Figure 8(left) of the article. Differential fiducial cross-section of the Z boson $p_T$ in events with $Z (\rightarrow ll) \ge 1 $ b-jets. The thin inner band corresponds to the statistical uncertainty of the data, and the outer band to statistical and systematic uncertainties of the data, added in quadrature.

Figure 8(right) of the article. Differential fiducial cross-section of the leading $b$-jet $p_T$ in events with $Z (\rightarrow ll) \ge 1 $ b-jets. The thin inner band corresponds to the statistical uncertainty of the data, and the outer band to statistical and systematic uncertainties of the data, added in quadrature.

Figure 9 of the article. Differential fiducial cross-section of the $\Delta R$ between the $Z$ boson and the leading $b$-jet in events with $Z (\rightarrow ll) \ge 1 $ b-jets. The thin inner band corresponds to the statistical uncertainty of the data, and the outer band to statistical and systematic uncertainties of the data, added in quadrature.

Figure 10(left) of the article. Differential fiducial cross-section of the $\Delta \phi$ between the leading and sub-leading $b$-jets in events with $Z (\rightarrow ll) \ge 2 $ b-jets. The thin inner band corresponds to the statistical uncertainty of the data, and the outer band to statistical and systematic uncertainties of the data, added in quadrature.

Figure 10(right) of the article. Differential fiducial cross-section of the invariant mass of the leading and sub-leading $b$-jets in events with $Z (\rightarrow ll) \ge 2 $ b-jets. The thin inner band corresponds to the statistical uncertainty of the data, and the outer band to statistical and systematic uncertainties of the data, added in quadrature.

Figure 11(left) of the article. Differential fiducial cross-section of the Z boson $p_T$ in events with $Z (\rightarrow ll) \ge 1 $ c-jets. The thin inner band corresponds to the statistical uncertainty of the data, and the outer band to statistical and systematic uncertainties of the data, added in quadrature.

Figure 11(right) of the article. Differential fiducial cross-section of the leading $c$-jet $p_T$ in events with $Z (\rightarrow ll) \ge 1 $ c-jets. The thin inner band corresponds to the statistical uncertainty of the data, and the outer band to statistical and systematic uncertainties of the data, added in quadrature.

Figure 12 of the article. Differential fiducial cross-section of the leading $c$-jet $x_F$ in events with $Z (\rightarrow ll) \ge 1 $ c-jets. The thin inner band corresponds to the statistical uncertainty of the data, and the outer band to statistical and systematic uncertainties of the data, added in quadrature.

Correction factors from parton level done with flavour dressing algorithms as seen in Ref. [2] of the paper to hadron level with R 0.3 cone labelling (see Tables 18 & 24) for the differential cross-section of the Z boson $p_T$ in events with $Z (\rightarrow ll) \ge 1 $ b-jets. Systematic errors include Sherpa 2.2.11 and MGaMC+Py8 FxFx uncertainties for what concerns the passage from hadron level flavour dressing to hadron level cone labelling, plus statistical uncertainty of Pythia8 simulations used for parton to hadron corrections. See Table 4.

Correction factors from parton level done with flavour dressing algorithms as seen in Ref. [2] of the paper to hadron level with R 0.3 cone labelling (see Tables 19 & 25) for the differential cross-section of the Z boson $p_T$ in events with $Z (\rightarrow ll) \ge 1 $ c-jets. Systematic errors include Sherpa 2.2.11 and MGaMC+Py8 FxFx uncertainties for what concerns the passage from hadron level flavour dressing to hadron level cone labelling, plus statistical uncertainty of Pythia8 simulations used for parton to hadron corrections. See Table 9.

Correction factors from parton level done with flavour dressing algorithms as seen in Ref. [2] of the paper to hadron level with R 0.3 cone labelling (see Tables 20 & 26) for the differential cross-section of the leading $b$-jet $p_T$ in events with $Z (\rightarrow ll) \ge 1 $ b-jets. Systematic errors include Sherpa 2.2.11 and MGaMC+Py8 FxFx uncertainties for what concerns the passage from hadron level flavour dressing to hadron level cone labelling, plus statistical uncertainty of Pythia8 simulations used for parton to hadron corrections. See Table 5.

Correction factors from parton level done with flavour dressing algorithms as seen in Ref. [2] of the paper to hadron level with R 0.3 cone labelling (see Tables 21 & 27) for the differential cross-section of the leading $c$-jet $p_T$ in events with $Z (\rightarrow ll) \ge 1 $ c-jets. Systematic errors include Sherpa 2.2.11 and MGaMC+Py8 FxFx uncertainties for what concerns the passage from hadron level flavour dressing to hadron level cone labelling, plus statistical uncertainty of Pythia8 simulations used for parton to hadron corrections. See Table 10.

Correction factors from parton level done with flavour dressing algorithms as seen in Ref. [2] of the paper to hadron level with R 0.3 cone labelling (see Tables 22 & 28) for the differential cross-section of the leading $c$-jet $x_F$ in events with $Z (\rightarrow ll) \ge 1 $ c-jets. Systematic errors include Sherpa 2.2.11 and MGaMC+Py8 FxFx uncertainties for what concerns the passage from hadron level flavour dressing to hadron level cone labelling, plus statistical uncertainty of Pythia8 simulations used for parton to hadron corrections. See Table 11.

Correction factors from parton level done with flavour dressing algorithms as seen in Ref. [2] of the paper of the paper to hadron level with R 0.3 cone labelling (see Tables 23 & 29) for the differential cross-section of $\Delta R$ between the $Z$ boson and the leading $b$-jet in events with $Z (\rightarrow ll) \ge 1 $ b-jets. Systematic errors include Sherpa 2.2.11 and MGaMC+Py8 FxFx uncertainties for what concerns the passage from hadron level flavour dressing to hadron level cone labelling, plus statistical uncertainty of Pythia8 simulations used for parton to hadron corrections. See Table 6.

Correction factors from hadron level done with flavour dressing algorithms as seen in Ref. [2] of the paper to hadron level R 0.3 cone labelling for the differential cross-section of the Z boson $p_T$ in events with $Z (\rightarrow ll) \ge 1 $ b-jets. Systematic errors include Sherpa 2.2.11 and MGaMC+Py8 FxFx uncertainties. See Table 12.

Correction factors from hadron level done with flavour dressing algorithms as seen in Ref. [2] of the paper to hadron level with R 0.3 cone labelling for the differential cross-section of the Z boson $p_T$ in events with $Z (\rightarrow ll) \ge 1 $ c-jets. Systematic errors include Sherpa 2.2.11 and MGaMC+Py8 FxFx uncertainties. See Table 13.

Correction factors from hadron level done with flavour dressing algorithms as seen in Ref. [2] of the paper to hadron level with R 0.3 cone labelling for the differential cross-section of the leading $b$-jet $p_T$ in events with $Z (\rightarrow ll) \ge 1 $ b-jets. Systematic errors include Sherpa 2.2.11 and MGaMC+Py8 FxFx uncertainties. See Table 14.

Correction factors from hadron level done with flavour dressing algorithms as seen in Ref. [2] of the paper to hadron level with R 0.3 cone labelling for the differential cross-section of the leading $c$-jet $p_T$ in events with $Z (\rightarrow ll) \ge 1 $ c-jets. Systematic errors include Sherpa 2.2.11 and MGaMC+Py8 FxFx uncertainties. See Table 15.

Correction factors from hadron level done with flavour dressing algorithms as seen in Ref. [2] of the paper to hadron level with R 0.3 cone labelling for the differential cross-section of the leading $c$-jet $x_F$ in events with $Z (\rightarrow ll) \ge 1 $ c-jets. Systematic errors include Sherpa 2.2.11 and MGaMC+Py8 FxFx uncertainties. See Table 16.

Correction factors from hadron level done with flavour dressing algorithms as seen in Ref. [2] of the paper of the paper to hadron level with R 0.3 cone labelling for the differential cross-section of $\Delta R$ between the $Z$ boson and the leading $b$-jet in events with $Z (\rightarrow ll) \ge 1 $ b-jets. Systematic errors include Sherpa 2.2.11 and MGaMC+Py8 FxFx uncertainties. See Table 17.

Correction factors from parton level to hadron level for the differential cross-section of the Z boson $p_T$ in events with $Z (\rightarrow ll) \ge 1 $ b-jets. Systematic errors statistical uncertainty of Pythia8 simulations. See Table 12.

