Covariance matrix of the absolute differential cross-section as function of $m^{bl}_{minimax}$ at particle level in the exclusive topology, accounting for the MC statistical uncertainties.

Relative differential cross-section as a function of $m^{bl}_{minimax}$ at particle level in the exclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections. The covariance matrices are evaluated using pseudo-experiments for data and MC statistical uncertainties, and added to the individual covariance matrices for the remaining uncertainties, as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $m^{bl}_{minimax}$ at particle level in the exclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the relative differential cross-section as function of $m^{bl}_{minimax}$ at particle level in the exclusive topology, accounting for the MC statistical uncertainties.

Total cross-section at particle level in the exclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the absolute differential cross-section as function of $\sigma_{WbWb}$ at particle level in the exclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the absolute differential cross-section as function of $\sigma_{WbWb}$ at particle level in the exclusive topology, accounting for the MC statistical uncertainties.

Absolute differential cross-section as a function of $N^{jets}$ at particle level in the inclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections. The covariance matrices are evaluated using pseudo-experiments for data and MC statistical uncertainties, and added to the individual covariance matrices for the remaining uncertainties, as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator. The last bin includes overflow events.

Covariance matrix of the absolute differential cross-section as function of $N^{jets}$ at particle level in the inclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the absolute differential cross-section as function of $N^{jets}$ at particle level in the inclusive topology, accounting for the MC statistical uncertainties.

Relative differential cross-section as a function of $N^{jets}$ at particle level in the inclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections. The covariance matrices are evaluated using pseudo-experiments for data and MC statistical uncertainties, and added to the individual covariance matrices for the remaining uncertainties, as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator. The last bin includes overflow events.

Covariance matrix of the relative differential cross-section as function of $N^{jets}$ at particle level in the inclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the relative differential cross-section as function of $N^{jets}$ at particle level in the inclusive topology, accounting for the MC statistical uncertainties.

Absolute differential cross-section as a function of $m^{bbll}$ at particle level in the inclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections. The covariance matrices are evaluated using pseudo-experiments for data and MC statistical uncertainties, and added to the individual covariance matrices for the remaining uncertainties, as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the absolute differential cross-section as function of $m^{bbll}$ at particle level in the inclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the absolute differential cross-section as function of $m^{bbll}$ at particle level in the inclusive topology, accounting for the MC statistical uncertainties.

Relative differential cross-section as a function of $m^{bbll}$ at particle level in the inclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections. The covariance matrices are evaluated using pseudo-experiments for data and MC statistical uncertainties, and added to the individual covariance matrices for the remaining uncertainties, as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $m^{bbll}$ at particle level in the inclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the relative differential cross-section as function of $m^{bbll}$ at particle level in the inclusive topology, accounting for the MC statistical uncertainties.

Absolute differential cross-section as a function of $m_{T}^{bb4l}$ at particle level in the inclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections. The covariance matrices are evaluated using pseudo-experiments for data and MC statistical uncertainties, and added to the individual covariance matrices for the remaining uncertainties, as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the absolute differential cross-section as function of $m_{T}^{bb4l}$ at particle level in the inclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the absolute differential cross-section as function of $m_{T}^{bb4l}$ at particle level in the inclusive topology, accounting for the MC statistical uncertainties.

Relative differential cross-section as a function of $m_{T}^{bb4l}$ at particle level in the inclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections. The covariance matrices are evaluated using pseudo-experiments for data and MC statistical uncertainties, and added to the individual covariance matrices for the remaining uncertainties, as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $m_{T}^{bb4l}$ at particle level in the inclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the relative differential cross-section as function of $m_{T}^{bb4l}$ at particle level in the inclusive topology, accounting for the MC statistical uncertainties.

Absolute differential cross-section as a function of $p_{T}^{b1b2}$ at particle level in the inclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections. The covariance matrices are evaluated using pseudo-experiments for data and MC statistical uncertainties, and added to the individual covariance matrices for the remaining uncertainties, as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the absolute differential cross-section as function of $p_{T}^{b1b2}$ at particle level in the inclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the absolute differential cross-section as function of $p_{T}^{b1b2}$ at particle level in the inclusive topology, accounting for the MC statistical uncertainties.

Relative differential cross-section as a function of $p_{T}^{b1b2}$ at particle level in the inclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections. The covariance matrices are evaluated using pseudo-experiments for data and MC statistical uncertainties, and added to the individual covariance matrices for the remaining uncertainties, as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $p_{T}^{b1b2}$ at particle level in the inclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the relative differential cross-section as function of $p_{T}^{b1b2}$ at particle level in the inclusive topology, accounting for the MC statistical uncertainties.

Absolute differential cross-section as a function of $p_{T}^{jet1}$ at particle level in the inclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections. The covariance matrices are evaluated using pseudo-experiments for data and MC statistical uncertainties, and added to the individual covariance matrices for the remaining uncertainties, as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the absolute differential cross-section as function of $p_{T}^{jet1}$ at particle level in the inclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the absolute differential cross-section as function of $p_{T}^{jet1}$ at particle level in the inclusive topology, accounting for the MC statistical uncertainties.

Relative differential cross-section as a function of $p_{T}^{jet1}$ at particle level in the inclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections. The covariance matrices are evaluated using pseudo-experiments for data and MC statistical uncertainties, and added to the individual covariance matrices for the remaining uncertainties, as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $p_{T}^{jet1}$ at particle level in the inclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the relative differential cross-section as function of $p_{T}^{jet1}$ at particle level in the inclusive topology, accounting for the MC statistical uncertainties.

Absolute differential cross-section as a function of $p_{T}^{jet2}$ at particle level in the inclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections. The covariance matrices are evaluated using pseudo-experiments for data and MC statistical uncertainties, and added to the individual covariance matrices for the remaining uncertainties, as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the absolute differential cross-section as function of $p_{T}^{jet2}$ at particle level in the inclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the absolute differential cross-section as function of $p_{T}^{jet2}$ at particle level in the inclusive topology, accounting for the MC statistical uncertainties.

Relative differential cross-section as a function of $p_{T}^{jet2}$ at particle level in the inclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections. The covariance matrices are evaluated using pseudo-experiments for data and MC statistical uncertainties, and added to the individual covariance matrices for the remaining uncertainties, as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $p_{T}^{jet2}$ at particle level in the inclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the relative differential cross-section as function of $p_{T}^{jet2}$ at particle level in the inclusive topology, accounting for the MC statistical uncertainties.

Absolute differential cross-section as a function of $p_{T}^{lep1}$ at particle level in the inclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections. The covariance matrices are evaluated using pseudo-experiments for data and MC statistical uncertainties, and added to the individual covariance matrices for the remaining uncertainties, as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the absolute differential cross-section as function of $p_{T}^{lep1}$ at particle level in the inclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the absolute differential cross-section as function of $p_{T}^{lep1}$ at particle level in the inclusive topology, accounting for the MC statistical uncertainties.

Relative differential cross-section as a function of $p_{T}^{lep1}$ at particle level in the inclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections. The covariance matrices are evaluated using pseudo-experiments for data and MC statistical uncertainties, and added to the individual covariance matrices for the remaining uncertainties, as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $p_{T}^{lep1}$ at particle level in the inclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the relative differential cross-section as function of $p_{T}^{lep1}$ at particle level in the inclusive topology, accounting for the MC statistical uncertainties.

Absolute differential cross-section as a function of $p_{T}^{lep2}$ at particle level in the inclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections. The covariance matrices are evaluated using pseudo-experiments for data and MC statistical uncertainties, and added to the individual covariance matrices for the remaining uncertainties, as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the absolute differential cross-section as function of $p_{T}^{lep2}$ at particle level in the inclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the absolute differential cross-section as function of $p_{T}^{lep2}$ at particle level in the inclusive topology, accounting for the MC statistical uncertainties.

Relative differential cross-section as a function of $p_{T}^{lep2}$ at particle level in the inclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections. The covariance matrices are evaluated using pseudo-experiments for data and MC statistical uncertainties, and added to the individual covariance matrices for the remaining uncertainties, as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $p_{T}^{lep2}$ at particle level in the inclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the relative differential cross-section as function of $p_{T}^{lep2}$ at particle level in the inclusive topology, accounting for the MC statistical uncertainties.

Absolute differential cross-section as a function of $p_{T}^{bb4l}$ at particle level in the inclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections. The covariance matrices are evaluated using pseudo-experiments for data and MC statistical uncertainties, and added to the individual covariance matrices for the remaining uncertainties, as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the absolute differential cross-section as function of $p_{T}^{bb4l}$ at particle level in the inclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the absolute differential cross-section as function of $p_{T}^{bb4l}$ at particle level in the inclusive topology, accounting for the MC statistical uncertainties.

Relative differential cross-section as a function of $p_{T}^{bb4l}$ at particle level in the inclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections. The covariance matrices are evaluated using pseudo-experiments for data and MC statistical uncertainties, and added to the individual covariance matrices for the remaining uncertainties, as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $p_{T}^{bb4l}$ at particle level in the inclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the relative differential cross-section as function of $p_{T}^{bb4l}$ at particle level in the inclusive topology, accounting for the MC statistical uncertainties.

Absolute differential cross-section as a function of $p_{T}^{bbll}$ at particle level in the inclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections. The covariance matrices are evaluated using pseudo-experiments for data and MC statistical uncertainties, and added to the individual covariance matrices for the remaining uncertainties, as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the absolute differential cross-section as function of $p_{T}^{bbll}$ at particle level in the inclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the absolute differential cross-section as function of $p_{T}^{bbll}$ at particle level in the inclusive topology, accounting for the MC statistical uncertainties.

