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

Date

01-11-2023

Authors

Aad G.
Abbott B.
Abeling K.
Abicht N. J.
Abidi S. H.
Aboulhorma A.
Abramowicz H.
Abreu H.
Abulaiti Y.
Abusleme Hoffman A. C.

Journal Title

Journal ISSN

Volume Title

Publisher

IOP Publishing Ltd

Abstract

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 -> b (b) over barb (b) over bar, 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%.

Description

Keywords

Trigger algorithms, Trigger concepts and systems (hardware and software)

Citation