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

Collaboration
Jun 16, 2023
37 pages
Published in:
  • JINST 18 (2023) 11, P11006
  • Published: Nov 10, 2023
e-Print:
Report number:
  • CERN-EP-2023-111
Experiments:

Citations per year

202320242025114
Abstract: (IOP)
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. In the case of Standard Model HH → bb̅bb̅, a key signature relying on b-jet triggers, the filter lowers the input rate to the remaininghigh-level trigger by a factor of five at the small cost of reducingthe overall signal efficiency by roughly 2%.
Note:
  • Trigger algorithms
  • Trigger concepts and systems (hardware and software)
  • p p: scattering
  • p p: colliding beams
  • Higgs particle: pair production
  • Higgs particle: hadronic decay
  • bottom: pair production
  • jet: hadronic
  • trigger: hardware
  • jet: trigger