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Compact Muon Solenoid
LHC, CERN

CMS-HIG-19-008 ; CERN-EP-2020-200
Measurement of the Higgs boson production rate in association with top quarks in final states with electrons, muons, and hadronically decaying tau leptons at $\sqrt{s} = $ 13 TeV
Eur. Phys. J. C 81 (2021) 378
Abstract: The rate for Higgs (H) bosons production in association with either one ($\mathrm{tH}$) or two (${\mathrm{t}}{\mathrm{\bar{t}}}\mathrm{H}$) top quarks is measured in final states containing multiple electrons, muons, or tau leptons decaying to hadrons and a neutrino, using proton-proton collisions recorded at a center-of-mass energy of 13 TeV by the CMS experiment. The analyzed data correspond to an integrated luminosity of 137 fb$^{-1}$. The analysis is aimed at events that contain $\mathrm{H} \to \mathrm{W}\mathrm{W}$, $\mathrm{H} \to \tau\tau$, or $\mathrm{H} \to \mathrm{Z}\mathrm{Z}$ decays and each of the top quark(s) decays either to lepton+jets or all-jet channels. Sensitivity to signal is maximized by including ten signatures in the analysis, depending on the lepton multiplicity. The separation among the $\mathrm{tH}$, the ${\mathrm{t}}{\mathrm{\bar{t}}}\mathrm{H}$, and the backgrounds is enhanced through machine-learning techniques and matrix-element methods. The measured production rates for the ${\mathrm{t}}{\mathrm{\bar{t}}}\mathrm{H}$ and $\mathrm{tH}$ signals correspond to 0.92 $\pm$ 0.19 (stat) $^{+0.17}_{-0.13}$ (syst) and 5.7 $\pm$ 2.7 (stat) $\pm$ 3.0 (syst) of their respective standard model (SM) expectations. The corresponding observed (expected) significance amounts to 4.7 (5.2) standard deviations for $\mathrm{t}\mathrm{\bar{t}}\mathrm{H}$, and to 1.4 (0.3) for $\mathrm{t}\mathrm{H}$ production. Assuming that the Higgs boson coupling to the tau lepton is equal in strength to its expectation in the SM, the coupling $y_{{\mathrm{t}}}$ of the Higgs boson to the top quark divided by its SM expectation, ${\kappa_{{\mathrm{t}}}}=y_{{\mathrm{t}}}/y_{{\mathrm{t}}}^{\mathrm{SM}}$, is constrained to be within $-0.9 < {\kappa_{{\mathrm{t}}}} < -0.7$ or $ 0.7 < {\kappa_{{\mathrm{t}}}} < 1.1$, at 95% confidence level. This result is the most sensitive measurement of the ${\mathrm{t}}{\mathrm{\bar{t}}}\mathrm{H}$ production rate to date.
Figures & Tables Summary References CMS Publications
Figures

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Figure 1:
Feynman diagrams at LO for $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ production.

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Figure 1-a:
Feynman diagram at LO for $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ production.

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Figure 1-b:
Feynman diagram at LO for $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ production.

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Figure 2:
Feynman diagrams at LO for $ {{\mathrm{t}} {\mathrm{H}}}$ production via the $t$-channel ($ {{{\mathrm{t}} {\mathrm{H}}} {\mathrm{q}}}$ in upper left and upper right) and $s$-channel (middle) processes, and for associated production of a Higgs boson with a single top quark and a W boson ($ {{{\mathrm{t}} {\mathrm{H}}}\mathrm{W}}$ in lower left and lower right). The $ {{{\mathrm{t}} {\mathrm{H}}} {\mathrm{q}}}$ and $ {{{\mathrm{t}} {\mathrm{H}}}\mathrm{W}}$ production processes are shown for the five-flavor scheme.

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Figure 2-a:
Feynman diagram at LO for the $ {{\mathrm{t}} {\mathrm{H}}}$ production via the $t$-channel $ {{{\mathrm{t}} {\mathrm{H}}} {\mathrm{q}}}$ process. This production processes is shown for the five-flavor scheme.

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Figure 2-b:
Feynman diagram at LO for the $ {{\mathrm{t}} {\mathrm{H}}}$ production via the $t$-channel $ {{{\mathrm{t}} {\mathrm{H}}} {\mathrm{q}}}$ process. This production processes is shown for the five-flavor scheme.

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Figure 2-c:
Feynman diagram at LO for the $ {{\mathrm{t}} {\mathrm{H}}}$ production via the $s$-channel process.

