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Neutrino interaction classification with a convolutional neural network in the DUNE far detector

  • Author(s): Abi, B
  • Acciarri, R
  • Acero, MA
  • Adamov, G
  • Adams, D
  • Adinolfi, M
  • Ahmad, Z
  • Ahmed, J
  • Alion, T
  • Alonso Monsalve, S
  • Alt, C
  • Anderson, J
  • Andreopoulos, C
  • Andrews, MP
  • Andrianala, F
  • Andringa, S
  • Ankowski, A
  • Antonova, M
  • Antusch, S
  • Aranda-Fernandez, A
  • Ariga, A
  • Arnold, LO
  • Arroyave, MA
  • Asaadi, J
  • Aurisano, A
  • Aushev, V
  • Autiero, D
  • Azfar, F
  • Back, H
  • Back, JJ
  • Backhouse, C
  • Baesso, P
  • Bagby, L
  • Bajou, R
  • Balasubramanian, S
  • Baldi, P
  • Bambah, B
  • Barao, F
  • Barenboim, G
  • Barker, GJ
  • Barkhouse, W
  • Barnes, C
  • Barr, G
  • Barranco Monarca, J
  • Barros, N
  • Barrow, JL
  • Bashyal, A
  • Basque, V
  • Bay, F
  • Bazo Alba, JL
  • Beacom, JF
  • Bechetoille, E
  • Behera, B
  • Bellantoni, L
  • Bellettini, G
  • Bellini, V
  • Beltramello, O
  • Belver, D
  • Benekos, N
  • Bento Neves, F
  • Berger, J
  • Berkman, S
  • Bernardini, P
  • Berner, RM
  • Berns, H
  • Bertolucci, S
  • Betancourt, M
  • Bezawada, Y
  • Bhattacharjee, M
  • Bhuyan, B
  • Biagi, S
  • Bian, J
  • Biassoni, M
  • Biery, K
  • Bilki, B
  • Bishai, M
  • Bitadze, A
  • Blake, A
  • Blanco Siffert, B
  • Blaszczyk, FDM
  • Blazey, GC
  • Blucher, E
  • Boissevain, J
  • Bolognesi, S
  • Bolton, T
  • Bonesini, M
  • Bongrand, M
  • Bonini, F
  • Booth, A
  • Booth, C
  • Bordoni, S
  • Borkum, A
  • Boschi, T
  • Bostan, N
  • Bour, P
  • Boyd, SB
  • Boyden, D
  • Bracinik, J
  • Braga, D
  • Brailsford, D
  • et al.
Abstract

The Deep Underground Neutrino Experiment is a next-generation neutrino oscillation experiment that aims to measure CP-violation in the neutrino sector as part of a wider physics program. A deep learning approach based on a convolutional neural network has been developed to provide highly efficient and pure selections of electron neutrino and muon neutrino charged-current interactions. The electron neutrino (antineutrino) selection efficiency peaks at 90% (94%) and exceeds 85% (90%) for reconstructed neutrino energies between 2-5 GeV. The muon neutrino (antineutrino) event selection is found to have a maximum efficiency of 96% (97%) and exceeds 90% (95%) efficiency for reconstructed neutrino energies above 2 GeV. When considering all electron neutrino and antineutrino interactions as signal, a selection purity of 90% is achieved. These event selections are critical to maximize the sensitivity of the experiment to CP-violating effects.

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