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.

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

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

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

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

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

Fiducial differential cross section of the electroweak $W^\pm W^\pm jj$ production as a function of $N_{\mathrm{gap}\,\mathrm{jets}}$. The correlation of uncertainties of the measured cross section across bins is presented in Table 14.

Fiducial differential cross section of the electroweak $W^\pm W^\pm jj$ production as a function of $\xi_{\mathrm{j}3}$. The correlation of uncertainties of the measured cross section across bins is presented in Table 15.

Fiducial differential cross section of the inclusive $W^\pm W^\pm jj$ production as a function of $m_{\ell\ell}$. The correlation of uncertainties of the measured cross section across bins is presented in Table 16.

Fiducial differential cross section of the inclusive $W^\pm W^\pm jj$ production as a function of $m_{\mathrm{T}}$. The correlation of uncertainties of the measured cross section across bins is presented in Table 17.

Fiducial differential cross section of the inclusive $W^\pm W^\pm jj$ production as a function of $m_{\mathrm{jj}}$. The correlation of uncertainties of the measured cross section across bins is presented in Table 18.

Fiducial differential cross section of the inclusive $W^\pm W^\pm jj$ production as a function of $N_{\mathrm{gap}\,\mathrm{jets}}$. The correlation of uncertainties of the measured cross section across bins is presented in Table 19.

Fiducial differential cross section of the inclusive $W^\pm W^\pm jj$ production as a function of $\xi_{\mathrm{j}3}$. The correlation of uncertainties of the measured cross section across bins is presented in Table 20.

Observed correlations between the bins of the LH-unfolded cross section of the electroweak $W^\pm W^\pm jj$ production as a function of $m_{\ell\ell}$. See Table 1.

Observed correlations between the bins of the LH-unfolded cross section of the electroweak $W^\pm W^\pm jj$ production as a function of $m_{\mathrm{T}}$. See Table 2.

Observed correlations between the bins of the LH-unfolded cross section of the electroweak $W^\pm W^\pm jj$ production as a function of $m_{\mathrm{jj}}$. See Table 3.

Observed correlations between the bins of the LH-unfolded cross section of the electroweak $W^\pm W^\pm jj$ production as a function of $N_{\mathrm{gap}\,\mathrm{jets}}$. See Table 4.

Observed correlations between the bins of the LH-unfolded cross section of the electroweak $W^\pm W^\pm jj$ production as a function of $\xi_{\mathrm{j}3}$. See Table 5.

Observed correlations between the bins of the LH-unfolded cross section of the inclusive $W^\pm W^\pm jj$ production as a function of $m_{\ell\ell}$. See Table 6.

Observed correlations between the bins of the LH-unfolded cross section of the inclusive $W^\pm W^\pm jj$ production as a function of $m_{\mathrm{T}}$. See Table 7.

Observed correlations between the bins of the LH-unfolded cross section of the inclusive $W^\pm W^\pm jj$ production as a function of $m_{\mathrm{jj}}$. See Table 8.

Observed correlations between the bins of the LH-unfolded cross section of the inclusive $W^\pm W^\pm jj$ production as a function of $N_{\mathrm{gap}\,\mathrm{jets}}$. See Table 9.

Observed correlations between the bins of the LH-unfolded cross section of the inclusive $W^\pm W^\pm jj$ production as a function of $\xi_{\mathrm{j}3}$. See Table 10.

Evolution of the one-dimensional expected and observed limits at 95% CL on the parameters corresponding to the quartic operators with label M0 as a function of the cut-off scale. The unitarity bounds as a function of the cut-off scale are defined for one non-zero Wilson coefficient.

Evolution of the one-dimensional expected and observed limits at 95% CL on the parameters corresponding to the quartic operators with label M1 as a function of the cut-off scale. The unitarity bounds as a function of the cut-off scale are defined for one non-zero Wilson coefficient.

Evolution of the one-dimensional expected and observed limits at 95% CL on the parameters corresponding to the quartic operators with label M7 as a function of the cut-off scale. The unitarity bounds as a function of the cut-off scale are defined for one non-zero Wilson coefficient. The limits on M7 were obtained without taking into account the SM-EFT interference for the EW W$^\pm$Zjj final state.

Evolution of the one-dimensional expected and observed limits at 95% CL on the parameters corresponding to the quartic operators with label S02 as a function of the cut-off scale. The unitarity bounds as a function of the cut-off scale are defined for one non-zero Wilson coefficient.