Correction factors from parton level to hadron level for the differential cross-section of the Z boson $p_T$ in events with $Z (\rightarrow ll) \ge 1 $ c-jets. Systematic errors include statistical uncertainty of Pythia8 simulations. See Table 13.

Correction factors from parton level to hadron level for the differential cross-section of the leading $b$-jet $p_T$ in events with $Z (\rightarrow ll) \ge 1 $ b-jets. Systematic errors include statistical uncertainty of Pythia8 simulations. See Table 14.

Correction factors from parton level to hadron level for the differential cross-section of the leading $c$-jet $p_T$ in events with $Z (\rightarrow ll) \ge 1 $ c-jets. Systematic errors include statistical uncertainty of Pythia8 simulations. See Table 15.

Correction factors from parton level to hadron level for the differential cross-section of the leading $c$-jet $x_F$ in events with $Z (\rightarrow ll) \ge 1 $ c-jets. Systematic errors include statistical uncertainty of Pythia8 simulations. See Table 16.

Correction factors from parton level to hadron level for the differential cross-section of $\Delta R$ between the $Z$ boson and the leading $b$-jet in events with $Z (\rightarrow ll) \ge 1 $ b-jets. Systematic errors include statistical uncertainty of Pythia8 simulations. See Table 17.

Distributions of representative kinematic variables in the misidentified background-enriched same-sign region: (a) the Higgs boson transverse momentum ($p_\text{T}^H$) in the $WH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ category, (b) the missing transverse momentum (${E_{\mathrm{T}}^{\mathrm{miss}}}$) in the $WH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ category, (c) the radial distance (dR$(\ell,\ell)$) between the two light leptons associated to the $Z\to\ell{}\ell$ decay process in the $ZH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ category, and (d) the invariant mass ($m_{\ell\ell}$) of the two light leptons associated to the $Z\to\ell{}\ell$ decay in the $ZH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ category. The hatched band represents the pre-fit statistical, experimental and theoretical uncertainties. The signal contributions are considered as part of the predictions and are normalized as predicted by the Standard Model.

Post-fit distributions for NN-based analysis of the NN-scores in the $ZH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ (a), $ZH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ (b), $WH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ (c) and $WH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ (d) categories. The hatched band indicates the total post-fit uncertainty of the total predicted yields. The post-fit signal contributions are considered as part of the predictions.

Post-fit distributions for NN-based analysis of the NN-scores in the $ZH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ (a), $ZH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ (b), $WH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ (c) and $WH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ (d) categories. The hatched band indicates the total post-fit uncertainty of the total predicted yields. The post-fit signal contributions are considered as part of the predictions.

Post-fit distributions for NN-based analysis of the NN-scores in the $ZH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ (a), $ZH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ (b), $WH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ (c) and $WH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ (d) categories. The hatched band indicates the total post-fit uncertainty of the total predicted yields. The post-fit signal contributions are considered as part of the predictions.

Post-fit distributions for NN-based analysis of the NN-scores in the $ZH(\\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ (a), $ZH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ (b), $WH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ (c) and $WH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ (d) categories. The hatched band indicates the total post-fit uncertainty of the total predicted yields. The post-fit signal contributions are considered as part of the predictions.

Post-fit yields from the NN-based fit performed with $\mu_{VH}^{\tau\tau}=\mu_{ZH}^{\tau\tau}=\mu_{WH}^{\tau\tau}$. The symbol $-$ is used when no events or $<10^{-2}$ events are present.

Event yields as a function of $\log_{10}(S/B)$ for data, background, and a Higgs boson signal with $m_{H} = 125$ GeV. Final-discriminant bins in all regions are combined into bins of $\log_{10}(S/B)$, where $S$ is the fitted signal and $B$ is the fitted background from the NN-based fit. The Higgs boson signal contribution is shown after re-scaling the SM cross-section according to the value of the signal strength extracted from data ($\mu = 1.28$). In the lower panel, the pull of the data relative to the background-only expectation, evaluated as the difference between the data and the background-only expectation divided by the square-root sum of the data and background statistical uncertainty, is shown. The solid line shows the expected pull in each bin for the best-fit signal value.

The fitted values of the Higgs boson signal strength $\mu_{VH}^{\tau\tau}$ for $m_{H} = 125$ GeV for the $WH$ and $ZH$ processes and their combination from the NN-based fit. The individual $\mu_{VH}^{\tau\tau}$ values for the $(W/Z)H$ processes are obtained from a simultaneous fit with the signal strength for each of the $WH$ and $ZH$ processes floating independently. The probability of compatibility of the individual signal strengths is 56\%.

Post-fit distributions for mass-based analysis for $m_{\mathrm{MMC}}$ in the (a) $ZH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$, (b) $ZH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$, and for $m_{\mathrm{2T}}$ in the (c) $WH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ and (d) $WH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ categories. The hatched band indicates the total post-fit uncertainty of the total predicted yields. The post-fit signal contributions are considered as part of the predictions.

Post-fit distributions for mass-based analysis for $m_{\mathrm{MMC}}$ in the (a) $ZH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$, (b) $ZH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$, and for $m_{\mathrm{2T}}$ in the (c) $WH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ and (d) $WH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ categories. The hatched band indicates the total post-fit uncertainty of the total predicted yields. The post-fit signal contributions are considered as part of the predictions.

Post-fit distributions for mass-based analysis for $m_{\mathrm{MMC}}$ in the (a) $ZH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$, (b) $ZH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$, and for $m_{\mathrm{2T}}$ in the (c) $WH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ and (d) $WH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ categories. The hatched band indicates the total post-fit uncertainty of the total predicted yields. The post-fit signal contributions are considered as part of the predictions.

Post-fit distributions for mass-based analysis for $m_{\mathrm{MMC}}$ in the (a) $ZH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$, (b) $ZH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$, and for $m_{\mathrm{2T}}$ in the (c) $WH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})# and (d) $WH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ categories. The hatched band indicates the total post-fit uncertainty of the total predicted yields. The post-fit signal contributions are considered as part of the predictions.

The fitted values from the NN-based fit of the Higgs boson signal strength $\mu_{VH}^{\tau\tau}$ for $m_{H} = 125$ GeV are shown separately for the $WH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$, $WH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$, $ZH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$, $ZH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ categories, the $WH$ and $ZH$ processes, and their full combination. The individual $\mu_{VH}^{\tau\tau}$ values for the $(W/Z)H$ processes are obtained from a simultaneous fit with the signal strength for each of the $WH$ and $ZH$ processes floating independently.

Summary table with the expected (exp) and observed (obs) values of the $\mu^{\tau\tau}_{\text{VH}}$ and the significance resulting from the mass-based fit.

Event yields as a function of $\log_{10}(S/B)$ for data, background, and a Higgs boson signal with $m_{H} = 125$ GeV. Final-discriminant bins in all regions are combined into bins of $\log_{10}(S/B)$, where $S$ is the fitted signal and $B$ is the fitted background from the NN-based fit. The Higgs boson signal contribution is shown after re-scaling the SM cross-section according to the value of the signal strength extracted from data ($\mu = 1.28$). In the lower panel, the pull of the data relative to the background-only expectation, evaluated as the difference between the data and the background-only expectation divided by the square-root sum of the data and background statistical uncertainty, is shown. The solid line shows the expected pull in each bin for the best-fit signal value.

Summary table with the expected (exp) and observed (obs) values of the $\mu^{\tau\tau}_{\text{VH}}$ and the significance resulting from the mass-based fit.

The fitted values from the mass-based fit of the Higgs boson signal strength $\mu_{VH}^{\tau\tau}$ for $m_{H} = 125$ GeV are shown for the $WH$ and $ZH$ processes and their combination. The individual $\mu_{VH}^{\tau\tau}$ values for the $(W/Z)H$ processes are obtained from a simultaneous fit with the signal strength for each of the $WH$ and $ZH$ processes floating independently. The probability of compatibility of the individual signal strengths is 85\%.

The fitted values from the mass-based fit of the Higgs boson signal strength $\mu_{VH}^{\tau\tau}$ for $m_{H} = 125$ GeV are shown separately for the $WH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$, $WH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$, $ZH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$, $ZH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ categories, the $WH$ and $ZH$ processes, and their full combination. The individual $\mu_{VH}^{\tau\tau}$ values for the $(W/Z)H$ processes are obtained from a simultaneous fit with the signal strength for each of the $WH$ and $ZH$ processes floating independently.