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Figure 2-d:
Feynman diagram at LO for the associated production of a Higgs boson with a single top quark and a W boson $ {{{\mathrm{t}} {\mathrm{H}}}\mathrm{W}}$. This production processes is shown for the five-flavor scheme.

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Figure 2-e:
Feynman diagram at LO for the associated production of a Higgs boson with a single top quark and a W boson $ {{{\mathrm{t}} {\mathrm{H}}}\mathrm{W}}$. This production processes is shown for the five-flavor scheme.

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Figure 3:
Diagram showing the categorization strategy used for the signal extraction, making use of MVA-based algorithms and topological variables. In addition to the ten channels, the ML fit receives input from two control regions (CRs) defined in Section 7.3.

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Figure 4:
Transverse momentum (left) and pseudorapidity (middle) distributions of bottom quarks produced in top quark decays in $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ signal events compared to $ {{\mathrm{t}} {\mathrm{\bar{t}}}}$+jets background events, and multiplicity of jets passing tight $ {\mathrm{b}}$ jet identification criteria (right). The latter distribution is shown separately for $ {{\mathrm{t}} {\mathrm{\bar{t}}}}$+jets background events in which a nonprompt lepton is misidentified as a prompt lepton and for those background events in which all reconstructed leptons are prompt leptons. The events are selected in the 2$\ell$SS$+$0${\tau _\mathrm {h}}$ channel.

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Figure 4-a:
Transverse momentum distribution of bottom quarks produced in top quark decays in $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ signal events compared to $ {{\mathrm{t}} {\mathrm{\bar{t}}}}$+jets background events. The events are selected in the 2$\ell$SS$+$0${\tau _\mathrm {h}}$ channel.

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Figure 4-b:
Pseudorapidity distribution of bottom quarks produced in top quark decays in $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ signal events compared to $ {{\mathrm{t}} {\mathrm{\bar{t}}}}$+jets background events. The events are selected in the 2$\ell$SS$+$0${\tau _\mathrm {h}}$ channel.

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Figure 4-c:
Multiplicity of jets passing tight $ {\mathrm{b}}$ jet identification criteria. The distribution is shown separately for $ {{\mathrm{t}} {\mathrm{\bar{t}}}}$+jets background events in which a nonprompt lepton is misidentified as a prompt lepton and for those background events in which all reconstructed leptons are prompt leptons. The events are selected in the 2$\ell$SS$+$0${\tau _\mathrm {h}}$ channel.

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Figure 5:
Distributions of $ {{m_{\mathrm {T}}} ^{{\text {fix}}}}$ for events containing an electron candidate of 25 $ < {p_{\mathrm {T}}} < $ 35 GeV in the ECAL barrel, which (left) passes the nominal selection and (right) passes the relaxed, but fails the nominal selection. The "electroweak'' (EWK) background refers to the sum of $\mathrm{W} $+jets, DY, and diboson production. The "rare'' backgrounds are defined in the text. The data in the fail sample agrees with the sum of multijet, EWK, $ {{\mathrm{t}} {\mathrm{\bar{t}}}}$+jets, and rare backgrounds by construction, as the number of multijet events in the fail sample is computed by subtracting the sum of EWK, $ {{\mathrm{t}} {\mathrm{\bar{t}}}}$+jets, and rare background contributions from the data. The misidentification probabilities are derived separately for each era: this figure shows, as an example, the results obtained with the 2017 data set. The uncertainty band represents the total uncertainty after the fit has been performed.

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Figure 5-a:
Distribution of $ {{m_{\mathrm {T}}} ^{{\text {fix}}}}$ for events containing an electron candidate of 25 $ < {p_{\mathrm {T}}} < $ 35 GeV in the ECAL barrel, which passes the nominal selection. The "electroweak'' (EWK) background refers to the sum of $\mathrm{W} $+jets, DY, and diboson production. The "rare'' backgrounds are defined in the text. The misidentification probabilities are derived separately for each era: this figure shows, as an example, the results obtained with the 2017 data set. The uncertainty band represents the total uncertainty after the fit has been performed.

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Figure 5-b:
Distribution of $ {{m_{\mathrm {T}}} ^{{\text {fix}}}}$ for events containing an electron candidate of 25 $ < {p_{\mathrm {T}}} < $ 35 GeV in the ECAL barrel, which passes the relaxed, but fails the nominal selection. The "electroweak'' (EWK) background refers to the sum of $\mathrm{W} $+jets, DY, and diboson production. The "rare'' backgrounds are defined in the text. The data in this sample agrees with the sum of multijet, EWK, $ {{\mathrm{t}} {\mathrm{\bar{t}}}}$+jets, and rare backgrounds by construction, as the number of multijet events in the fail sample is computed by subtracting the sum of EWK, $ {{\mathrm{t}} {\mathrm{\bar{t}}}}$+jets, and rare background contributions from the data. The misidentification probabilities are derived separately for each era: this figure shows, as an example, the results obtained with the 2017 data set. The uncertainty band represents the total uncertainty after the fit has been performed.