Evolution of the one-dimensional expected and observed limits at 95% CL on the parameters corresponding to the quartic operators with label S1 as a function of the cut-off scale. The unitarity bounds as a function of the cut-off scale are defined for one non-zero Wilson coefficient.

Evolution of the one-dimensional expected and observed limits at 95% CL on the parameters corresponding to the quartic operators with label T0 as a function of the cut-off scale. The unitarity bounds as a function of the cut-off scale are defined for one non-zero Wilson coefficient.

Evolution of the one-dimensional expected and observed limits at 95% CL on the parameters corresponding to the quartic operators with label T1 as a function of the cut-off scale. The unitarity bounds as a function of the cut-off scale are defined for one non-zero Wilson coefficient.

Evolution of the one-dimensional expected and observed limits at 95% CL on the parameters corresponding to the quartic operators with label T2 as a function of the cut-off scale. The unitarity bounds as a function of the cut-off scale are defined for one non-zero Wilson coefficient.

Expected and observed exclusion limits at 95% CL for $\sigma_{\mathrm{VBF}}(\mathrm{H}^{\pm\pm}_5) \times \mathcal{B}(\mathrm{H}^{\pm\pm}_5 \rightarrow W^{\pm}W^{\pm})$ as a function of the doubly-charged Higgs mass.

Expected and observed exclusion limits at 95% CL for $\sin\theta_{\mathrm{H}}$ as a function of the doubly-charged Higgs mass in the Georgi-Machacek model.

Expected (dashed black line) and observed (solid red line) 95% CL exclusion limits on the higgsino simplified model being considered. These are shown with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively. The limits set by the latest ATLAS searches using the soft lepton and disappearing track signatures are illustrated by the blue and green regions, respectively, while the limit imposed by the LEP experiments is shown in gray. The dot-dashed gray line indicates the predicted mass-splitting for the pure higgsino scenario.

Expected (dashed black line) and observed (solid red line) 95% CL exclusion limits on the higgsino simplified model being considered. These are shown with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively. The limits set by the latest ATLAS searches using the soft lepton and disappearing track signatures are illustrated by the blue and green regions, respectively, while the limit imposed by the LEP experiments is shown in gray. The dot-dashed gray line indicates the predicted mass-splitting for the pure higgsino scenario.

Expected (dashed black line) and observed (solid red line) 95% CL exclusion limits on the higgsino simplified model being considered. These are shown with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively. The limits set by the latest ATLAS searches using the soft lepton and disappearing track signatures are illustrated by the blue and green regions, respectively, while the limit imposed by the LEP experiments is shown in gray. The dot-dashed gray line indicates the predicted mass-splitting for the pure higgsino scenario.

Expected (dashed black line) and observed (solid red line) 95% CL exclusion limits on the higgsino simplified model being considered. These are shown with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively. The limits set by the latest ATLAS searches using the soft lepton and disappearing track signatures are illustrated by the blue and green regions, respectively, while the limit imposed by the LEP experiments is shown in gray. The dot-dashed gray line indicates the predicted mass-splitting for the pure higgsino scenario.

Expected and observed CLs values per signal point represented by the grey numbers. The expected (dashed) and observed (solid) 95% CL exclusion limits are overlaid along with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively.

Expected and observed CLs values per signal point represented by the grey numbers. The expected (dashed) and observed (solid) 95% CL exclusion limits are overlaid along with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively.

Expected and observed cross-section upper-limit per signal point represented by the grey numbers. The expected (dashed) and observed (solid) 95% CL exclusion limits are overlaid along with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively.

Expected and observed cross-section upper-limit per signal point represented by the grey numbers. The expected (dashed) and observed (solid) 95% CL exclusion limits are overlaid along with $\pm 1\sigma_{\mathrm{exp}}$ (yellow band) from experimental systematic and statistical uncertainties, and with $\pm 1\sigma_{\mathrm{theory}}^{\mathrm{SUSY}}$ (red dotted lines) from signal cross-section uncertainties, respectively.

Truth-level signal acceptances for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$) in a SR with the $S(d_0)$ requirement removed. The acceptance is defined as the fraction of accepted events divided by the total number of events in the generator-level signal Monte Carlo simulation, where the signal candidate track is identified as the charged particle with the largest distance between the interaction vertex and the secondary vertex of the higgsino decays.

