Expected and observed $95\%$ CL limits on the absolute value of the up-type quark coupling parameter $|\zeta_\mathrm{u}|$ for masses of the $A$ boson ranging from $20$ to $90\,\mathrm{GeV}$.

Observed $p_0$ values for the fits on the production cross-section for $gg\rightarrow A$ times the branching ratio for $A$ decaying into two $\tau$-leptons for $A$ boson masses from $20$ to $90\,\mathrm{GeV}$. For the fit on the up-type quark coupling parameter the $p_0$ values agree up to a precision of $O(10^{-5})$.

Expected (dashed black line) and observed (solid red line) 95% CL exclusion limits on the compressed SUSY simplified model with a bino-like LSP and wino-like NLSPs being considered. These are shown with $\pm1\sigma_\text{exp}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm1\sigma^{\text{SUSY}}_{\text{theory}}$ (red dotted lines) from signal cross-section uncertainties, respectively. The limits set by the ATLAS searches using the soft lepton signature is illustrated by the blue region while the limit imposed by the LEP experiments is shown in grey.

Expected (dashed black line) and observed (solid red line) 95% CL exclusion limits on the compressed SUSY simplified model with a bino-like LSP and wino-like NLSPs being considered. These are shown with $\pm1\sigma_ ext{exp}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm1\sigma^{ ext{SUSY}}_{ ext{theory}}$ (red dotted lines) from signal cross-section uncertainties, respectively. The limits set by the ATLAS searches using the soft lepton signature is illustrated by the blue region while the limit imposed by the LEP experiments is shown in grey.

The expected upper limits on the cross-sections at 95% CL for the simplified SUSY model featuring the production of mass-degenerate pairs of wino-like $\widetilde{\chi}_{2}^{0}$ and $\widetilde{\chi}_{1}^{\pm}$ particles in association with at least two jets. The production modes considered are $\widetilde{\chi}_{2}^{0}\widetilde{\chi}_{1}^{\pm}$, $\widetilde{\chi}_{1}^{\pm}\widetilde{\chi}_{1}^{\mp}$, $\widetilde{\chi}_{2}^{0}\widetilde{\chi}_{2}^{0}$, and $\widetilde{\chi}_{1}^{\pm}\widetilde{\chi}_{1}^{\pm}$.

The observed upper limits on the cross-sections at 95% CL for the simplified SUSY model featuring the production of mass-degenerate pairs of wino-like $\widetilde{\chi}_{2}^{0}$ and $\widetilde{\chi}_{1}^{\pm}$ particles in association with at least two jets. The production modes considered are $\widetilde{\chi}_{2}^{0}\widetilde{\chi}_{1}^{\pm}$, $\widetilde{\chi}_{1}^{\pm}\widetilde{\chi}_{1}^{\mp}$, $\widetilde{\chi}_{2}^{0}\widetilde{\chi}_{2}^{0}$, and $\widetilde{\chi}_{1}^{\pm}\widetilde{\chi}_{1}^{\pm}$.

Truth-level signal acceptances in $\text{SR}_\text{2j}$ with BDT score $\in [0.88, 1.0]$. All of the considered production modes ($\widetilde{\chi}_{2}^{0}\widetilde{\chi}_{1}^{\pm}$, $\widetilde{\chi}_{1}^{\pm}\widetilde{\chi}_{1}^{\mp}$, $\widetilde{\chi}_{2}^{0}\widetilde{\chi}_{2}^{0}$, and $\widetilde{\chi}_{1}^{\pm}\widetilde{\chi}_{1}^{\pm}$) are included. The acceptance is defined as the fraction of accepted events divided by the total number of events in the generator-level signal Monte Carlo simulation. The generator-level selections are the same as the ones at reconstruction level.