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Figure 6:
Transverse momentum distributions of nonprompt (left) electrons and (right) muons in simulated $ {{\mathrm{t}} {\mathrm{\bar{t}}}}$+jets events, for the three cases "nominal'', "relaxed, $f_{i}$ from $ {{\mathrm{t}} {\mathrm{\bar{t}}}}$+jets'', and "relaxed, $f_{i}$ from multijet'' discussed in text. The figure illustrates that a nonclosure correction needs to be applied to the probabilities $f_{i}$ measured for electrons in data, while no such correction is needed for muons.

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Figure 6-a:
Transverse momentum distributions of nonprompt electrons in simulated $ {{\mathrm{t}} {\mathrm{\bar{t}}}}$+jets events, for the three cases "nominal'', "relaxed, $f_{i}$ from $ {{\mathrm{t}} {\mathrm{\bar{t}}}}$+jets'', and "relaxed, $f_{i}$ from multijet'' discussed in text. The figure illustrates that a nonclosure correction needs to be applied to the probabilities $f_{i}$ measured for electrons in data.

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Figure 6-b:
Transverse momentum distributions of nonprompt muons in simulated $ {{\mathrm{t}} {\mathrm{\bar{t}}}}$+jets events, for the three cases "nominal'', "relaxed, $f_{i}$ from $ {{\mathrm{t}} {\mathrm{\bar{t}}}}$+jets'', and "relaxed, $f_{i}$ from multijet'' discussed in text. The figure illustrates that no nonclosure correction needs to be applied to the probabilities $f_{i}$ measured for muons in data.

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Figure 7:
Distributions of $m_{\mathrm{e} \mathrm{e}}$ for (left) SS and (right) OS electron pairs in $ {{\mathrm{Z} /\gamma ^{*}} \to \mathrm{e} \mathrm{e}}$ candidate events in which both electrons are in the ECAL barrel and have transverse momenta within the range 25 $ < {p_{\mathrm {T}}} < $ 50 GeV, for data recorded in 2018, compared to the expectation. Uncertainties shown are statistical only.

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Figure 7-a:
Distribution of $m_{\mathrm{e} \mathrm{e}}$ for SS electron pairs in $ {{\mathrm{Z} /\gamma ^{*}} \to \mathrm{e} \mathrm{e}}$ candidate events in which both electrons are in the ECAL barrel and have transverse momenta within the range 25 $ < {p_{\mathrm {T}}} < $ 50 GeV, for data recorded in 2018, compared to the expectation. Uncertainties shown are statistical only.

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Figure 7-b:
Distribution of $m_{\mathrm{e} \mathrm{e}}$ for OS electron pairs in $ {{\mathrm{Z} /\gamma ^{*}} \to \mathrm{e} \mathrm{e}}$ candidate events in which both electrons are in the ECAL barrel and have transverse momenta within the range 25 $ < {p_{\mathrm {T}}} < $ 50 GeV, for data recorded in 2018, compared to the expectation. Uncertainties shown are statistical only.

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Figure 8:
Distributions of the activation value of the ANN output node with the highest activation value for events selected in the 2$\ell$SS$+$0${\tau _\mathrm {h}}$ channel and classified as $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ signal (upper left), $ {{\mathrm{t}} {\mathrm{H}}}$ signal (upper right), $ {{\mathrm{t}} {\mathrm{\bar{t}}}\mathrm{W}}$ background (lower left), and other backgrounds (lower right). The distributions expected for the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ signals and for background processes are shown for the values of the parameters of interest and of the nuisance parameters obtained from the ML fit. The best fit value of the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ production rates amounts to $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}} = $ 0.92 and $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{H}}}} = $ 5.7 times the rates expected in the SM.

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Figure 8-a:
Distribution of the activation value of the ANN output node with the highest activation value for events selected in the 2$\ell$SS$+$0${\tau _\mathrm {h}}$ channel and classified as $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ signal. The distributions expected for the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ signals and for background processes are shown for the values of the parameters of interest and of the nuisance parameters obtained from the ML fit. The best fit value of the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ production rates amounts to $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}} = $ 0.92 and $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{H}}}} = $ 5.7 times the rates expected in the SM.

