Quantifying vacuum-like jets in heavy-ion collisions: a Machine Learning study

23 Jun 2026, 19:40
20m
Garland 064

Garland 064

Poster presentation Poster session

Speaker

João A. Gonçalves (LIP - IST)

Description

The modification of jets by interaction with the Quark Gluon Plasma has been extensively established through the comparison of observables computed for samples of jets produced in nucleus-nucleus collisions and proton-proton collisions. The presence of vacuum-like jets, jets that experienced little interaction with the Quark Gluon Plasma, in the nucleus-nucleus samples dilutes the overall observed modification hindering the detailed study of the underlying physical mechanisms. The ability to ascertain on a jet-by-jet basis the degree of modification of a jet would be an invaluable step in overcoming this limitation. We consider a Transformer classifier, trained on a low-level representation of jets given by the 4-momenta of all its constituents. We show that the Transformer is able to capture discriminating information not accessible to other architectures which use high-level physical observables as input. The Transformer allows us to identify, in the experimentally relevant case where both medium response and underlying event contamination are accounted for, a class of jets that have been unequivocally modified. Further, we perform a robust estimate of the upper bound for the fraction of jets in nucleus-nucleus collisions that are, for all purposes, indistinguishable from those produced in proton-proton collisions.

https://inspirehep.net/literature/2872254

Is this an experimental talk? No
Is this on behalf of a collaboration? No
Are you willing to present as a poster if it is not selected for oral presentation? Yes

Authors

Dr Guilherme Milhano (LIP-Lisbon & CERN TH) João A. Gonçalves (LIP - IST) Miguel Crispim Romao (University of Southampton)

Presentation materials