Relative differential cross-section as a function of $p_{T}^{bbll}$ at particle level in the inclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections. The covariance matrices are evaluated using pseudo-experiments for data and MC statistical uncertainties, and added to the individual covariance matrices for the remaining uncertainties, as described in the text. The measured differential cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the relative differential cross-section as function of $p_{T}^{bbll}$ at particle level in the inclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the relative differential cross-section as function of $p_{T}^{bbll}$ at particle level in the inclusive topology, accounting for the MC statistical uncertainties.

Total cross-section at particle level in the inclusive topology. Note that the values shown here are obtained by propagating the individual uncertainties to the measured cross-sections, while the covariance matrices are evaluated using pseudo-experiments as described in the text. The measured cross-section is compared with the prediction obtained with the Powheg+Pythia8 Monte Carlo generator.

Covariance matrix of the absolute differential cross-section as function of $\sigma_{WbWb}$ at particle level in the inclusive topology, accounting for the data statistical uncertainties.

Covariance matrix of the absolute differential cross-section as function of $\sigma_{WbWb}$ at particle level in the inclusive topology, accounting for the MC statistical uncertainties.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $\sigma_{WbWb}$ in the exclusive topology and as function of $m^{bl}_{minimax}$ in the exclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $m^{bl}_{minimax}$ in the exclusive topology and as function of $N^{jets}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $m^{bl}_{minimax}$ in the exclusive topology and as function of $m^{bbll}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $m^{bl}_{minimax}$ in the exclusive topology and as function of $m_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $m^{bl}_{minimax}$ in the exclusive topology and as function of $p_{T}^{b1b2}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $m^{bl}_{minimax}$ in the exclusive topology and as function of $p_{T}^{jet1}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $m^{bl}_{minimax}$ in the exclusive topology and as function of $p_{T}^{jet2}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $m^{bl}_{minimax}$ in the exclusive topology and as function of $p_{T}^{lep1}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $m^{bl}_{minimax}$ in the exclusive topology and as function of $p_{T}^{lep2}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $m^{bl}_{minimax}$ in the exclusive topology and as function of $p_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $m^{bl}_{minimax}$ in the exclusive topology and as function of $p_{T}^{bbll}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $m^{bl}_{minimax}$ in the exclusive topology and as function of $\sigma_{WbWb}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $\sigma_{WbWb}$ in the exclusive topology and as function of $N^{jets}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $\sigma_{WbWb}$ in the exclusive topology and as function of $m^{bbll}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $\sigma_{WbWb}$ in the exclusive topology and as function of $m_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $\sigma_{WbWb}$ in the exclusive topology and as function of $p_{T}^{b1b2}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $\sigma_{WbWb}$ in the exclusive topology and as function of $p_{T}^{jet1}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $\sigma_{WbWb}$ in the exclusive topology and as function of $p_{T}^{jet2}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $\sigma_{WbWb}$ in the exclusive topology and as function of $p_{T}^{lep1}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $\sigma_{WbWb}$ in the exclusive topology and as function of $p_{T}^{lep2}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $\sigma_{WbWb}$ in the exclusive topology and as function of $p_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $\sigma_{WbWb}$ in the exclusive topology and as function of $p_{T}^{bbll}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $\sigma_{WbWb}$ in the exclusive topology and as function of $\sigma_{WbWb}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $m^{bbll}$ in the inclusive topology and as function of $N^{jets}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $m^{bbll}$ in the inclusive topology and as function of $m_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $m^{bbll}$ in the inclusive topology and as function of $p_{T}^{b1b2}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{jet1}$ in the inclusive topology and as function of $m^{bbll}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{jet2}$ in the inclusive topology and as function of $p_{T}^{jet1}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{lep1}$ in the inclusive topology and as function of $p_{T}^{jet2}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{lep2}$ in the inclusive topology and as function of $p_{T}^{lep1}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{lep2}$ in the inclusive topology and as function of $p_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{lep2}$ in the inclusive topology and as function of $p_{T}^{bbll}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $\sigma_{WbWb}$ in the inclusive topology and as function of $p_{T}^{lep2}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $m_{T}^{bb4l}$ in the inclusive topology and as function of $N^{jets}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{b1b2}$ in the inclusive topology and as function of $N^{jets}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{jet1}$ in the inclusive topology and as function of $N^{jets}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{jet1}$ in the inclusive topology and as function of $m_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{jet1}$ in the inclusive topology and as function of $p_{T}^{b1b2}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{jet2}$ in the inclusive topology and as function of $N^{jets}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{jet2}$ in the inclusive topology and as function of $m^{bbll}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{jet2}$ in the inclusive topology and as function of $m_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{jet2}$ in the inclusive topology and as function of $p_{T}^{b1b2}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{lep1}$ in the inclusive topology and as function of $N^{jets}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{lep1}$ in the inclusive topology and as function of $m^{bbll}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{lep1}$ in the inclusive topology and as function of $m_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{lep1}$ in the inclusive topology and as function of $p_{T}^{b1b2}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{lep1}$ in the inclusive topology and as function of $p_{T}^{jet1}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{lep2}$ in the inclusive topology and as function of $N^{jets}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{lep2}$ in the inclusive topology and as function of $m^{bbll}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{lep2}$ in the inclusive topology and as function of $m_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{lep2}$ in the inclusive topology and as function of $p_{T}^{b1b2}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{lep2}$ in the inclusive topology and as function of $p_{T}^{jet1}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{lep2}$ in the inclusive topology and as function of $p_{T}^{jet2}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $N^{jets}$ in the inclusive topology and as function of $p_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{bbll}$ in the inclusive topology and as function of $N^{jets}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{bbll}$ in the inclusive topology and as function of $m^{bbll}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{bbll}$ in the inclusive topology and as function of $m_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{bbll}$ in the inclusive topology and as function of $p_{T}^{b1b2}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $p_{T}^{jet1}$ in the inclusive topology and as function of $p_{T}^{bbll}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $\sigma_{WbWb}$ in the inclusive topology and as function of $N^{jets}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $\sigma_{WbWb}$ in the inclusive topology and as function of $m^{bbll}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $\sigma_{WbWb}$ in the inclusive topology and as function of $m_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $\sigma_{WbWb}$ in the inclusive topology and as function of $p_{T}^{b1b2}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $\sigma_{WbWb}$ in the inclusive topology and as function of $p_{T}^{jet1}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $\sigma_{WbWb}$ in the inclusive topology and as function of $p_{T}^{jet2}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $\sigma_{WbWb}$ in the inclusive topology and as function of $p_{T}^{lep1}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $\sigma_{WbWb}$ in the inclusive topology and as function of $p_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the absolute differential cross-sections at particle level as function of $\sigma_{WbWb}$ in the inclusive topology and as function of $p_{T}^{bbll}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $m^{bl}_{minimax}$ in the exclusive topology and as function of $N^{jets}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $m^{bl}_{minimax}$ in the exclusive topology and as function of $m^{bbll}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $m^{bl}_{minimax}$ in the exclusive topology and as function of $m_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $m^{bl}_{minimax}$ in the exclusive topology and as function of $p_{T}^{b1b2}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $m^{bl}_{minimax}$ in the exclusive topology and as function of $p_{T}^{jet1}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $m^{bl}_{minimax}$ in the exclusive topology and as function of $p_{T}^{jet2}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $m^{bl}_{minimax}$ in the exclusive topology and as function of $p_{T}^{lep1}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $m^{bl}_{minimax}$ in the exclusive topology and as function of $p_{T}^{lep2}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $m^{bl}_{minimax}$ in the exclusive topology and as function of $p_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $m^{bl}_{minimax}$ in the exclusive topology and as function of $p_{T}^{bbll}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $m^{bbll}$ in the inclusive topology and as function of $N^{jets}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $m^{bbll}$ in the inclusive topology and as function of $m_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $m^{bbll}$ in the inclusive topology and as function of $p_{T}^{b1b2}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{jet1}$ in the inclusive topology and as function of $m^{bbll}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{jet2}$ in the inclusive topology and as function of $p_{T}^{jet1}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{lep1}$ in the inclusive topology and as function of $p_{T}^{jet2}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{lep2}$ in the inclusive topology and as function of $p_{T}^{lep1}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{lep2}$ in the inclusive topology and as function of $p_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{lep2}$ in the inclusive topology and as function of $p_{T}^{bbll}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $m_{T}^{bb4l}$ in the inclusive topology and as function of $N^{jets}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{b1b2}$ in the inclusive topology and as function of $N^{jets}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{jet1}$ in the inclusive topology and as function of $N^{jets}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{jet1}$ in the inclusive topology and as function of $m_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{jet1}$ in the inclusive topology and as function of $p_{T}^{b1b2}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{jet2}$ in the inclusive topology and as function of $N^{jets}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{jet2}$ in the inclusive topology and as function of $m^{bbll}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{jet2}$ in the inclusive topology and as function of $m_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{jet2}$ in the inclusive topology and as function of $p_{T}^{b1b2}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{lep1}$ in the inclusive topology and as function of $N^{jets}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{lep1}$ in the inclusive topology and as function of $m^{bbll}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{lep1}$ in the inclusive topology and as function of $m_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{lep1}$ in the inclusive topology and as function of $p_{T}^{b1b2}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{lep1}$ in the inclusive topology and as function of $p_{T}^{jet1}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{lep2}$ in the inclusive topology and as function of $N^{jets}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{lep2}$ in the inclusive topology and as function of $m^{bbll}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{lep2}$ in the inclusive topology and as function of $m_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{lep2}$ in the inclusive topology and as function of $p_{T}^{b1b2}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{lep2}$ in the inclusive topology and as function of $p_{T}^{jet1}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{lep2}$ in the inclusive topology and as function of $p_{T}^{jet2}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $N^{jets}$ in the inclusive topology and as function of $p_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{bbll}$ in the inclusive topology and as function of $N^{jets}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{bbll}$ in the inclusive topology and as function of $m^{bbll}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{bbll}$ in the inclusive topology and as function of $m_{T}^{bb4l}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{bbll}$ in the inclusive topology and as function of $p_{T}^{b1b2}$ in the inclusive topology.