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Figure 8-b:
Distribution of the activation value of the ANN output node with the highest activation value for events selected in the 2$\ell$SS$+$0${\tau _\mathrm {h}}$ channel and classified as $ {{\mathrm{t}} {\mathrm{H}}}$ signal. The distributions expected for the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ signals and for background processes are shown for the values of the parameters of interest and of the nuisance parameters obtained from the ML fit. The best fit value of the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ production rates amounts to $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}} = $ 0.92 and $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{H}}}} = $ 5.7 times the rates expected in the SM.

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Figure 8-c:
Distribution of the activation value of the ANN output node with the highest activation value for events selected in the 2$\ell$SS$+$0${\tau _\mathrm {h}}$ channel and classified as $ {{\mathrm{t}} {\mathrm{\bar{t}}}\mathrm{W}}$ background. The distributions expected for the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ signals and for background processes are shown for the values of the parameters of interest and of the nuisance parameters obtained from the ML fit. The best fit value of the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ production rates amounts to $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}} = $ 0.92 and $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{H}}}} = $ 5.7 times the rates expected in the SM.

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Figure 8-d:
Distribution of the activation value of the ANN output node with the highest activation value for events selected in the 2$\ell$SS$+$0${\tau _\mathrm {h}}$ channel and classified as other backgrounds. The distributions expected for the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ signals and for background processes are shown for the values of the parameters of interest and of the nuisance parameters obtained from the ML fit. The best fit value of the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ production rates amounts to $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}} = $ 0.92 and $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{H}}}} = $ 5.7 times the rates expected in the SM.

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Figure 9:
Distributions of the activation value of the ANN output node with the highest activation value for events selected in the 3$\ell{+}$0${\tau _\mathrm {h}}$ channel and classified as $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ signal (upper left), $ {{\mathrm{t}} {\mathrm{H}}}$ signal (upper right), and background (lower left), and for events selected in the 2$\ell$SS$+$1${\tau _\mathrm {h}}$ channel (lower right). In case of the 2$\ell$SS$+$1${\tau _\mathrm {h}}$ channel, the activation value of the ANN output nodes for $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ signal, $ {{\mathrm{t}} {\mathrm{H}}}$ signal, and background are shown together in a single histogram, concatenating histogram bins as appropriate and enumerating the bins by a monotonously increasing number. The distributions expected for the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ signals and for background processes are shown for the values of the parameters of interest and of the nuisance parameters obtained from the ML fit. The best fit value of the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ production rates amounts to $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}} = $ 0.92 and $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{H}}}} = $ 5.7 times the rates expected in the SM.

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Figure 9-a:
Distributions of the activation value of the ANN output node with the highest activation value for events selected in the 3$\ell{+}$0${\tau _\mathrm {h}}$ channel and classified as $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ signal. The distributions expected for the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ signals and for background processes are shown for the values of the parameters of interest and of the nuisance parameters obtained from the ML fit. The best fit value of the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ production rates amounts to $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}} = $ 0.92 and $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{H}}}} = $ 5.7 times the rates expected in the SM.

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Figure 9-b:
Distributions of the activation value of the ANN output node with the highest activation value for events selected in the 3$\ell{+}$0${\tau _\mathrm {h}}$ channel and classified as $ {{\mathrm{t}} {\mathrm{H}}}$ signal. The distributions expected for the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ signals and for background processes are shown for the values of the parameters of interest and of the nuisance parameters obtained from the ML fit. The best fit value of the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ production rates amounts to $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}} = $ 0.92 and $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{H}}}} = $ 5.7 times the rates expected in the SM.

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Figure 9-c:
Distributions of the activation value of the ANN output node with the highest activation value for events selected in the 3$\ell{+}$0${\tau _\mathrm {h}}$ channel and classified as background. The distributions expected for the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ signals and for background processes are shown for the values of the parameters of interest and of the nuisance parameters obtained from the ML fit. The best fit value of the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ production rates amounts to $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}} = $ 0.92 and $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{H}}}} = $ 5.7 times the rates expected in the SM.

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Figure 9-d:
Distributions of the activation value of the ANN output node with the highest activation value for events selected in the 2$\ell$SS$+$1${\tau _\mathrm {h}}$ channel. The activation value of the ANN output nodes for $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ signal, $ {{\mathrm{t}} {\mathrm{H}}}$ signal, and background are shown together in a single histogram, concatenating histogram bins as appropriate and enumerating the bins by a monotonously increasing number. The distributions expected for the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ signals and for background processes are shown for the values of the parameters of interest and of the nuisance parameters obtained from the ML fit. The best fit value of the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ production rates amounts to $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}} = $ 0.92 and $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{H}}}} = $ 5.7 times the rates expected in the SM.

