$\sigma(\mathrm{pp}\to\mathrm{Z+Y(1S)})\mathcal{B}(\mathrm{Z}\to\mu\mu)\mathcal{B}(\mathrm{Y(1S)}\to\mu\mu) / \sigma(\mathrm{pp}\to\mathrm{Z})\mathcal{B}(\mathrm{Z}\to\mu\mu\mu\mu)$

$\sigma(\mathrm{pp}\to\mathrm{Z+Y(1S)})\mathcal{B}(\mathrm{Z}\to\mu\mu)\mathcal{B}(\mathrm{Y(1S)}\to\mu\mu) / \sigma(\mathrm{pp}\to\mathrm{Z})\mathcal{B}(\mathrm{Z}\to\mu\mu\mu\mu)$

$\sigma(\mathrm{pp}\to\mathrm{Z+Y(1S)})\mathcal{B}(\mathrm{Z}\to\mu\mu)\mathcal{B}(\mathrm{Y(1S)}\to\mu\mu) / \sigma(\mathrm{pp}\to\mathrm{Z})\mathcal{B}(\mathrm{Z}\to\mu\mu\mu\mu)$

inclusive DPS effective cross section

differential DPS effective cross section vs Y(1S) $p_\mathrm{T}$

differential DPS effective cross section vs Z $p_\mathrm{T}$

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.

Measured and predicted cross sections (fb) in bins of photon transverse momentum $p_{T}^{\gamma}$. The fiducial phase space definition follows the analysis selection in the paper.

Expected and observed 95% CL intervals for anomalous coupling parameters. All other anomalous coupling parameters are fixed to zero when extracting each interval.

Expected and observed 95% CL upper limits on the V' boson production cross section as functions of the resonance mass mV' in the HVT model A.

Expected and observed 95% CL upper limits on the V' boson production cross section as functions of the resonance mass mV' in the HVT model B.

Expected and observed 95% CL upper limits on the V' boson production cross section as functions of the resonance mass mV' in the HVT model C.

Expected and observed 95% CL exclusion contour in gF-gH parameter space for the DIQ channel at 3 TeV. Here, model A corresponds to (0.556, 0.562) and model B to (-2.928, 0.146)

Expected and observed 95% CL exclusion contour in gF-gH parameter space for the DIQ channel at 4 TeV.

Expected and observed 95% CL exclusion contour in gF-gH parameter space for the DIL channel at 3 TeV.

Expected and observed 95% CL exclusion contour in gF-gH parameter space for the DIL channel at 4 TeV.

Expected and observed 95% CL exclusion contour in gH-gF parameter space for the DIB channel at 3 TeV.

Expected and observed 95% CL exclusion contour in gH-gF parameter space for the DIB channel at 4 TeV.

Expected and observed 95% CL exclusion contour in gF-gH parameter space for the Full Combined channel at 3 TeV.

Expected and observed 95% CL exclusion contour in gF-gH parameter space for the Full Combined channel at 4 TeV.

Expected and observed 95% CL exclusion contour in g_q12-g_q3 parameter space at m_V' = 3 TeV. Uncertainty bands shown as separate contour lines. Channels not in combination are shown separately.

Expected and observed 95% CL exclusion contour in g_q12-g_q3 parameter space at m_V' = 4 TeV. Uncertainty bands shown as separate contour lines. Channels not in combination are shown separately.

Expected and observed 95% CL upper limits on the W' production cross section in the HVT Model A benchmark, compared with the theoretical prediction.

Expected and observed 95% CL upper limits on the W' production cross section in the HVT Model B benchmark, compared with the theoretical prediction.

Expected and observed 95% CL upper limits on the W' production cross section in the HVT Model C benchmark, compared with the theoretical prediction.

Expected and observed 95% CL upper limits on the Z' production cross section in the HVT Model A benchmark, compared with the theoretical prediction.

Expected and observed 95% CL upper limits on the Z' production cross section in the HVT Model B benchmark, compared with the theoretical prediction.

Expected and observed 95% CL upper limits on the Z' production cross section in the HVT Model C benchmark, compared with the theoretical prediction.

Normalized differential cross sections, compared with the SM predictions, as a function of the absolute value of pseudorapidity of the subleading jet in transverse momentum. The SM predictions are obtained using Madgraph5_aMC@NLO version 2.6.5 at NLO in QCD with PYTHIA version 8.240

Normalized differential cross sections, compared with the SM predictions, as a function of the invariant mass of the two jets. The SM predictions are obtained using Madgraph5_aMC@NLO version 2.6.5 at NLO in QCD with PYTHIA version 8.240

Normalized differential cross sections, compared with the SM predictions, as a function of the photon's transverse momentum. The SM predictions are obtained using Madgraph5_aMC@NLO version 2.6.5 at NLO in QCD with PYTHIA version 8.240

Normalized differential cross sections, compared with the SM predictions, as a function of the event centrality as defined in Ref.[13] of the paper. The SM predictions are obtained using Madgraph5_aMC@NLO version 2.6.5 at NLO in QCD with PYTHIA version 8.240

Normalized differential cross sections, compared with the SM predictions, as a function of the Zeppenfeld variable that is defined in Eq.(1) of the paper. The SM predictions are obtained using Madgraph5_aMC@NLO version 2.6.5 at NLO in QCD with PYTHIA version 8.240

Negative of twice in the difference in the log-likelihood as a function of $c_{\mathrm{W}}$, based on 138 $\mathrm{fb}^{-1}$ of CMS data at 13 TeV.

Negative of twice in the difference in the log-likelihood as a function of $c_{\mathrm{HWB}}$, based on 138 $\mathrm{fb}^{-1}$ of CMS data at 13 TeV.

Negative of twice in the difference in the log-likelihood as a function of $c_{\mathrm{HWB}}$ and $c_{\mathrm{W}}$, based on 138 $\mathrm{fb}^{-1}$ of CMS data at 13 TeV.

Predicted and measured EWK $\gamma\mathrm{jj}$ fiducial cross sections.

Data vs. the ABCD method background prediction for 2017 in $\mathrm{SR_{b}^{mm}}$. Events are divided by the bin width, hence fractional data counts. Error bars show statistical uncertainties of data. The blue band shows the propagated uncertainty of all individual fit variations in a given bin, which we consider to be uncorrelated. The lower panels show the ratio of the observed data to the background estimation.

Data vs. the ABCD method background prediction for 2018 in $\mathrm{SR_{b}^{mm}}$. Events are divided by the bin width, hence fractional data counts. Error bars show statistical uncertainties of data. The blue band shows the propagated uncertainty of all individual fit variations in a given bin, which we consider to be uncorrelated. The lower panels show the ratio of the observed data to the background estimation.

Data vs. the ABCD method background prediction for 2016 in $\mathrm{SR_{b+\textrm{j}/b}^{mm}}$. Events are divided by the bin width, hence fractional data counts. Error bars show statistical uncertainties of data. The blue band shows the propagated uncertainty of all individual fit variations in a given bin, which we consider to be uncorrelated. The lower panels show the ratio of the observed data to the background estimation.

Data vs. the ABCD method background prediction for 2017 in $\mathrm{SR_{b+\textrm{j}/b}^{mm}}$. Events are divided by the bin width, hence fractional data counts. Error bars show statistical uncertainties of data. The blue band shows the propagated uncertainty of all individual fit variations in a given bin, which we consider to be uncorrelated. The lower panels show the ratio of the observed data to the background estimation.

Data vs. the ABCD method background prediction for 2018 in $\mathrm{SR_{b+\textrm{j}/b}^{mm}}$. Events are divided by the bin width, hence fractional data counts. Error bars show statistical uncertainties of data. The blue band shows the propagated uncertainty of all individual fit variations in a given bin, which we consider to be uncorrelated. The lower panels show the ratio of the observed data to the background estimation.