Statistical covariance matrix between the relative differential cross-sections at particle level as function of $p_{T}^{jet1}$ in the inclusive topology and as function of $p_{T}^{bbll}$ in the inclusive topology.

Cutflows and signal efficiencies for the Stealth SYY SUSY model in the $1\ell$ channel corresponding to two values of $m_{\tilde{t}}$.

Cutflows and signal efficiencies for the RPV SUSY model in the $2\ell$ channel corresponding to two values of $m_{\tilde{t}}$.

Cutflows and signal efficiencies for the Stealth SYY SUSY model in the $2\ell$ channel corresponding to two values of $m_{\tilde{t}}$.

Signal efficiencies for the RPV SUSY model in the $0\ell$ channel corresponding to the four ABCD regions

Signal efficiencies for the SYY SUSY model in the $0\ell$ channel corresponding to the four ABCD regions

Signal efficiencies for the RPV SUSY model in the $1\ell$ channel corresponding to the four ABCD regions

Signal efficiencies for the SYY SUSY model in the $1\ell$ channel corresponding to the four ABCD regions

Signal efficiencies for the RPV SUSY model in the $2\ell$ channel corresponding to the four ABCD regions

Signal efficiencies for the SYY SUSY model in the $2\ell$ channel corresponding to the four ABCD regions

Expected and observed 95% CL upper limit on the top squark pair production cross section as a function of the top squark mass for the RPV SUSY model in the $0\ell$ channel

Expected and observed 95% CL upper limit on the top squark pair production cross section as a function of the top squark mass for the RPV SUSY model in the $1\ell$ channel

Expected and observed 95% CL upper limit on the top squark pair production cross section as a function of the top squark mass for the RPV SUSY model in the $2\ell$ channel

Expected and observed 95% CL upper limit on the top squark pair production cross section as a function of the top squark mass for the RPV SUSY model in the Combo channel

The $N_{jets}$ distributions from the background-only fits to data in the $0\ell$. The signal distribution overlaid corresponds to the RPV model with $m_{\tilde{t}} = 400$ GeV with the signal strength parameter $r$ set to one. The four pannels in each row show the $N_{jets}$ distributions for the A, B, C, and D regions (left to right).

The $N_{jets}$ distributions from the background-only fits to data in the $1\ell$. The signal distribution overlaid corresponds to the RPV model with $m_{\tilde{t}} = 400$ GeV with the signal strength parameter $r$ set to one. The four pannels in each row show the $N_{jets}$ distributions for the A, B, C, and D regions (left to right).

The $N_{jets}$ distributions from the background-only fits to data in the $2\ell$. The signal distribution overlaid corresponds to the RPV model with $m_{\tilde{t}} = 400$ GeV with the signal strength parameter $r$ set to one. The four pannels in each row show the $N_{jets}$ distributions for the A, B, C, and D regions (left to right).

The $N_{jets}$ distributions from the background-only fits to data in the $0\ell$. The signal distribution overlaid corresponds to the RPV model with $m_{\tilde{t}} = 800$ GeV with the signal strength parameter $r$ set to one. The four pannels in each row show the $N_{jets}$ distributions for the A, B, C, and D regions (left to right).

The $N_{jets}$ distributions from the background-only fits to data in the $1\ell$. The signal distribution overlaid corresponds to the RPV model with $m_{\tilde{t}} = 800$ GeV with the signal strength parameter $r$ set to one. The four pannels in each row show the $N_{jets}$ distributions for the A, B, C, and D regions (left to right).

The $N_{jets}$ distributions from the background-only fits to data in the $2\ell$. The signal distribution overlaid corresponds to the RPV model with $m_{\tilde{t}} = 800$ GeV with the signal strength parameter $r$ set to one. The four pannels in each row show the $N_{jets}$ distributions for the A, B, C, and D regions (left to right).

Expected and observed 95% CL upper limit on the top squark pair production cross section as a function of the top squark mass for the SYY SUSY model in the $0\ell$ channel

Expected and observed 95% CL upper limit on the top squark pair production cross section as a function of the top squark mass for the SYY SUSY model in the $1\ell$ channel

Expected and observed 95% CL upper limit on the top squark pair production cross section as a function of the top squark mass for the SYY SUSY model in the $2\ell$ channel

Expected and observed 95% CL upper limit on the top squark pair production cross section as a function of the top squark mass for the SYY SUSY model in the Combo channel

The $N_{jets}$ distributions from the background-only fits to data in the $0\ell$. The signal distribution overlaid corresponds to the Stealth SYY model with $m_{\tilde{t}} = 400$ GeV with the signal strength parameter $r$ set to one. The four pannels in each row show the $N_{jets}$ distributions for the A, B, C, and D regions (left to right).

The $N_{jets}$ distributions from the background-only fits to data in the $1\ell$. The signal distribution overlaid corresponds to the Stealth SYY model with $m_{\tilde{t}} = 400$ GeV with the signal strength parameter $r$ set to one. The four pannels in each row show the $N_{jets}$ distributions for the A, B, C, and D regions (left to right).

The $N_{jets}$ distributions from the background-only fits to data in the $2\ell$. The signal distribution overlaid corresponds to the Stealth SYY model with $m_{\tilde{t}} = 400$ GeV with the signal strength parameter $r$ set to one. The four pannels in each row show the $N_{jets}$ distributions for the A, B, C, and D regions (left to right).

The $N_{jets}$ distributions from the background-only fits to data in the $0\ell$. The signal distribution overlaid corresponds to the Stealth SYY model with $m_{\tilde{t}} = 800$ GeV with the signal strength parameter $r$ set to one. The four pannels in each row show the $N_{jets}$ distributions for the A, B, C, and D regions (left to right).

The $N_{jets}$ distributions from the background-only fits to data in the $1\ell$. The signal distribution overlaid corresponds to the Stealth SYY model with $m_{\tilde{t}} = 800$ GeV with the signal strength parameter $r$ set to one. The four pannels in each row show the $N_{jets}$ distributions for the A, B, C, and D regions (left to right).

The $N_{jets}$ distributions from the background-only fits to data in the $2\ell$. The signal distribution overlaid corresponds to the Stealth SYY model with $m_{\tilde{t}} = 800$ GeV with the signal strength parameter $r$ set to one. The four pannels in each row show the $N_{jets}$ distributions for the A, B, C, and D regions (left to right).

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $p_{\mathrm{T}}^{\mathrm{lead.\,lep.}}$.

Fiducial differential cross-sections as a function of $p_{\mathrm{T}}^{\mathrm{sub-lead.\,lep.}}$. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The right-hand-side axis indicates the integrated cross-section of the rightmost bin. The results are compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1, with the NNLO + PS predictions from Powheg MiNNLO + Pythia8 and Geneva + Pythia8, as well as Sherpa2.2.12 NLO + PS predictions. The last three predictions are combined with Sherpa 2.2.2 for the $gg$ initial state and Sherpa 2.2.12 for electroweak $WWjj$ production. These contributions are modelled at LO but a NLO QCD $k$-factor of 1.7 is applied for gluon induced production. Theoretical predictions are indicated as markers with vertical lines denoting PDF, scale and parton shower uncertainties. Markers are staggered for better visibility.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $p_{\mathrm{T}}^{\mathrm{sub-lead.\,lep.}}$.

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $p_{\mathrm{T}}^{\mathrm{sub-lead.\,lep.}}$.

Fiducial differential cross-sections as a function of $p_{\mathrm{T},e\mu}$. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The right-hand-side axis indicates the integrated cross-section of the rightmost bin. The results are compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1, with the NNLO + PS predictions from Powheg MiNNLO + Pythia8 and Geneva + Pythia8, as well as Sherpa2.2.12 NLO + PS predictions. The last three predictions are combined with Sherpa 2.2.2 for the $gg$ initial state and Sherpa 2.2.12 for electroweak $WWjj$ production. These contributions are modelled at LO but a NLO QCD $k$-factor of 1.7 is applied for gluon induced production. Theoretical predictions are indicated as markers with vertical lines denoting PDF, scale and parton shower uncertainties. Markers are staggered for better visibility.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $p_{\mathrm{T},e\mu}$.

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $p_{\mathrm{T},e\mu}$.

Fiducial differential cross-sections as a function of $|y_{e\mu}|$. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The results are compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1, with the NNLO + PS predictions from Powheg MiNNLO + Pythia8 and Geneva + Pythia8, as well as Sherpa2.2.12 NLO + PS predictions. The last three predictions are combined with Sherpa 2.2.2 for the $gg$ initial state and Sherpa 2.2.12 for electroweak $WWjj$ production. These contributions are modelled at LO but a NLO QCD $k$-factor of 1.7 is applied for gluon induced production. Theoretical predictions are indicated as markers with vertical lines denoting PDF, scale and parton shower uncertainties. Markers are staggered for better visibility.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $|y_{e\mu}|$.

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $|y_{e\mu}|$.