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Figure 10:
Distributions of the BDT output for events selected in the 1$\ell{+}$1${\tau _\mathrm {h}}$ (upper left), 0$\ell{+}$2${\tau _\mathrm {h}}$ (upper right), and 2$\ell$OS$+$1${\tau _\mathrm {h}}$ (lower) channels. The distributions expected for the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ signals and for background processes are shown for the values of the parameters of interest and of the nuisance parameters obtained from the ML fit. The best fit value of the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ production rates amounts to $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}} = $ 0.92 and $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{H}}}} = $ 5.7 times the rates expected in the SM.

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Figure 10-a:
Distributions of the BDT output for events selected in the 1$\ell{+}$1${\tau _\mathrm {h}}$ channel. The distributions expected for the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ signals and for background processes are shown for the values of the parameters of interest and of the nuisance parameters obtained from the ML fit. The best fit value of the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ production rates amounts to $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}} = $ 0.92 and $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{H}}}} = $ 5.7 times the rates expected in the SM.

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Figure 10-b:
Distributions of the BDT output for events selected in the 0$\ell{+}$2${\tau _\mathrm {h}}$ channel. The distributions expected for the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ signals and for background processes are shown for the values of the parameters of interest and of the nuisance parameters obtained from the ML fit. The best fit value of the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ production rates amounts to $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}} = $ 0.92 and $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{H}}}} = $ 5.7 times the rates expected in the SM.

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Figure 10-c:
Distributions of the BDT output for events selected in the 2$\ell$OS$+$1${\tau _\mathrm {h}}$ channel. The distributions expected for the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ signals and for background processes are shown for the values of the parameters of interest and of the nuisance parameters obtained from the ML fit. The best fit value of the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ production rates amounts to $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}} = $ 0.92 and $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{H}}}} = $ 5.7 times the rates expected in the SM.

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Figure 11:
Distributions of the BDT output used for the signal extraction in the 1$\ell{+}$2${\tau _\mathrm {h}}$ (upper left), 4$\ell{+}$0${\tau _\mathrm {h}}$ (upper right), 3$\ell{+}$1${\tau _\mathrm {h}}$ (lower left), and 2$\ell{+}$2${\tau _\mathrm {h}}$ (lower right) channels. The distributions expected for the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ signals and for background processes are shown for the values of the parameters of interest and of the nuisance parameters obtained from the ML fit. The best fit value of the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ production rates amounts to $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}} = $ 0.92 and $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{H}}}} = $ 5.7 times the rates expected in the SM.

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Figure 11-a:
Distributions of the BDT output used for the signal extraction in the 1$\ell{+}$2${\tau _\mathrm {h}}$ channel. The distributions expected for the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ signals and for background processes are shown for the values of the parameters of interest and of the nuisance parameters obtained from the ML fit. The best fit value of the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ production rates amounts to $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}} = $ 0.92 and $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{H}}}} = $ 5.7 times the rates expected in the SM.

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Figure 11-b:
Distributions of the BDT output used for the signal extraction in the 4$\ell{+}$0${\tau _\mathrm {h}}$ channel. The distributions expected for the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ signals and for background processes are shown for the values of the parameters of interest and of the nuisance parameters obtained from the ML fit. The best fit value of the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ production rates amounts to $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}} = $ 0.92 and $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{H}}}} = $ 5.7 times the rates expected in the SM.

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Figure 11-c:
Distributions of the BDT output used for the signal extraction in the 3$\ell{+}$1${\tau _\mathrm {h}}$ channel. The distributions expected for the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ signals and for background processes are shown for the values of the parameters of interest and of the nuisance parameters obtained from the ML fit. The best fit value of the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ production rates amounts to $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}} = $ 0.92 and $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{H}}}} = $ 5.7 times the rates expected in the SM.

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Figure 11-d:
Distributions of the BDT output used for the signal extraction in the 2$\ell{+}$2${\tau _\mathrm {h}}$ channel. The distributions expected for the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ signals and for background processes are shown for the values of the parameters of interest and of the nuisance parameters obtained from the ML fit. The best fit value of the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ production rates amounts to $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}} = $ 0.92 and $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{H}}}} = $ 5.7 times the rates expected in the SM.

