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.

Invariant mass distribution of final state particles in SR1 HF category ($\text{H}\to\text{J}/\psi\gamma$ signal)

Invariant mass distribution of final state particles in SR1 Z-LP category ($\text{Z}\to\text{J}/\psi\gamma$ signal)

Invariant mass distribution of final state particles in SR1 Z-HP category ($\text{Z}\to\text{J}/\psi\gamma$ signal)

Invariant mass distribution of final state particles in SR2 category ($\text{H}\to\psi(\text{2S})\gamma$ signal)

Invariant mass distribution of final state particles in SR2 category ($\text{H}\to\psi(\text{2S})\gamma$ signal)

Invariant mass distribution of final state particles in control region category ($\text{H}\to\mu\mu\gamma$ background)

Observed and expected (with $\pm 1$, $\pm 2$ standard deviation bands) exclusion limits at 95% C.L. on the branching fraction $\mathcal{B}$ of the $(\text{H,Z}) \to \psi(\text{nS})\gamma$ decays

Observed (expected) upper limits at 95% C.L. on the normalized values with respect to the SM expectation, denoted as the signal strength parameter $\mu$, of the product of the cross section $\sigma$ and the branching fraction $\mathcal{B}$ of the $(\text{H,Z}) \to \psi(\text{nS})\gamma$ decays, and the branching fraction, assuming a SM Z and H boson cross section.

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.

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}.

Observed profile likelihood projection on mH, for the 2e2mu final state, using the N-2D′ VXBS approach. Both statistical and systematic uncertainties have been considered.

Observed profile likelihood projection on mH, for the 2mu2e final state, using the N-2D′ VXBS approach. Both statistical and systematic uncertainties have been considered.

Result of the Higgs boson width measurement using the on-shell production only, shown as 1 − CL curve extracted using the Feldman–Cousins approach (black dots). The error bars represent the spread of the simulated experiments for each point.

Observed profile likelihood projections from the Higgs boson width fit using the full combination of H → ZZ → 4l with the off-shell H → ZZ → 2l2nu [Nature Phys. 18 (2022) 1329].

Expected profile likelihood projections from the Higgs boson width fit using the full combination of H → ZZ → 4l with the off-shell H → ZZ → 2l2nu [Nature Phys. 18 (2022) 1329].

Observed profile likelihood projections from the Higgs boson width fit using the on- and off-shell H → ZZ → 4l channel.

Expected (dashed) profile likelihood projections from the Higgs boson width fit using the on- and off-shell H → ZZ → 4l channel.

Observed 2D profile likelihood projection of the off-shell signal strength parameters (mu off-shell, mu off-shell) from the fit to the combined off-shell H → ZZ → 4l and 2l2nu channels. [Nature Phys. 18 (2022) 1329] The best fit value is shown by the black cross and the SM prediction by the red x. The 68% and 95%CL contours are given by the dashed and solid curves, respectively. The color scale to the right of the plot relates the quantitative values.

Difference between data and simulation in Z → 2mu events, normalized to simulation, as a function of transverse momentum (pt) for three different pseudorapidity (|eta|) range, in 2016 pre-VPF, for positive muons.

Difference between data and simulation in Z → 2mu events, normalized to simulation, as a function of transverse momentum (pt) for three different pseudorapidity (|eta|) range, in 2016 pre-VPF, for negative muons.

Difference between data and simulation in J/Psi → 2mu events, normalized to simulation, as a function of the transverse momentum (pt) for two different pseudorapidity (|eta|) ranges, in 2016 pre-VPF, for positive muons.

Difference between data and simulation in J/Psi → 2mu events, normalized to simulation, as a function of the transverse momentum (pt) for two different pseudorapidity (|eta|) ranges, in 2016 pre-VPF, for negative muons.

Difference between data and simulation in Z → 2e events, normalized to simulation, as a function of transverse momentum (pt) for three different pseudorapidity (|eta|) ranges in 2016 pre-VPF.

