$\xi$ distributions for different jet $p_T$ bins.

$\xi$ distributions for different jet $p_T$ bins.

The $j_T/p_{T}^{\rm jet}$ distributions for different jet $p_T$ bins.

The $j_T/p_{T}^{\rm jet}$ distributions for different jet $p_T$ bins.

$r$ distributions for different jet $p_T$ bins.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

The unfolded dijet balance distribution, $(1/N_{dijet})(dN_{dijet}/dx_{j})$, as function of $x_{j}$ for the $10-60$, $60-120$, $120-185$, $185-250$ and $250-400$ multiplicity ranges with leading and subleading jets at forward and midrapidity regions, respectively.

The unfolded dijet balance distribution, $(1/N_{dijet})(dN_{dijet}/dx_{j})$, as function of $x_{j}$ for the $10-60$, $60-120$, $120-185$, $185-250$ and $250-400$ multiplicity ranges with leading and subleading jets at backward and midrapidity regions, respectively.

The ratio of unfolded dijet balance distribution to the lower multiplicity range, $10-60$, as function of $x_{j}$ for the $60-120$, $120-185$, $185-250$ and $250-400$ ranges with both jets at the midrapidity regions.

The ratio of unfolded dijet balance distribution to the lower multiplicity range, $10-60$, as function of $x_{j}$ for the $60-120$, $120-185$, $185-250$ and $250-400$ ranges with leading and subleading jets at midrapidity and forward regions, respectively.

The ratio of unfolded dijet balance distribution to the lower multiplicity range, $10-60$, as function of $x_{j}$ for the $60-120$, $120-185$, $185-250$ and $250-400$ ranges with leading and subleading jets at midrapidity and backward regions, respectively.

The ratio of unfolded dijet balance distribution to the lower multiplicity range, $10-60$, as function of $x_{j}$ for the $60-120$, $120-185$, $185-250$ and $250-400$ ranges with leading and subleading jets at forward and midrapidity regions, respectively.

The ratio of unfolded dijet balance distribution to the lower multiplicity range, $10-60$, as function of $x_{j}$ for the $60-120$, $120-185$, $185-250$ and $250-400$ ranges with leading and subleading jets at backward and midrapidity regions, respectively.

Mean xj ratio, $\langle x_{j} \rangle$, in the range $10-60$ as unfolded for different multiplicities, for different leading and subleading jet combinations for the midrapidity, forward, and backward regions

The reconstructed (raw) dijet balance distribution, $(1/N_{dijet})(dN_{dijet}/dx_{j})$, as function of $x_{j}$ for the $10-60$, $60-120$, $120-185$, $185-250$ and $250-400$ multiplicity ranges with both jets at the midrapidity regions.

The reconstructed (raw) dijet balance distribution, $(1/N_{dijet})(dN_{dijet}/dx_{j})$, as function of $x_{j}$ for the $10-60$, $60-120$, $120-185$, $185-250$ and $250-400$ multiplicity ranges with leading and subleading jets at midrapidity and forward regions, respectively.

The reconstructed (raw) dijet balance distribution, $(1/N_{dijet})(dN_{dijet}/dx_{j})$, as function of $x_{j}$ for the $10-60$, $60-120$, $120-185$, $185-250$ and $250-400$ multiplicity ranges with leading and subleading jets at midrapidity and backward regions, respectively.

The reconstructed (raw) dijet balance distribution, $(1/N_{dijet})(dN_{dijet}/dx_{j})$, as function of $x_{j}$ for the $10-60$, $60-120$, $120-185$, $185-250$ and $250-400$ multiplicity ranges with leading and subleading jets at forward and midrapidity regions, respectively.

The reconstructed (raw) dijet balance distribution, $(1/N_{dijet})(dN_{dijet}/dx_{j})$, as function of $x_{j}$ for the $10-60$, $60-120$, $120-185$, $185-250$ and $250-400$ multiplicity ranges with leading and subleading jets at backward and midrapidity regions, respectively.

The ratio of reconstructed (raw) dijet balance distribution to the lower multiplicity range, $10-60$, as function of $x_{j}$ for the $60-120$, $120-185$, $185-250$ and $250-400$ ranges with both jets at the midrapidity regions.

The ratio of reconstructed (raw) dijet balance distribution to the lower multiplicity range, $10-60$, as function of $x_{j}$ for the $60-120$, $120-185$, $185-250$ and $250-400$ ranges with leading and subleading jets at midrapidity and forward regions, respectively.