Truth-level signal acceptances for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$) in a SR with the $S(d_0)$ requirement removed. The acceptance is defined as the fraction of accepted events divided by the total number of events in the generator-level signal Monte Carlo simulation, where the signal candidate track is identified as the charged particle with the largest distance between the interaction vertex and the secondary vertex of the higgsino decays.

Truth-level signal acceptances for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$) in a SR with the $S(d_0)$ requirement removed. The acceptance is defined as the fraction of accepted events divided by the total number of events in the generator-level signal Monte Carlo simulation, where the signal candidate track is identified as the charged particle with the largest distance between the interaction vertex and the secondary vertex of the higgsino decays.

Truth-level signal acceptances for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$) in a SR with the $S(d_0)$ requirement removed. The acceptance is defined as the fraction of accepted events divided by the total number of events in the generator-level signal Monte Carlo simulation, where the signal candidate track is identified as the charged particle with the largest distance between the interaction vertex and the secondary vertex of the higgsino decays.

Truth-level signal acceptances for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$) in a SR with the $S(d_0)$ requirement removed. The acceptance is defined as the fraction of accepted events divided by the total number of events in the generator-level signal Monte Carlo simulation, where the signal candidate track is identified as the charged particle with the largest distance between the interaction vertex and the secondary vertex of the higgsino decays.

Truth-level signal acceptances for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$) in a SR with the $S(d_0)$ requirement removed. The acceptance is defined as the fraction of accepted events divided by the total number of events in the generator-level signal Monte Carlo simulation, where the signal candidate track is identified as the charged particle with the largest distance between the interaction vertex and the secondary vertex of the higgsino decays.

Signal efficiencies in SR-Low for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Signal efficiencies in SR-Low for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Signal efficiencies in SR-Low for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Signal efficiencies in SR-Low for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Signal efficiencies in SR-Low for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Signal efficiencies in SR-Low for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Signal efficiencies in SR-High for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Signal efficiencies in SR-High for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Signal efficiencies in SR-High for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Signal efficiencies in SR-High for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Signal efficiencies in SR-High for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Signal efficiencies in SR-High for each production process ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$), defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level, where the $S(d_0)$ selecton efficiency has the largest impact. The higgsino decay products from $\Delta \mathrm{m}(\tilde{\chi}_1^\pm,\tilde{\chi}_1^0) < 0.4$ GeV signal have $p_{\mathrm{T}}$ too low to be reconstructed as the signal candidate tracks, and therefore the identified signal candidate tracks are typically from pile-up collisions or underlying events similar to the QCD track background, causing a low $S(d_0)$ selection efficiency in these plots.

Event selection cutflows for signal samples with $m(\tilde{\chi}_{1}^0)$ = 150 GeV and $\Delta m(\tilde{\chi}_{1}^\pm, \tilde{\chi}_{1}^0)$ = 1.5, 1.0, and 0.75 GeV, including all six production processes ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$). The cross-section used to obtain the initial number of events ($\sigma(\mathrm{n}_{\mathrm{jets}}) \geq 1$) refers to an emission of at least one gluon or quark with $p_{\mathrm{T}} > 50$ GeV at the parton level.

Event selection cutflows for signal samples with $m(\tilde{\chi}_{1}^0)$ = 150 GeV and $\Delta m(\tilde{\chi}_{1}^\pm, \tilde{\chi}_{1}^0)$ = 0.5, 0.35, and 0.25 GeV, including all six production processes ($\tilde{\chi}_1^\pm \tilde{\chi}_1^0$, $\tilde{\chi}_1^\pm \tilde{\chi}_2^0$, $\tilde{\chi}_1^+ \tilde{\chi}_1^-$, and $\tilde{\chi}_2^0 \tilde{\chi}_1^0$). The cross-section used to obtain the initial number of events ($\sigma(\mathrm{n}_{\mathrm{jets}}) \geq 1$) refers to an emission of at least one gluon or quark with $p_{\mathrm{T}} > 50$ GeV at the parton level.

The impact of the eight most important systematic uncertainties on \(R_t\), in %.

The post-fit yields in the two SRs. All uncertainties applied in the analysis are included.

Limits on EFT parameters and Vtb extracted from the analysis. The upper and lower limits correspond to 95% CL.

Results of the main analysis.

Pre-fit distribution of the NN discriminant \(D_{\text{nn}}\) in SR plus.

Post-fit distribution of the NN discriminant \(D_{\text{nn}}\) in SR plus.

Post-fit distribution of the \(\Delta\phi(\vec{p}_{T}^{miss},\mu)\) variable in the muon-plus CR.

