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 event yields in $\textrm{SR}$ compared with post-fit expectations from Monte Carlo simulations, as a function of the scalar sum of lepton and jet transverse momenta, $H_{\mathrm{T}}$. The last bin includes overflow events. `Signal (prod.)' and `Signal (dec.)' refer to the single-top-quark production and top-quark pair decay signal contributions, respectively.

Expected and observed 95$\%$ CL upper limits on the branching ratio corresponding to the decay of a top quark to a muon and a tau lepton through a cLFV process for scalar, vector and tensor couplings. In the vector case, all vector operators are assumed to contribute simultaneously with the same effective coupling strength. The table shows the endpoint values of $\mathcal{B}(\mathrm{t}\to\mu\tau\mathrm{u})$ and $\mathcal{B}(\mathrm{t}\to\mu\tau\mathrm{c})$, which are interpolated linearly for each limit.

Expected and observed 95$\%$ CL upper limits on the Wilson coefficients for scalar, vector and tensor couplings of a top quark to a muon and a tau lepton through a cLFV process. In the vector case, all vector operators are assumed to contribute simultaneously with the same effective coupling strength. The table shows the endpoint values of the $|c^{\mu\tau\mathrm{ut}}|$ and $|c^{\mu\tau\mathrm{ct}}|$ Wilson coefficients, which are interpolated assuming a linear relationship between $\mathcal{B}(\mathrm{t}\to\mu\tau\mathrm{u})$ and $\mathcal{B}(\mathrm{t}\to\mu\tau\mathrm{c})$.

Observed event yields in $\textrm{SR}$ compared with pre-fit expectations from Monte Carlo simulations, as a function of the scalar sum of lepton and jet transverse momenta, $H_{\mathrm{T}}$. The last bin includes overflow events. The signal yields represent a leptoquark mass of $m_{S_{1}} = 1$ TeV and a coupling strength of $\lambda^{\textrm{LQ}} = 2.0$.

Observed event yields in $\textrm{SR}$ compared with post-fit expectations from Monte Carlo simulations, as a function of the scalar sum of lepton and jet transverse momenta, $H_{\mathrm{T}}$. The last bin includes overflow events. The signal yields represent a leptoquark mass of $m_{S_{1}} = 1$ TeV and a coupling strength of $\lambda^{\textrm{LQ}} = 2.0$.

Observed and expected exclusion 95$\%$ CL upper limits on the $S_{1}$ leptoquark coupling strength $\lambda^{\textrm{LQ}}$ as a function of LQ mass, $m_{S_{1}}$.

Theoretical cross-sections for single-top-quark production and top-quark decays through cLFV interactions involving vector, scalar and tensor EFT Wilson coefficients. The column titled as $c^{(ijk3)}_{\textrm{vector}}$ represents the individual cross-section contributions from each of $c_{\mathsf{lq}}^{-(ijk3)}$, $c_{\mathsf{eq}}^{(ijk3)}$, $c_{\mathsf{lu}}^{(ijk3)}$ and $c_{\mathsf{eu}}^{(ijk3)}$. The coefficient indices represent the lepton flavour generations ($i,j = 1,2,3$ where $i \neq j$) and light quark flavour generations ($k = 1,2$). The single-top-quark production cross-sections are quoted for $u$- and $c$-quark couplings separately, while they are combined for the $t\bar{t}$ decay process ($q_k = u,c$). The scale and PDF uncertainties are given. The value of each Wilson coefficient is set to 1.0 for the calculation of the cross-section.

Requirements for each analysis region. The symbol $\ell_{3}$ denotes the lowest $p_{\mathrm{T}}$ lepton. In $\mathrm{CR}t\bar{t}\mu$ an additional requirement is placed on the leading muon $p_{\mathrm{T}}$ ($p^{\mu_1}_\mathrm{T}$) and dilepton invariant masses in order to reject signal events.

Post-fit event yields for each analysis region entering the fit, with correlations on the full systematic uncertainties taken into account as determined in the fit under a signal+background hypothesis. The 'fake electron' category in the CR$t\bar{t}\mu$ control region collects small contributions primarily from $t\bar{t}\gamma$ and $Z\gamma$ which enter the event selection due to photon conversions.

Expected and observed 95$\%$ CL upper limits on Wilson coefficients corresponding to 2Q2L EFT operators which could introduce a cLFV top decay in the $\mu\tau$ channel, and existing limits from JHEP04 (2019) 014 (previous). The previous limits shown for $c^{1(ijk3)}_{\mathsf{lequ}}$ and $c^{3(ijk3)}_{\mathsf{lequ}}$ are tightened by a factor of $\sqrt{2}$, as JHEP04 (2019) 014 does not assume that these operators are Hermitian. Results are shown separately for the $\mu\tau ut$ and $\mu\tau ct$ interactions. The lepton generations are denoted by $i,j=2,3$ for $\mu$ and $\tau$ (where $i \neq j$) and the quark generations are denoted by $k=1,2$ for $u$ and $c$, respectively.

Expected and observed 95$\%$ CL upper limits on the branching ratio ($\mathcal{B}$) corresponding to the decay of a top quark to a muon and a $\tau$ lepton through a cLFV process using specific Wilson coefficients corresponding to 2Q2L EFT operators. Results are shown separately for $\mu\tau ut$ and $\mu\tau ct$ interactions. The lepton generations are denoted by $i,j=2,3$ for $\mu$ and $\tau$ (where $i \neq j$) and the quark generations are denoted by $k=1,2$ for $u$ and $c$, respectively.

Expected and observed 95% CL upper limits on the inclusive branching ratio ($\mathcal{B}$) corresponding to the decay of a top quark to a muon and a $\tau$-lepton through a cLFV process. Limits are shown for the statistical uncertainty only and for the full set of statistical and systematic uncertainties.

Expected and observed 95$\%$ CL upper limits on the Wilson coefficients corresponding to EFT operators inducing the decay of a top quark to a muon, a tau lepton and an up quark through a cLFV process ($\mu\tau ut$ interaction).

Expected and observed 95$\%$ CL upper limits on the Wilson coefficients corresponding to EFT operators inducing the decay of a top quark to a muon, a tau lepton and a charm quark through a cLFV process ($\mu\tau ct$ interaction).