The ratio of reconstructed (raw) dijet balance distribution to the lower multiplicity range, $10-60$, as function of $x_{j}$ for the $60-120$, $120-185$, $185-250$ and $250-400$ ranges with leading and subleading jets at midrapidity and backward regions, respectively.

The ratio of reconstructed (raw) dijet balance distribution to the lower multiplicity range, $10-60$, as function of $x_{j}$ for the $60-120$, $120-185$, $185-250$ and $250-400$ ranges with leading and subleading jets at forward and midrapidity regions, respectively.

The ratio of reconstructed (raw) dijet balance distribution to the lower multiplicity range, $10-60$, as function of $x_{j}$ for the $60-120$, $120-185$, $185-250$ and $250-400$ ranges with leading and subleading jets at backward and midrapidity regions, respectively.

Mean xj ratio, $\langle x_{j} \rangle$, in the range $10-60$ as reconstructed (raw) for different multiplicities, for different leading and subleading jet combinations for the midrapidity, forward, and backward regions

The distributions of the variables used in the simultaneous fit for the SR. The black points with error bars represent the data and their statistical uncertainties, whereas the shaded band represents the predicted uncertainties. The bottom panel in each figure shows the ratio of the number of events observed in data to that of the total SM prediction. The last bin of each plot has been extended to include the overflow contribution.

Expected and observed 95% upper limits on the product of the cross section and branching fraction$\sigma(\mathrm{pp} \ ightarrow W\mathrm{a})\mathcal{B}(W ightarrow \ell^{+} v_{\ell})\mathcal{B}(\mathrm{a} \rightarrow Z\gamma)\mathcal{B}(Z \rightarrow \ell^{+} \ell^{-})$ s a function of the ALP mass from 110 to 400 GeV

Expected and observed 95% upper limits on the photophobic ALP model parameter $1/f_{\mathrm{a}}$ as a function of ALP mass reinterpreted from $1/f_{\mathrm{a}}=2~\mathrm{TeV}^{-1}$

Distributions of the number of hits in the cluster (Nhits) for the DT category in the signal region (SR). The last histogram bin contains all overflow events.

Distributions of the number of hits in the cluster (Nhits) for the DT category in the out-of-time (OOT) region. The last histogram bin contains all overflow events.

Distributions of the number of hits in the cluster (Nhits) for the CSC category in the signal region (SR). The last histogram bin contains all overflow events.

Distributions of the number of hits in the cluster (Nhits) for the CSC category in the out-of-time (OOT) region. The last histogram bin contains all overflow events.

Distributions of the number of hits in the cluster (Nhits) for the DT category in the out-of-time (OOT) region. The last histogram bin contains all overflow events.

The 95% CL observed and expected upper limits on the VLL production cross section as a function of the VLL mass for the pseudoscalar mean proper decay length c$\tau$ = 0.025 m. The pseudoscalar mass is 2 GeV.

Distributions of the number of hits in the cluster (Nhits) for the CSC category in the out-of-time (OOT) region. The last histogram bin contains all overflow events.

The 95% CL observed and expected upper limits on the VLL production cross section as a function of the pseudoscalar mean proper decay length c$\tau$ for VLL Mass of 700 GeV. The pseudoscalar mass is 2 GeV.

The 95% CL observed and expected upper limits on the VLL production cross section as a function of the VLL mass for the pseudoscalar mean proper decay length c$\tau$ = 0.025 m. The pseudoscalar mass is 2 GeV.

The 95% CL observed upper limits on the VLL production cross section as a function of the VLL mass and the pseudoscalar mean proper decay length c$\tau$. The pseudoscalar mass is 2 GeV.

The 95% CL observed and expected upper limits on the VLL production cross section as a function of the pseudoscalar mean proper decay length c$\tau$ for VLL Mass of 700 GeV. The pseudoscalar mass is 2 GeV.

The 95% CL observed exclusion contour on the VLL production cross section as a function of the VLL mass and the pseudoscalar mean proper decay length c$\tau$. The pseudoscalar mass is 2 GeV.

The 95% CL observed upper limits on the VLL production cross section as a function of the VLL mass and the pseudoscalar mean proper decay length c$\tau$. The pseudoscalar mass is 2 GeV.

Selection efficiencies in the CSC category signal region (SR) for different signal hypothesis. The pseudoscalar mass is 2 GeV.