Fiducial differential cross-sections as a function of $m_{e\mu}$. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The right-hand-side axis indicates the integrated cross-section of the rightmost bin. The results are compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1, with the NNLO + PS predictions from Powheg MiNNLO + Pythia8 and Geneva + Pythia8, as well as Sherpa2.2.12 NLO + PS predictions. The last three predictions are combined with Sherpa 2.2.2 for the $gg$ initial state and Sherpa 2.2.12 for electroweak $WWjj$ production. These contributions are modelled at LO but a NLO QCD $k$-factor of 1.7 is applied for gluon induced production. Theoretical predictions are indicated as markers with vertical lines denoting PDF, scale and parton shower uncertainties. Markers are staggered for better visibility.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $m_{e\mu}$.

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $m_{e\mu}$.

Fiducial differential cross-sections as a function of $|\Delta\phi_{e\mu}|$. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The results are compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1, with the NNLO + PS predictions from Powheg MiNNLO + Pythia8 and Geneva + Pythia8, as well as Sherpa2.2.12 NLO + PS predictions. The last three predictions are combined with Sherpa 2.2.2 for the $gg$ initial state and Sherpa 2.2.12 for electroweak $WWjj$ production. These contributions are modelled at LO but a NLO QCD $k$-factor of 1.7 is applied for gluon induced production. Theoretical predictions are indicated as markers with vertical lines denoting PDF, scale and parton shower uncertainties. Markers are staggered for better visibility.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $|\Delta\phi_{e\mu}|$.

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $|\Delta\phi_{e\mu}|$.

Fiducial differential cross-sections as a function of $\cos(\theta^{*})$. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The results are compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1, with the NNLO + PS predictions from Powheg MiNNLO + Pythia8 and Geneva + Pythia8, as well as Sherpa2.2.12 NLO + PS predictions. The last three predictions are combined with Sherpa 2.2.2 for the $gg$ initial state and Sherpa 2.2.12 for electroweak $WWjj$ production. These contributions are modelled at LO but a NLO QCD $k$-factor of 1.7 is applied for gluon induced production. Theoretical predictions are indicated as markers with vertical lines denoting PDF, scale and parton shower uncertainties. Markers are staggered for better visibility.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $\cos(\theta^{*})$.

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $\cos(\theta^{*})$.

Fiducial differential cross-sections as a function of $E_{\mathrm{T}}^{\mathrm{miss}}$. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The right-hand-side axis indicates the integrated cross-section of the rightmost bin. The results are compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1, with the NNLO + PS predictions from Powheg MiNNLO + Pythia8 and Geneva + Pythia8, as well as Sherpa2.2.12 NLO + PS predictions. The last three predictions are combined with Sherpa 2.2.2 for the $gg$ initial state and Sherpa 2.2.12 for electroweak $WWjj$ production. These contributions are modelled at LO but a NLO QCD $k$-factor of 1.7 is applied for gluon induced production. Theoretical predictions are indicated as markers with vertical lines denoting PDF, scale and parton shower uncertainties. Markers are staggered for better visibility.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $E_{\mathrm{T}}^{\mathrm{miss}}$.

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $E_{\mathrm{T}}^{\mathrm{miss}}$.

Fiducial differential cross-sections as a function of $H_{\mathrm{T}}^{\mathrm{lep}+\mathrm{MET}}$. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The right-hand-side axis indicates the integrated cross-section of the rightmost bin. The results are compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1, with the NNLO + PS predictions from Powheg MiNNLO + Pythia8 and Geneva + Pythia8, as well as Sherpa2.2.12 NLO + PS predictions. The last three predictions are combined with Sherpa 2.2.2 for the $gg$ initial state and Sherpa 2.2.12 for electroweak $WWjj$ production. These contributions are modelled at LO but a NLO QCD $k$-factor of 1.7 is applied for gluon induced production. Theoretical predictions are indicated as markers with vertical lines denoting PDF, scale and parton shower uncertainties. Markers are staggered for better visibility.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $H_{\mathrm{T}}^{\mathrm{lep}+\mathrm{MET}}$.

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $H_{\mathrm{T}}^{\mathrm{lep}+\mathrm{MET}}$.

Fiducial differential cross-sections as a function of $m_{\mathrm{T},e\mu}$. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The right-hand-side axis indicates the integrated cross-section of the rightmost bin. The results are compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1, with the NNLO + PS predictions from Powheg MiNNLO + Pythia8 and Geneva + Pythia8, as well as Sherpa2.2.12 NLO + PS predictions. The last three predictions are combined with Sherpa 2.2.2 for the $gg$ initial state and Sherpa 2.2.12 for electroweak $WWjj$ production. These contributions are modelled at LO but a NLO QCD $k$-factor of 1.7 is applied for gluon induced production. Theoretical predictions are indicated as markers with vertical lines denoting PDF, scale and parton shower uncertainties. Markers are staggered for better visibility.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $m_{\mathrm{T},e\mu}$.

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $m_{\mathrm{T},e\mu}$.

Fiducial differential cross-sections as a function of the number of jets. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The results are compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1, with the NNLO + PS predictions from Powheg MiNNLO + Pythia8 and Geneva + Pythia8, as well as Sherpa2.2.12 NLO + PS predictions. The last three predictions are combined with Sherpa 2.2.2 for the $gg$ initial state and Sherpa 2.2.12 for electroweak $WWjj$ production. These contributions are modelled at LO but a NLO QCD $k$-factor of 1.7 is applied for gluon induced production. Theoretical predictions are indicated as markers with vertical lines denoting PDF, scale and parton shower uncertainties. Markers are staggered for better visibility.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable Number of jets ($p_{\mathrm{T}} > $ 30 GeV).

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable Number of jets ($p_{\mathrm{T}} > $ 30 GeV).

Fiducial differential cross-sections as a function of $S_{\mathrm{T}}$. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The right-hand-side axis indicates the integrated cross-section of the rightmost bin. The results are compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1, with the NNLO + PS predictions from Powheg MiNNLO + Pythia8 and Geneva + Pythia8, as well as Sherpa2.2.12 NLO + PS predictions. The last three predictions are combined with Sherpa 2.2.2 for the $gg$ initial state and Sherpa 2.2.12 for electroweak $WWjj$ production. These contributions are modelled at LO but a NLO QCD $k$-factor of 1.7 is applied for gluon induced production. Theoretical predictions are indicated as markers with vertical lines denoting PDF, scale and parton shower uncertainties. Markers are staggered for better visibility.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $S_{\mathrm{T}}$.

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $S_{\mathrm{T}}$.

Fiducial differential cross-sections for $p_{\mathrm{T},e\mu}$ in the region with 85 $<m_{e\mu}<$ 150, for the nNNLO MATRIX prediction and various four flavour PDF sets. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The right-hand-side axis indicates the integrated cross-section of the rightmost bin. The measurement is compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1 using four different four-flavour NNLO PDF sets: NNPDF3.0, NNPDF3.1, CT18, and MSHT20.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $p_{\mathrm{T},e\mu}$ (85 $<m_{e\mu}<$ 150).

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $p_{\mathrm{T},e\mu}$ (85 $<m_{e\mu}<$ 150).

Fiducial differential cross-sections for $|y_{e\mu}|$ in the region with 85 $<m_{e\mu}<$ 150, for the nNNLO MATRIX prediction and various four flavour PDF sets. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The measurement is compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1 using four different four-flavour NNLO PDF sets: NNPDF3.0, NNPDF3.1, CT18, and MSHT20.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $|y_{e\mu}|$ (85 $<m_{e\mu}<$ 150).

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $|y_{e\mu}|$ (85 $<m_{e\mu}<$ 150).

Fiducial differential cross-sections for $p_{\mathrm{T},e\mu}$ in the region with 150 $<m_{e\mu}<$ 250, for the nNNLO MATRIX prediction and various four flavour PDF sets. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The right-hand-side axis indicates the integrated cross-section of the rightmost bin. The measurement is compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1 using four different four-flavour NNLO PDF sets: NNPDF3.0, NNPDF3.1, CT18, and MSHT20.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $p_{\mathrm{T},e\mu}$ (150 $<m_{e\mu}<$ 250).

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $p_{\mathrm{T},e\mu}$ (150 $<m_{e\mu}<$ 250).

Fiducial differential cross-sections for $|y_{e\mu}|$ in the region with 150 $<m_{e\mu}<$ 250, for the nNNLO MATRIX prediction and various four flavour PDF sets. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The measurement is compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1 using four different four-flavour NNLO PDF sets: NNPDF3.0, NNPDF3.1, CT18, and MSHT20.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $|y_{e\mu}|$ (150 $<m_{e\mu}<$ 250).

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $|y_{e\mu}|$ (150 $<m_{e\mu}<$ 250).

Fiducial differential cross-sections for $p_{\mathrm{T},e\mu}$ in the region with $m_{e\mu}>$ 250, for the nNNLO MATRIX prediction and various four flavour PDF sets. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The right-hand-side axis indicates the integrated cross-section of the rightmost bin. The measurement is compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1 using four different four-flavour NNLO PDF sets: NNPDF3.0, NNPDF3.1, CT18, and MSHT20.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $p_{\mathrm{T},e\mu}$ ($m_{e\mu}>$ 250).

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $p_{\mathrm{T},e\mu}$ ($m_{e\mu}>$ 250).

Fiducial differential cross-sections for $|y_{e\mu}|$ in the region with $m_{e\mu}>$ 250, for the nNNLO MATRIX prediction and various four flavour PDF sets. The measured cross-section values are shown as points with error bars giving the statistical uncertainty and solid bands indicating the size of the total uncertainty. The measurement is compared to fixed-order nNNLO QCD + NLO EW predictions of Matrix 2.1 using four different four-flavour NNLO PDF sets: NNPDF3.0, NNPDF3.1, CT18, and MSHT20.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $|y_{e\mu}|$ ($m_{e\mu}>$ 250).

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $|y_{e\mu}|$ ($m_{e\mu}>$ 250).

