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2026 article

Performance of heavy-flavour jet identification in the CMS high-level trigger in proton-proton collisions at $ \sqrt{s}= $ 13.6 TeV

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The CMS trigger system plays a crucial role during data taking, reducing the large collision rate delivered by the LHC to a few kHz for data storage and subsequent off\-line analysis. The system aims to maintain a high selection efficiency for a wide range of processes, including those involving jets originating from heavy-flavour quarks (b and c), which provide a distinctive signature in many physics analyses. To achieve this while maintaining a sustainable trigger output rate, dedicated jet flavour identification methods are developed and optimized for use in the high-level trigger (HLT). This paper presents the design, commissioning, and performance of deep-learning-based jet identification algorithms deployed in the HLT during 2022--2024, for proton-proton collisions at $ \sqrt{s}= $ 13.6 TeV. The new algorithms enabled significant improvements in signal efficiency for a variety of key physics processes, including the non-resonant production of Higgs boson pairs decaying to four b quarks, as well as Higgs boson production via both vector boson fusion and in association with a $ \mathrm{t} \overline{\mathrm{t}} $ pair, in the $ {\mathrm{H} \to \mathrm{b}\overline{\mathrm{b}}} $ and $ {\mathrm{H} \to \mathrm{c}\overline{\mathrm{c}}} $ decay channels.

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Sujets associés

Particle physics theoretical and experimental studiesParticle Detector Development and PerformanceAstrophysics and Cosmic Phenomena

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