Distributions of $d\phi({E_{\mathrm{T}}^{\mathrm{miss}}},\tau_{1})$ (left) and $\eta$ of the leading $p_\text{T}$ $\tau_{\mathrm{had}-\mathrm{vis}}$ (right) in the $WH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ $Z\to\tau\tau$ validation region. The hatched band represents the pre-fit statistical, experimental and theoretical uncertainties. The signal contributions are considered as part of the predictions.

Distributions of $d\phi({E_{\mathrm{T}}^{\mathrm{miss}}},\tau_{1})$ (left) and $\eta$ of the leading $p_\text{T}$ $\tau_{\mathrm{had}-\mathrm{vis}}$ (right) in the $WH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ $Z\to\tau\tau$ validation region. The hatched band represents the pre-fit statistical, experimental and theoretical uncertainties. The signal contributions are considered as part of the predictions.

Distributions of the radial distance $dR(\tau_{1},\tau_{2})$ between the two $\tau_{\mathrm{had}-\mathrm{vis}}$ (left) and of the ${E_{\mathrm{T}}^{\mathrm{miss}}}$ (right) in the $WH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ $W\mathrm{ +jets}$ validation region. The hatched band represents the pre-fit statistical, experimental and theoretical uncertainties. The signal contributions are considered as part of the predictions.

Distributions of the radial distance $dR(\tau_{1},\tau_{2})$ between the two $\tau_{\mathrm{had}-\mathrm{vis}}$ (left) and of the ${E_{\mathrm{T}}^{\mathrm{miss}}}$ (right) in the $WH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ $W\mathrm{ +jets}$ validation region. The hatched band represents the pre-fit statistical, experimental and theoretical uncertainties. The signal contributions are considered as part of the predictions.

Distributions of the ${m_{\mathrm{MMC}}}$ (left) and of the $p_\text{T}$ of the leading $p_\text{T}$ light lepton (right) in the $WH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ $t\bar{t}$ validation region. The hatched band represents the pre-fit statistical, experimental and theoretical uncertainties. The signal contributions are considered as part of the predictions.

Distributions of the ${m_{\mathrm{MMC}}}$ (left) and of the $p_\text{T}$ of the leading $p_\text{T}$ light lepton (right) in the $WH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ $t\bar{t}$ validation region. The hatched band represents the pre-fit statistical, experimental and theoretical uncertainties. The signal contributions are considered as part of the predictions.

Distributions of the $m_{\mathrm{2T}}$ (left) and of the $\eta$ of the leading $p_\text{T}$ $\tau_{\mathrm{had}-\mathrm{vis}}$ in the $WH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ $Z\to\tau\tau$ validation region. The hatched band represents the pre-fit statistical, experimental and theoretical uncertainties. The signal contributions are considered as part of the predictions.

Distributions of the $m_{\mathrm{2T}}$ (left) and of the $\eta$ of the leading $p_\text{T}$ $\tau_{\mathrm{had}-\mathrm{vis}}$ in the $WH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ $Z\to\tau\tau$ validation region. The hatched band represents the pre-fit statistical, experimental and theoretical uncertainties. The signal contributions are considered as part of the predictions.

Distributions of the $dR({\tau_{\mathrm{lep}}},{\tau_{\mathrm{had}}})$ between the two objects associated to the Higgs boson decay and of the invariant mass $m_{\ell,\ell}$ of the two light leptons in the $WH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ all-same-sign validation region. The hatched band represents the pre-fit statistical, experimental and theoretical uncertainties. The signal contributions are considered as part of the predictions.

Distributions of the $dR({\tau_{\mathrm{lep}}},{\tau_{\mathrm{had}}})$ between the two objects associated to the Higgs boson decay and of the invariant mass $m_{\ell,\ell}$ of the two light leptons in the $WH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ all-same-sign validation region. The hatched band represents the pre-fit statistical, experimental and theoretical uncertainties. The signal contributions are considered as part of the predictions.

Distributions of the NN-score in the signal regions sidebands of the $ZH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ (a), $ZH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ (b), $WH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ (c), $WH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ (d) categories.The hatched band represents the pre-fit statistical, experimental and theoretical uncertainties. The signal contributions are considered as part of the predictions and are normalized to the fit result performed with one parameter of interest.

Distributions of the NN-score in the signal regions sidebands of the $ZH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ (a), $ZH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ (b), $WH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ (c), $WH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ (d) categories.The hatched band represents the pre-fit statistical, experimental and theoretical uncertainties. The signal contributions are considered as part of the predictions and are normalized to the fit result performed with one parameter of interest.

Distributions of the NN-score in the signal regions sidebands of the $ZH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ (a), $ZH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ (b), $WH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ (c), $WH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ (d) categories.The hatched band represents the pre-fit statistical, experimental and theoretical uncertainties. The signal contributions are considered as part of the predictions and are normalized to the fit result performed with one parameter of interest.

Distributions of the NN-score in the signal regions sidebands of the $ZH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ (a), $ZH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ (b), $WH(\tau_{\mathrm{lep}}\tau_{\mathrm{had}})$ (c), $WH(\tau_{\mathrm{had}}\tau_{\mathrm{had}})$ (d) categories.The hatched band represents the pre-fit statistical, experimental and theoretical uncertainties. The signal contributions are considered as part of the predictions and are normalized to the fit result performed with one parameter of interest.

Summary of results for cross-section of non-prompt $\psi(2S)$ decaying to a muon pair for 13 TeV data in fb/GeV. Uncertainties are statistical and systematic, respectively.

Summary of results for non-prompt fraction of $J/\psi$ decaying to a muon pair as a percentage for 13 TeV data. Uncertainties are statistical and systematic, respectively.

Summary of results for non-prompt fraction of $\psi(2S)$ decaying to a muon pair as a percentage for 13 TeV data. Uncertainties are statistical and systematic, respectively.

Summary of results for prompt $\psi(2S)$ over $J/\psi$ ratio as a percentage for 13 TeV data. Uncertainties are statistical and systematic, respectively.

Summary of results for non-prompt $\psi(2S)$ over $J/\psi$ ratio as a percentage for 13 TeV data. Uncertainties are statistical and systematic, respectively.

Correction factors for an assumed angular dependence $\propto 1+\lambda_{\theta} \cos^2\theta $ in the helicity frame, for several values of the parameter $\lambda_{\theta}$. The correction factors were found to be the same (within 1% - 2%) for $J/\psi$ and $\psi(2S)$ mesons, for prompt and non-prompt production mechanisms, and for the three rapidity intervals considered in this paper.