Pre-fit distribution of the NN discriminant \(D_{\text{nn}}\) in SR minus.

Post-fit distribution of the NN discriminant \(D_{\text{nn}}\) in SR minus.

Post-fit distribution of the \(\Delta\phi(\vec{p}_{T}^{miss},\mu)\) variable in the muon-minus CR.

Pre-fit distribution of the invariant mass of the untagged jet and the b-tagged jet, \(m(jb)\), in SR plus.

Pre-fit distribution of the absolute value of the pseudorapidity of the untagged jet, \(|\eta(j)|\), in SR plus.

Pre-fit distribution of the absolute value of the difference in \(p_{\text{T}}\) between the reconstructed W boson and the jet pair, \(|\Delta p_{\text{T}}(W, jb)|\), in SR plus.

Pre-fit distribution of the difference in azimuth angle between the reconstructed W boson and the jet pair, \(|\Delta\phi(W, jb)|\), in SR plus.

Pre-fit distribution of the invariant mass of the reconstructed top quark, \(m(t)\), in SR plus.

Pre-fit distribution of the absolute value of the difference in pseudorapidity between the charged lepton and the untagged jet, \(|\Delta\eta(\ell ,j)|\), SR plus.

Pre-fit distribution of the angular distance of the charged lepton and the untagged jet, \(\Delta R(\ell ,j)\), in SR plus.

Pre-fit distribution of the absolute value of the difference in pseudorapidity between the b-tagged jet and the charged lepton, \(|\Delta\eta(b,\ell )|\), in SR plus.

Two-dimensional distribution of the invariant mass $m_{DV}$ and the track multiplicity in the High-pT jet SR for observed data events

Two-dimensional distribution of the invariant mass $m_{DV}$ and the track multiplicity in the High-pT jet SR for expected signal events in the strong gluino pair pair production model with m(gluino)=1.8 TeV, m(chi0)=0.2 TeV, tau(chi0)=0.1 ns

Two-dimensional distribution of the invariant mass $m_{DV}$ and the track multiplicity in the Trackless jet SR for observed data events

Two-dimensional distribution of the invariant mass $m_{DV}$ and the track multiplicity in the Trackless jet SR for expected signal events in the electroweak pair production model

Expected exclusion limits at 95% CL on the lifetime and mass of the neutralino in electroweakino pair production models

Expected (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in electroweakino pair production models

Expected (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in electroweakino pair production models

Observed exclusion limits at 95% CL on the lifetime and mass of the neutralino in electroweakino pair production models

Observed (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in electroweakino pair production models

Observed (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in electroweakino pair production models

Expected exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.4 TeV

Expected (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.4 TeV

Expected (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.4 TeV

Observed exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.4 TeV

Observed (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.4 TeV

Observed (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.4 TeV

Exclusion limits at 95% CL on the production cross section in the electroweak pair production model.

Exclusion limits at 95% CL on the production cross section in the strong gluino pair production models and m(gluino)=2.4 TeV

Expected exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.0 TeV

Expected (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.0 TeV

Expected (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.0 TeV

Observed exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.0 TeV

Observed (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.0 TeV

Observed (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.0 TeV

Expected exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.2 TeV

Expected (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.2 TeV

Expected (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.2 TeV

Observed exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.2 TeV

Observed (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.2 TeV

Observed (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the neutralino in strong gluino pair production models and m(gluino)=2.2 TeV

Expected exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=50 GeV

Expected (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=50 GeV

Expected (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=50 GeV

Observed exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=50 GeV

Observed (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=50 GeV

Observed (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=50 GeV

Expected exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=450 GeV

Expected (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=450 GeV

Expected (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=450 GeV

Observed exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=450 GeV

Observed (+1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=450 GeV

Observed (-1 sigma) exclusion limits at 95% CL on the lifetime and mass of the gluino in strong gluino pair production models and m(chi0)=450 GeV

Expected exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.01 ns

Expected (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.01 ns

Expected (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.01 ns

Observed exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.01 ns

Observed (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.01 ns

Observed (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.01 ns

Expected exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.1 ns

Expected (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.1 ns

Expected (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.1 ns

Observed exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.1 ns

Observed (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.1 ns

Observed (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=0.1 ns

Expected exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=1 ns

Expected (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=1 ns

Expected (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=1 ns

Observed exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=1 ns

Observed (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=1 ns

Observed (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=1 ns

Expected exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=10 ns

Expected (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=10 ns

Expected (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=10 ns

Observed exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=10 ns

Observed (+1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=10 ns

Observed (-1 sigma) exclusion limits at 95% CL on the mass of the gluino and neutralino in strong gluino pair production models and tau(chi0)=10 ns

Exclusion limits at 95% CL on the production cross section in the strong gluino pair production models and m($ ilde{\chi}^0_1$)=1.25 TeV

Acceptance cutflow for the High-pT SR for representative points in the strong gluino pair production model. See additional resources for more information.

