The measured differences of mass differences between vector and ground states.

The measured ratios of mass differences between vector and ground states.

Likelihood scan of cHuRe1122 versus cHuRe33. Other Wilson coefficients are fixed to zero.

Likelihood scan of cHdRe1122 versus cHdRe33. Other Wilson coefficients are fixed to zero.

Likelihood scan of cW versus cWtil. Other Wilson coefficients are fixed to zero.

Likelihood scan of cHqMRe1122 versus cHqMRe33. Other Wilson coefficients are profiled as well.

Likelihood scan of cHq3MRe1122 versus cHq3MRe33. Other Wilson coefficients are profiled as well.

Likelihood scan of cHuRe1122 versus cHuRe33. Other Wilson coefficients are profiled as well.

Likelihood scan of cHdRe1122 versus cHdRe33. Other Wilson coefficients are profiled as well.

Likelihood scan of cW versus cWtil. Other Wilson coefficients are profiled as well.

Distributions of discriminant for the $2_{m}^{+}$ and $0^{-}$ models.

Comparison of the shapes extrapolated with a linear or quadratic extrapolation of the QCD contribution in the W+ signal region.

Comparison of the shapes extrapolated with a linear or quadratic extrapolation of the QCD contribution in the W- signal region.

Post-fit distributions of the transverse mass in the W+ signal region.

Post-fit distributions of the transverse mass in the W- signal region.

Post-fit distributions of the dimuon mass in the Z boson signal region.

Example plot for the extrapolation of the QCD contribution from a region with inverted relative isolation criterion to the W+ signal region in the transverse mass bin 12 < mT < 18 GeV. The values corresponding to the smallest relative muon isolation are extrapolated with a linear (smaller value) and quadratic (larger value) function.

Example plot for the extrapolation of the QCD contribution from a region with inverted relative isolation criterion to the W- signal region in the transverse mass bin 12 < mT < 18 GeV.The values corresponding to the smallest relative muon isolation are extrapolated with a linear (smaller value) and quadratic (larger value) function.

Example plot for the extrapolation of the QCD contribution from a region with inverted relative isolation criterion to the W+ signal region in the transverse mass bin 102 < mT < 108 GeV.The values corresponding to the smallest relative muon isolation are extrapolated with a linear (larger value) and quadratic (smaller value) function.

Example plot for the extrapolation of the QCD contribution from a region with inverted relative isolation criterion to the W- signal region in the transverse mass bin 102 < mT < 108 GeV.The values corresponding to the smallest relative muon isolation are extrapolated with a linear (smaller value) and quadratic (larger value) function.

The table compares theoretical and measured values of the product of the fiducial cross sections and branching fractions. The theoretical predictions are generated with DYTurbo in combination with three different PDF sets. All values are normalized to the corresponding measured value. The relative uncertainties on the measured values are given separately with and without the contribution from the luminosity uncertainty.

The table compares theoretical and measured values of the product of the total cross sections and branching fractions. The theoretical predictions are generated with DYTurbo in combination with three different PDF sets. All values are normalized to the corresponding measured value. The relative uncertainties on the measured values are given separately with and without the contribution from the luminosity uncertainty.

The table compares theoretical and measured ratios of the product of the fiducial cross sections and branching fractions. The theoretical predictions are generated with DYTurbo in combination with three different PDF sets. All values are normalized to the corresponding measured value.

The table compares theoretical and measured ratios of the product of the total cross sections and branching fractions. The theoretical predictions are generated with DYTurbo in combination with three different PDF sets. All values are normalized to the corresponding measured value.

Comparison of the measured and theoretical cross sections for Z, W+, W-, and W production at different center-of-mass energies. The theoretical predictions are generated with DYTurbo in combination with the NNPDF 3.1 PDF set.

Corrected distributions of the normalized EEC within jets, differential in $ \left\langle p_{\rm T,jet} \right\rangle R_{L} $ at $R_{\rm jet} =$ 0.6 for one $p_{\rm T, jet}$ selection. Each distribution is normalized to integrate to one in $R_{L}$ prior to shifting.