The asymptotic 95% CL limits on the product of cross section ($\sigma$), branching fraction into a pair of muons ($\mathcal{B}$) to dimuons, acceptance (A), and efficiency ($\epsilon$) in $\mathrm{SR_{b}^{mm}}$. A combination of both limits depends on the relative acceptance contributions in each region and is omitted here.

The asymptotic 95% CL limits on the product of cross section ($\sigma$), branching fraction into a pair of muons ($\mathcal{B}$) to dimuons, acceptance (A), and efficiency ($\epsilon$) in $\mathrm{SR_{b+\textrm{j}/b}^{mm}}$. A combination of both limits depends on the relative acceptance contributions in each region and is omitted here.

Cutflow for signal samples in 2016. Samples are divided by generated mass, signal region, and the b to s quark flavor changing coupling of the $Z^\prime$, dbs. For some mass values, multiple values of this coupling strength have been generated. It is described in this minimal lagrangian: $\mathcal{L} \supset Z^{\prime}_{\eta} \Big[ g_{\mu}\, \bar{\mu}\, \gamma^{\eta}\, \mu + \big( g_b\, \delta_{bs}\, \bar{s}\, \gamma^{\eta}\, P_{L}\, b + \text{h.c.} \big) \Big]$. The cutflow shows the selection into signal regions, and then the effects of specialized HTLT and RelMET selections, which grow with greater mass.

Cutflow for signal samples in 2017. Samples are divided by generated mass, signal region, and the b to s quark flavor changing coupling of the $Z^\prime$, dbs. For some mass values, multiple values of this coupling strength have been generated. It is described in this minimal lagrangian: $\mathcal{L} \supset Z^{\prime}_{\eta} \Big[ g_{\mu}\, \bar{\mu}\, \gamma^{\eta}\, \mu + \big( g_b\, \delta_{bs}\, \bar{s}\, \gamma^{\eta}\, P_{L}\, b + \text{h.c.} \big) \Big]$. The cutflow shows the selection into signal regions, and then the effects of specialized HTLT and RelMET selections, which grow with greater mass.

Cutflow for signal samples in 2018. Samples are divided by generated mass, signal region, and the b to s quark flavor changing coupling of the $Z^\prime$, dbs. For some mass values, multiple values of this coupling strength have been generated. It is described in this minimal lagrangian: $\mathcal{L} \supset Z^{\prime}_{\eta} \Big[ g_{\mu}\, \bar{\mu}\, \gamma^{\eta}\, \mu + \big( g_b\, \delta_{bs}\, \bar{s}\, \gamma^{\eta}\, P_{L}\, b + \text{h.c.} \big) \Big]$. The cutflow shows the selection into signal regions, and then the effects of specialized HTLT and RelMET selections, which grow with greater mass.

Distribution of the mass of the AK8 jet selected as the $\phi$ boson candidate for data and simulated background events in the (TopL, XbbL) validation region for the electron channel. The distribution is shown before the final fit for signal extraction.

Invariant mass distribution of the T quark candidates selected in the $T\to tH$ channel, for events with at least one forward jet in the signal region (TopT, XbbT). For these events, the reconstructed mass of the Higgs boson candidate is required to be between 110 and 140 GeV. Distribution is shown for events in the muon channel. The first (last) bin of the distribution also includes underflow (overflow) events. The lower panel reports the data minus the expected number of events normalized to the statistical uncertainty of the data. The orange band represents the systematic uncertainties, also normalized to the statistical uncertainty of the data.

Invariant mass distribution of the T quark candidates selected in the $T\to tH$ channel, for events with at least one forward jet in the signal region (TopT, XbbT). For these events, the reconstructed mass of the Higgs boson candidate is required to be between 110 and 140 GeV. Distribution is shown for events in the electron channel. The first (last) bin of the distribution also includes underflow (overflow) events. The lower panel reports the data minus the expected number of events normalized to the statistical uncertainty of the data. The orange band represents the systematic uncertainties, also normalized to the statistical uncertainty of the data.

Invariant mass distribution of the T quark candidates selected in the $T\to tH$ channel, for events with at least one forward jet in the signal region (TopL, XbbT). For these events, the reconstructed mass of the Higgs boson candidate is required to be between 110 and 140 GeV. Distribution is shown for events in the muon channel. The first (last) bin of the distribution also includes underflow (overflow) events. The lower panel reports the data minus the expected number of events normalized to the statistical uncertainty of the data. The orange band represents the systematic uncertainties, also normalized to the statistical uncertainty of the data.

Invariant mass distribution of the T quark candidates selected in the $T\to tH$ channel, for events with at least one forward jet in the signal region (TopL, XbbT). For these events, the reconstructed mass of the Higgs boson candidate is required to be between 110 and 140 GeV. Distribution is shown for events in the electron channel. The first (last) bin of the distribution also includes underflow (overflow) events. The lower panel reports the data minus the expected number of events normalized to the statistical uncertainty of the data. The orange band represents the systematic uncertainties, also normalized to the statistical uncertainty of the data.

Observed 95% CL upper limits on the single T quark production cross section times the branching fraction of the $T\to t\phi \to bl\nu b\bar{b}$ channel as a function of $m_{T}$ and $m_{\phi}$ masses.

Observed (solid line) and expected (dashed line) 95% CL upper limit on the single T quark production cross section times the branching fraction of the $T \to t\phi\to bl\nu b\bar{b}$ channel as a function of the $m_{T}$, for fixed value of $m_{\phi}$ = 25 GeV. The inner (green) and outer (yellow) bands represent the regions containing 68% and 95%, respectively, of the limit values expected under the background-only hypothesis.

Observed (solid line) and expected (dashed line) 95% CL upper limit on the single T quark production cross section times the branching fraction of the $T \to t\phi\to bl\nu b\bar{b}$ channel as a function of the $m_{T}$, for fixed value of $m_{\phi}$ = 50 GeV. The inner (green) and outer (yellow) bands represent the regions containing 68% and 95%, respectively, of the limit values expected under the background-only hypothesis.

Observed (solid line) and expected (dashed line) 95% CL upper limit on the single T quark production cross section times the branching fraction of the $T \to t\phi\to bl\nu b\bar{b}$ channel as a function of the $m_{T}$, for fixed value of $m_{\phi}$ = 75 GeV. The inner (green) and outer (yellow) bands represent the regions containing 68% and 95%, respectively, of the limit values expected under the background-only hypothesis.

Observed (solid line) and expected (dashed line) 95% CL upper limit on the single T quark production cross section times the branching fraction of the $T \to t\phi\to bl\nu b\bar{b}$ channel as a function of the $m_{T}$, for fixed value of $m_{\phi}$ = 100 GeV. The inner (green) and outer (yellow) bands represent the regions containing 68% and 95%, respectively, of the limit values expected under the background-only hypothesis.

Observed (solid line) and expected (dashed line) 95% CL upper limit on the single T quark production cross section times the branching fraction of the $T \to t\phi\to bl\nu b\bar{b}$ channel as a function of the $m_{T}$, for fixed value of $m_{\phi}$ = 125 GeV. The inner (green) and outer (yellow) bands represent the regions containing 68% and 95%, respectively, of the limit values expected under the background-only hypothesis.

Observed (solid line) and expected (dashed line) 95% CL upper limit on the single T quark production cross section times the branching fraction of the $T \to t\phi\to bl\nu b\bar{b}$ channel as a function of the $m_{T}$, for fixed value of $m_{\phi}$ = 150 GeV. The inner (green) and outer (yellow) bands represent the regions containing 68% and 95%, respectively, of the limit values expected under the background-only hypothesis.

