ATLAS Jet Flavor Tagging with AI: The GN2 Algorithm
Artikel konnten nicht hinzugefügt werden
Der Titel konnte nicht zum Warenkorb hinzugefügt werden.
Der Titel konnte nicht zum Merkzettel hinzugefügt werden.
„Von Wunschzettel entfernen“ fehlgeschlagen.
„Podcast folgen“ fehlgeschlagen
„Podcast nicht mehr folgen“ fehlgeschlagen
ATLAS Jet Flavor Tagging with AI: The GN2 Algorithm
-
Gesprochen von:
-
Von:
Über diesen Titel
he ATLAS Experiment at CERN has embraced modern AI techniques to revolutionise jet flavour tagging, a crucial process in analysing particle collisions. A new algorithm called GN2, powered by a Transformer neural network, directly analyses information from particle tracks and jets, eliminating the need for previous, hand-crafted algorithms. This advancement significantly improves the identification of b-jets and c-jets, which are vital for Standard Model measurements and the search for new physics phenomena. The ATLAS Collaboration has established robust pipelines to integrate and train these AI algorithms, leading to a substantial leap in performance and offering deeper insights into the physics signatures learned by the model. This innovative approach is already having a significant impact on ATLAS physics research, including enhancing the precision of Higgs boson studies and the search for new particles.
Paper link: https://arxiv.org/pdf/2505.19689
