Flavour tagging with graph neural networks with the ATLAS detector

2023/06/07 by A. Duperrin, Duperrin, Arnaud · 3 citations
Physics and Astronomy · #FOS: Physical sciences #High Energy Physics - Experiment (hep-ex) #High-Energy Particle Collisions Research #Particle Detector Development and Performance #Particle physics theoretical and experimental studies

paper · pdf · doi:10.48550/arxiv.2306.04415

openalex publication_date 2023/06/07 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

The identification of jets containing a b-hadron, referred to as b-tagging, plays an important role for various physics measurements and searches carried out by the ATLAS experiment at the CERN Large Hadron Collider (LHC). The most recent b-tagging algorithm developments based on graph neural network architectures are presented. Preliminary performance on Run 3 data in pp collisions at √ s = 13.6 TeV is shown and expected performance at the High-Luminosity LHC (HL-LHC) discussed.

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