Acceptance cutflow for the Trackless SR for representative points in the electroweak pair production model. See additional resources for more information.

Acceptance cutflow for the Trackless SR for representative points in the electroweak pair production model with heavy-flavor quarks final state. See additional resources for more information.

Acceptance cutflow for the High-pT SR for representative points in the electroweak pair production model with heavy-flavor quarks final state. See additional resources for more information.

Reinterpretation Material: Event-level Efficiency for HighPt SR selections, R < 1150 mm

Reinterpretation Material: Event-level Efficiency for HighPt SR selections, R [1150, 3870] mm

Reinterpretation Material: Event-level Efficiency for HighPt SR selections, R > 3870 mm

Reinterpretation Material: Event-level Efficiency for Trackless SR selections, R < 1150 mm

Reinterpretation Material: Event-level Efficiency for Trackless SR selections, R [1150, 3870] mm

Reinterpretation Material: Event-level Efficiency for Trackless SR selections, R > 3870 mm

Reinterpretation Material: Vertex-level Efficiency for R < 22 mm

Reinterpretation Material: Vertex-level Efficiency for R [22, 25] mm

Reinterpretation Material: Vertex-level Efficiency for R [25, 29] mm

Reinterpretation Material: Vertex-level Efficiency for R [29, 38] mm

Reinterpretation Material: Vertex-level Efficiency for R [38, 46] mm

Reinterpretation Material: Vertex-level Efficiency for R [46, 73] mm

Reinterpretation Material: Vertex-level Efficiency for R [73, 84] mm

Reinterpretation Material: Vertex-level Efficiency for R [84, 111] mm

Reinterpretation Material: Vertex-level Efficiency for R [111, 120] mm

Reinterpretation Material: Vertex-level Efficiency for R [120, 145] mm

Reinterpretation Material: Vertex-level Efficiency for R [145, 180] mm

Reinterpretation Material: Vertex-level Efficiency for R [180, 300] mm

Cutflow (acceptance x efficiency) for the High-pT SR for representative points in the strong gluino pair production model. See additional resources for more information.

Cutflow (acceptance x efficiency) for the Trackless SR for representative points in the electroweak pair production model. See additional resources for more information.

Cutflow (acceptance x efficiency) for the Trackless SR for representative points in the electroweak pair production model with heavy-flavor quarks. See additional resources for more information.

Cutflow (acceptance x efficiency) for the High-pT SR for representative points in the electroweak pair production model with heavy-flavor quarks. See additional resources for more information.

Observed 95% CL exclusion limits on the simplified models of chargino-pair production decaying via W bosons.

$+1\sigma$ observed 95% CL exclusion limits on the simplified models of chargino-pair production decaying via W bosons.

$-1\sigma$ observed 95% CL exclusion limits on the simplified models of chargino-pair production decaying via W bosons.

Expected 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.

$+1\sigma$ expected 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.

$-1\sigma$ expected 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.

Observed 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.

$+1\sigma$ observed 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.

$-1\sigma$ observed 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.

Expected 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and h bosons.

$+1\sigma$ expected 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and h bosons.

$-1\sigma$ expected 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and h bosons.

Observed 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and h bosons.

$+1\sigma$ observed 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and h bosons.

$-1\sigma$ observed 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and h bosons.

Expected 95% CL exclusion limits on the simplified models of higgsino GGM scenarios.

$+1\sigma$ expected 95% CL exclusion limits on the simplified models of higgsino GGM scenarios.

$-1\sigma$ expected 95% CL exclusion limits on the simplified models of higgsino GGM scenarios.

Observed 95% CL exclusion limits on the simplified models of higgsino GGM scenarios.

$+1\sigma$ observed 95% CL exclusion limits on the simplified models of higgsino GGM scenarios.

$-1\sigma$ observed 95% CL exclusion limits on the simplified models of higgsino GGM scenarios.

Observed upper limit on the signal cross section in fb for the production of $\tilde{\chi}_1^{+}\tilde{\chi}_{1}^{-}$.

