Pre-fit background composition of the SR$3\ell$ Prod. The table shows the event yields as opposed to just the percentages of the relevant background processes.

Post-fit plot of $H_\text{T}(\text{jets})$ in the SR$2\ell$ Dec from a signal-blinded background-only fit.

Post-fit plot of $m(t_\text{SM}, b\text{-jet}_0)$ in the SR$2\ell$ Prod from a signal-blinded background-only fit.

Post-fit plot of $m(\ell_\text{OS},\ell_\text{SS,1})$ in the SR$3\ell$ Dec from a signal-blinded background-only fit.

Post-fit plot of $m(\ell_\text{OS},\ell_\text{SS,1})$ in the SR$3\ell$ Prod from a signal-blinded background-only fit.

Post-fit plot of $D_\text{NN}(tHc)$ in the SR$2\ell$ Dec from the full fit to data.

Post-fit plot of $D_\text{NN}(tHc)$ in the SR$2\ell$ Prod from the full fit to data.

Post-fit plot of $D_\text{NN}(tHc)$ in the SR$3\ell$ Dec from the full fit to data.

Post-fit plot of $D_\text{NN}(tHc)$ in the SR$3\ell$ Prod from the full fit to data.

Post-fit plot of $p_\text{T}(\ell_1)$ in the CR$2\ell$ HF$e$ from the full fit to data.

Post-fit plot of $p_\text{T}(\ell_1)$ in the CR$2\ell$ HF$\mu$ from the full fit to data.

Post-fit plot of $p_\text{T}(\ell_1)$ in the CR$2\ell$ $t\bar{t}V$ from the full fit to data.

Post-fit plot of $p_\text{T}(\ell_2)$ in the CR$3\ell$ HF$e$ from the full fit to data.

Post-fit plot of $p_\text{T}(\ell_2)$ in the CR$3\ell$ HF$\mu$ from the full fit to data.

Post-fit plot of $p_\text{T}(b\text{-jet}_0)$ in the CR$3\ell$ $t\bar{t}W$ from the full fit to data.

Post-fit plot of $p_\text{T}(b\text{-jet}_0)$ in the CR$3\ell$ $t\bar{t}Z$ from the full fit to data.

Observed and expected upper exclusion limits on the branching ratio $\mathcal{B}(t\to Hu)$ for different analyses and their statistical combination.

Observed and expected upper exclusion limits on the branching ratio $\mathcal{B}(t\to Hc)$ for different analyses and their statistical combination.

Post-fit normalisation factors of free-floating background processes and the signal normalisation.

Post-fit predicted and observed yields in all $2\ell$SS signal and control regions. Pre-fit signal contributions for a signal cross section equivalent to $\mathcal{B}(t\to Hq)=0.1\,\%$ are given as well.

Post-fit predicted and observed yields in all $3\ell$ signal and control regions. Pre-fit signal contributions for a signal cross section equivalent to $\mathcal{B}(t\to Hq)=0.1\,\%$ are given as well.

Expected upper limits on $\mathcal{B}(t\to Hq)$ for the nominal fit and alternative fit configurations. One contains the full phase space but only considers statistical uncertainties. Two other configurations consider the full set of systematic uncertainties, but only encompass one final state.

Expected and observed upper limits on $\mathcal{B}(t\to Hq)$ and $|C_{u\phi}^{qt,tq}|$ for the full fit containing all systematic uncertainties.

Pre-fit plot of $H_\text{T}(\text{jets})$ in the SR$2\ell$ Dec from a signal-blinded background-only fit.

Pre-fit plot of $m(t_\text{SM}, b\text{-jet}_0)$ in the SR$2\ell$ Prod from a signal-blinded background-only fit.

Pre-fit plot of $m(\ell_\text{OS},\ell_\text{SS,1})$ in the SR$3\ell$ Dec from a signal-blinded background-only fit.

Pre-fit plot of $m(\ell_\text{OS},\ell_\text{SS,1})$ in the SR$3\ell$ Prod from a signal-blinded background-only fit.

Post-fit plot of $D_\text{NN}(tHu)$ in the SR$2\ell$ Dec from the full fit to data.

Post-fit plot of $D_\text{NN}(tHu)$ in the SR$2\ell$ Prod from the full fit to data.

Post-fit plot of $D_\text{NN}(tHu)$ in the SR$3\ell$ Dec from the full fit to data.

Post-fit plot of $D_\text{NN}(tHu)$ in the SR$3\ell$ Prod from the full fit to data.

Pre-fit plot of $D_\text{NN}(tHc)$ in the SR$2\ell$ Dec from the full fit to data.

Pre-fit plot of $D_\text{NN}(tHc)$ in the SR$2\ell$ Prod from the full fit to data.

Pre-fit plot of $D_\text{NN}(tHc)$ in the SR$3\ell$ Dec from the full fit to data.

Pre-fit plot of $D_\text{NN}(tHc)$ in the SR$3\ell$ Prod from the full fit to data.

Pre-fit plot of $D_\text{NN}(tHu)$ in the SR$2\ell$ Dec from the full fit to data.

Pre-fit plot of $D_\text{NN}(tHu)$ in the SR$2\ell$ Prod from the full fit to data.

Pre-fit plot of $D_\text{NN}(tHu)$ in the SR$3\ell$ Dec from the full fit to data.

Pre-fit plot of $D_\text{NN}(tHu)$ in the SR$3\ell$ Prod from the full fit to data.

Pre-fit plot of $p_\text{T}(\ell_1)$ in the CR$2\ell$ HF$e$ from the full fit to data.

Pre-fit plot of $p_\text{T}(\ell_1)$ in the CR$2\ell$ HF$\mu$ from the full fit to data.

Pre-fit plot of $p_\text{T}(\ell_1)$ in the CR$2\ell$ $t\bar{t}V$ from the full fit to data.