Difference between data and simulation in Z → 2mu events, normalized to simulation, as a function of transverse momentum (pt) for three different pseudorapidity (|eta|) range, in 2016 post-VPF, for positive muons.

Difference between data and simulation in Z → 2mu events, normalized to simulation, as a function of transverse momentum (pt) for three different pseudorapidity (|eta|) range, in 2016 post-VPF, for negative muons.

Difference between data and simulation in J/Psi → 2mu events, normalized to simulation, as a function of the transverse momentum (pt) for two different pseudorapidity (|eta|) ranges, in 2016 post-VPF, for positive muons.

Difference between data and simulation in J/Psi → 2mu events, normalized to simulation, as a function of the transverse momentum (pt) for two different pseudorapidity (|eta|) ranges, in 2016 post-VPF, for negative muons.

Difference between data and simulation in Z → 2e events, normalized to simulation, as a function of transverse momentum (pt) for three different pseudorapidity (|eta|) ranges in 2016 post-VPF.

Difference between data and simulation in Z → 2mu events, normalized to simulation, as a function of transverse momentum (pt) for three different pseudorapidity (|eta|) range, in 2017, for positive muons.

Difference between data and simulation in Z → 2mu events, normalized to simulation, as a function of transverse momentum (pt) for three different pseudorapidity (|eta|) range, in 2017, for negative muons.

Difference between data and simulation in J/Psi → 2mu events, normalized to simulation, as a function of the transverse momentum (pt) for two different pseudorapidity (|eta|) ranges, in 2017, for positive muons.

Difference between data and simulation in J/Psi → 2mu events, normalized to simulation, as a function of the transverse momentum (pt) for two different pseudorapidity (|eta|) ranges, in 2017, for negative muons.

Difference between data and simulation in Z → 2e events, normalized to simulation, as a function of transverse momentum (pt) for three different pseudorapidity (|eta|) ranges in 2017.

Difference between data and simulation in Z → 2mu events, normalized to simulation, as a function of transverse momentum (pt) for three different pseudorapidity (|eta|) range, in 2018, for positive muons.

Difference between data and simulation in Z → 2mu events, normalized to simulation, as a function of transverse momentum (pt) for three different pseudorapidity (|eta|) range, in 2018, for negative muons.

Difference between data and simulation in J/Psi → 2mu events, normalized to simulation, as a function of the transverse momentum (pt) for two different pseudorapidity (|eta|) ranges, in 2018, for positive muons.

Difference between data and simulation in J/Psi → 2mu events, normalized to simulation, as a function of the transverse momentum (pt) for two different pseudorapidity (|eta|) ranges, in 2018, for negative muons.

Difference between data and simulation in Z → 2e events, normalized to simulation, as a function of transverse momentum (pt) for three different pseudorapidity (|eta|) ranges in 2018.

The observed likelihood scan as a function of mH using the N-2D'_VXBS$ approach.

The expected likelihood scan as a function of mH using the N-2D'_VXBS$ approach. Expected likelihood has been obtained with the hypothesis mH = 125.38 GeV

Comparison of measured with the predicted dilepton mass resolution using the event-by-event mass uncertainty for Z → 2e events in data in 2016 pre-VPF.

Comparison of measured with the predicted dilepton mass resolution using the event-by-event mass uncertainty for Z → 2mu events in data 2016 pre-VPF.

Comparison of measured with the predicted dilepton mass resolution using the event-by-event mass uncertainty for Z → 2e events in data in 2016 post-VPF.

Comparison of measured with the predicted dilepton mass resolution using the event-by-event mass uncertainty for Z → 2mu events in data 2016 post-VPF.

Comparison of measured with the predicted dilepton mass resolution using the event-by-event mass uncertainty for Z → 2e events in data in 2017.

Comparison of measured with the predicted dilepton mass resolution using the event-by-event mass uncertainty for Z → 2mu events in data 2017.

Comparison of measured with the predicted dilepton mass resolution using the event-by-event mass uncertainty for Z → 2e events in data in 2018.