Observed (solid line) and expected (dashed line) 95% CL upper limit on the single T quark production cross section times the branching fraction of the $T \to t\phi\to bl\nu b\bar{b}$ channel as a function of the $m_{T}$, for fixed value of $m_{\phi}$ = 175 GeV. The inner (green) and outer (yellow) bands represent the regions containing 68% and 95%, respectively, of the limit values expected under the background-only hypothesis.

Observed (solid line) and expected (dashed line) 95% CL upper limit on the single T quark production cross section times the branching fraction of the $T \to t\phi\to bl\nu b\bar{b}$ channel as a function of the $m_{T}$, for fixed value of $m_{\phi}$ = 200 GeV. The inner (green) and outer (yellow) bands represent the regions containing 68% and 95%, respectively, of the limit values expected under the background-only hypothesis.

Observed (solid line) and expected (dashed line) 95% CL upper limit on the single T quark production cross section times the branching fraction of the $T \to t\phi\to bl\nu b\bar{b}$ channel as a function of the $m_{T}$, for fixed value of $m_{\phi}$ = 250 GeV. The inner (green) and outer (yellow) bands represent the regions containing 68% and 95%, respectively, of the limit values expected under the background-only hypothesis.

Observed (solid line) and expected (dashed line) 95% CL upper limit on the single T quark production cross section times the branching fraction of the $T \to tH$ channel as a function of the $m_{T}$ mass. The inner (green) and the outer (yellow) bands represent the region containing 68% and 95%, respectively, of the limit values expected under the background-only hypothesis. The solid red (blue) curve shows the theoretical expectation at NLO for a singlet T quark assuming a narrow-width resonance of width 1% (5%) of the resonance mass [6,7].

Post-fit agreement between data and MC prediction for the $SR_{\mathrm{loose}}^{2\ell3j}$ signal region, which uses the invariant mass of the c-tagged jet and the geometrically closest b-tagged jet, $m_{\mathit{cb}}^{\mathrm{min}\Delta R}$, as an observable. The hatched uncertainty bands include all uncertainties and their correlations. The last bins contain overflow events. "Other Top" includes single-top-quark production and associated production of $t\bar{t}$ and single top quarks with bosons. "Non-Top" includes W+jets, Z+jets, and diboson processes.

Post-fit agreement between data and MC prediction for the $SR_{\mathrm{loose}}^{1\ell6ji}$ signal region, which uses the jet multiplicity, $N_{\mathrm{jets}}$, as an observable. The hatched uncertainty bands include all uncertainties and their correlations. The last bins contain overflow events. "Other Top" includes single-top-quark production and associated production of $t\bar{t}$ and single top quarks with bosons. "Non-Top" includes W+jets, Z+jets, and diboson processes.

Post-fit agreement between data and MC prediction for the $SR_{\mathrm{tight}}^{1\ell6ji}$ signal region, which uses the jet multiplicity, $N_{\mathrm{jets}}$, as an observable. The hatched uncertainty bands include all uncertainties and their correlations. The last bins contain overflow events. "Other Top" includes single-top-quark production and associated production of $t\bar{t}$ and single top quarks with bosons. "Non-Top" includes W+jets, Z+jets, and diboson processes.

Post-fit agreement between data and MC prediction for the $SR_{\mathrm{loose}}^{2\ell4ji}$ signal region, which uses the jet multiplicity, $N_{\mathrm{jets}}$, as an observable. The hatched uncertainty bands include all uncertainties and their correlations. The last bins contain overflow events. "Other Top" includes single-top-quark production and associated production of $t\bar{t}$ and single top quarks with bosons. "Non-Top" includes W+jets, Z+jets, and diboson processes.

Post-fit agreement between data and MC prediction for the $SR_{\mathrm{tight}}^{2\ell4ji}$ signal region, which uses the jet multiplicity, $N_{\mathrm{jets}}$, as an observable. The hatched uncertainty bands include all uncertainties and their correlations. The last bins contain overflow events. "Other Top" includes single-top-quark production and associated production of $t\bar{t}$ and single top quarks with bosons. "Non-Top" includes W+jets, Z+jets, and diboson processes.

Jet multiplicity and tagging criteria for the SRs and CRs in the single-lepton and dilepton channels. All single-lepton regions are defined in the 5-jet-exclusive and 6-jet-inclusive jet selections, all dilepton regions in the 3-jet-exclusive and 4-jet-inclusive jet selections. By construction, $\mathrm{SR}^{2\ell}_{\mathrm{tight}}$ only exists for the 4-jet-inclusive selection. Identical requirements on inclusive and exclusive working points, e.g., one c@22% and one c@11% in the $\mathrm{CR}_1^{1\ell}$, indicate a veto of additional tags at the inclusive working point.

Breakdown of the fiducial $t\bar{t}+{\geq}2c$ and $t\bar{t}+1c$ cross-section uncertainties. Systematic uncertainties are grouped into signal and background modeling, instrumental, and MC statistics categories. The table lists the fractional uncertainty in the measured cross-sections in percent and is estimated from the covariance matrix of the profile likelihood fit, following EPJC 84 (2024) 593. Individual groups of uncertainties can be added in quadrature to obtain the total uncertainty. JES and JER denote the jet energy scale and resolution uncertainties, respectively. The fractional uncertainties in the fitted $t\bar{t}+{\geq}1c$ and $t\bar{t}+\text{light}$ normalization factors are included in the data statistics category. For presentation purposes, all uncertainties are symmetrized.

Measured fiducial cross-section values in comparison with various NLO+PS predictions. The uncertainties in the predictions include independent and simultaneous variations of the $\mu_R$ and $\mu_F$ scales and uncertainties in the choice of the PDF set, but no uncertainties in the parton shower or hadronization. The uncertainties in the measured values include all statistical and systematic uncertainties. For presentation purposes, the quoted measurement and prediction uncertainties are symmetrized.

Measured and predicted values for the $t\bar{t}+{\geq}1b$, $t\bar{t}+{\geq}2c$, and $t\bar{t}+1c$ cross-sections and for the cross-section ratios of these processes to total $t\bar{t}+\text{jets}$ production. The quoted uncertainties in the measurements include statistical and systematic uncertainties. The predictions are taken from the nominal setup using inclusive $t\bar{t}$ Powheg+Pythia8 predictions for the $t\bar{t}+{\geq}2c$, $t\bar{t}+1c$, and $t\bar{t}+\text{light}$ processes, and $t\bar{t}+b\bar{b}$ Powheg+Pythia8 predictions for the $t\bar{t}+{\geq}1b$ process. The first use the 5FS, the latter the 4FS, where the $b$-quarks are treated as massive particles and are included in the matrix element calculation. The uncertainties in the predictions include independent and simultaneous variations of the $\mu_R$ and $\mu_F$ scales and uncertainties in the choice of the PDF set.

Nuisance parameters with a large impact on the fiducial measurement: ranking of the ten most impactful nuisance parameters for the $t\bar{t}+{\geq}2c$ cross-section measurement. The colored boxes indicate the impact of the nuisance parameters, $\Delta\mu$ (top axis), on the corresponding parameter of interest, $\mu$. They are calculated from the covariance matrix using the post-fit up (down) uncertainties of the parameter of interest and the nuisance parameter, $\sigma_{\mathrm{POI}}^{\mathrm{up}}$ and $\sigma_{\mathrm{NP}}^{\mathrm{up}}$ ($\sigma_{\mathrm{POI}}^{\mathrm{down}}$ and $\sigma_{\mathrm{NP}}^{\mathrm{down}}$), and their linear correlation coefficient, $\rho$, following EPJC 84 (2024) 593. The data points and error bars indicate the post-fit values and uncertainties of the nuisance parameters relative to their pre-fit values, $\theta_0$, in units of their pre-fit uncertainties, $\Delta \theta$ (bottom axis). A hollow circle indicates that the nuisance parameter has a Poisson constraint.