The 95% CL observed exclusion contour on the VLL production cross section as a function of the VLL mass and the pseudoscalar mean proper decay length c$\tau$. The pseudoscalar mass is 2 GeV.

Selection efficiencies in the DT category signal region (SR) for different signal hypothesis. The pseudoscalar mass is 2 GeV.

Selection efficiencies in the CSC category signal region (SR) for different signal hypothesis. The pseudoscalar mass is 2 GeV.

Selection efficiencies in the DT category signal region (SR) for different signal hypothesis. The pseudoscalar mass is 2 GeV.

The cluster reconstruction efficiency, including both DT and CSC clusters, as a function of the simulated r and |z| decay positions of the pseudoscalar into photons in events with MET > 200 GeV, for a VLL mass of 300 GeV and a pseudoscalar mass of 2 GeV, and a range of ctau values uniformly distributed between 0.01 and 0.1 m.

The cluster reconstruction efficiency, including both DT and CSC clusters, as a function of the simulated r and |z| decay positions of the pseudoscalar into photons in events with MET > 200 GeV, for a VLL mass of 500 GeV and a pseudoscalar mass of 2 GeV, and a range of ctau values uniformly distributed between 0.01 and 0.1 m.

The unfolded jet axis decorrelation distribution,$\frac{1}{N} \frac{dN}{d\Delta j}$, as a function of $\Delta j$ for the $0-10\%$, $10-30\%$, $30-50\%$, and $50-80\%$ centrality bins in the $230 < p_{\mathrm{T}} < 300$ GeV interval.

Expected and observed upper limits for the b-quark-associated Higgs boson production cross section times branching fraction of the decay into a b quark pair at 95% CL as functions of $m_\phi$ for the 2018 FH category. The vertical dashed lines indicate the boundaries of usage of the different fit ranges, as reflected in the rightmost column of Table 2.

Expected and observed upper limits for the b-quark-associated Higgs boson production cross section times branching fraction of the decay into a b quark pair at 95% CL as functions of $m_\phi$, corresponding to the Run 2 combination. The vertical dashed line separates the mass range where only the 2017 SL category contributes on its left, from the region where also the 2017 FH and 2018 FH categories contribute on its right. The expected limits from the 2017 SL, 2017 FH, and 2018 FH datasets as well as from the previously published result based on the 2016 dataset are also shown as colored lines.

Interpretation in the $M_h^{125}$ scenario of the MSSM: observed and expected upper limits at 95% CL on the parameter tan(beta) as functions of the mass of the CP-odd boson, $m_{A}$. The higgsino mass parameter has been set to $\mu = +1$ TeV. The hashed area indicates the parameter region in which the mass of the lightest MSSM Higgs boson does not coincide with 125 GeV within a margin of 3 GeV.

Interpretation in the $M_h^{125}$ scenario of the MSSM: observed and expected upper limits at 95% CL on the parameter tan(beta) as functions of the mass of the CP-odd boson, $m_{A}$. The higgsino mass parameter has been set to $\mu = -1$ TeV. The hashed area indicates the parameter region in which the mass of the lightest MSSM Higgs boson does not coincide with 125 GeV within a margin of 3 GeV.

Interpretation in the $M_h^{125}$ scenario of the MSSM: observed and expected upper limits at 95% CL on the parameter tan(beta) as functions of the mass of the CP-odd boson, $m_{A}$. The higgsino mass parameter has been set to $\mu = -2$ TeV. The hashed area indicates the parameter region in which the mass of the lightest MSSM Higgs boson does not coincide with 125 GeV within a margin of 3 GeV.

Interpretation in the $M_h^{125}$ scenario of the MSSM: observed and expected upper limits at 95% CL on the parameter tan(beta) as functions of the mass of the CP-odd boson, $m_{A}$. The higgsino mass parameter has been set to $\mu = -3$ TeV. The hashed area indicates the parameter region in which the mass of the lightest MSSM Higgs boson does not coincide with 125 GeV within a margin of 3 GeV.

Interpretation in the $m_h^{mod+}$ scenario of the MSSM: observed and expected upper limits at 95% CL on the parameter tan(beta) as functions of the mass of the CP-odd boson, $m_{A}$. The hashed area indicates the parameter region in which the mass of the lightest MSSM Higgs boson does not coincide with 125 GeV within a margin of 3 GeV.

Interpretation in the hMSSM scenario of the MSSM: observed and expected upper limits at 95% CL on the parameter tan(beta) as functions of the mass of the CP-odd boson, $m_{A}$.