Truth-level signal acceptances in $\text{SR}_{\geq\text{3j}}$ with BDT score $\in [0.88, 1.0]$. All of the considered production modes ($\widetilde{\chi}_{2}^{0}\widetilde{\chi}_{1}^{\pm}$, $\widetilde{\chi}_{1}^{\pm}\widetilde{\chi}_{1}^{\mp}$, $\widetilde{\chi}_{2}^{0}\widetilde{\chi}_{2}^{0}$, and $\widetilde{\chi}_{1}^{\pm}\widetilde{\chi}_{1}^{\pm}$) are included. The acceptance is defined as the fraction of accepted events divided by the total number of events in the generator-level signal Monte Carlo simulation. The generator-level selections are the same as the ones at reconstruction level.

Signal efficiencies in $\text{SR}_\text{2j}$ with BDT score $\in [0.88, 1.0]$. All of the considered production modes ($\widetilde{\chi}_{2}^{0}\widetilde{\chi}_{1}^{\pm}$, $\widetilde{\chi}_{1}^{\pm}\widetilde{\chi}_{1}^{\mp}$, $\widetilde{\chi}_{2}^{0}\widetilde{\chi}_{2}^{0}$, and $\widetilde{\chi}_{1}^{\pm}\widetilde{\chi}_{1}^{\pm}$) are included. The efficiency is defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level. The generator-level selections are the same as the ones at reconstruction level.

Signal efficiencies in $\text{SR}_{\geq\text{3j}}$ with BDT score $\in [0.88, 1.0]$. All of the considered production modes ($\widetilde{\chi}_{2}^{0}\widetilde{\chi}_{1}^{\pm}$, $\widetilde{\chi}_{1}^{\pm}\widetilde{\chi}_{1}^{\mp}$, $\widetilde{\chi}_{2}^{0}\widetilde{\chi}_{2}^{0}$, and $\widetilde{\chi}_{1}^{\pm}\widetilde{\chi}_{1}^{\pm}$) are included. The efficiency is defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level. The generator-level selections are the same as the ones at reconstruction level.

Event selection cutflows for signal samples with $m(\tilde\chi^0_2) =100~\text{GeV}$ and $\Delta m(\tilde\chi^0_2 / \tilde\chi^\pm_1,\tilde\chi^0_1) = 0.2~\text{GeV}, 1.0~\text{GeV},$ and $5.0~\text{GeV}$. The first number in the column for each mass point corresponds to the signal event yield after applying the associated cut while the second number in parentheses represents the efficiency with respect to the previous cut. All of the production modes are included. The total cross-section used to obtain the initial number of events ($\sigma$) includes the cuts applied at parton level as described in the main text.

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.

Distributions of the $\mathrm{NN^{SvsB}}$ output for data and the expected background after the likelihood fit in the $SR_{cQu --}$ signal region. The post-fit background expectations are shown as filled histograms, the combined pre-fit background expectations are shown as dashed lines. The signal distribution using the Wilson coefficient values $c_{tu}^{(1)}=0.04$, $c_{Qu}^{(1)}=0.1$, $c_{Qu}^{(8)}=0.1$ is shown with a dotted line, normalized to the same number of events as the background.

Summary of the observed and predicted number of events in the five 2$\ell$ control regions. The background prediction is shown after the combined likelihood fit to data under the signal-plus-background hypothesis across all control regions and signal regions. The uncertainties in the total yields are smaller than the sum in quadrature of the uncertainties in the individual contributions due to anti-correlations resulting from the likelihood fit. Int Conv refers to events with photon conversions in the inner detector, while Mat Conv refers to events with photon conversions in the detector material. QMisID refers to events with charge-misidentified lepton.

Summary of the observed and predicted number of events in the four 3$\ell$ control regions. The background prediction is shown after the combined likelihood fit to data under the signal-plus-background hypothesis across all control regions and signal regions. The uncertainties in the total yields are smaller than the sum in quadrature of the uncertainties in the individual contributions due to anti-correlations resulting from the likelihood fit. Int Conv refers to events with photon conversions in the inner detector, while Mat Conv refers to events with photon conversions in the detector material. QMisID refers to events with charge-misidentified lepton.