Nuisance parameters with a large impact on the fiducial measurement: ranking of the ten most impactful nuisance parameters for the $t\bar{t}+1c$ cross-section measurement. The colored boxes indicate the impact of the nuisance parameters, $\Delta\mu$ (top axis), on the corresponding parameter of interest, $\mu$. They are calculated from the covariance matrix using the post-fit up (down) uncertainties of the parameter of interest and the nuisance parameter, $\sigma_{\mathrm{POI}}^{\mathrm{up}}$ and $\sigma_{\mathrm{NP}}^{\mathrm{up}}$ ($\sigma_{\mathrm{POI}}^{\mathrm{down}}$ and $\sigma_{\mathrm{NP}}^{\mathrm{down}}$), and their linear correlation coefficient, $\rho$, following EPJC 84 (2024) 593. The data points and error bars indicate the post-fit values and uncertainties of the nuisance parameters relative to their pre-fit values, $\theta_0$, in units of their pre-fit uncertainties, $\Delta \theta$ (bottom axis). A hollow circle indicates that the nuisance parameter has a Poisson constraint.

Nuisance parameters with a large impact on the fiducial measurement: ranking of the ten most impactful nuisance parameters for the $t\bar{t}+{\geq}2c$ ratio to total $t\bar{t}+\text{jets}$ production. The colored boxes indicate the impact of the nuisance parameters, $\Delta\mu$ (top axis), on the corresponding parameter of interest, $\mu$. They are calculated from the covariance matrix using the post-fit up (down) uncertainties of the parameter of interest and the nuisance parameter, $\sigma_{\mathrm{POI}}^{\mathrm{up}}$ and $\sigma_{\mathrm{NP}}^{\mathrm{up}}$ ($\sigma_{\mathrm{POI}}^{\mathrm{down}}$ and $\sigma_{\mathrm{NP}}^{\mathrm{down}}$), and their linear correlation coefficient, $\rho$, following EPJC 84 (2024) 593. The data points and error bars indicate the post-fit values and uncertainties of the nuisance parameters relative to their pre-fit values, $\theta_0$, in units of their pre-fit uncertainties, $\Delta \theta$ (bottom axis). A hollow circle indicates that the nuisance parameter has a Poisson constraint.

Nuisance parameters with a large impact on the fiducial measurement: ranking of the ten most impactful nuisance parameters for the $t\bar{t}+1c$ ratio to total $t\bar{t}+\text{jets}$ production. The colored boxes indicate the impact of the nuisance parameters, $\Delta\mu$ (top axis), on the corresponding parameter of interest, $\mu$. They are calculated from the covariance matrix using the post-fit up (down) uncertainties of the parameter of interest and the nuisance parameter, $\sigma_{\mathrm{POI}}^{\mathrm{up}}$ and $\sigma_{\mathrm{NP}}^{\mathrm{up}}$ ($\sigma_{\mathrm{POI}}^{\mathrm{down}}$ and $\sigma_{\mathrm{NP}}^{\mathrm{down}}$), and their linear correlation coefficient, $\rho$, following EPJC 84 (2024) 593. The data points and error bars indicate the post-fit values and uncertainties of the nuisance parameters relative to their pre-fit values, $\theta_0$, in units of their pre-fit uncertainties, $\Delta \theta$ (bottom axis). A hollow circle indicates that the nuisance parameter has a Poisson constraint.

Efficiencies and rejection rates for the $b$- and $c$-jet tagging working points of the $b/c$-tagger, as well as the selection cuts on the discriminants, $\mathcal{D}_b'$ and $\mathcal{D}_c'$ that define the tagging bins. The primes indicate that a standard logistic function is applied to the discriminants. The b@70% and c@22% working points are inclusive of their respective tighter working points. The values were estimated from single-lepton and dilepton $t\bar{t}$ events simulated with Powheg + Pythia 8.

Efficiencies and rejection rates for the $b$- and $c$-jet tagging working points of the $b/c$-tagger, as well as the selection cuts on the discriminants, $\mathcal{D}_b'$ and $\mathcal{D}_c'$ that define the tagging bins. The primes indicate that a standard logistic function is applied to the discriminants. The b@70% and c@22% working points are inclusive of their respective tighter working points. The values were estimated from single-lepton and dilepton $t\bar{t}$ events simulated with Powheg + Pythia 8.

Pre-fit event yields in the twelve single-lepton and dilepton control regions (CRs) of the analysis. The quoted uncertainties include both statistical and systematic components, but all normalization factors are fixed to their pre-fit values with no uncertainties. All uncertainties are assumed to be uncorrelated. "Other Top" includes single-top-quark production and associated production of $t\bar{t}$ and single top quarks with bosons. "Non-Top" includes W+jets, Z+jets, and diboson processes. The "Fakes" category includes events from misidentified leptons and non-prompt leptons, estimated through the data-driven matrix method in the single-lepton channel and through MC predictions in the dilepton channel.

Pre-fit event yields in the seven signal regions (SRs) of the analysis. The quoted uncertainties include both statistical and systematic components, but all normalization factors are fixed to their pre-fit values with no uncertainties. All uncertainties are assumed to be uncorrelated. "Other Top" includes single-top-quark production and associated production of $t\bar{t}$ and single top quarks with bosons. "Non-Top" includes W+jets, Z+jets, and diboson processes. The "Fakes" category includes events from misidentified leptons and non-prompt leptons, estimated through the data-driven matrix method in the single-lepton channel and through MC predictions in the dilepton channel.

Post-fit event yields in the twelve single-lepton and dilepton control regions (CRs) of the analysis. The quoted uncertainties include both statistical and systematic components, and post-fit correlations between uncertainties are taken into account. "Other Top" includes single-top-quark production and associated production of $t\bar{t}$ and single top quarks with bosons. "Non-Top" includes W+jets, Z+jets, and diboson processes. The "Fakes" category includes events from misidentified leptons and non-prompt leptons, estimated through the data-driven matrix method in the single-lepton channel and through MC predictions in the dilepton channel.

Post-fit event yields in the seven signal regions (SRs) of the analysis. The quoted uncertainties include both statistical and systematic components, and post-fit correlations between uncertainties are taken into account. "Other Top" includes single-top-quark production and associated production of $t\bar{t}$ and single top quarks with bosons. "Non-Top" includes W+jets, Z+jets, and diboson processes. The "Fakes" category includes events from misidentified leptons and non-prompt leptons, estimated through the data-driven matrix method in the single-lepton channel and through MC predictions in the dilepton channel.

The 95% CL upper limits on the inclusive signal strength $ r = \sigma_{HH} /\sigma_{HH} ^\text{SM} $ for each channel and their combination. The inner (green) band and the outer (yellow) band indicate the 68 and 95% CL intervals, respectively, under the background-only hypothesis. The $ b\overline{b}b\overline{b} $ and $ b\overline{b}WW $ contributions have been combined in order to simplify the presentation of results.

The 95$\%$ CL upper limits on the VBF signal strength $r_{VBF HH} = \sigma_{VBF HH}/\sigma_{VBF HH}^{SM}$ for each channel and their combination. The inner (green) band and the outer (yellow) band indicate the 68 and 95$\%$ CL intervals, respectively, under the background-only hypothesis. Not all of the eight channels are used to extract the combined VBF limit. The contributing channels are indicated in the figure. The b\overline{b}b\overline{b} $ and $ b\overline{b}WW $ contributions have been combined in order to simplify the presentation of results.

The 95$\%$ CL upper limits on the inclusive HH cross section as a function of $\kappa_\lambda$. All other couplings are set to the values predicted by the SM. The theoretical uncertainties in the HH GGF and VBF signal cross sections are not considered because here we directly constrain the measured cross section.The inner (green) band and the outer (yellow) band indicate the 68 and 95$\%$ CL intervals, respectively, under the background-only hypothesis. The star shows the limit at the SM value for $\kappa_\lambda$.

