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.

Results for the $P_3$ angular observable. The first uncertainties are statistical and the second systematic.

Results for the $P_4^\prime$ angular observable. The first uncertainties are statistical and the second systematic.

Results for the $P_5^\prime$ angular observable. The first uncertainties are statistical and the second systematic.

Results for the $P_6^\prime$ angular observable. The first uncertainties are statistical and the second systematic.

Results for the $P_8^\prime$ angular observable. The first uncertainties are statistical and the second systematic.

Results for the CP averaged observables $F_L$ and $P_1$–$P_8^\prime$. The first uncertainties are statistical and the second systematic.

Correlation matrix of angular observables Fl and P1–P8', considering only the statistical uncertainties from the maximum-likelihood fit in the interval 1.1 < $q^2$ < 2 GeV$^2$

Correlation matrix of angular observables Fl and P1–P8', considering only the statistical uncertainties from the maximum-likelihood fit in the interval 2 < $q^2$ < 4.3 GeV$^2$

Correlation matrix of angular observables Fl and P1–P8', considering only the statistical uncertainties from the maximum-likelihood fit in the interval 4.3 < $q^2$ < 6 GeV$^2$

Correlation matrix of angular observables Fl and P1–P8', considering only the statistical uncertainties from the maximum-likelihood fit in the interval 6 < $q^2$ < 8.68 GeV$^2$

Correlation matrix of angular observables Fl and P1–P8', considering only the statistical uncertainties from the maximum-likelihood fit in the interval 10.09 < $q^2$ < 12.86 GeV$^2$

Correlation matrix of angular observables Fl and P1–P8', considering only the statistical uncertainties from the maximum-likelihood fit in the interval 14.18 < $q^2$ < 16 GeV$^2$

Distributions in $m_{Z'}^{rec}$ for data in the SRs, together with fits of the background functions under the background-only hypothesis for the electron channel. The number of observed events in each bin is divided by the bin width. The signal predictions are shown for different Z' boson masses, normalized to an arbitrary cross section of 1 fb. In the panels below the distributions, the ratios of data to the background function are displayed. The shaded green areas represent the statistical uncertainty from the fit. The $\chi^2$ values per number of degrees of freedom ($\chi^2$/n.d.f.) and the corresponding $p$-values are provided for each fit.

Expected upper limits at 95% CL on the product of the production cross section and the branching fraction as a function of the Z' boson mass.Each line corresponds to the three different final states and their combined result.

Expected and observed upper limits at 95% CL on the product of the production cross section and the branching fraction as functions of the Z' boson mass from the combination of all final states. The limits are compared with the predictions of the HVT model and the expected limits (shown by red curves) from a previous analysis.

Prediction from the HVT model.

Observed upper limits at 95% CL on gF for different Z' boson masses as functions of the product of $g_{H}$ with the sign of $g_{F}$. The two benchmark scenarios of the HVT model are shown by the black markers.

Differential cross section of tZq as a function of the transverse momentum of the lepton coming from the W boson decay. The overflow is included in the last bin.

Differential cross section of ttZ+tWZ as a function of the azimuthal angle between the two leptons coming from the Z boson. The overflow is included in the last bin.

Differential cross section of tZq as a function of the azimuthal angle between the two leptons coming from the Z boson. The overflow is included in the last bin.

Differential cross section of ttZ+tWZ as a function of the $\Delta$R between the Z boson and the lepton coming from the W boson. The overflow is included in the last bin.

Differential cross section of tZq as a function of the $\Delta$R between the Z boson and the lepton coming from the W boson. The overflow is included in the last bin.

Differential cross section of ttZ+tWZ as a function of the cosine of the polar angle between the Z boson and the negatively charged lepton coming from its decay, boosted into the Z boson restframe.

Differential cross section of tZq as a function of the cosine of the polar angle between the Z boson and the negatively charged lepton coming from its decay, boosted into the Z boson restframe.

Normalized differential cross section of ttZ+tWZ as a function of the transverse momentum of the Z boson. The overflow is included in the last bin.

Normalized differential cross section of tZq as a function of the transverse momentum of the Z boson. The overflow is included in the last bin.

Normalized differential cross section of ttZ+tWZ as a function of the transverse momentum of the lepton coming from the W boson decay. The overflow is included in the last bin.

Normalized differential cross section of tZq as a function of the transverse momentum of the lepton coming from the W boson decay. The overflow is included in the last bin.

Normalized differential cross section of ttZ+tWZ as a function of the azimuthal angle between the two leptons coming from the Z boson. The overflow is included in the last bin.