Ranking of nuisance parameters by post-fit impact on cLFV signal strength $\mu$ (the parameter of interest, POI). The pre-fit (post-fit) impact of each nuisance parameter is calculated as the difference to the fitted value of cLFV signal strength between the nominal fit and a fit when fixing the corresponding nuisance parameter to $\hat{\theta}\pm\Delta\theta$ ($\hat{\theta}\pm\Delta\hat{\theta}$), where $\hat{\theta}$ is the best-fit value of the nuisance parameter and $\Delta\theta$ ($\Delta\hat{\theta}$) is its pre-fit (post-fit) uncertainty. The pulls of the nuisance parameters are calculated relative to zero. These pulls and their post-fit errors, $\Delta\hat{\theta} / \Delta\theta$, are given in the second column of the table.

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.

Post-fit distributions for the number of jets ($N_{j}$) in CR 1b(-). The QmisID represents the backgrounds with a mis-assigned charge. HF e and HF $\mu$ are the backgrounds with fake/non-prompt leptons. Mat. Conv. and Low $m_{\gamma*}$ are the material and virtual photon conversions.

Post-fit distribution for the difference between the number of positive events and the number of negative events ($N_{+}-N_{-}$) as a function of the number of jets ($N_{j}$) in the sum of four $t\bar{t}W$ CRs and the SR.

Post-fit distributions for the fitted variables in the CRs for the fake/non-prompt lepton background - CR HF e. The QmisID represents the backgrounds with a mis-assigned charge. HF e and HF $\mu$ are the backgrounds with fake/non-prompt leptons. Mat. Conv. and Low $m_{\gamma*}$ are the material and virtual photon conversions.

Post-fit distributions for the fitted variables in the CRs for the fake/non-prompt lepton background - CR HF $\mu$. The QmisID represents the backgrounds with a mis-assigned charge. HF e and HF $\mu$ are the backgrounds with fake/non-prompt leptons. Mat. Conv. and Low $m_{\gamma*}$ are the material and virtual photon conversions.

Post-fit distributions for the fitted variables in the CRs for the fake/non-prompt lepton background - CR Mat. Conv.. The QmisID represents the backgrounds with a mis-assigned charge. HF e and HF $\mu$ are the backgrounds with fake/non-prompt leptons. Mat. Conv. and Low $m_{\gamma*}$ are the material and virtual photon conversions.

Post-fit distributions for the fitted variables in the CRs for the fake/non-prompt lepton background - CR Low $m_{\gamma*}$. The QmisID represents the backgrounds with a mis-assigned charge. HF e and HF $\mu$ are the backgrounds with fake/non-prompt leptons. Mat. Conv. and Low $m_{\gamma*}$ are the material and virtual photon conversions.

Comparison between data and the predictions after a fit to data for the GNN distribution in the SR. The QmisID represents the backgrounds with a mis-assigned charge. HF e and HF $\mu$ are the backgrounds with fake/non-prompt leptons. Mat. Conv. and Low $m_{\gamma*}$ are the material and virtual photon conversions.

Comparison between data and prediction after the fit to data in the signal-enriched region with GNN >= 0.6 for the distributions of the number of jets. The QmisID represents the backgrounds with a mis-assigned charge. HF e and HF $\mu$ are the backgrounds with fake/non-prompt leptons. Mat. Conv. and Low $m_{\gamma*}$ are the material and virtual photon conversions.

Comparison between data and prediction after the fit to data in the signal-enriched region with GNN >= 0.6 for the distributions of the number of b-jets. The QmisID represents the backgrounds with a mis-assigned charge. HF e and HF $\mu$ are the backgrounds with fake/non-prompt leptons. Mat. Conv. and Low $m_{\gamma*}$ are the material and virtual photon conversions.

Comparison between data and prediction after the fit to data in the signal-enriched region with GNN >= 0.6 for the distributions of the sum of the four highest PCBT scores of jets in the event. The QmisID represents the backgrounds with a mis-assigned charge. HF e and HF $\mu$ are the backgrounds with fake/non-prompt leptons. Mat. Conv. and Low $m_{\gamma*}$ are the material and virtual photon conversions.

Comparison between data and prediction after the fit to data in the signal-enriched region with GNN >= 0.6 for the distributions of the sum of transverse momenta over all jets and leptons in the event. The QmisID represents the backgrounds with a mis-assigned charge. HF e and HF $\mu$ are the backgrounds with fake/non-prompt leptons. Mat. Conv. and Low $m_{\gamma*}$ are the material and virtual photon conversions.

Two-dimensional negative log-likelihood contour for the $t\bar{t}t$ cross section ($\sigma_{t\bar{t}t}$) versus the $t\bar{t}t\bar{t}$ cross section ($\sigma_{t\bar{t}t\bar{t}}$) when the normalisation of both processes are treated as free parameters in the fit.

The negative log-likelihood values as a function of the Higgs oblique parameter $\hat{H}$.

The measured and expected cross-sections of $t\bar{t}t\bar{t}$ production.

Observed 68% CL Limit Contour in $\kappa_t,\alpha$ with $t\bar tt\bar t$ parameterized as a function of $\kappa_t,\alpha$, and the $t\bar tH$ parameterization profiled. This is the lower part of the contour.

Observed 68% CL Limit Contour in $\kappa_t,\alpha$ with $t\bar tt\bar t$ parameterized as a function of $\kappa_t,\alpha$, and the $t\bar tH$ parameterization profiled. This is the upper part of the contour.

Observed 95% CL Limit Contour in $\kappa_t,\alpha$ with $t\bar tt\bar t$ parameterized as a function of $\kappa_t,\alpha$, and the $t\bar tH$ parameterization profiled.

Expected 68% CL Limit Contour in $\kappa_t,\alpha$ with $t\bar tt\bar t$ parameterized as a function of $\kappa_t,\alpha$, and the $t\bar tH$ parameterization profiled.

Expected 95% CL Limit Contour in $\kappa_t,\alpha$ with $t\bar tt\bar t$ parameterized as a function of $\kappa_t,\alpha$, and the $t\bar tH$ parameterization profiled.

