Simultaneous coupling measurement $\kappa_V/\kappa_f$

Simultaneous coupling measurement $\kappa_V/\kappa_f$

Simultaneous coupling measurement $\kappa_V/\kappa_f$

Couplings resolved loops. Numbers are in $\kappa_i$.

Couplings effective loops.

Upper limits at 95% CL on the SM strength modifier for the HH production, per final state and combined.

Upper limits at 95% CL on the HH production cross section for different values of $\kappa_\lambda$.

Upper limits at 95% CL on the HH production cross section for different values of $\kappa_{2V}$.

Signal strength modifiers per production channel tims decay mode $\mu_i^f$.

Couplings effective loops including the invisible and undetermined branching fractions.

$\kappa_{\lambda}$ 68 and 95% confidence intervals, from single and double Higgs productions.

Simultaneous coupling measurement $\kappa_\lambda/\kappa_{2V}$

Simultaneous coupling measurement $\kappa_\lambda/\kappa_{2V}$

Simultaneous coupling measurement $\kappa_\lambda/\kappa_{2V}$

Observed correlations between the signal strength modifiers per production mode, $\mu_i$

Observed correlations between the signal strength modifiers per decay channel, $\mu^f$

Observed correlations between the signal strength modifiers per production mode times decay channel $\mu_i^f$.

Observed correlations between the coupling modifiers in the resolved loop model

Observed correlations between the coupling modifiers in the effective loop model

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Final dijet $v_{2}$, $v_{3}$ and $v_{4}$ results presented as a function of centrality.

Post-fit distribution of the $M(ll)$ variable for the ultrahigh-$p_{\mathrm{T}}^{\mathrm{miss}}$ bins in the '2l soft' signal region of the '2/3l soft' analysis.

Post-fit distribution of the $M(ll)$ variable for the low-$p_{\mathrm{T}}^{\mathrm{miss}}$ bins in the '3l soft' signal region of the the '2/3l soft' analysis.

Post-fit distribution of the $M(ll)$ variable for the medium-$p_{\mathrm{T}}^{\mathrm{miss}}$ bins in the '3l soft' signal region of the the '2/3l soft' analysis.

Post-fit distribution of the $m_{\mathrm{T2}}(ll)$ variable for low-$p_{\mathrm{T}}^{\mathrm{miss}}$ bins in the '2l soft' signal region of the '2/3l soft' analysis.

Post-fit distribution of the $m_{\mathrm{T2}}(ll)$ variable for medium-$p_{\mathrm{T}}^{\mathrm{miss}}$ bins in the '2l soft' signal region of the '2/3l soft' analysis.

Post-fit distribution of the $m_{\mathrm{T2}}(ll)$ variable for high-$p_{\mathrm{T}}^{\mathrm{miss}}$ bins in the '2l soft' signal region of the '2/3l soft' analysis.

Post-fit distribution of the $m_{\mathrm{T2}}(ll)$ variable for ultrahigh-$p_{\mathrm{T}}^{\mathrm{miss}}$ bins in the '2l soft' signal region of the '2/3l soft' analysis.

2SS $\ell/{\geq}\,3\ell$ search: observed and expected yields across the SRs in category A, events with three light leptons of which at least two form an OSSF pair, after the requirement that the leading-lepton $p_{\mathrm{T}}$ be greater than 30 GeV is applied.

2SS $\ell/{\geq}\,3\ell$ search: observed and expected yields across the SRs of the '${\geq}\ 3\ell$' search in category B, events with three light leptons and no OSSF pair, after the requirement that the leading-lepton $p_{\mathrm{T}}$ be greater than 30 GeV is applied.

Wino-bino model: cross section limits in the model parameter space, for wino-like chargino-neutralino production in the WZ topology for the full parameter space.

Wino-bino model: cross section limits in the model parameter space, for wino-like chargino-neutralino production in the WZ topology for the compressed space.

Wino-bino model: cross section limits in the model parameter space, for wino-like chargino-neutralino production in the WH topology for the full parameter space.

Wino-bino model: cross section limits in the model parameter space, for wino-like chargino-neutralino production with mixed topology with equal branching fraction to WZ and WH.

Wino-bino model: exclusion contours from the individual and combined analyses targeting WZ topology for the full parameter space. For visualization of the exclusion contours, linear interpolation is employed to account for the limited granularity of the available signal samples.

Wino-bino model: exclusion contours from the individual and combined analyses targeting the corresponding compressed region. For visualization of the exclusion contours, linear interpolation is employed to account for the limited granularity of the available signal samples.

Wino-bino model: exclusion contours from the individual and combined analyses targeting the WH topology for the full parameter space. For visualization of the exclusion contours, linear interpolation is employed to account for the limited granularity of the available signal samples.

Wino-bino model: exclusion contours from the individual and combined analyses targeting combined contours for these two topologies. For visualization of the exclusion contours, linear interpolation is employed to account for the limited granularity of the available signal samples.

GMSB model: expected and observed cross section limits for the neutralino-neutralino production for the ZZ topology.

GMSB model: expected and observed cross section limits for the neutralino-neutralino production for the HH topology.

GMSB model: expected and observed cross section limits for the neutralino-neutralino production for the mixed topology with equal branching fraction to H and Z.

GMSB model: cross section limits for neutralino-neutralino production as a function of the NSLP mass and the branching fraction to the H boson for the combination of the searches.

GMSB model: exclusion limit for neutralino-neutralino production as a function of the NSLP mass and the branching fraction to the H boson for the combination of the searches along with the input searches. For visualization of the exclusion contours, linear interpolation is employed to account for the limited granularity of the available signal samples.

Cross section upper limit(s) in the mass plane of NLSP and LSP masses for the higgsino-bino model.

Mass plane cross section upper limit for direct slepton pair production, with observed and expected exclusion limits in the full mass plane from the combination.

Mass plane cross section upper limit for direct slepton pair production, with observed and expected exclusion limits in the compressed region from '2/3l' soft search.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

The elliptic flow after nonflow subtraction, $v_{2}^{sub}/4$, for $f_0(980)$ as a function of $<KE_{T}>/4$ in pPb collision at 8.16 TeV.

The elliptic flow after nonflow subtraction, $v_{2}^{sub}/2$, for $f_0(980)$ as a function of $<p_{T}>/2$ in pPb collision at 8.16 TeV.

The elliptic flow after nonflow subtraction, $v_{2}^{sub}/4$, for $f_0(980)$ as a function of $<p_{T}>/4$ in pPb collision at 8.16 TeV.

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.