Normalized differential cross section of tZq as a function of the azimuthal angle between the two leptons coming from the Z boson. The overflow is included in the last bin.

Normalized differential cross section of ttZ+tWZ as a function of the $\Delta$R between the Z boson and the lepton coming from the W boson. The overflow is included in the last bin.

Normalized differential cross section of tZq as a function of the $\Delta$R between the Z boson and the lepton coming from the W boson. The overflow is included in the last bin.

Normalized differential cross section of ttZ+tWZ as a function of the cosine of the polar angle between the Z boson and the negatively charged lepton coming from its decay, boosted into the Z boson restframe.

Normalized differential cross section of tZq as a function of the cosine of the polar angle between the Z boson and the negatively charged lepton coming from its decay, boosted into the Z boson restframe.

Covariance matrix for the differential cross sections as a function of the transverse momentum of the Z boson.

Covariance matrix for the differential cross sections as a function of the transverse momentum of the lepton coming from the W boson decay.

Covariance matrix for the differential cross sections as a function of the $\Delta$R between the Z boson and the lepton coming from the W boson.

Covariance matrix for the differential cross sections as a function of the azimuthal angle between the two leptons coming from the Z boson.

Covariance matrix for the differential cross sections as a function of the cosine of the polar angle between the Z boson and the negatively charged lepton coming from its decay, boosted into the Z boson restframe.

Distributions for data and expected signal and background contributions of the MVA score for the µ + jets channel in the 3j1b category, before the maximum likelihood fit. The vertical error bars represent the statistical uncertainty in the data, and the shaded band the uncertainty in the prediction. All uncertainties considered in the analysis are included in the uncertainty band. The lower panels show the data-to-prediction ratio. The first and last bins in each distribution include underflow and overflow events, respectively.

Observed and predicted number of events in each of the eight categories of the signal region, before the maximum likelihood fit. The vertical error bars represent the statistical uncertainty in the data, and the shaded band the uncertainty in the prediction. All uncertainties considered in the analysis are included in the uncertainty band. The lower panels show the data-to-prediction ratio.

Distributions for the e + jets final state before the maximum likelihood fit, MVA score bins for the 3j1b category and ∆R med ( j, j 0 ) bins for the other categories. The vertical error bars represent the statistical uncertainty in the data, and the shaded band the uncertainty of the prediction. All uncertainties considered in the analysis are included in the uncertainty band. The lower panels show the data-to-simulation ratio, where the simulations are adjusted according to their normalization before the fit. The first and last bins in each distribution include underflow and overflow events, respectively.

Distributions for the e + jets final state after the maximum likelihood fit, MVA score bins for the 3j1b category and ∆R med ( j, j 0 ) bins for the other categories. The vertical error bars represent the statistical uncertainty in the data, and the shaded band the uncertainty of the prediction. All uncertainties considered in the analysis are included in the uncertainty band. The lower panels show the data-to-simulation ratio, where the simulations are adjusted according to their normalization after the fit. The first and last bins in each distribution include underflow and overflow events, respectively.

Distributions for the µ + jets final state before the maximum likelihood fit, MVA score bins for the 3j1b category and ∆R med ( j, j 0 ) bins for the other categories. The vertical error bars represent the statistical uncertainty in the data, and the shaded band the uncertainty of the prediction. All uncertainties considered in the analysis are included in the uncertainty band. The lower panels show the data-to-simulation ratio, where the simulations are adjusted according to their normalization before the fit. The first and last bins in each distribution include underflow and overflow events, respectively.

Distributions for the µ + jets final state after the maximum likelihood fit, MVA score bins for the 3j1b category and ∆R med ( j, j 0 ) bins for the other categories. The vertical error bars represent the statistical uncertainty in the data, and the shaded band the uncertainty of the prediction. All uncertainties considered in the analysis are included in the uncertainty band. The lower panels show the data-to-simulation ratio, where the simulations are adjusted according to their normalization after the fit. The first and last bins in each distribution include underflow and overflow events, respectively.

Covariance matrix for the lepton+jets ML fit.

Covariance matrix for the combination ML fit.

Distributions in $S_T$ in the SR for the electron channel, after a background-only fit to the data. The signal distributions are scaled to the cross section predicted by the theory. The hatched bands show the post-fit uncertainty band, combining all sources of uncertainty. The ratio of data to the background predictions is shown in the panels below the distributions.

The $G_{\text{i}}^{\text{Strips}}$ distribution in the PASS region for events passing the event selection and with $55 < p_{\mathrm{T}} < 200$ GeV.

The $G_{\text{i}}^{\text{Strips}}$ distribution in the FAIL region for events passing the event selection and with $p_{\mathrm{T}} > 200$ GeV.