Measured value of the charge asymmetry, $A_{C}$.

Charge asymmetry $A_C$ measured as a function of the absolute difference of the absolute lepton rapidities $||\eta_{l+}|-|\eta_{l-}||$. The measured values are shown as points, whose error bars represent the statistical uncertainty, while the solid bands indicate the size of the total uncertainty. In the bottom panel, the central value of the charge asymmetry divided by the total uncertainty of the $A_C$ measurement is shown. The measurement is compared with the NNLO+PS predictions from Powheg MiNNLO+Pythia8 with vertical lines denoting PDF uncertainties.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $A_{C}$ vs. $||\eta_{l+}|-|\eta_{l-}||$.

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $A_{C}$ vs. $||\eta_{l+}|-|\eta_{l-}||$.

Charge asymmetry $A_C$ measured as a function of the invariant mass of the dilepton system $m_{e\mu}$. The measured values are shown as points, whose error bars represent the statistical uncertainty, while the solid bands indicate the size of the total uncertainty. In the bottom panel, the central value of the charge asymmetry divided by the total uncertainty of the $A_C$ measurement is shown. The measurement is compared with the NNLO+PS predictions from Powheg MiNNLO+Pythia8 with vertical lines denoting PDF uncertainties.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $A_{C}$ vs. $m_{e\mu}$.

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $A_{C}$ vs. $m_{e\mu}$.

Measured value of the asymmetry in the CP-odd observable $O_{z}$, $A_{CP}$.

The post-fit $p_{\mathrm{T}}^{\text{miss}}$ distribution of the 1 b jet, 0 forward jet, $t\leq 0$ signal region in the single lepton channel. A representative signal model distribution is shown for the scalar mediator interaction with $(m_{\chi},m_{\phi})=(1,100)$GeV and couplings set to unity. The grey dashed area in the upper panel represents the total uncertainty in all of the backgrounds and the chosen signal model, while in the lower panel it represents only the total uncertainty in the backgrounds.

The post-fit $p_{\mathrm{T}}^{\text{miss}}$ distribution of the 1 b jet, 0 forward jet, $t>0$ signal region in the single lepton channel. A representative signal model distribution is shown for the scalar mediator interaction with $(m_{\chi},m_{\phi})=(1,100)$GeV and couplings set to unity. The grey dashed area in the upper panel represents the total uncertainty in all of the backgrounds and the chosen signal model, while in the lower panel it represents only the total uncertainty in the backgrounds.

The post-fit $p_{\mathrm{T}}^{\text{miss}}$ distribution of the 1 b jet, $\geq 1$ forward jet, $t\leq 0$ signal region in the single lepton channel. A representative signal model distribution is shown for the scalar mediator interaction with $(m_{\chi},m_{\phi})=(1,100)$GeV and couplings set to unity. The grey dashed area in the upper panel represents the total uncertainty in all of the backgrounds and the chosen signal model, while in the lower panel it represents only the total uncertainty in the backgrounds.

The post-fit $p_{\mathrm{T}}^{\text{miss}}$ distribution of the 1 b jet, $\geq 1$ forward jet, $t>0$ signal region in the single lepton channel. A representative signal model distribution is shown for the scalar mediator interaction with $(m_{\chi},m_{\phi})=(1,100)$GeV and couplings set to unity. The grey dashed area in the upper panel represents the total uncertainty in all of the backgrounds and the chosen signal model, while in the lower panel it represents only the total uncertainty in the backgrounds.

The post-fit $p_{\mathrm{T}}^{\text{miss}}$ distribution of the $\geq 2$ b jet, $t\leq 0$ signal region in the single lepton channel. A representative signal model distribution is shown for the scalar mediator interaction with $(m_{\chi},m_{\phi})=(1,100)$GeV and couplings set to unity. The grey dashed area in the upper panel represents the total uncertainty in all of the backgrounds and the chosen signal model, while in the lower panel it represents only the total uncertainty in the backgrounds.

The post-fit $p_{\mathrm{T}}^{\text{miss}}$ distribution of the $\geq 2$ b jet, $t>0$ signal region in the single lepton channel. A representative signal model distribution is shown for the scalar mediator interaction with $(m_{\chi},m_{\phi})=(1,100)$GeV and couplings set to unity. The grey dashed area in the upper panel represents the total uncertainty in all of the backgrounds and the chosen signal model, while in the lower panel it represents only the total uncertainty in the backgrounds.

The post-fit NN output score distribution of the $\geq 2$ b jet, different flavor signal region in the dileptonic channel. A representative signal model distribution is shown for the scalar mediator interaction with $(m_{\chi},m_{\phi})=(1,100)$GeV and couplings set to unity. The grey dashed area in the upper panel represents the total uncertainty in all of the backgrounds and the chosen signal model, while in the lower panel it represents only the total uncertainty in the backgrounds.

The post-fit NN output score distribution of the $\geq 2$ b jet, same flavor signal region in the dileptonic channel. A representative signal model distribution is shown for the scalar mediator interaction with $(m_{\chi},m_{\phi})=(1,100)$GeV and couplings set to unity. The grey dashed area in the upper panel represents the total uncertainty in all of the backgrounds and the chosen signal model, while in the lower panel it represents only the total uncertainty in the backgrounds.

The post-fit NN output score distribution of the 1 b jet, different flavor signal region in the dileptonic channel. A representative signal model distribution is shown for the scalar mediator interaction with $(m_{\chi},m_{\phi})=(1,100)$GeV and couplings set to unity. The grey dashed area in the upper panel represents the total uncertainty in all of the backgrounds and the chosen signal model, while in the lower panel it represents only the total uncertainty in the backgrounds.

The post-fit NN output score distribution of the 1 b jet, same flavor signal region in the dileptonic channel. A representative signal model distribution is shown for the scalar mediator interaction with $(m_{\chi},m_{\phi})=(1,100)$GeV and couplings set to unity. The grey dashed area in the upper panel represents the total uncertainty in all of the backgrounds and the chosen signal model, while in the lower panel it represents only the total uncertainty in the backgrounds.

The model-independent 95\% CL limits on production cross section for new physics processes for the scalar interaction. The expected limit is shown by the black dashed line with the 68 and 95\% CL uncertainty bands in green and yellow, respectively, while the observed limit is shown by the solid black line. Theoretical LO cross section values for the DM model and their associated uncertainties are also presented (grey line).

The model-independent 95\% CL limits on production cross section for new physics processes for the pseudoscalar interaction. The expected limit is shown by the black dashed line with the 68 and 95\% CL uncertainty bands in green and yellow, respectively, while the observed limit is shown by the solid black line. Theoretical LO cross section values for the DM model and their associated uncertainties are also presented (grey line).

The post-fit $p_{\mathrm{T}}^{\text{miss}}$ distribution of the QCD control region in the all hadronic channel. The grey dashed area in the upper and lower panels represents the total uncertainty in all of the backgrounds.

The post-fit $p_{\mathrm{T}}^{\text{miss}}$ distribution of the tt(1l) control region in the all hadronic channel. The grey dashed area in the upper and lower panels represents the total uncertainty in all of the backgrounds.

The post-fit $p_{\mathrm{T}}^{\text{miss}}$ distribution of the W+jets control region in the all hadronic channel. The grey dashed area in the upper and lower panels represents the total uncertainty in all of the backgrounds.

The post-fit $p_{\mathrm{T}}^{\text{miss}}$ distribution of the Z(2l) control region in the all hadronic channel. The grey dashed area in the upper and lower panels represents the total uncertainty in all of the backgrounds.

The post-fit $p_{\mathrm{T}}^{\text{miss}}$ distribution of the W+jets control region in the single lepton channel. The grey dashed area in the upper and lower panels represents the total uncertainty in all of the backgrounds.

The post-fit $p_{\mathrm{T}}^{\text{miss}}$ distribution of the tt(2l) control region in the single lepton channel. The grey dashed area in the upper and lower panels represents the total uncertainty in all of the backgrounds.

The post-fit $(N_{\text{jet}},N_{\text{bjet}})$ distribution of the ttZ control region in the dileptonic channel. The grey dashed area in the upper and lower panels represents the total uncertainty in all of the backgrounds.

The post-fit NN distribution of the Drell-Yan control region in the dileptonic channel. The grey dashed area in the upper and lower panels represents the total uncertainty in all of the backgrounds.

Predicted signal yields for the 2016, 2017, and 2018 data-taking periods, corresponding to $36.3\,\text{fb}^{-1}$, $41.5\,\text{fb}^{-1}$, and $59.7\,\text{fb}^{-1}$, respectively, after the application of each search requirement for the t+DM $(m_{\chi},m_{\phi}) = (1,50)$ GeV scalar mediator signal hypothesis for the all hadronic channel. The requirements listed up to and including the $M_{T}^{b}$ cut are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. The last three requirements show the separate yields after the cumulative requirements up to the $M_{T}^{b}$ cut.

Predicted signal yields for the 2016, 2017, and 2018 data-taking period, corresponding to $36.3\,\text{fb}^{-1}$, $41.5\,\text{fb}^{-1}$, and $59.7\,\text{fb}^{-1}$, respectively, after the application of each search requirement for the t+DM $(m_{\chi},m_{\phi}) = (1,500)$ GeV scalar mediator signal hypothesis for the all hadronic channel. The requirements listed up to and including the $M_{T}^{b}$ cut are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. The last three requirements show the separate yields after the cumulative requirements up to the $M_{T}^{b}$ cut.