Pre-fit plot of $p_\text{T}(\ell_2)$ in the CR$3\ell$ HF$e$ from the full fit to data.

Pre-fit plot of $p_\text{T}(\ell_2)$ in the CR$3\ell$ HF$\mu$ from the full fit to data.

Pre-fit plot of $p_\text{T}(b\text{-jet}_0)$ in the CR$3\ell$ $t\bar{t}W$ from the full fit to data.

Pre-fit plot of $p_\text{T}(b\text{-jet}_0)$ in the CR$3\ell$ $t\bar{t}Z$ from the full fit to data.

Ranking of fit nuisance parameters according to their impact on the post-fit $tHu$ signal normalisation when fixed to $\pm1\sigma$

Ranking of fit nuisance parameters according to their impact on the post-fit $tHc$ signal normalisation when fixed to $\pm1\sigma$

Expected upper exclusion limits on the branching ratio $\mathcal{B}(t\to Hu)$ for each individual final state and the full analysis.

Expected upper exclusion limits on the branching ratio $\mathcal{B}(t\to Hc)$ for each individual final state and the full analysis.

Definition of the tetralepton signal regions.

Definition of the fiducial volumes at particle- and parton-level. Leptons refer exclusively to electrons and muons - they are dressed with additional radiation at particle-level, but not at parton-level.

Definition of the dilepton $t\bar{t}$ validation regions.

Pre-fit distribution of the number of $b$-jets in 2L-$e\mu$-6j2b, this distribution is not used in the fit.

Pre-fit distribution of the DNN output 2L-$e\mu$-6j1b, this distribution is not used in the fit.

Pre-fit distribution of the DNN output 2L-$e\mu$-5j2b, this distribution is not used in the fit.

Pre-fit distribution of the DNN output 2L-$e\mu$-6j2b, this distribution is not used in the fit.

Definition of the tetralepton control region.

Definition of the trilepton fakes control regions.

Pre-fit distribution of jet multiplicity in CR-$t\bar{t}$-e region.

Pre-fit distribution of loose lepton transverse momentum in CR-$t\bar{t}$-$\mu$ region.

Pre-fit distribution of the transverse mass of the trailing lepton and the missing transverse momentum in CR-Z-e region.

Post-fit distribution of jet multiplicity in CR-$t\bar{t}$-e region

Post-fit distribution of loose lepton transverse momentum in CR-$t\bar{t}$-$\mu$ region

Post-fit distribution of the transverse mass of the trailing lepton and the missing transverse momentum in CR-Z-e region

Post-fit distribution of NN output in SR-2L-5j2b region.

Post-fit distribution of NN output in SR-2L-6j1b region.

Post-fit distribution of NN output in SR-2L-6j2b region.

Post-fit distribution of DNN-$t\bar{t}Z$ output in 3L-SR-ttZ region.

Post-fit distribution of DNN-$t\bar{t}Z$ outputt in 3L-SR-tZq region.

Post fit events yields in 3L-SR-WZ region.

Post-fit distribution of NN output in 4L-SR-SF region.

Post-fit distribution of NN output in 4L-SR-DF region.

Post-fit distribution of b-tagger output for leading b-jet in 4L-CR-ZZ region.

Measured values of the background normalizations obtained from the combined fit. The uncertainties include statistical and systematic sources.

Measured $\sigma_{t\bar{t}\text{Z}}$ cross sections obtained from the fits in the different lepton channels. The uncertainties include statistical and systematic sources.

Grouped impact of systematic uncertainties in the combined inclusive fit to data.

Unfolded absolute cross section as a function of $p^{Z}_{T}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 8 top-left).

Unfolded absolute cross section as a function of $p^{Z}_{T}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 8 top-right).

Unfolded normalized cross section as a function of $p^{Z}_{T}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 8 bottom-left).

Unfolded normalized cross section as a function of $p^{Z}_{T}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 8 bottom-right).

Unfolded absolute cross section as a function of $|y^{Z}$| in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 17 top-left and Figure 11 top-left).

Unfolded absolute cross section as a function of $|y^{Z}$| in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 17 top-right).

Unfolded normalized cross section as a function of $|y^{Z}$| in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 17 bottom-left).

Unfolded normalized cross section as a function of $|y^{Z}$| in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 17 bottom-right).

Unfolded absolute cross section as a function of cos $\theta_{Z}^{*}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 18 top-left and Figure 11 top-right).

Unfolded absolute cross section as a function of cos $\theta_{Z}^{*}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 18 top-right).

Unfolded normalized cross section as a function of cos $\theta_{Z}^{*}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 18 bottom-left).

Unfolded normalized cross section as a function of cos $\theta_{Z}^{*}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 18 bottom-right).

Unfolded absolute cross section as a function of $p_{T}^{\mathrm{top}}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 19 top-left and Figure 11 bottom-left).

Unfolded absolute cross section as a function of $p_{T}^{\mathrm{top}}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 19, top-right).

Unfolded normalized cross section as a function of $p_{T}^{\mathrm{top}}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 19, bottom-left).

Unfolded normalized cross section as a function of $p_{T}^{\mathrm{top}}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 19, bottom-right).

Unfolded absolute cross section as a function of $p_{T}^{t\bar{t}}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 20 top-left and Figure 11 bottom-right).

Unfolded absolute cross section as a function of $p_{T}^{t\bar{t}}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 20, top-right).

Unfolded normalized cross section as a function of $p_{T}^{t\bar{t}}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 20, bottom-left)

Unfolded normalized cross section as a function of $p_{T}^{t\bar{t}}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 20, bottom-right)

Unfolded absolute cross section as a function of $|\Delta\Phi(t\bar{t}, Z)|/\pi$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 21 top-left and Figure 12 top-left).

Unfolded absolute cross section as a function of $|\Delta\Phi(t\bar{t}, Z)|/\pi$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 21, top-right).

