channels. Uncertainties shown in this table are statistical and systematic uncertainties respectively. In this table, SSDL\&ML and OSDL (2016) represent results from EPJC 80 (2020) 75 and JHEP 11 (2019) 082 respectively.

The distribution of the BDT discriminants for the full 2016--2018 data set in the all-hadronic channel. The SR category shown in this figure is defined by $N_\textrm{RT} = 2$, $H_T > 1100$ GeV. The background from QCD multijet and $\textrm{t}\bar{\textrm{t}}$ production is derived from control regions in the data. Estimates for the $\textrm{t}\bar{\textrm{t}}\textrm{t}\bar{\textrm{t}}$ signal and other backgrounds are shown using simulated samples. The hatched bands correspond to the estimated total uncertainty after the fit.

Expected and observed significance (in standard deviations) for $\textrm{t}\bar{\textrm{t}}\textrm{t}\bar{\textrm{t}}$ production from each final state and the combination with previous CMS results (EPJC 80 (2020) 75 and JHEP 11 (2019) 082). The same-sign dilepton and multilepton (SSDL\&ML) final state results are from EPJC 80 (2020) 75.

Measured signal strength ($\mu = \sigma_{\textrm{t}\bar{\textrm{t}}\textrm{t}\bar{\textrm{t}}}/ \sigma_{\textrm{t}\bar{\textrm{t}}\textrm{t}\bar{\textrm{t}}} ^{\textrm{SM}}$), corresponding cross section (in fb), and the expected and observed significance (in standard deviations) for $\textrm{t}\bar{\textrm{t}}\textrm{t}\bar{\textrm{t}}$ production from all analysis channels. This table shows production from each analysis channel in this Letter, the combination of those channels, the results from previously published results, and the full combination of all CMS 2016-2018 results.

The total coherent $\mathrm{J}/\psi$ photoproduction cross section as a function of photon-nuclear center-of-mass energy per nucleon $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$, measured in PbPb ultra-peripheral collisions at $\sqrt{s_{\mathrm{NN}}}$ = 5.02 TeV. The $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$ values used correspond to the center of each rapidity range. The theoretical uncertainties is due to the uncertainties in the photon flux.

The nuclear gluon suppression factor $R_{\mathrm{g}}^{\mathrm{Pb}}$ as a function of Bjorken $x$ extracted from the CMS measurement of the coherent $\mathrm{J}/\psi$ photoproduction in PbPb ultra-peripheral collisions at $\sqrt{s_{\mathrm{NN}}}$ = 5.02 TeV. The $x$ values are evaluated at the centers of their corresponding rapidity ranges. The theoretical uncertainties are due to the uncertainties in the photon flux and the impulse approximation model.

The nuclear gluon suppression factor $R_{\mathrm{g}}^{\mathrm{Pb}}$ as a function of Bjorken $x$ extracted from the CMS measurement of the coherent $\mathrm{J}/\psi$ photoproduction in PbPb ultra-peripheral collisions at $\sqrt{s_{\mathrm{NN}}}$ = 5.02 TeV. The $x$ values are evaluated at the centers of their corresponding rapidity ranges. The theoretical uncertainties are due to the uncertainties in the photon flux and the impulse approximation model.

The total covariance matrix of the total coherent photoproduction cross section as a function of photon-nuclear center-of-mass energy per nucleon $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$. The covariance matrix includes both the experimental and theoretical (photon flux) uncertainties. The bins are ordered as increasing in $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$.

The photon flux values from STARLight as a function of rapidity, in different neutron multiplicity classes: 0n0n, 0nXn, and XnXn.

The experimental covariance matrix of the total coherent photoproduction cross section as a function of photon-nuclear center-of-mass energy per nucleon $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$. The bins are ordered as increasing in $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$.

The covariance matrix for the flux in the 0n0n neutron multiplicity class.

The theoretical (photon flux) covariance matrix of the total coherent photoproduction cross section as a function of photon-nuclear center-of-mass energy per nucleon $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$. The bins are ordered as increasing in $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$.

The covariance matrix for the flux in the 0nXn neutron multiplicity class.

The covariance matrix for the flux in the XnXn neutron multiplicity class.