The 95$\%$ CL upper limits on the inclusive HH cross section as a function of $\kappa_{2V}$. All other couplings are set to the values predicted by the SM. The theoretical uncertainties in the HH VBF signal cross sections are not considered because here we directly constrain the measured cross section.The inner (green) band and the outer (yellow) band indicate the 68 and 95$\%$ CL intervals, respectively, under the background-only hypothesis. The star shows the limit at the SM value for $\kappa_{2V}$.

The profile likelihood ratio test statistic $-2\Delta\log(L)$ as a function of coupling modifiers $\kappa_\lambda$ for the combination of all channels, when all the other parameters are fixed to their SM values.

The profile likelihood ratio test statistic $-2\Delta\log(L)$ as a function of coupling modifiers $\kappa_{2V}$ for the combination of all channels, when all the other parameters are fixed to their SM values.

The 68 $\%$ CL expected contours of $-2\Delta\log(L)$ in the ($\kappa_\lambda$, $\kappa_{2V}$) plane for the combination of all channels when all the other parameters are fixed to their SM values.

The 95$\%$ CL expected contours of $-2\Delta\log(L)$ in the ($\kappa_\lambda$, $\kappa_{2V}$) plane for the combination of all channels when all the other parameters are fixed to their SM values.

The 68 $\%$ CL observed contours of $-2\Delta\log(L)$ in the ($\kappa_\lambda$, $\kappa_{2V}$) plane for the combination of all channels when all the other parameters are fixed to their SM values.

The 95$\%$ observed CL contours of $-2\Delta\log(L)$ in the ($\kappa_\lambda$, $\kappa_{2V}$) plane for the combination of all channels when all the other parameters are fixed to their SM values.

The 5 standard deviation expected contours of $-2\Delta\log(L)$ in the ($\kappa_\lambda$, $\kappa_{2V}$) plane for the combination of all channels when all the other parameters are fixed to their SM values.

The 5 standard deviation observed contours of $-2\Delta\log(L)$ in the ($\kappa_\lambda$, $\kappa_{2V}$) plane for the combination of all channels when all the other parameters are fixed to their SM values.

The observed best-fit values in the ($\kappa_\lambda$, $\kappa_{2V}$) plane for the combination of all channels when all the other parameters are fixed to their SM values.

The 68 $\%$ expected CL contours of $-2\Delta\log(L)$ in the ($\kappa_{V}$, $\kappa_{2V}$) plane for the combination of all channels when all the other parameters are fixed to their SM values.

The 68$\%$ expected CL contours of $-2\Delta\log(L)$ in the ($\kappa_{V}$, $\kappa_{2V}$) plane for the combination of all channels when all the other parameters are fixed to their SM values.

The 95$\%$ CL expected contours of $-2\Delta\log(L)$ in the ($\kappa_{V}$, $\kappa_{2V}$) plane for the combination of all channels when all the other parameters are fixed to their SM values.

The 95$\%$ CL observed contours of $-2\Delta\log(L)$ in the ($\kappa_{V}$, $\kappa_{2V}$) plane for the combination of all channels when all the other parameters are fixed to their SM values.

The 5 standard deviation expected contours of $-2\Delta\log(L)$ in the ($\kappa_{V}$, $\kappa_{2V}$) plane for the combination of all channels when all the other parameters are fixed to their SM values.

The 5 standard deviation observed contours of $-2\Delta\log(L)$ in the ($\kappa_{V}$, $\kappa_{2V}$) plane for the combination of all channels when all the other parameters are fixed to their SM values.

The observed best-fit values in the ($\kappa_{V}$, $\kappa_{2V}$) plane for the combination of all channels when all the other parameters are fixed to their SM values.

The 68 $\%$ CL expected contours of $-2\Delta\log(L)$ in the ($\kappa_\lambda$, $\kappa_t$) plane for the combination of all channels when all the other parameters are fixed to their SM values.

The 68 $\%$ CL observed contours of $-2\Delta\log(L)$ in the ($\kappa_\lambda$, $\kappa_t$) plane for the combination of all channels when all the other parameters are fixed to their SM values.

The 95$\%$ CL expected contours of $-2\Delta\log(L)$ in the ($\kappa_\lambda$, $\kappa_t$) plane for the combination of all channels when all the other parameters are fixed to their SM values.

The 95$\%$ CL observed contours of $-2\Delta\log(L)$ in the ($\kappa_\lambda$, $\kappa_t$) plane for the combination of all channels when all the other parameters are fixed to their SM values.

The observed best-fit values in the ($\kappa_\lambda$, $\kappa_t$) plane for the combination of all channels when all the other parameters are fixed to their SM values.

Upper limits on the HH production cross section at 95$\%$ CL for the two sets of HEFT benchmarks. The theoretical uncertainties in the HH GGF signal cross section are not considered because we directly constrain the measured cross section.

Upper limits on the HH cross section as a function of the $C_2$ coupling modifier. The theoretical uncertainties in the HH GGF signal cross section are not considered because we directly constrain the measured cross section.

The profile likelihood ratio test statistic $-2\Delta\log(L)$ as a function of the $c_2$ coupling modifier.

The 68$\%$CL expected contours of $-2\Delta\log(L)$ in the ($c_2$,$\kappa_t$) for the combination of all channels when all the other parameters are fixed to their SM value.

The 68$\%$CL observed contours of $-2\Delta\log(L)$ in the ($c_2$,$\kappa_t$) for the combination of all channels when all the other parameters are fixed to their SM value.

The 95$\%$CL expected contours of $-2\Delta\log(L)$ in the ($c_2$,$\kappa_t$) for the combination of all channels when all the other parameters are fixed to their SM value.

The 95$\%$CL observed contours of $-2\Delta\log(L)$ in the ($c_2$,$\kappa_t$) for the combination of all channels when all the other parameters are fixed to their SM value.

The 68 $\%$ CL expected contours of $-2\Delta\log(L)$ in the ($c_2$, $\kappa_\lambda$) for the combination of all channels when all the other parameters are fixed to their SM value.

The 68 $\%$ CL observed contours of $-2\Delta\log(L)$ in the ($c_2$, $\kappa_\lambda$) for the combination of all channels when all the other parameters are fixed to their SM value.

The 95 $\%$ CL expected contours of $-2\Delta\log(L)$ in the ($c_2$, $\kappa_\lambda$) for the combination of all channels when all the other parameters are fixed to their SM value.

The 95 $\%$ CL observed contours of $-2\Delta\log(L)$ in the ($c_2$, $\kappa_\lambda$) for the combination of all channels when all the other parameters are fixed to their SM value.

The $-2\Delta\log(L)$ scan for the combination of all channels as a function of $|\cos{\alpha}|$ for singlet extensions of the SM with spontaneous $Z_2$ symmetry breaking. The $|\cos{\alpha}|$ is constrained at 95\% CL between 0.79 and 1. The ranges of $|\cos{\alpha}|$ and $\lambda_\text{eff}$ are chosen to guarantee the validity of the models. The excluded regions are below the curves shown.

The 95$\%$ CL expected contour of $-2\Delta\log(L)$ in the ($|\cos{\alpha}|$, $\lambda_{eff}$) plane, where $\lambda_{eff}$=$\lambda_\alpha$-$\tan{(\alpha)\frac{m_{2}}{\nu}}$. The ranges of $|\cos{\alpha}|$ and $\lambda_{eff}$ are chosen to guarantee the validity of the models. The excluded regions are to the left of the curves shown.