Interpretation in 2HDM scenarios: observed and expected upper limits at 95% CL on the parameter tan(beta) as a function of $m_{A}$ for cos(beta-alpha) = 0.1, for the 2HDM $\it Type-II$ scenario.

Interpretation in 2HDM scenarios: observed and expected upper limits at 95% CL on the parameter tan(beta) as functions of cos(beta-alpha) for masses of $m_{A} = m_{H} = 300$ GeV, for the 2HDM $\it Type-II$ scenario.

Interpretation in 2HDM scenarios: observed and expected upper limits at 95% CL on the parameter tan(beta) as a function of $m_{A}$ for cos(beta-alpha) = 0.1, for the 2HDM $\it Flipped$ scenario.

Interpretation in 2HDM scenarios: observed and expected upper limits at 95% CL on the parameter tan(beta) as functions of cos(beta-alpha) for masses of $m_{A} = m_{H} = 300$ GeV, for the 2HDM $\it Flipped$ scenario.

Interpretation in the 2HDM flipped scenario: observed and expected upper limits at 95% CL on the parameter tan(beta) as functions of cos(beta-alpha) for mass of $m_{A} = m_{H} = 140$ GeV.

Interpretation in the 2HDM flipped scenario: observed and expected upper limits at 95% CL on the parameter tan(beta) as functions of cos(beta-alpha) for mass of $m_{A} = m_{H} = 600$ GeV.

Interpretation in the 2HDM flipped scenario: observed and expected upper limits at 95% CL on the parameter tan(beta) as functions of cos(beta-alpha) for mass of $m_{A} = m_{H} = 900$ GeV.

Interpretation in the 2HDM flipped scenario: observed and expected upper limits at 95% CL on the parameter tan(beta) as functions of cos(beta-alpha) for mass of $m_{A} = m_{H} = 1200$ GeV.

Simulated signal shapes for three representative values of the Higgs boson mass $m_\phi$ in the 2017 SL channel.

Simulated signal shapes for three representative values of the Higgs boson mass $m_\phi$ in the 2017 FH channel.

Simulated signal shapes for three representative values of the Higgs boson mass $m_\phi$ in the 2018 FH channel.

Background-only fits to the M12 distribution in each fit range of the 2017 analysis in the SL category

Background-only fits to the M12 distribution in each fit range of the 2017 analysis in the SL category

Background-only fits to the M12 distribution in each fit range of the 2017 analysis in the SL category

Background-only fits to the M12 distribution in each fit range of the 2017 analysis in the FH category

Background-only fits to the M12 distribution in each fit range of the 2017 analysis in the FH category

Background-only fits to the M12 distribution in each fit range of the 2017 analysis in the FH category

Background-only fits to the M12 distribution in each fit range of the 2017 analysis in the FH category

Background-only fits to the M12 distribution in each fit range of the 2018 analysis in the FH category

Background-only fits to the M12 distribution in each fit range of the 2018 analysis in the FH category

Background-only fits to the M12 distribution in each fit range of the 2018 analysis in the FH category

Background-only fits to the M12 distribution in each fit range of the 2018 analysis in the FH category

Suppl. Fig. 7. The reconstructed shower angle for all single photon events. The individual signal and background event type categories added together form the unconstrained prediction.

Suppl. Fig. 7. The constrained covariance matrix for the reconstructed shower angle for all single-photon events. The matrix shows uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. Data statistical uncertainties are not included. An example of how to add Pearson data statistical uncertainties can be found in the example code repository.

Suppl. Fig. 7. The unconstrained covariance matrix for reconstructed shower angle for all single-photon events. The matrix shows uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. Data statistical uncertainties are not included. An example of how to add Pearson data statistical uncertainties can be found in the example code repository.

Fig. 3. The reconstructed number of protons, with a proton KE energy threshold of 35 MeV, for all single-photon events. The individual signal and background event type categories added together form the unconstrained prediction.

Fig. 4, Suppl. Fig. 8. The reconstructed shower energy for zero proton events binned from 0 to 600 MeV. The individual signal and background event type categories added together form the unconstrained prediction.

Fig. 4. The constrained covariance matrix for the reconstructed shower energy for zero proton events binned from 0 to 600 MeV. The matrix shows uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. Data statistical uncertainties are not included. An example of how to add Pearson data statistical uncertainties can be found in the example code repository.

