Transforming jet flavour tagging at ATLAS
Centre National de la Recherche Scientifique · Aix-Marseille Université · +257 more institutions
Abstract
Jet flavour tagging enables the identification of jets originating from heavy-flavour quarks in proton-proton collisions at the Large Hadron Collider, playing a critical role in its physics programmes. This paper presents GN2, a transformer-based flavour tagging algorithm deployed by the ATLAS Collaboration that represents a different methodology compared to previous approaches. Designed to classify jets based on the flavour of their constituent particles, GN2 processes low-level tracking information in an end-to-end architecture and incorporates physics-informed auxiliary training objectives to enhance both interpretability and performance. Its performance is validated in both simulation and collision data.…
Citation impact
- FWCI
- 85.75
- Percentile
- 100%
- References
- 80
Authors
2938- GAG. AadCorresponding
Centre National de la Recherche Scientifique, Aix-Marseille Université
- EAE. Aakvaag
University of Bergen
- BAB. Abbott
University of Oklahoma
- SASara Abdelhameed
New York University Abu Dhabi
- KAKarin Abeling
University of Göttingen
Topics & keywords
- Atlas (anatomy)
- Flavour
- Higgs boson
- Large Hadron Collider
- Interpretability
- Quark
- Jet (fluid)
- Collision
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