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Figure 12:
Distributions of discriminating observables in the 3$\ell{+}$0${\tau _\mathrm {h}}$ (left) and 4$\ell{+}$0${\tau _\mathrm {h}}$ (right) control region. The distributions expected for the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ signals and for background processes are shown for the values of the parameters of interest and of the nuisance parameters obtained from the ML fit. The best fit value of the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ production rates amounts to $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}} = $ 0.92 and $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{H}}}} = $ 5.7 times the rates expected in the SM.

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Figure 12-a:
Distributions of discriminating observables in the 3$\ell{+}$0${\tau _\mathrm {h}}$ control region. The distributions expected for the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ signals and for background processes are shown for the values of the parameters of interest and of the nuisance parameters obtained from the ML fit. The best fit value of the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ production rates amounts to $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}} = $ 0.92 and $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{H}}}} = $ 5.7 times the rates expected in the SM.

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Figure 12-b:
Distributions of discriminating observables in the 4$\ell{+}$0${\tau _\mathrm {h}}$ control region. The distributions expected for the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ signals and for background processes are shown for the values of the parameters of interest and of the nuisance parameters obtained from the ML fit. The best fit value of the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ production rates amounts to $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}} = $ 0.92 and $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{H}}}} = $ 5.7 times the rates expected in the SM.

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Figure 13:
Distribution of the decimal logarithm of the ratio between the expected $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}+ {{\mathrm{t}} {\mathrm{H}}}$ signal and the expected sum of background contributions in each bin of the 105 distributions that are included in the ML fit used for the signal extraction. The distributions expected for signal and background processes are computed for $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}} = $ 0.92, $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{H}}}} = $ 5.7, and the values of nuisance parameters obtained from the ML fit.

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Figure 14:
Production rate $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}}$ of the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ signal (left) and $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{H}}}}$ of $ {{\mathrm{t}} {\mathrm{H}}}$ signal (right), in units of their rate of production expected in the SM, measured in each of the ten channels individually and for the combination of all channels. The central value of the signal strength in the 2$\ell{+}$2${\tau _\mathrm {h}}$ is constrained to be greater than zero.

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Figure 14-a:
Production rate $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}}$ of the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ signal, in units of their rate of production expected in the SM, measured in each of the ten channels individually and for the combination of all channels. The central value of the signal strength in the 2$\ell{+}$2${\tau _\mathrm {h}}$ is constrained to be greater than zero.

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Figure 14-b:
Production rate $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}}$ of the $ {\hat{\mu}}_{{{\mathrm{t}} {\mathrm{H}}}}$ of $ {{\mathrm{t}} {\mathrm{H}}}$ signal, in units of their rate of production expected in the SM, measured in each of the three channels individually and for the combination of all channels.

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Figure 15:
Two-dimensional contours of the likelihood function $\mathcal {L}$, given by Eq. (3), as a function of the production rates of the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ signals ($ {\mu}_{{{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}}$ and $ {\mu}_{{{\mathrm{t}} {\mathrm{H}}}}$) and of the $ {{\mathrm{t}} {\mathrm{\bar{t}}}\mathrm{Z}}$ and $ {{\mathrm{t}} {\mathrm{\bar{t}}}\mathrm{W}}$ backgrounds ($ {\mu}_{{{\mathrm{t}} {\mathrm{\bar{t}}}\mathrm{Z}}}$ and $ {\mu}_{{{\mathrm{t}} {\mathrm{\bar{t}}}\mathrm{W}}}$). The two production rates that are not shown on either the $x$ or the $y$ axis are profiled such that the function $\mathcal {L}$ attains its minimum at each point in the $x$-$y$ plane.

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Figure 15-a:
Two-dimensional contours of the likelihood function $\mathcal {L}$, given by Eq. (3) ($ {\mu}_{{{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}}$ vs $ {\mu}_{{{\mathrm{t}} {\mathrm{H}}}}$). The production rates that are not shown on either the $x$ or the $y$ axis are profiled such that the function $\mathcal {L}$ attains its minimum at each point in the $x$-$y$ plane.

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Figure 15-b:
Two-dimensional contours of the likelihood function $\mathcal {L}$, given by Eq. (3) ($ {\mu}_{{{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}}$ vs $ {\mu}_{{{\mathrm{t}} {\mathrm{\bar{t}}}\mathrm{W}}}$). The production rates that are not shown on either the $x$ or the $y$ axis are profiled such that the function $\mathcal {L}$ attains its minimum at each point in the $x$-$y$ plane.

