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


Aad, G ORCID: 0000-0002-6665-4934, Abbott, B ORCID: 0000-0002-5888-2734, Abeling, K ORCID: 0000-0002-1002-1652, Abicht, NJ ORCID: 0000-0001-5763-2760, Abidi, SH ORCID: 0000-0002-8496-9294, Aboulhorma, A ORCID: 0000-0002-9987-2292, Abramowicz, H ORCID: 0000-0001-5329-6640, Abreu, H ORCID: 0000-0002-1599-2896, Abulaiti, Y ORCID: 0000-0003-0403-3697, Abusleme Hoffman, AC ORCID: 0000-0003-0762-7204 et al (show 2923 more authors) (2023) Fast b-tagging at the high-level trigger of the ATLAS experiment in LHC Run 3. Journal of Instrumentation, 18 (11). P11006-P11006.

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Abstract

<jats:title>Abstract</jats:title> <jats:p>The ATLAS experiment relies on real-time hadronic jet reconstruction and <jats:italic>b</jats:italic>-tagging to record fully hadronic events containing <jats:italic>b</jats:italic>-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 <jats:italic>b</jats:italic>-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 <jats:italic>HH → bb̅bb̅</jats:italic>, a key signature relying on <jats:italic>b</jats:italic>-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%.</jats:p>

Item Type: Article
Divisions: Faculty of Health and Life Sciences
Faculty of Science and Engineering > School of Physical Sciences
Faculty of Health and Life Sciences > Institute of Systems, Molecular and Integrative Biology
Depositing User: Symplectic Admin
Date Deposited: 16 Feb 2024 09:44
Last Modified: 16 Mar 2024 02:51
DOI: 10.1088/1748-0221/18/11/p11006
Open Access URL: https://iopscience.iop.org/article/10.1088/1748-02...
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3178729
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