Predicted signal yields for the 2016, 2017, and 2018 data-taking period, corresponding to $36.3\,\text{fb}^{-1}$, $41.5\,\text{fb}^{-1}$, and $59.7\,\text{fb}^{-1}$, respectively, after the application of each search requirement for the t+DM $(m_{\chi},m_{a}) = (1,50)$ GeV pseudoscalar mediator signal hypothesis for the all hadronic channel. The requirements listed up to and including the $M_{T}^{b}$ cut are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. The last three requirements show the separate yields after the cumulative requirements up to the $M_{T}^{b}$ cut.

Predicted signal yields for the 2016, 2017, and 2018 data-taking period, corresponding to $36.3\,\text{fb}^{-1}$, $41.5\,\text{fb}^{-1}$, and $59.7\,\text{fb}^{-1}$, respectively, after the application of each search requirement for the t+DM $(m_{\chi},m_{a}) = (1,500)$ GeV pseudoscalar mediator signal hypothesis for the all hadronic channel. The requirements listed up to and including the $M_{T}^{b}$ cut are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. The last three requirements show the separate yields after the cumulative requirements up to the $M_{T}^{b}$ cut.

Predicted signal yields for the 2016, 2017, and 2018 data-taking period, corresponding to $36.3\,\text{fb}^{-1}$, $41.5\,\text{fb}^{-1}$, and $59.7\,\text{fb}^{-1}$, respectively, after the application of each search requirement for the tt+DM $(m_{\chi},m_{\phi}) = (1,50)$ GeV scalar mediator signal hypothesis for the all hadronic channel. The requirements listed up to and including the $M_{T}^{b}$ cut are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. The last three requirements show the separate yields after the cumulative requirements up to the $M_{T}^{b}$ cut.

Predicted signal yields for the 2016, 2017, and 2018 data-taking period, corresponding to $36.3\,\text{fb}^{-1}$, $41.5\,\text{fb}^{-1}$, and $59.7\,\text{fb}^{-1}$, respectively, after the application of each search requirement for the tt+DM $(m_{\chi},m_{\phi}) = (1,500)$ GeV scalar mediator signal hypothesis for the all hadronic channel. The requirements listed up to and including the $M_{T}^{b}$ cut are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. The last three requirements show the separate yields after the cumulative requirements up to the $M_{T}^{b}$ cut.

Predicted signal yields for the 2016, 2017, and 2018 data-taking period, corresponding to $36.3\,\text{fb}^{-1}$, $41.5\,\text{fb}^{-1}$, and $59.7\,\text{fb}^{-1}$, respectively, after the application of each search requirement for the tt+DM $(m_{\chi},m_{a}) = (1,50)$ GeV pseudoscalar mediator signal hypothesis for the all hadronic channel. The requirements listed up to and including the $M_{T}^{b}$ cut are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. The last three requirements show the separate yields after the cumulative requirements up to the $M_{T}^{b}$ cut.

Predicted signal yields for the 2016, 2017, and 2018 data-taking period, corresponding to $36.3\,\text{fb}^{-1}$, $41.5\,\text{fb}^{-1}$, and $59.7\,\text{fb}^{-1}$, respectively, after the application of each search requirement for the tt+DM $(m_{\chi},m_{a}) = (1,500)$ GeV pseudoscalar mediator signal hypothesis for the all hadronic channel. The requirements listed up to and including the $M_{T}^{b}$ cut are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. The last three requirements show the separate yields after the cumulative requirements up to the $M_{T}^{b}$ cut.

Predicted signal yields for the 2016, 2017, and 2018 data-taking period, corresponding to $36.3\,\text{fb}^{-1}$, $41.5\,\text{fb}^{-1}$, and $59.7\,\text{fb}^{-1}$, respectively, after the application of each search requirement for the t+DM $(m_{\chi},m_{\phi}) = (1,50)$ GeV scalar mediator signal hypothesis for the single lepton channel. The requirements listed up to and including the $M_{T2}^{W}$ cut are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. The last six requirements show the separate yields after the cumulative requirements up to the $M_{T2}^{W}$ cut.

Predicted signal yields for the 2016, 2017, and 2018 data-taking period, corresponding to $36.3\,\text{fb}^{-1}$, $41.5\,\text{fb}^{-1}$, and $59.7\,\text{fb}^{-1}$, respectively, after the application of each search requirement for the t+DM $(m_{\chi},m_{\phi}) = (1,500)$ GeV scalar mediator signal hypothesis for the single lepton channel. The requirements listed up to and including the $M_{T2}^{W}$ cut are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. The last six requirements show the separate yields after the cumulative requirements up to the $M_{T2}^{W}$ cut.

Predicted signal yields for the 2016, 2017, and 2018 data-taking period, corresponding to $36.3\,\text{fb}^{-1}$, $41.5\,\text{fb}^{-1}$, and $59.7\,\text{fb}^{-1}$, respectively, after the application of each search requirement for the t+DM $(m_{\chi},m_{a}) = (1,50)$ GeV pseudoscalar mediator signal hypothesis for the single lepton channel. The requirements listed up to and including the $M_{T2}^{W}$ cut are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. The last six requirements show the separate yields after the cumulative requirements up to the $M_{T2}^{W}$ cut.

Predicted signal yields for the 2016, 2017, and 2018 data-taking period, corresponding to $36.3\,\text{fb}^{-1}$, $41.5\,\text{fb}^{-1}$, and $59.7\,\text{fb}^{-1}$, respectively, after the application of each search requirement for the t+DM $(m_{\chi},m_{a}) = (1,500)$ GeV pseudoscalar mediator signal hypothesis for the single lepton channel. The requirements listed up to and including the $M_{T2}^{W}$ cut are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. The last six requirements show the separate yields after the cumulative requirements up to the $M_{T2}^{W}$ cut.

Predicted signal yields for the 2016, 2017, and 2018 data-taking period, corresponding to $36.3\,\text{fb}^{-1}$, $41.5\,\text{fb}^{-1}$, and $59.7\,\text{fb}^{-1}$, respectively, after the application of each search requirement for the tt+DM $(m_{\chi},m_{\phi}) = (1,50)$ GeV scalar mediator signal hypothesis for the single lepton channel. The requirements listed up to and including the $M_{T2}^{W}$ cut are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. The last six requirements show the separate yields after the cumulative requirements up to the $M_{T2}^{W}$ cut.

Predicted signal yields for the 2016, 2017, and 2018 data-taking period, corresponding to $36.3\,\text{fb}^{-1}$, $41.5\,\text{fb}^{-1}$, and $59.7\,\text{fb}^{-1}$, respectively, after the application of each search requirement for the tt+DM $(m_{\chi},m_{\phi}) = (1,500)$ GeV scalar mediator signal hypothesis for the single lepton channel. The requirements listed up to and including the $M_{T2}^{W}$ cut are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. The last six requirements show the separate yields after the cumulative requirements up to the $M_{T2}^{W}$ cut.

Predicted signal yields for the 2016, 2017, and 2018 data-taking period, corresponding to $36.3\,\text{fb}^{-1}$, $41.5\,\text{fb}^{-1}$, and $59.7\,\text{fb}^{-1}$, respectively, after the application of each search requirement for the tt+DM $(m_{\chi},m_{a}) = (1,50)$ GeV pseudoscalar mediator signal hypothesis for the single lepton channel. The requirements listed up to and including the $M_{T2}^{W}$ cut are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. The last six requirements show the separate yields after the cumulative requirements up to the $M_{T2}^{W}$ cut.

Predicted signal yields for the 2016, 2017, and 2018 data-taking period, corresponding to $36.3\,\text{fb}^{-1}$, $41.5\,\text{fb}^{-1}$, and $59.7\,\text{fb}^{-1}$, respectively, after the application of each search requirement for the tt+DM $(m_{\chi},m_{a}) = (1,500)$ GeV pseudoscalar mediator signal hypothesis for the single lepton channel. The requirements listed up to and including the $M_{T2}^{W}$ cut are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. The last six requirements show the separate yields after the cumulative requirements up to the $M_{T2}^{W}$ cut.

Predicted signal yields for the 2016, 2017, and 2018 data-taking period, corresponding to $36.3\,\text{fb}^{-1}$, $41.5\,\text{fb}^{-1}$, and $59.7\,\text{fb}^{-1}$, respectively, after the application of each search requirement for the t+DM $(m_{\chi},m_{\phi}) = (1,50)$ GeV scalar mediator signal hypothesis for the dileptonic channel. The requirements listed up to and including the Z window cut are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. The last four requirements show the separate yields after the cumulative requirements up to the Z window cut.

Predicted signal yields for the 2016, 2017, and 2018 data-taking period, corresponding to $36.3\,\text{fb}^{-1}$, $41.5\,\text{fb}^{-1}$, and $59.7\,\text{fb}^{-1}$, respectively, after the application of each search requirement for the t+DM $(m_{\chi},m_{\phi}) = (1,500)$ GeV scalar mediator signal hypothesis for the dileptonic channel. The requirements listed up to and including the Z window cut are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. The last four requirements show the separate yields after the cumulative requirements up to the Z window cut.

Predicted signal yields for the 2016, 2017, and 2018 data-taking period, corresponding to $36.3\,\text{fb}^{-1}$, $41.5\,\text{fb}^{-1}$, and $59.7\,\text{fb}^{-1}$, respectively, after the application of each search requirement for the t+DM $(m_{\chi},m_{a}) = (1,50)$ GeV pseudoscalar mediator signal hypothesis for the dileptonic channel. The requirements listed up to and including the Z window cut are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. The last four requirements show the separate yields after the cumulative requirements up to the Z window cut.