The $G_{\text{i}}^{\text{Strips}}$ distribution in the PASS region for events passing the event selection and with $p_{\mathrm{T}} > 200$ GeV.

Mass spectrum predicted in the signal region defined by $G_{\text{i}}^{\text{Strips}} > 0.22$ and $p_{\mathrm{T}} > 70$ GeV.

Cross section limits for gluino and supersymmetric top R-hadrons for both background prediction methods.

Cross section limits for supersymmetric tau models for both background prediction methods.

Cross section limits for DY-produced tau prime models (single and multicharged) for both background prediction methods.

Cross section limits for Z prime to multicharged tau prime model for both background prediction methods. All Z prime models assume a narrow width, and a 100% branching fraction to 600 GeV tau primes.

2D exclusion showing the observed cross section limit as a function of the multicharged tau prime mass and Z prime mass for the ionization method.

2D exclusion showing the observed cross section limit as a function of the multicharged tau prime mass and Z prime mass for the mass method.

Cumulative selection efficiency for the data and for two signal hypotheses.

Expected and observed mass limits obtained using 2017-2018 data for various HSCP candidate models,for the two background estimate methods.

Mass windows used in the mass method as a function of the signal target mass for the signal samples assuming a charge of $1e$ and $2e$, as appropriate to the signal model.

Mass spectrum predicted in the validation region defined by $0.018 < G_{\text{i}}^{\text{Strips}} < 0.057$ and $p_{\mathrm{T}} > 70$ GeV. The thresholds used in the $G_{\text{i}}^{\text{Strips}}$ requirement represent the 50% and 90% quantile of the distribution.

Trigger efficiency for the $\tilde{g}$ signals as a function of $\beta$ for $\text{abs(}\eta\text{)}<0.3$. The up and down variations are conservatively estimated assuming a delay of 1.5 ns in the muon chambers (equivalent to the time resolution of the chambers) and are used to evaluate the signal systematic uncertainties.

Trigger efficiency for the $\tilde{g}$ signals as a function of $\beta$ for $0.3<\text{abs(}\eta\text{)}<0.6$. The up and down variations are conservatively estimated assuming a delay of 1.5 ns in the muon chambers (equivalent to the time resolution of the chambers) and are used to evaluate the signal systematic uncertainties.

Trigger efficiency for the $\tilde{g}$ signals as a function of $\beta$ for $0.6<\text{abs(}\eta\text{)}<0.9$. The up and down variations are conservatively estimated assuming a delay of 1.5 ns in the muon chambers (equivalent to the time resolution of the chambers) and are used to evaluate the signal systematic uncertainties.

Trigger efficiency for the $\tilde{g}$ signals as a function of $\beta$ for $0.9<\text{abs(}\eta\text{)}<1.2$. The up and down variations are conservatively estimated assuming a delay of 1.5 ns in the muon chambers (equivalent to the time resolution of the chambers) and are used to evaluate the signal systematic uncertainties.

Trigger efficiency for the $\tilde{g}$ signals as a function of $\beta$ for $1.2<\text{abs(}\eta\text{)}<2.1$. The up and down variations are conservatively estimated assuming a delay of 1.5 ns in the muon chambers (equivalent to the time resolution of the chambers) and are used to evaluate the signal systematic uncertainties.

Trigger efficiency for the $\tilde{g}$ signals as a function of $\beta$ for $2.1<\text{abs(}\eta\text{)}<2.4$. The up and down variations are conservatively estimated assuming a delay of 1.5 ns in the muon chambers (equivalent to the time resolution of the chambers) and are used to evaluate the signal systematic uncertainties.

Trigger efficiency for the $\tilde{\tau}$ signals as a function of $\beta$ for $\text{abs(}\eta\text{)}<0.3$. The up and down variations are conservatively estimated assuming a delay of 1.5 ns in the muon chambers (equivalent to the time resolution of the chambers) and are used to evaluate the signal systematic uncertainties.

Trigger efficiency for the $\tilde{\tau}$ signals as a function of $\beta$ for $0.3<\text{abs(}\eta\text{)}<0.6$. The up and down variations are conservatively estimated assuming a delay of 1.5 ns in the muon chambers (equivalent to the time resolution of the chambers) and are used to evaluate the signal systematic uncertainties.

Trigger efficiency for the $\tilde{\tau}$ signals as a function of $\beta$ for $0.6<\text{abs(}\eta\text{)}<0.9$. The up and down variations are conservatively estimated assuming a delay of 1.5 ns in the muon chambers (equivalent to the time resolution of the chambers) and are used to evaluate the signal systematic uncertainties.