Comparison of measured with the predicted dilepton mass resolution using the event-by-event mass uncertainty for Z → 2mu events in data 2018.

Observed profile likelihood projections from the Higgs boson width fit using the on- and off-shell H → ZZ → 4l channel with kappa Q constrained to 0.

Expected profile likelihood projections from the Higgs boson width fit using the on- and off-shell H → ZZ → 4l channel with kappa Q constrained to 0.

Observed profile likelihood projection on the Higgs boson width using on- and off-shell production. The analysis of H → ZZ → 4l, considering an unconstrained coupling strength κQ is presented.

Expected profile likelihood projection on the Higgs boson width using on- and off-shell production. The analysis of H → ZZ → 4l, considering an unconstrained coupling strength κQ is presented.

Expected profile likelihood projection on muF off-shell using on- and off-shell production for H → ZZ → 4l.

Observed profile likelihood projection on muF off-shell using on- and off-shell production for H → ZZ → 4l.

Expected profile likelihood projection on muF off-shell using using the full combination of H → ZZ → 4l with the off-shell H → ZZ → 2l2nu [Nature Phys. 18 (2022) 1329].

Observed profile likelihood projection on muF off-shell using using the full combination of H → ZZ → 4l with the off-shell H → ZZ → 2l2nu [Nature Phys. 18 (2022) 1329].

Expected profile likelihood projection on muV off-shell using on- and off-shell production for H → ZZ → 4l.

Observed profile likelihood projection on muV off-shell using on- and off-shell production for H → ZZ → 4l.

Expected profile likelihood projection on muV off-shell using using the full combination of H → ZZ → 4l with the off-shell H → ZZ → 2l2nu.

Observed profile likelihood projection on muV off-shell using using the full combination of H → ZZ → 4l with the off-shell H → ZZ → 2l2nu [Nature Phys. 18 (2022) 1329].

Expected profile likelihood projection on mu off-shell using on- and off-shell production for H → ZZ → 4l.

Observed profile likelihood projection on mu off-shell using on- and off-shell production for H → ZZ → 4l.

Expected profile likelihood projection on mu off-shell using using the full combination of H → ZZ → 4l with the off-shell H → ZZ → 2l2nu [Nature Phys. 18 (2022) 1329].

Observed profile likelihood projection on mu off-shell using using the full combination of H → ZZ → 4l with the off-shell H → ZZ → 2l2nu [Nature Phys. 18 (2022) 1329].

Covariance for full matrix measurement all bins from $m(t\bar{t})$ fit

Results for full matrix measurement inclusive from $p_{T}(t)$

Covariance for full matrix measurement inclusive from $p_{T}(t)$

Results for full matrix measurement all bins from $p_{T}(t)$ fit

Covariance for full matrix measurement all bins from $p_{T}(t)$ fit

Results for full matrix measurement differential in $m(t\bar{t})$

Covariance for full matrix measurement differential in $m(t\bar{t})$

Results for full matrix measurement differential in $m(t\bar{t})$ for $|cos(\theta)| < 0.4$

Covariance for full matrix measurement differential in $m(t\bar{t})$ for $|cos(\theta)| < 0.4$