Comparison of the observed limits on the three WCs to the limit obtained by the ATLAS Run~1 analysis of events with $b$-tagged jets and a same-sign lepton pair [JHEP10(2015)150]. The cross-section limits from that analysis are converted to the limits on the WCs by using the fitted EFT parametrization. The bounds on the WCs are shown at the 68$\%$ CL (solid) and/or 95$\%$ CL (dashed) levels. For the ATLAS Run~1 analysis only the bounds at 95$\%$ CL are available. The vertical bar represents the SM prediction. The new-physics scale is set to $\Lambda = 1 \, \text{TeV}$.

Observed lower limits at 95$\%$ confidence level on the scale of new physics $\Lambda$ for Wilson coefficient values of 0.01, 1 and $4\pi^2$. The limits are compared with the limits obtained by the ATLAS Run~1 analysis of events with $b$-tagged jets and a same-sign lepton pair.

Observed and expected limits at 95$\%$ confidence level on the cross-section of $\sigma(pp \rightarrow tt)$.

2D likelihood scans of the Wilson coefficients $c_{tu}^{(1)}$ versus $c_{Qu}^{(1)}$. The new-physics scale is set to $\Lambda = 1 \, \text{TeV}$. In the table the $2\Delta$NLL values are shown which correspond to the minimized negative log likelihood for a given Wilson coefficient pair.

2D likelihood scans of the Wilson coefficients $c_{tu}^{(1)}$ versus $c_{Qu}^{(8)}$. The new-physics scale is set to $\Lambda = 1 \, \text{TeV}$. In the table the $2\Delta$NLL values are shown which correspond to the minimized negative log likelihood for a given Wilson coefficient pair.

2D likelihood scans of the Wilson coefficients $c_{Qu}^{(1)}$ versus $c_{Qu}^{(8)}$. The new-physics scale is set to $\Lambda = 1 \, \text{TeV}$. In the table the $2\Delta$NLL values are shown which correspond to the minimized negative log likelihood for a given Wilson coefficient pair.

1D-likelihood scan for $c_{tu}^{(1)}$. The observed and expected limits at 68\% and 95\% confidence level (CL) can be read off by finding the intersection of the likelihood scan curve with the 1$\sigma$ and 2$\sigma$ lines. The new-physics scale is set to $\Lambda = 1 \, \text{TeV}$. In the table the $2\Delta$NLL values are shown which correspond to the minimized negative log likelihood for a given Wilson coefficient value.

1D-likelihood scan for $c_{Qu}^{(1)}$. The observed and expected limits at 68\% and 95\% confidence level (CL) can be read off by finding the intersection of the likelihood scan curve with the 1$\sigma$ and 2$\sigma$ lines. The new-physics scale is set to $\Lambda = 1 \, \text{TeV}$. In the table the $2\Delta$NLL values are shown which correspond to the minimized negative log likelihood for a given Wilson coefficient value.

1D-likelihood scan for $c_{Qu}^{(8)}$. The observed and expected limits at 68\% and 95\% confidence level (CL) can be read off by finding the intersection of the likelihood scan curve with the 1$\sigma$ and 2$\sigma$ lines. The new-physics scale is set to $\Lambda = 1 \, \text{TeV}$. In the table the $2\Delta$NLL values are shown which correspond to the minimized negative log likelihood for a given Wilson coefficient value.

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 95% CL upper limits on the branching fraction $\mathcal{B}(\mathrm{H \to SS})$ with $\mathrm{S}\to\tau\tau$ decay, for different LLP masses $m_{\mathrm{S}}$ and proper decay lengths $c\tau_{0}$.

The 95% CL limits on the LLP mass $m_{\mathrm{S}}$ for different proper decay lengths $c\tau_{0}$ assuming a branching fraction of 1% for the $\mathrm{H \to SS}$ decay, and with subsequent $\mathrm{S \to b\overline{b}}$ decay.

The 95% CL limits on the LLP mass $m_{\mathrm{S}}$ for different proper decay lengths $c\tau_{0}$ assuming a branching fraction of 1% for the $\mathrm{H \to SS}$ decay, and with subsequent $\mathrm{S \to d \overline{d}}$ decay.

The 95% CL limits on the dark-sector top quark partner mass $m_{T}$ for different hidden glueball masses $m_{0}$ in the fraternal twin Higgs model.