$R_\text{CP}$ plotted as a function of approximated $x_p$ for $-1.0 < y_b < 0.0$ and $0.0 < y^* < 1.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_p$ for $-1.0 < y_b < 0.0$ and $1.0 < y^* < 2.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_p$ for $-1.0 < y_b < 0.0$ and $2.0 < y^* < 3.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_p$ for $0.0 < y_b < 1.0$ and $0.0 < y^* < 1.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_p$ for $0.0 < y_b < 1.0$ and $1.0 < y^* < 2.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_p$ for $0.0 < y_b < 1.0$ and $2.0 < y^* < 4.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_p$ for $1.0 < y_b < 2.0$ and $0.0 < y^* < 1.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_p$ for $1.0 < y_b < 2.0$ and $1.0 < y^* < 2.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_p$ for $1.0 < y_b < 2.0$ and $2.0 < y^* < 3.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_p$ for $2.0 < y_b < 3.0$ and $0.0 < y^* < 1.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_p$ for $2.0 < y_b < 3.0$ and $1.0 < y^* < 2.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_p$ for $3.0 < y_b < 4.0$ and $0.0 < y^* < 1.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_{Pb}$ for $-3.0 < y_b < -2.0$ and $0.0 < y^* < 1.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_{Pb}$ for $-2.0 < y_b < -1.0$ and $0.0 < y^* < 1.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_{Pb}$ for $-2.0 < y_b < -1.0$ and $1.0 < y^* < 2.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_{Pb}$ for $-1.0 < y_b < 0.0$ and $0.0 < y^* < 1.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_{Pb}$ for $-1.0 < y_b < 0.0$ and $1.0 < y^* < 2.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_{Pb}$ for $-1.0 < y_b < 0.0$ and $2.0 < y^* < 3.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_{Pb}$ for $0.0 < y_b < 1.0$ and $0.0 < y^* < 1.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_{Pb}$ for $0.0 < y_b < 1.0$ and $1.0 < y^* < 2.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_{Pb}$ for $0.0 < y_b < 1.0$ and $2.0 < y^* < 4.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_{Pb}$ for $1.0 < y_b < 2.0$ and $0.0 < y^* < 1.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_{Pb}$ for $1.0 < y_b < 2.0$ and $1.0 < y^* < 2.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_{Pb}$ for $1.0 < y_b < 2.0$ and $2.0 < y^* < 3.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_{Pb}$ for $2.0 < y_b < 3.0$ and $0.0 < y^* < 1.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_{Pb}$ for $2.0 < y_b < 3.0$ and $1.0 < y^* < 2.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_{Pb}$ for $3.0 < y_b < 4.0$ and $0.0 < y^* < 1.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_\mathrm{F}$ for $-3.0 < y_b < -2.0$ and $0.0 < y^* < 1.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_\mathrm{F}$ for $-2.0 < y_b < -1.0$ and $0.0 < y^* < 1.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_\mathrm{F}$ for $-2.0 < y_b < -1.0$ and $1.0 < y^* < 2.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_\mathrm{F}$ for $-1.0 < y_b < 0.0$ and $0.0 < y^* < 1.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_\mathrm{F}$ for $-1.0 < y_b < 0.0$ and $1.0 < y^* < 2.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_\mathrm{F}$ for $-1.0 < y_b < 0.0$ and $2.0 < y^* < 3.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_\mathrm{F}$ for $0.0 < y_b < 1.0$ and $0.0 < y^* < 1.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_\mathrm{F}$ for $0.0 < y_b < 1.0$ and $1.0 < y^* < 2.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_\mathrm{F}$ for $0.0 < y_b < 1.0$ and $2.0 < y^* < 4.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_\mathrm{F}$ for $1.0 < y_b < 2.0$ and $0.0 < y^* < 1.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_\mathrm{F}$ for $1.0 < y_b < 2.0$ and $1.0 < y^* < 2.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_\mathrm{F}$ for $1.0 < y_b < 2.0$ and $2.0 < y^* < 3.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_\mathrm{F}$ for $2.0 < y_b < 3.0$ and $0.0 < y^* < 1.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_\mathrm{F}$ for $2.0 < y_b < 3.0$ and $1.0 < y^* < 2.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$R_\text{CP}$ plotted as a function of approximated $x_\mathrm{F}$ for $3.0 < y_b < 4.0$ and $0.0 < y^* < 1.0$, constructed using $\langle y_{\text{b}} \rangle$ and $\langle y^{*} \rangle$. The proton-going direction is defined by $y_{\text{b}} > 0$.

$\langle T_{\text{AB}} \rangle$ normalized per-event dijet yields in $0-10$% collisions as a function of $\langle y_{\text{b}} \rangle$ for $40.0 < p_{\text{T,Avg}} \text{ [GeV]} < 49.6$ and $0.0 < y^{*} < 1.0$.

$\langle T_{\text{AB}} \rangle$ normalized per-event dijet yields in $60-90$% collisions as a function of $\langle y_{\text{b}} \rangle$ for $40.0 < p_{\text{T,Avg}} \text{ [GeV]} < 49.6$ and $0.0 < y^{*} < 1.0$.

$\langle T_{\text{AB}} \rangle$ normalized per-event dijet yields in $0-10$% collisions as a function of $\langle y_{\text{b}} \rangle$ for $49.6 < p_{\text{T,Avg}} \text{ [GeV]} < 61.4$ and $0.0 < y^{*} < 1.0$.

$\langle T_{\text{AB}} \rangle$ normalized per-event dijet yields in $60-90$% collisions as a function of $\langle y_{\text{b}} \rangle$ for $49.6 < p_{\text{T,Avg}} \text{ [GeV]} < 61.4$ and $0.0 < y^{*} < 1.0$.

$\langle T_{\text{AB}} \rangle$ normalized per-event dijet yields in $0-10$% collisions as a function of $\langle y_{\text{b}} \rangle$ for $61.4 < p_{\text{T,Avg}} \text{ [GeV]} < 76.1$ and $0.0 < y^{*} < 1.0$.

$\langle T_{\text{AB}} \rangle$ normalized per-event dijet yields in $60-90$% collisions as a function of $\langle y_{\text{b}} \rangle$ for $61.4 < p_{\text{T,Avg}} \text{ [GeV]} < 76.1$ and $0.0 < y^{*} < 1.0$.

$\langle T_{\text{AB}} \rangle$ normalized per-event dijet yields in $0-10$% collisions as a function of $\langle y_{\text{b}} \rangle$ for $40.0 < p_{\text{T,Avg}} \text{ [GeV]} < 49.6$ and $1.0 < y^{*} < 2.0$.

$\langle T_{\text{AB}} \rangle$ normalized per-event dijet yields in $60-90$% collisions as a function of $\langle y_{\text{b}} \rangle$ for $40.0 < p_{\text{T,Avg}} \text{ [GeV]} < 49.6$ and $1.0 < y^{*} < 2.0$.

$\langle T_{\text{AB}} \rangle$ normalized per-event dijet yields in $0-10$% collisions as a function of $\langle y_{\text{b}} \rangle$ for $49.6 < p_{\text{T,Avg}} \text{ [GeV]} < 61.4$ and $1.0 < y^{*} < 2.0$.

$\langle T_{\text{AB}} \rangle$ normalized per-event dijet yields in $60-90$% collisions as a function of $\langle y_{\text{b}} \rangle$ for $49.6 < p_{\text{T,Avg}} \text{ [GeV]} < 61.4$ and $1.0 < y^{*} < 2.0$.

$\langle T_{\text{AB}} \rangle$ normalized per-event dijet yields in $0-10$% collisions as a function of $\langle y_{\text{b}} \rangle$ for $61.4 < p_{\text{T,Avg}} \text{ [GeV]} < 76.1$ and $1.0 < y^{*} < 2.0$.

$\langle T_{\text{AB}} \rangle$ normalized per-event dijet yields in $60-90$% collisions as a function of $\langle y_{\text{b}} \rangle$ for $61.4 < p_{\text{T,Avg}} \text{ [GeV]} < 76.1$ and $1.0 < y^{*} < 2.0$.

$\langle T_{\text{AB}} \rangle$ normalized per-event dijet yields in $0-10$% collisions as a function of $\langle y_{\text{b}} \rangle$ for $40.0 < p_{\text{T,Avg}} \text{ [GeV]} < 49.6$ and $2.0 < y^{*} < 4.0$.

$\langle T_{\text{AB}} \rangle$ normalized per-event dijet yields in $60-90$% collisions as a function of $\langle y_{\text{b}} \rangle$ for $40.0 < p_{\text{T,Avg}} \text{ [GeV]} < 49.6$ and $2.0 < y^{*} < 4.0$.

$\langle T_{\text{AB}} \rangle$ normalized per-event dijet yields in $0-10$% collisions as a function of $\langle y_{\text{b}} \rangle$ for $49.6 < p_{\text{T,Avg}} \text{ [GeV]} < 61.4$ and $2.0 < y^{*} < 4.0$.

$\langle T_{\text{AB}} \rangle$ normalized per-event dijet yields in $60-90$% collisions as a function of $\langle y_{\text{b}} \rangle$ for $49.6 < p_{\text{T,Avg}} \text{ [GeV]} < 61.4$ and $2.0 < y^{*} < 4.0$.

$\langle T_{\text{AB}} \rangle$ normalized per-event dijet yields in $0-10$% collisions as a function of $\langle y_{\text{b}} \rangle$ for $61.4 < p_{\text{T,Avg}} \text{ [GeV]} < 76.1$ and $2.0 < y^{*} < 4.0$.

$\langle T_{\text{AB}} \rangle$ normalized per-event dijet yields in $60-90$% collisions as a function of $\langle y_{\text{b}} \rangle$ for $61.4 < p_{\text{T,Avg}} \text{ [GeV]} < 76.1$ and $2.0 < y^{*} < 4.0$.

Signal selection efficiency times acceptance for charged Higgs boson with masses between $60\,$GeV to $168\,$GeV. The efficiency times acceptance drops at high masses rapidly due to the low momentum of the $b$-quark produced together with the charged Higgs boson. For the $168\,$GeV mass point the efficiency times acceptance is larger than for the $160\,$GeV mass point due to having a higher probability that the top quark, which decays into the charged Higgs boson and a $b$-quark, is off-shell.