The total covariance matrix of the total coherent photoproduction cross section as a function of photon-nuclear center-of-mass energy per nucleon $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$. The covariance matrix includes both the experimental and theoretical (photon flux) uncertainties. The bins are ordered as increasing in $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$.

The experimental covariance matrix of the total coherent photoproduction cross section as a function of photon-nuclear center-of-mass energy per nucleon $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$. The bins are ordered as increasing in $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$.

The theoretical (photon flux) covariance matrix of the total coherent photoproduction cross section as a function of photon-nuclear center-of-mass energy per nucleon $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$. The bins are ordered as increasing in $W_{\gamma \mathrm{N}}^{\mathrm{Pb}}$.

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

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

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

Differential cross section measurements in bins of pT4l (v3)

Differential cross section measurements in bins of rapidity4l (v3)

Differential cross section measurements in bins of costheta1 (v3)

Differential cross section measurements in bins of costheta1 (v4 (2e2mu))

Differential cross section measurements in bins of costheta1 (v4 (4e+4mu))

Differential cross section measurements in bins of costheta2 (v3)

Differential cross section measurements in bins of costheta2 (v4 (2e2mu))

Differential cross section measurements in bins of costheta2 (v4 (4e+4mu))

Differential cross section measurements in bins of phi (v3)

Differential cross section measurements in bins of phi (v4 (2e2mu))

Differential cross section measurements in bins of phi (v4 (4e+4mu))

Differential cross section measurements in bins of phi1 (v3)

Differential cross section measurements in bins of phi1 (v4 (2e2mu))

Differential cross section measurements in bins of phi1 (v4 (4e+4mu))

Differential cross section measurements in bins of costhetastar (v3)

Differential cross section measurements in bins of costhetastar (v4 (2e2mu))

Differential cross section measurements in bins of costhetastar (v4 (4e+4mu))

Differential cross section measurements in bins of massZ1 (v3)

Differential cross section measurements in bins of massZ1 (v4 (2e2mu))

Differential cross section measurements in bins of massZ1 (v4 (4e+4mu))

Differential cross section measurements in bins of massZ2 (v3)

Differential cross section measurements in bins of massZ2 (v4 (2e2mu))

Differential cross section measurements in bins of massZ2 (v4 (4e+4mu))

Differential cross section measurements in bins of pTj1 (v3)

Differential cross section measurements in bins of pTHj (v3)

Differential cross section measurements in bins of mHj (v3)

Differential cross section measurements in bins of pTj2 (v3)

Differential cross section measurements in bins of mjj (v3)

Differential cross section measurements in bins of absdetajj (v3)

Differential cross section measurements in bins of dphijj (v3)

Differential cross section measurements in bins of pTHjj (v3)

Differential cross section measurements in bins of TCjmax (v3)

Differential cross section measurements in bins of TBjmax (v3)

Differential cross section measurements in bins of D0m (v3)

Differential cross section measurements in bins of D0m (v4 (2e2mu))

Differential cross section measurements in bins of D0m (v4 (4e+4mu))

Differential cross section measurements in bins of Dcp (v3)

Differential cross section measurements in bins of Dcp (v4 (2e2mu))

Differential cross section measurements in bins of Dcp (v4 (4e+4mu))

Differential cross section measurements in bins of D0hp (v3)

Differential cross section measurements in bins of D0hp (v4 (2e2mu))

Differential cross section measurements in bins of D0hp (v4 (4e+4mu))

Differential cross section measurements in bins of Dint (v3)

Differential cross section measurements in bins of Dint (v4 (2e2mu))

Differential cross section measurements in bins of Dint (v4 (4e+4mu))

Differential cross section measurements in bins of DL1 (v3)

Differential cross section measurements in bins of DL1 (v4 (2e2mu))

Differential cross section measurements in bins of DL1 (v4 (4e+4mu))

Differential cross section measurements in bins of DL1Zg (v3)

Differential cross section measurements in bins of DL1Zg (v4 (2e2mu))

Differential cross section measurements in bins of DL1Zg (v4 (4e+4mu))

Differential cross section measurements in bins of rapidity4l_pT4l (v3, bin 0)

Differential cross section measurements in bins of rapidity4l_pT4l (v3, bin 1)

Differential cross section measurements in bins of rapidity4l_pT4l (v3, bin 2)