Corrected distributions of the charge-selected EEC compared with the inclusive case for $R_{\rm jet}$ = 0.6 with a jet transverse momentum selection of 20 $ < p_{\rm T, jet} <$ 30 GeV/c.

Corrected distributions of the EEC charged ratio for $R_{\rm jet}$ = 0.6 with a jet transverse momentum selection of 20 $ < p_{\rm T, jet} <$ 30 GeV/c.

Corrected distributions of the normalized EEC differential in $R_{L}$ for $R_{\rm jet}=$ 0.4, with jet transverse momentum selections 15 $< p_{\rm T, jet} <$ 20 GeV/c and 30 $< p_{\rm T, jet} <$ 50 GeV/c

Corrected distributions of the normalized EEC within jets, differential in $ \left\langle p_{\rm T,jet} \right\rangle R_{L} $ at $R_{\rm jet} =$ 0.4 for one $p_{\rm T, jet}$ selection. Each distribution is normalized to integrate to one in $R_{L}$ prior to shifting.

Corrected distributions of the normalized EEC within jets, differential in $ \left\langle p_{\rm T,jet} \right\rangle R_{L} $ at $R_{\rm jet} =$ 0.4 for one $p_{\rm T, jet}$ selection. Each distribution is normalized to integrate to one in $R_{L}$ prior to shifting.

Corrected distributions of the normalized EEC within jets, differential in $ \left\langle p_{\rm T,jet} \right\rangle R_{L} $ at $R_{\rm jet} =$ 0.4 for one $p_{\rm T, jet}$ selection. Each distribution is normalized to integrate to one in $R_{L}$ prior to shifting.

Corrected distributions of the charge-selected EEC compared with the inclusive case for $R_{\rm jet}$ = 0.4 with a jet transverse momentum selection of 20 $ < p_{\rm T, jet} <$ 30 GeV/c.

Corrected distributions of the EEC charged ratio for $R_{\rm jet}$ = 0.4 with a jet transverse momentum selection of 20 $ < p_{\rm T, jet} <$ 30 GeV/c.

Observed two-dimensional likelihood scans for $c_{Hq}^{(1)}$ vs. $c_{Hq}^{(3)}$ while other coefficients are fixed at their SM values.

Observed two-dimensional likelihood scans for $c_{Hq}^{(1)}$ vs. $c_{Hu}$ while allowing the other coefficients to float freely at each point of the sca.

Observed two-dimensional likelihood scans for $c_{Hq}^{(1)}$ vs. $c_{Hu}$ while other coefficients are fixed at their SM values.

Observed two-dimensional likelihood scans for $c_{Hq}^{(1)}$ vs. $c_{Hd}$ while allowing the other coefficients to float freely at each point of the sca.

Observed two-dimensional likelihood scans for $c_{Hq}^{(1)}$ vs. $c_{Hd}$ while other coefficients are fixed at their SM values.

Observed two-dimensional likelihood scans for $c_{Hq}^{(3)}$ vs. $c_{Hu}$ while allowing the other coefficients to float freely at each point of the sca.

Observed two-dimensional likelihood scans for $c_{Hq}^{(3)}$ vs. $c_{Hu}$ while other coefficients are fixed at their SM values.

Observed two-dimensional likelihood scans for $c_{Hq}^{(3)}$ vs. $c_{Hd}$ while allowing the other coefficients to float freely at each point of the sca.

Observed two-dimensional likelihood scans for $c_{Hq}^{(3)}$ vs. $c_{Hd}$ while other coefficients are fixed at their SM values.

Observed two-dimensional likelihood scans for $c_{Hu}$ vs. $c_{Hd}$ while allowing the other coefficients to float freely at each point of the sca.

Observed two-dimensional likelihood scans for $c_{Hu}$ vs. $c_{Hd}$ while other coefficients are fixed at their SM values.

Observed two-dimensional likelihood scans for $c_{Hq}^{(1)}$ vs. $g^{(2)}_{ZZ}$ while allowing the other coefficients to float freely at each point of the sca.

