CMS-PAS-HIG-19-011

CMS-PAS-HIG-19-011
Measurement of the ttH and tH production rates in the H $\to\mathrm{b\overline{b}}$ decay channel with 138 fb $^{-1}$ of proton-proton collision data at $\sqrt{s}=$ 13 TeV
CMS Collaboration
22 August 2023

Abstract: An analysis of the production of a Higgs boson (H) in association with a top quark-antiquark pair (ttH) or a single top quark (tH) in the channel where the Higgs boson decays into a bottom quark-antiquark pair (H $\to\mathrm{b\overline{b}}$ ) is presented. The analysis utilises proton-proton collision data collected at the CERN LHC with the CMS experiment at $\sqrt{s}=$ 13 TeV between 2016 and 2018, which correspond to an integrated luminosity of 138 fb $^{-1}$ . All three decay channels of the $\mathrm{t\overline{t}}$ system are considered. Various signal interpretations are performed. The observed ttH production rate relative to the standard model (SM) expectation is 0.33 $\pm$ 0.26 $=$ 0.33 $\pm$ 0.17 (stat) $\pm$ 0.21 (syst). Additionally, the ttH production rate is determined in intervals of Higgs boson $p_{\mathrm{T}}$ . An upper limit at 95% confidence level on the tH production rate of 14.6 times the SM expectation is observed, with an expectation of 19.3 $^{+9.2}_{-6.0}$ . Finally, constraints are derived on the strength and structure of the coupling between the Higgs boson and the top quark from simultaneous extraction of the ttH and tH production rates.
Links: CDS record (PDF) ; CADI line (restricted) ; These preliminary results are superseded in this paper, Submitted to JHEP. The superseded preliminary plots can be found here.