Unfolded normalized cross section as a function of $|\Delta\Phi(t\bar{t}, Z)|/\pi$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 21, bottom-left).

Unfolded normalized cross section as a function of $|\Delta\Phi(t\bar{t}, Z)|/\pi$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 21, top-right).

Unfolded absolute cross section as a function of $m^{t\bar{t}Z}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 22 top-left and Figure 12 bottom-left).

Unfolded absolute cross section as a function of $m^{t\bar{t}Z}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 22, top-right).

Unfolded normalized cross section as a function of $m^{t\bar{t}Z}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 22, bottom-left).

Unfolded normalized cross section as a function of $m^{t\bar{t}Z}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 22, bottom-right).

Unfolded absolute cross section as a function of $m^{t\bar{t}}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 23 top-left and Figure 12 bottom-right).

Unfolded absolute cross section as a function of $m^{t\bar{t}}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 23, top-right).

Unfolded normalized cross section as a function of $m^{t\bar{t}}$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 23, bottom-left).

Unfolded normalized cross section as a function of $m^{t\bar{t}}$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 23, bottom-right).

Unfolded absolute cross section as a function of $|y^{t\bar{t}Z}|$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 24 top-left and Figure 12 top-right).

Unfolded absolute cross section as a function of $|y^{t\bar{t}Z}|$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 24, top-right).

Unfolded normalized cross section as a function of $|y^{t\bar{t}Z}|$ in the combination of $3\ell$ and $4\ell$ channels at particle-level (Figure 24, bottom-left).

Unfolded normalized cross section as a function of $|y^{t\bar{t}Z}|$ in the combination of $3\ell$ and $4\ell$ channels at parton-level (Figure 24, bottom-right).

Unfolded absolute cross section as a function of $H_{\text{T}}^{\text{l}}$ in the trilepton channel at particle-level (Figure 25 top-left and Figure 9 top-left).

Unfolded absolute cross section as a function of $H_{\text{T}}^{\text{l}}$ in the trilepton channel at parton-level (Figure 25 top-right).

Unfolded normalized cross section as a function of $H_{\text{T}}^{\text{l}}$ in the trilepton channel at particle-level (Figure 25 bottom-left).

Unfolded normalized cross section as a function of $H_{\text{T}}^{\text{l}}$ in the trilepton channel at parton-level (Figure 25 bottom-right).

Unfolded absolute cross section as a function of $|\Delta\Phi(Z, t_{lep})|/\pi$ in the trilepton channel at particle-level (Figure 26 top-left and Figure 10 bottom-left).

Unfolded absolute cross section as a function of $|\Delta\Phi(Z, t_{lep})|/\pi$ in the trilepton channel at parton-level (Figure 26 top-right).

Unfolded normalized cross section as a function of $|\Delta\Phi(Z, t_{lep})|/\pi$ in the trilepton channel at particle-level (Figure 26 bottom-left).

Unfolded normalized cross section as a function of $|\Delta\Phi(Z, t_{lep})|/\pi$ in the trilepton channel at parton-level (Figure 26 bottom-right).

Unfolded absolute cross section as a function of $|\Delta y(Z, t_{lep})|$ in the trilepton channel at particle-level (Figure 27 top-left and Figure 10 bottom-right).

Unfolded absolute cross section as a function of $|\Delta y(Z, t_{lep})|$ in the trilepton channel at parton-level (Figure 27 top-right).

Unfolded normalized cross section as a function of $|\Delta y(Z, t_{lep})|$ in the trilepton channel at particle-level (Figure 27 bottom-left).

Unfolded normalized cross section as a function of $|\Delta y(Z, t_{lep})|$ in the trilepton channel at parton-level (Figure 27 bottom-right).

Unfolded absolute cross section as a function of $p_{\text{T}}^{\ell, non-Z}$ in the trilepton channel at particle-level (Figure 28 top-left and Figure 10 top-left).

Unfolded absolute cross section as a function of $p_{\text{T}}^{\ell, non-Z}$ in the trilepton channel at parton-level (Figure 28 top-right).

Unfolded normalized cross section as a function of $p_{\text{T}}^{\ell, non-Z}$ in the trilepton channel at particle-level (Figure 28 bottom-left).

Unfolded normalized cross section as a function of $p_{\text{T}}^{\ell, non-Z}$ in the trilepton channel at parton-level (Figure 28 bottom-right).

Unfolded absolute cross section as a function of $N_{\text{jets}}$ in the trilepton channel at particle-level (Figure 29 left and Figure 9 bottom-left).

Unfolded normalized cross section as a function of $N_{\text{jets}}$ in the trilepton channel at particle-level (Figure 29 right).

Unfolded absolute cross section as a function of $H_{\text{T}}^{\text{l}}$ in the tetralepton channel at particle-level (Figure 30 top-left and Figure 9 top-right).

Unfolded absolute cross section as a function of $H_{\text{T}}^{\text{l}}$ in the tetralepton channel at parton-level (Figure 30 top-right).

Unfolded normalized cross section as a function of $H_{\text{T}}^{\text{l}}$ in the tetralepton channel at particle-level (Figure 30 bottom-left).

Unfolded normalized cross section as a function of $H_{\text{T}}^{\text{l}}$ in the tetralepton channel at parton-level (Figure 30 bottom-right).

Unfolded absolute cross section as a function of $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ in the tetralepton channel at particle-level (Figure 31 top-left and Figure 10 top-right).

Unfolded absolute cross section as a function of $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ in the tetralepton channel at parton-level (Figure 31 top-right).

Unfolded normalized cross section as a function of $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ in the tetralepton channel at particle-level (Figure 31 bottom-left).

Unfolded normalized cross section as a function of $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ in the tetralepton channel at parton-level (Figure 31 bottom-right).

Unfolded absolute cross section as a function of $N_{\text{jets}}$ in the tetralepton channel at particle-level (Figure 32 left and Figure 9 bottom-right).

