Fast b-tagging at the high-level trigger of the ATLAS experiment in LHC Run 3


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Aad G., Abbott B., Abeling K., Abicht N., Abidi S., Aboulhorma A., ...Daha Fazla

Journal of Instrumentation, cilt.18, sa.11, 2023 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 18 Sayı: 11
  • Basım Tarihi: 2023
  • Doi Numarası: 10.1088/1748-0221/18/11/p11006
  • Dergi Adı: Journal of Instrumentation
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, Index Islamicus, INSPEC
  • Anahtar Kelimeler: Trigger algorithms, Trigger concepts and systems (hardware and software)
  • Ankara Üniversitesi Adresli: Evet

Özet

The ATLAS experiment relies on real-time hadronic jet reconstruction and b-tagging to record fully hadronic events containing b-jets. These algorithms require track reconstruction, which is computationally expensive and could overwhelm the high-level-trigger farm, even at the reduced event rate that passes the ATLAS first stage hardware-based trigger. In LHC Run 3, ATLAS has mitigated these computational demands by introducing a fast neural-network-based b-tagger, which acts as a low-precision filter using input from hadronic jets and tracks. It runs after a hardware trigger and before the remaining high-level-trigger reconstruction. This design relies on the negligible cost of neural-network inference as compared to track reconstruction, and the cost reduction from limiting tracking to specific regions of the detector. In the case of Standard Model HH → bb̄bb̄, a key signature relying on b-jet triggers, the filter lowers the input rate to the remaining high-level trigger by a factor of five at the small cost of reducing the overall signal efficiency by roughly 2%.