The 95$\%$ CL observed contour of $-2\Delta\log(L)$ in the ($|\cos{\alpha}|$, $\lambda_{eff}$) plane, where $\lambda_{eff}$=$\lambda_\alpha$-$\tan{(\alpha)\frac{m_{2}}{\nu}}$. The ranges of $|\cos{\alpha}|$ and $\lambda_{eff}$ are chosen to guarantee the validity of the models. The excluded regions are to the left of the curves shown.

The 95% CL expected contour of $-2\Delta\log(L)$ for the combination of all channels in the ($m_{H}$, $\tan\beta$) plane for a fixed value of $|\cos(\beta-\alpha)|=0.2$ in the 2HDM-I model. In these and all other cases considered in this paper, $m_H$ = $m_A$. The ranges of $m_{H}$ and $\tan\beta$ are chosen to guarantee the validity of the models. The excluded regions are below the curves shown. The value $\tan\beta$ = 0.5 is excluded for $m_{H}$ > 800 GeV for all models considered.

The 95$\%$ CL observed contour of $-2\Delta\log(L)$ for the combination of all channels in the ($m_{H}$, $\tan\beta$) plane for a fixed value of $|\cos(\beta-\alpha)|=0.2$ in the 2HDM-I model. In these and all other cases considered in this paper, $m_H$ = $m_A$. The ranges of $m_{H}$ and $\tan\beta$ are chosen to guarantee the validity of the models. The excluded regions are below the curves shown. The value $\tan\beta$ = 0.5 is excluded for $m_{H}$ > 800 GeV for all models considered.

The 95$\%$ CL contour of $-2\Delta\log(L)$ for the combination of all channels in the ($m_{H}$, $\tan\beta$) plane for a fixed value of $|\cos(\beta-\alpha)|=0.2$ for the 2HDM I models. In these and all other cases considered in this paper, $m_H$ = $m_A$. The ranges of $m_{H}$ and $\tan\beta$ are chosen to guarantee the validity of the models. The excluded regions are below the curves shown. The value $\tan\beta$ = 0.5 is excluded for $m_{H}$ > 800 GeV for all models considered.

The 95$\%$ CL contour of $-2\Delta\log(L)$ for the combination of all channels in the ($m_{H}$, $\tan\beta$) plane for a fixed value of $|\cos(\beta-\alpha)|=0.2$ for the 2HDM II models. In these and all other cases considered in this paper, $m_H$ = $m_A$. The ranges of $m_{H}$ and $\tan\beta$ are chosen to guarantee the validity of the models. The excluded regions are below the curves shown. The value $\tan\beta$ = 0.5 is excluded for $m_{H}$ > 800 GeV for all models considered.

The 95$\%$ CL contour of $-2\Delta\log(L)$ for the combination of all channels in the ($m_{H}$, $\tan\beta$) plane for a fixed value of $|\cos(\beta-\alpha)|=0.2$ for the 2HDM X models. In these and all other cases considered in this paper, $m_H$ = $m_A$. The ranges of $m_{H}$ and $\tan\beta$ are chosen to guarantee the validity of the models. The excluded regions are below the curves shown. The value $\tan\beta$ = 0.5 is excluded for $m_{H}$ > 800 GeV for all models considered.

The 95$\%$ CL contour of $-2\Delta\log(L)$ for the combination of all channels in the ($m_{H}$, $\tan\beta$) plane for a fixed value of $|\cos(\beta-\alpha)|=0.2$ for the 2HDM Y models. In these and all other cases considered in this paper, $m_H$ = $m_A$. The ranges of $m_{H}$ and $\tan\beta$ are chosen to guarantee the validity of the models. The excluded regions are below the curves shown. The value $\tan\beta$ = 0.5 is excluded for $m_{H}$ > 800 GeV for all models considered.

The 95$\%$ CL expected contour of $-2\Delta\log(L)$ for the combination of all channels in the ($|\cos(\beta-\alpha)|$, $\tan\beta$) plane for a fixed value of $m_{H}=1000GeV$ in the 2HDM-I model. In these and all other cases considered in this paper, $m_H$ = $m_A$. The ranges of $|\cos(\beta-\alpha)|$ and $\tan\beta$ are chosen to guarantee the validity of the models. The excluded regions are below the curves shown. The value $\tan\beta$ = 0.5 is excluded for $|\cos(\beta-\alpha)|$ > 0.16 and $|\cos(\beta-\alpha)|$ < -0.13 for all models considered.

The 95$\%$ CL observed contour of $-2\Delta\log(L)$ for the combination of all channels in the ($|\cos(\beta-\alpha)|$, $\tan\beta$) plane for a fixed value of $m_{H}=1000GeV$ in the 2HDM-I model. In these and all other cases considered in this paper, $m_H$ = $m_A$. The ranges of $|\cos(\beta-\alpha)|$ and $\tan\beta$ are chosen to guarantee the validity of the models. The excluded regions are below the curves shown. The value $\tan\beta$ = 0.5 is excluded for $|\cos(\beta-\alpha)|$ > 0.16 and $|\cos(\beta-\alpha)|$ < -0.13 for all models considered.

The 95% CL contour of $-2\Delta\log(L)$ for the combination of all channels in the ($|\cos(\beta-\alpha)|$, $\tan\beta$) plane for a fixed value of $m_{H}=1000GeV$ for the 2HDM I models. In these and all other cases considered in this paper, $m_H$ = $m_A$. The ranges of $|\cos(\beta-\alpha)|$ and $\tan\beta$ are chosen to guarantee the validity of the models. The excluded regions are below the curves shown. The value $\tan\beta$ = 0.5 is excluded for $|\cos(\beta-\alpha)|$ > 0.16 and $|\cos(\beta-\alpha)|$ < -0.13 for all models considered.

The 95% CL contour of $-2\Delta\log(L)$ for the combination of all channels in the ($|\cos(\beta-\alpha)|$, $\tan\beta$) plane for a fixed value of $m_{H}=1000GeV$ for the 2HDM II models. In these and all other cases considered in this paper, $m_H$ = $m_A$. The ranges of $|\cos(\beta-\alpha)|$ and $\tan\beta$ are chosen to guarantee the validity of the models. The excluded regions are below the curves shown. The value $\tan\beta$ = 0.5 is excluded for $|\cos(\beta-\alpha)|$ > 0.16 and $|\cos(\beta-\alpha)|$ < -0.13 for all models considered.

The 95% CL contour of $-2\Delta\log(L)$ for the combination of all channels in the ($|\cos(\beta-\alpha)|$, $\tan\beta$) plane for a fixed value of $m_{H}=1000GeV$ for the 2HDM X models. In these and all other cases considered in this paper, $m_H$ = $m_A$. The ranges of $|\cos(\beta-\alpha)|$ and $\tan\beta$ are chosen to guarantee the validity of the models. The excluded regions are below the curves shown. The value $\tan\beta$ = 0.5 is excluded for $|\cos(\beta-\alpha)|$ > 0.16 and $|\cos(\beta-\alpha)|$ < -0.13 for all models considered.

The 95% CL contour of $-2\Delta\log(L)$ for the combination of all channels in the ($|\cos(\beta-\alpha)|$, $\tan\beta$) plane for a fixed value of $m_{H}=1000GeV$ for the 2HDM Y models. In these and all other cases considered in this paper, $m_H$ = $m_A$. The ranges of $|\cos(\beta-\alpha)|$ and $\tan\beta$ are chosen to guarantee the validity of the models. The excluded regions are below the curves shown. The value $\tan\beta$ = 0.5 is excluded for $|\cos(\beta-\alpha)|$ > 0.16 and $|\cos(\beta-\alpha)|$ < -0.13 for all models considered.