Best fit values of $\mu_{t\bar{t}}$ and $f_{\mathrm{HF}}$ parameters at charged Higgs masses between $60\,$GeV and $168\,$GeV.

Differential cross-section in bins of subleading muon $p_\mathrm{T]$. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

Differential cross-section in bins of leading muon $\eta$. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

Differential cross-section in bins of subleading muon $\eta$. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

Differential cross-section in bins of leading muon $\phi$. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

Differential cross-section in bins of subleading muon $\phi$. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

Differential cross-section in bins of leading charged particle jet $p_\mathrm{T]$. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

Differential cross-section in bins of subleading charged particle jet $p_\mathrm{T]$. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

Differential cross-section in bins of leading charged particle jet rapidity. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

Differential cross-section in bins of subleading charged particle jet rapidity. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

Differential cross-section in bins of leading charged particle jet azimuth. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

Differential cross-section in bins of subleading charged particle jet azimuth. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

Differential cross-section in bins of leading charged particle jet mass. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

Differential cross-section in bins of subleading charged particle jet mass. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

Differential cross-section in bins of leading charged particle jet constituent multiplicity. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

Differential cross-section in bins of subleading charged particle jet constituent multiplicity. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

Differential cross-section in bins of leading charged particle jet $\tau_1$. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

Differential cross-section in bins of subleading charged particle jet $\tau_1$. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

Differential cross-section in bins of leading charged particle jet $\tau_2$. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

Differential cross-section in bins of subleading charged particle jet $\tau_2$. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

Differential cross-section in bins of leading charged particle jet $\tau_3$. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

Differential cross-section in bins of subleading charged particle jet $\tau_3$. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

Differential cross-section in bins of leading charged particle jet $\tau_{21}$. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

Differential cross-section in bins of $\Delta R$ between the leading charged particle jet and the dilepton system. The actual measurement is unbinned and available with examples at <a href="https://gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024">gitlab.cern.ch/atlas-physics/public/sm-z-jets-omnifold-2024</a>

