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Author DUNE Collaboration (Abi, B. et al); Antonova, M.; Barenboim, G.; Cervera-Villanueva, A.; De Romeri, V.; Fernandez Menendez, P.; Garcia-Peris, M.A.; Izmaylov, A.; Martin-Albo, J.; Masud, M.; Mena, O.; Novella, P.; Sorel, M.; Ternes, C.A.; Tortola, M.; Valle, J.W.F. url  doi
openurl 
  Title Neutrino interaction classification with a convolutional neural network in the DUNE far detector Type Journal Article
  Year 2020 Publication Physical Review D Abbreviated Journal Phys. Rev. D  
  Volume 102 Issue (up) 9 Pages 092003 - 20pp  
  Keywords  
  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.  
  Address [Decowski, M. P.; De Jong, P.] Univ Amsterdam, NL-1098 XG Amsterdam, Netherlands, Email: saul.alonso.monsalve@cern.ch;  
  Corporate Author Thesis  
  Publisher Amer Physical Soc Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2470-0010 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000587596500004 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 4598  
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Author DUNE Collaboration (Abud, A.A. et al); Amedo, P.; Antonova, M.; Barenboim, G.; Cervera-Villanueva, A.; De Romeri, V.; Garcia-Peris, M.A.; Martin-Albo, J.; Martinez-Mirave, P.; Mena, O.; Molina Bueno, L.; Novella, P.; Pompa, F.; Rocabado Rocha, J.L.; Sorel, M.; Tortola, M.; Valle, J.W.F. url  doi
openurl 
  Title Identification and reconstruction of low-energy electrons in the ProtoDUNE-SP detector Type Journal Article
  Year 2023 Publication Physical Review D Abbreviated Journal Phys. Rev. D  
  Volume 107 Issue (up) 9 Pages 092012 - 22pp  
  Keywords  
  Abstract Measurements of electrons from ?e interactions are crucial for the Deep Underground Neutrino Experiment (DUNE) neutrino oscillation program, as well as searches for physics beyond the standard model, supernova neutrino detection, and solar neutrino measurements. This article describes the selection and reconstruction of low-energy (Michel) electrons in the ProtoDUNE-SP detector. ProtoDUNE-SP is one of the prototypes for the DUNE far detector, built and operated at CERN as a charged particle test beam experiment. A sample of low-energy electrons produced by the decay of cosmic muons is selected with a purity of 95%. This sample is used to calibrate the low-energy electron energy scale with two techniques. An electron energy calibration based on a cosmic ray muon sample uses calibration constants derived from measured and simulated cosmic ray muon events. Another calibration technique makes use of the theoretically well-understood Michel electron energy spectrum to convert reconstructed charge to electron energy. In addition, the effects of detector response to low-energy electron energy scale and its resolution including readout electronics threshold effects are quantified. Finally, the relation between the theoretical and reconstructed low-energy electron energy spectra is derived, and the energy resolution is characterized. The low-energy electron selection presented here accounts for about 75% of the total electron deposited energy. After the addition of lost energy using a Monte Carlo simulation, the energy resolution improves from about 40% to 25% at 50 MeV. These results are used to validate the expected capabilities of the DUNE far detector to reconstruct low-energy electrons.  
  Address [Isenhower, L.] Abilene Christian Univ, Abilene, TX 79601 USA, Email: zdjurcic@anl.gov;  
  Corporate Author Thesis  
  Publisher Amer Physical Soc Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2470-0010 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:001010953400003 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 5588  
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