Differential cross section measurements in bins of njets_pt30_eta4p7_pT4l (v3, bin 0)

Differential cross section measurements in bins of njets_pt30_eta4p7_pT4l (v3, bin 1)

Differential cross section measurements in bins of njets_pt30_eta4p7_pT4l (v3, bin 2)

Differential cross section measurements in bins of pTj1_pTj2 (v3)

Differential cross section measurements in bins of pT4l_pTHj (v3)

Differential cross section measurements in bins of massZ1_massZ2 (v3)

Differential cross section measurements in bins of TCjmax_pT4l (v3, bin 0)

Differential cross section measurements in bins of TCjmax_pT4l (v3, bin 1)

Differential cross section measurements in bins of TCjmax_pT4l (v3, bin 2)

Differential cross section measurements in bins of TCjmax_pT4l (v3, bin 3)

Correlations of higgs fiducial cross section in bins of absdetajj in v3.

Correlations of higgs fiducial cross section in bins of TBjmax in v3.

Correlations of higgs fiducial cross section in bins of massZ1 in v3.

Correlations of higgs fiducial cross section in bins of D0m in v3.

Correlations of higgs fiducial cross section in bins of DL1 in v3.

Correlations of higgs fiducial cross section in bins of mass4l in v3.

Correlations of higgs fiducial cross section in bins of pT4l in v3.

Correlations of higgs fiducial cross section in bins of phi in v3.

Correlations of higgs fiducial cross section in bins of pTHj in v3.

Correlations of higgs fiducial cross section in bins of pTj1 in v3.

Correlations of higgs fiducial cross section in bins of mHj in v3.

Correlations of higgs fiducial cross section in bins of pTHjj in v3.

Correlations of higgs fiducial cross section in bins of DL1Zg in v3.

Correlations of higgs fiducial cross section in bins of njets.

Correlations of higgs fiducial cross section in bins of pTj2 in v3.

Correlations of higgs fiducial cross section in bins of TCjmax in v3.

Correlations of higgs fiducial cross section in bins of rapidity4l in v3.

Correlations of higgs fiducial cross section in bins of costheta2 in v3.

Correlations of higgs fiducial cross section in bins of Dint in v3.

Correlations of higgs fiducial cross section in bins of Dcp in v3.

Correlations of higgs fiducial cross section in bins of phi1 in v3.

Correlations of higgs fiducial cross section in bins of costhetastar in v3.

Correlations of higgs fiducial cross section in bins of D0hp in v3.

Correlations of higgs fiducial cross section in bins of mjj in v3.

Correlations of higgs fiducial cross section in bins of massZ2 in v3.

Correlations of higgs fiducial cross section in bins of costheta1 in v3.

Correlations of higgs fiducial cross section in bins of dphijj in v3.

Correlations of higgs fiducial cross section in bins of massZ1 in v4.

Correlations of higgs fiducial cross section in bins of Dint in v4.

Correlations of higgs fiducial cross section in bins of DL1 in v4.

Correlations of higgs fiducial cross section in bins of D0m in v4.

Correlations of higgs fiducial cross section in bins of massZ2 in v4.

Correlations of higgs fiducial cross section in bins of DL1Zg in v4.

Correlations of higgs fiducial cross section in bins of Dcp in v4.

Correlations of higgs fiducial cross section in bins of D0hp in v4.

Correlations of higgs fiducial cross section in bins of phi in v4.

Correlations of higgs fiducial cross section in bins of costheta2 in v4.

Correlations of higgs fiducial cross section in bins of phi1 in v4.

Correlations of higgs fiducial cross section in bins of costheta1 in v4.

Correlations of higgs fiducial cross section in bins of costhetastar in v4.

Correlations of higgs fiducial cross section in bins of njets vs pt.

Correlations of higgs fiducial cross section in bins of rapidity4l vs pT4l in v3.

Correlations of higgs fiducial cross section in bins of pTj1 vs pTj2 in v3.

Correlations of higgs fiducial cross section in bins of pT4l vs pTHj in v3.

Correlations of higgs fiducial cross section in bins of massZ1 vs massZ2 in v3.

Correlations of higgs fiducial cross section in bins of TCjmax vs pT4l in v3.