Figures & Tables	Summary	Additional Figures & Tables	References	CMS Publications

Figures
png pdf	Figure 1: Representative leading-order Feynman diagrams for the associated production of a Higgs boson and a top quark-antiquark pair (left) and for the associated production of a single top quark and a Higgs boson in the $t$ channel, where the Higgs boson couples to the top quark (centre) or the W boson (right).
png pdf	Figure 1-a: Representative leading-order Feynman diagrams for the associated production of a Higgs boson and a top quark-antiquark pair (left) and for the associated production of a single top quark and a Higgs boson in the $t$ channel, where the Higgs boson couples to the top quark (centre) or the W boson (right).
png pdf	Figure 1-b: Representative leading-order Feynman diagrams for the associated production of a Higgs boson and a top quark-antiquark pair (left) and for the associated production of a single top quark and a Higgs boson in the $t$ channel, where the Higgs boson couples to the top quark (centre) or the W boson (right).
png pdf	Figure 1-c: Representative leading-order Feynman diagrams for the associated production of a Higgs boson and a top quark-antiquark pair (left) and for the associated production of a single top quark and a Higgs boson in the $t$ channel, where the Higgs boson couples to the top quark (centre) or the W boson (right).
png pdf	Figure 2: Jet multiplicity distribution in the FH (upper left), SL (upper right), and DL (lower) channels, after the baseline selection and prior to the fit to the data. Here, the QCD background prediction is taken from simulation. The expected ttH signal contribution, scaled as indicated in the legend for better visibility, is also overlayed (line). The uncertainty band represents the total uncertainty. The last bins include overflow events.
png pdf	Figure 2-a: Jet multiplicity distribution in the FH (upper left), SL (upper right), and DL (lower) channels, after the baseline selection and prior to the fit to the data. Here, the QCD background prediction is taken from simulation. The expected ttH signal contribution, scaled as indicated in the legend for better visibility, is also overlayed (line). The uncertainty band represents the total uncertainty. The last bins include overflow events.
png pdf	Figure 2-b: Jet multiplicity distribution in the FH (upper left), SL (upper right), and DL (lower) channels, after the baseline selection and prior to the fit to the data. Here, the QCD background prediction is taken from simulation. The expected ttH signal contribution, scaled as indicated in the legend for better visibility, is also overlayed (line). The uncertainty band represents the total uncertainty. The last bins include overflow events.
png pdf	Figure 2-c: Jet multiplicity distribution in the FH (upper left), SL (upper right), and DL (lower) channels, after the baseline selection and prior to the fit to the data. Here, the QCD background prediction is taken from simulation. The expected ttH signal contribution, scaled as indicated in the legend for better visibility, is also overlayed (line). The uncertainty band represents the total uncertainty. The last bins include overflow events.
png pdf	Figure 3: Average $\Delta\eta$ between any two b-tagged jets (upper), MEM discriminant output (middle), and $p_{\mathrm{T}}$ of the Higgs boson candidate identified with reconstruction BDT (lower) for events passing the baseline selection requirements and additionally $\geq$ 6 jets in the SL channel prefit (left) and with the postfit background model (right) obtained from the fit to data described in Section 10. In the prefit case, the ttH signal contribution, scaled by a factor 25 for better visibility, is also overlayed (line). Where applicable, the last bins include overflow events.
png pdf	Figure 3-a: Average $\Delta\eta$ between any two b-tagged jets (upper), MEM discriminant output (middle), and $p_{\mathrm{T}}$ of the Higgs boson candidate identified with reconstruction BDT (lower) for events passing the baseline selection requirements and additionally $\geq$ 6 jets in the SL channel prefit (left) and with the postfit background model (right) obtained from the fit to data described in Section 10. In the prefit case, the ttH signal contribution, scaled by a factor 25 for better visibility, is also overlayed (line). Where applicable, the last bins include overflow events.
png pdf	Figure 3-b: Average $\Delta\eta$ between any two b-tagged jets (upper), MEM discriminant output (middle), and $p_{\mathrm{T}}$ of the Higgs boson candidate identified with reconstruction BDT (lower) for events passing the baseline selection requirements and additionally $\geq$ 6 jets in the SL channel prefit (left) and with the postfit background model (right) obtained from the fit to data described in Section 10. In the prefit case, the ttH signal contribution, scaled by a factor 25 for better visibility, is also overlayed (line). Where applicable, the last bins include overflow events.
png pdf	Figure 3-c: Average $\Delta\eta$ between any two b-tagged jets (upper), MEM discriminant output (middle), and $p_{\mathrm{T}}$ of the Higgs boson candidate identified with reconstruction BDT (lower) for events passing the baseline selection requirements and additionally $\geq$ 6 jets in the SL channel prefit (left) and with the postfit background model (right) obtained from the fit to data described in Section 10. In the prefit case, the ttH signal contribution, scaled by a factor 25 for better visibility, is also overlayed (line). Where applicable, the last bins include overflow events.
png pdf	Figure 3-d: Average $\Delta\eta$ between any two b-tagged jets (upper), MEM discriminant output (middle), and $p_{\mathrm{T}}$ of the Higgs boson candidate identified with reconstruction BDT (lower) for events passing the baseline selection requirements and additionally $\geq$ 6 jets in the SL channel prefit (left) and with the postfit background model (right) obtained from the fit to data described in Section 10. In the prefit case, the ttH signal contribution, scaled by a factor 25 for better visibility, is also overlayed (line). Where applicable, the last bins include overflow events.
png pdf	Figure 3-e: Average $\Delta\eta$ between any two b-tagged jets (upper), MEM discriminant output (middle), and $p_{\mathrm{T}}$ of the Higgs boson candidate identified with reconstruction BDT (lower) for events passing the baseline selection requirements and additionally $\geq$ 6 jets in the SL channel prefit (left) and with the postfit background model (right) obtained from the fit to data described in Section 10. In the prefit case, the ttH signal contribution, scaled by a factor 25 for better visibility, is also overlayed (line). Where applicable, the last bins include overflow events.
png pdf	Figure 3-f: Average $\Delta\eta$ between any two b-tagged jets (upper), MEM discriminant output (middle), and $p_{\mathrm{T}}$ of the Higgs boson candidate identified with reconstruction BDT (lower) for events passing the baseline selection requirements and additionally $\geq$ 6 jets in the SL channel prefit (left) and with the postfit background model (right) obtained from the fit to data described in Section 10. In the prefit case, the ttH signal contribution, scaled by a factor 25 for better visibility, is also overlayed (line). Where applicable, the last bins include overflow events.
png pdf	Figure 4: Minimum $\Delta R$ between any two b-tagged jets (upper), MEM discriminant output (middle), and $p_{\mathrm{T}}$ of the Higgs boson candidate identified as pair of b-tagged jets closest in $\Delta R$ (lower) for events passing the baseline selection requirements and additionally $\geq$ 4 jets in the DL channel prefit (left) and with the postfit background model (right) obtained from the fit to data described in Section 10. In the prefit case, the ttH signal contribution, scaled by a factor 50 for better visibility, is also overlayed (line). Where applicable, the last bins include overflow events.
png pdf	Figure 4-a: Minimum $\Delta R$ between any two b-tagged jets (upper), MEM discriminant output (middle), and $p_{\mathrm{T}}$ of the Higgs boson candidate identified as pair of b-tagged jets closest in $\Delta R$ (lower) for events passing the baseline selection requirements and additionally $\geq$ 4 jets in the DL channel prefit (left) and with the postfit background model (right) obtained from the fit to data described in Section 10. In the prefit case, the ttH signal contribution, scaled by a factor 50 for better visibility, is also overlayed (line). Where applicable, the last bins include overflow events.
png pdf	Figure 4-b: Minimum $\Delta R$ between any two b-tagged jets (upper), MEM discriminant output (middle), and $p_{\mathrm{T}}$ of the Higgs boson candidate identified as pair of b-tagged jets closest in $\Delta R$ (lower) for events passing the baseline selection requirements and additionally $\geq$ 4 jets in the DL channel prefit (left) and with the postfit background model (right) obtained from the fit to data described in Section 10. In the prefit case, the ttH signal contribution, scaled by a factor 50 for better visibility, is also overlayed (line). Where applicable, the last bins include overflow events.
png pdf	Figure 4-c: Minimum $\Delta R$ between any two b-tagged jets (upper), MEM discriminant output (middle), and $p_{\mathrm{T}}$ of the Higgs boson candidate identified as pair of b-tagged jets closest in $\Delta R$ (lower) for events passing the baseline selection requirements and additionally $\geq$ 4 jets in the DL channel prefit (left) and with the postfit background model (right) obtained from the fit to data described in Section 10. In the prefit case, the ttH signal contribution, scaled by a factor 50 for better visibility, is also overlayed (line). Where applicable, the last bins include overflow events.
png pdf	Figure 4-d: Minimum $\Delta R$ between any two b-tagged jets (upper), MEM discriminant output (middle), and $p_{\mathrm{T}}$ of the Higgs boson candidate identified as pair of b-tagged jets closest in $\Delta R$ (lower) for events passing the baseline selection requirements and additionally $\geq$ 4 jets in the DL channel prefit (left) and with the postfit background model (right) obtained from the fit to data described in Section 10. In the prefit case, the ttH signal contribution, scaled by a factor 50 for better visibility, is also overlayed (line). Where applicable, the last bins include overflow events.
png pdf	Figure 4-e: Minimum $\Delta R$ between any two b-tagged jets (upper), MEM discriminant output (middle), and $p_{\mathrm{T}}$ of the Higgs boson candidate identified as pair of b-tagged jets closest in $\Delta R$ (lower) for events passing the baseline selection requirements and additionally $\geq$ 4 jets in the DL channel prefit (left) and with the postfit background model (right) obtained from the fit to data described in Section 10. In the prefit case, the ttH signal contribution, scaled by a factor 50 for better visibility, is also overlayed (line). Where applicable, the last bins include overflow events.
png pdf	Figure 4-f: Minimum $\Delta R$ between any two b-tagged jets (upper), MEM discriminant output (middle), and $p_{\mathrm{T}}$ of the Higgs boson candidate identified as pair of b-tagged jets closest in $\Delta R$ (lower) for events passing the baseline selection requirements and additionally $\geq$ 4 jets in the DL channel prefit (left) and with the postfit background model (right) obtained from the fit to data described in Section 10. In the prefit case, the ttH signal contribution, scaled by a factor 50 for better visibility, is also overlayed (line). Where applicable, the last bins include overflow events.
png pdf	Figure 5: Illustration of the analysis strategy for the inclusive ttH and tH signal-strength modifier and coupling and CP measurements (upper) and for the ttH STXS measurement (lower). The procedure is applied separately for the three years of data taking.
png pdf	Figure 5-a: Illustration of the analysis strategy for the inclusive ttH and tH signal-strength modifier and coupling and CP measurements (upper) and for the ttH STXS measurement (lower). The procedure is applied separately for the three years of data taking.
png pdf	Figure 5-b: Illustration of the analysis strategy for the inclusive ttH and tH signal-strength modifier and coupling and CP measurements (upper) and for the ttH STXS measurement (lower). The procedure is applied separately for the three years of data taking.
