TY  - JOUR
AU  - Charan, Abtin Narimani
TI  - Particle identification with the Belle II calorimeter using machine learning
JO  - Journal of physics / Conference Series
VL  - 2438
IS  - 1
SN  - 1742-6588
CY  - Bristol
PB  - IOP Publ.
M1  - PUBDB-2025-02482
M1  - arXiv:2301.11654
SP  - 012111 -
PY  - 2023
N1  - 5 pages, 6 figures, Proceedings for poster contribution to 20th International Workshop on Advanced Computing and Analysis Techniques in Physics Research, 29 November - 3 December 2021, It will be published in: IOP Conference Series
AB  - I present an application of a convolutional neural network (CNN) to separate muons and pions in the Belle II electromagnetic calorimeter (ECL). The ECL is designed to measure the energy deposited by charged and neutral particles. It also provides important contributions to the particle identification (PID) system. Identification of low-momenta muons and pions in the ECL is crucial if they do not reach the outer muon detector. Track-seeded cluster energy images provide the maximal possible information. The shape of the energy depositions for muons and pions in the crystals around an extrapolated track at the entering point of the ECL is used together with crystal positions in θ − ϕ plane and transverse momentum of the track to train a CNN. The CNN exploits the difference between the dispersed energy depositions from pion hadronic interactions and the more localized muon electromagnetic interactions. Using simulation, the performance of the CNN algorithm is compared with other PID methods at Belle II which are based on track-matched clustering information. The results show that the CNN PID method improves muon-pion separation in low momentum.
T2  - 20th International Workshop on Advanced Computing and Analysis Techniques in Physics Research
CY  - 29 Nov 2021 - 3 Dec 2021, Daejeon (South Korea)
Y2  - 29 Nov 2021 - 3 Dec 2021
M2  - Daejeon, South Korea
KW  - electron positron: annihilation (INSPIRE)
KW  - electron positron: colliding beams (INSPIRE)
KW  - momentum: low (INSPIRE)
KW  - muon: detector (INSPIRE)
KW  - tracks: transverse momentum (INSPIRE)
KW  - calorimeter: electromagnetic (INSPIRE)
KW  - muon: particle identification (INSPIRE)
KW  - pi: particle identification (INSPIRE)
KW  - BELLE (INSPIRE)
KW  - crystal (INSPIRE)
KW  - electromagnetic interaction (INSPIRE)
KW  - cluster (INSPIRE)
KW  - machine learning (INSPIRE)
KW  - neutral particle (INSPIRE)
KW  - particle identification: performance (INSPIRE)
KW  - neural network (INSPIRE)
KW  - statistical analysis (INSPIRE)
KW  - data analysis method (INSPIRE)
KW  - numerical calculations: Monte Carlo (INSPIRE)
KW  - experimental results (INSPIRE)
LB  - PUB:(DE-HGF)8 ; PUB:(DE-HGF)16
DO  - DOI:10.1088/1742-6596/2438/1/012111
UR  - https://bib-pubdb1.desy.de/record/634234
ER  -