The 95% CL limits on the dark-sector top quark partner mass $m_{T}$ for different hidden glueball masses $m_{0}$ in the folded SUSY model.

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).

Distribution of the RF output for events in the 2j1b region. The number of observed events (points) and estimated signal and background events (filled histograms) before the maximum likelihood fit are shown. The vertical bars on the points represent the statistical uncertainty in the data, and the hatched band the total uncertainty in the estimated events before the fit. The lower panels display the ratio of the data to the sum of the estimated events (points) before the fit, with the bands giving the corresponding uncertainties.

The distribution of the Subleading jet $p_{T}$ for events in the 2j2b region. The number of observed events (points) and estimated signal and background events (filled histograms) from the maximum likelihood fit are shown. The vertical bars on the points represent the statistical uncertainty in the data, and the hatched band the total uncertainty in the estimated events after the fit. The lower panels display the ratio of the data to the sum of the estimated events (points) after the fit, with the bands giving the corresponding uncertainties.

Distribution of the Subleading jet $p_{T}$ for events in the 2j2b region. The number of observed events (points) and estimated signal and background events (filled histograms) before the maximum likelihood fit are shown. The vertical bars on the points represent the statistical uncertainty in the data, and the hatched band the total uncertainty in the estimated events before the fit. The lower panels display the ratio of the data to the sum of the estimated events (points) before the fit, with the bands giving the corresponding uncertainties.

Observed and theoretical cross sections. In the observed, the first uncertainty is statistical, the second is the systematic, and the third the luminosity. In the theoretical, the first uncertainty is due to scale variations, the second due to the choice of PDF. The theoretical cross section has been computed at approximate third-order in QCD, with the addition of third-order corrections of soft gluon emission terms, assuming a top quark mass of 172.5 GeV and using the PDF4LHC21 PDF set.

The distribution of the RF output for events in the 1j1b region. The number of observed events (points) and estimated signal and background events (filled histograms) from the maximum likelihood fit are shown. The vertical bars on the points represent the statistical uncertainty in the data, and the hatched band the total uncertainty in the estimated events after the fit. The lower panels display the ratio of the data to the sum of the estimated events (points) after the fit, with the bands giving the corresponding uncertainties.

The number of estimated signal and background events after the fit in the 1j1b, 2j1b, and 2j2b regions compared to the observed number of events. The total uncertainties in the estimated events after the fit are given.

The distribution of the RF output for events in the 2j1b region. The number of observed events (points) and estimated signal and background events (filled histograms) from the maximum likelihood fit are shown. The vertical bars on the points represent the statistical uncertainty in the data, and the hatched band the total uncertainty in the estimated events after the fit. The lower panels display the ratio of the data to the sum of the estimated events (points) after the fit, with the bands giving the corresponding uncertainties.

Normalised fiducial differential tW production cross section as a function of the $Leading$ $lepton$ $p_{T}$. The horizontal bars on the points show the bin width. Predictions from POWHEG (PH) DR and DS + PYTHIA 8 (P8), POWHEG DR + HERWIG 7 (H7), MADGRAPH5_aMC@NLO (aMC) DR, DR2, DS and DS with a dynamic factor + PYTHIA 8 are also shown. The grey band represents the statistical uncertainty and the yellow band the total uncertainty. In the lower panels, the ratio of the predictions to the data is shown.

The distribution of the Subleading jet $p_{T}$ for events in the 2j2b region. The number of observed events (points) and estimated signal and background events (filled histograms) from the maximum likelihood fit are shown. The vertical bars on the points represent the statistical uncertainty in the data, and the hatched band the total uncertainty in the estimated events after the fit. The lower panels display the ratio of the data to the sum of the estimated events (points) after the fit, with the bands giving the corresponding uncertainties.

Normalised fiducial differential tW production cross section as a function of the $p_{Z}(e^{\pm}, \mu^{\pm}, j)$. The horizontal bars on the points show the bin width. Predictions from POWHEG (PH) DR and DS + PYTHIA 8 (P8), POWHEG DR + HERWIG 7 (H7), MADGRAPH5_aMC@NLO (aMC) DR, DR2, DS and DS with a dynamic factor + PYTHIA 8 are also shown. The grey band represents the statistical uncertainty and the yellow band the total uncertainty. In the lower panels, the ratio of the predictions to the data is shown.

