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Author DUNE Collaboration (Abud, A.A. et al); Antonova, M.; Barenboim, G.; Cervera-Villanueva, A.; De Romeri, V.; Fernandez Menendez, P.; Garcia-Peris, M.A.; Martin-Albo, J.; Martinez-Mirave, P.; Mena, O.; Molina Bueno, L.; Novella, P.; Pompa, F.; Sorel, M.; Ternes, C.A.; Tortola, M.; Valle, J.W.F. url  doi
openurl 
  Title Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network Type Journal Article
  Year 2022 Publication European Physical Journal C Abbreviated Journal Eur. Phys. J. C  
  Volume 82 Issue 10 Pages 903 - 19pp  
  Keywords  
  Abstract 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.  
  Address [Isenhower, L.] Abilenexs Christian Univ, Abilene, TX 79601 USA, Email: tjyang@fnal.gov  
  Corporate Author Thesis  
  Publisher Springer Place of Publication (up) Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1434-6044 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000866503200001 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 5386  
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