Absolute differential cross-section as a function of RC large-R jet $\tau_{21}$ at particle level in the $\ell$+jets channel. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of RC large-R jet $\tau_{21}$ at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Relative differential cross-section as a function of RC large-R jet $\tau_{21}$ at particle level in the $\ell$+jets channel. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of RC large-R jet $\tau_{3}$ at particle level in the $\ell$+jets channel. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of RC large-R jet $\tau_{3}$ at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Relative differential cross-section as a function of RC large-R jet $\tau_{3}$ at particle level in the $\ell$+jets channel. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of RC large-R jet ECF2 at particle level in the $\ell$+jets channel. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of RC large-R jet ECF2 at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Relative differential cross-section as a function of RC large-R jet ECF2 at particle level in the $\ell$+jets channel. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of RC large-R jet $D_{2}$ at particle level in the $\ell$+jets channel. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of RC large-R jet $D_{2}$ at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Relative differential cross-section as a function of RC large-R jet $D_{2}$ at particle level in the $\ell$+jets channel. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of RC large-R jet $C_{3}$ at particle level in the $\ell$+jets channel. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of RC large-R jet $C_{3}$ at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Relative differential cross-section as a function of RC large-R jet $C_{3}$ at particle level in the $\ell$+jets channel. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of RC large-R jet $p_\mathrm{T}^{d,*}$ (jet $p_T$ dispersion) at particle level in the $\ell$+jets channel. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of RC large-R jet $p_\mathrm{T}^{d,*}$ (jet $p_T$ dispersion) at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Relative differential cross-section as a function of RC large-R jet $p_\mathrm{T}^{d,*}$ (jet $p_T$ dispersion) at particle level in the $\ell$+jets channel. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute differential cross-section as a function of RC large-R jet LHA at particle level in the $\ell$+jets channel. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the Absolute differential cross-section as function of RC large-R jet LHA at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Relative differential cross-section as a function of RC large-R jet LHA at particle level in the $\ell$+jets channel. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of RC large-R jet $D_{2}$ vs $m^{top}$ at particle level in the $\ell$+jets channel in 122.5 GeV < $m^{top}$ < 157.5 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of RC large-R jet $D_{2}$ vs $m^{top}$ at particle level in the $\ell$+jets channel in 157.5 GeV < $m^{top}$ < 187.5 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of RC large-R jet $D_{2}$ vs $m^{top}$ at particle level in the $\ell$+jets channel in 187.5 GeV < $m^{top}$ < 222.5 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix between the Absolute double-differential cross-section as function of RC large-R jet $D_{2}$ vs $m^{top}$ in 122.5 GeV < $m^{top}$ < 157.5 GeV and the Absolute double-differential cross-section as function of RC large-R jet $D_{2}$ vs $m^{top}$ in 122.5 GeV < $m^{top}$ < 157.5 GeV at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Covariance matrix between the Absolute double-differential cross-section as function of RC large-R jet $D_{2}$ vs $m^{top}$ in 157.5 GeV < $m^{top}$ < 187.5 GeV and the Absolute double-differential cross-section as function of RC large-R jet $D_{2}$ vs $m^{top}$ in 122.5 GeV < $m^{top}$ < 157.5 GeV at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Covariance matrix between the Absolute double-differential cross-section as function of RC large-R jet $D_{2}$ vs $m^{top}$ in 157.5 GeV < $m^{top}$ < 187.5 GeV and the Absolute double-differential cross-section as function of RC large-R jet $D_{2}$ vs $m^{top}$ in 157.5 GeV < $m^{top}$ < 187.5 GeV at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Covariance matrix between the Absolute double-differential cross-section as function of RC large-R jet $D_{2}$ vs $m^{top}$ in 187.5 GeV < $m^{top}$ < 222.5 GeV and the Absolute double-differential cross-section as function of RC large-R jet $D_{2}$ vs $m^{top}$ in 122.5 GeV < $m^{top}$ < 157.5 GeV at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Covariance matrix between the Absolute double-differential cross-section as function of RC large-R jet $D_{2}$ vs $m^{top}$ in 187.5 GeV < $m^{top}$ < 222.5 GeV and the Absolute double-differential cross-section as function of RC large-R jet $D_{2}$ vs $m^{top}$ in 157.5 GeV < $m^{top}$ < 187.5 GeV at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Covariance matrix between the Absolute double-differential cross-section as function of RC large-R jet $D_{2}$ vs $m^{top}$ in 187.5 GeV < $m^{top}$ < 222.5 GeV and the Absolute double-differential cross-section as function of RC large-R jet $D_{2}$ vs $m^{top}$ in 187.5 GeV < $m^{top}$ < 222.5 GeV at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Relative double-differential cross-section as a function of RC large-R jet $D_{2}$ vs $m^{top}$ at particle level in the $\ell$+jets channel in 122.5 GeV < $m^{top}$ < 157.5 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Relative double-differential cross-section as a function of RC large-R jet $D_{2}$ vs $m^{top}$ at particle level in the $\ell$+jets channel in 157.5 GeV < $m^{top}$ < 187.5 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Relative double-differential cross-section as a function of RC large-R jet $D_{2}$ vs $m^{top}$ at particle level in the $\ell$+jets channel in 187.5 GeV < $m^{top}$ < 222.5 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of RC large-R jet $\tau_{32}$ vs $m^{top}$ at particle level in the $\ell$+jets channel in 122.5 GeV < $m^{top}$ < 157.5 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of RC large-R jet $\tau_{32}$ vs $m^{top}$ at particle level in the $\ell$+jets channel in 157.5 GeV < $m^{top}$ < 187.5 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of RC large-R jet $\tau_{32}$ vs $m^{top}$ at particle level in the $\ell$+jets channel in 187.5 GeV < $m^{top}$ < 222.5 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix between the Absolute double-differential cross-section as function of RC large-R jet $\tau_{32}$ vs $m^{top}$ in 122.5 GeV < $m^{top}$ < 157.5 GeV and the Absolute double-differential cross-section as function of RC large-R jet $\tau_{32}$ vs $m^{top}$ in 122.5 GeV < $m^{top}$ < 157.5 GeV at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Covariance matrix between the Absolute double-differential cross-section as function of RC large-R jet $\tau_{32}$ vs $m^{top}$ in 157.5 GeV < $m^{top}$ < 187.5 GeV and the Absolute double-differential cross-section as function of RC large-R jet $\tau_{32}$ vs $m^{top}$ in 122.5 GeV < $m^{top}$ < 157.5 GeV at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Covariance matrix between the Absolute double-differential cross-section as function of RC large-R jet $\tau_{32}$ vs $m^{top}$ in 157.5 GeV < $m^{top}$ < 187.5 GeV and the Absolute double-differential cross-section as function of RC large-R jet $\tau_{32}$ vs $m^{top}$ in 157.5 GeV < $m^{top}$ < 187.5 GeV at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Covariance matrix between the Absolute double-differential cross-section as function of RC large-R jet $\tau_{32}$ vs $m^{top}$ in 187.5 GeV < $m^{top}$ < 222.5 GeV and the Absolute double-differential cross-section as function of RC large-R jet $\tau_{32}$ vs $m^{top}$ in 122.5 GeV < $m^{top}$ < 157.5 GeV at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Covariance matrix between the Absolute double-differential cross-section as function of RC large-R jet $\tau_{32}$ vs $m^{top}$ in 187.5 GeV < $m^{top}$ < 222.5 GeV and the Absolute double-differential cross-section as function of RC large-R jet $\tau_{32}$ vs $m^{top}$ in 157.5 GeV < $m^{top}$ < 187.5 GeV at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Covariance matrix between the Absolute double-differential cross-section as function of RC large-R jet $\tau_{32}$ vs $m^{top}$ in 187.5 GeV < $m^{top}$ < 222.5 GeV and the Absolute double-differential cross-section as function of RC large-R jet $\tau_{32}$ vs $m^{top}$ in 187.5 GeV < $m^{top}$ < 222.5 GeV at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Relative double-differential cross-section as a function of RC large-R jet $\tau_{32}$ vs $m^{top}$ at particle level in the $\ell$+jets channel in 122.5 GeV < $m^{top}$ < 157.5 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Relative double-differential cross-section as a function of RC large-R jet $\tau_{32}$ vs $m^{top}$ at particle level in the $\ell$+jets channel in 157.5 GeV < $m^{top}$ < 187.5 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Relative double-differential cross-section as a function of RC large-R jet $\tau_{32}$ vs $m^{top}$ at particle level in the $\ell$+jets channel in 187.5 GeV < $m^{top}$ < 222.5 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of RC large-R jet $\tau_{32}$ vs $p_{T}$ at particle level in the $\ell$+jets channel in 350.0 GeV < $p_{T}$ < 500.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of RC large-R jet $\tau_{32}$ vs $p_{T}$ at particle level in the $\ell$+jets channel in 500.0 GeV < $p_{T}$ < 550.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of RC large-R jet $\tau_{32}$ vs $p_{T}$ at particle level in the $\ell$+jets channel in 550.0 GeV < $p_{T}$ < 650.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of RC large-R jet $\tau_{32}$ vs $p_{T}$ at particle level in the $\ell$+jets channel in 650.0 GeV < $p_{T}$ < 750.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of RC large-R jet $\tau_{32}$ vs $p_{T}$ at particle level in the $\ell$+jets channel in 750.0 GeV < $p_{T}$ < 2000.