png pdf	Figure 6: Categorisation efficiency of the ttH signal events in the STXS analysis in the different categories of the FH channel (upper row, middle row left), the SL channel (middle row right, lower row left), and the DL channel (lower row right).
png pdf	Figure 6-a: Categorisation efficiency of the ttH signal events in the STXS analysis in the different categories of the FH channel (upper row, middle row left), the SL channel (middle row right, lower row left), and the DL channel (lower row right).
png pdf	Figure 6-b: Categorisation efficiency of the ttH signal events in the STXS analysis in the different categories of the FH channel (upper row, middle row left), the SL channel (middle row right, lower row left), and the DL channel (lower row right).
png pdf	Figure 6-c: Categorisation efficiency of the ttH signal events in the STXS analysis in the different categories of the FH channel (upper row, middle row left), the SL channel (middle row right, lower row left), and the DL channel (lower row right).
png pdf	Figure 6-d: Categorisation efficiency of the ttH signal events in the STXS analysis in the different categories of the FH channel (upper row, middle row left), the SL channel (middle row right, lower row left), and the DL channel (lower row right).
png pdf	Figure 6-e: Categorisation efficiency of the ttH signal events in the STXS analysis in the different categories of the FH channel (upper row, middle row left), the SL channel (middle row right, lower row left), and the DL channel (lower row right).
png pdf	Figure 6-f: Categorisation efficiency of the ttH signal events in the STXS analysis in the different categories of the FH channel (upper row, middle row left), the SL channel (middle row right, lower row left), and the DL channel (lower row right).
png pdf	Figure 7: Observed (points) and postfit expected (filled histograms) yields in each discriminant (category yield, ANN score, or ratio of ANN scores) bin for the 2016 (upper), 2017 (middle), and 2018 (lower) data-taking periods. The uncertainty bands include the total uncertainty of the fit model. The lower pads show the ratio of the data to the background (points) and of the postfit expected signal+background to the background-only contribution (line).
png pdf	Figure 7-a: Observed (points) and postfit expected (filled histograms) yields in each discriminant (category yield, ANN score, or ratio of ANN scores) bin for the 2016 (upper), 2017 (middle), and 2018 (lower) data-taking periods. The uncertainty bands include the total uncertainty of the fit model. The lower pads show the ratio of the data to the background (points) and of the postfit expected signal+background to the background-only contribution (line).
png pdf	Figure 7-b: Observed (points) and postfit expected (filled histograms) yields in each discriminant (category yield, ANN score, or ratio of ANN scores) bin for the 2016 (upper), 2017 (middle), and 2018 (lower) data-taking periods. The uncertainty bands include the total uncertainty of the fit model. The lower pads show the ratio of the data to the background (points) and of the postfit expected signal+background to the background-only contribution (line).
png pdf	Figure 7-c: Observed (points) and postfit expected (filled histograms) yields in each discriminant (category yield, ANN score, or ratio of ANN scores) bin for the 2016 (upper), 2017 (middle), and 2018 (lower) data-taking periods. The uncertainty bands include the total uncertainty of the fit model. The lower pads show the ratio of the data to the background (points) and of the postfit expected signal+background to the background-only contribution (line).
png pdf	Figure 8: Best-fit results of the ttH signal-strength modifier $\mu_{{\mathrm{t}\overline{\mathrm{t}}} \mathrm{H}}$ in each channel (upper three rows), in each year (middle three rows), and in the combination of all channels and years (lower row). Uncertainties are correlated between the channels and years.
png pdf	Figure 9: Observed likelihood-ratio test statistic (blue shading) as a function of the ttH signal-strength modifier $\mu_{{\mathrm{t}\overline{\mathrm{t}}} \mathrm{H}}$ and the ${\mathrm{t}\overline{\mathrm{t}}} \text{B}$ background normalisation, together with the observed (blue) and SM expected (black) best-fit points (cross and diamond markers) as well as the 68% (solid lines) and 95% (dashed lines) CL regions. The ${\mathrm{t}\overline{\mathrm{t}}} \text{C}$ background normalisation and all other nuisance parameters are profiled such that the likelihood attains its minimum at each point in the plane.
png pdf	Figure 10: Postfit values of the nuisance parameters (black markers), shown as the difference of their best-fit values, $\hat{\theta}$ , and prefit values, $\theta_{0}$ , relative to the prefit uncertainties $\Delta\theta$ . The impact $\Delta\hat{\mu}$ of the nuisance parameters on the signal strength $\mu_{{\mathrm{t}\overline{\mathrm{t}}} \mathrm{H}}$ is computed as the difference of the nominal best fit value of $\mu$ and the best fit value obtained when fixing the nuisance parameter under scrutiny to its best fit value $\hat{\theta}$ plus/minus its postfit uncertainty (coloured areas). The nuisance parameters are ordered by their impact, and only the 20 highest ranked parameters are shown.
png pdf	Figure 11: Observed (points) and postfit expected (filled histograms) yields in each STXS analysis discriminant bin in the signal regions of the SL and DL channels for the 2016 (upper), 2017 (middle), and 2018 (lower) data-taking periods. The fitted signal distributions (lines labelled ttH 1 to 5) in each Higgs boson $p_{\mathrm{T}}$ bin are shown in the middle pads. The lower pads show the ratio of the data to the background (points) and of the postfit expected total signal+background to the background-only contribution (line). The uncertainty bands include the total uncertainty of the fit model.
png pdf	Figure 11-a: Observed (points) and postfit expected (filled histograms) yields in each STXS analysis discriminant bin in the signal regions of the SL and DL channels for the 2016 (upper), 2017 (middle), and 2018 (lower) data-taking periods. The fitted signal distributions (lines labelled ttH 1 to 5) in each Higgs boson $p_{\mathrm{T}}$ bin are shown in the middle pads. The lower pads show the ratio of the data to the background (points) and of the postfit expected total signal+background to the background-only contribution (line). The uncertainty bands include the total uncertainty of the fit model.
png pdf	Figure 11-b: Observed (points) and postfit expected (filled histograms) yields in each STXS analysis discriminant bin in the signal regions of the SL and DL channels for the 2016 (upper), 2017 (middle), and 2018 (lower) data-taking periods. The fitted signal distributions (lines labelled ttH 1 to 5) in each Higgs boson $p_{\mathrm{T}}$ bin are shown in the middle pads. The lower pads show the ratio of the data to the background (points) and of the postfit expected total signal+background to the background-only contribution (line). The uncertainty bands include the total uncertainty of the fit model.
png pdf	Figure 11-c: Observed (points) and postfit expected (filled histograms) yields in each STXS analysis discriminant bin in the signal regions of the SL and DL channels for the 2016 (upper), 2017 (middle), and 2018 (lower) data-taking periods. The fitted signal distributions (lines labelled ttH 1 to 5) in each Higgs boson $p_{\mathrm{T}}$ bin are shown in the middle pads. The lower pads show the ratio of the data to the background (points) and of the postfit expected total signal+background to the background-only contribution (line). The uncertainty bands include the total uncertainty of the fit model.
png pdf	Figure 12: Best-fit results of the ttH signal-strength modifiers $\mu_{{\mathrm{t}\overline{\mathrm{t}}} \mathrm{H}}$ in the different bins of Higgs boson $p_{\mathrm{T}}$ (left) and their correlations (right) of the STXS measurement.
png pdf	Figure 12-a: Best-fit results of the ttH signal-strength modifiers $\mu_{{\mathrm{t}\overline{\mathrm{t}}} \mathrm{H}}$ in the different bins of Higgs boson $p_{\mathrm{T}}$ (left) and their correlations (right) of the STXS measurement.
png pdf	Figure 12-b: Best-fit results of the ttH signal-strength modifiers $\mu_{{\mathrm{t}\overline{\mathrm{t}}} \mathrm{H}}$ in the different bins of Higgs boson $p_{\mathrm{T}}$ (left) and their correlations (right) of the STXS measurement.
png pdf	Figure 13: Observed (solid vertical line) and expected (dashed vertical line) upper 95% CL limit on the tH signal strength modifier $\mu_{\mathrm{t}\mathrm{H}}$ for different channels and years, where the uncertainties are uncorrelated between the channels and years, and in their combination. The green (yellow) areas indicate the one (two) standard deviation confidence intervals on the expected limit.
png pdf	Figure 14: Observed likelihood-ratio test statistic (blue shading) as a function of the ttH and tH signal strength modifiers $\mu_{{\mathrm{t}\overline{\mathrm{t}}} \mathrm{H}}$ and $\mu_{\mathrm{t}\mathrm{H}}$ , together with the observed (blue) and SM expected (black) best-fit points (cross and diamond markers) as well as the 68% (solid lines) and 95% (dashed lines) CL regions.
png pdf	Figure 15: Observed likelihood ratio test statistic (blue shading) as a function of $\kappa_{\mathrm{t}}$ and $\kappa_{\text{V}}$ , together with the observed (blue) and SM expected (black) best-fit points (cross and diamond markers) as well as the 68% (solid lines) and 95% (dashed lines) CL regions (left). The observed (solid blue line) and expected (dotted black line) values of the likelihood ratio for $\kappa_{\text{V}}=$ 1 are also shown (right), together with the 1 (green area) and 2 (yellow area) standard deviations confidence intervals.
png pdf	Figure 15-a: Observed likelihood ratio test statistic (blue shading) as a function of $\kappa_{\mathrm{t}}$ and $\kappa_{\text{V}}$ , together with the observed (blue) and SM expected (black) best-fit points (cross and diamond markers) as well as the 68% (solid lines) and 95% (dashed lines) CL regions (left). The observed (solid blue line) and expected (dotted black line) values of the likelihood ratio for $\kappa_{\text{V}}=$ 1 are also shown (right), together with the 1 (green area) and 2 (yellow area) standard deviations confidence intervals.
png pdf	Figure 15-b: Observed likelihood ratio test statistic (blue shading) as a function of $\kappa_{\mathrm{t}}$ and $\kappa_{\text{V}}$ , together with the observed (blue) and SM expected (black) best-fit points (cross and diamond markers) as well as the 68% (solid lines) and 95% (dashed lines) CL regions (left). The observed (solid blue line) and expected (dotted black line) values of the likelihood ratio for $\kappa_{\text{V}}=$ 1 are also shown (right), together with the 1 (green area) and 2 (yellow area) standard deviations confidence intervals.
png pdf	Figure 16: Observed likelihood ratio test statistic (blue shading) as a function of $\kappa_{\mathrm{t}}$ and $\tilde{\kappa}_{\mathrm{t}}$ , where $\kappa_{\text{V}}=$ 1, together with the observed (blue) and SM expected (black) best-fit points (cross and diamond markers) as well as the 68% (solid lines) and 95% (dashed lines) CL regions (left).
png pdf	Figure 17: The observed (solid blue line) and expected (dotted black line) likelihood ratio test statistic as a function of $f_{\text{CP}}$ (left) and $\cos\alpha$ (right), where $\kappa_{\text{V}}$ is 1 and $\kappa^{\prime}_{\mathrm{t}}=\sqrt{\tilde{\kappa}_{\mathrm{t}}^{2}+\kappa_{\mathrm{t}}^{2}}$ , the overall modifier of the top-Higgs coupling strength, is profiled such that the likelihood attains its minimum at each point in the plane.
png pdf	Figure 17-a: The observed (solid blue line) and expected (dotted black line) likelihood ratio test statistic as a function of $f_{\text{CP}}$ (left) and $\cos\alpha$ (right), where $\kappa_{\text{V}}$ is 1 and $\kappa^{\prime}_{\mathrm{t}}=\sqrt{\tilde{\kappa}_{\mathrm{t}}^{2}+\kappa_{\mathrm{t}}^{2}}$ , the overall modifier of the top-Higgs coupling strength, is profiled such that the likelihood attains its minimum at each point in the plane.
png pdf	Figure 17-b: The observed (solid blue line) and expected (dotted black line) likelihood ratio test statistic as a function of $f_{\text{CP}}$ (left) and $\cos\alpha$ (right), where $\kappa_{\text{V}}$ is 1 and $\kappa^{\prime}_{\mathrm{t}}=\sqrt{\tilde{\kappa}_{\mathrm{t}}^{2}+\kappa_{\mathrm{t}}^{2}}$ , the overall modifier of the top-Higgs coupling strength, is profiled such that the likelihood attains its minimum at each point in the plane.