The $-2\Delta\log(L)$ scan for the combination of all channels as a function of $\xi$ for MCHM$_4$. The range of $\xi$ is chosen to guarantee the validity of the model. At 95% CL, $\xi$ is constrained to be between 0 and 0.45 in MCHM$_4$.

The $-2\Delta\log(L)$ scan for the combination of all channels as a function of $\xi$ for MCHM$_5$. The range of $\xi$ is chosen to guarantee the validity of the model. At 95% CL, $\xi$ is constrained to be between 0 and 0.26 in MCHM$_5$.

Treatment of most important common systematic uncertainties in the S2 scenario.

The expected upper limits at 95% CL on the HH signal strength from the combination of all the considered channels at different integrated luminosities for the S2 scenario.

The expected upper limits at 95% CL on the HH signal strength from the combination of all the considered channels under different assumptions on the systematic uncertainties for an integrated luminosity of 3000fb$^{-1}$ (right).

The expected $-2\Delta\log(L)$ scan as a function of coupling modifier $\kappa_\lambda$ for the combination of all contributing channels, projected to different integrated luminosities. All other parameters are fixed to their SM values.

The expected $-2\Delta\log(L)$ scan as a function of coupling modifier $\kappa_\lambda$ for the combination of all contributing channels, projected under different assumptions on the systematic uncertainties for an integrated luminosity of 3000fb$^{-1}$. All other parameters are fixed to their SM values.

Expected significance for the HH signal projected to 2000 or 3000 fb$^{-1}$ under different assumptions of systematic uncertainties.

The expected signal significance as a function of integrated luminosity for the nominal scenario of systematic uncertainties S2 and for the scenario with statistical uncertainties only.

The expected signal significance as a function of $\kappa_\lambda$ under different assumptions on the systematic uncertainties for an integrated luminosity of 3000fb$^{-1}$.

The 95$\%$ CL upper limits on the inclusive HH signal strenngth as a function of $\kappa_{\lambda}$ coupling modifier. All other couplings are set to the values predicted by the SM. The theoretical uncertainties in the HH VBF signal cross sections are not considered because here we directly constrain the measured cross section.The inner (green) band and the outer (yellow) band indicate the 68 and 95$\%$ CL intervals, respectively, under the background-only hypothesis.

The 95$\%$ CL upper limits on the inclusive HH signal strenngth as a function of $\kappa_{2V}$ coupling modifier. All other couplings are set to the values predicted by the SM. The theoretical uncertainties in the HH VBF signal cross sections are not considered because here we directly constrain the measured cross section.The inner (green) band and the outer (yellow) band indicate the 68 and 95$\%$ CL intervals, respectively, under the background-only hypothesis.

The $-2\Delta\log(L)$ scan as a function of $\kappa_\lambda$ for all channels, when all the other parameters are fixed to their SM value.

The $-2\Delta\log(L)$ scan as a function of $\kappa_{2V}$ for all channels, when all the other parameters are fixed to their SM value.

The $-2\Delta\log(L)$ scan as a function of $\kappa_\lambda$ for all channels, when all the other parameters are fixed to their SM value.

The 95$\%$ CL upper limits on the inclusive HH cross section as a function of $\kappa_\lambda$ coupling modifier for all channels. All other couplings are set to the values predicted by the SM. The theoretical uncertainties in the HH GGF and VBF signal cross sections are not considered because here we directly constrain the measured cross section.

The 95$\%$ CL upper limits on the inclusive VBF HH cross section as a function of $\kappa_{2V}$ coupling modifier for all channels. All other couplings are set to the values predicted by the SM. The theoretical uncertainties in the HH GGF and VBF signal cross sections are not considered because here we directly constrain the measured cross section.

The 95$\%$ CL upper limits on the inclusive HH signal strength as a function of $\kappa_\lambda$ coupling modifier for all channels. All other couplings are set to the values predicted by the SM. The theoretical uncertainties in the HH GGF and VBF signal cross sections are not considered because here we directly constrain the measured cross section.

The 95$\%$ CL upper limits on the inclusive VBF HH signal strength as a function of $\kappa_{2V}$ coupling modifier for all channels. All other couplings are set to the values predicted by the SM. The theoretical uncertainties in the HH GGF and VBF signal cross sections are not considered because here we directly constrain the measured cross section.

The best fit value for $\kappa_\lambda$ compared to the SM expectation for all channels and their combination, when all the other parameters are fixed to their SM values.

The best fit value for $\kappa_2V$ compared to the SM expectation for all channels and their combination, when all the other parameters are fixed to their SM values.

The 68$\%$ CL expected contours of $-2\Delta\log(L)$ in the ($\kappa_{V}$, $\kappa_{2V}$) plane for the combination of all channels when all the other parameters are fixed to their SM values.

The 68$\%$ CL observed contours of $-2\Delta\log(L)$ in the ($\kappa_{V}$, $\kappa_{2V}$) plane for the combination of all channels when all the other parameters are fixed to their SM values.

The 95$\%$ CL expected contours of $-2\Delta\log(L)$ in the ($\kappa_{V}$, $\kappa_{2V}$) plane for the combination of all channels when all the other parameters are fixed to their SM values.

The 95$\%$ CL observed contours of $-2\Delta\log(L)$ in the ($\kappa_{V}$, $\kappa_{2V}$) plane for the combination of all channels when all the other parameters are fixed to their SM values.

The 5 $\sigma$ expected contours of $-2\Delta\log(L)$ in the ($\kappa_{V}$, $\kappa_{2V}$) plane for the combination of all channels when all the other parameters are fixed to their SM values.

The 5 $\sigma$ observed contours of $-2\Delta\log(L)$ in the ($\kappa_{V}$, $\kappa_{2V}$) plane for the combination of all channels when all the other parameters are fixed to their SM values.

The best-fit values of ($\kappa_{V}$, $\kappa_{2V}$) for the combination of all channels when all the other parameters are fixed to their SM values.

The 95$\%$ CL upper limits on the inclusive VBF HH signal strength as a function of $\kappa_{2V}$ coupling modifier for all channels. All other couplings are set to the values predicted by the SM. The theoretical uncertainties in the HH GGF and VBF signal cross sections are not considered because here we directly constrain the measured cross section. The inner (green) band and the outer (yellow) band indicate the 68 and 95% CL intervals, respectively, under the background-only hypothesis.

The $-2\Delta\log(L)$ scan as a function of the $c_2$ coupling modifier for all channels, when all the other parameters are fixed to their SM values.

The 95% CL upper limits on the inclusive HH cross section as a function of the $c_2$ coupling modifier for all channels. All other couplings are set to the values predicted by the SM. The theoretical uncertainties in the HH ggF signal cross sections are not considered because we directly constrain the measured cross section.

The 95% CL upper limits on the inclusive HH signal strength as a function of the $c_2$ coupling modifier for all channels. All other couplings are set to the values predicted by the SM. The theoretical uncertainties in the HH ggF signal cross sections are considered in this case

The best fit value for the $c_2$ coupling modifier compared to the SM expectation for all channels and their combination, when all the other parameters are fixed to their SM values.

The observed 68 $\%$ CL observed contours ($\kappa_\lambda$ =1.0) of $-2\Delta\log(L)$ in the ($c_2$, $\kappa_t$) plane for the combination of all channels when $\kappa_t$ is allowed to vary. The range of $\kappa_t$ is set between 0.5 and 1.5 to avoid unphysical areas of the phase space. All the other parameters are fixed to their SM values.

The observed 68 $\%$ CL observed contours (floating $\kappa_\lambda$) of $-2\Delta\log(L)$ in the ($c_2$, $\kappa_t$) plane for the combination of all channels when $\kappa_t$ is allowed to vary. The range of $\kappa_t$ is set between 0.5 and 1.5 to avoid unphysical areas of the phase space. All the other parameters are fixed to their SM values.