The analyses used in combination for each scenario to set limits in models of the production of $\tilde{\chi}_1^{+}\tilde{\chi}_{1}^{-}$.

Observed upper limit on the signal cross section in fb for chargino--neutralino production decaying via W and Z bosons.

The analyses used in combination for each scenario to set limits in models of chargino--neutralino production decaying via W and Z bosons.

Expected 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.

$+1\sigma$ expected 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.

$-1\sigma$ expected 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.

Observed 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.

$+1\sigma$ observed 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.

$-1\sigma$ observed 95% CL exclusion limits on the simplified models of chargino--neutralino production decaying via W and Z bosons.

Observed upper limit on the signal cross section in fb for chargino--neutralino production decaying via W and h bosons.

The analyses used in combination for each scenario to set limits in models of chargino--neutralino production decaying via W and h bosons.

Observed upper limit on the signal cross section in fb for higgsino GGM scenarios.

The analyses used in combination for each scenario to set limits in higgsino GGM scenarios.

Parametrization of the $A_{X}$ factor, defined as the fraction of diphoton resonances satisfying the fiducial acceptance at the particle level, as function of $m_{X}$ obtained from the narrow width simulated signal samples produced in gluon fusion.

The correction factor, $C_{X}$, defined as the ratio between the number of reconstructed signal events passing the analysis cuts and the number of signal events at the particle level generated within the fiducial volume, and acceptance correction factor, $A_{X}$, defined as the fraction of diphoton resonances satisfying the fiducial acceptance at the particle level. Both are computed for NWA spin-0 models as a function of $m_{X}$.

Effect of event selections on a scalar MC signal sample generated for $m_{X}$ = 15 GeV and on the data. For the MC sample, the efficiencies are shown after applying event weights and a truth level filter that requires two photons with $p^{\gamma\gamma}_{T}>40$ GeV; for the data, the absolute yields are shown. The initial yields for data include a trigger preselection that is the OR of a list of single photon and diphoton triggers. The "2 $loose$ photons" step includes the kinematic acceptance cuts.

Parameterization of the Double Sided Crystal Ball function parameters describing the scalar mass resolution model as a function of $m_{X}$ [GeV].

Observed (solid line) and expected (dashed line) 95\% CL limits on the product of the production cross section times the branching ratio of a narrow width spin-0 resonance $X$ produced via gluon-gluon initial states decaying to a $Z$ boson and a photon, $\sigma(pp\to X)\cdot\mathcal{B}(X\to Z\gamma)$, as a function of the resonance mass $m_{X}$. Observed (expected) results are derived from ensemble tests for $m_{X}>1850 (900)$~\GeV. The green and yellow solid bands correspond to the $\pm1\sigma$ and $\pm2\sigma$ intervals for the expected upper limits. The limits in the $m_{X}$ ranges from 220 GeV to 3400 GeV and are obtained from the combined $ee\gamma$ and $\mu\mu\gamma$ channels.

Observed (solid line) and expected (dashed line) 95\% CL limits on the product of the production cross section times the branching ratio of a narrow width spin-2 resonance $X$ produced via gluon-gluon initial states decaying to a $Z$ boson and a photon, $\sigma(pp\to X)\cdot\mathcal{B}(X\to Z\gamma)$, as a function of the resonance mass $m_{X}$. Observed (expected) results are derived from ensemble tests for $m_{X}>1850 (900)$~\GeV. The green and yellow solid bands correspond to the $\pm1\sigma$ and $\pm2\sigma$ intervals for the expected upper limit respectively. The limits in the $m_{X}$ ranges from 220 GeV to 3400 GeV and are obtained from the combined $ee\gamma$ and $\mu\mu\gamma$ channels..

Observed (solid line) and expected (dashed line) 95\% CL limits on the product of the production cross section times the branching ratio of a narrow width spin-2 resonance $X$ produced via $q\bar{q}$ initial states decaying to a $Z$ boson and a photon, $\sigma(pp\to X)\cdot\mathcal{B}(X\to Z\gamma)$, as a function of the resonance mass $m_{X}$. Observed (expected) results are derived from ensemble tests for $m_{X}>1850 (900)$~\GeV. The green and yellow solid bands correspond to the $\pm1\sigma$ and $\pm2\sigma$ intervals for the expected upper limit respectively. The limits in the $m_{X}$ ranges from 220 GeV to 3400 GeV and are obtained from the combined $ee\gamma$ and $\mu\mu\gamma$ channels.

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.