Observed and theoretical cross sections. In the observed, the first uncertainty is statistical, the second is the systematic, and the third the luminosity. In the theoretical, the first uncertainty is due to scale variations, the second due to the choice of PDF. The theoretical cross section has been computed at approximate third-order in QCD, with the addition of third-order corrections of soft gluon emission terms, assuming a top quark mass of 172.5 GeV and using the PDF4LHC21 PDF set.

Normalised fiducial differential tW production cross section as a function of the $Jet$ $p_{T}$. The horizontal bars on the points show the bin width. Predictions from POWHEG (PH) DR and DS + PYTHIA 8 (P8), POWHEG DR + HERWIG 7 (H7), MADGRAPH5_aMC@NLO (aMC) DR, DR2, DS and DS with a dynamic factor + PYTHIA 8 are also shown. The grey band represents the statistical uncertainty and the yellow band the total uncertainty. In the lower panels, the ratio of the predictions to the data is shown.

The number of estimated signal and background events after the fit in the 1j1b, 2j1b, and 2j2b regions compared to the observed number of events. The total uncertainties in the estimated events after the fit are given.

Normalised fiducial differential tW production cross section as a function of the $m(e^{\pm}, \mu^{\pm}, j)$. The horizontal bars on the points show the bin width. Predictions from POWHEG (PH) DR and DS + PYTHIA 8 (P8), POWHEG DR + HERWIG 7 (H7), MADGRAPH5_aMC@NLO (aMC) DR, DR2, DS and DS with a dynamic factor + PYTHIA 8 are also shown. The grey band represents the statistical uncertainty and the yellow band the total uncertainty. In the lower panels, the ratio of the predictions to the data is shown.

Normalised fiducial differential tW production cross section as a function of the $Leading$ $lepton$ $p_{T}$. The horizontal bars on the points show the bin width. Predictions from POWHEG (PH) DR and DS + PYTHIA 8 (P8), POWHEG DR + HERWIG 7 (H7), MADGRAPH5_aMC@NLO (aMC) DR, DR2, DS and DS with a dynamic factor + PYTHIA 8 are also shown. The grey band represents the statistical uncertainty and the yellow band the total uncertainty. In the lower panels, the ratio of the predictions to the data is shown.

Normalised fiducial differential tW production cross section as a function of the $\Delta\phi(e^{\pm}, \mu^{\pm})/\pi$. The horizontal bars on the points show the bin width. Predictions from POWHEG (PH) DR and DS + PYTHIA 8 (P8), POWHEG DR + HERWIG 7 (H7), MADGRAPH5_aMC@NLO (aMC) DR, DR2, DS and DS with a dynamic factor + PYTHIA 8 are also shown. The grey band represents the statistical uncertainty and the yellow band the total uncertainty. In the lower panels, the ratio of the predictions to the data is shown.

Normalised fiducial differential tW production cross section as a function of the $p_{Z}(e^{\pm}, \mu^{\pm}, j)$. The horizontal bars on the points show the bin width. Predictions from POWHEG (PH) DR and DS + PYTHIA 8 (P8), POWHEG DR + HERWIG 7 (H7), MADGRAPH5_aMC@NLO (aMC) DR, DR2, DS and DS with a dynamic factor + PYTHIA 8 are also shown. The grey band represents the statistical uncertainty and the yellow band the total uncertainty. In the lower panels, the ratio of the predictions to the data is shown.

Normalised fiducial differential tW production cross section as a function of the $m_{T}(e^{\pm}, \mu^{\pm}, j, p_{T}^{miss})$. The horizontal bars on the points show the bin width. Predictions from POWHEG (PH) DR and DS + PYTHIA 8 (P8), POWHEG DR + HERWIG 7 (H7), MADGRAPH5_aMC@NLO (aMC) DR, DR2, DS and DS with a dynamic factor + PYTHIA 8 are also shown. The grey band represents the statistical uncertainty and the yellow band the total uncertainty. In the lower panels, the ratio of the predictions to the data is shown.