Tables
png pdf	Table 1: Trigger selection criteria in the fully-hadronic (FH) channel. Multiple triggers, each represented by one row, are used per year and combined with a logical OR. In the case of the four-jet trigger, the minimum jet $p_{\mathrm{T}}$ is different for each jet and separated by a slash (/).
png pdf	Table 2: Generator version and configuration of the ${\mathrm{t}\overline{\mathrm{t}}}$ and ${\mathrm{t}\overline{\mathrm{t}}} \mathrm{b}\overline{\mathrm{b}}$ samples. The parameters $m_{\mathrm{t}}$ and $m_{\mathrm{b}}$ denote the top quark and bottom quark mass, respectively, $m_{\mathrm{T},\mathrm{t}}$ , $m_{\mathrm{T},\mathrm{b}}$ , and $m_{\mathrm{T},\mathrm{g}}$ the transverse mass of the top quark, the bottom quark, and additional gluons, respectively, and $h_{\text{damp}}$ the parton-shower matching scale.
png pdf	Table 3: Baseline selection criteria in the fully-hadronic (FH), single-lepton (SL), and dilepton (DL) channels based on the observables defined in the text. Where the criteria differ per year of data taking, they are quoted as three values, corresponding to 2016/2017/2018, respectively.
png pdf	Table 4: Categorisation scheme in the FH channel, applied independently in each jet-multiplicity category. The $m_{\mathrm{qq}}$ selection criteria refer to events with 7 or 8 ( $\geq$ 9) jets.
png pdf	Table 5: Observables used as input variables to the ANN per channel. Observables marked with a $^{\dagger}$ are constructed using information from the BDT-based event reconstruction.
png pdf	Table 6: Systematic uncertainties considered in the analysis. ``Type'' refers to rate (R) or rate and shape (S) altering uncertainties. ``Correlation'' indicates whether the uncertainty is treated as correlated, partially correlated (as detailed in the text), or uncorrelated across the years 2016--18. Uncertainties for ${\mathrm{t}\overline{\mathrm{t}}}$ +jets events marked with a $^{\dagger}$ are treated as partially correlated between each of the STXS categories and the other categories in the STXS analysis.
png pdf	Table 7: Best-fit results of the ttH signal-strength modifier $\mu_{{\mathrm{t}\overline{\mathrm{t}}} \mathrm{H}}$ in each channel and in their combination. Uncertainties are correlated between the channels.
png pdf	Table 8: Contributions of different sources of uncertainty to the result for the fit to the data (observed) and to the expectation from simulation (expected). The quoted uncertainties $\Delta\mu_{{\mathrm{t}\overline{\mathrm{t}}} \mathrm{H}}$ in $\mu_{{\mathrm{t}\overline{\mathrm{t}}} \mathrm{H}}$ are obtained by fixing the listed sources of uncertainties to their postfit values in the fit and subtracting the obtained result in quadrature from the result of the full fit. The statistical uncertainty is evaluated by fixing all nuisance parameters to their postfit values and repeating the fit. The quadratic sum of the contributions is different from the total uncertainty because of correlations between the nuisance parameters.
png pdf	Table 9: Best-fit results of the ttH signal-strength modifier $\mu_{{\mathrm{t}\overline{\mathrm{t}}} \mathrm{H}}$ in the different bins of Higgs boson $p_{\mathrm{T}}$ of the STXS measurement.

