\begin{document}$b\overline{b} /c\overline{c} /gg$\end{document} and \begin{document}$\tau\overline{\tau} /WW^{*} /ZZ^{*} $\end{document}, where the W or Z bosons decay hadronically, are presented in the context of the CEPC experiment, assuming a scenario with 5600 fb−1 of collision data at a center-of-mass energy of 240 GeV. In this study the Higgs bosons are produced in association with a Z boson, with the Z boson decaying into a pair of muons \begin{document}$(\mu^{+}\mu^{-})$\end{document}, which have high efficiency and resolution. To separate all decay channels simultaneously with high accuracy, the Particle Flow Network (PFN), a graph-based machine learning model, is considered. The precise classification provided by the PFN is employed in measuring the branching fractions using the migration matrix method, which accurately corrects for detector effects in each decay channel. The statistical uncertainty of the measured branching ratio is estimated to be 0.55% in the\begin{document}$H\to b\overline{b}$\end{document} final state and approximately 1.5% − 16% in the \begin{document}$H\to c\overline{c} /gg/\tau\overline{\tau}/WW^{*} /ZZ^{*} $\end{document} final states. In addition, the main sources of systematic uncertainties in the measurement of the branching fractions are discussed."> Measurements of decay branching fractions of the Higgs boson to hadronic final states at the CEPC -
  • [1]

    G. Aad, T. Abajyan, B. Abbottet al., Phys. Lett. B716, 1 (2012)

  • [2]

    S. Chatrchyan, V. Khachatryan, A. Sirunyanet al., Phys. Lett. B716, 30 (2012)

  • [3]

    ERN and A. Gerbershagen,A Multi-TeV Linear Collider Based on CLIC Technology: CLIC Conceptual Design Report, CERN Yellow Reports: Monographs (CERN, 2012), ISBN 978-92-9083-379-6.

  • [4]

    A. Abada, M. Abbrescia, S. AbdusSalamet al., Eur. Phys. J. Spec. Top.228, 261 (2019)

  • [5]

    H. Baer, T. Barklow, K. Fujiiet al.,The international linear collider technical design report - volume 2: Physics (2013), arXiv: 1306.6352

  • [6]

    T. C. S. Group,CEPC Conceptual Design Report: Volume 1 - Accelerator (2018), arXiv: 1809.00285

  • [7]

    T. C. S. Group,CEPC Conceptual Design Report: Volume 2 - Physics Detector (2018), arXiv: 1811.10545

  • [8]

    LHC Higgs Cross Section Working Group,Handbook of LHC Higgs Cross Sections: 1. Inclusive Observables (2011), arXiv: 1101.0593

  • [9]

    LHC Higgs Cross Section Working Group,Handbook of LHC Higgs Cross Sections: 2. Differential Distributions (2012), arXiv: 1201.3084

  • [10]

    LHC Higgs Cross Section Working Group,Handbook of LHC Higgs Cross Sections: 3. Higgs Properties (2013), arXiv: 1307.1347

  • [11]

    G. Aadet al. (ATLAS), Nature607, 52 (2022) [Erratum: Nature612, E24 (2022)], arXiv: 2207.00092

  • [12]

    P. T. Komiske, E. M. Metodiev, and J. Thaler, JHEP01, 121 (2019) ISSN 1029-8479

  • [13]

    W. Kilian, T. Ohl, and J. Reuter, Eur. Phys. J. C 71 (2011), ISSN 1434-6052

  • [14]

    T. Sjöstrand, S. Mrenna, and P. Skands, JHEP05, 026 (2006), arXiv: hep-ph/0603175

  • [15]

    J. de Favereau, C. Delaere, P. Deminet al., JHEP02, 057 (2014), ISSN 1029-8479

  • [16]

    Y. Bai, C. H. Chen, Y. Q. Fanget al., Chin. Phys. C44, 013001 (2020)

  • [17]

    H. Qu and L. Gouskos, Phys. Rev. D101, 056019 (2020), ISSN 2470-0029

  • [18]

    H. Qu, C. Li, and S. Qian,Particle transformer for jet tagging(2022), arXiv: 2202.03772

  • [19]

    M. Zaheer, S. Kottur, S. Ravanbakhshet al.,Deep sets(2018), arXiv: 1703.06114

  • [20]

    K. He, X. Zhang, S. Renet al.,Delving deep into rectifiers: Surpassing human-level performance on imagenet classification (2015), arXiv: 1502.01852

  • [21]

    D. P. Kingma and J. Ba,Adam: A method for stochastic optimization (2017), arXiv: 1412.6980

  • [22]

    L. van der Maaten and G. E. Hinton, Journal of Machine Learning Research9, 2579 (2008)

  • [23]

    G. Li, L. Liao, X. Louet al., Chin. Phys. C46, 113001 (2022)

Baidu
map