Normalised fiducial differential tW production cross section as a function of the $Jet$ $p_{T}$. The horizontal bars on the points show the bin width. Predictions from POWHEG (PH) DR and DS + PYTHIA 8 (P8), POWHEG DR + HERWIG 7 (H7), MADGRAPH5_aMC@NLO (aMC) DR, DR2, DS and DS with a dynamic factor + PYTHIA 8 are also shown. The grey band represents the statistical uncertainty and the yellow band the total uncertainty. In the lower panels, the ratio of the predictions to the data is shown.

The p-values from the goodness-of-fit tests comparing the six differential cross section measurements with the predictions from POWHEG (PH) DR and DS + PYTHIA 8 (P8), POWHEG DR + HERWIG 7 (H7), MADGRAPH5 aMC@NLO (aMC) DR, DR2, DS, and DS with a dynamic factor + PYTHIA 8. The complete covariance matrix from the results and the statistical uncertainties in the predictions are taken into account.

Normalised fiducial differential tW production cross section as a function of the $m(e^{\pm}, \mu^{\pm}, j)$. The horizontal bars on the points show the bin width. Predictions from POWHEG (PH) DR and DS + PYTHIA 8 (P8), POWHEG DR + HERWIG 7 (H7), MADGRAPH5_aMC@NLO (aMC) DR, DR2, DS and DS with a dynamic factor + PYTHIA 8 are also shown. The grey band represents the statistical uncertainty and the yellow band the total uncertainty. In the lower panels, the ratio of the predictions to the data is shown.

Distribution of the RF output for events in the 1j1b region. The number of observed events (points) and estimated signal and background events (filled histograms) before the maximum likelihood fit are shown. The vertical bars on the points represent the statistical uncertainty in the data, and the hatched band the total uncertainty in the estimated events before the fit. The lower panels display the ratio of the data to the sum of the estimated events (points) before the fit, with the bands giving the corresponding uncertainties.

Normalised fiducial differential tW production cross section as a function of the $\Delta\phi(e^{\pm}, \mu^{\pm})/\pi$. The horizontal bars on the points show the bin width. Predictions from POWHEG (PH) DR and DS + PYTHIA 8 (P8), POWHEG DR + HERWIG 7 (H7), MADGRAPH5_aMC@NLO (aMC) DR, DR2, DS and DS with a dynamic factor + PYTHIA 8 are also shown. The grey band represents the statistical uncertainty and the yellow band the total uncertainty. In the lower panels, the ratio of the predictions to the data is shown.

Distribution of the RF output for events in the 2j1b region. The number of observed events (points) and estimated signal and background events (filled histograms) before the maximum likelihood fit are shown. The vertical bars on the points represent the statistical uncertainty in the data, and the hatched band the total uncertainty in the estimated events before the fit. The lower panels display the ratio of the data to the sum of the estimated events (points) before the fit, with the bands giving the corresponding uncertainties.

Normalised fiducial differential tW production cross section as a function of the $m_{T}(e^{\pm}, \mu^{\pm}, j, p_{T}^{miss})$. The horizontal bars on the points show the bin width. Predictions from POWHEG (PH) DR and DS + PYTHIA 8 (P8), POWHEG DR + HERWIG 7 (H7), MADGRAPH5_aMC@NLO (aMC) DR, DR2, DS and DS with a dynamic factor + PYTHIA 8 are also shown. The grey band represents the statistical uncertainty and the yellow band the total uncertainty. In the lower panels, the ratio of the predictions to the data is shown.

Distribution of the Subleading jet $p_{T}$ for events in the 2j2b region. The number of observed events (points) and estimated signal and background events (filled histograms) before the maximum likelihood fit are shown. The vertical bars on the points represent the statistical uncertainty in the data, and the hatched band the total uncertainty in the estimated events before the fit. The lower panels display the ratio of the data to the sum of the estimated events (points) before the fit, with the bands giving the corresponding uncertainties.