Predicted signal yields for the 2016, 2017, and 2018 data-taking period, corresponding to $36.3\,\text{fb}^{-1}$, $41.5\,\text{fb}^{-1}$, and $59.7\,\text{fb}^{-1}$, respectively, after the application of each search requirement for the t+DM $(m_{\chi},m_{a}) = (1,500)$ GeV pseudoscalar mediator signal hypothesis for the dileptonic channel. The requirements listed up to and including the Z window cut are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. The last four requirements show the separate yields after the cumulative requirements up to the Z window cut.

Predicted signal yields for the 2016, 2017, and 2018 data-taking period, corresponding to $36.3\,\text{fb}^{-1}$, $41.5\,\text{fb}^{-1}$, and $59.7\,\text{fb}^{-1}$, respectively, after the application of each search requirement for the tt+DM $(m_{\chi},m_{\phi}) = (1,50)$ GeV scalar mediator signal hypothesis for the dileptonic channel. The requirements listed up to and including the Z window cut are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. The last four requirements show the separate yields after the cumulative requirements up to the Z window cut.

Predicted signal yields for the 2016, 2017, and 2018 data-taking period, corresponding to $36.3\,\text{fb}^{-1}$, $41.5\,\text{fb}^{-1}$, and $59.7\,\text{fb}^{-1}$, respectively, after the application of each search requirement for the tt+DM $(m_{\chi},m_{\phi}) = (1,500)$ GeV scalar mediator signal hypothesis for the dileptonic channel. The requirements listed up to and including the Z window cut are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. The last four requirements show the separate yields after the cumulative requirements up to the Z window cut.

Predicted signal yields for the 2016, 2017, and 2018 data-taking period, corresponding to $36.3\,\text{fb}^{-1}$, $41.5\,\text{fb}^{-1}$, and $59.7\,\text{fb}^{-1}$, respectively, after the application of each search requirement for the tt+DM $(m_{\chi},m_{a}) = (1,50)$ GeV pseudoscalar mediator signal hypothesis for the dileptonic channel. The requirements listed up to and including the Z window cut are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. The last four requirements show the separate yields after the cumulative requirements up to the Z window cut.

Predicted signal yields for the 2016, 2017, and 2018 data-taking period, corresponding to $36.3\,\text{fb}^{-1}$, $41.5\,\text{fb}^{-1}$, and $59.7\,\text{fb}^{-1}$, respectively, $41.5\,\text{fb}^{-1}$, and $59.7\,\text{fb}^{-1}$, respectively, after the application of each search requirement for the tt+DM $(m_{\chi},m_{a}) = (1,500)$ GeV pseudoscalar mediator signal hypothesis for the dileptonic channel. The requirements listed up to and including the Z window cut are cumulative such that only the events and objects passing a given requirement are considered in subsequent requirements. The last four requirements show the separate yields after the cumulative requirements up to the Z window cut.

Cross sections calculated to leading order (LO) accuracy for the tt+DM scalar mediator signal process considering all possible decays from the visible particles in the final state.

Cross sections calculated to leading order (LO) accuracy for the tt+DM pseudoscalar mediator signal process considering all possible decays from the visible particles in the final state.

Cross sections calculated to leading order (LO) accuracy for the tt+DM scalar mediator signal process considering dileptonic decays from the visible particles in the final state.

Cross sections calculated to leading order (LO) accuracy for the tt+DM pseudoscalar mediator signal process considering dileptonic decays from the visible particles in the final state.

Cross sections calculated to leading order (LO) accuracy for the t+DM t-channel scalar mediator signal process considering all possible decays from the visible particles in the final state.

Cross sections calculated to leading order (LO) accuracy for the t+DM tW-channel scalar mediator signal process considering all possible decays from the visible particles in the final state.

Cross sections calculated to leading order (LO) accuracy for the t+DM t-channel pseudoscalar mediator signal process considering all possible decays from the visible particles in the final state.

Cross sections calculated to leading order (LO) accuracy for the t+DM tW-channel pseudoscalar mediator signal process considering all possible decays from the visible particles in the final state.

Cross sections calculated to leading order (LO) accuracy for the t+DM tW-channel scalar mediator signal process considering dileptonic decays from the visible particles in the final state.

Cross sections calculated to leading order (LO) accuracy for the t+DM tW-channel pseudoscalar mediator signal process considering dileptonic decays from the visible particles in the final state.

The 95% CL limits on the cross-section $\sigma(pp \rightarrow Z' \rightarrow \chi \chi$) times branching ratio B in fb with all statistical and systematic uncertainties, for the $R_{\text{inv}}=$0.6 signal points.

Data yield in the PFN signal region.

Yield of data in the ANTELOPE signal region in the binning used for BumpHunter fitting.

Observed profile likelihood as a function of $\sigma\times\mathcal{B}_{H\rightarrow WW^{*}}$ normalised by the SM expectation for the single-channel measurements

Two-dimensional likelihood scan of the measured values of $\sigma_{ZH}\times\mathcal{B}_{H\rightarrow WW^{*}}$ vs. $\sigma_{WH}\times\mathcal{B}_{H\rightarrow WW^{*}}$.

The observed values of the background normalisation factors for the combined 2-POI fit. The uncertainties correspond to the total of all statistical and systematic sources.

Measured cross sections times the $H\rightarrow WW^{*}$ branching ratio for the $p_T^V$ scheme.

Measured cross sections times the $H\rightarrow WW^{*}$ branching ratio for the STXS scheme. Note: the uncertainties of "-0" are due to the confidence interval reaching the minimum allowed value of the POI.

Correlation matrix of the POIs and normalisation factors for the 2-POI inclusive analysis

Correlation matrix of the parameters of interest, normalisation factors and nuissance parameters for the $p_T^V$ scheme

Correlation matrix of the parameters of interest, normalisation factors and nuissance parameters for the STXS scheme

Event data from Z-dominated SR

The combined covariance matrix for the differential cross-section distribution.

Statistical covariance matrix for the differential cross-section distribution.

Statistical covariance matrix for the differential cross-section distribution.

Systematic covariance matrix for the differential cross-section distribution.

Systematic covariance matrix for the differential cross-section distribution.

Distribution of $E_{\text{T}}^{\text{miss}}$ in SROS-on-b-$e\mu\mu$. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by a black arrow. The last bin includes the overflow. The `Others' category contains the production of Higgs boson, 3-top, 4-top, and single-top processes. Distributions for SBH signals are overlaid. The bottom panels show the ratio of the observed data to the predicted total background yields. The hatched band includes all statistical and systematic uncertainties.

Distribution of $m_{\text{T}}^{\text{min}}$ in SROS-on-b-$e\mu\mu$. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by a black arrow. The last bin includes the overflow. The `Others' category contains the production of Higgs boson, 3-top, 4-top, and single-top processes. Distributions for SBH signals are overlaid. The bottom panels show the ratio of the observed data to the predicted total background yields. The hatched band includes all statistical and systematic uncertainties.

Distribution of $E_{\text{T}}^{\text{miss}}$ in SRSS-$2\mu$. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by a black arrow. The last bin includes the overflow. The `Others' category contains the production of Higgs boson, 3-top, 4-top, and single-top processes. Distributions for SBH signals are overlaid. The bottom panels show the ratio of the observed data to the predicted total background yields. The hatched band includes all statistical and systematic uncertainties.

Observed ($N_{\text{obs}}$) and expected ($N_{\text{exp}}$) yields after the background-only fit for the flavor-merged inclusive SRs. The third and fourth columns list the 95\% CL upper limits on the visible cross-section ($\sigma_{\text{vis}}^{95}$) and on the number of signal events ($S_\text{obs}^{95}$). The fifth column ($S_\text{exp}^{95}$) shows the 95\% CL upper limit on the number of signal events, given the expected number of background events and its $\pm 1\sigma$ variations. The last two columns indicate the CL$_{\text{b}}$ value, i.e. the confidence level observed for the background-only hypothesis, and the discovery $p$-value ($p(s = 0)$) with its associated statistical significance $Z$. If the observed yield is below the expected yield, the $p$-value is capped at 0.5.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ are considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ are considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ are considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ are considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ are considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ are considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where only $\tilde{e}_{\text{L}}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where only $\tilde{e}_{\text{L}}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where only $\tilde{e}_{\text{L}}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where only $\tilde{e}_{\text{L}}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where only $\tilde{e}_{\text{L}}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where only $\tilde{e}_{\text{L}}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where only $\tilde{\mu}_{\text{L}}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where only $\tilde{\mu}_{\text{L}}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where only $\tilde{\mu}_{\text{L}}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where only $\tilde{\mu}_{\text{L}}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where only $\tilde{\mu}_{\text{L}}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Observed and expected exclusion limits on the SBH model where only $\tilde{\mu}_{\text{L}}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100~GeV.

Distribution of $E_{\text{T}}^{\text{miss}}$ in SROS-off-b-$e\mu\mu$. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by a black arrow. The last bin includes the overflow. The `Others' category contains the production of Higgs boson, 3-top, 4-top, and single-top processes. Distributions for SBH signals are overlaid. The bottom panels show the ratio of the observed data to the predicted total background yields. Ratio values outside the graph range are indicated by brown arrows. The hatched band includes all statistical and systematic uncertainties.

Distribution of $m_{\text{T}}^{\text{min}}$ in SROS-off-b-$e\mu\mu$. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by a black arrow. The last bin includes the overflow. The `Others' category contains the production of Higgs boson, 3-top, 4-top, and single-top processes. Distributions for SBH signals are overlaid. The bottom panels show the ratio of the observed data to the predicted total background yields. Ratio values outside the graph range are indicated by brown arrows. The hatched band includes all statistical and systematic uncertainties.