Trigger efficiency for the $\tilde{\tau}$ signals as a function of $\beta$ for $0.9<\text{abs(}\eta\text{)}<1.2$. The up and down variations are conservatively estimated assuming a delay of 1.5 ns in the muon chambers (equivalent to the time resolution of the chambers) and are used to evaluate the signal systematic uncertainties.

Trigger efficiency for the $\tilde{\tau}$ signals as a function of $\beta$ for $1.2<\text{abs(}\eta\text{)}<2.1$. The up and down variations are conservatively estimated assuming a delay of 1.5 ns in the muon chambers (equivalent to the time resolution of the chambers) and are used to evaluate the signal systematic uncertainties.

Trigger efficiency for the $\tilde{\tau}$ signals as a function of $\beta$ for $2.1<\text{abs(}\eta\text{)}<2.4$. The up and down variations are conservatively estimated assuming a delay of 1.5 ns in the muon chambers (equivalent to the time resolution of the chambers) and are used to evaluate the signal systematic uncertainties.

Trigger efficiency as a function of $\beta$, for the $\tilde{g}$ signals.

Trigger efficiency as a function of $\beta$, for the $\tilde{\tau}$ signals.

Cross section limits for $\tilde{g}$ R-hadrons obtained with the ionization method.

Cross section limits for $\tilde{g}$ R-hadrons obtained with the mass method.

Cross section limits for $\tilde{t}$ R-hadrons obtained with the ionization method.

Cross section limits for $\tilde{t}$ R-hadrons obtained with the mass method.

Cross section limits for $\tilde{\tau}$ obtained with the ionization method.

Cross section limits for $\tilde{\tau}$ obtained with the mass method.

Cross section limits for $\tilde{\tau}$ production within the GMSB SPS7 modelobtained with the ionization method.

Cross section limits for $\tilde{\tau}$ production within the GMSB SPS7 model obtained with the mass method.

Cross section limits for DY-produced $\tau'$ with $abs(Q) = 1e$ with the ionization method.

Cross section limits for DY-produced $\tau'$ with $abs(Q) = 1e$ with the mass method.

Cross section limits for DY-produced $\tau'$ with $abs(Q) = 2e$ with the ionization method.

Cross section limits for DY-produced $\tau'$ with $abs(Q) = 2e$ with the mass method.

Cross section limits for the production of $Z'$ boson decaying into a pair of $\tau'$ fermions of charge $2e$ (with a branching fraction equal to 1 and a fixed $\tau'$ mass of 600 GeV), obtained with the ionization method.

Cross section limits for the production of $Z'$ boson decaying into a pair of $\tau'$ fermions of charge $2e$ (with a branching fraction equal to 1 and a fixed $\tau'$ mass of 600 GeV), obtained with the mass method.

Two-dimensional exclusion showing the observed cross section limit as a function of the masses of the $\tau'$ (on the $x$ axis) and of the $Z'$ boson (on the $y$ axis), for the ionization method.

Two-dimensional exclusion showing the observed cross section limit as a function of the masses of the $\tau'$ (on the $x$ axis) and of the $Z'$ boson (on the $y$ axis), for the mass method.

Expected background yield, expected signal yield, and observed data for the mass method for 2017.

Expected background yield, expected signal yield, and observed data for the mass method for 2018.

Selection efficieny for GMSB supersymmetric $\tau$.

Selection efficiency for gluino R-hardon samples.

Selection efficiency for supersymmetric top R-hadrons.

Selection efficiency for pair-produced supersymmetric $\tau$.

Selection efficiency for $\tau'$ with $|Q| = 1e$.

Selection efficiecny for $\tau'$ with $|Q| = 2e$.

Selection efficiency for $Z'$ (mass = 3 TeV) going to $\tau'$ with $|Q| = 2e$.

Selection efficiency for $Z'$ (mass 5 TeV) goes to $\tau'$ with $|Q| = 2e$.

Selection efficiency for $Z'$ going to $\tau'$ (mass 600 GeV) with $|Q| = 2e$.

Selection efficiency for $Z'$ going to $\tau'$ (mass 1 TeV) with charge $|Q| = 2e$.

Observed and expected 68% and 95% confidence intervals on the Wilson coefficients associated with the EFT dimension-8 operators.

Observed (black) and expected (red) 68% (solid) and 95% (dashed) CL contours for the negative logarithm of 2D likelihood as functions of the reported dim-6 bosonic (or mixed) Wilson coefficient pairs, specifically for c_{HW} and f_{M0}.