Observed two-dimensional likelihood scans for $c_{Hq}^{(1)}$ vs. $g^{(2)}_{ZZ}$ while other coefficients are fixed at their SM values.

Observed two-dimensional likelihood scans for $c_{Hq}^{(3)}$ vs. $g^{(2)}_{ZZ}$ while allowing the other coefficients to float freely at each point of the sca.

Observed two-dimensional likelihood scans for $c_{Hq}^{(3)}$ vs. $g^{(2)}_{ZZ}$ while other coefficients are fixed at their SM values.

Observed two-dimensional likelihood scans for $c_{Hu}$ vs. $g^{(2)}_{ZZ}$ while allowing the other coefficients to float freely at each point of the sca.

Observed two-dimensional likelihood scans for $c_{Hu}$ vs. $g^{(2)}_{ZZ}$ while other coefficients are fixed at their SM values.

Observed two-dimensional likelihood scans for $c_{Hq}^{(1)}$ vs. $g^{(4)}_{ZZ}$ while allowing the other coefficients to float freely at each point of the sca.

Observed two-dimensional likelihood scans for $c_{Hq}^{(1)}$ vs. $g^{(4)}_{ZZ}$ while other coefficients are fixed at their SM values.

Observed two-dimensional likelihood scans for $c_{Hq}^{(3)}$ vs. $g^{(4)}_{ZZ}$ while allowing the other coefficients to float freely at each point of the sca.

Observed two-dimensional likelihood scans for $c_{Hq}^{(3)}$ vs. $g^{(4)}_{ZZ}$ while other coefficients are fixed at their SM values.

Observed two-dimensional likelihood scans for $c_{Hu}$ vs. $g^{(4)}_{ZZ}$ while allowing the other coefficients to float freely at each point of the sca.

Observed two-dimensional likelihood scans for $c_{Hu}$ vs. $g^{(4)}_{ZZ}$ while other coefficients are fixed at their SM values.

Observed two-dimensional likelihood scans for $c_{Hd}$ vs. $g^{(2)}_{ZZ}$ while allowing the other coefficients to float freely at each point of the sca.

Observed two-dimensional likelihood scans for $c_{Hd}$ vs. $g^{(2)}_{ZZ}$ while other coefficients are fixed at their SM values.

Observed two-dimensional likelihood scans for $c_{Hd}$ vs. $g^{(4)}_{ZZ}$ while allowing the other coefficients to float freely at each point of the sca.

Observed two-dimensional likelihood scans for $c_{Hd}$ vs. $g^{(4)}_{ZZ}$ while other coefficients are fixed at their SM values.

Observed two-dimensional likelihood scans for $g^{(2)}_{ZZ}$ vs. $g^{(4)}_{ZZ}$ while allowing the other coefficients to float freely at each point of the sca.

Observed two-dimensional likelihood scans for $g^{(2)}_{ZZ}$ vs. $g^{(4)}_{ZZ}$ while other coefficients are fixed at their SM values.

Tuned intrinsic kT parameters ShowerHandler:IntrinsicPtGaussian in Herwig with the underlying-event tune CH2 at nucleon-nucleon center-of-mass energy from 38.8 GeV to 13 TeV.

Tuned intrinsic kT parameters ShowerHandler:IntrinsicPtGaussian in Herwig with the underlying-event tune CH3 at nucleon-nucleon center-of-mass energy from 38.8 GeV to 13 TeV.

Tuned intrinsic kT parameters BeamRemnants:PrimordialkThard in Pythia with the underlying-event tune CP5 and ISR starting scale SpaceShower:pT0Ref = 1 GeV at nucleon-nucleon center-of-mass energy from 38.8 GeV to 13 TeV.

Tuned intrinsic kT parameters ShowerHandler:IntrinsicPtGaussian in Herwig with the underlying-event tune CH3 and ISR starting scale SudakovCommon:pTmin=0.7 GeV at nucleon-nucleon center-of-mass energy from 38.8 GeV to 13 TeV.

