@Article{ATLASCollaborationAad_etal2023,
author="ATLAS Collaboration (Aad, G. et al
and Akiot, A.
and Amos, K. R.
and Aparisi Pozo, J. A.
and Bailey, A. J.
and Bouchhar, N.
and Cabrera Urban, S.
and Cantero, J.
and Cardillo, F.
and Castillo Gimenez, V.
and Chitishvili, M.
and Costa, M. J.
and Didenko
and Escobar, C.
and Fiorini, L.
and Fullana Torregrosa, E.
and Fuster, J.
and Garcia, C.
and Garcia Navarro, J. E.
and Gomez Delegido, A. J.
and Gonzalez de la Hoz, S.
and Gonzalvo Rodriguez, G. R.
and Guerrero Rojas, J. G. R.
and Lacasta, C.
and Marti-Garcia, S.
and Martinez Agullo, P.
and Miralles Lopez, M.
and Mitsou, V. A.
and Monsonis Romero, L.
and Moreno Llacer, M.
and Munoz Perez, D.
and Navarro-Gonzalez, J.
and Poveda, J.
and Prades Iba{\~{n}}ez, A.
and Rubio Jimenez, A.
and Ruiz-Martinez, A.
and Sabatini, P.
and Salt, J.
and Sanchez Sebastian, V.
and Sayago Galvan, I.
and Senthilkumar, V.
and Soldevila, U.
and Sanchez, J.
and Torro Pastor, E.
and Valero, A.
and Valiente Moreno, E.
and Valls Ferrer, J. A.
and Varriale, L.
and Villaplana Perez, M.
and Vos, M.",
title="Fast b-tagging at the high-level trigger of the ATLAS experiment in LHC Run 3",
journal="Journal of Instrumentation",
year="2023",
publisher="IOP Publishing Ltd",
volume="18",
number="11",
pages="P11006 - 38pp",
optkeywords="Trigger algorithms; Trigger concepts and systems (hardware and software)",
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{\%}.",
optnote="WOS:001123791900004",
optnote="exported from refbase (https://references.ific.uv.es/refbase/show.php?record=5972), last updated on Fri, 15 Mar 2024 08:52:50 +0000",
issn="1748-0221",
doi="10.1088/1748-0221/18/11/P11006",
opturl="https://arxiv.org/abs/2306.09738",
opturl="https://doi.org/10.1088/1748-0221/18/11/P11006",
language="English"
}