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Figure 15-c:
Two-dimensional contours of the likelihood function $\mathcal {L}$, given by Eq. (3) ($ {\mu}_{{{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}}$ vs $ {\mu}_{{{\mathrm{t}} {\mathrm{\bar{t}}}\mathrm{Z}}}$). The production rates that are not shown on either the $x$ or the $y$ axis are profiled such that the function $\mathcal {L}$ attains its minimum at each point in the $x$-$y$ plane.

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Figure 15-d:
Two-dimensional contours of the likelihood function $\mathcal {L}$, given by Eq. (3) ($ {\mu}_{{{\mathrm{t}} {\mathrm{\bar{t}}}\mathrm{Z}}}$ vs $ {\mu}_{{{\mathrm{t}} {\mathrm{\bar{t}}}\mathrm{W}}}$). The production rates that are not shown on either the $x$ or the $y$ axis are profiled such that the function $\mathcal {L}$ attains its minimum at each point in the $x$-$y$ plane.

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Figure 16:
Probability for $ {{\mathrm{t}} {\mathrm{H}}}$ signal events produced by the $ {{{\mathrm{t}} {\mathrm{H}}} {\mathrm{q}}}$ (left) and $ {{{\mathrm{t}} {\mathrm{H}}}\mathrm{W}}$ (right) production process to pass the event selection criteria for the 2$\ell$SS$+$0${\tau _\mathrm {h}}$, 3$\ell{+}$0${\tau _\mathrm {h}}$, and 2$\ell$SS$+$1${\tau _\mathrm {h}}$ channels in each of the Higgs boson decay modes as a function of the ratio $ {\kappa _{{\mathrm{t}}}}/ {\kappa _{\mathrm{V}}}$ of the Higgs boson couplings to the top quark and to the W boson.

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Figure 16-a:
Probability for $ {{\mathrm{t}} {\mathrm{H}}}$ signal events produced by the $ {{{\mathrm{t}} {\mathrm{H}}} {\mathrm{q}}}$ production process to pass the event selection criteria for the 2$\ell$SS$+$0${\tau _\mathrm {h}}$, 3$\ell{+}$0${\tau _\mathrm {h}}$, and 2$\ell$SS$+$1${\tau _\mathrm {h}}$ channels in each of the Higgs boson decay modes as a function of the ratio $ {\kappa _{{\mathrm{t}}}}/ {\kappa _{\mathrm{V}}}$ of the Higgs boson couplings to the top quark and to the W boson.

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Figure 16-b:
Probability for $ {{\mathrm{t}} {\mathrm{H}}}$ signal events produced by the $ {{{\mathrm{t}} {\mathrm{H}}}\mathrm{W}}$ production process to pass the event selection criteria for the 2$\ell$SS$+$0${\tau _\mathrm {h}}$, 3$\ell{+}$0${\tau _\mathrm {h}}$, and 2$\ell$SS$+$1${\tau _\mathrm {h}}$ channels in each of the Higgs boson decay modes as a function of the ratio $ {\kappa _{{\mathrm{t}}}}/ {\kappa _{\mathrm{V}}}$ of the Higgs boson couplings to the top quark and to the W boson.

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Figure 17:
Dependence of the likelihood function $\mathcal {L}$ in Eq. (3), as a function of $ {\kappa _{{\mathrm{t}}}}$, profiling over $ {\kappa _{\mathrm{V}}}$ (left), and as a function of $ {\kappa _{{\mathrm{t}}}}$ and $ {\kappa _{\mathrm{V}}}$ (right).

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Figure 17-a:
Dependence of the likelihood function $\mathcal {L}$ in Eq. (3), as a function of $ {\kappa _{{\mathrm{t}}}}$, profiling over $ {\kappa _{\mathrm{V}}}$.

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Figure 17-b:
Dependence of the likelihood function $\mathcal {L}$ in Eq. (3), as a function of $ {\kappa _{{\mathrm{t}}}}$ and $ {\kappa _{\mathrm{V}}}$.
Tables

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Table 1:
Standard model cross sections for the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ signals as well as for the most relevant background processes. The cross sections are quoted for pp collisions at $\sqrt {s} = $ 13 TeV. The quoted value for DY production includes a generator-level requirement of $m_{\mathrm{Z} /\gamma ^*} > $ 50 GeV.

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Table 2:
Event selections applied in the 2$\ell$SS$+$0${\tau _\mathrm {h}}$, 2$\ell$SS$+$1${\tau _\mathrm {h}}$, 3$\ell{+}$0${\tau _\mathrm {h}}$, and 3$\ell{+}$1${\tau _\mathrm {h}}$ channels. The ${p_{\mathrm {T}}}$ thresholds applied to the lepton of highest, second-highest, and third-highest ${p_{\mathrm {T}}}$ are separated by slashes. The symbol "--'' indicates that no requirement is applied.

