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HK: Fachverband Physik der Hadronen und Kerne

HK 21: Heavy-Ion Collisions and QCD Phases III

HK 21.3: Talk

Tuesday, March 12, 2024, 16:15–16:30, HBR 62: EG 03

J/ψ measurements with machine learning and Kalman filter techniques with ALICE at the LHC — •Pengzhong Lu — GSI Helmholtzzentrum für Schwerionenforschung, Darmstadt, Germany — University of Science and Technology of China, Hefei, China

Quarkonium production offers an effective way to study the properties of the quark-gluon plasma (QGP) created in ultra-relativistic heavy-ion collisions. While the prompt J/ψ production provides information on suppression and (re-)generation mechanisms in the QGP, the non-prompt J/ψ component (from b-hadron decays) allows one to study heavy quark energy loss in the medium. J/ψ meson production measurements in pp collisions, besides providing a reference for the corresponding measurements in p–Pb and Pb–Pb collisions, are also crucial to better understand quantum chromodynamics.

In this talk, the performance of the combined usage of KFParticle and machine learning (ML) for the measurement of prompt and non-prompt J/ψ production will be presented. The KFParticle package, based on the Kalman Filter algorithm, shows good performances in the reconstruction of particle decays. Combining it with ML techniques will significantly improve the signal reconstruction efficiencies and signal-to-background ratios. Results from this study in ALICE Run 3 pp collisions at √s = 13.6 TeV, based on the data collected in 2022, will be shown.

Keywords: quarkonium; associated production