Flavour tagging with graph neural networks with the ATLAS detector

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 $\sqrt{s}=13.6$ TeV is shown and expected performance at the High-Luminosity LHC (HL-LHC) discussed.

6 pages, 2 figures, 1 table, Presented at DIS2023: XXX International Workshop on Deep-Inelastic Scattering and Related Subjects, Michigan State University, USA, 27-31 March 2023

Cited by in corpus (1)

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