Unfolded normalized cross section as a function of $N_{\text{jets}}$ in the tetralepton channel at particle-level (Figure 32 right).

Bootstrap replicas (0-499) for data in all regions used in inclusive cross section measurement. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (500-999) for data in all regions used in inclusive cross section measurement. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (0-499) for data, variable $|\Delta\Phi(t\bar{t}, Z)|/\pi$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (500-999) for data, variable $|\Delta\Phi(t\bar{t}, Z)|/\pi$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (0-499) for data, variable $|\Delta\Phi(Z, t_{lep})|/\pi$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (500-999) for data, variable $|\Delta\Phi(Z, t_{lep})|/\pi$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (0-499) for data, variable $m^{t\bar{t}}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (500-999) for data, variable $m^{t\bar{t}}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (0-499) for data, variable $N_{\text{jets}}$ in $3\ell$ channel. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (500-999) for data, variable $N_{\text{jets}}$ in $3\ell$ channel. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (0-499) for data, variable $|y^{t\bar{t}Z}|$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (500-999) for data, variable $|y^{t\bar{t}Z}|$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (0-499) for data, variable $H_{\text{T}}^{\text{l}}$ in $3\ell$ channel. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (500-999) for data, variable $H_{\text{T}}^{\text{l}}$ in $3\ell$ channel. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (0-499) for data, variable $y^{Z}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (500-999) for data, variable $y^{Z}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (0-499) for data, variable $p_{T}^{\mathrm{top}}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (500-999) for data, variable $p_{T}^{\mathrm{top}}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (0-499) for data, variable cos $\theta^{*}_{Z}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (500-999) for data, variable cos $\theta^{*}_{Z}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (0-499) for data, variable $p_{\text{T}}^{\ell, non-Z}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (500-999) for data, variable $p_{\text{T}}^{\ell, non-Z}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (0-499) for data, variable $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (500-999) for data, variable $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (0-499) for data, variable $H_{\text{T}}^{\text{l}}$ in $4\ell$ channel. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (500-999) for data, variable $H_{\text{T}}^{\text{l}}$ in $4\ell$ channel. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (0-499) for data, variable $m^{t\bar{t}Z}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (500-999) for data, variable $m^{t\bar{t}Z}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (0-499) for data, variable $N_{\text{jets}}$ in $4\ell$ channel. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (500-999) for data, variable $N_{\text{jets}}$ in $4\ell$ channel. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (0-499) for data, variable $|\Delta y(Z, t_{lep})|$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (500-999) for data, variable $|\Delta y(Z, t_{lep})|$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (0-499) for data, variable $p^{Z}_{T}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (500-999) for data, variable $p^{Z}_{T}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (0-499) for data, variable $p_{T}^{t\bar{t}}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Bootstrap replicas (500-999) for data, variable $p_{T}^{t\bar{t}}$. The used bootstrap method is described in ATL-PHYS-PUB-2021-011 (https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2021-011/).

Parton-level acceptance and selection efficiency histograms for $|\Delta\Phi(Z, t_{lep})|/\pi$ variable.

Parton-level acceptance and selection efficiency histograms for $|\Delta y(Z, t_{lep})|$ variable.

Parton-level acceptance and selection efficiency histograms for $H_{\text{T}}^{\text{ l}}$ variable.

Parton-level acceptance and selection efficiency histograms for $p_{\text{T}}^{\ell, non-Z}$ variable.

Parton-level acceptance and selection efficiency histograms for $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ variable.

Parton-level acceptance and selection efficiency histograms for $H_{\text{T}}^{\text{ l}}$ variable.

Parton-level acceptance and selection efficiency histograms for cos $\theta_{Z}^{*}$ variable.

Parton-level acceptance and selection efficiency histograms for $p^{Z}_{T}$ variable.

Parton-level acceptance and selection efficiency histograms for $|y^{Z}$| variable.

Parton-level acceptance and selection efficiency histograms for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable.

Parton-level acceptance and selection efficiency histograms for $m^{t\bar{t}}$ variable.

Parton-level acceptance and selection efficiency histograms for $m^{t\bar{t}Z}$ variable.

Parton-level acceptance and selection efficiency histograms for $p_{T}^{\mathrm{top}}$ variable.

Parton-level acceptance and selection efficiency histograms for $p_{T}^{t\bar{t}}$ variable.

Parton-level acceptance and selection efficiency histograms for $|y^{t\bar{t}Z}|$ variable.

Particle-level acceptance and selection efficiency histograms for $|\Delta\Phi(Z, t_{lep})|/\pi$ variable.

Particle-level acceptance and selection efficiency histograms for $|\Delta y(Z, t_{lep})|$ variable.

Particle-level acceptance and selection efficiency histograms for $H_{\text{T}}^{\text{ l}}$ variable.

Particle-level acceptance and selection efficiency histograms for $N_{\text{jets}}$ variable.

Particle-level acceptance and selection efficiency histograms for $p_{\text{T}}^{\ell, non-Z}$ variable.

Particle-level acceptance and selection efficiency histograms for $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ variable.

Particle-level acceptance and selection efficiency histograms for $H_{\text{T}}^{\text{ l}}$ variable.

Particle-level acceptance and selection efficiency histograms for $N_{\text{jets}}$ variable.

Particle-level acceptance and selection efficiency histograms for cos $\theta_{Z}^{*}$ variable.

Particle-level acceptance and selection efficiency histograms for $p^{Z}_{T}$ variable.

Particle-level acceptance and selection efficiency histograms for $|y^{Z}$| variable.

Particle-level acceptance and selection efficiency histograms for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable.

Particle-level acceptance and selection efficiency histograms for $m^{t\bar{t}}$ variable.

Particle-level acceptance and selection efficiency histograms for $m^{t\bar{t}Z}$ variable.