Observed (black) and expected (red) 68% (solid) and 95% (dashed) CL contours for the negative logarithm of 2D likelihood as functions of the reported dim-6 bosonic (or mixed) Wilson coefficient pairs, specifically for c_{HW} and c_{Hbox}.

Observed (black) and expected (red) 68% (solid) and 95% (dashed) CL contours for the negative logarithm of 2D likelihood as functions of the reported dim-6 bosonic (or mixed) Wilson coefficient pairs, specifically for c_{Hl3} and c_{Hq3}.

Observed (black) and expected (red) 68% (solid) and 95% (dashed) CL contours for the negative logarithm of 2D likelihood as functions of the reported dim-6 bosonic (or mixed) Wilson coefficient pairs, specifically for c_{HW} and f_{T0}.

Observed (black) and expected (red) 68% (solid) and 95% (dashed) CL contours for the negative logarithm of 2D likelihood as functions of the reported dim-6 bosonic (or mixed) Wilson coefficient pairs, specifically for c_{HW} and f_{S0}.

Observed (black) and expected (red) 68% (solid) and 95% (dashed) CL contours for the negative logarithm of 2D likelihood as functions of the reported dim-6 bosonic (or mixed) Wilson coefficient pairs, specifically for c_{HW} and c_{HWB}.

Observed (black) and expected (red) 68% (solid) and 95% (dashed) CL contours for the negative logarithm of 2D likelihood as functions of the reported dim-6 bosonic (or mixed) Wilson coefficient pairs, specifically for c_{Hq1} and c_{Hq3}.

Observed (black) and expected (red) 68% (solid) and 95% (dashed) CL contours for the negative logarithm of 2D likelihood as functions of the reported dim-6 bosonic (or mixed) Wilson coefficient pairs, specifically for c_{Hbox} and f_{S0}.

Observed (black) and expected (red) 68% (solid) and 95% (dashed) CL contours for the negative logarithm of 2D likelihood as functions of the reported dim-6 bosonic (or mixed) Wilson coefficient pairs, specifically for c_{W} and c_{HW}.

Observed (black) and expected (red) 68% (solid) and 95% (dashed) CL contours for the negative logarithm of 2D likelihood as functions of the reported dim-6 bosonic (or mixed) Wilson coefficient pairs, specifically for c_{W} and f_{T0}.

Observed (black) and expected (red) 68% (solid) and 95% (dashed) CL contours for the negative logarithm of 2D likelihood as functions of the reported dim-6 bosonic (or mixed) Wilson coefficient pairs, specifically for c_{W} and f_{M0}.

Observed (black) and expected (red) 68% (solid) and 95% (dashed) CL contours for the negative logarithm of 2D likelihood as functions of the reported dim-6 bosonic (or mixed) Wilson coefficient pairs, specifically for c_{W} and c_{Hbox}.

Observed (black) and expected (red) 68% (solid) and 95% (dashed) CL contours for the negative logarithm of 2D likelihood as functions of the reported dim-6 bosonic (or mixed) Wilson coefficient pairs, specifically for c_{Hbox} and c_{HDD}.

Observed (black) and expected (red) 68% (solid) and 95% (dashed) CL contours for the negative logarithm of 2D likelihood as functions of the reported dim-6 bosonic (or mixed) Wilson coefficient pairs, specifically for c_{HW} and c_{HDD}.

Observed (black) and expected (red) 68% (solid) and 95% (dashed) CL contours for the negative logarithm of 2D likelihood as functions of the reported dim-6 bosonic (or mixed) Wilson coefficient pairs, specifically for c_{W} and f_{S0}.

Observed (black) and expected (red) 68% (solid) and 95% (dashed) CL contours for the negative logarithm of 2D likelihood as functions of the reported dim-6 bosonic (or mixed) Wilson coefficient pairs, specifically for c_{Hbox} and f_{T0}.

Observed (black) and expected (red) 68% (solid) and 95% (dashed) CL contours for the negative logarithm of 2D likelihood as functions of the reported dim-6 bosonic (or mixed) Wilson coefficient pairs, specifically for c_{HWB} and c_{Hbox}.

Observed (black) and expected (red) 68% (solid) and 95% (dashed) CL contours for the negative logarithm of 2D likelihood as functions of the reported dim-6 bosonic (or mixed) Wilson coefficient pairs, specifically for c_{Hl3} and c_{Hq1}.

Observed (black) and expected (red) 68% (solid) and 95% (dashed) CL contours for the negative logarithm of 2D likelihood as functions of the reported dim-6 bosonic (or mixed) Wilson coefficient pairs, specifically for c_{Hbox} and f_{M0}.

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.