SMuK 2023 – wissenschaftliches Programm
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HK: Fachverband Physik der Hadronen und Kerne
HK 28: Heavy-Ion Collisions and QCD Phases VI
HK 28.5: Vortrag
Mittwoch, 22. März 2023, 15:15–15:30, SCH/A315
Prompt and non-prompt J/ψ with machine learning and Kalman filter techniques with ALICE in Run 3 — •Pengzhong Lu for the ALICE Germany collaboration — GSI Helmholtzzentrum für Schwerionenforschung GmbH, 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 the commissioning of this new methodology in Pb-Pb collisions at √sNN = 5.02 TeV from Run 2 will be shown, followed by the study of the first Run 3 data from pp collisions at √s = 13.6 TeV.