Particle-level acceptance and selection efficiency histograms for $p_{T}^{\mathrm{top}}$ variable.

Particle-level acceptance and selection efficiency histograms for $p_{T}^{t\bar{t}}$ variable.

Particle-level acceptance and selection efficiency histograms for $|y^{t\bar{t}Z}|$ variable.

Migration matrix for cos $\theta_{Z}^{*}$ variable at particle-level in region SR-3L-ttZ.

Migration matrix for cos $\theta_{Z}^{*}$ variable at particle-level in region SR-3L-tZq.

Migration matrix for cos $\theta_{Z}^{*}$ variable at particle-level in region SR-3L-WZ.

Migration matrix for cos $\theta_{Z}^{*}$ variable at particle-level in region SR-4L-DF.

Migration matrix for cos $\theta_{Z}^{*}$ variable at particle-level in region SR-4L-SF.

Migration matrix for cos $\theta_{Z}^{*}$ variable at particle-level in region CR-4L-ZZ.

Migration matrix for cos $\theta_{Z}^{*}$ variable at parton-level in region SR-3L-ttZ.

Migration matrix for cos $\theta_{Z}^{*}$ variable at parton-level in region SR-3L-tZq.

Migration matrix for cos $\theta_{Z}^{*}$ variable at parton-level in region SR-3L-WZ.

Migration matrix for cos $\theta_{Z}^{*}$ variable at parton-level in region SR-4L-DF.

Migration matrix for cos $\theta_{Z}^{*}$ variable at parton-level in region SR-4L-SF.

Migration matrix for cos $\theta_{Z}^{*}$ variable at parton-level in region CR-4L-ZZ.

Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at particle-level in region SR-3L-ttZ.

Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at particle-level in region SR-3L-tZq.

Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at particle-level in region SR-3L-WZ.

Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at particle-level in region SR-4L-DF.

Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at particle-level in region SR-4L-SF.

Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at particle-level in region CR-4L-ZZ.

Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at parton-level in region SR-3L-ttZ.

Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at parton-level in region SR-3L-tZq.

Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at parton-level in region SR-3L-WZ.

Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at parton-level in region SR-4L-DF.

Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at parton-level in region SR-4L-SF.

Migration matrix for $|\Delta\Phi(t\bar{t}, Z)|/\pi$ variable at parton-level in region CR-4L-ZZ.

Migration matrix for $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ variable at particle-level in region SR-4L-DF.

Migration matrix for $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ variable at particle-level in region SR-4L-SF.

Migration matrix for $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ variable at particle-level in region CR-4L-ZZ.

Migration matrix for $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ variable at parton-level in region SR-4L-DF.

Migration matrix for $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ variable at parton-level in region SR-4L-SF.

Migration matrix for $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ variable at parton-level in region CR-4L-ZZ.

Migration matrix for $|\Delta\Phi(Z, t_{lep})|/\pi$ variable at particle-level in region SR-3L-ttZ.

Migration matrix for $|\Delta\Phi(Z, t_{lep})|/\pi$ variable at particle-level in region SR-3L-tZq.

Migration matrix for $|\Delta\Phi(Z, t_{lep})|/\pi$ variable at particle-level in region SR-3L-WZ.

Migration matrix for $|\Delta\Phi(Z, t_{lep})|/\pi$ variable at parton-level in region SR-3L-ttZ.

Migration matrix for $|\Delta\Phi(Z, t_{lep})|/\pi$ variable at parton-level in region SR-3L-tZq.

Migration matrix for $|\Delta\Phi(Z, t_{lep})|/\pi$ variable at parton-level in region SR-3L-WZ.

Migration matrix for $|\Delta y(Z, t_{lep})|$ variable at particle-level in region SR-3L-ttZ.

Migration matrix for $|\Delta y(Z, t_{lep})|$ variable at particle-level in region SR-3L-tZq.

Migration matrix for $|\Delta y(Z, t_{lep})|$ variable at particle-level in region SR-3L-WZ.

Migration matrix for $|\Delta y(Z, t_{lep})|$ variable at parton-level in region SR-3L-ttZ.

Migration matrix for $|\Delta y(Z, t_{lep})|$ variable at parton-level in region SR-3L-tZq.

Migration matrix for $|\Delta y(Z, t_{lep})|$ variable at parton-level in region SR-3L-WZ.

Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at particle-level in region SR-4L-DF.

Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at particle-level in region SR-4L-SF.

Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at particle-level in region CR-4L-ZZ.

Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at parton-level in region SR-4L-DF.

Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at parton-level in region SR-4L-SF.

Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at parton-level in region CR-4L-ZZ.

Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at particle-level in region SR-3L-ttZ.

Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at particle-level in region SR-3L-tZq.

Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at particle-level in region SR-3L-WZ.

Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at parton-level in region SR-3L-ttZ.

Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at parton-level in region SR-3L-tZq.

Migration matrix for $H_{\text{T}}^{\text{ l}}$ variable at parton-level in region SR-3L-WZ.

Migration matrix for $m^{t\bar{t}Z}$ variable at particle-level in region SR-3L-ttZ.

Migration matrix for $m^{t\bar{t}Z}$ variable at particle-level in region SR-3L-tZq.

Migration matrix for $m^{t\bar{t}Z}$ variable at particle-level in region SR-3L-WZ.

Migration matrix for $m^{t\bar{t}Z}$ variable at particle-level in region SR-4L-DF.

Migration matrix for $m^{t\bar{t}Z}$ variable at particle-level in region SR-4L-SF.

Migration matrix for $m^{t\bar{t}Z}$ variable at particle-level in region CR-4L-ZZ.

Migration matrix for $m^{t\bar{t}Z}$ variable at parton-level in region SR-3L-ttZ.

Migration matrix for $m^{t\bar{t}Z}$ variable at parton-level in region SR-3L-tZq.

Migration matrix for $m^{t\bar{t}Z}$ variable at parton-level in region SR-3L-WZ.