Observed 68% CL Limit Contour in $\kappa_t,\alpha$ with $t\bar tt\bar t$ parameterized as a function of $\kappa_t,\alpha$, and the $t\bar tH$ parameterization profiled. This is the lower part of the contour.

Observed 68% CL Limit Contour in $\kappa_t,\alpha$ with $t\bar tt\bar t$ parameterized as a function of $\kappa_t,\alpha$, and the $t\bar tH$ parameterization profiled. This is the upper part of the contour.

Observed 95% CL Limit Contour in $\kappa_t,\alpha$ with $t\bar tt\bar t$ parameterized as a function of $\kappa_t,\alpha$, and the $t\bar tH$ parameterization profiled.

Expected 68% CL Limit Contour in $\kappa_t,\alpha$ with $t\bar tt\bar t$ parameterized as a function of $\kappa_t,\alpha$, and the $t\bar tH$ parameterization profiled.

Expected 95% CL Limit Contour in $\kappa_t,\alpha$ with $t\bar tt\bar t$ parameterized as a function of $\kappa_t,\alpha$, and the $t\bar tH$ parameterization profiled.

Distribution of the NN output in the $\geq$1fj$\,$SR in data and the expected contribution of the signal and background processes after the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions considering the correlations of the uncertainties as obtained by the fit.

Distribution of the NN output in the $t\bar{t}\gamma\,$CR in data and the expected contribution of the signal and background processes after the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions considering the correlations of the uncertainties as obtained by the fit.

Total event yield in the $W\gamma\,$CR in data and the expected contribution of the signal and background processes after the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions considering the correlations of the uncertainties as obtained by the fit.

Distribution of the scalar sum of the jet transverse momenta in the 0fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions. The first and last bins include the underflow and overflow, respectively.

Distribution of the $\eta$ of the $b$-tagged jet in the 0fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions.

Distribution of the reconstructed top-quark mass in the 0fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions. The first and last bins include the underflow and overflow, respectively.

Distribution of the $p_{\mathrm{T}}$ of the top-quark+photon system in the 0fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions and the last bin includes the overflow.

Distribution of the photon $p_{\mathrm{T}}$ in the 0fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions and the last bin includes the overflow.

Distribution of the photon $\eta$ in the 0fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions.

Distribution of the scalar sum of the jet transverse momenta in the $\geq$1fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions and the last bin includes the overflow.

Distribution of the invariant mass of the $b$-tagged jet and the highest-$p_{\mathrm{T}}$ forward jet in the $\geq$1fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions and the last bin includes the overflow.

Distribution of $p_{\mathrm{T}}$ of the highest-$p_{\mathrm{T}}$ forward jet in the $\geq$1fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions and the last bin includes the overflow.

Distribution of the difference in $\eta$ between the highest-$p_{\mathrm{T}}$ forward jet and the photon in the $\geq$1fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions and the last bin includes the overflow.

Distribution of the energy of the system formed by the highest-$p_{\mathrm{T}}$ forward jet and the photon in the $\geq$1fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions. The first and last bins include the underflow and overflow, respectively.

Distribution of the $\eta$ of the $b$-tagged jet in the $\geq$1fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions.

Distribution of the reconstructed top-quark mass in the $\geq$1fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions. The first and last bins include the underflow and overflow, respectively.

Distribution of the $p_{\mathrm{T}}$ of the top-quark and photon system in the $\geq$1fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions and the last bin includes the overflow.

Distribution of the photon $p_{\mathrm{T}}$ in the $\geq$1fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions and the last bin includes the overflow.

Distribution of the photon $\eta$ in the $\geq$1fj$\,$SR in data and for the sum of all processes expectations before the profile-likelihood fit. The "Total" column corresponds to the sum of the expected contributions from the signal and background processes. The uncertainty represents the sum of statistical and systematic uncertainties in the signal and background predictions.

Ordered list of the 30 systematic uncertainties with the largest impact on the measured signal normalisation in the fit to data in the parton-level measurement considered as nuisance parameters (NPs) in the profile-likelihood fit. The column "NP value, error" corresponds to the nominal best-fit values and the corresponding uncertainties. The impact of each NP, $\Delta\sigma$/$\sigma_{\mathrm{pred}}$, is computed by comparing the nominal best-fit value of the POI ($\sigma$/$\sigma_{\mathrm{pred}}$) with the result of the fits when fixing the considered NP to its best-fit value shifted by its pre-fit and post-fit uncertainties. The corresponding impacts are listed in the "POI impact prefit high/low" and "POI impact high/low" columns, respectively. The "MC stat." NPs represent the MC statistical uncertainty and they enter the likelihood with a Poisson term, while all the other NPs enter the likelihood via a Gaussian term.

Ordered list of the 30 systematic uncertainties with the largest impact on the measured signal normalisation in the fit to data in the particle-level measurement considered as nuisance parameters (NPs) in the profile-likelihood fit. The column "NP value, error" corresponds to the nominal best-fit values and the corresponding uncertainties. The impact of each NP, $\Delta\sigma$/$\sigma_{\mathrm{pred}}$, is computed by comparing the nominal best-fit value of the POI ($\sigma$/$\sigma_{\mathrm{pred}}$) with the result of the fits when fixing the considered NP to its best-fit value shifted by its pre-fit and post-fit uncertainties. The corresponding impacts are listed in the "POI impact prefit high/low" and "POI impact high/low" columns, respectively. The "MC stat." NPs represent the MC statistical uncertainty and they enter the likelihood with a Poisson term, while all the other NPs enter the likelihood via a Gaussian term.

This table lists the kinematic requirements on parton-level objects used to define of the fiducial phase space for the parton-level measurement. Frixione isolation ($\href{https://arxiv.org/abs/hep-ph/9801442}{\text{hep-ph/9801442}}$) with a chosen radius of $\Delta R = 0.2$ is applied to photons ($\gamma$). The measured fiducial parton-level cross section is $\sigma_{tq\gamma}\times\mathcal{B}(t\rightarrow l\nu b) = 688\pm 23(\text{stat.})^{+75}_{-71}(\text{syst.})\,$fb.