Summary

A combined analysis of the associated production of a Higgs boson (H) with a top quark-antiquark pair (ttH) or a single top quark (tH) with the Higgs boson decaying into a bottom quark-antiquark pair has been presented. The analysis has been performed using pp collision data recorded with the CMS detector at a centre-of-mass energy of 13 TeV, corresponding to an integrated luminosity of

$\mathcal{L}$ . Candidate events are selected in mutually exclusive categories according to the lepton and jet multiplicity, targeting all decay channels of the

$\mathrm{t} \overline{\mathrm{t}}$ system. Neural network discriminants are used to further categorise the events according to the most probable process, targeting the signal and different topologies of the dominant

${\mathrm{t}\overline{\mathrm{t}}}$ +jets background, as well as to separate the signal from the background. Compared to previous CMS results in this channel, several updates of the analysis strategy as well as modelling of the

${\mathrm{t}\overline{\mathrm{t}}}$ +jets background based on state-of-the art

${\mathrm{t}\overline{\mathrm{t}}} \mathrm{b}\overline{\mathrm{b}}$ simulations have been adopted, and an extended set of interpretations is performed. A best-fit value of the ttH production cross section relative to the standard model (SM) expectation of 0.33

$\pm$ 0.26

$=$ 0.33

$\pm$ 0.17 (stat)

$\pm$ 0.21 (syst) is obtained. The analysis is additionally performed within the Simplified Template Cross Section framework in five intervals of Higgs boson

$p_{\mathrm{T}}$ , probing potential

$p_{\mathrm{T}}$ dependent deviations from the SM expectation. An observed (expected) upper limit on the tH production cross section relative to the SM expectation of 14.6 (19.3) at 95% confidence level is derived. Information on the Higgs boson coupling strength is furthermore inferred from a simultaneous fit of the ttH and tH production rates, probing either the coupling strength of the Higgs boson to top quarks and to heavy vector bosons, or possible CP-odd admixtures in the coupling between the Higgs boson and top quarks.

