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| CMS-PAS-HIG-18-019 | ||
| Measurement of the associated production of a Higgs boson with a top quark pair in final states with electrons, muons and hadronically decaying $\tau$ leptons in data recorded in 2017 at $\sqrt{s} = $ 13 TeV | ||
| CMS Collaboration | ||
| November 2018 | ||
| Abstract: The production of a Higgs boson in association with a top quark pair ($\mathrm{t}\overline{\mathrm{t}}\mathrm{H}$) is measured in final states with electrons, muons and hadronically decaying $\tau$ leptons. Events are selected from a sample of proton-proton collisions at a $\sqrt{s} = $ 13 TeV center-of-mass energy, recorded by the CMS experiment in 2017 and corresponding to an integrated luminosity of 41.5 fb$^{-1}$. Machine learning and matrix element methods are used to optimize the analysis sensitivity. The observed (expected) $\mathrm{t}\overline{\mathrm{t}}\mathrm{H}$ production rate is 0.75$^{+0.46}_{-0.43}$ (1.00$^{+0.39}_{-0.35}$) times the expected rate in the standard model, which corresponds to an observed (expected) significance of 1.7$\sigma$ (2.9$\sigma$). In addition, these results are combined with those previously obtained from the data set collected in 2016 and corresponding to an integrated luminosity of 35.9 fb$^{-1}$. The observed (expected) signal rate for the combined fit is 0.96$^{+0.34}_{-0.31}$ (1.00$^{+0.30}_{-0.27}$) times the expected rate in the standard model, which corresponds to an observed (expected) significance of 3.2$\sigma$ (4.0$\sigma$). | ||
| Links: CDS record (PDF) ; inSPIRE record ; CADI line (restricted) ; | ||
| Figures | |
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Figure 1:
An example Feynman diagram for $ {\mathrm {t}} {\overline {\mathrm {t}}} {{\mathrm {H}}}$ production, followed by $ {{\mathrm {H}}}$ boson decay into a $ {\tau}$ pair [6]. |
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Figure 2:
Distributions in the discriminating observables used for the signal extraction in the $2 {\ell} {\text {ss}}$ and $3 {\ell}$ categories. Post-fit yields and uncertainties for the $ {{{\mathrm {t}}} {{\overline {\mathrm {t}}}} {{\mathrm {H}}}}$ signal and the background processes are shown. In (a) and (c) the distributions for the $2 {\ell} {\text {ss}}$ and $3 {\ell}$ sub-categories are shown; the x-axis labels "bl'' and "bt'' stand for "b-tag loose'' and "b-tag tight'', respectively. Further details are given in Section 7.2.1. |
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Figure 2-a:
The distributions for the $2 {\ell} {\text {ss}}$ sub-categories are shown. Further details are given in Section 7.2.1. |
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Figure 2-b:
Distribution in the discriminating observable used for the signal extraction in the $2 {\ell} {\text {ss}}$ categories. Post-fit yields and uncertainties for the $ {{{\mathrm {t}}} {{\overline {\mathrm {t}}}} {{\mathrm {H}}}}$ signal and the background processes are shown. Further details are given in Section 7.2.1. |
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Figure 2-c:
The $3 {\ell}$ sub-categories are shown; the x-axis labels "bl'' and "bt'' stand for "b-tag loose'' and "b-tag tight'', respectively. Further details are given in Section 7.2.1. |
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Figure 2-d:
Distribution in the discriminating observables used for the signal extraction in the $3 {\ell}$ categories. Post-fit yields and uncertainties for the $ {{{\mathrm {t}}} {{\overline {\mathrm {t}}}} {{\mathrm {H}}}}$ signal and the background processes are shown. Further details are given in Section 7.2.1. |
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Figure 3:
Distributions in the discriminating observables used for the signal extraction in (a) the $1 {\ell}+2 {{\tau}_{\mathrm {h}}} $, (b) the $2 {\ell}+2 {{\tau}_{\mathrm {h}}} $, (c) the $2 {\ell}ss+1 {{\tau}_{\mathrm {h}}} $, and (d) $3 {\ell}+1 {{\tau}_{\mathrm {h}}} $ categories. Post-fit yields and uncertainties for the $ {{{\mathrm {t}}} {{\overline {\mathrm {t}}}} {{\mathrm {H}}}}$ signal and the background processes are shown. |
