BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//CERN//INDICO//EN
BEGIN:VEVENT
SUMMARY:Pion and muon identification in charged-current muon-neutrino inte
 raction in the upgraded near detector of the T2K Experiment
DTSTART;VALUE=DATE-TIME:20261028T060000Z
DTEND;VALUE=DATE-TIME:20261028T061500Z
DTSTAMP;VALUE=DATE-TIME:20261023T153055Z
UID:indico-contribution-6228@cern.ch
DESCRIPTION:Speakers: Alexandr Shvartsman (INR RAS)\nThe upgraded near neu
 trino detector of the T2K experiment is briefly described. The central par
 t is the 3D scintillator fine-grained detector (SuperFGD). The detector co
 mprised of about 2 million 1 × 1 × 1 cm3 plastic scintillator cubes with
  three orthogonal holes for wavelength shifting fiber readout. It is used 
 as an active neutrino target to detect charged particles and photons. A co
 mbination of SuperFGD with the other subdetector systems in the ND280 dete
 ctor provides a possibility to detect more neutrino events (due to an addi
 tional active target)\, as well as to increase the accuracy of the neutrin
 o events reconstruction.\n \nIn charged-current muon-neutrino analysis\, t
 he outgoing muon is selected to reconstruct the neutrino energy. In SuperF
 GD\, however\, pions can be misidentified as muons\, complicating this sel
 ection. This work uses a Graph Neural Network (GNN) to identify muons and 
 pions. We present the efficiency and purity of the GNN-based classificatio
 n of these particles and discuss its impact on event selections. The resul
 ts are based on Monte Carlo simulations of neutrino interactions in the up
 graded ND280 detector.\n \n \n1. K. Abe et al. (T2K Collaboration)\, The T
 2K experiment\, Nucl. Instrum. Meth. A 659 (2011) 106-135\, DOI: 10.1016/j
 .nima.2011.06.067  \n  \n2. Yu. Kudenko et al. (T2K Collaboration)\, The n
 ear neutrino detector of the T2K experiment\, Nucl. Instrum. Meth. A 598 (
 2009) 289-295\, DOI: 10.1016/j.nima.2008.08.029  \n  \n3. Abe S. et al.\, 
 The super fine-grained detector for the T2K neutrino oscillation experimen
 t. Nucl.Instrum.Meth.A 1092 (2026) 171882\n  \n4. Abe K. [et al.]. T2K ND2
 80 Upgrade – Technical Design Report\, JINST 6. 2011. P12004 [arXiv:1901
 .03750 ] Jan. 11 2019\, 196 p.\n \n5. Shlomi\, J.\, Battaglia\, P.\, & Vli
 mant\, J.-R. "Graph neural networks in particle physics." Machine Learning
 : Science and Technology 2.2 (2021): 021001.\n\nhttps://indico.particle.me
 phi.ru/event/626/contributions/6228/
LOCATION:Sevastopol Hotel
URL:https://indico.particle.mephi.ru/event/626/contributions/6228/
END:VEVENT
END:VCALENDAR