Additional Figures
png pdf	Additional Figure 1: Transverse momentum of leading jet, ranked in $p_{\mathrm{T}}$ , for events in the SL channel after the baseline selection in the The last bins include overflow events. category, prefit (left) and with the postfit background model obtained from the fit of the final classifier distributions to data (right). The uncertainty band represents the total uncertainty. The last bins include overflow events.
png pdf	Additional Figure 1-a: Transverse momentum of leading jet, ranked in $p_{\mathrm{T}}$ , for events in the SL channel after the baseline selection in the The last bins include overflow events. category, prefit (left) and with the postfit background model obtained from the fit of the final classifier distributions to data (right). The uncertainty band represents the total uncertainty. The last bins include overflow events.
png pdf	Additional Figure 1-b: Transverse momentum of leading jet, ranked in $p_{\mathrm{T}}$ , for events in the SL channel after the baseline selection in the The last bins include overflow events. category, prefit (left) and with the postfit background model obtained from the fit of the final classifier distributions to data (right). The uncertainty band represents the total uncertainty. The last bins include overflow events.
png pdf	Additional Figure 2: Transverse momentum of third leading b-tagged jet, ranked in $p_{\mathrm{T}}$ , for events in the SL channel after the baseline selection in the ( $\geq$ 6 jets, $\geq$ 4 b tags) category, prefit (left) and with the postfit background model obtained from the fit of the final classifier distributions to data (right). The uncertainty band represents the total uncertainty. The last bins include overflow events.
png pdf	Additional Figure 2-a: Transverse momentum of third leading b-tagged jet, ranked in $p_{\mathrm{T}}$ , for events in the SL channel after the baseline selection in the ( $\geq$ 6 jets, $\geq$ 4 b tags) category, prefit (left) and with the postfit background model obtained from the fit of the final classifier distributions to data (right). The uncertainty band represents the total uncertainty. The last bins include overflow events.
png pdf	Additional Figure 2-b: Transverse momentum of third leading b-tagged jet, ranked in $p_{\mathrm{T}}$ , for events in the SL channel after the baseline selection in the ( $\geq$ 6 jets, $\geq$ 4 b tags) category, prefit (left) and with the postfit background model obtained from the fit of the final classifier distributions to data (right). The uncertainty band represents the total uncertainty. The last bins include overflow events.
png pdf	Additional Figure 3: b tagging discriminant value of leading jet, ranked in $p_{\mathrm{T}}$ , for events in the SL channel after the baseline selection in the ( $\geq$ 6 jets, $\geq$ 4 b tags) category, prefit (left) and with the postfit background model obtained from the fit of the final classifier distributions to data (right). The uncertainty band represents the total uncertainty.
png pdf	Additional Figure 3-a: b tagging discriminant value of leading jet, ranked in $p_{\mathrm{T}}$ , for events in the SL channel after the baseline selection in the ( $\geq$ 6 jets, $\geq$ 4 b tags) category, prefit (left) and with the postfit background model obtained from the fit of the final classifier distributions to data (right). The uncertainty band represents the total uncertainty.
png pdf	Additional Figure 3-b: b tagging discriminant value of leading jet, ranked in $p_{\mathrm{T}}$ , for events in the SL channel after the baseline selection in the ( $\geq$ 6 jets, $\geq$ 4 b tags) category, prefit (left) and with the postfit background model obtained from the fit of the final classifier distributions to data (right). The uncertainty band represents the total uncertainty.
png pdf	Additional Figure 4: Third highest b tagging discriminant value of all jets for events in the SL channel after the baseline selection in the ( $\geq$ 6 jets, $\geq$ 4 b tags) category, prefit (left) and with the postfit background model obtained from the fit of the final classifier distributions to data (right). The uncertainty band represents the total uncertainty.
png pdf	Additional Figure 4-a: Third highest b tagging discriminant value of all jets for events in the SL channel after the baseline selection in the ( $\geq$ 6 jets, $\geq$ 4 b tags) category, prefit (left) and with the postfit background model obtained from the fit of the final classifier distributions to data (right). The uncertainty band represents the total uncertainty.
png pdf	Additional Figure 4-b: Third highest b tagging discriminant value of all jets for events in the SL channel after the baseline selection in the ( $\geq$ 6 jets, $\geq$ 4 b tags) category, prefit (left) and with the postfit background model obtained from the fit of the final classifier distributions to data (right). The uncertainty band represents the total uncertainty.
png pdf	Additional Figure 5: Transverse momentum of pair of b-tagged jets closest in $\Delta R$ for events in the SL channel after the baseline selection in the ( $\geq$ 6 jets, $\geq$ 4 b tags) category, prefit (left) and with the postfit background model obtained from the fit of the final classifier distributions to data (right). The uncertainty band represents the total uncertainty. The last bins include overflow events.
png pdf	Additional Figure 5-a: Transverse momentum of pair of b-tagged jets closest in $\Delta R$ for events in the SL channel after the baseline selection in the ( $\geq$ 6 jets, $\geq$ 4 b tags) category, prefit (left) and with the postfit background model obtained from the fit of the final classifier distributions to data (right). The uncertainty band represents the total uncertainty. The last bins include overflow events.
png pdf	Additional Figure 5-b: Transverse momentum of pair of b-tagged jets closest in $\Delta R$ for events in the SL channel after the baseline selection in the ( $\geq$ 6 jets, $\geq$ 4 b tags) category, prefit (left) and with the postfit background model obtained from the fit of the final classifier distributions to data (right). The uncertainty band represents the total uncertainty. The last bins include overflow events.
png pdf	Additional Figure 6: Invariant mass of pair of b-tagged jets with mass closest to 125 GeV for events in the DL channel after the baseline selection, prefit (left) and with the postfit background model obtained from the fit of the final classifier distributions to data (right). The uncertainty band represents the total uncertainty. The last bins include overflow events.
png pdf	Additional Figure 6-a: Invariant mass of pair of b-tagged jets with mass closest to 125 GeV for events in the DL channel after the baseline selection, prefit (left) and with the postfit background model obtained from the fit of the final classifier distributions to data (right). The uncertainty band represents the total uncertainty. The last bins include overflow events.
png pdf	Additional Figure 6-b: Invariant mass of pair of b-tagged jets with mass closest to 125 GeV for events in the DL channel after the baseline selection, prefit (left) and with the postfit background model obtained from the fit of the final classifier distributions to data (right). The uncertainty band represents the total uncertainty. The last bins include overflow events.
png pdf	Additional Figure 7: Transverse momentum of pair of b-tagged jets with mass closest to 125 GeV for events in the DL channel after the baseline selection, prefit (left) and with the postfit background model obtained from the fit of the final classifier distributions to data (right). The uncertainty band represents the total uncertainty. The last bins include overflow events.
png pdf	Additional Figure 7-a: Transverse momentum of pair of b-tagged jets with mass closest to 125 GeV for events in the DL channel after the baseline selection, prefit (left) and with the postfit background model obtained from the fit of the final classifier distributions to data (right). The uncertainty band represents the total uncertainty. The last bins include overflow events.
png pdf	Additional Figure 7-b: Transverse momentum of pair of b-tagged jets with mass closest to 125 GeV for events in the DL channel after the baseline selection, prefit (left) and with the postfit background model obtained from the fit of the final classifier distributions to data (right). The uncertainty band represents the total uncertainty. The last bins include overflow events.
png pdf	Additional Figure 8: Transverse momentum of pair of b-tagged jets closest in $\Delta R$ for events in the DL channel after the baseline selection, prefit (left) and with the postfit background model obtained from the fit of the final classifier distributions to data (right). The uncertainty band represents the total uncertainty. The last bins include overflow events.
png pdf	Additional Figure 8-a: Transverse momentum of pair of b-tagged jets closest in $\Delta R$ for events in the DL channel after the baseline selection, prefit (left) and with the postfit background model obtained from the fit of the final classifier distributions to data (right). The uncertainty band represents the total uncertainty. The last bins include overflow events.
png pdf	Additional Figure 8-b: Transverse momentum of pair of b-tagged jets closest in $\Delta R$ for events in the DL channel after the baseline selection, prefit (left) and with the postfit background model obtained from the fit of the final classifier distributions to data (right). The uncertainty band represents the total uncertainty. The last bins include overflow events.
png pdf	Additional Figure 9: Average $\Delta\eta$ between any two b-tagged jets for events in the SL channel after the baseline selection in the ( $\geq$ 6 jets, $\geq$ 4 b tags) category prior to the fit to data, where the ${\mathrm{t}\overline{\mathrm{t}}} \text{B}$ background contribution has been estimated using the ${\mathrm{t}\overline{\mathrm{t}}}$ 5 FS sample. The uncertainty band represents the total uncertainty. The last bin includes overflow events.
png pdf	Additional Figure 10: Validation of the QCD background estimation procedure: ANN output distribution observed in data compared to the predicted contributions from QCD (from data-driven procedure) and from other background processes (from simulation) in the ( $\geq$ 9 jets, $\geq$ 4 b tags) validation region of the FH channel.
png pdf	Additional Figure 11: Prefit expected (filled histograms) and observed (points) yields in each discriminant bin for the 2016 (top), 2017 (middle), and 2018 (bottom) data-taking periods. The uncertainty bands include the total uncertainty of the fit model. The lower pads show the ratio of the data to the background (points) and of the prefit expected signal+background to the background-only contribution (line).
png pdf	Additional Figure 11-a: Prefit expected (filled histograms) and observed (points) yields in each discriminant bin for the 2016 (top), 2017 (middle), and 2018 (bottom) data-taking periods. The uncertainty bands include the total uncertainty of the fit model. The lower pads show the ratio of the data to the background (points) and of the prefit expected signal+background to the background-only contribution (line).
png pdf	Additional Figure 11-b: Prefit expected (filled histograms) and observed (points) yields in each discriminant bin for the 2016 (top), 2017 (middle), and 2018 (bottom) data-taking periods. The uncertainty bands include the total uncertainty of the fit model. The lower pads show the ratio of the data to the background (points) and of the prefit expected signal+background to the background-only contribution (line).
png pdf	Additional Figure 11-c: Prefit expected (filled histograms) and observed (points) yields in each discriminant bin for the 2016 (top), 2017 (middle), and 2018 (bottom) data-taking periods. The uncertainty bands include the total uncertainty of the fit model. The lower pads show the ratio of the data to the background (points) and of the prefit expected signal+background to the background-only contribution (line).
png pdf	Additional Figure 12: Observed (points) and prefit expected (filled histograms) yields in each STXS analysis discriminant bin in the signal regions of the SL and DL channels for the 2016 (top), 2017 (middle), and 2018 (bottom) data-taking periods. The signal distributions in each Higgs boson $p_{\mathrm{T}}$ bin are also overlayed (lines labelled ${\mathrm{t}\overline{\mathrm{t}}} \mathrm{H}$ 1 to 5). The uncertainty bands include the total uncertainty of the fit model. The lower pads show the ratio of the data to the background (points) and of the prefit expected signal+background to the background-only contribution (lines).
png pdf	Additional Figure 12-a: Observed (points) and prefit expected (filled histograms) yields in each STXS analysis discriminant bin in the signal regions of the SL and DL channels for the 2016 (top), 2017 (middle), and 2018 (bottom) data-taking periods. The signal distributions in each Higgs boson $p_{\mathrm{T}}$ bin are also overlayed (lines labelled ${\mathrm{t}\overline{\mathrm{t}}} \mathrm{H}$ 1 to 5). The uncertainty bands include the total uncertainty of the fit model. The lower pads show the ratio of the data to the background (points) and of the prefit expected signal+background to the background-only contribution (lines).
png pdf	Additional Figure 12-b: Observed (points) and prefit expected (filled histograms) yields in each STXS analysis discriminant bin in the signal regions of the SL and DL channels for the 2016 (top), 2017 (middle), and 2018 (bottom) data-taking periods. The signal distributions in each Higgs boson $p_{\mathrm{T}}$ bin are also overlayed (lines labelled ${\mathrm{t}\overline{\mathrm{t}}} \mathrm{H}$ 1 to 5). The uncertainty bands include the total uncertainty of the fit model. The lower pads show the ratio of the data to the background (points) and of the prefit expected signal+background to the background-only contribution (lines).
png pdf	Additional Figure 12-c: Observed (points) and prefit expected (filled histograms) yields in each STXS analysis discriminant bin in the signal regions of the SL and DL channels for the 2016 (top), 2017 (middle), and 2018 (bottom) data-taking periods. The signal distributions in each Higgs boson $p_{\mathrm{T}}$ bin are also overlayed (lines labelled ${\mathrm{t}\overline{\mathrm{t}}} \mathrm{H}$ 1 to 5). The uncertainty bands include the total uncertainty of the fit model. The lower pads show the ratio of the data to the background (points) and of the prefit expected signal+background to the background-only contribution (lines).
png pdf	Additional Figure 13: Postfit values of the nuisance parameters (black markers) in the STXS analysis, shown as the difference of their best-fit values, $\hat{\theta}$ , and prefit values, $\theta_{0}$ , relative to the prefit uncertainties $\Delta\theta$ . The impact $\Delta\hat{\mu}_{{\mathrm{t}\overline{\mathrm{t}}} \mathrm{H}}^{i}$ of the nuisance parameters on the signal strength $\mu_{{\mathrm{t}\overline{\mathrm{t}}} \mathrm{H}}^{i}$ in the $i$ -th STXS bin is computed as the difference of the nominal best fit value of $\mu_{{\mathrm{t}\overline{\mathrm{t}}} \mathrm{H}}^{i}$ and the best fit value obtained when fixing the nuisance parameter under scrutiny to its best fit value $\hat{\theta}$ plus/minus its postfit uncertainty (coloured areas). The nuisance parameters are ordered by the quadratic sum of their relative impacts on all five $\mu_{{\mathrm{t}\overline{\mathrm{t}}} \mathrm{H}}^{i}$ , and only the 20 highest ranked parameters are shown.
png pdf	Additional Figure 14: Correlations of the best-fit ${\mathrm{t}\overline{\mathrm{t}}} \mathrm{H}$ signal-strength modifiers $\mu_{{\mathrm{t}\overline{\mathrm{t}}} \mathrm{H}}^{i}$ in the different STXS bins $i$ and the global ( ${\mathrm{t}\overline{\mathrm{t}}} \text{B}$ ) and per-bin ( ${\mathrm{t}\overline{\mathrm{t}}} \text{B}\;i$ ) ${\mathrm{t}\overline{\mathrm{t}}} \text{B}$ background normalisation parameters.