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix between the Absolute double-differential cross-section as function of RC large-R jet $\tau_{32}$ vs $p_{T}$ in 350.0 GeV < $p_{T}$ < 500.0 GeV and the Absolute double-differential cross-section as function of RC large-R jet $\tau_{32}$ vs $p_{T}$ in 350.0 GeV < $p_{T}$ < 500.0 GeV at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Covariance matrix between the Absolute double-differential cross-section as function of RC large-R jet $\tau_{32}$ vs $p_{T}$ in 500.0 GeV < $p_{T}$ < 550.0 GeV and the Absolute double-differential cross-section as function of RC large-R jet $\tau_{32}$ vs $p_{T}$ in 350.0 GeV < $p_{T}$ < 500.0 GeV at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Covariance matrix between the Absolute double-differential cross-section as function of RC large-R jet $\tau_{32}$ vs $p_{T}$ in 500.0 GeV < $p_{T}$ < 550.0 GeV and the Absolute double-differential cross-section as function of RC large-R jet $\tau_{32}$ vs $p_{T}$ in 500.0 GeV < $p_{T}$ < 550.0 GeV at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Covariance matrix between the Absolute double-differential cross-section as function of RC large-R jet $\tau_{32}$ vs $p_{T}$ in 550.0 GeV < $p_{T}$ < 650.0 GeV and the Absolute double-differential cross-section as function of RC large-R jet $\tau_{32}$ vs $p_{T}$ in 350.0 GeV < $p_{T}$ < 500.0 GeV at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Covariance matrix between the Absolute double-differential cross-section as function of RC large-R jet $\tau_{32}$ vs $p_{T}$ in 550.0 GeV < $p_{T}$ < 650.0 GeV and the Absolute double-differential cross-section as function of RC large-R jet $\tau_{32}$ vs $p_{T}$ in 500.0 GeV < $p_{T}$ < 550.0 GeV at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Covariance matrix between the Absolute double-differential cross-section as function of RC large-R jet $\tau_{32}$ vs $p_{T}$ in 550.0 GeV < $p_{T}$ < 650.0 GeV and the Absolute double-differential cross-section as function of RC large-R jet $\tau_{32}$ vs $p_{T}$ in 550.0 GeV < $p_{T}$ < 650.0 GeV at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Covariance matrix between the Absolute double-differential cross-section as function of RC large-R jet $\tau_{32}$ vs $p_{T}$ in 650.0 GeV < $p_{T}$ < 750.0 GeV and the Absolute double-differential cross-section as function of RC large-R jet $\tau_{32}$ vs $p_{T}$ in 350.0 GeV < $p_{T}$ < 500.0 GeV at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Covariance matrix between the Absolute double-differential cross-section as function of RC large-R jet $\tau_{32}$ vs $p_{T}$ in 650.0 GeV < $p_{T}$ < 750.0 GeV and the Absolute double-differential cross-section as function of RC large-R jet $\tau_{32}$ vs $p_{T}$ in 500.0 GeV < $p_{T}$ < 550.0 GeV at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Covariance matrix between the Absolute double-differential cross-section as function of RC large-R jet $\tau_{32}$ vs $p_{T}$ in 650.0 GeV < $p_{T}$ < 750.0 GeV and the Absolute double-differential cross-section as function of RC large-R jet $\tau_{32}$ vs $p_{T}$ in 550.0 GeV < $p_{T}$ < 650.0 GeV at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Covariance matrix between the Absolute double-differential cross-section as function of RC large-R jet $\tau_{32}$ vs $p_{T}$ in 650.0 GeV < $p_{T}$ < 750.0 GeV and the Absolute double-differential cross-section as function of RC large-R jet $\tau_{32}$ vs $p_{T}$ in 650.0 GeV < $p_{T}$ < 750.0 GeV at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Covariance matrix between the Absolute double-differential cross-section as function of RC large-R jet $\tau_{32}$ vs $p_{T}$ in 750.0 GeV < $p_{T}$ < 2000.0 GeV and the Absolute double-differential cross-section as function of RC large-R jet $\tau_{32}$ vs $p_{T}$ in 350.0 GeV < $p_{T}$ < 500.0 GeV at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Covariance matrix between the Absolute double-differential cross-section as function of RC large-R jet $\tau_{32}$ vs $p_{T}$ in 750.0 GeV < $p_{T}$ < 2000.0 GeV and the Absolute double-differential cross-section as function of RC large-R jet $\tau_{32}$ vs $p_{T}$ in 500.0 GeV < $p_{T}$ < 550.0 GeV at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Covariance matrix between the Absolute double-differential cross-section as function of RC large-R jet $\tau_{32}$ vs $p_{T}$ in 750.0 GeV < $p_{T}$ < 2000.0 GeV and the Absolute double-differential cross-section as function of RC large-R jet $\tau_{32}$ vs $p_{T}$ in 550.0 GeV < $p_{T}$ < 650.0 GeV at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Covariance matrix between the Absolute double-differential cross-section as function of RC large-R jet $\tau_{32}$ vs $p_{T}$ in 750.0 GeV < $p_{T}$ < 2000.0 GeV and the Absolute double-differential cross-section as function of RC large-R jet $\tau_{32}$ vs $p_{T}$ in 650.0 GeV < $p_{T}$ < 750.0 GeV at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Covariance matrix between the Absolute double-differential cross-section as function of RC large-R jet $\tau_{32}$ vs $p_{T}$ in 750.0 GeV < $p_{T}$ < 2000.0 GeV and the Absolute double-differential cross-section as function of RC large-R jet $\tau_{32}$ vs $p_{T}$ in 750.0 GeV < $p_{T}$ < 2000.0 GeV at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Relative double-differential cross-section as a function of RC large-R jet $\tau_{32}$ vs $p_{T}$ at particle level in the $\ell$+jets channel in 350.0 GeV < $p_{T}$ < 500.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Relative double-differential cross-section as a function of RC large-R jet $\tau_{32}$ vs $p_{T}$ at particle level in the $\ell$+jets channel in 500.0 GeV < $p_{T}$ < 550.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Relative double-differential cross-section as a function of RC large-R jet $\tau_{32}$ vs $p_{T}$ at particle level in the $\ell$+jets channel in 550.0 GeV < $p_{T}$ < 650.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Relative double-differential cross-section as a function of RC large-R jet $\tau_{32}$ vs $p_{T}$ at particle level in the $\ell$+jets channel in 650.0 GeV < $p_{T}$ < 750.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Relative double-differential cross-section as a function of RC large-R jet $\tau_{32}$ vs $p_{T}$ at particle level in the $\ell$+jets channel in 750.0 GeV < $p_{T}$ < 2000.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of RC large-R jet $D_{2}$ vs $p_{T}$ at particle level in the $\ell$+jets channel in 350.0 GeV < $p_{T}$ < 500.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of RC large-R jet $D_{2}$ vs $p_{T}$ at particle level in the $\ell$+jets channel in 500.0 GeV < $p_{T}$ < 550.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of RC large-R jet $D_{2}$ vs $p_{T}$ at particle level in the $\ell$+jets channel in 550.0 GeV < $p_{T}$ < 650.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of RC large-R jet $D_{2}$ vs $p_{T}$ at particle level in the $\ell$+jets channel in 650.0 GeV < $p_{T}$ < 750.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Absolute double-differential cross-section as a function of RC large-R jet $D_{2}$ vs $p_{T}$ at particle level in the $\ell$+jets channel in 750.0 GeV < $p_{T}$ < 2000.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix between the Absolute double-differential cross-section as function of RC large-R jet $D_{2}$ vs $p_{T}$ in 350.0 GeV < $p_{T}$ < 500.0 GeV and the Absolute double-differential cross-section as function of RC large-R jet $D_{2}$ vs $p_{T}$ in 350.0 GeV < $p_{T}$ < 500.0 GeV at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Covariance matrix between the Absolute double-differential cross-section as function of RC large-R jet $D_{2}$ vs $p_{T}$ in 500.0 GeV < $p_{T}$ < 550.0 GeV and the Absolute double-differential cross-section as function of RC large-R jet $D_{2}$ vs $p_{T}$ in 350.0 GeV < $p_{T}$ < 500.0 GeV at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Covariance matrix between the Absolute double-differential cross-section as function of RC large-R jet $D_{2}$ vs $p_{T}$ in 500.0 GeV < $p_{T}$ < 550.0 GeV and the Absolute double-differential cross-section as function of RC large-R jet $D_{2}$ vs $p_{T}$ in 500.0 GeV < $p_{T}$ < 550.0 GeV at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Covariance matrix between the Absolute double-differential cross-section as function of RC large-R jet $D_{2}$ vs $p_{T}$ in 550.0 GeV < $p_{T}$ < 650.0 GeV and the Absolute double-differential cross-section as function of RC large-R jet $D_{2}$ vs $p_{T}$ in 350.0 GeV < $p_{T}$ < 500.0 GeV at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Covariance matrix between the Absolute double-differential cross-section as function of RC large-R jet $D_{2}$ vs $p_{T}$ in 550.0 GeV < $p_{T}$ < 650.0 GeV and the Absolute double-differential cross-section as function of RC large-R jet $D_{2}$ vs $p_{T}$ in 500.0 GeV < $p_{T}$ < 550.0 GeV at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Covariance matrix between the Absolute double-differential cross-section as function of RC large-R jet $D_{2}$ vs $p_{T}$ in 550.0 GeV < $p_{T}$ < 650.0 GeV and the Absolute double-differential cross-section as function of RC large-R jet $D_{2}$ vs $p_{T}$ in 550.0 GeV < $p_{T}$ < 650.0 GeV at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Covariance matrix between the Absolute double-differential cross-section as function of RC large-R jet $D_{2}$ vs $p_{T}$ in 650.0 GeV < $p_{T}$ < 750.0 GeV and the Absolute double-differential cross-section as function of RC large-R jet $D_{2}$ vs $p_{T}$ in 350.0 GeV < $p_{T}$ < 500.0 GeV at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Covariance matrix between the Absolute double-differential cross-section as function of RC large-R jet $D_{2}$ vs $p_{T}$ in 650.0 GeV < $p_{T}$ < 750.0 GeV and the Absolute double-differential cross-section as function of RC large-R jet $D_{2}$ vs $p_{T}$ in 500.0 GeV < $p_{T}$ < 550.0 GeV at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Covariance matrix between the Absolute double-differential cross-section as function of RC large-R jet $D_{2}$ vs $p_{T}$ in 650.0 GeV < $p_{T}$ < 750.0 GeV and the Absolute double-differential cross-section as function of RC large-R jet $D_{2}$ vs $p_{T}$ in 550.0 GeV < $p_{T}$ < 650.0 GeV at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Covariance matrix between the Absolute double-differential cross-section as function of RC large-R jet $D_{2}$ vs $p_{T}$ in 650.0 GeV < $p_{T}$ < 750.0 GeV and the Absolute double-differential cross-section as function of RC large-R jet $D_{2}$ vs $p_{T}$ in 650.0 GeV < $p_{T}$ < 750.0 GeV at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Covariance matrix between the Absolute double-differential cross-section as function of RC large-R jet $D_{2}$ vs $p_{T}$ in 750.0 GeV < $p_{T}$ < 2000.0 GeV and the Absolute double-differential cross-section as function of RC large-R jet $D_{2}$ vs $p_{T}$ in 350.0 GeV < $p_{T}$ < 500.0 GeV at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Covariance matrix between the Absolute double-differential cross-section as function of RC large-R jet $D_{2}$ vs $p_{T}$ in 750.0 GeV < $p_{T}$ < 2000.0 GeV and the Absolute double-differential cross-section as function of RC large-R jet $D_{2}$ vs $p_{T}$ in 500.0 GeV < $p_{T}$ < 550.0 GeV at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Covariance matrix between the Absolute double-differential cross-section as function of RC large-R jet $D_{2}$ vs $p_{T}$ in 750.0 GeV < $p_{T}$ < 2000.0 GeV and the Absolute double-differential cross-section as function of RC large-R jet $D_{2}$ vs $p_{T}$ in 550.0 GeV < $p_{T}$ < 650.0 GeV at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Covariance matrix between the Absolute double-differential cross-section as function of RC large-R jet $D_{2}$ vs $p_{T}$ in 750.0 GeV < $p_{T}$ < 2000.0 GeV and the Absolute double-differential cross-section as function of RC large-R jet $D_{2}$ vs $p_{T}$ in 650.0 GeV < $p_{T}$ < 750.0 GeV at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Covariance matrix between the Absolute double-differential cross-section as function of RC large-R jet $D_{2}$ vs $p_{T}$ in 750.0 GeV < $p_{T}$ < 2000.0 GeV and the Absolute double-differential cross-section as function of RC large-R jet $D_{2}$ vs $p_{T}$ in 750.0 GeV < $p_{T}$ < 2000.0 GeV at particle level in the $\ell$+jets channel, accounting for the statistical uncertainty.

