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Institut Jožef Stefan, Ljubljana (IJS)
  • New graph-neural-network flavor tagger for Belle II and measurement of ▫$\sin 2\phi_1$▫ in ▫$B^0 \to J/\psi K_S^0$▫ decays
    Adachi, Ichiro ...
    We present GFlaT, a new algorithm that uses a graph-neural-network to determine the flavor of neutral 𝐵 mesons produced in ϒ⁡(4⁢𝑆) decays. It improves previous algorithms by using the information ... from all charged final-state particles and the relations between them. We evaluate its performance using 𝐵 decays to flavor-specific hadronic final states reconstructed in a 362  fb−1 sample of electron-positron collisions collected at the ϒ⁡(4⁢𝑆) resonance with the Belle II detector at the SuperKEKB collider. We achieve an effective tagging efficiency of (37.40±0.43±0.36%), where the first uncertainty is statistical and the second systematic, which is 18% better than the previous Belle II algorithm. Demonstrating the algorithm, we use 𝐵0→𝐽/𝜓⁢𝐾0 S decays to measure the mixing-induced and direct 𝐶⁢𝑃 violation parameters, 𝑆=(0.724±0.035±0.009) and 𝐶=(−0.035±0.026±0.029).
    Vir: Physical review. D. [Elektronski vir]. - ISSN 2470-0029 (Vol. 110, [article no.] 012001, no. 1, 2024, str. 012001-1-012001-14)
    Vrsta gradiva - e-članek ; neleposlovje za odrasle
    Leto - 2024
    Jezik - angleški
    COBISS.SI-ID - 202274307

    Povezava(-e):

    https://journals.aps.org/prd/abstract/10.1103/PhysRevD.110.012001
    DOI

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