Fig. 4. The unconstrained covariance matrix for reconstructed shower energy for zero proton events binned from 0 to 600 MeV. The matrix shows uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. Data statistical uncertainties are not included. An example of how to add Pearson data statistical uncertainties can be found in the example code repository.

Fig. 6. The reconstructed shower energy for zero proton events binned from 150 to 1250 MeV, with LEE prediction. The individual signal and background event type categories added together form the unconstrained prediction. The "LEE" category is the unfolded MiniBooNE LEE model prediction scaled under the neutrino-target nucleon interaction assumption.

Fig. 6. The constrained covariance matrix for the reconstructed shower energy for zero proton events binned from 150 to 1250 MeV. Both with and without the LEE model added. The matrix shows uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. Data statistical uncertainties are not included. An example of how to add Pearson data statistical uncertainties can be found in the example code repository.

Fig. 6. The unconstrained covariance matrix for reconstructed shower energy for zero proton events binned from 150 to 1250 MeV. Both with and without the LEE model added. The matrix shows uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. Data statistical uncertainties are not included. An example of how to add Pearson data statistical uncertainties can be found in the example code repository.

Suppl. Fig. 10. The reconstructed shower backwards projected distance for zero proton events. The individual signal and background event type categories added together form the unconstrained prediction.

Suppl. Fig. 9. The reconstructed shower angle for zero proton events. Includes LEE model prediction. The individual signal and background event type categories added together form the unconstrained prediction. The "LEE" category is the unfolded MiniBooNE LEE model prediction scaled under the neutrino-target nucleon interaction assumption.

Suppl. Fig. 9. The constrained covariance matrix for the reconstructed shower angle for zero proton events. The matrix shows uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. Data statistical uncertainties are not included. An example of how to add Pearson data statistical uncertainties can be found in the example code repository.

Suppl. Fig. 9. The unconstrained covariance matrix for reconstructed shower angle for zero proton events. The matrix shows uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. Data statistical uncertainties are not included. An example of how to add Pearson data statistical uncertainties can be found in the example code repository.

1$\gamma$Xp shower energy and angle selection efficiencies for true 1$\gamma$Xp events. NaN values indicate a "divide by zero" case where zero events were present in the bin before any selection was applied. Energy and Angle values represent bin lower edges.

1$\gamma$0p shower energy and angle selection efficiencies for true single-photon events with no other true particles of any energy. NaN values indicate a "divide by zero" case where zero events were present in the bin before any selection was applied. Energy and Angle values represent bin lower edges.

Covariance matrix showing uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. Pearson data statistical uncertainties have been included, and include small correlations due to events which can be selected by both WC and Pandora. The first four bins are the WC $1\gamma Np$, WC $1\gamma 0p$, Pandora $1\gamma 1p$, and Pandora $1\gamma 0p$ channels, and the next four sets of 16 bins are the NC $\pi^0 Np$, NC $\pi^0 0p$, $\nu_\mu$CC $Np$, and $\nu_\mu$CC $0p$ channels. This corresponds to Fig. 1 of the paper and Fig. 6 of the Supplemental Material.

Constrained WC $1\gamma Np$ energy distribution. There are 6 bins from 0 to 600 MeV of reconstructed shower energy, with an additional overflow bin. Constrained systematic uncertainties on the predictions are illustrated, and a more detailed covariance matrix is included in the Constrained Energy Distributions Covariance Matrix tab. This corresponds to Fig. 2 of the paper.

Constrained WC $1\gamma 0p$ energy distribution. There are 14 bins from 0 to 700 MeV of reconstructed shower energy, with an additional overflow bin. Constrained systematic uncertainties on the predictions are illustrated, and a more detailed covariance matrix is included in the Constrained Energy Distributions Covariance Matrix tab. This corresponds to Fig. 2 of the paper.

Constrained Pandora $1\gamma 1p$ energy distribution. There are 6 bins from 0 to 600 MeV of reconstructed shower energy, with an additional overflow bin. Constrained systematic uncertainties on the predictions are illustrated, and a more detailed covariance matrix is included in the Constrained Energy Distributions Covariance Matrix tab. This corresponds to Fig. 2 of the paper.

Constrained Pandora $1\gamma 0p$ energy distribution. There are 14 bins from 0 to 700 MeV of reconstructed shower energy, with an additional overflow bin. Constrained systematic uncertainties on the predictions are illustrated, and a more detailed covariance matrix is included in the Constrained Energy Distributions Covariance Matrix tab. This corresponds to Fig. 2 of the paper.