This table lists the kinematic requirements on particle-level objects used to define of the fiducial phase space for the particle-level measurement. The particle level objects are photons ($\gamma$) not from a hadron decay, neutrinos not from a hadron decay ($\nu$), prompt electrons and muons ($\ell$) "dressed" by adding close-by ($\Delta R < 0.1$) photons, and anti-$k_t$ $R = 0.4$ jets built from stable particles ($\tau > 30\,$ps) and tau leptons excluding neutrinos and prompt dressed muons. Jets are $b$-tagged ($b$-jet) using ghost-matched $b$-hadrons with $p_{\text{T}} > 5\,$GeV. Apart from the kinematic requirements, isolation and overlap removal criteria are applied. Jets within $\Delta R = 0.4$ of a photon are removed if the $p_{\text{T}}$ of charged particles within $\Delta R = 0.3$ of the photon is smaller than $10\,\%$ of its $p_{\text{T}}$. Jets within $\Delta R = 0.4$ of a lepton are removed. Events are removed where a photon is close ($\Delta R < 0.4$) to a lepton or a surviving jet. The measured fiducial particle-level cross section is $\sigma_{tq\gamma}\times\mathcal{B}(t\rightarrow l\nu b)+\sigma_{t(\rightarrow l\nu b\gamma)q} = 303\pm 9(\text{stat.})^{+33}_{-32}(\text{syst.})\,$fb.

Comparison between data and background prediction before the fit (Pre-Fit) for the mass of the FCNC top-quark candidate in SR1. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The four FCNC LH signals are also shown separately, normalized to five times the cross-section corresponding to the most stringent observed branching ratio limits. The first (last) bin in all distributions includes the underflow (overflow). The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction before the fit (Pre-Fit) for the mass of the SM top-quark candidate in SR2. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The four FCNC LH signals are also shown separately, normalized to five times the cross-section corresponding to the most stringent observed branching ratio limits. The first (last) bin in all distributions includes the underflow (overflow). The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction before the fit (Pre-Fit) for the transverse momentum of the Z boson candidate in SR2. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The four FCNC LH signals are also shown separately, normalized to five times the cross-section corresponding to the most stringent observed branching ratio limits. The first (last) bin in all distributions includes the underflow (overflow). The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZu LH coupling extraction. The distribution is for the $D_{1}$ discriminant in the mass sideband CR1. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZu LH signals are also separately shown, normalized to 500 times the best fit of the signal yield. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZu LH coupling extraction. The distribution is for the $D_{2}^{u}$ discriminant in the mass sideband CR2. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZu LH signals are also separately shown, normalized to 500 times the best fit of the signal yield. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZu LH coupling extraction. The distribution is for the $D_{1}$ discriminant in SR1. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZu LH signals are also separately shown, normalized to 50 times the best fit of the signal yield. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZu LH coupling extraction. The distribution is for the $D_{2}^{u}$ discriminant in SR2. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZu LH signals are also separately shown, normalized to 50 times the best fit of the signal yield. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZc LH coupling extraction. The distribution is for the $D_{1}$ discriminant in the mass sideband CR1. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZc LH signals are also separately shown, normalized to 500 times the best fit of the signal yield. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZc LH coupling extraction. The distribution is for the $D_{2}^{c}$ discriminant in the mass sideband CR2. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZc LH signals are also separately shown, normalized to 500 times the best fit of the signal yield. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZc LH coupling extraction. The distribution is for the $D_{1}$ discriminant in SR1. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZc LH signals are also separately shown, normalized to 50 times the best fit of the signal yield. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZc LH coupling extraction. The distribution is for the $D_{2}^{c}$ discriminant in SR2. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZc LH signals are also separately shown, normalized to 50 times the best fit of the signal yield. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZu LH coupling extraction. The distribution is for the leading lepton $p_{T}$ in the $t\bar{t}$ CR. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZu LH signals are also shown separately, normalized to $10^{3}$ times the best fit of the signal yield. The last bin includes the overflow. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZu LH coupling extraction. The distribution is for the third lepton $p_{T}$ in the $t\bar{t}$ CR. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZu LH signals are also shown separately, normalized to $10^{3}$ times the best fit of the signal yield. The last bin includes the overflow. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZu LH coupling extraction. The distribution is for the leading lepton $p_{T}$ in the $t\bar{t}Z$ CR. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZu LH signals are also shown separately, normalized to $10^{3}$ times the best fit of the signal yield. The last bin includes the overflow. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Comparison between data and background prediction after the fit to data (Post-Fit) for the FCNC tZu LH coupling extraction. The distribution is for the $D_{1}$ discriminant in the $t\bar{t}Z$ CR. The uncertainty band includes both the statistical and systematic uncertainties in the background prediction. The FCNC tZu LH signals are also shown separately, normalized to $10^{3}$ times the best fit of the signal yield. The lower panels show the ratios of the data (Data) to the background prediction (Bkg.).

Correlation matrix of all the parameters including nuisance parameters used in the profile likelihood unfolding fit on $A_{C}$.

Distribution of ${E}_{T}^{miss}$ after the fit of the multijet backgrounds, in the electron channel, in the $t\bar{t}$ 3-jets VR, without applying the cut on ${E}_{T}^{miss}$. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit. The last bin includes the overflow. The uncertainty band indicates the simulation's statistical uncertainty, the normalisation uncertainties for different processes ($40$ % for $W$+jets production, $30$ % for multijet background and $6$ % for top-quark processes) and the multijet background shape uncertainty in each bin, summed in quadrature. The lower panel of the figure shows the ratio of the data to the prediction.

Distribution of ${E}_{T}^{miss}$ after the fit of the multijet backgrounds, in the electron channel, in the $t\bar{t}$ 4-jets VR, without applying the cut on ${E}_{T}^{miss}$. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit. The last bin includes the overflow. The uncertainty band indicates the simulation's statistical uncertainty, the normalisation uncertainties for different processes ($40$ % for $W$+jets production, $30$ % for multijet background and $6$ % for top-quark processes) and the multijet background shape uncertainty in each bin, summed in quadrature. The lower panel of the figure shows the ratio of the data to the prediction.