Migration matrix for $m^{t\bar{t}Z}$ variable at parton-level in region SR-4L-DF.

Migration matrix for $m^{t\bar{t}Z}$ variable at parton-level in region SR-4L-SF.

Migration matrix for $m^{t\bar{t}Z}$ variable at parton-level in region CR-4L-ZZ.

Migration matrix for $m^{t\bar{t}}$ variable at particle-level in region SR-3L-ttZ.

Migration matrix for $m^{t\bar{t}}$ variable at particle-level in region SR-3L-tZq.

Migration matrix for $m^{t\bar{t}}$ variable at particle-level in region SR-3L-WZ.

Migration matrix for $m^{t\bar{t}}$ variable at particle-level in region SR-4L-DF.

Migration matrix for $m^{t\bar{t}}$ variable at particle-level in region SR-4L-SF.

Migration matrix for $m^{t\bar{t}}$ variable at particle-level in region CR-4L-ZZ.

Migration matrix for $m^{t\bar{t}}$ variable at parton-level in region SR-3L-ttZ.

Migration matrix for $m^{t\bar{t}}$ variable at parton-level in region SR-3L-tZq.

Migration matrix for $m^{t\bar{t}}$ variable at parton-level in region SR-3L-WZ.

Migration matrix for $m^{t\bar{t}}$ variable at parton-level in region SR-4L-DF.

Migration matrix for $m^{t\bar{t}}$ variable at parton-level in region SR-4L-SF.

Migration matrix for $m^{t\bar{t}}$ variable at parton-level in region CR-4L-ZZ.

Migration matrix for $N_{\text{jets}}$ variable at particle-level in region SR-4L-DF.

Migration matrix for $N_{\text{jets}}$ variable at particle-level in region SR-4L-SF.

Migration matrix for $N_{\text{jets}}$ variable at particle-level in region CR-4L-ZZ.

Migration matrix for $N_{\text{jets}}$ variable at particle-level in region SR-3L-ttZ.

Migration matrix for $N_{\text{jets}}$ variable at particle-level in region SR-3L-tZq.

Migration matrix for $N_{\text{jets}}$ variable at particle-level in region SR-3L-WZ.

Migration matrix for $p^{Z}_{T}$ variable at particle-level in region SR-3L-ttZ.

Migration matrix for $p^{Z}_{T}$ variable at particle-level in region SR-3L-tZq.

Migration matrix for $p^{Z}_{T}$ variable at particle-level in region SR-3L-WZ.

Migration matrix for $p^{Z}_{T}$ variable at particle-level in region SR-4L-DF.

Migration matrix for $p^{Z}_{T}$ variable at particle-level in region SR-4L-SF.

Migration matrix for $p^{Z}_{T}$ variable at particle-level in region CR-4L-ZZ.

Migration matrix for $p^{Z}_{T}$ variable at parton-level in region SR-3L-ttZ.

Migration matrix for $p^{Z}_{T}$ variable at parton-level in region SR-3L-tZq.

Migration matrix for $p^{Z}_{T}$ variable at parton-level in region SR-3L-WZ.

Migration matrix for $p^{Z}_{T}$ variable at parton-level in region SR-4L-DF.

Migration matrix for $p^{Z}_{T}$ variable at parton-level in region SR-4L-SF.

Migration matrix for $p^{Z}_{T}$ variable at parton-level in region CR-4L-ZZ.

Migration matrix for $p_{T}^{\mathrm{top}}$ variable at particle-level in region SR-3L-ttZ.

Migration matrix for $p_{T}^{\mathrm{top}}$ variable at particle-level in region SR-3L-tZq.

Migration matrix for $p_{T}^{\mathrm{top}}$ variable at particle-level in region SR-3L-WZ.

Migration matrix for $p_{T}^{\mathrm{top}}$ variable at particle-level in region SR-4L-DF.

Migration matrix for $p_{T}^{\mathrm{top}}$ variable at particle-level in region SR-4L-SF.

Migration matrix for $p_{T}^{\mathrm{top}}$ variable at particle-level in region CR-4L-ZZ.

Migration matrix for $p_{T}^{\mathrm{top}}$ variable at parton-level in region SR-3L-ttZ.

Migration matrix for $p_{T}^{\mathrm{top}}$ variable at parton-level in region SR-3L-tZq.

Migration matrix for $p_{T}^{\mathrm{top}}$ variable at parton-level in region SR-3L-WZ.

Migration matrix for $p_{T}^{\mathrm{top}}$ variable at parton-level in region SR-4L-DF.

Migration matrix for $p_{T}^{\mathrm{top}}$ variable at parton-level in region SR-4L-SF.

Migration matrix for $p_{T}^{\mathrm{top}}$ variable at parton-level in region CR-4L-ZZ.

Migration matrix for $p_{T}^{t\bar{t}}$ variable at particle-level in region SR-3L-ttZ.

Migration matrix for $p_{T}^{t\bar{t}}$ variable at particle-level in region SR-3L-tZq.

Migration matrix for $p_{T}^{t\bar{t}}$ variable at particle-level in region SR-3L-WZ.

Migration matrix for $p_{T}^{t\bar{t}}$ variable at particle-level in region SR-4L-DF.

Migration matrix for $p_{T}^{t\bar{t}}$ variable at particle-level in region SR-4L-SF.

Migration matrix for $p_{T}^{t\bar{t}}$ variable at particle-level in region CR-4L-ZZ.

Migration matrix for $p_{T}^{t\bar{t}}$ variable at parton-level in region SR-3L-ttZ.

Migration matrix for $p_{T}^{t\bar{t}}$ variable at parton-level in region SR-3L-tZq.

Migration matrix for $p_{T}^{t\bar{t}}$ variable at parton-level in region SR-3L-WZ.

