000003465 001__ 3465
000003465 005__ 20230315131105.0
000003465 037__ $$aBELLE2-TALK-CONF-2023-023
000003465 041__ $$aeng
000003465 100__ $$aXavier Simó
000003465 245__ $$aParticle identification at Belle II using Neural Networks
000003465 260__ $$aDPG Fühjahrstagung $$c2023-03-15
000003465 300__ $$amult. p
000003465 520__ $$aWe will present improvements to the charged-particle identification algorithms used by the Belle II experiment located at KEK, Japan. So far, different approaches have been used to tackle the challenge of combining the information from each subdetector into a single variable for particle identification in an optimal way. We will present evaluations of the performance of a Neural Network based approach that combines information such as the likelihood values from each subdetector and the measured momentum of the particle track. funded by the DFG under Germany’s Excellence Strategy - EXC2094- 390783311 and BMBF Verbundforschung (05H21WOKBA BELLE2)
000003465 700__ $$aDaniel Greenwald
000003465 700__ $$aStefan Wallner
000003465 700__ $$aStephan Paul
000003465 8560_ $$fxavi.simo@tum.de
000003465 8564_ $$uhttps://docs.belle2.org/record/3465/files/BELLE2-TALK-CONF-2023-023.pdf