Distribution of $m_{T}^{W}$ after the fit of the multijet backgrounds, in the muon channel, in the signal region, without applying the cut on $m_{T}^{W}$. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit. The last bin includes the overflow. The uncertainty band indicates the simulation's statistical uncertainty, the normalisation uncertainties for different processes ($40$ % for $W$+jets production, $30$ % for multijet background and $6$ % for top-quark processes) and the multijet background shape uncertainty in each bin, summed in quadrature. The lower panel of the figure shows the ratio of the data to the prediction.

Distribution of $m_{T}^{W}$ after the fit of the multijet backgrounds, in the muon channel, in the $W$+jets VR, without applying the cut on $m_{T}^{W}$. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit. The last bin includes the overflow. The uncertainty band indicates the simulation's statistical uncertainty, the normalisation uncertainties for different processes ($40$ % for $W$+jets production, $30$ % for multijet background and $6$ % for top-quark processes) and the multijet background shape uncertainty in each bin, summed in quadrature. The lower panel of the figure shows the ratio of the data to the prediction.

Distribution of $m_{T}^{W}$ after the fit of the multijet backgrounds, in the muon channel, in the $t\bar{t}$ 3-jets VR, without applying the cut on $m_{T}^{W}$. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit. The last bin includes the overflow. The uncertainty band indicates the simulation's statistical uncertainty, the normalisation uncertainties for different processes ($40$ % for $W$+jets production, $30$ % for multijet background and $6$ % for top-quark processes) and the multijet background shape uncertainty in each bin, summed in quadrature. The lower panel of the figure shows the ratio of the data to the prediction.

Distribution of $m_{T}^{W}$ after the fit of the multijet backgrounds, in the muon channel, in the $t\bar{t}$ 4-jets VR, without applying the cut on $m_{T}^{W}$. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit. The last bin includes the overflow. The uncertainty band indicates the simulation's statistical uncertainty, the normalisation uncertainties for different processes ($40$ % for $W$+jets production, $30$ % for multijet background and $6$ % for top-quark processes) and the multijet background shape uncertainty in each bin, summed in quadrature. The lower panel of the figure shows the ratio of the data to the prediction.

Expected distributions of the MEM discriminant $P(S|X)$ in the SR, for the s-channel single-top signal, and for the $t\bar{t}$ and $W$+jets backgrounds, for MEM discriminant values larger than $2.0\times10^{-4}$. Each distribution is normalised to unity. The binning is the same as the optimised binning used in the signal extraction fit, resulting in a non-linear horizontal scale.

Distribution of the MEM discriminant $P(S|X)$ in the $W$+jets VR. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit presented in Section 5 in the paper. The uncertainty band indicates the simulation's statistical uncertainty and the normalisation uncertainties for the various processes in each bin, summed in quadrature. The ratio of the observed number to the predicted number of events in each bin is shown in the lower panel of the figure, with different vertical axis ranges. The binning is the same as the optimised binning used in the signal extraction fit described in Section 8 in the paper, resulting in a non-linear horizontal scale.

Distribution of the MEM discriminant $P(S|X)$ in the $t\bar{t}$ 3-jets VR. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit presented in Section 5 in the paper. The uncertainty band indicates the simulation's statistical uncertainty and the normalisation uncertainties for the various processes in each bin, summed in quadrature. The ratio of the observed number to the predicted number of events in each bin is shown in the lower panel of the figure, with different vertical axis ranges. The binning is the same as the optimised binning used in the signal extraction fit described in Section 8 in the paper, resulting in a non-linear horizontal scale.

Distribution of the MEM discriminant $P(S|X)$ in the $t\bar{t}$ 4-jets VR. Simulated events are normalised to the expected number of events given the integrated luminosity, after applying the normalisation factors obtained in the multijet fit presented in Section 5 in the paper. The uncertainty bands indicate the simulation's statistical uncertainty and the normalisation uncertainties for the various processes in each bin, summed in quadrature. The ratio of the observed number to the predicted number of events in each bin is shown in the lower panel of the figure, with different vertical axis ranges. The binning is the same as the optimised binning used in the signal extraction fit described in Section 8 in the paper, resulting in a non-linear horizontal scale.

Distribution of the MEM discriminant $P(S|X)$ in the SR before the fit to data, for MEM discriminant values larger than $2.0\times10^{-4}$. The lower panel of the figure shows the ratio of the data to the prediction, with different vertical axis ranges. The uncertainty band indicates the total uncertainties and their correlations in each bin. The uncertainties in the $t\bar{t}$ and $W$+jets normalisation factors, as well as in the s-channel signal cross-section, are not defined pre-fit and therefore not included. The binning is the same as the optimised binning used in the fit, resulting in a non-linear horizontal scale.

Distribution of the MEM discriminant $P(S|X)$ in the SR after the fit to data, for MEM discriminant values larger than $2.0\times10^{-4}$. The lower panel of the figure shows the ratio of the data to the prediction, with different vertical axis ranges. The uncertainty band indicates the total uncertainties and their correlations in each bin. The binning is the same as the optimised binning used in the fit, resulting in a non-linear horizontal scale.

Distribution of the MEM discriminant $P(S|X)$ in the SR after the fit to data, for MEM discriminant values larger than $2.0\times10^{-4}$, after subtraction of all backgrounds. The fitted distribution for the simulation of the signal is shown together with the post-fit uncertainty in the backgrounds. The binning is the same as the optimised binning used in the fit, resulting in a non-linear horizontal scale.

Pre-fit and post-fit event yields in the SR, for MEM discriminant values larger than $2.0\times10^{-4}$. The central value of the event yield for each process is calculated by summing the values of the discriminant bin contents, using the nominal expected yield for the pre-fit value, and the best-fit estimate for the post-fit value. The error includes statistical and systematic uncertainties summed in quadrature. All sources of systematic uncertainties are included, taking into account correlations and anti-correlations in the post-fit case. The uncertainties in the $t\bar{t}$ and $W$+jets normalisation factors, as well as in the s-channel signal cross-section, are not defined pre-fit and therefore only included in the post-fit uncertainties.