Constrained covariance matrix showing constrained uncertainties and correlations between bins due to flux uncertainties, cross-section uncertainties, hadron reinteraction uncertainties, detector systematic uncertainties, Monte-Carlo statistical uncertainties, and dirt (outside cryostat) uncertainties. Pearson data statistical uncertainties have been included, and include small correlations due to events which can be selected by both WC and Pandora. The first seven bins are the WC $1\gamma Np$ reconstructed shower energy from 0-600 MeV with an overflow bin, the next 15 bins are the WC $1\gamma 0p$ reconstructed shower energy from 0-700 MeV with an overflow bin, the next seven bins are the Pandora $1\gamma 1p$ reconstructed shower energy from 0-600 MeV with an overflow bin, and the last 15 bins are the Pandora $1\gamma 0p$ reconstructed shower energy from 0-700 MeV with an overflow bin. This corresponds to Fig. 2 of the paper.

2D efficiency matrix showing the efficiency of the WC $1\gamma Np$ selection with respect to all true NC Delta Radiative Decay events which interact in the fiducial volume. The efficiency is shown as a function of true photon energy and angle. There are 10 bins from -1 to 1 in true photon $\cos \theta$ and 15 bins from 0 to 1500 MeV in true photon energy. NaN values indicate a "divide by zero" case where zero events were present in the bin before any selection was applied. This corresponds to Fig. 9 of the Supplemental Material.

2D efficiency matrix showing the efficiency of the WC $1\gamma 0p$ selection with respect to all true NC Delta Radiative Decay events which interact in the fiducial volume. The efficiency is shown as a function of true photon energy and angle. There are 10 bins from -1 to 1 in true photon $\cos \theta$ and 30 bins from 0 to 1500 MeV in true photon energy. NaN values indicate a "divide by zero" case where zero events were present in the bin before any selection was applied. This corresponds to Fig. 9 of the Supplemental Material.

2D efficiency matrix showing the efficiency of the Pandora $1\gamma 1p$ selection with respect to all true NC Delta Radiative Decay events which interact in the fiducial volume. The efficiency is shown as a function of true photon energy and angle. There are 10 bins from -1 to 1 in true photon $\cos \theta$ and 15 bins from 0 to 1500 MeV in true photon energy, with lower bin edges indicated in the table. NaN values indicate a "divide by zero" case where zero events were present in the bin before any selection was applied. This corresponds to Fig. 9 of the Supplemental Material.

2D efficiency matrix showing the efficiency of the Pandora $1\gamma 0p$ selection with respect to all true NC Delta Radiative Decay events which interact in the fiducial volume. The efficiency is shown as a function of true photon energy and angle. There are 10 bins from -1 to 1 in true photon $\cos \theta$ and 30 bins from 0 to 1500 MeV in true photon energy, with lower bin edges indicated in the table. NaN values indicate a "divide by zero" case where zero events were present in the bin before any selection was applied. This corresponds to Fig. 9 of the Supplemental Material.

2D efficiency matrix showing the efficiency of the WC $1\gamma 0p$ selection with respect to all true zero-primary-final-state-proton NC Delta Radiative Decay events which interact in the fiducial volume. The efficiency is shown as a function of true photon energy and angle. There are 10 bins from -1 to 1 in true photon $\cos \theta$ and 30 bins from 0 to 1500 MeV in true photon energy, with lower bin edges indicated in the table. NaN values indicate a "divide by zero" case where zero events were present in the bin before any selection was applied.

2D efficiency matrix showing the efficiency of the Pandora $1\gamma 0p$ selection with respect to all true zero-primary-final-state-proton NC Delta Radiative Decay events which interact in the fiducial volume. The efficiency is shown as a function of true photon energy and angle. There are 10 bins from -1 to 1 in true photon $\cos \theta$ and 30 bins from 0 to 1500 MeV in true photon energy, with lower bin edges indicated in the table. NaN values indicate a "divide by zero" case where zero events were present in the bin before any selection was applied.

Measured inclusive fiducial H->ZZ->4l cross section as a function of the center-of-mass energy.

Postfit reconstructed distributions of the Higgs boson transverse momentum.

Postfit reconstructed distributions of the Higgs boson rapidity.

Higgs fiducial cross section in bins of pT of the Higgs boson.

Higgs fiducial cross section in bins of absolute value of rapidity of the Higgs boson.

Correlation matrix of fit in different final states

Correlation matrix of fit in pT(4l) bins

Correlation matrix of fit in abs(y(4l)) bins