Tuned intrinsic kT parameters BeamRemnants:PrimordialkThard in Pythia with the underlying-event tune CP5 at proton-proton center-of-mass energy 38.8 GeV versus the dilepton mass range of the process.

Tuned intrinsic kT parameters BeamRemnants:PrimordialkThard in Pythia with the underlying-event tune CP5 at proton-proton center-of-mass energy 8000 GeV versus the dilepton mass range of the process.

Tuned intrinsic kT parameters BeamRemnants:PrimordialkThard in Pythia with the underlying-event tune CP5 at proton-nucleon center-of-mass energy 8160 GeV versus the dilepton mass range of the process.

Tuned intrinsic kT parameters BeamRemnants:PrimordialkThard in Pythia with the underlying-event tune CP5 at proton-nucleon center-of-mass energy 13000 GeV versus the dilepton mass range of the process.

Tuned intrinsic kT parameters ShowerHandler:IntrinsicPtGaussian in Herwig with the underlying-event tune CH2 at proton-proton center-of-mass energy 38.8 GeV versus the dilepton mass range of the process.

Tuned intrinsic kT parameters ShowerHandler:IntrinsicPtGaussian in Herwig with the underlying-event tune CH2 at proton-proton center-of-mass energy 8000 GeV versus the dilepton mass range of the process.

Tuned intrinsic kT parameters ShowerHandler:IntrinsicPtGaussian in Herwig with the underlying-event tune CH2 at proton-nucleon center-of-mass energy 8160 GeV versus the dilepton mass range of the process.

Tuned intrinsic kT parameters ShowerHandler:IntrinsicPtGaussian in Herwig with the underlying-event tune CH2 at proton-proton center-of-mass energy 13000 GeV versus the dilepton mass range of the process.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters among various generator settings at proton-proton center-of-mass energy 38.8 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters among various generator settings at proton-proton center-of-mass energy 62 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters among various generator settings at proton-proton center-of-mass energy 200 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters among various generator settings at proton-anti-proton center-of-mass energy 1800 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters among various generator settings at proton-anti-proton center-of-mass energy 1960 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters among various generator settings at proton-proton center-of-mass energy 2760 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters among various generator settings at proton-proton center-of-mass energy 8000 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters among various generator settings at proton-nucleon center-of-mass energy 8160 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters among various generator settings at proton-proton center-of-mass energy 13000 GeV when fitting to the CMS measurement.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters among various generator settings at proton-proton center-of-mass energy 13000 GeV when fitting to the LHCb measurement.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters between the two generator settings of Pythia at proton-proton center-of-mass energy 38.8 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters between the two generator settings of Pythia at proton-proton center-of-mass energy 62 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters between the two generator settings of Pythia at proton-proton center-of-mass energy 200 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters between the two generator settings of Pythia at proton-anti-proton center-of-mass energy 1800 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters between the two generator settings of Pythia at proton-anti-proton center-of-mass energy 1960 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters between the two generator settings of Pythia at proton-proton center-of-mass energy 2760 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters between the two generator settings of Pythia at proton-proton center-of-mass energy 8000 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters between the two generator settings of Pythia at proton-nucleon center-of-mass energy 8160 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters between the two generator settings of Pythia at proton-proton center-of-mass energy 13000 GeV when fitting to the CMS measurement.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters between the two generator settings of Pythia at proton-proton center-of-mass energy 13000 GeV when fitting to the LHCb measurement.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters between the two generator settings of Herwig at proton-proton center-of-mass energy 38.8 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters between the two generator settings of Herwig at proton-proton center-of-mass energy 62 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters between the two generator settings of Herwig at proton-proton center-of-mass energy 200 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters between the two generator settings of Herwig at proton-anti-proton center-of-mass energy 1800 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters between the two generator settings of Herwig at proton-anti-proton center-of-mass energy 1960 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters between the two generator settings of Herwig at proton-proton center-of-mass energy 2760 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters between the two generator settings of Herwig at proton-proton center-of-mass energy 8000 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters between the two generator settings of Herwig at proton-nucleon center-of-mass energy 8160 GeV.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters between the two generator settings of Herwig at proton-proton center-of-mass energy 13000 GeV when fitting to the CMS measurement.