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Figure 3-a:
Distributions in the discriminating observables used for the signal extraction in the $1 {\ell}+2 {{\tau}_{\mathrm {h}}} $ category. Post-fit yields and uncertainties for the $ {{{\mathrm {t}}} {{\overline {\mathrm {t}}}} {{\mathrm {H}}}}$ signal and the background processes are shown. |
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Figure 3-b:
Distributions in the discriminating observables used for the signal extraction in the $2 {\ell}+2 {{\tau}_{\mathrm {h}}} $ category. Post-fit yields and uncertainties for the $ {{{\mathrm {t}}} {{\overline {\mathrm {t}}}} {{\mathrm {H}}}}$ signal and the background processes are shown. |
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Figure 3-c:
Distributions in the discriminating observables used for the signal extraction in the $2 {\ell}ss+1 {{\tau}_{\mathrm {h}}} $ category. Post-fit yields and uncertainties for the $ {{{\mathrm {t}}} {{\overline {\mathrm {t}}}} {{\mathrm {H}}}}$ signal and the background processes are shown. |
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Figure 3-d:
Distributions in the discriminating observables used for the signal extraction in the $3 {\ell}+1 {{\tau}_{\mathrm {h}}} $ category. Post-fit yields and uncertainties for the $ {{{\mathrm {t}}} {{\overline {\mathrm {t}}}} {{\mathrm {H}}}}$ signal and the background processes are shown. |
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Figure 4:
Measured signal rates, normalized to the SM $ {\mathrm {t}} {\overline {\mathrm {t}}} {{\mathrm {H}}}$ production rate, for the individual categories and for the combination of all seven categories. |
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Figure 5:
95% CL upper limits on the signal-rate multiplier, $\mu $, obtained for the individual categories and for the combination of all seven categories. |
| Tables | |
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Table 1:
List of event generators used to produce samples for signal and background processes. |
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Table 2:
Event selections applied in the $2 {\ell} {\text {ss}}$, $2 {\ell} {\text {ss}}+ 1 {{\tau}_{\mathrm {h}}} $, $1 {\ell}+ 2 {{\tau}_{\mathrm {h}}} $ and $2 {\ell}+ 2 {{\tau}_{\mathrm {h}}} $ categories. |
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Table 3:
Event selections applied in the $3 {\ell}$, $3 {\ell}+1 {{\tau}_{\mathrm {h}}} $ and $4 {\ell}$ categories. |
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Table 4:
Variables used in the multivariate discriminators for the channels with and without taus. Only one multivariate discriminant is used in categories with ${{\tau}_{\mathrm {h}}}$. For the categories without ${{\tau}_{\mathrm {h}}}$, two different multivariate discriminants are constructed, each one providing better discrimination against a specific background process. The $cos(\theta)^*$ between leading and trailing ${{{\tau}_{\mathrm {h}}}}$s is measured in the rest frame of the ${{\tau}_{\mathrm {h}}}$ pair. Masses of ${{\ell}}$s $+$ leading ${{\tau}_{\mathrm {h}}}$, in the $3 {\ell}+ 1 {{\tau}_{\mathrm {h}}} $ category, are constructed based on the leptons that have opposite signs to ${{\tau}_{\mathrm {h}}}$. |
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Table 5:
Summary of the main sources of systematic uncertainty and their impact on the measured signal rate. The $\Delta \mu $/$\mu $ column shows the approximate relative shift in signal rate when varying the systematic uncertainty source by its value. Impacts are shown both for the 2017 analysis and for the 2016 + 2017 combined analysis. A general indication on the treatment of their correlations between the 2016 and 2017 samples in the combined analysis is also given. |
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Table 6:
The selected number of events in categories based on leptons and hadronic $\tau $s ($ {{\tau}_{\mathrm {h}}} $). The numbers in row "SM expectation'' also include $ {{{\mathrm {t}}} {{\overline {\mathrm {t}}}} {{\mathrm {H}}}}$ process. The rates are adjusted using the maximum-likelihood fit (post-fit). |