Relative double-differential cross-section as a function of RC large-R jet $D_{2}$ vs $p_{T}$ at particle level in the $\ell$+jets channel in 350.0 GeV < $p_{T}$ < 500.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Relative double-differential cross-section as a function of RC large-R jet $D_{2}$ vs $p_{T}$ at particle level in the $\ell$+jets channel in 500.0 GeV < $p_{T}$ < 550.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Relative double-differential cross-section as a function of RC large-R jet $D_{2}$ vs $p_{T}$ at particle level in the $\ell$+jets channel in 550.0 GeV < $p_{T}$ < 650.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Relative double-differential cross-section as a function of RC large-R jet $D_{2}$ vs $p_{T}$ at particle level in the $\ell$+jets channel in 650.0 GeV < $p_{T}$ < 750.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Relative double-differential cross-section as a function of RC large-R jet $D_{2}$ vs $p_{T}$ at particle level in the $\ell$+jets channel in 750.0 GeV < $p_{T}$ < 2000.0 GeV. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

2 sigma band of expected combination limits at 95% CL in the $(m_{a},m_{A})$ plane under the assumption of $sin\theta$ = 0.35.

Observed combination limits at 95% CL in the $(m_{a},m_{A})$ plane under the assumption of $sin\theta$ = 0.7.

Expected combination limits at 95% CL in the $(m_{a},m_{A})$ plane under the assumption of $sin\theta$ = 0.7.

1 sigma band of expected combination limits at 95% CL in the $(m_{a},m_{A})$ plane under the assumption of $sin\theta$ = 0.7.

2 sigma band of expected combination limits at 95% CL in the $(m_{a},m_{A})$ plane under the assumption of $sin\theta$ = 0.7.

Observed limits of H(inv) at 95% CL in the $(m_{a},m_{\chi})$ plane under the assumption of $m_{A}$ = 1.2 TeV, $tan\beta$ = 1.0 and $sin\theta$ = 0.35.

Expected limits of H(inv) at 95% CL in the $(m_{a},m_{\chi})$ plane under the assumption of $m_{A}$ = 1.2 TeV, $tan\beta$ = 1.0 and $sin\theta$ = 0.35.

Observed limits of monoh(bb) at 95% CL in the $(m_{a},m_{\chi})$ plane under the assumption of $m_{A}$ = 1.2 TeV, $tan\beta$ = 1.0 and $sin\theta$ = 0.35.

Expected limits of monoh(bb) at 95% CL in the $(m_{a},m_{\chi})$ plane under the assumption of $m_{A}$ = 1.2 TeV, $tan\beta$ = 1.0 and $sin\theta$ = 0.35.

Observed limits of $h\to aa \to \mu\mu\tau\tau$ at 95% CL in the $(m_{a},m_{\chi})$ plane under the assumption of $m_{A}$ = 1.2 TeV, $tan\beta$ = 1.0 and $sin\theta$ = 0.35. Data points included are corresponding to the lower bound of the exclusion contour. The region above the bound was excluded.

Observed limits of $h\to aa \to bbbb$ at 95% CL in the $(m_{a},m_{\chi})$ plane under the assumption of $m_{A}$ = 1.2 TeV, $tan\beta$ = 1.0 and $sin\theta$ = 0.35. Data points included are corresponding to the lower bound of the exclusion contour. The region above the bound was excluded.

Observed limits of $h\to aa \to bb\mu\mu$ at 95% CL in the $(m_{a},m_{\chi})$ plane under the assumption of $m_{A}$ = 1.2 TeV, $tan\beta$ = 1.0 and $sin\theta$ = 0.35. Data points included are corresponding to the lower bound of the exclusion contour. The region above the bound was excluded.

Observed limits of $h\to aa \to 4 \mu$ at 95% CL in the $(m_{a},m_{\chi})$ plane under the assumption of $m_{A}$ = 1.2 TeV, $tan\beta$ = 1.0 and $sin\theta$ = 0.35. Data points included are corresponding to the lower bound of the exclusion contour. The region above the bound was excluded.

Observed limits of $h\to aa \to 4 \mu$ at 95% CL in the $(m_{a},m_{\chi})$ plane under the assumption of $m_{A}$ = 1.2 TeV, $tan\beta$ = 1.0 and $sin\theta$ = 0.35. Data points included are corresponding to the lower bound of the exclusion contour. The region above the bound was excluded.

Observed limits of $h\to aa \to 4 \mu$ at 95% CL in the $(m_{a},m_{\chi})$ plane under the assumption of $m_{A}$ = 1.2 TeV, $tan\beta$ = 1.0 and $sin\theta$ = 0.35. Data points included are corresponding to the lower bound of the exclusion contour. The region above the bound was excluded.

Observed combination limits at 95% CL in the $(m_{A},tan\beta)$ plane under the assumption of $sin\theta$ = 0.35.

Expected combination limits at 95% CL in the $(m_{A},tan\beta)$ plane under the assumption of $sin\theta$ = 0.35.

1 sigma band of expected combination limits at 95% CL in the $(m_{A},tan\beta)$ plane under the assumption of $sin\theta$ = 0.35.

2 sigma band of expected combination limits at 95% CL in the $(m_{A},tan\beta)$ plane under the assumption of $sin\theta$ = 0.35.

Observed combination limits at 95% CL in the $(m_{A},tan\beta)$ plane under the assumption of $sin\theta$ = 0.7.

Expected combination limits at 95% CL in the $(m_{A},tan\beta)$ plane under the assumption of $sin\theta$ = 0.7.

1 sigma band of expected combination limits at 95% CL in the $(m_{A},tan\beta)$ plane under the assumption of $sin\theta$ = 0.7.

2 sigma band of expected combination limits at 95% CL in the $(m_{A},tan\beta)$ plane under the assumption of $sin\theta$ = 0.7.

Observed combination limits at 95% CL in the $(m_{a},tan\beta)$ plane under the assumption of $sin\theta$ = 0.35.

Expected combination limits at 95% CL in the $(m_{a},tan\beta)$ plane under the assumption of $sin\theta$ = 0.35.

1 sigma band of expected combination limits at 95% CL in the $(m_{a},tan\beta)$ plane under the assumption of $sin\theta$ = 0.35.

2 sigma band of expected combination limits at 95% CL in the $(m_{a},tan\beta)$ plane under the assumption of $sin\theta$ = 0.35.

Observed combination limits at 95% CL in the $(m_{a},tan\beta)$ plane under the assumption of $sin\theta$ = 0.7.

Expected combination limits at 95% CL in the $(m_{a},tan\beta)$ plane under the assumption of $sin\theta$ = 0.7.

1 sigma band of expected combination limits at 95% CL in the $(m_{a},tan\beta)$ plane under the assumption of $sin\theta$ = 0.7.

2 sigma band of expected combination limits at 95% CL in the $(m_{a},tan\beta)$ plane under the assumption of $sin\theta$ = 0.7.

Observed and expected combination limits at 95% CL as a function of $sin\theta$ for the low-mass hypothesis $m_{A}$ = 0.6 TeV, $m_{a}$ = 200 GeV.

Observed and expected combination limits at 95% CL as a function of $sin\theta$ for the high-mass hypothesis $m_{A}$ = 1 TeV, $m_{a}$ = 350 GeV.

Observed and expected combination limits at 95% CL as a function of $m_{\chi}$ following the parameter choices of $m_{A}$ = 1 TeV, $m_{a}$ = 400 GeV.

Table with post-fit yields in the four regions used in the measurement. The correlations of the nuisance parameters, as obtained by the fit, are considered for the calculation of the uncertainties.

Ratio of the $t\bar{t}$ to the $Z$-boson cross section compared to the predictions for several sets of parton distribution functions. The total cross section for $t\bar{t}$ production and the fiducial cross section for $Z$-boson production are used. The uncertainty on the prediction represents the PDF+$\alpha_{s}$ variations.

Nuisance parameter ranking plot for the $t\bar{t}$ signal-strength. Only the 10 most important nuisance parameters are shown. The impact of each nuisance parameter on the measured cross section, is defined as the shift induced in measured cross-section as the nuisance parameter is shifted by its pre-fit and post-fit uncertainties from its nominal best-fit value and then fixed while all other nuisance parameters profiled.

Nuisance parameter ranking plot for the ratio of the $t\bar{t}$ and $Z$-boson signal-strengths. Only the 10 most important nuisance parameters are shown. The impact of each nuisance parameter on the measured ratio, is defined as the shift induced in measured ratio as the nuisance parameter is shifted by its pre-fit and post-fit uncertainties from its nominal best-fit value and then fixed while all other nuisance parameters profiled.

Nuisance parameter ranking plot for the $Z$-boson signal-strength. Only the 10 most important nuisance parameters are shown. The impact of each nuisance parameter on the measured cross section, is defined as the shift induced in measured cross-section as the nuisance parameter is shifted by its pre-fit and post-fit uncertainties from its nominal best-fit value and then fixed while all other nuisance parameters profiled.