Additional Tables

png pdf

Additional Table 1:
Results of background model robustness tests performed in the SL+DL channels. For the tests, pseudo data are generated sampling the

${\mathrm{t}\overline{\mathrm{t}}} \text{B}$ component from alternative

${\mathrm{t}\overline{\mathrm{t}}} \text{B}$ predictions, and fitted using the nominal signal+background model. The injected signal corresponds to the SM expectation (

$\mu_{{\mathrm{t}\overline{\mathrm{t}}} \mathrm{H}} =$ 1). Pseudo data are sampled in different scenarios. First, the data are sampled from the nominal background model used in the analysis, as a cross-check. Second, the

${\mathrm{t}\overline{\mathrm{t}}} \text{B}$ yield from the

${\mathrm{t}\overline{\mathrm{t}}} \mathrm{b}\overline{\mathrm{b}}$ sample is scaled by a factor 1.2. In the next two tests, the

${\mathrm{t}\overline{\mathrm{t}}} \text{B}$ component is taken from the

${\mathrm{t}\overline{\mathrm{t}}}$ sample, once at its nominal value and once scaling its yield up by a factor 1.2. The table lists the mean values of the best-fit signal strength modifier, as well as the

${\mathrm{t}\overline{\mathrm{t}}} \text{B}$ and

${\mathrm{t}\overline{\mathrm{t}}} \text{C}$ background normalisation parameters obtained in the fits to the pseudo data. The quoted uncertainty corresponds to the RMS of the distributions. The statistical uncertainty on the mean values is below 1%. In all cases the fitted signal strength is compatible with the injected value of 1, showing that the fit is robust against potential mismodelling of the

${\mathrm{t}\overline{\mathrm{t}}} \text{B}$ component. Also the

${\mathrm{t}\overline{\mathrm{t}}} \text{B}$ and

${\mathrm{t}\overline{\mathrm{t}}} \text{C}$ normalisations are compatible with the injected values within.