The observed 95 $\%$ CL observed contours ($\kappa_\lambda$ =1.0) of $-2\Delta\log(L)$ in the ($c_2$, $\kappa_t$) plane for the combination of all channels when $\kappa_t$ is allowed to vary. The range of $\kappa_t$ is set between 0.5 and 1.5 to avoid unphysical areas of the phase space. All the other parameters are fixed to their SM values.

The observed 95 $\%$ CL observed contours (floating $\kappa_\lambda$) of $-2\Delta\log(L)$ in the ($c_2$, $\kappa_t$) plane for the combination of all channels when $\kappa_t$ is allowed to vary. The range of $\kappa_t$ is set between 0.5 and 1.5 to avoid unphysical areas of the phase space. All the other parameters are fixed to their SM values.

The best fit values ($\kappa_\lambda$ =1.0) of ($c_2$, $\kappa_t$) for the combination of all channels when $\kappa_t$ is allowed to vary. The range of $\kappa_t$ is set between 0.5 and 1.5 to avoid unphysical areas of the phase space. All the other parameters are fixed to their SM values.

The best fit values (floating $\kappa_\lambda$) of ($c_2$, $\kappa_t$) for the combination of all channels when $\kappa_t$ is allowed to vary. The range of $\kappa_t$ is set between 0.5 and 1.5 to avoid unphysical areas of the phase space. All the other parameters are fixed to their SM values.

The observed 68$\%$ CL cobsevred contours ($\kappa_{t}$ =1.0 (SM)) of $-2\Delta\log(L)$ in the ($c_2$, $\kappa_\lambda$) plane for the combination of all channels when $\kappa_\lambda$ is allowed to vary. The range of $\kappa_\lambda$ is set between -15 and 15 to avoid unphysical areas of the phase space. All the other parameters are fixed to their SM values.

The observed 68$\%$ CL cobsevred contours (floating $\kappa_{t}$) of $-2\Delta\log(L)$ in the ($c_2$, $\kappa_\lambda$) plane for the combination of all channels when $\kappa_\lambda$ is allowed to vary. The range of $\kappa_\lambda$ is set between -15 and 15 to avoid unphysical areas of the phase space. All the other parameters are fixed to their SM values.

The observed 95$\%$ CL cobsevred contours ($\kappa_{t}$ =1.0 (SM)) of $-2\Delta\log(L)$ in the ($c_2$, $\kappa_\lambda$) plane for the combination of all channels when $\kappa_\lambda$ is allowed to vary. The range of $\kappa_\lambda$ is set between -15 and 15 to avoid unphysical areas of the phase space. All the other parameters are fixed to their SM values.

The observed 95$\%$ CL cobsevred contours (floating $\kappa_{t}$) of $-2\Delta\log(L)$ in the ($c_2$, $\kappa_\lambda$) plane for the combination of all channels when $\kappa_\lambda$ is allowed to vary. The range of $\kappa_\lambda$ is set between -15 and 15 to avoid unphysical areas of the phase space. All the other parameters are fixed to their SM values.

The best fit values ($\kappa_{t}$ =1.0 (SM)) of ($c_2$, $\kappa_\lambda$) for the combination of all channels when $\kappa_\lambda$ is allowed to vary. The range of $\kappa_\lambda$ is set between -15 and 15 to avoid unphysical areas of the phase space. All the other parameters are fixed to their SM values.

The best fit values (floating $\kappa_{t}$) for ($c_2$, $\kappa_\lambda$) for the combination of all channels when $\kappa_\lambda$ is allowed to vary. The range of $\kappa_\lambda$ is set between -15 and 15 to avoid unphysical areas of the phase space. All the other parameters are fixed to their SM values.

The observed 68% CL contours of $-2\Delta\log(L)$ in the ($c_2$, $\kappa_\lambda$) plane for the combination of all channels when all the other parameters are fixed to their SM value. The best fit value and 68% CL contour for the $b\bar{b}\tau\tau$ channel are not within the range of the figure.

The observed best fit values in the ($c_2$, $\kappa_\lambda$) plane for the combination of all channels when all the other parameters are fixed to their SM value. The best fit value and 68% CL contour for the $b\bar{b}\tau\tau$ channel are not within the range of the figure.

The observed 68% CL contours of $-2\Delta\log(L)$ in the ($c_2$, $\kappa_\lambda$) plane for the $b\bar{b}b\bar{b}$ resolved channel when all the other parameters are fixed to their SM value. The best fit value and 68% CL contour for the $b\bar{b}\tau\tau$ channel are not within the range of the figure.

The observed best fit values in the ($c_2$, $\kappa_\lambda$) plane for the $b\bar{b}b\bar{b}$ resolved channel when all the other parameters are fixed to their SM value. The best fit value and 68% CL contour for the $b\bar{b}\tau\tau$ channel are not within the range of the figure.

The observed 68% CL contours of $-2\Delta\log(L)$ in the ($c_2$, $\kappa_\lambda$) plane for the $b\bar{b}b\bar{b}$ merged channel when all the other parameters are fixed to their SM value. The best fit value and 68% CL contour for the $b\bar{b}\tau\tau$ channel are not within the range of the figure.

The observed best fit values in the ($c_2$, $\kappa_\lambda$) plane for the $b\bar{b}b\bar{b}$ merged channel when all the other parameters are fixed to their SM value. The best fit value and 68% CL contour for the $b\bar{b}\tau\tau$ channel are not within the range of the figure.

The observed 68% CL contours of $-2\Delta\log(L)$ in the ($c_2$, $\kappa_\lambda$) plane for the $b\bar{b}\gamma\gamma$ channel when all the other parameters are fixed to their SM value. The best fit value and 68% CL contour for the $b\bar{b}\tau\tau$ channel are not within the range of the figure.

The observed best fit values in the ($c_2$, $\kappa_\lambda$) plane for the $b\bar{b}\gamma\gamma$ channel when all the other parameters are fixed to their SM value. The best fit value and 68% CL contour for the $b\bar{b}\tau\tau$ channel are not within the range of the figure.

The observed 68% CL contours of $-2\Delta\log(L)$ in in the ($c_2$, $\kappa_\lambda$) plane for the $b\bar{b}W^{+}W^{-}$ channel when all the other parameters are fixed to their SM value. The best fit value and 68% CL contour for the $b\bar{b}\tau\tau$ channel are not within the range of the figure.

The best fit values in in the ($c_2$, $\kappa_\lambda$) plane for the $b\bar{b}W^{+}W^{-}$ channel when all the other parameters are fixed to their SM value. The best fit value and 68% CL contour for the $b\bar{b}\tau\tau$ channel are not within the range of the figure.

The observed 68% CL contours of $-2\Delta\log(L)$ in in the ($c_2$, $\kappa_\lambda$) plane for the multilepton channel when all the other parameters are fixed to their SM value. The best fit value and 68% CL contour for the $b\bar{b}\tau\tau$ channel are not within the range of the figure.

The best fit values in in the ($c_2$, $\kappa_\lambda$) plane for the multilepton channel when all the other parameters are fixed to their SM value. The best fit value and 68% CL contour for the $b\bar{b}\tau\tau$ channel are not within the range of the figure.

The observed 68% CL contours of $-2\Delta\log(L)$ in in the ($c_2$, $\kappa_\lambda$) plane for the $W^{+}W^{-}\gamma\gamma$ channel when all the other parameters are fixed to their SM value. The best fit value and 68% CL contour for the $b\bar{b}\tau\tau$ channel are not within the range of the figure.

The best fit values in in the ($c_2$, $\kappa_\lambda$) plane for the $W^{+}W^{-}\gamma\gamma$ channel when all the other parameters are fixed to their SM value. The best fit value and 68% CL contour for the $b\bar{b}\tau\tau$ channel are not within the range of the figure.