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Table 7:
The measured and expected signal rates are presented as signal-rate multipliers, $\mu $, which are normalized to the SM $ {\mathrm {t}} {\overline {\mathrm {t}}} {{\mathrm {H}}}$ production rate, for the individual categories and for the combination of all seven categories. In addition, a combination with the results obtained from the 2016 dataset [6] is made and added to the table. The * indicates that a lower boundary was introduced in the allowed $\mu $ range to improve the fit convergence properties in the low-yield $2 {\ell}+ 2 {{\tau}_{\mathrm {h}}} $ category. |
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Table 8:
95% CL upper limits on the signal-rate multiplier, $\mu $, obtained for the individual categories and for the combination of all seven categories. In addition, a combination with the results obtained from the 2016 dataset [6] is made and added to the table. The observed limit is compared to the expected limits for the background-only hypothesis ($\mu = $ 0) and for the hypothesis where the SM $ {{{\mathrm {t}}} {{\overline {\mathrm {t}}}} {{\mathrm {H}}}}$ process is expected ($\mu = $ 1). |
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Table 9:
Selected number of events in the $1 {\ell}+ 2 {{\tau}_{\mathrm {h}}} $, $2 {\ell}ss + 1 {{\tau}_{\mathrm {h}}} $, $2 {\ell}+ 2 {{\tau}_{\mathrm {h}}} $, and $3 {\ell}+ 1 {{\tau}_{\mathrm {h}}} $ categories. The "SM expectation'' row also includes the $ {{{\mathrm {t}}} {{\overline {\mathrm {t}}}} {{\mathrm {H}}}}$ process. The rates are adjusted using the maximum-likelihood fit (post-fit). |
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Table 10:
Selected number of events in the $2 {\ell}ss$ subcategories. The "SM expectation'' row also includes the $ {{{\mathrm {t}}} {{\overline {\mathrm {t}}}} {{\mathrm {H}}}}$ process. The rates are adjusted using the maximum-likelihood fit (post-fit). |
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Table 11:
Selected number of events in the $2 {\ell}ss$ control regions. The "SM expectation'' row also includes the $ {{{\mathrm {t}}} {{\overline {\mathrm {t}}}} {{\mathrm {H}}}}$ process. The rates are adjusted using the maximum-likelihood fit (post-fit). |
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Table 12:
Selected number of events in the $3 {\ell}$ and $4 {\ell}$ categories. The "SM expectation'' row also includes the $ {{{\mathrm {t}}} {{\overline {\mathrm {t}}}} {{\mathrm {H}}}}$ process. The rates are adjusted using the maximum-likelihood fit (post-fit). |
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Table 13:
Selected number of events in the $3 {\ell}$ and $4 {\ell}$ control regions. The "SM expectation'' row also includes the $ {{{\mathrm {t}}} {{\overline {\mathrm {t}}}} {{\mathrm {H}}}}$ process. The rates are adjusted using the maximum-likelihood fit (post-fit). |
| Summary |
| A measurement of the production of a Higgs boson in association with a top quark pair in final states with electrons, muons and hadronically decaying $\tau$ leptons has been presented. Events from the sample of proton-proton collisions recorded by the CMS experiment in 2017 are categorized according to the number of leptons and ${\tau_\mathrm{h}}$. Machine learning and matrix element methods are used to optimize the analysis sensitivity. A $\mathrm{t}\overline{\mathrm{t}}\mathrm{H}$ production rate of 0.75$^{+0.46}_{-0.43}$ (1.00$^{+0.39}_{-0.35}$) times the SM expectation is observed (expected), corresponding to a significance of 1.7$\sigma$ ($2.9\sigma$). These results are combined with those obtained from the data set collected in 2016 and reported in Ref. [6]. The combined fit yields an observed (expected) signal rate of 0.96$^{+0.34}_{-0.31}$ (1.00$^{+0.30}_{-0.27}$) times the SM expectation, which corresponds to a significance of 3.2$\sigma$ (4.0$\sigma$). All results are consistent with the SM expectation. |
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Compact Muon Solenoid LHC, CERN |
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