Results for full matrix measurement differential in $p_{T}(t)$

Covariance for full matrix measurement differential in $p_{T}(t)$

Results for $D$ measurement inclusive from $m(t\bar{t})$

Covariance for $D$ measurement inclusive from $m(t\bar{t})$

Results for $D$ measurement inclusive from $p_{T}(t)$

Covariance for $D$ measurement inclusive from $p_{T}(t)$

Results for $\tilde{D}$ measurement inclusive in $m(t\bar{t})$

Covariance for $\tilde{D}$ measurement inclusive in $m(t\bar{t})$

Results for $\tilde{D}$ measurement inclusive in $p_{T}(t)$

Covariance for $\tilde{D}$ measurement inclusive in $p_{T}(t)$

Results for $D$ measurement all bins from from $m(t\bar{t})$ fit

Covariance for $D$ measurement all bins from from $m(t\bar{t})$ fit

Results for $D$ measurement all bins from from $p_{T}(t)$ fit

Covariance for $D$ measurement all bins from from $p_{T}(t)$ fit

Results for $\tilde{D}$ measurement all bins from from $m(t\bar{t})$ fit

Covariance for $\tilde{D}$ measurement all bins from from $m(t\bar{t})$ fit

Results for $\tilde{D}$ measurement all bins from from $p_{T}(t)$ fit

Covariance for $\tilde{D}$ measurement all bins from from $p_{T}(t)$ fit

Results for $D$ measurement differential in $m(t\bar{t})$

Covariance for $D$ measurement differential in $m(t\bar{t})$

Results for $\tilde{D}$ measurement differential in $m(t\bar{t})$

Covariance for $\tilde{D}$ measurement differential in $m(t\bar{t})$

Results for $\tilde{D}$ measurement differential in $m(t\bar{t})$ for $|cos(\theta)| < 0.4$

Covariance for $\tilde{D}$ measurement differential in $m(t\bar{t})$ for $|cos(\theta)| < 0.4$

Results for $D$ measurement differential in $p_{T}(t)$

Covariance for $D$ measurement differential in $p_{T}(t)$

Results for $\tilde{D}$ measurement differential in $p_{T}(t)$

Covariance for $\tilde{D}$ measurement differential in $p_{T}(t)$

The Bs meson $p_{\rm{T}}$-dependent RAA in PpPp. The measurment was carried out inside a fiducial region respecting ($p_{\rm{T}}$<10 & 1.5<|y|<2.4) and ($p_{\rm{T}}$>10 & |y|<2.4).

Observed and predicted $p_T^{miss}$ ($U$) distributions in the 1b category, in the Signal Region. The bottom plot shows the ratio of observed and predicted (both prefit and postfit) distributions along with an uncertainty band that includes both the systematic and statistical components.

Observed and predicted $p_T^{miss}$ ($U$) distributions in the 1b category, in the $Z(\ell\ell)$ Control Region. The bottom plot shows the ratio of observed and predicted (both prefit and postfit) distributions along with an uncertainty band that includes both the systematic and statistical components.

Observed and predicted $p_T^{miss}$ ($U$) distributions in the 1b category, in the $W(\ell\nu)$ Control Region. The bottom plot shows the ratio of observed and predicted (both prefit and postfit) distributions along with an uncertainty band that includes both the systematic and statistical components.

Observed and predicted $\cos\Theta$* distributions in the 2b category, in the Signal Region. The bottom plot shows the ratio of observed and predicted (both prefit and postfit) distributions along with an uncertainty band that includes both the systematic and statistical components.

Observed and predicted $\cos\Theta$* distributions in the 2b category, in the $Z(\ell\ell)$ Control Region. The bottom plot shows the ratio of observed and predicted (both prefit and postfit) distributions along with an uncertainty band that includes both the systematic and statistical components.

Observed and predicted $\cos\Theta$* distributions in the 2b category, in the $t\bar{t}$ Control Region. The bottom plot shows the ratio of observed and predicted (both prefit and postfit) distributions along with an uncertainty band that includes both the systematic and statistical components.

The $95\%$ CL upper limit on the signal strength modifier of DM produced in association with a pair of bottom quarks for $m_A=600$ GeV, $\sin\theta=0.7$, $m_\chi=1$ GeV, and $\tan\beta=35$, for the combination of SR1 and SR2. The green and yellow bands show the $\pm 1$ and $\pm 2$ standard deviations from expected limits. The mass points below the red line are excluded.

$95\%$ CL upper limit on the signal strength in the $m_a-\tan\beta$ plane. The shaded area above the curve is excluded.

$95\%$ CL upper limit on the signal strength in the $m_a-\sin\theta$ plane. The shaded area above the curve is excluded.

$95\%$ CL upper limit on the signal strength in the $m_a-m_\chi$ plane. The shaded area below the curve is excluded.