Covariance of the data uncertainty contribution to the tuned intrinsic kT parameters between the two generator settings of Herwig at proton-proton center-of-mass energy 13000 GeV when fitting to the LHCb measurement.

The model-independent 95\% \CL expected and observed upper limits set on ${\sigma(\PP\to 2\Pa+\PX)\mathcal{B}^2(\Pa\to 2\PGm)\alphaGen}$ over the range $0.21 < \MPa < 9\GeV$ for the combined 2016, 2017, and 2018 analyses. Mass ranges that overlap with \JPsi and \PgU resonances are excluded from the search

The 95\% \CL observed upper limits on the effective coupling $\CahLambda$ of the ALP to the SM Higgs assuming the branching fraction of the ALP to muons is 1 (blue) and 0.1 (orange), for both the expected (dashed) and observed (solid) limits

The 95\% \CL observed upper limits on the effective coupling $\cll/\Lambda$ of the ALP to the SM leptons. The orange shaded region represents the parameter space excluded by this search under three choices of $\CahLambda$ $1\TeV^{-2}$ (solid), $0.1\TeV^{-2}$ (dashed), and $0.01\TeV^{-2}$ (dotted)

The 95\% \CL observed upper limits on $\varepsilon^{2} \mathcal{B}(\ZDark \to \sDark \overline{\sDark}) \mathcal{B}^{2}(\sDark \rightarrow 2\PGm)$ for the vector portal model as a function of the dark scalar mass $\MsDark$ and dark vector boson mass $\MZDark$. The yellow and green bands indicate one and two standard deviation values of the limit, respectively. Because the model-independent limits are calculated only up to a dimuon mass of 60\GeV, the \sDark mass considered for these limits is below 60\GeV

The 95\% \CL observed upper limits for $\sigma(\PP\to\PhOneTwo\to 2\PaOne) \mathcal{B}^2(\PaOne\to 2\PGm)$ for the NMSSM as a function of $\MPaOne$ for $\MPhOneTwo$ = 90~GEV. The data presented here reflect the results of the 2017 and 2018 datasets combined with the previously published results of the 2016 dataset in \cite{CMS:2018jid}

The 95\% \CL observed upper limits for $\sigma(\PP\to\PhOneTwo\to 2\PaOne) \mathcal{B}^2(\PaOne\to 2\PGm)$ for the NMSSM as a function of $\MPaOne$ for $\MPhOneTwo$ = 125~GEV. The data presented here reflect the results of the 2017 and 2018 datasets combined with the previously published results of the 2016 dataset in \cite{CMS:2018jid}

The 95\% \CL observed upper limits for $\sigma(\PP\to\PhOneTwo\to 2\PaOne) \mathcal{B}^2(\PaOne\to 2\PGm)$ for the NMSSM as a function of $\MPaOne$ for $\MPhOneTwo$ = 150~GEV. The data presented here reflect the results of the 2017 and 2018 datasets combined with the previously published results of the 2016 dataset in \cite{CMS:2018jid}

The 95\% \CL observed upper limits (black solid curves) from this search as interpreted in the dark SUSY scenario for the process $\PP \to \Ph \to 2\nOne \to 2\gammaDark + 2\nDark \to 4\PGm + \PX$, with \mbox{$\MnOne = 60\GeV$} and $\MnDark = 1\GeV$. The limits are presented in the plane of $\varepsilon$ and $\MgammaDark$. The color gradient represents different branching fraction assumptions for \mbox{$\mathcal{B}(\Ph \to 2\nOne \to 2\gammaDark + 2\nDark)$}, ranging from dark orange (0.05\%) to light orange (10\%). The degradation of the limit around 1\GeV is attributed to the drop in the dimuon branching fraction $\mathcal{B}(\gammaDark \to 2\mu)$ due to the dimuon resonance of the $\phi$ meson~\cite{Batell:2009yf}

non prompt $\psi(2S)$ $\lambda_\theta$