Karlsruhe 2024 – wissenschaftliches Programm

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T: Fachverband Teilchenphysik

T 113: Silicon trackers 6

T 113.1: Vortrag

Freitag, 8. März 2024, 09:00–09:15, Geb. 30.22: kl. HS B

Slow pion identification at the Belle II PXD with machine learning — •Johannes Bilk and Sören Lange — II. Physikalisches Institut (Subatomare Physik), Justus-Liebig- Universität Giessen

The identification of slow pions in Belle II experiments presents a notable challenge, arising from their high dE/dx energy loss and their short flight path in the tracking detectors. This study introduces a method employing advanced machine learning algorithms to accurately detect pions with momentum p<100 MeV/c exclusively with the Belle II pixeldetector (PXD). By analyzing detector signals (in particular a 9x9 pixel matrix) with image processing and pattern recognition methods, this approach significantly boosts the efficiency and accuracy. Offline and online (FPGA) implemenation will be discussed.

Keywords: machine learning; slow pions; belle 2