Migration matrix for $p_{T}^{t\bar{t}}$ variable at parton-level in region SR-4L-DF.

Migration matrix for $p_{T}^{t\bar{t}}$ variable at parton-level in region SR-4L-SF.

Migration matrix for $p_{T}^{t\bar{t}}$ variable at parton-level in region CR-4L-ZZ.

Migration matrix for $p_{\text{T}}^{\ell, non-Z}$ variable at particle-level in region SR-3L-ttZ.

Migration matrix for $p_{\text{T}}^{\ell, non-Z}$ variable at particle-level in region SR-3L-tZq.

Migration matrix for $p_{\text{T}}^{\ell, non-Z}$ variable at particle-level in region SR-3L-WZ.

Migration matrix for $p_{\text{T}}^{\ell, non-Z}$ variable at parton-level in region SR-3L-ttZ.

Migration matrix for $p_{\text{T}}^{\ell, non-Z}$ variable at parton-level in region SR-3L-tZq.

Migration matrix for $p_{\text{T}}^{\ell, non-Z}$ variable at parton-level in region SR-3L-WZ.

Migration matrix for $|y^{Z}$| variable at particle-level in region SR-3L-ttZ.

Migration matrix for $|y^{Z}$| variable at particle-level in region SR-3L-tZq.

Migration matrix for $|y^{Z}$| variable at particle-level in region SR-3L-WZ.

Migration matrix for $|y^{Z}$| variable at particle-level in region SR-4L-DF.

Migration matrix for $|y^{Z}$| variable at particle-level in region SR-4L-SF.

Migration matrix for $|y^{Z}$| variable at particle-level in region CR-4L-ZZ.

Migration matrix for $|y^{Z}$| variable at parton-level in region SR-3L-ttZ.

Migration matrix for $|y^{Z}$| variable at parton-level in region SR-3L-tZq.

Migration matrix for $|y^{Z}$| variable at parton-level in region SR-3L-WZ.

Migration matrix for $|y^{Z}$| variable at parton-level in region SR-4L-DF.

Migration matrix for $|y^{Z}$| variable at parton-level in region SR-4L-SF.

Migration matrix for $|y^{Z}$| variable at parton-level in region CR-4L-ZZ.

Migration matrix for $|y^{t\bar{t}Z}|$ variable at particle-level in region SR-3L-ttZ.

Migration matrix for $|y^{t\bar{t}Z}|$ variable at particle-level in region SR-3L-tZq.

Migration matrix for $|y^{t\bar{t}Z}|$ variable at particle-level in region SR-3L-WZ.

Migration matrix for $|y^{t\bar{t}Z}|$ variable at particle-level in region SR-4L-DF.

Migration matrix for $|y^{t\bar{t}Z}|$ variable at particle-level in region SR-4L-SF.

Migration matrix for $|y^{t\bar{t}Z}|$ variable at particle-level in region CR-4L-ZZ.

Migration matrix for $|y^{t\bar{t}Z}|$ variable at parton-level in region SR-3L-ttZ.

Migration matrix for $|y^{t\bar{t}Z}|$ variable at parton-level in region SR-3L-tZq.

Migration matrix for $|y^{t\bar{t}Z}|$ variable at parton-level in region SR-3L-WZ.

Migration matrix for $|y^{t\bar{t}Z}|$ variable at parton-level in region SR-4L-DF.

Migration matrix for $|y^{t\bar{t}Z}|$ variable at parton-level in region SR-4L-SF.

Migration matrix for $|y^{t\bar{t}Z}|$ variable at parton-level in region CR-4L-ZZ.

Covariance matrix for absolute cross section as a function of $p_{T}^{\mathrm{top}}$ at particle-level.

Covariance matrix for normalized cross section as a function of $p_{T}^{\mathrm{top}}$ at particle-level.

Covariance matrix for absolute cross section as a function of $p_{T}^{\mathrm{top}}$ at parton-level.

Covariance matrix for normalized cross section as a function of $p_{T}^{\mathrm{top}}$ at parton-level.

Covariance matrix for absolute cross section as a function of $p_{T}^{t\bar{t}}$ at particle-level.

Covariance matrix for normalized cross section as a function of $p_{T}^{t\bar{t}}$ at particle-level.

Covariance matrix for absolute cross section as a function of $p_{T}^{t\bar{t}}$ at parton-level.

Covariance matrix for normalized cross section as a function of $p_{T}^{t\bar{t}}$ at parton-level.

Covariance matrix for absolute cross section as a function of $|\Delta\Phi(t\bar{t}, Z)|/\pi$ at particle-level.

Covariance matrix for normalized cross section as a function of $|\Delta\Phi(t\bar{t}, Z)|/\pi$ at particle-level.

Covariance matrix for absolute cross section as a function of $|\Delta\Phi(t\bar{t}, Z)|/\pi$ at parton-level.

Covariance matrix for normalized cross section as a function of $|\Delta\Phi(t\bar{t}, Z)|/\pi$ at parton-level.

Covariance matrix for absolute cross section as a function of $m^{t\bar{t}Z}$ at particle-level.

Covariance matrix for normalized cross section as a function of $m^{t\bar{t}Z}$ at particle-level.

Covariance matrix for absolute cross section as a function of $m^{t\bar{t}Z}$ at parton-level.

Covariance matrix for normalized cross section as a function of $m^{t\bar{t}Z}$ at parton-level.

Covariance matrix for absolute cross section as a function of $m^{t\bar{t}}$ at particle-level.

Covariance matrix for normalized cross section as a function of $m^{t\bar{t}}$ at particle-level.

Covariance matrix for absolute cross section as a function of $m^{t\bar{t}}$ at parton-level.

Covariance matrix for normalized cross section as a function of $m^{t\bar{t}}$ at parton-level.

Covariance matrix for absolute cross section as a function of $|y^{t\bar{t}Z}|$ at particle-level.

