Scholars@Duke
Journal cover image

Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network

Publication ,  Journal Article
Abed Abud, A; Abi, B; Acciarri, R; Acero, MA; Adames, MR; Adamov, G; Adamowski, M; Adams, D; Adinolfi, M; Aduszkiewicz, A; Aguilar, J; Alt, C ...
Published in: European Physical Journal C
October 1, 2022
Published version (DOI)

Liquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the technology has been used in a number of recent neutrino experiments, and is the technology of choice for the Deep Underground Neutrino Experiment (DUNE). In order to perform high precision measurements of neutrinos in the detector, final state particles need to be effectively identified, and their energy accurately reconstructed. This article proposes an algorithm based on a convolutional neural network to perform the classification of energy deposits and reconstructed particles as track-like or arising from electromagnetic cascades. Results from testing the algorithm on experimental data from ProtoDUNE-SP, a prototype of the DUNE far detector, are presented. The network identifies track- and shower-like particles, as well as Michel electrons, with high efficiency. The performance of the algorithm is consistent between experimental data and simulation.

Duke Scholars

Kate Scholberg
Author Kate Scholberg Physics
Altmetric Attention Stats
Dimensions Citation Stats

Published In

European Physical Journal C

DOI

10.1140/epjc/s10052-022-10791-2

EISSN

1434-6052

ISSN

1434-6044

Publication Date

October 1, 2022

Volume

82

Issue

10

Related Subject Headings

  • Nuclear & Particles Physics
  • 5107 Particle and high energy physics
  • 5102 Atomic, molecular and optical physics
  • 5101 Astronomical sciences
  • 0206 Quantum Physics
  • 0202 Atomic, Molecular, Nuclear, Particle and Plasma Physics
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Abed Abud, A., Abi, B., Acciarri, R., Acero, M. A., Adames, M. R., Adamov, G., … Bezawada, Y. (2022). Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network. European Physical Journal C, 82(10). https://doi.org/10.1140/epjc/s10052-022-10791-2
Abed Abud, A., B. Abi, R. Acciarri, M. A. Acero, M. R. Adames, G. Adamov, M. Adamowski, et al. “Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network.” European Physical Journal C 82, no. 10 (October 1, 2022). https://doi.org/10.1140/epjc/s10052-022-10791-2.
Abed Abud A, Abi B, Acciarri R, Acero MA, Adames MR, Adamov G, et al. Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network. European Physical Journal C. 2022 Oct 1;82(10).
Abed Abud, A., et al. “Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network.” European Physical Journal C, vol. 82, no. 10, Oct. 2022. Scopus, doi:10.1140/epjc/s10052-022-10791-2.
Abed Abud A, Abi B, Acciarri R, Acero MA, Adames MR, Adamov G, Adamowski M, Adams D, Adinolfi M, Aduszkiewicz A, Aguilar J, Ahmad Z, Ahmed J, Aimard B, Ali-Mohammadzadeh B, Alion T, Allison K, Alonso Monsalve S, AlRashed M, Alt C, Alton A, Alvarez R, Amedo P, Anderson J, Andreopoulos C, Andreotti M, Andrews M, Andrianala F, Andringa S, Anfimov N, Ankowski A, Antoniassi M, Antonova M, Antoshkin A, Antusch S, Aranda-Fernandez A, Arellano L, Arnold LO, Arroyave MA, Asaadi J, Asquith L, Aurisano A, Aushev V, Autiero D, Ayala Lara V, Ayala-Torres M, Azfar F, Babicz M, Back A, Back H, Back JJ, Backhouse C, Bagaturia I, Bagby L, Balashov N, Balasubramanian S, Baldi P, Baller B, Bambah B, Barao F, Barenboim G, Barker G, Barkhouse W, Barnes C, Barr G, Barranco Monarca J, Barros A, Barros N, Barrow JL, Basharina-Freshville A, Bashyal A, Basque V, Batchelor C, Batista das Chagas E, Battat J, Battisti F, Bay F, Bazetto MCQ, Bazo Alba J, Beacom JF, Bechetoille E, Behera B, Beigbeder C, Bellantoni L, Bellettini G, Bellini V, Beltramello O, Benekos N, Benitez Montiel C, Bento Neves F, Berger J, Berkman S, Bernardini P, Berner RM, Bersani A, Bertolucci S, Betancourt M, Betancur Rodríguez A, Bevan A, Bezawada Y. Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network. European Physical Journal C. 2022 Oct 1;82(10).
Journal cover image

Published In

European Physical Journal C

DOI

10.1140/epjc/s10052-022-10791-2

EISSN

1434-6052

ISSN

1434-6044

Publication Date

October 1, 2022

Volume

82

Issue

10

Related Subject Headings

  • Nuclear & Particles Physics
  • 5107 Particle and high energy physics
  • 5102 Atomic, molecular and optical physics
  • 5101 Astronomical sciences
  • 0206 Quantum Physics
  • 0202 Atomic, Molecular, Nuclear, Particle and Plasma Physics