References
1	ATLAS Collaboration	Observation of Higgs boson production in association with a top quark pair at the LHC with the ATLAS detector	PLB 784 (2018) 159	1806.00425
2	CMS Collaboration	Observation of $\mathrm{t}\overline{\mathrm{t}}\mathrm{H}$ production	PRL 120 (2018) 231801	CMS-HIG-17-035 1804.02610
3	ATLAS Collaboration	Observation of $\mathrm{H}\to\mathrm{b}\overline{\mathrm{b}}$ decays and VH production with the ATLAS detector	PLB 786 (2018) 59	1808.08238
4	CMS Collaboration	Observation of Higgs boson decay to bottom quarks	PRL 121 (2018) 121801	CMS-HIG-18-016 1808.08242
5	F. Maltoni, K. Paul, T. Stelzer, and S. Willenbrock	Associated production of Higgs and single top at hadron colliders	PRD 64 (2001) 094023	hep-ph/0106293
6	M. Farina et al.	Lifting degeneracies in Higgs couplings using single top production in association with a Higgs boson	JHEP 05 (2013) 022	1211.3736
7	P. Agrawal, S. Mitra, and A. Shivaji	Effect of anomalous couplings on the associated production of a single top quark and a Higgs boson at the LHC	JHEP 12 (2013) 077	1211.4362
8	F. Demartin, F. Maltoni, K. Mawatari, and M. Zaro	Higgs production in association with a single top quark at the LHC	EPJC 75 (2015) 267	1504.00611
9	LHC Higgs Cross Section Working Group	Handbook of LHC Higgs cross sections: 4. deciphering the nature of the Higgs sector		1610.07922
10	ATLAS Collaboration	Measurement of Higgs boson decay into b-quarks in associated production with a top-quark pair in pp collisions at $\sqrt{s}=$ 13 TeV with the ATLAS detector	JHEP 06 (2022) 097	2111.06712
11	CMS Collaboration	Search for $\mathrm{t}\overline{\mathrm{t}}\mathrm{H}$ production in the $\mathrm{H}\to\mathrm{b}\overline{\mathrm{b}}$ decay channel with leptonic $\mathrm{t}\overline{\mathrm{t}}$ decays in proton-proton collisions at $\sqrt{s}=$ 13 TeV	JHEP 03 (2019) 026	CMS-HIG-17-026 1804.03682
12	CMS Collaboration	Search for $\mathrm{t}\overline{\mathrm{t}}\mathrm{H}$ production in the all-jet final state in proton-proton collisions at $\sqrt{s}=$ 13 TeV	JHEP 06 (2018)	CMS-HIG-17-022 1803.06986
13	CMS Collaboration	Search for associated production of a Higgs boson and a single top quark in proton-proton collisions at $\sqrt{s}=$ 13 TeV	PRD 99 (2019) 092005	CMS-HIG-18-009 1811.09696
14	ATLAS Collaboration	Probing the $CP$ nature of the top-Higgs Yukawa coupling in $\mathrm{t}\overline{\mathrm{t}}\mathrm{H}$ and $\mathrm{t}\mathrm{H}$ events with $\mathrm{H}\to\mathrm{b}\overline{\mathrm{b}}$ decays using the ATLAS detector at the LHC	Submitted to PLB, 2023	2303.05974
15	CMS Collaboration	The CMS experiment at the CERN LHC	JINST 3 (2008) S08004
16	CMS Collaboration	Performance of the CMS level-1 trigger in proton-proton collisions at $\sqrt{s}=$ 13 TeV	JINST 15 (2020) P10017	CMS-TRG-17-001 2006.10165
17	CMS Collaboration	The CMS trigger system	JINST 12 (2017) P01020	CMS-TRG-12-001 1609.02366
18	CMS Collaboration	Precision luminosity measurement in proton-proton collisions at $\sqrt{s}=$ 13 TeV in 2015 and 2016 at CMS	EPJC 81 (2021) 800	CMS-LUM-17-003 2104.01927
19	CMS	CMS luminosity measurement for the 2017 data-taking period at $\sqrt{s}=$ 13 TeV	CMS Physics Analysis Summary, 2017 CMS-PAS-LUM-17-004	CMS-PAS-LUM-17-004
20	CMS	CMS luminosity measurement for the 2018 data-taking period at $\sqrt{s}=$ 13 TeV	CMS Physics Analysis Summary, 2018 CMS-PAS-LUM-18-002	CMS-PAS-LUM-18-002
21	GEANT4 Collaboration	GEANT 4---a simulation toolkit	NIM A 506 (2003) 250
22	P. Nason	A new method for combining NLO QCD with shower Monte Carlo algorithms	JHEP 11 (2004) 040	hep-ph/0409146
23	S. Frixione, P. Nason, and C. Oleari	Matching NLO QCD computations with parton shower simulations: the POWHEG method	JHEP 11 (2007) 070	0709.2092
24	S. Alioli, P. Nason, C. Oleari, and E. Re	A general framework for implementing NLO calculations in shower Monte Carlo programs: the POWHEG BOX	JHEP 06 (2010) 043	1002.2581
25	T. Je žo and P. Nason	On the treatment of resonances in next-to-leading order calculations matched to a parton shower	JHEP 12 (2015) 065	1509.09071
26	H. B. Hartanto, B. Jager, L. Reina, and D. Wackeroth	Higgs boson production in association with top quarks in the POWHEG BOX	PRD 91 (2015) 094003	1501.04498
27	J. Alwall et al.	The automated computation of tree-level and next-to-leading order differential cross sections, and their matching to parton shower simulations	JHEP 07 (2014) 079	1405.0301
28	T. Sjöstrand et al.	An introduction to PYTHIA 8.2	Comput. Phys. Commun. 191 (2015) 159	1410.3012
29	NNPDF Collaboration	Parton distributions from high-precision collider data	EPJC 77 (2017) 663	1706.00428
30	CMS Collaboration	Extraction and validation of a new set of CMS PYTHIA 8 tunes from underlying-event measurements	EPJC 80 (2020) 4	CMS-GEN-17-001 1903.12179
31	CMS Collaboration	Event generator tunes obtained from underlying event and multiparton scattering measurements	EPJC 76 (2016) 155	CMS-GEN-14-001 1512.00815
32	F. Maltoni, G. Ridolfi, and M. Ubiali	b-initiated processes at the LHC: a reappraisal	JHEP 07 (2012) 022	1203.6393
33	F. Demartin et al.	$\mathrm{t}\mathrm{W}\mathrm{H}$ associated production at the LHC	EPJC 77 (2017) 34	1607.05862
34	J. S. Gainer et al.	Exploring theory space with Monte Carlo reweighting	JHEP 10 (2014) 078	1404.7129
35	O. Mattelaer	On the maximal use of Monte Carlo samples: re-weighting events at NLO accuracy	EPJC 76 (2016) 674	1607.00763
36	T. Ježo, J. M. Lindert, N. Moretti, and S. Pozzorini	New NLOPS predictions for $\mathrm{t}\overline{\mathrm{t}}+\mathrm{b}$ -jet production at the LHC	EPJC 78 (2018) 502	1802.00426
37	F. Buccioni et al.	OpenLoops 2	EPJC 79 (2019) 866	1907.13071
38	F. Cascioli et al.	NLO matching for $\mathrm{t}\overline{\mathrm{t}}\mathrm{b}\overline{\mathrm{b}}$ production with massive b-quarks	PLB 734 (2014) 210	1309.5912
39	F. Buccioni, S. Kallweit, S. Pozzorini, and M. F. Zoller	NLO QCD predictions for $\mathrm{t}\overline{\mathrm{t}}\mathrm{b}\overline{\mathrm{b}}$ production in association with a light jet at the LHC	JHEP 12 (2019) 015	1907.13624
40	S. Alioli, P. Nason, C. Oleari, and E. Re	NLO single-top production matched with shower in POWHEG: $s$ - and $t$ -channel contributions	JHEP 09 (2009) 111	0907.4076
41	E. Re	Single-top Wt-channel production matched with parton showers using the POWHEG method	EPJC 71 (2011) 1547	1009.2450
42	R. Frederix and S. Frixione	Merging meets matching in MC@NLO	JHEP 12 (2012) 061	1209.6215
43	J. Alwall et al.	Comparative study of various algorithms for the merging of parton showers and matrix elements in hadronic collisions	EPJC 53 (2008) 473	0706.2569
44	CMS Collaboration	A measurement of the Higgs boson mass in the diphoton decay channel	PLB 805 (2020) 135425	CMS-HIG-19-004 2002.06398
45	M. Cacciari et al.	Top-pair production at hadron colliders with next-to-next-to-leading logarithmic soft-gluon resummation	PLB 710 (2012) 612	1111.5869
46	P. Bärnreuther, M. Czakon, and A. Mitov	Percent-level-precision physics at the Tevatron: next-to-next-to-leading order QCD corrections to $\mathrm{q}\overline{\mathrm{q}}\to\mathrm{t}\overline{\mathrm{t}}\text{+X}$	PRL 109 (2012) 132001	1204.5201
47	M. Czakon and A. Mitov	NNLO corrections to top-pair production at hadron colliders: the all-fermionic scattering channels	JHEP 12 (2012) 054	1207.0236
48	M. Czakon and A. Mitov	NNLO corrections to top pair production at hadron colliders: the quark-gluon reaction	JHEP 01 (2013) 080	1210.6832
49	M. Beneke, P. Falgari, S. Klein, and C. Schwinn	Hadronic top-quark pair production with NNLL threshold resummation	NPB 855 (2012) 695	1109.1536
50	M. Czakon, P. Fiedler, and A. Mitov	Total top-quark pair-production cross section at hadron colliders through $o({\alpha_s}^4)$	PRL 110 (2013) 252004	1303.6254
51	M. Czakon and A. Mitov	Top++: a program for the calculation of the top-pair cross-section at hadron colliders	Comput. Phys. Commun. 185 (2014) 2930	1112.5675
52	N. Kidonakis	Two-loop soft anomalous dimensions for single top quark associated production with $\mathrm{W^-}$ or $\mathrm{H}^{-}$	PRD 82 (2010) 054018	1005.4451
53	M. Aliev et al.	HATHOR: HAdronic Top and Heavy quarks crOss section calculatoR	Comput. Phys. Commun. 182 (2011) 1034	1007.1327
54	P. Kant et al.	HatHor for single top-quark production: Updated predictions and uncertainty estimates for single top-quark production in hadronic collisions	Comput. Phys. Commun. 191 (2015) 74	1406.4403
55	F. Maltoni, D. Pagani, and I. Tsinikos	Associated production of a top-quark pair with vector bosons at NLO in QCD: impact on $\mathrm{t}\overline{\mathrm{t}}\mathrm{H}$ searches at the LHC	JHEP 02 (2016) 113	1507.05640
56	J. M. Campbell, R. K. Ellis, and C. Williams	Vector boson pair production at the LHC	JHEP 07 (2011) 018	1105.0020
57	CMS Collaboration	Particle-flow reconstruction and global event description with the CMS detector	JINST 12 (2017) P10003	CMS-PRF-14-001 1706.04965
58	CMS Collaboration	Technical proposal for the phase-2 upgrade of the Compact Muon Solenoid	CMS Technical Proposal CERN-LHCC-2015-010, CMS-TDR-15-02, 2015 CDS
59	CMS Collaboration	Performance of the CMS muon detector and muon reconstruction with proton-proton collisions at $\sqrt{s}=$ 13 TeV	JINST 13 (2018) P06015	CMS-MUO-16-001 1804.04528
60	CMS Collaboration	Electron and photon reconstruction and identification with the CMS experiment at the CERN LHC	JINST 16 (2021) P05014	CMS-EGM-17-001 2012.06888
61	CMS Collaboration	ECAL 2016 refined calibration and Run2 summary plots	CMS Detector Performance Summary CMS-DP-2020-021, 2020 CDS
62	M. Cacciari, G. P. Salam, and G. Soyez	The anti- $k_{\mathrm{T}}$ jet clustering algorithm	JHEP 04 (2008) 063	0802.1189
63	M. Cacciari, G. P. Salam, and G. Soyez	FastJet user manual	EPJC 72 (2012) 1896	1111.6097
64	M. Cacciari, G. P. Salam, and G. Soyez	The catchment area of jets	JHEP 04 (2008) 005	0802.1188
65	CMS Collaboration	Jet energy scale and resolution in the CMS experiment in pp collisions at 8 TeV	JINST 12 (2017) P02014	CMS-JME-13-004 1607.03663
66	CMS Collaboration	Identification of heavy-flavour jets with the CMS detector in pp collisions at 13 TeV	JINST 13 (2018) P05011	CMS-BTV-16-002 1712.07158
67	E. Bols et al.	Jet flavour classification using DeepJet	JINST 15 (2020) P12012	2008.10519
68	CMS Collaboration	B-tagging performance of the CMS legacy dataset 2018	CMS Detector Performance Summary CMS-DP-2021-004, 2021 CDS
69	CMS Collaboration	Performance of missing transverse momentum reconstruction in proton-proton collisions at $\sqrt{s} =$ 13 TeV using the CMS detector	JINST 14 (2019) P07004	CMS-JME-17-001 1903.06078
70	K. Kondo	Dynamical likelihood method for reconstruction of events with missing momentum. 1: Method and toy models	J. Phys. Soc. Jap. 57 (1988) 4126
71	CMS Collaboration	Inclusive and differential cross section measurements of $\mathrm{t}\overline{\mathrm{t}}\mathrm{b}\overline{\mathrm{b}}$ production in the lepton+jets channel at $\sqrt{s}=$ 13 TeV with the CMS detector	CMS Physics Analysis Summary, 2023 CMS-PAS-TOP-22-009	CMS-PAS-TOP-22-009
72	CMS Collaboration	Measurement of the cross section for $\mathrm{t}\overline{\mathrm{t}}$ production with additional jets and b jets in pp collisions at $\sqrt{s}=$ 13 TeV	JHEP 07 (2020) 125	CMS-TOP-18-002 2003.06467
73	CMS Collaboration	Measurement of the $\mathrm{t}\overline{\mathrm{t}}\mathrm{b}\overline{\mathrm{b}}$ production cross section in the all-jet final state in pp collisions at $\sqrt{s}=$ 13 TeV	PLB 803 (2020) 135285	CMS-TOP-18-011 1909.05306
74	ATLAS and CMS Collaborations, and the LHC Higgs Combination Group	Procedure for the LHC Higgs boson search combination in summer 2011	ATL-PHYS-PUB-2011-011, CMS NOTE-2011/005, 2011 link
75	J. S. Conway	Incorporating nuisance parameters in likelihoods for multisource spectra	PHYSTAT 201 (2011) 1	1103.0354
76	J. D. Bjorken and S. J. Brodsky	Statistical model for electron-positron annihilation into hadrons	PRD 1 (1970) 1416
77	G. C. Fox and S. Wolfram	Event shapes in $\mathrm{e}^+\mathrm{e}^-$ annihilation	Nuclear Physics B 157 (1979) 543
78	I. Goodfellow, Y. Bengio, and A. Courville	Deep Learning	MIT Press, 2016 link
79	J. K. Lindsey	Parametric statistical inference	Clarendon Press, Oxford, England, 1996
80	CMS Collaboration	Performance of deep tagging algorithms for boosted double quark jet topology in proton-proton collisions at 13 TeV with the phase-0 CMS detector	CMS Detector Performance Summary CMS-DP-2018-046, 2018 CDS
81	F. Chollet et al.	Keras	link
82	S. Jasper, L. Hugo, and P. A. Ryan	Practical bayesian optimization of machine learning algorithms		1206.2944
83	F. Luca, D. Michele, F. Paolo, and P. Massimiliano	Forward and reverse gradient-based hyperparameter optimization	in 34th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol. 70. PMLR, 2017
84	NNPDF Collaboration	Parton distributions for the LHC Run II	JHEP 04 (2015) 040	1410.8849
85	P. Skands, S. Carrazza, and J. Rojo	Tuning PYTHIA 8.1: the Monash 2013 tune	EPJC 74 (2014) 3024	1404.5630
86	CMS Collaboration	Measurement of differential cross sections for the production of top quark pairs and of additional jets in lepton+jets events from pp collisions at $\sqrt{s}=$ 13 TeV	PRD 97 (2018) 112003	CMS-TOP-17-002 1803.08856
87	J. R. Andersen et al.	Les Houches 2017: Physics at TeV colliders standard model working group report		1803.07977
88	CMS Tracker Group Collaboration	The CMS phase-1 pixel detector upgrade	JINST 16 (2021) P02027	2012.14304
89	R. Barlow and C. Beeston	Fitting using finite Monte Carlo samples	Comp. Phys. Commun. 77 (1993) 219
90	CMS Collaboration	First measurement of the cross section for top quark pair production with additional charm jets using dileptonic final states in pp collisions at $\sqrt{s}=$ 13 TeV	PLB 820 (2021) 136565	CMS-TOP-20-003 2012.09225
91	LHC Higgs Cross Section Working Group	Handbook of LHC Higgs cross sections: 3. Higgs properties		1307.1347
92	A. V. Gritsan, R. Röntsch, M. Schulze, and M. Xiao	Constraining anomalous Higgs boson couplings to the heavy flavor fermions using matrix element techniques	PRD 94 (2016) 055023	1606.03107
93	F. Demartin et al.	Higgs characterisation at NLO in QCD: CP properties of the top-quark Yukawa interaction	EPJC 74 (2014) 3065	1407.5089