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Table 3:
Event selections applied in the 0$\ell{+}$2${\tau _\mathrm {h}}$, 1$\ell{+}$1${\tau _\mathrm {h}}$, 1$\ell{+}$2${\tau _\mathrm {h}}$, and 2$\ell{+}$2${\tau _\mathrm {h}}$ channels. The ${p_{\mathrm {T}}}$ thresholds applied to the lepton and to the $ {\tau _\mathrm {h}} $ of highest and second-highest ${p_{\mathrm {T}}}$ are separated by slashes. The symbol "--'' indicates that no requirement is applied.

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Table 4:
Event selections applied in the 2$\ell$OS$+$1${\tau _\mathrm {h}}$ and 4$\ell{+}$0${\tau _\mathrm {h}}$ channels. The symbol "--'' indicates that no requirement is applied.

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Table 5:
Input variables to the multivariant discriminants in each of the ten analysis channels. The symbol "--'' indicates that the variable is not used.

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Table 6:
Number of events selected in the $3 {\ell}$- and $4 {\ell}$-CRs and in the CR for the $ {{\mathrm{t}} {\mathrm{\bar{t}}}\mathrm{W} (\mathrm{W})}$ background, compared to the event yields expected from different types of background and from the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ and $ {{\mathrm{t}} {\mathrm{H}}}$ signals, after the fit to data is performed as described in Section 9. Uncertainties shown include all systematic components. The symbol "--'' indicates that the corresponding background does not apply.

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Table 7:
Summary of the sources of systematic and statistical uncertainties and their impact on the measurement of the $ {{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}$ plus $ {{\mathrm{t}} {\mathrm{H}}}$ signal rate $ {\mu}_{{{\mathrm{t}} {\mathrm{\bar{t}}} {\mathrm{H}}}+ {{\mathrm{t}} {\mathrm{H}}}}$, and the measured value of the unconstrained nuisance parameters. The quantity $\Delta {\mu}_{x}/ {\mu}_{x}$ corresponds to the change in uncertainty when fixing the nuisance parameters associated with that uncertainty in the fit. Under the label "MC and sideband statistical uncertainty'' are the uncertainties associated with the limited number of simulated MC events and the amount of data events in the application region of the MP method.
Summary
The rate for Higgs boson production in association with either one or two top quarks has been measured in events containing multiple electrons, muons, and hadronically decaying tau leptons, using data recorded by the CMS experiment in pp collisions at $\sqrt{s} = $ 13 TeV in 2016, 2017, and 2018. The analyzed data corresponds to an integrated luminosity of 137 fb$^{-1}$. Ten different experimental signatures are considered in the analysis, differing by the multiplicity of electrons, muons, and hadronically decaying tau leptons, and targeting events in which the Higgs boson decays via $\mathrm{H} \to \mathrm{W}\mathrm{W}$, $\mathrm{H} \to \tau\tau$, or $\mathrm{H} \to \mathrm{Z}\mathrm{Z}$, whereas the top quark(s) decay either semi-leptonically or hadronically. The measured production rates for the ${\mathrm{t}}{\mathrm{\bar{t}}}\mathrm{H}$ and $\mathrm{tH}$ signals amount to 0.92 $\pm$ 0.19 (stat) $^{+0.17}_{-0.13}$ (syst) and 5.7 $\pm$ 2.7 (stat) $\pm$ 3.0 (syst) times their respective standard model (SM) expectations. The corresponding observed (expected) significance amounts to 4.7 (5.2) standard deviations for $\mathrm{t}\mathrm{\bar{t}}\mathrm{H}$, and to $1.4$ ($0.3$) for $\mathrm{t}\mathrm{H}$ production. Assuming that the Higgs boson coupling to the tau lepton is equal in strength to the values expected in the SM, the coupling $y_{{\mathrm{t}}}$ of the Higgs boson to the top quark divided by its SM expectation, ${\kappa_{{\mathrm{t}}}}=y_{{\mathrm{t}}}/y_{{\mathrm{t}}}^{\mathrm{SM}}$, is constrained to be within $-0.9 < {\kappa_{{\mathrm{t}}}} < -0.7$ or $0.7 < {\kappa_{{\mathrm{t}}}} < 1.1$, at 95% confidence level. This result is the most sensitive measurement of the ${\mathrm{t}}{\mathrm{\bar{t}}}\mathrm{H}$ production rate to date.
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Compact Muon Solenoid
LHC, CERN