Distribution of $E_{\text{T}}^{\text{miss}}$ in SRSS-$eee$. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by a black arrow. The last bin includes the overflow. The `Others' category contains the production of Higgs boson, 3-top, 4-top, and single-top processes. Distributions for SBH signals are overlaid. The bottom panels show the ratio of the observed data to the predicted total background yields. Ratio values outside the graph range are indicated by brown arrows. The hatched band includes all statistical and systematic uncertainties.

Distribution of $E_{\text{T}}^{\text{miss}}$ in SRSS-$ee\mu$. The SR selections are applied for each distribution, except for the variable shown, for which the selection is indicated by a black arrow. The last bin includes the overflow. The `Others' category contains the production of Higgs boson, 3-top, 4-top, and single-top processes. Distributions for SBH signals are overlaid. The bottom panels show the ratio of the observed data to the predicted total background yields. Ratio values outside the graph range are indicated by brown arrows. The hatched band includes all statistical and systematic uncertainties.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 150 GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 150 GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 150 GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 150 GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 150 GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ is considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $m(\tilde{\ell}_{\text{L}}^{\pm})$ vs $m(\tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 150 GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ are considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $\Delta m(\tilde{\chi}^0_3, \tilde{\chi}^0_1)$ vs $\Delta m(\tilde{\ell}_{\text{L}}, \tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100 GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ are considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $\Delta m(\tilde{\chi}^0_3, \tilde{\chi}^0_1)$ vs $\Delta m(\tilde{\ell}_{\text{L}}, \tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100 GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ are considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $\Delta m(\tilde{\chi}^0_3, \tilde{\chi}^0_1)$ vs $\Delta m(\tilde{\ell}_{\text{L}}, \tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100 GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ are considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $\Delta m(\tilde{\chi}^0_3, \tilde{\chi}^0_1)$ vs $\Delta m(\tilde{\ell}_{\text{L}}, \tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100 GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ are considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $\Delta m(\tilde{\chi}^0_3, \tilde{\chi}^0_1)$ vs $\Delta m(\tilde{\ell}_{\text{L}}, \tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100 GeV.

Observed and expected exclusion limits on the SBH model where mass-degenerate $\tilde{e}_{\text{L}}$, $\tilde{\mu}_{\text{L}}$ and $\tilde{\nu}$ are considered. The expected 95% CL exclusion limit is shown as a dashed black line, with the yellow band indicating $\pm1\sigma_{\text{exp}}$ including all uncertainties except for the signal cross-section uncertainty. The observed 95% CL exclusion limit is shown as a red solid line, with the dotted red lines indicating $\pm1\sigma_{\text{theory}}$ due to the signal cross-section uncertainty. The limits are shown projected onto the $\Delta m(\tilde{\chi}^0_3, \tilde{\chi}^0_1)$ vs $\Delta m(\tilde{\ell}_{\text{L}}, \tilde{\chi}^0_3)$ plane, with $m(\tilde{\chi}^0_1)$ assumed to be 100 GeV.

The expected upper limits on the cross-section for each signal point. The gray numbers represent the values. The expected (dashed) and observed (solid) 95% CL exclusion limits are overlaid. An asymptotic approximation is employed in the CL$_{\text{s}}$ calculation instead of the full calculation using pseudo-experiments.

The observed upper limits on the cross-section for each signal point. The gray numbers represent the values. The expected (dashed) and observed (solid) 95% CL exclusion limits are overlaid. An asymptotic approximation is employed in the CL$_{\text{s}}$ calculation instead of the full calculation using pseudo-experiments.

Acceptance for signals with $m(\tilde{\chi}^0_1)=100$ GeV in flavored-merged SRs. The acceptance is given by the ratio of weighted selected events in the SR to the weighted total number of generated events. The selection is based on generator-level particle information.

Acceptance for signals with $m(\tilde{\chi}^0_1)=100$ GeV in flavored-merged SRs. The acceptance is given by the ratio of weighted selected events in the SR to the weighted total number of generated events. The selection is based on generator-level particle information.

Acceptance for signals with $m(\tilde{\chi}^0_1)=100$ GeV in flavored-merged SRs. The acceptance is given by the ratio of weighted selected events in the SR to the weighted total number of generated events. The selection is based on generator-level particle information.

Acceptance for signals with $m(\tilde{\chi}^0_1)=100$ GeV in flavored-merged SRs. The acceptance is given by the ratio of weighted selected events in the SR to the weighted total number of generated events. The selection is based on generator-level particle information.

Acceptance for signals with $m(\tilde{\chi}^0_1)=100$ GeV in flavored-merged SRs. The acceptance is given by the ratio of weighted selected events in the SR to the weighted total number of generated events. The selection is based on generator-level particle information.

Acceptance for signals with $m(\tilde{\chi}^0_1)=100$ GeV in flavored-merged SRs. The acceptance is given by the ratio of weighted selected events in the SR to the weighted total number of generated events. The selection is based on generator-level particle information.

Acceptance for signals with $m(\tilde{\chi}^0_1)=100$ GeV in flavored-merged SRs. The acceptance is given by the ratio of weighted selected events in the SR to the weighted total number of generated events. The selection is based on generator-level particle information.

Efficiencies for signals with $m(\tilde{\chi}^0_1)=100$ GeV in the $m_{3\ell}$ merged SRSFOS and SRSS. The efficiency is defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level. Efficiencies below 0.002% are rounded to 0. The efficiency values are affected by statistical fluctuations due to the limited number of events.

Efficiencies for signals with $m(\tilde{\chi}^0_1)=100$ GeV in the $m_{3\ell}$ merged SRSFOS and SRSS. The efficiency is defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level. Efficiencies below 0.002% are rounded to 0. The efficiency values are affected by statistical fluctuations due to the limited number of events.

Efficiencies for signals with $m(\tilde{\chi}^0_1)=100$ GeV in the $m_{3\ell}$ merged SRSFOS and SRSS. The efficiency is defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level. Efficiencies below 0.002% are rounded to 0. The efficiency values are affected by statistical fluctuations due to the limited number of events.

Efficiencies for signals with $m(\tilde{\chi}^0_1)=100$ GeV in the $m_{3\ell}$ merged SRSFOS and SRSS. The efficiency is defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level. Efficiencies below 0.002% are rounded to 0. The efficiency values are affected by statistical fluctuations due to the limited number of events.

Efficiencies for signals with $m(\tilde{\chi}^0_1)=100$ GeV in the $m_{3\ell}$ merged SRSFOS and SRSS. The efficiency is defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level. Efficiencies below 0.002% are rounded to 0. The efficiency values are affected by statistical fluctuations due to the limited number of events.

Efficiencies for signals with $m(\tilde{\chi}^0_1)=100$ GeV in the $m_{3\ell}$ merged SRSFOS and SRSS. The efficiency is defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level. Efficiencies below 0.002% are rounded to 0. The efficiency values are affected by statistical fluctuations due to the limited number of events.

Efficiencies for signals with $m(\tilde{\chi}^0_1)=100$ GeV in the $m_{3\ell}$ merged SRSFOS and SRSS. The efficiency is defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level. Efficiencies below 0.002% are rounded to 0. The efficiency values are affected by statistical fluctuations due to the limited number of events.

Efficiencies for signals with $m(\tilde{\chi}^0_1)=100$ GeV in the $m_{3\ell}$ merged SRSFOS and SRSS. The efficiency is defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level. Efficiencies below 0.002% are rounded to 0. The efficiency values are affected by statistical fluctuations due to the limited number of events.

Efficiencies for signals with $m(\tilde{\chi}^0_1)=100$ GeV in the $m_{3\ell}$ merged SRSFOS and SRSS. The efficiency is defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level. Efficiencies below 0.002% are rounded to 0. The efficiency values are affected by statistical fluctuations due to the limited number of events.

Efficiencies for signals with $m(\tilde{\chi}^0_1)=100$ GeV in the $m_{3\ell}$ merged SRSFOS and SRSS. The efficiency is defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level. Efficiencies below 0.002% are rounded to 0. The efficiency values are affected by statistical fluctuations due to the limited number of events.

Efficiencies for signals with $m(\tilde{\chi}^0_1)=100$ GeV in the $m_{3\ell}$ merged SRSFOS and SRSS. The efficiency is defined by the number of events of reconstructed-level signal simulation divided by the number of events obtained at generator level. Efficiencies below 0.002% are rounded to 0. The efficiency values are affected by statistical fluctuations due to the limited number of events.

Summary of the number of events passing each selection for the $m(\tilde{\ell}_{\text{L}}^{\pm},\tilde{\chi}^0_3,\tilde{\chi}^0_1)=(300, 200, 100)$, $(550, 300, 100)$, $(450, 180, 100)$ GeV signal points, including all production processes. After the initial selections, the table is split into row blocks per inclusive region, and then further for each SR channel. Flavor-binned SRs are shown for SROS-on-b for reference. The generator level selections require to have two or more leptons.

Summary of the number of events passing each selection for the $m(\tilde{\ell}_{\text{L}}^{\pm},\tilde{\chi}^0_3,\tilde{\chi}^0_1)=(300, 200, 100)$, $(550, 300, 100)$, $(450, 180, 100)$ GeV signal points, including all production processes. After the initial selections, the table is split into row blocks per inclusive region, and then further for each SR channel. Flavor-binned SRs are shown for SROS-off-b for reference. The generator level selections require to have two or more leptons.

Summary of the number of events passing each selection for the $m(\tilde{\ell}_{\text{L}}^{\pm},\tilde{\chi}^0_3,\tilde{\chi}^0_1)=(300, 200, 100)$, $(550, 300, 100)$, $(450, 180, 100)$ GeV signal points, including all production processes. After the initial selections, the table is split into row blocks per inclusive region, and then further for each SR channel. Flavor-binned SRs are shown. The generator level selections require to have two or more leptons.