Observed impact of the different sources of uncertainty on the measured s-channel signal cross-section, grouped by categories. The impact of each category is obtained by repeating the fit after having fixed the set of nuisance parameters corresponding to that category, subtracting the square of the resulting uncertainty from the square of the uncertainty found in the full fit, and calculating the square root. The 'Systematic uncertainties' category combines all sources of systematic uncertainties. The statistical uncertainty is obtained by repeating the fit after having fixed all nuisance parameters, including the $t\bar{t}$ and $W$+jets normalisation factors. 'Total' gives the total uncertainty on the measurement.

Observed impact of the different sources of $t\bar{t}$ modelling uncertainty on the measured s-channel signal cross-section. The impact of each category is obtained by repeating the fit after having fixed the set of nuisance parameters corresponding to that category, subtracting the square of the resulting uncertainty from the square of the uncertainty found in the full fit, and calculating the square root. 'PS & had.' refers to the parton shower and hadronisation model, and 'ME/PS matching' to the matching of the ME to the parton shower.

Observed impact of the different sources of s-channel modelling uncertainty on the measured s-channel signal cross-section. The impact of each category is obtained by repeating the fit after having fixed the set of nuisance parameters corresponding to that category, subtracting the square of the resulting uncertainty from the square of the uncertainty found in the full fit, and calculating the square root. 'PS & had.' refers to the parton shower and hadronisation model, as described in Section 7 in the paper.

Observed impact of the different sources of t-channel modelling uncertainty on the measured s-channel signal cross-section. The impact of each category is obtained by repeating the fit after having fixed the set of nuisance parameters corresponding to that category, subtracting the square of the resulting uncertainty from the square of the uncertainty found in the full fit, and calculating the square root. 'PS & had.' refers to the parton shower and hadronisation model, as described in Section 7 in the paper.

Observed impact of the different sources of $tW$ modelling uncertainty on the measured s-channel signal cross-section, grouped by categories. The impact of each category is obtained by repeating the fit after having fixed the set of nuisance parameters corresponding to that category, subtracting the square of the resulting uncertainty from the square of the uncertainty found in the full fit, and calculating the square root. 'PS & had.' refers to the parton shower and hadronisation model, and '$t\bar{t}$ overlap' to the algorithm removing the overlap between $tW$ and $t\bar{t}$ production at NLO, as described in Section 7 in the paper.

Observed impact of the different sources of PDF uncertainties on the measured s-channel signal cross-section, grouped by categories. The impact of each category is obtained by repeating the fit after having fixed the set of nuisance parameters corresponding to that category, subtracting the square of the resulting uncertainty from the square of the uncertainty found in the full fit, and calculating the square root.

Comparison between data and prediction after the fit to data in the signal region for the leading-jet $p_{T}$. The last bin includes the overflow. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.

Comparison between data and prediction after the fit to data in the signal region for the leading-jet $\eta$. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.

Comparison between data and prediction after the fit to data in the signal region for the subleading-jet $p_{T}$. The last bin includes the overflow. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.

Comparison between data and prediction after the fit to data in the signal region for the subleading-jet $\eta$. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.

Comparison between data and prediction after the fit to data in the signal region for the lepton $p_{T}$. The last bin includes the overflow. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.

Comparison between data and prediction after the fit to data in the signal region for the lepton $\eta$. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.

Comparison between data and prediction after the fit to data in the signal region for the ${E}_{T}^{miss}$. The last bin includes the overflow. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.

Comparison between data and prediction after the fit to data in the signal region for the $m_{T}^{W}$. The last bin includes the overflow. The uncertainty band includes all uncertainties and their correlations. The lower panel of the figure shows the ratio of the data to the prediction.

Nuisance parameters ranked according to their post-fit impacts on the best-fit value of the ratio $\mu$ of the measured cross-section to the predicted cross-section. In the figure, only the 20 nuisance parameters with the largest post-fit impacts are shown. The empty (solid) blue rectangles illustrate the pre-fit (post-fit) impact on $\mu$, corresponding to the upper axis. The pre-fit (post-fit) impact of each nuisance parameter, $\Delta\mu$, is calculated as the difference in the fitted value of $\mu$ between the nominal fit and the fit when fixing the corresponding nuisance parameter to $\hat{\theta}\pm\Delta\theta$ ($\hat{\theta}\pm\Delta\hat{\theta}$), where $\hat{\theta}$ is the best-fit value of the nuisance parameter and $\Delta\theta$ ($\Delta\hat{\theta}$) is its pre-fit (post-fit) uncertainty. Several systematic uncertainties are split into different nuisance parameters, which are indicated by NP. JES (JER) indicates jet energy scale (resolution), and $\gamma$ indicates a nuisance parameter associated to the MC statistics in one of the 18 bins numbered from 0 to 17. The black points show the best-fit values of the nuisance parameters, with the error bars representing the post-fit uncertainties. Each nuisance parameter is shown wrt. its nominal value, $\theta_0$, and in units of its pre-fit uncertainty, except the free-floating normalisation factors of the $t\bar{t}$ and $W$+jets backgrounds, and the parameters associated to the MC statistics in each bin, for which the post-fit values and uncertainties are shown.

Correlation matrix of the nuisance parameters and of the ratio $\mu$ of the measured cross-section to the predicted cross-section. The correlations are given after the fit to data. In the figure, only the parameters which have a correlation of at least 0.2 with any other parameter are shown.

Distribution of the MEM discriminant $P(S|X)$ in the SR for MEM discriminant values larger than $2.0\times10^{-4}$, for the collision data used for the measurement, and for 1000 pseudo-data replicas, generated using a bootstrapping technique, in order to assess the statistical correlations between this measurement and others, for the purpose of combinations. The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the <a href="https://zenodo.org/record/5361038">BootstrapGenerator</a> software package , which implements a technique described in <a href="https://cds.cern.ch/record/2759945/">ATL-PHYS-PUB-2021-011</a>. The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. Each pseudo-data replica is assigned an index, ranging from 0 to 999, corresponding to the random number index used consistently for each observed data event.