Covariance matrix for normalized cross section as a function of $|y^{t\bar{t}Z}|$ at particle-level.

Covariance matrix for absolute cross section as a function of $|y^{t\bar{t}Z}|$ at parton-level.

Covariance matrix for normalized cross section as a function of $|y^{t\bar{t}Z}|$ at parton-level.

Covariance matrix for absolute cross section as a function of cos $\theta_{Z}^{*}$ at particle-level.

Covariance matrix for normalized cross section as a function of cos $\theta_{Z}^{*}$ at particle-level.

Covariance matrix for absolute cross section as a function of cos $\theta_{Z}^{*}$ at parton-level.

Covariance matrix for normalized cross section as a function of cos $\theta_{Z}^{*}$ at parton-level.

Covariance matrix for absolute cross section as a function of $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ at particle-level.

Covariance matrix for normalized cross section as a function of $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ at particle-level.

Covariance matrix for absolute cross section as a function of $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ at parton-level.

Covariance matrix for normalized cross section as a function of $|\Delta\Phi(l_{t}^{+}, l_{\bar{t}}^{-})|/\pi$ at parton-level.

Covariance matrix for absolute cross section as a function of $|\Delta\Phi(Z, t_{lep})|/\pi$ at particle-level.

Covariance matrix for normalized cross section as a function of $|\Delta\Phi(Z, t_{lep})|/\pi$ at particle-level.

Covariance matrix for absolute cross section as a function of $|\Delta\Phi(Z, t_{lep})|/\pi$ at parton-level.

Covariance matrix for normalized cross section as a function of $|\Delta\Phi(Z, t_{lep})|/\pi$ at parton-level.

Covariance matrix for absolute cross section as a function of $|\Delta y(Z, t_{lep})|$ at particle-level.

Covariance matrix for normalized cross section as a function of $|\Delta y(Z, t_{lep})|$ at particle-level.

Covariance matrix for absolute cross section as a function of $|\Delta y(Z, t_{lep})|$ at parton-level.

Covariance matrix for normalized cross section as a function of $|\Delta y(Z, t_{lep})|$ at parton-level.

Covariance matrix for absolute cross section as a function of $H_{\text{T}}^{\text{l}}$ at in the tetralepton channel particle-level.

Covariance matrix for normalized cross section as a function of $H_{\text{T}}^{\text{l}}$ at in the tetralepton channel particle-level.

Covariance matrix for absolute cross section as a function of $H_{\text{T}}^{\text{l}}$ at in the tetralepton channel parton-level.

Covariance matrix for normalized cross section as a function of $H_{\text{T}}^{\text{l}}$ in the tetralepton channel at parton-level.

Covariance matrix for absolute cross section as a function of $H_{\text{T}}^{\text{l}}$ in the trilepton channel at particle-level.

Covariance matrix for normalized cross section as a function of $H_{\text{T}}^{\text{l}}$ in the trilepton channel at particle-level.

Covariance matrix for absolute cross section as a function of $H_{\text{T}}^{\text{l}}$ in the trilepton channel at parton-level.

Covariance matrix for normalized cross section as a function of $H_{\text{T}}^{\text{l}}$ in the trilepton channel at parton-level.

Covariance matrix for absolute cross section as a function of $N_{\text{jets}}$ in the tetralepton channel at particle-level.

Covariance matrix for normalized cross section as a function of $N_{\text{jets}}$ in the tetralepton channel at particle-level.

Covariance matrix for absolute cross section as a function of $N_{\text{jets}}$ in the trilepton channel at particle-level.

Covariance matrix for normalized cross section as a function of $N_{\text{jets}}$ in the trilepton channel at particle-level.

Covariance matrix for absolute cross section as a function of $p^{Z}_{T}$ at particle-level.

Covariance matrix for normalized cross section as a function of $p^{Z}_{T}$ at particle-level.

Covariance matrix for absolute cross section as a function of $p^{Z}_{T}$ at parton-level.

Covariance matrix for normalized cross section as a function of $p^{Z}_{T}$ at parton-level.

Covariance matrix for absolute cross section as a function of $p_{\text{T}}^{\ell, non-Z}$ at particle-level.

Covariance matrix for normalized cross section as a function of $p_{\text{T}}^{\ell, non-Z}$ at particle-level.

Covariance matrix for absolute cross section as a function of $p_{\text{T}}^{\ell, non-Z}$ at parton-level.

Covariance matrix for normalized cross section as a function of $p_{\text{T}}^{\ell, non-Z}$ at parton-level.

Covariance matrix for absolute cross section as a function of $|y^{Z}$| at particle-level.

Covariance matrix for normalized cross section as a function of $|y^{Z}$| at particle-level.

Covariance matrix for absolute cross section as a function of $|y^{Z}$| at parton-level.

Covariance matrix for normalized cross section as a function of $|y^{Z}$| at parton-level.

Ranking of nuisance parameters and background normalizations on signal strength for inclusive cross section measurement in combination of all channels

Observed and expected 68% and 95% credible intervals for the top-boson operators, in the marginalised linear fit.

Observed and expected 68% and 95% credible intervals for the top-boson operators, in the marginalised quadratic fit.

Observed and expected 68% and 95% credible intervals for the top-boson operators, in the independent quadratic fits (allowing only one Wilson Coefficient to be non-zero).

Observed and expected 68% and 95% credible intervals for the four-quark operators, in the marginalised linear fit.

Observed and expected 68% and 95% credible intervals for the four-quark operators, in the marginalised quadratic fit.

Observed and expected 68% and 95% credible intervals for the four-quark operators, in the independent quadratic fits (allowing only one Wilson Coefficient to be non-zero).

Observed and expected 68% and 95% credible intervals for Fisher-rotated directions of EFT sensitivity, in the marginalised linear fit.

Correlation matrix of the input particle-level observables used in the EFT fit.

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.

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.