SMuK 2023 – wissenschaftliches Programm
Bereiche | Tage | Auswahl | Suche | Aktualisierungen | Downloads | Hilfe
HK: Fachverband Physik der Hadronen und Kerne
HK 53: AI Topical Day – Computing II (joint session HK/AKPIK)
HK 53.4: Vortrag
Donnerstag, 23. März 2023, 14:45–15:00, HSZ/0103
Machine Learning Algorithms for Pattern Recognition with the PANDA Barrel DIRC — •Yannic Wolf1,2, Roman Dzhygadlo1, Klaus Peters1,2, Georg Schepers1, Carsten Schwarz1, and Jochen Schwiening1 — 1GSI Helmholtzzentrum für Schwerionenforschung GmbH, Darmstadt — 2Goethe-Universität Frankfurt
Precise and fast hadronic particle identification (PID) is crucial to reach the physics goals of the PANDA detector at FAIR. The Barrel DIRC (Detection of Internally Reflected Cherenkov light) is a key detector for the identification of charged hadrons in PANDA. Several reconstruction algorithms have been developed to extract the PID information from the measured location and arrival time of the Cherenkov photons. In comparison to other Ring Imaging Cherenkov detectors, the hit patterns observed with DIRC counters do not appear as rings on the photosensor plane but as complex, disjoint 3D-patterns.
Using the recent advances in machine learning (ML) algorithms, especially in the area of image recognition, we plan to develop new ML PID algorithms for the PANDA Barrel DIRC and compare the results to conventional reconstruction methods. In search for the best performance, different network architectures are currently under investigation.