Measured values of the signal cross-section and of the $t\bar{t}$ and $W$+jets normalisation factors, obtained by statistical-only fits to the collision data used for the measurement, and to 1000 pseudo-data replicas, generated using a bootstrapping technique, in order to assess the statistical correlations between this measurement and others, for the purpose of combinations. The central values and their statistical uncertainties are obtained by repeating the fit after having fixed all nuisance parameters, except the $t\bar{t}$ and $W$+jets normalisation factors, which are let free-floating (unlike for the statistical uncertainty on the cross-section quoted in the paper). The replicas are obtained by reweighting each observed data event by a random integer generated according to Poisson statistics, using the <a href="https://zenodo.org/record/5361038">BootstrapGenerator</a> software package , which implements a technique described in <a href="https://cds.cern.ch/record/2759945/">ATL-PHYS-PUB-2021-011</a>. The ATLAS event number and run number of each event are used as seed to uniquely but reproducibly initialise the random number generator for each event. Each pseudo-data replica is assigned an index, ranging from 0 to 999, corresponding to the random number index used consistently for each observed data event.

Correlation matrix for the individual sources of systematic uncertainty considered in the analysis, for the combined opposite sign (OS) and same sign (SS) binned-template profile likelihood fit to data. The OS or SS refers to the charge signs of the primary lepton and the soft muon. The gamma parameters are NPs used to describe the effect of the limited statistics of the samples.

The unfolded differential charge asymmetry as a function of the transverse momentum of the top pair system. The measured values are given with statistical and systematic uncertainties. The SM theory predictions calculated at NNLO in QCD and NLO in EW theory are listed. The scale uncertainty is obtained by varying renormalisation and factorisation scales independently by a factor of 2 or 0.5 around $\mu_0$ to calculate the maximum and minimum value of the asymmetry, respectively. The nominal value $\mu_0$ is chosen as $H_T/4$. The variations in which one scale is multiplied by 2 while the other scale is divided by 2 are excluded. Finally, the scale and MC integration uncertainties are added in quadrature.

The unfolded differential charge asymmetry as a function of the longitudinal boost of the top pair system. The measured values are given with statistical and systematic uncertainties. The SM theory predictions calculated at NNLO in QCD and NLO in EW theory are listed. The scale uncertainty is obtained by varying renormalisation and factorisation scales independently by a factor of 2 or 0.5 around $\mu_0$ to calculate the maximum and minimum value of the asymmetry, respectively. The nominal value $\mu_0$ is chosen as $H_T/4$. The variations in which one scale is multiplied by 2 while the other scale is divided by 2 are excluded. Finally, the scale and MC integration uncertainties are added in quadrature.

The unfolded inclusive leptonic asymmetry. The unfolded $A_C^{\ell\bar{\ell}}$ is obtained in the reduced phase-space defined by the requirement $|\Delta |\eta_{\ell\bar{\ell}}||<2.5$. The measured values are given with statistical and systematic uncertainties. The SM theory predictions calculated at NLO in QCD and NLO in EW theory are listed. The theory uncertainty is obtained by varying both scales by a factor of 0.5 or 2.0 to calculate the minimum and maximum value of the asymmetry, respectively.

The unfolded differential leptonic asymmetry as a function of the invariant mass of the di-lepton pair. The unfolded $A_C^{\ell\bar{\ell}}$ is obtained in the reduced phase-space defined by the requirement $|\Delta |\eta_{\ell\bar{\ell}}||<2.5$. The measured values are given with statistical and systematic uncertainties. The SM theory predictions calculated at NLO in QCD and NLO in EW theory are listed. The theory uncertainty is obtained by varying both scales by a factor of 0.5 or 2.0 to calculate the minimum and maximum value of the asymmetry, respectively.

The unfolded differential leptonic asymmetry as a function of the transverse momentum of the di-lepton pair. The unfolded $A_C^{\ell\bar{\ell}}$ is obtained in the reduced phase-space defined by the requirement $|\Delta |\eta_{\ell\bar{\ell}}||<2.5$. The measured values are given with statistical and systematic uncertainties. The SM theory predictions calculated at NLO in QCD and NLO in EW theory are listed. The theory uncertainty is obtained by varying both scales by a factor of 0.5 or 2.0 to calculate the minimum and maximum value of the asymmetry, respectively.

The unfolded differential leptonic asymmetry as a function of the longitudinal boost of the di-lepton pair. The unfolded $A_C^{\ell\bar{\ell}}$ is obtained in the reduced phase-space defined by the requirement $|\Delta |\eta_{\ell\bar{\ell}}||<2.5$. The measured values are given with statistical and systematic uncertainties. The SM theory predictions calculated at NLO in QCD and NLO in EW theory are listed. The theory uncertainty is obtained by varying both scales by a factor of 0.5 or 2.0 to calculate the minimum and maximum value of the asymmetry, respectively.

Individual 68% and 95% CL bounds on the relevant Wilson coefficients of the SM Effective Field Theory in units of $\text{TeV}^{-2}$. The bounds are derived from the $A_C^{t\bar{t}}$ inclusive measurement. The experimental uncertainties are accounted for, in the form of the complete covariance matrix that keeps track of correlations between bins for the differential measurement. The theory uncertainty from the NNLO QCD + NLO EW calculation is included by explicitly varying the renormalization and factorization scales, or the parton density functions, in the calculation and registering the variations in the intervals.

