0583128 - FZÚ 2024 RIV US eng J - Journal Article
Aad, G. - Abbott, B. - Abeling, K. - Chudoba, Jiří - Federičová, Pavla - Hejbal, Jiří - Jačka, Petr - Kepka, Oldřich - Kroll, Jiří - Kupčo, Alexander - Latoňová, Věra - Lokajíček, Miloš - Lysák, Roman - Marčišovský, Michal - Mikeštíková, Marcela - Němeček, Stanislav - Šícho, Petr - Staroba, Pavel - Svatoš, Michal - Taševský, Marek … Total 2900 authors
Fast b-tagging at the high-level trigger of the ATLAS experiment in LHC Run 3.
Journal of Instrumentation. Roč. 18, č. 11 (2023), č. článku P11006. ISSN 1748-0221. E-ISSN 1748-0221
R&D Projects: GA MŠMT LM2023040
Institutional support: RVO:68378271
Keywords : trigger algorithms * trigger concepts and systems (hardware and software) * p p: scattering
OECD category: Particles and field physics
Impact factor: 1.3, year: 2023 ; AIS: 0.425, rok: 2023
Method of publishing: Open access
DOI: https://doi.org/10.1088/1748-0221/18/11/P11006

The ATLAS experiment relies on real-time hadronic jetreconstruction and b-tagging to record fully hadronic eventscontaining b-jets. These algorithms require track reconstruction,which is computationally expensive and could overwhelm thehigh-level-trigger farm, even at the reduced event rate that passesthe ATLAS first stage hardware-based trigger. In LHC Run 3, ATLAShas mitigated these computational demands by introducing a fastneural-network-based b-tagger, which acts as a low-precisionfilter using input from hadronic jets and tracks. It runs after ahardware trigger and before the remaining high-level-triggerreconstruction. This design relies on the negligible cost ofneural-network inference as compared to track reconstruction, andthe cost reduction from limiting tracking to specific regions of thedetector.
Permanent Link: https://hdl.handle.net/11104/0351119