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Application of Machine Learning for the Analysis of Higgs Boson Production in Association with Single Top-Quark

  • PHYSICS OF ELEMENTARY PARTICLES AND ATOMIC NUCLEI. EXPERIMENT
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Abstract

This work describes results of application of a neural network for the classification of the Higgs boson in association with a single top quark signal production \(pp \to tH\) and the main background processes \(pp \to tt,ttH,ttW,ttZ\) production at the LHC in the ATLAS experiment. The tH channel is sensitive to the sign of the tH-coupling unlike the ttH. Also, an accurate measurement of the Higgs-top coupling is sensitive to the Beyond the Standard Model physics [1, 2].

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REFERENCES

  1. F. Demartin, F. Maltoni, K. Mawatari, and M. Zaro, “Higgs production in association with a single top-quark at the LHC,” (2015). arXiv:1504.00611.

  2. M. Kraus, T. Martini, S. Peitzsch, and P. Uwer, “Exploring BSM Higgs couplings in single top-quark production,” (2022). arXiv:1908.09100.

  3. C. Grojean, “Higgs physics,” (2017). arXiv: 1708.00794v1.

  4. Keras. https://keras.io/https://keras.io/.

  5. TMVA. https://root.cern/manual/tmva/https:// root.cern/manual/tmva/.

  6. ROOT. https://root.cern/https://root.cern/.

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Authors and Affiliations

  1. Joint Institute for Nuclear Research, 141980, Dubna, Moscow oblast, Russia

    A. R. Didenko

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  1. A. R. Didenko
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Correspondence to A. R. Didenko.

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Didenko, A.R. Application of Machine Learning for the Analysis of Higgs Boson Production in Association with Single Top-Quark. Phys. Part. Nuclei Lett. 20, 1169–1172 (2023). https://doi.org/10.1134/S1547477123050229

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  • DOI: https://doi.org/10.1134/S1547477123050229

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