Individual 68% and 95% CL bounds on the relevant Wilson coefficients of the SM Effective Field Theory in units of $\text{TeV}^{-2}$. The bounds are derived from the $A_C^{t\bar{t}}$ vs $m_{t\bar{t}}$ measurement. The experimental uncertainties are accounted for, in the form of the complete covariance matrix that keeps track of correlations between bins for the differential measurement. The theory uncertainty from the NNLO QCD + NLO EW calculation is included by explicitly varying the renormalization and factorization scales, or the parton density functions, in the calculation and registering the variations in the intervals.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ inclusive measurement. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $\beta_{z,t\bar{t}}$ measurement for $\beta_{z,t\bar{t}}$ $\in$ [0,0.3]. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $\beta_{z,t\bar{t}}$ measurement for $\beta_{z,t\bar{t}}$ $\in$ [0.3,0.6]. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $\beta_{z,t\bar{t}}$ measurement for $\beta_{z,t\bar{t}}$ $\in$ [0.6,0.8]. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $\beta_{z,t\bar{t}}$ measurement for $\beta_{z,t\bar{t}}$ $\in$ [0.8,1]. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $m_{t\bar{t}}$ measurement for $m_{t\bar{t}}$ < 500 GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $m_{t\bar{t}}$ measurement for $m_{t\bar{t}}$ $\in$ [500,750] GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $m_{t\bar{t}}$ measurement for $m_{t\bar{t}}$ $\in$ [750,1000] GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $m_{t\bar{t}}$ measurement for $m_{t\bar{t}}$ $\in$ [1000,1500] GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $m_{t\bar{t}}$ measurement for $m_{t\bar{t}}$ > 1500 GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $p_{T,t\bar{t}}$ measurement for $p_{T,t\bar{t}}$ < 30 GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $p_{T,t\bar{t}}$ measurement for $p_{T,t\bar{t}}$ $\in$ [30,120] GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{t\bar{t}}$ vs $p_{T,t\bar{t}}$ measurement for $p_{T,t\bar{t}}$ > 120 GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ inclusive measurement. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ vs $\beta_{z,\ell\bar{\ell}}$ measurement for $\beta_{z,\ell\bar{\ell}}$ $\in$[0,0.3]. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ vs $\beta_{z,\ell\bar{\ell}}$ measurement for $\beta_{z,\ell\bar{\ell}}$ $\in$[0.3,0.6]. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ vs $\beta_{z,\ell\bar{\ell}}$ measurement for $\beta_{z,\ell\bar{\ell}}$ $\in$[0.6,0.8]. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ vs $\beta_{z,\ell\bar{\ell}}$ measurement for $\beta_{z,\ell\bar{\ell}}$ $\in$[0.8,1]. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ vs $m_{\ell\bar{\ell}}$ measurement for $m_{\ell\bar{\ell}}$ < 200 GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ vs $m_{\ell\bar{\ell}}$ measurement for $m_{\ell\bar{\ell}}$ $\in$ [200,300] GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ vs $m_{\ell\bar{\ell}}$ measurement for $m_{\ell\bar{\ell}}$ $\in$ [300,400] GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ vs $m_{\ell\bar{\ell}}$ measurement for $m_{\ell\bar{\ell}}$ > 400 GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ vs $p_{T,\ell\bar{\ell}}$ measurement for $p_{T,\ell\bar{\ell}}$ < 20 GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ vs $p_{T,\ell\bar{\ell}}$ measurement for $p_{T,\ell\bar{\ell}}$ $\in$ [20, 70] GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Ranking of the systematic uncertainties with marginalisation for the $A_C^{\ell\ell}$ vs $p_{T,\ell\bar{\ell}}$ measurement for $p_{T,\ell\bar{\ell}}$ > 70 GeV. The effect on unfolded $A_C$ for down and up variation of the systematic uncertainty is shown, respectively. The pulls and constraints of the ranked NPs are obtained from data.

Post-marginalisation correlation coefficients $\rho_{ij}$ of nuisance parameters for the $A_C^{t\bar{t}}$ inclusive measurement. Only $|\rho_{ij}| > 0.05$ values are included.

Post-marginalisation correlation coefficients $\rho_{ij}$ of nuisance parameters for the $A_C^{t\bar{t}}$ vs $m_{t\bar{t}}$ measurement. Only $|\rho_{ij}| > 0.05$ values are included.

Post-marginalisation correlation coefficients $\rho_{ij}$ of nuisance parameters for the $A_C^{t\bar{t}}$ vs $p_{T,t\bar{t}}$ measurement. Only $|\rho_{ij}| > 0.05$ values are included.

Post-marginalisation correlation coefficients $\rho_{ij}$ of nuisance parameters for the $A_C^{t\bar{t}}$ vs $\beta_{z,t\bar{t}}$ measurement. Only $|\rho_{ij}| > 0.05$ values are included.

Post-marginalisation correlation coefficients $\rho_{ij}$ of nuisance parameters for the $A_C^{\ell\ell}$ inclusive measurement. Only $|\rho_{ij}| > 0.05$ values are included.

Post-marginalisation correlation coefficients $\rho_{ij}$ of nuisance parameters for the $A_C^{\ell\ell}$ vs $m_{\ell\bar{\ell}}$ measurement. Only $|\rho_{ij}| > 0.05$ values are included.

Post-marginalisation correlation coefficients $\rho_{ij}$ of nuisance parameters for the $A_C^{\ell\ell}$ vs $p_{T,\ell\bar{\ell}}$ measurement. Only $|\rho_{ij}| > 0.05$ values are included.

Post-marginalisation correlation coefficients $\rho_{ij}$ of nuisance parameters for the $A_C^{\ell\ell}$ vs $\beta_{z,\ell\bar{\ell}}$ measurement. Only $|\rho_{ij}| > 0.05$ values are included.

Covariance matrix for the $A_C^{t\bar{t}}$ vs $m_{t\bar{t}}$ measurement. The total (stat. + syst.) uncertainties are considered.

Covariance matrix for the $A_C^{t\bar{t}}$ vs $p_{T,t\bar{t}}$ measurement. The total (stat. + syst.) uncertainties are considered.

Covariance matrix for the $A_C^{t\bar{t}}$ vs $\beta_{z,t\bar{t}}$ measurement. The total (stat. + syst.) uncertainties are considered.

Covariance matrix for the $A_C^{\ell\ell}$ vs $m_{\ell\bar{\ell}}$ measurement. The total (stat. + syst.) uncertainties are considered.

Covariance matrix for the $A_C^{\ell\ell}$ vs $p_{T,\ell\bar{\ell}}$ measurement. The total (stat. + syst.) uncertainties are considered.

Covariance matrix for the $A_C^{\ell\ell}$ vs $\beta_{z,\ell\bar{\ell}}$ measurement. The total (stat. + syst.) uncertainties are considered.