The p-values from the goodness-of-fit tests comparing the six differential cross section measurements with the predictions from POWHEG (PH) DR and DS + PYTHIA 8 (P8), POWHEG DR + HERWIG 7 (H7), MADGRAPH5 aMC@NLO (aMC) DR, DR2, DS, and DS with a dynamic factor + PYTHIA 8. The complete covariance matrix from the results and the statistical uncertainties in the predictions are taken into account.

Response matrix between detector and particle level for the $Leading$ $lepton$ $p_{T}$.

Response matrix between detector and particle level for the $Leading$ $lepton$ $p_{T}$.

Response matrix between detector and particle level for the $p_{Z}(e^{\pm}, \mu^{\pm}, j)$.

Response matrix between detector and particle level for the $p_{Z}(e^{\pm}, \mu^{\pm}, j)$.

Response matrix between detector and particle level for the $Jet$ $p_{T}$.

Response matrix between detector and particle level for the $Jet$ $p_{T}$.

Response matrix between detector and particle level for the $m(e^{\pm}, \mu^{\pm}, j)$.

Response matrix between detector and particle level for the $m(e^{\pm}, \mu^{\pm}, j)$.

Response matrix between detector and particle level for the $\Delta\phi(e^{\pm}, \mu^{\pm})/\pi$.

Response matrix between detector and particle level for the $\Delta\phi(e^{\pm}, \mu^{\pm})/\pi$.

Response matrix between detector and particle level for the $m_{T}(e^{\pm}, \mu^{\pm}, j, p_{T}^{miss})$.

Response matrix between detector and particle level for the $m_{T}(e^{\pm}, \mu^{\pm}, j, p_{T}^{miss})$.

Covariance matrix including all uncertainties of the normalised differential cross section in bins of $Leading$ $lepton$ $p_{T}$ in units of $1/GeV^{2}$.

Covariance matrix including all uncertainties of the normalised differential cross section in bins of $Leading$ $lepton$ $p_{T}$ in units of $1/GeV^{2}$.

Covariance matrix including all uncertainties of the normalised differential cross section in bins of $p_{Z}(e^{\pm}, \mu^{\pm}, j)$ in units of $1/GeV^{2}$.

Covariance matrix including all uncertainties of the normalised differential cross section in bins of $p_{Z}(e^{\pm}, \mu^{\pm}, j)$ in units of $1/GeV^{2}$.

Covariance matrix including all uncertainties of the normalised differential cross section in bins of $Jet$ $p_{T}$ in units of $1/GeV^{2}$.

Covariance matrix including all uncertainties of the normalised differential cross section in bins of $Jet$ $p_{T}$ in units of $1/GeV^{2}$.

Covariance matrix including all uncertainties of the normalised differential cross section in bins of $m(e^{\pm}, \mu^{\pm}, j)$ in units of $1/GeV^{2}$.

Covariance matrix including all uncertainties of the normalised differential cross section in bins of $m(e^{\pm}, \mu^{\pm}, j)$ in units of $1/GeV^{2}$.

Covariance matrix including all uncertainties of the normalised differential cross section in bins of $\Delta\phi(e^{\pm}, \mu^{\pm})/\pi$ in units of 1.

Covariance matrix including all uncertainties of the normalised differential cross section in bins of $\Delta\phi(e^{\pm}, \mu^{\pm})/\pi$ in units of 1.

Covariance matrix including all uncertainties of the normalised differential cross section in bins of $m_{T}(e^{\pm}, \mu^{\pm}, j, p_{T}^{miss})$ in units of $1/GeV^{2}$.

Covariance matrix including all uncertainties of the normalised differential cross section in bins of $m_{T}(e^{\pm}, \mu^{\pm}, j, p_{T}^{miss})$ in units of $1/GeV^{2}$.

Self-Normalized $J/\psi$ yields in the same arms before and after dimuon subtraction and the comparison with PYTHIA 8 simulations

Self-normalized $\psi(2S)$ to $J/\psi$ yields ratio as a function of Self-normalized $N_{ch}$ in the same arms

Self-normalized $\psi(2S)$ to $J/\psi$ yields ratio as a function of Self-normalized $N_{ch}$ in opposite arms